Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors.

PubMed

Razavian, Narges; Blecker, Saul; Schmidt, Ann Marie; Smith-McLallen, Aaron; Nigam, Somesh; Sontag, David

2015-12-01

We present a new approach to population health, in which data-driven predictive models are learned for outcomes such as type 2 diabetes. Our approach enables risk assessment from readily available electronic claims data on large populations, without additional screening cost. Proposed model uncovers early and late-stage risk factors. Using administrative claims, pharmacy records, healthcare utilization, and laboratory results of 4.1 million individuals between 2005 and 2009, an initial set of 42,000 variables were derived that together describe the full health status and history of every individual. Machine learning was then used to methodically enhance predictive variable set and fit models predicting onset of type 2 diabetes in 2009-2011, 2010-2012, and 2011-2013. We compared the enhanced model with a parsimonious model consisting of known diabetes risk factors in a real-world environment, where missing values are common and prevalent. Furthermore, we analyzed novel and known risk factors emerging from the model at different age groups at different stages before the onset. Parsimonious model using 21 classic diabetes risk factors resulted in area under ROC curve (AUC) of 0.75 for diabetes prediction within a 2-year window following the baseline. The enhanced model increased the AUC to 0.80, with about 900 variables selected as predictive (p < 0.0001 for differences between AUCs). Similar improvements were observed for models predicting diabetes onset 1-3 years and 2-4 years after baseline. The enhanced model improved positive predictive value by at least 50% and identified novel surrogate risk factors for type 2 diabetes, such as chronic liver disease (odds ratio [OR] 3.71), high alanine aminotransferase (OR 2.26), esophageal reflux (OR 1.85), and history of acute bronchitis (OR 1.45). Liver risk factors emerge later in the process of diabetes development compared with obesity-related factors such as hypertension and high hemoglobin A1c. In conclusion, population-level risk prediction for type 2 diabetes using readily available administrative data is feasible and has better prediction performance than classical diabetes risk prediction algorithms on very large populations with missing data. The new model enables intervention allocation at national scale quickly and accurately and recovers potentially novel risk factors at different stages before the disease onset.

12 CFR Appendix B to Part 3 - Risk-Based Capital Guidelines; Market Risk Adjustment

Code of Federal Regulations, 2011 CFR

2011-01-01

... management systems at least annually. (c) Market risk factors. The bank's internal model must use risk factors sufficient to measure the market risk inherent in all covered positions. The risk factors must... risk weighting factor indicated in Table 2 of this appendix. The specific risk capital charge component...

Disease risk curves.

PubMed

Hughes, G; Burnett, F J; Havis, N D

2013-11-01

Disease risk curves are simple graphical relationships between the probability of need for treatment and evidence related to risk factors. In the context of the present article, our focus is on factors related to the occurrence of disease in crops. Risk is the probability of adverse consequences; specifically in the present context it denotes the chance that disease will reach a threshold level at which crop protection measures can be justified. This article describes disease risk curves that arise when risk is modeled as a function of more than one risk factor, and when risk is modeled as a function of a single factor (specifically the level of disease at an early disease assessment). In both cases, disease risk curves serve as calibration curves that allow the accumulated evidence related to risk to be expressed on a probability scale. When risk is modeled as a function of the level of disease at an early disease assessment, the resulting disease risk curve provides a crop loss assessment model in which the downside is denominated in terms of risk rather than in terms of yield loss.

Recent development of risk-prediction models for incident hypertension: An updated systematic review

PubMed Central

Xiao, Lei; Liu, Ya; Wang, Zuoguang; Li, Chuang; Jin, Yongxin; Zhao, Qiong

2017-01-01

Background Hypertension is a leading global health threat and a major cardiovascular disease. Since clinical interventions are effective in delaying the disease progression from prehypertension to hypertension, diagnostic prediction models to identify patient populations at high risk for hypertension are imperative. Methods Both PubMed and Embase databases were searched for eligible reports of either prediction models or risk scores of hypertension. The study data were collected, including risk factors, statistic methods, characteristics of study design and participants, performance measurement, etc. Results From the searched literature, 26 studies reporting 48 prediction models were selected. Among them, 20 reports studied the established models using traditional risk factors, such as body mass index (BMI), age, smoking, blood pressure (BP) level, parental history of hypertension, and biochemical factors, whereas 6 reports used genetic risk score (GRS) as the prediction factor. AUC ranged from 0.64 to 0.97, and C-statistic ranged from 60% to 90%. Conclusions The traditional models are still the predominant risk prediction models for hypertension, but recently, more models have begun to incorporate genetic factors as part of their model predictors. However, these genetic predictors need to be well selected. The current reported models have acceptable to good discrimination and calibration ability, but whether the models can be applied in clinical practice still needs more validation and adjustment. PMID:29084293

A new method to quantify the health risks from sources of perfluoroalkyl substances, combined with positive matrix factorization and risk assessment models.

PubMed

Xu, Jiao; Shi, Guo-Liang; Guo, Chang-Sheng; Wang, Hai-Ting; Tian, Ying-Ze; Huangfu, Yan-Qi; Zhang, Yuan; Feng, Yin-Chang; Xu, Jian

2018-01-01

A hybrid model based on the positive matrix factorization (PMF) model and the health risk assessment model for assessing risks associated with sources of perfluoroalkyl substances (PFASs) in water was established and applied at Dianchi Lake to test its applicability. The new method contains 2 stages: 1) the sources of PFASs were apportioned by the PMF model and 2) the contribution of health risks from each source was calculated by the new hybrid model. Two factors were extracted by PMF, with factor 1 identified as aqueous fire-fighting foams source and factor 2 as fluoropolymer manufacturing and processing and perfluorooctanoic acid production source. The health risk of PFASs in the water assessed by the health risk assessment model was 9.54 × 10 -7  a -1 on average, showing no obvious adverse effects to human health. The 2 sources' risks estimated by the new hybrid model ranged from 2.95 × 10 -10 to 6.60 × 10 -6  a -1 and from 1.64 × 10 -7 to 1.62 × 10 -6  a -1 , respectively. The new hybrid model can provide useful information on the health risks of PFAS sources, which is helpful for pollution control and environmental management. Environ Toxicol Chem 2018;37:107-115. © 2017 SETAC. © 2017 SETAC.

Data Sources for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Cancer.gov

The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).

Quantifying links between stroke and risk factors: a study on individual health risk appraisal of stroke in a community of Chongqing.

PubMed

Wu, Yazhou; Zhang, Ling; Yuan, Xiaoyan; Wu, Yamin; Yi, Dong

2011-04-01

The objective of this study is to investigate the risk factors of stroke in a community in Chongqing by setting quantitative criteria for determining the risk factors of stroke. Thus, high-risk individuals can be identified and laid a foundation for predicting individual risk of stroke. 1,034 cases with 1:2 matched controls (2,068) were chosen from five communities in Chongqing including Shapingba, Xiaolongkan, Tianxingqiao, Yubei Road and Ciqikou. Participants were interviewed with a uniform questionnaire. The risk factors of stroke and the odds ratios of risk factors were analyzed with a logistic regression model, and risk exposure factors of different levels were converted into risk scores using statistical models. For men, ten risk factors including hypertension (5.728), family history of stroke (4.599), and coronary heart disease (5.404), among others, were entered into the main effect model. For women, 11 risk factors included hypertension (5.270), family history of stroke (4.866), hyperlipidemia (4.346), among others. The related risk scores were added to obtain a combined risk score to predict the individual's risk of stoke in the future. An individual health risk appraisal model of stroke, which was applicable to individuals of different gender, age, health behavior, disease and family history, was established. In conclusion, personal diseases including hypertension, diabetes mellitus, etc., were very important to the prevalence of stoke. The prevalence of stroke can be effectively reduced by changing unhealthy lifestyles and curing the positive individual disease. The study lays a foundation for health education to persuade people to change their unhealthy lifestyles or behaviors, and could be used in community health services.

Risk modelling study for carotid endarterectomy.

PubMed

Kuhan, G; Gardiner, E D; Abidia, A F; Chetter, I C; Renwick, P M; Johnson, B F; Wilkinson, A R; McCollum, P T

2001-12-01

The aims of this study were to identify factors that influence the risk of stroke or death following carotid endarterectomy (CEA) and to develop a model to aid in comparative audit of vascular surgeons and units. A series of 839 CEAs performed by four vascular surgeons between 1992 and 1999 was analysed. Multiple logistic regression analysis was used to model the effect of 15 possible risk factors on the 30-day risk of stroke or death. Outcome was compared for four surgeons and two units after adjustment for the significant risk factors. The overall 30-day stroke or death rate was 3.9 per cent (29 of 741). Heart disease, diabetes and stroke were significant risk factors. The 30-day predicted stroke or death rates increased with increasing risk scores. The observed 30-day stroke or death rate was 3.9 per cent for both vascular units and varied from 3.0 to 4.2 per cent for the four vascular surgeons. Differences in the outcomes between the surgeons and vascular units did not reach statistical significance after risk adjustment. Diabetes, heart disease and stroke are significant risk factors for stroke or death following CEA. The risk score model identified patients at higher risk and aided in comparative audit.

Conceptualizing a Dynamic Fall Risk Model Including Intrinsic Risks and Exposures.

PubMed

Klenk, Jochen; Becker, Clemens; Palumbo, Pierpaolo; Schwickert, Lars; Rapp, Kilan; Helbostad, Jorunn L; Todd, Chris; Lord, Stephen R; Kerse, Ngaire

2017-11-01

Falls are a major cause of injury and disability in older people, leading to serious health and social consequences including fractures, poor quality of life, loss of independence, and institutionalization. To design and provide adequate prevention measures, accurate understanding and identification of person's individual fall risk is important. However, to date, the performance of fall risk models is weak compared with models estimating, for example, cardiovascular risk. This deficiency may result from 2 factors. First, current models consider risk factors to be stable for each person and not change over time, an assumption that does not reflect real-life experience. Second, current models do not consider the interplay of individual exposure including type of activity (eg, walking, undertaking transfers) and environmental risks (eg, lighting, floor conditions) in which activity is performed. Therefore, we posit a dynamic fall risk model consisting of intrinsic risk factors that vary over time and exposure (activity in context). eHealth sensor technology (eg, smartphones) begins to enable the continuous measurement of both the above factors. We illustrate our model with examples of real-world falls from the FARSEEING database. This dynamic framework for fall risk adds important aspects that may improve understanding of fall mechanisms, fall risk models, and the development of fall prevention interventions. Copyright © 2017 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

A Predictive Risk Model for A(H7N9) Human Infections Based on Spatial-Temporal Autocorrelation and Risk Factors: China, 2013–2014

PubMed Central

Dong, Wen; Yang, Kun; Xu, Quan-Li; Yang, Yu-Lian

2015-01-01

This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression analyses were utilized to investigate the risk factors associated with their distribution, and nine risk factors were significantly associated with the occurrence of A(H7N9) human infections: the spatial-temporal factor φ (OR = 2546669.382, p < 0.001), migration route (OR = 0.993, p < 0.01), river (OR = 0.861, p < 0.001), lake(OR = 0.992, p < 0.001), road (OR = 0.906, p < 0.001), railway (OR = 0.980, p < 0.001), temperature (OR = 1.170, p < 0.01), precipitation (OR = 0.615, p < 0.001) and relative humidity (OR = 1.337, p < 0.001). The improved model obtained a better prediction performance and a higher fitting accuracy than the traditional model: in the improved model 90.1% (91/101) of the cases during February 2014 occurred in the high risk areas (the predictive risk > 0.70) of the predictive risk map, whereas 44.6% (45/101) of which overlaid on the high risk areas (the predictive risk > 0.70) for the traditional model, and the fitting accuracy of the improved model was 91.6% which was superior to the traditional model (86.1%). The predictive risk map generated based on the improved model revealed that the east and southeast of China were the high risk areas of A(H7N9) human infections in February 2014. These results provided baseline data for the control and prevention of future human infections. PMID:26633446

A Multi-Domain Model of Risk Factors for ODD Symptoms in a Community Sample of 4-Year-Olds

ERIC Educational Resources Information Center

Lavigne, John V.; Gouze, Karen R.; Hopkins, Joyce; Bryant, Fred B.; LeBailly, Susan A.

2012-01-01

Few studies have been designed to assess the pathways by which risk factors are associated with symptoms of psychopathology across multiple domains, including contextual factors, parental depression, parenting, and child characteristics. The present study examines a cross-sectional model of risk factors for symptoms of Oppositional Defiant…

Characterizing the Intersection of Co-Occurring Risk Factors for Illicit Drug Abuse and Dependence in a U.S. Nationally Representative Sample

PubMed Central

Kurti, Allison N.; Keith, Diana R.; Noble, Alyssa; Priest, Jeff S.; Sprague, Brian; Higgins, Stephen T.

2016-01-01

Few studies have attempted to characterize how co-occurring risk factors for substance use disorders intersect. A recent study examined this question regarding cigarette smoking and demonstrated that co-occurring risk factors generally act independently. The present study examines whether that same pattern of independent intersection of risk factors extends to illicit drug abuse/dependence using a U.S. nationally representative sample (National Survey on Drug Use and Health, 2011–2013). Logistic regression and classification and regression tree (CART) modeling were used to examine risk of past-year drug abuse/dependence associated with a well-established set of risk factors for substance use (age, gender, race/ethnicity, education, poverty, smoking status, alcohol abuse/dependence, mental illness). Each of these risk factors was associated with significant increases in the odds of drug abuse/dependence in univariate logistic regressions. Each remained significant in a multivariate model examining all eight risk factors simultaneously. CART modeling of these 8 risk factors identified subpopulation risk profiles wherein drug abuse/dependence prevalence varied from < 1% to > 80% corresponding to differing combinations of risk factors present. Alcohol abuse/dependence and cigarette smoking had the strongest associations with drug abuse/dependence risk. These results demonstrate that co-occurring risk factors for illicit drug/abuse dependence generally intersect in the same independent manner as risk factors for cigarette smoking, underscoring further fundamental commonalities across these different types of substance use disorders. These results also underscore the fundamental importance of differences in the presence of co-occurring risk factors when considering the often strikingly different prevalence rates of illicit drug abuse/dependence in U.S. population subgroups. PMID:27687534

Prediction and Informative Risk Factor Selection of Bone Diseases.

PubMed

Li, Hui; Li, Xiaoyi; Ramanathan, Murali; Zhang, Aidong

2015-01-01

With the booming of healthcare industry and the overwhelming amount of electronic health records (EHRs) shared by healthcare institutions and practitioners, we take advantage of EHR data to develop an effective disease risk management model that not only models the progression of the disease, but also predicts the risk of the disease for early disease control or prevention. Existing models for answering these questions usually fall into two categories: the expert knowledge based model or the handcrafted feature set based model. To fully utilize the whole EHR data, we will build a framework to construct an integrated representation of features from all available risk factors in the EHR data and use these integrated features to effectively predict osteoporosis and bone fractures. We will also develop a framework for informative risk factor selection of bone diseases. A pair of models for two contrast cohorts (e.g., diseased patients versus non-diseased patients) will be established to discriminate their characteristics and find the most informative risk factors. Several empirical results on a real bone disease data set show that the proposed framework can successfully predict bone diseases and select informative risk factors that are beneficial and useful to guide clinical decisions.

Adolescent Problem Behavior in Navi Mumbai: An Exploratory Study of Psychosocial Risk and Protection

ERIC Educational Resources Information Center

Solomon, R. J.

2007-01-01

Background: A conceptual framework about protective factors (models protection, controls protection, support protection) and risk factors (models risk, opportunity risk, vulnerability risk) was employed to articulate the content of five psychosocial contexts of adolescent life--individual, family, peers, school, and neighborhood--in a study of…

12 CFR Appendix E to Part 225 - Capital Adequacy Guidelines for Bank Holding Companies: Market Risk Measure

Code of Federal Regulations, 2011 CFR

2011-01-01

.... (2) Specific risk means changes in the market value of specific positions due to factors other than... factors. The organization's internal model must use risk factors sufficient to measure the market risk inherent in all covered positions. The risk factors must address interest rate risk, 12 equity price risk...

Using an autologistic regression model to identify spatial risk factors and spatial risk patterns of hand, foot and mouth disease (HFMD) in Mainland China

PubMed Central

2014-01-01

Background There have been large-scale outbreaks of hand, foot and mouth disease (HFMD) in Mainland China over the last decade. These events varied greatly across the country. It is necessary to identify the spatial risk factors and spatial distribution patterns of HFMD for public health control and prevention. Climate risk factors associated with HFMD occurrence have been recognized. However, few studies discussed the socio-economic determinants of HFMD risk at a space scale. Methods HFMD records in Mainland China in May 2008 were collected. Both climate and socio-economic factors were selected as potential risk exposures of HFMD. Odds ratio (OR) was used to identify the spatial risk factors. A spatial autologistic regression model was employed to get OR values of each exposures and model the spatial distribution patterns of HFMD risk. Results Results showed that both climate and socio-economic variables were spatial risk factors for HFMD transmission in Mainland China. The statistically significant risk factors are monthly average precipitation (OR = 1.4354), monthly average temperature (OR = 1.379), monthly average wind speed (OR = 1.186), the number of industrial enterprises above designated size (OR = 17.699), the population density (OR = 1.953), and the proportion of student population (OR = 1.286). The spatial autologistic regression model has a good goodness of fit (ROC = 0.817) and prediction accuracy (Correct ratio = 78.45%) of HFMD occurrence. The autologistic regression model also reduces the contribution of the residual term in the ordinary logistic regression model significantly, from 17.25 to 1.25 for the odds ratio. Based on the prediction results of the spatial model, we obtained a map of the probability of HFMD occurrence that shows the spatial distribution pattern and local epidemic risk over Mainland China. Conclusions The autologistic regression model was used to identify spatial risk factors and model spatial risk patterns of HFMD. HFMD occurrences were found to be spatially heterogeneous over the Mainland China, which is related to both the climate and socio-economic variables. The combination of socio-economic and climate exposures can explain the HFMD occurrences more comprehensively and objectively than those with only climate exposures. The modeled probability of HFMD occurrence at the county level reveals not only the spatial trends, but also the local details of epidemic risk, even in the regions where there were no HFMD case records. PMID:24731248

Personality Correlates of Midlife Cardiometabolic Risk: The Explanatory Role of Higher-Order Factors of the Five Factor Model

PubMed Central

Dermody, Sarah S.; Wright, Aidan G.C.; Cheong, JeeWon; Miller, Karissa G.; Muldoon, Matthew F.; Flory, Janine D.; Gianaros, Peter J.; Marsland, Anna L.; Manuck, Stephen B.

2015-01-01

Objective Varying associations are reported between Five Factor Model (FFM) personality traits and cardiovascular diseaabolic risk within a hierarchical model of personality that posits higherse risk. Here, we further examine dispositional correlates of cardiomet -order traits of Stability (shared variance of Agreeableness, Conscientiousness, inverse Neuroticism) and Plasticity (Extraversion, Openness), and test hypothesized mediation via biological and behavioral factors. Method In an observational study of 856 community volunteers aged 30–54 years (46% male, 86% Caucasian), latent variable FFM traits (using multiple-informant reports) and aggregated cardiometabolic risk (indicators: insulin resistance, dyslipidemia, blood pressure, adiposity) were estimated using confirmatory factor analysis (CFA). The cardiometabolic factor was regressed on each personality factor or higher-order trait. Cross-sectional indirect effects via systemic inflammation, cardiac autonomic control, and physical activity were tested. Results CFA models confirmed the Stability “meta-trait,” but not Plasticity. Lower Stability was associated with heightened cardiometabolic risk. This association was accounted for by inflammation, autonomic function, and physical activity. Among FFM traits, only Openness was associated with risk over and above Stability and, unlike Stablity, this relationship was unexplained by the intervening variables. Conclusions A Stability meta-trait covaries with midlife cardiometabolic risk, and this association is accounted for by three candidate biological and behavioral factors. PMID:26249259

A simple prognostic model for overall survival in metastatic renal cell carcinoma.

PubMed

Assi, Hazem I; Patenaude, Francois; Toumishey, Ethan; Ross, Laura; Abdelsalam, Mahmoud; Reiman, Tony

2016-01-01

The primary purpose of this study was to develop a simpler prognostic model to predict overall survival for patients treated for metastatic renal cell carcinoma (mRCC) by examining variables shown in the literature to be associated with survival. We conducted a retrospective analysis of patients treated for mRCC at two Canadian centres. All patients who started first-line treatment were included in the analysis. A multivariate Cox proportional hazards regression model was constructed using a stepwise procedure. Patients were assigned to risk groups depending on how many of the three risk factors from the final multivariate model they had. There were three risk factors in the final multivariate model: hemoglobin, prior nephrectomy, and time from diagnosis to treatment. Patients in the high-risk group (two or three risk factors) had a median survival of 5.9 months, while those in the intermediate-risk group (one risk factor) had a median survival of 16.2 months, and those in the low-risk group (no risk factors) had a median survival of 50.6 months. In multivariate analysis, shorter survival times were associated with hemoglobin below the lower limit of normal, absence of prior nephrectomy, and initiation of treatment within one year of diagnosis.

A simple prognostic model for overall survival in metastatic renal cell carcinoma

PubMed Central

Assi, Hazem I.; Patenaude, Francois; Toumishey, Ethan; Ross, Laura; Abdelsalam, Mahmoud; Reiman, Tony

2016-01-01

Introduction: The primary purpose of this study was to develop a simpler prognostic model to predict overall survival for patients treated for metastatic renal cell carcinoma (mRCC) by examining variables shown in the literature to be associated with survival. Methods: We conducted a retrospective analysis of patients treated for mRCC at two Canadian centres. All patients who started first-line treatment were included in the analysis. A multivariate Cox proportional hazards regression model was constructed using a stepwise procedure. Patients were assigned to risk groups depending on how many of the three risk factors from the final multivariate model they had. Results: There were three risk factors in the final multivariate model: hemoglobin, prior nephrectomy, and time from diagnosis to treatment. Patients in the high-risk group (two or three risk factors) had a median survival of 5.9 months, while those in the intermediate-risk group (one risk factor) had a median survival of 16.2 months, and those in the low-risk group (no risk factors) had a median survival of 50.6 months. Conclusions: In multivariate analysis, shorter survival times were associated with hemoglobin below the lower limit of normal, absence of prior nephrectomy, and initiation of treatment within one year of diagnosis. PMID:27217858

Enhancing the Value of Population-Based Risk Scores for Institutional-Level Use.

PubMed

Raza, Sajjad; Sabik, Joseph F; Rajeswaran, Jeevanantham; Idrees, Jay J; Trezzi, Matteo; Riaz, Haris; Javadikasgari, Hoda; Nowicki, Edward R; Svensson, Lars G; Blackstone, Eugene H

2016-07-01

We hypothesized that factors associated with an institution's residual risk unaccounted for by population-based models may be identifiable and used to enhance the value of population-based risk scores for quality improvement. From January 2000 to January 2010, 4,971 patients underwent aortic valve replacement (AVR), either isolated (n = 2,660) or with concomitant coronary artery bypass grafting (AVR+CABG; n = 2,311). Operative mortality and major morbidity and mortality predicted by The Society of Thoracic Surgeons (STS) risk models were compared with observed values. After adjusting for patients' STS score, additional and refined risk factors were sought to explain residual risk. Differences between STS model coefficients (risk-factor strength) and those specific to our institution were calculated. Observed operative mortality was less than predicted for AVR (1.6% [42 of 2,660] vs 2.8%, p < 0.0001) and AVR+CABG (2.6% [59 of 2,311] vs 4.9%, p < 0.0001). Observed major morbidity and mortality was also lower than predicted for isolated AVR (14.6% [389 of 2,660] vs 17.5%, p < 0.0001) and AVR+CABG (20.0% [462 of 2,311] vs 25.8%, p < 0.0001). Shorter height, higher bilirubin, and lower albumin were identified as additional institution-specific risk factors, and body surface area, creatinine, glomerular filtration rate, blood urea nitrogen, and heart failure across all levels of functional class were identified as refined risk-factor variables associated with residual risk. In many instances, risk-factor strength differed substantially from that of STS models. Scores derived from population-based models can be enhanced for institutional level use by adjusting for institution-specific additional and refined risk factors. Identifying these and measuring differences in institution-specific versus population-based risk-factor strength can identify areas to target for quality improvement initiatives. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Energy risk in the arbitrage pricing model: an empirical and theoretical study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bremer, M.A.

1986-01-01

This dissertation empirically explores the Arbitrage Pricing Theory in the context of energy risk for securities over the 1960s, 1970s, and early 1980s. Starting from a general multifactor pricing model, the paper develops a two factor model based on a market-like factor and an energy factor. This model is then tested on portfolios of securities grouped according to industrial classification using several econometric techniques designed to overcome some of the more serious estimation problems common to these models. The paper concludes that energy risk is priced in the 1970s and possibly even in the 1960s. Energy risk is found tomore » be priced in the sense that investors who hold assets subjected to energy risk are paid for this risk. The classic version of the Capital Asset Pricing Model which posits the market as the single priced factor is rejected in favor of the Arbitrage Pricing Theory or multi-beta versions of the Capital Asset Pricing Model. The study introduces some original econometric methodology to carry out empirical tests.« less

Risk factors for the treatment outcome of retreated pulmonary tuberculosis patients in China: an optimized prediction model.

PubMed

Wang, X-M; Yin, S-H; Du, J; Du, M-L; Wang, P-Y; Wu, J; Horbinski, C M; Wu, M-J; Zheng, H-Q; Xu, X-Q; Shu, W; Zhang, Y-J

2017-07-01

Retreatment of tuberculosis (TB) often fails in China, yet the risk factors associated with the failure remain unclear. To identify risk factors for the treatment failure of retreated pulmonary tuberculosis (PTB) patients, we analyzed the data of 395 retreated PTB patients who received retreatment between July 2009 and July 2011 in China. PTB patients were categorized into 'success' and 'failure' groups by their treatment outcome. Univariable and multivariable logistic regression were used to evaluate the association between treatment outcome and socio-demographic as well as clinical factors. We also created an optimized risk score model to evaluate the predictive values of these risk factors on treatment failure. Of 395 patients, 99 (25·1%) were diagnosed as retreatment failure. Our results showed that risk factors associated with treatment failure included drug resistance, low education level, low body mass index (6 months), standard treatment regimen, retreatment type, positive culture result after 2 months of treatment, and the place where the first medicine was taken. An Optimized Framingham risk model was then used to calculate the risk scores of these factors. Place where first medicine was taken (temporary living places) received a score of 6, which was highest among all the factors. The predicted probability of treatment failure increases as risk score increases. Ten out of 359 patients had a risk score >9, which corresponded to an estimated probability of treatment failure >70%. In conclusion, we have identified multiple clinical and socio-demographic factors that are associated with treatment failure of retreated PTB patients. We also created an optimized risk score model that was effective in predicting the retreatment failure. These results provide novel insights for the prognosis and improvement of treatment for retreated PTB patients.

Methodology for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Cancer.gov

This model-based approach uses data from both the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS) to produce estimates of the prevalence rates of cancer risk factors and screening behaviors at the state, health service area, and county levels.

A prognostic index for natural killer cell lymphoma after non-anthracycline-based treatment: a multicentre, retrospective analysis.

PubMed

Kim, Seok Jin; Yoon, Dok Hyun; Jaccard, Arnaud; Chng, Wee Joo; Lim, Soon Thye; Hong, Huangming; Park, Yong; Chang, Kian Meng; Maeda, Yoshinobu; Ishida, Fumihiro; Shin, Dong-Yeop; Kim, Jin Seok; Jeong, Seong Hyun; Yang, Deok-Hwan; Jo, Jae-Cheol; Lee, Gyeong-Won; Choi, Chul Won; Lee, Won-Sik; Chen, Tsai-Yun; Kim, Kiyeun; Jung, Sin-Ho; Murayama, Tohru; Oki, Yasuhiro; Advani, Ranjana; d'Amore, Francesco; Schmitz, Norbert; Suh, Cheolwon; Suzuki, Ritsuro; Kwong, Yok Lam; Lin, Tong-Yu; Kim, Won Seog

2016-03-01

The clinical outcome of extranodal natural killer T-cell lymphoma (ENKTL) has improved substantially as a result of new treatment strategies with non-anthracycline-based chemotherapies and upfront use of concurrent chemoradiotherapy or radiotherapy. A new prognostic model based on the outcomes obtained with these contemporary treatments was warranted. We did a retrospective study of patients with newly diagnosed ENKTL without any previous treatment history for the disease who were given non-anthracycline-based chemotherapies with or without upfront concurrent chemoradiotherapy or radiotherapy with curative intent. A prognostic model to predict overall survival and progression-free survival on the basis of pretreatment clinical and laboratory characteristics was developed by filling a multivariable model on the basis of the dataset with complete data for the selected risk factors for an unbiased prediction model. The final model was applied to the patients who had complete data for the selected risk factors. We did a validation analysis of the prognostic model in an independent cohort. We did multivariate analyses of 527 patients who were included from 38 hospitals in 11 countries in the training cohort. Analyses showed that age greater than 60 years, stage III or IV disease, distant lymph-node involvement, and non-nasal type disease were significantly associated with overall survival and progression-free survival. We used these data as the basis for the prognostic index of natural killer lymphoma (PINK), in which patients are stratified into low-risk (no risk factors), intermediate-risk (one risk factor), or high-risk (two or more risk factors) groups, which were associated with 3-year overall survival of 81% (95% CI 75-86), 62% (55-70), and 25% (20-34), respectively. In the 328 patients with data for Epstein-Barr virus DNA, a detectable viral DNA titre was an independent prognostic factor for overall survival. When these data were added to PINK as the basis for another prognostic index (PINK-E)-which had similar low-risk (zero or one risk factor), intermediate-risk (two risk factors), and high-risk (three or more risk factors) categories-significant associations with overall survival were noted (81% [95% CI 75-87%], 55% (44-66), and 28% (18-40%), respectively). These results were validated and confirmed in an independent cohort, although the PINK-E model was only significantly associated with the high-risk group compared with the low-risk group. PINK and PINK-E are new prognostic models that can be used to develop risk-adapted treatment approaches for patients with ENKTL being treated in the contemporary era of non-anthracycline-based therapy. Samsung Biomedical Research Institute. Copyright © 2016 Elsevier Ltd. All rights reserved.

Validating the Copenhagen Psychosocial Questionnaire (COPSOQ-II) Using Set-ESEM: Identifying Psychosocial Risk Factors in a Sample of School Principals

PubMed Central

Dicke, Theresa; Marsh, Herbert W.; Riley, Philip; Parker, Philip D.; Guo, Jiesi; Horwood, Marcus

2018-01-01

School principals world-wide report high levels of strain and attrition resulting in a shortage of qualified principals. It is thus crucial to identify psychosocial risk factors that reflect principals' occupational wellbeing. For this purpose, we used the Copenhagen Psychosocial Questionnaire (COPSOQ-II), a widely used self-report measure covering multiple psychosocial factors identified by leading occupational stress theories. We evaluated the COPSOQ-II regarding factor structure and longitudinal, discriminant, and convergent validity using latent structural equation modeling in a large sample of Australian school principals (N = 2,049). Results reveal that confirmatory factor analysis produced marginally acceptable model fit. A novel approach we call set exploratory structural equation modeling (set-ESEM), where cross-loadings were only allowed within a priori defined sets of factors, fit well, and was more parsimonious than a full ESEM. Further multitrait-multimethod models based on the set-ESEM confirm the importance of a principal's psychosocial risk factors; Stressors and depression were related to demands and ill-being, while confidence and autonomy were related to wellbeing. We also show that working in the private sector was beneficial for showing a low psychosocial risk, while other demographics have little effects. Finally, we identify five latent risk profiles (high risk to no risk) of school principals based on all psychosocial factors. Overall the research presented here closes the theory application gap of a strong multi-dimensional measure of psychosocial risk-factors. PMID:29760670

Validating the Copenhagen Psychosocial Questionnaire (COPSOQ-II) Using Set-ESEM: Identifying Psychosocial Risk Factors in a Sample of School Principals.

PubMed

Dicke, Theresa; Marsh, Herbert W; Riley, Philip; Parker, Philip D; Guo, Jiesi; Horwood, Marcus

2018-01-01

School principals world-wide report high levels of strain and attrition resulting in a shortage of qualified principals. It is thus crucial to identify psychosocial risk factors that reflect principals' occupational wellbeing. For this purpose, we used the Copenhagen Psychosocial Questionnaire (COPSOQ-II), a widely used self-report measure covering multiple psychosocial factors identified by leading occupational stress theories. We evaluated the COPSOQ-II regarding factor structure and longitudinal, discriminant, and convergent validity using latent structural equation modeling in a large sample of Australian school principals ( N = 2,049). Results reveal that confirmatory factor analysis produced marginally acceptable model fit. A novel approach we call set exploratory structural equation modeling (set-ESEM), where cross-loadings were only allowed within a priori defined sets of factors, fit well, and was more parsimonious than a full ESEM. Further multitrait-multimethod models based on the set-ESEM confirm the importance of a principal's psychosocial risk factors; Stressors and depression were related to demands and ill-being, while confidence and autonomy were related to wellbeing. We also show that working in the private sector was beneficial for showing a low psychosocial risk, while other demographics have little effects. Finally, we identify five latent risk profiles (high risk to no risk) of school principals based on all psychosocial factors. Overall the research presented here closes the theory application gap of a strong multi-dimensional measure of psychosocial risk-factors.

Disentangling the relationships between maternal smoking during pregnancy and co-occurring risk factors

PubMed Central

Ellingson, Jarrod M.; Rickert, Martin E.; Lichtenstein, Paul; Långström, Niklas; D’Onofrio, Brian M.

2013-01-01

Background Maternal smoking during pregnancy (SDP) has been extensively studied as a risk factor for adverse offspring outcomes and is known to co-occur with other familial risk factors. Accounting for general familial risk factors has attenuated associations between SDP and adverse offspring outcomes, and identifying these confounds will be critical to elucidating the relationship between SDP and its psychological correlates. Methods The current study aimed to disentangle the relationship between maternal SDP and co-occurring risk factors (maternal criminal activity, drug problems, teen pregnancy, educational attainment, and cohabitation at childbirth) using a population-based sample of full- (n=206,313) and half-sister pairs (n=19,363) from Sweden. Logistic regression models estimated the strength of association between SDP and co-occurring risk factors. Bivariate behavioral genetic models estimated the degree to which associations between SDP and co-occurring risk factors are attributable to genetic and environmental factors. Results Maternal SDP was associated with an increase in all co-occurring risk factors. Of the variance associated with SDP, 45% was attributed to genetic factors and 53% was attributed to unshared environmental factors. In bivariate models, genetic factors accounted for 21% (non- drug-, non-violence-related crimes) to 35% (drug-related crimes) of the covariance between SDP and co-occurring risk factors. Unshared environmental factors accounted for the remaining covariance. Conclusions The genetic factors that influence a woman’s criminal behavior, substance abuse, and her offspring’s rearing environment also influence SDP. Therefore, the intergenerational transmission of genes conferring risk for antisocial behavior and substance misuse may influence the associations between maternal SDP and adverse offspring outcomes. PMID:22115276

Early Life Stress and Sleep Restriction as Risk Factors in PTSD: An Integrative Pre-Clinical Approach

DTIC Science & Technology

2014-04-01

potential risk factors, with high relevance to soldiers. The primary aims of the project are thus. 1) To establish an effective animal model of PTSD that...develop the model as a platform for pharmacological testing of novel targets for drug development 5) As an additional aim – once an effective animal model...thus: 1) To establish an effective animal model of PTSD that would take into consideration the contribution of risk factors to the induction of the

Predictive Modeling of Risk Factors and Complications of Cataract Surgery

PubMed Central

Gaskin, Gregory L; Pershing, Suzann; Cole, Tyler S; Shah, Nigam H

2016-01-01

Purpose To quantify the relationship between aggregated preoperative risk factors and cataract surgery complications, as well as to build a model predicting outcomes on an individual-level—given a constellation of demographic, baseline, preoperative, and intraoperative patient characteristics. Setting Stanford Hospital and Clinics between 1994 and 2013. Design Retrospective cohort study Methods Patients age 40 or older who received cataract surgery between 1994 and 2013. Risk factors, complications, and demographic information were extracted from the Electronic Health Record (EHR), based on International Classification of Diseases, 9th edition (ICD-9) codes, Current Procedural Terminology (CPT) codes, drug prescription information, and text data mining using natural language processing. We used a bootstrapped least absolute shrinkage and selection operator (LASSO) model to identify highly-predictive variables. We built random forest classifiers for each complication to create predictive models. Results Our data corroborated existing literature on postoperative complications—including the association of intraoperative complications, complex cataract surgery, black race, and/or prior eye surgery with an increased risk of any postoperative complications. We also found a number of other, less well-described risk factors, including systemic diabetes mellitus, young age (<60 years old), and hyperopia as risk factors for complex cataract surgery and intra- and post-operative complications. Our predictive models based on aggregated outperformed existing published models. Conclusions The constellations of risk factors and complications described here can guide new avenues of research and provide specific, personalized risk assessment for a patient considering cataract surgery. The predictive capacity of our models can enable risk stratification of patients, which has utility as a teaching tool as well as informing quality/value-based reimbursements. PMID:26692059

The Role of Social Contexts in Adolescence: Context Protection and Context Risk in the United States and China

ERIC Educational Resources Information Center

Costa, Frances M.; Jessor, Richard; Turbin, Mark S.; Dong, Qi; Zhang, Hongchuan; Wang, Changhai

2005-01-01

A theoretical framework about protective factors (models protection, controls protection, support protection) and risk factors (models risk, opportunity risk, vulnerability risk) was employed to articulate the content of 4 key contexts of adolescent life--family, peers, school, and neighborhood--in a cross-national study of problem behavior among…

The influence of socioeconomic factors on cardiovascular disease risk factors in the context of economic development in the Samoan archipelago.

PubMed

Ezeamama, Amara E; Viali, Satupaitea; Tuitele, John; McGarvey, Stephen T

2006-11-01

Early in economic development there are positive associations between socioeconomic status (SES) and cardiovascular disease (CVD) risk factors, and in the most developed market economy societies there are negative associations. The purpose of this report is to describe cross-sectional and longitudinal associations between indicators of SES and CVD risk factors in a genetically homogenous population of Samoans at different levels of economic development. At baseline 1289 participants 25-58yrs, and at 4-year follow-up, 963 participants were studied in less economically developed Samoa and in more developed American Samoa. SES was assessed by education, occupation, and material lifestyle at baseline. The CVD risk factors, obesity, type-2 diabetes and hypertension were measured at baseline and 4-year follow-up, and an index of any incident CVD risk factor at follow-up was calculated. Sex and location (Samoa and American Samoa) specific multivariable logistic regression models were used to test for relationships between SES and CVD risk factors at baseline after adjustment for age and the other SES indicators. In addition an ordinal SES index was constructed for each individual based on all three SES indicators, and used in a multivariable model to estimate the predicted probability of CVD risk factors across the SES index for the two locations. In both the models using specific SES measures and CVD risk factor outcomes, and the models using the ordinal SES index and predicted probabilities of CVD risk factors, we detected a pattern of high SES associated with: (1) elevated odds of CVD risk factors in less developed Samoa, and (2) decreased odds of CVD risk factors in more developed American Samoa. We conclude that the pattern of inverse associations between SES and CVD risk factors in Samoa and direct associations in American Samoa is attributable to the heterogeneity across the Samoas in specific exposures to social processes of economic development and the natural history of individual CVD risk factors. The findings suggest that interventions on non-communicable diseases in the Samoas must be devised based on the level of economic development, the socio-economic context of risk factor exposures, and individual characteristics such as age, sex and education level.

Risk models of dating aggression across different adolescent relationships: a developmental psychopathology approach.

PubMed

Williams, Tricia S; Connolly, Jennifer; Pepler, Debra; Craig, Wendy; Laporte, Lise

2008-08-01

The present study examined physical dating aggression in different adolescent relationships and assessed linear, threshold, and moderator risk models for recurrent aggressive relationships. The 621 participants (59% girls, 41% boys) were drawn from a 1-year longitudinal survey of Canadian high school youths ranging from Grade 9 through Grade 12. Approximately 13% of participants reported recurrent dating aggression across 2 different relationships. Using peer and dyadic risk factors from Time 1 of the study, the authors confirmed a linear risk model, such that adolescents in 2 different violent relationships had significantly more contextual risk factors than did adolescents in 1 or no violent relationship. Further, structural equation modeling assessing moderation of contextual risk factors indicated that, for adolescents with high acceptance of dating aggression, peer aggression and delinquency significantly predicted recurrent aggression in a new relationship. In comparison, for adolescents with low acceptance of dating aggression, negative relationship characteristics significantly predicted recurrent aggression. Acceptance did not moderate concurrent associations between risk factors and aggression in 1 relationship. Results support a developmental psychopathological approach to the understanding of recurrent aggression and its associated risk factors. Copyright 2008 APA, all rights reserved.

12 CFR Appendix C to Part 325 - Risk-Based Capital for State Non-Member Banks: Market Risk

Code of Federal Regulations, 2011 CFR

2011-01-01

... commodity prices. (2) Specific risk means changes in the market value of specific positions due to factors... its risk measurement and risk management systems at least annually. (c) Market risk factors. The bank's internal model must use risk factors sufficient to measure the market risk inherent in all covered...

Job stress models for predicting burnout syndrome: a review.

PubMed

Chirico, Francesco

2016-01-01

In Europe, the Council Directive 89/391 for improvement of workers' safety and health has emphasized the importance of addressing all occupational risk factors, and hence also psychosocial and organizational risk factors. Nevertheless, the construct of "work-related stress" elaborated from EU-OSHA is not totally corresponding with the "psychosocial" risk, that is a broader category of risk, comprising various and different psychosocial risk factors. The term "burnout", without any binding definition, tries to integrate symptoms as well as cause of the burnout process. In Europe, the most important methods developed for the work related stress risk assessment are based on the Cox's transactional model of job stress. Nevertheless, there are more specific models for predicting burnout syndrome. This literature review provides an overview of job burnout, highlighting the most important models of job burnout, such as the Job Strain, the Effort/Reward Imbalance and the Job Demands-Resources models. The difference between these models and the Cox's model of job stress is explored.

The relationship between the effect of pravastatin and risk factors for coronary heart disease in Japanese patients with hypercholesterolemia.

PubMed

Ishikawa, Toshitsugu; Mizuno, Kyoichi; Nakaya, Noriaki; Ohashi, Yasuo; Tajima, Naoko; Kushiro, Toshio; Teramoto, Tamio; Uchiyama, Shinichiro; Nakamura, Haruo

2008-10-01

Several epidemiologic studies in Japan have shown the risk factors for coronary heart disease (CHD) in the general population. The present analysis determined the risk factors for CHD in the MEGA Study, a large primary prevention trial with pravastatin in Japanese with hypercholesterolemia. The relationship between each baseline characteristic and the risk of CHD for the 5-year study period were evaluated using the Cox proportional hazard model. The multivariable predictors of CHD were sex, age, high-density lipoprotein-cholesterol (HDL-C), diabetes mellitus (DM), hypertension (HT), and history of smoking. Serum total and low-density lipoprotein-cholesterol were not independent risk factors for CHD in the current analysis. In addition, the effect of pravastatin was evaluated by subgroups in each risk factor using the interaction in a Cox model. Diet plus pravastatin treatment reduced CHD risk by 14-43% compared with diet alone, regardless of the presence or absence of risk factors. The risk factors for CHD were sex, age, DM, HT, smoking, and low HDL-C in the MEGA Study. The pravastatin treatment was effective for reducing the risk of CHD, regardless of the presence of risk factors.

12 CFR Appendix E to Part 208 - Capital Adequacy Guidelines for State Member Banks; Market Risk Measure

Code of Federal Regulations, 2011 CFR

2011-01-01

... positions due to factors other than broad market movements and includes event and default risk as well as... its risk measurement and risk management systems at least annually. (c) Market risk factors. The bank's internal model must use risk factors sufficient to measure the market risk inherent in all covered...

Income inequality and cardiovascular disease risk factors in a highly unequal country: a fixed-effects analysis from South Africa.

PubMed

Adjaye-Gbewonyo, Kafui; Kawachi, Ichiro; Subramanian, S V; Avendano, Mauricio

2018-03-06

Chronic stress associated with high income inequality has been hypothesized to increase CVD risk and other adverse health outcomes. However, most evidence comes from high-income countries, and there is limited evidence on the link between income inequality and biomarkers of chronic stress and risk for CVD. This study examines how changes in income inequality over recent years relate to changes in CVD risk factors in South Africa, home to some of the highest levels of income inequality globally. We linked longitudinal data from 9356 individuals interviewed in the 2008 and 2012 National Income Dynamics Study to district-level Gini coefficients estimated from census and survey data. We investigated whether subnational district income inequality was associated with several modifiable risk factors for cardiovascular disease (CVD) in South Africa, including body mass index (BMI), waist circumference, blood pressure, physical inactivity, smoking, and high alcohol consumption. We ran individual fixed-effects models to examine the association between changes in income inequality and changes in CVD risk factors over time. Linear models were used for continuous metabolic outcomes while conditional Poisson models were used to estimate risk ratios for dichotomous behavioral outcomes. Both income inequality and prevalence of most CVD risk factors increased over the period of study. In longitudinal fixed-effects models, changes in district Gini coefficients were not significantly associated with changes in CVD risk factors. Our findings do not support the hypothesis that subnational district income inequality is associated with CVD risk factors within the high-inequality setting of South Africa.

Empirical analysis of farmers' drought risk perception: objective factors, personal circumstances, and social influence.

PubMed

Duinen, Rianne van; Filatova, Tatiana; Geurts, Peter; Veen, Anne van der

2015-04-01

Drought-induced water shortage and salinization are a global threat to agricultural production. With climate change, drought risk is expected to increase as drought events are assumed to occur more frequently and to become more severe. The agricultural sector's adaptive capacity largely depends on farmers' drought risk perceptions. Understanding the formation of farmers' drought risk perceptions is a prerequisite to designing effective and efficient public drought risk management strategies. Various strands of literature point at different factors shaping individual risk perceptions. Economic theory points at objective risk variables, whereas psychology and sociology identify subjective risk variables. This study investigates and compares the contribution of objective and subjective factors in explaining farmers' drought risk perception by means of survey data analysis. Data on risk perceptions, farm characteristics, and various other personality traits were collected from farmers located in the southwest Netherlands. From comparing the explanatory power of objective and subjective risk factors in separate models and a full model of risk perception, it can be concluded that farmers' risk perceptions are shaped by both rational and emotional factors. In a full risk perception model, being located in an area with external water supply, owning fields with salinization issues, cultivating drought-/salt-sensitive crops, farm revenue, drought risk experience, and perceived control are significant explanatory variables of farmers' drought risk perceptions. © 2014 Society for Risk Analysis.

Projections of preventable risks for cardiovascular disease in Canada to 2021: a microsimulation modelling approach

PubMed Central

Manuel, Douglas G.; Tuna, Meltem; Hennessy, Deirdre; Okhmatovskaia, Anya; Finès, Philippe; Tanuseputro, Peter; Tu, Jack V.; Flanagan, William

2014-01-01

Background Reductions in preventable risks associated with cardiovascular disease have contributed to a steady decrease in its incidence over the past 50 years in most developed countries. However, it is unclear whether this trend will continue. Our objective was to examine future risk by projecting trends in preventable risk factors in Canada to 2021. Methods We created a population-based microsimulation model using national data on births, deaths and migration; socioeconomic data; cardiovascular disease risk factors; and algorithms for changes in these risk factors (based on sociodemographic characteristics and previous cardiovascular disease risk). An initial population of 22.5 million people, representing the Canadian adult population in 2001, had 13 characteristics including the risk factors used in clinical risk prediction. There were 6.1 million potential exposure profiles for each person each year. Outcome measures included annual prevalence of risk factors (smoking, obesity, diabetes, hypertension and lipid levels) and of co-occurring risks. Results From 2003 to 2009, the projected risks of cardiovascular disease based on the microsimulation model closely approximated those based on national surveys. Except for obesity and diabetes, all risk factors were projected to decrease through to 2021. The largest projected decreases were for the prevalence of smoking (from 25.7% in 2001 to 17.7% in 2021) and uncontrolled hypertension (from 16.1% to 10.8%). Between 2015 and 2017, obesity was projected to surpass smoking as the most prevalent risk factor. Interpretation Risks of cardiovascular disease are projected to decrease modestly in Canada, leading to a likely continuing decline in its incidence. PMID:25077135

Gender-specific risk factors for virologic failure in KwaZulu-Natal: Automobile ownership and financial insecurity

PubMed Central

HARE, Anna Q.; ORDÓÑEZ, Claudia E.; JOHNSON, Brent A.; RIO, Carlos DEL; KEARNS, Rachel A.; WU, Baohua; HAMPTON, Jane; WU, Peng; SUNPATH, Henry; MARCONI, Vincent C.

2014-01-01

We sought to examine which socioeconomic indicators are risk factors for virologic failure among HIV-1 infected patients receiving antiretroviral therapy in KwaZulu-Natal, South Africa. A case-control study of virologic failure was conducted among patients recruited from the outpatient clinic at McCord Hospital in Durban, South Africa between October 1, 2010 and June 30, 2012. Cases were those failing first-line antiretroviral therapy (ART), defined as viral load > 1000 copies/mL. Univariate logistic regression was performed on sociodemographic data for the outcome of virologic failure. Variables found significant (p<.05) were used in multivariate models and all models were stratified by gender. Of 158 cases and 300 controls, 35% were male and median age was 40 years. Gender stratification of models revealed automobile ownership was a risk factor among males, while variables of financial insecurity (unemployment, non-spouse family paying for care, staying with family) were risk factors for women. In this cohort, financial insecurity among women and automobile ownership among men were risk factors for virologic failure. Risk factor differences between genders demonstrate limitations of generalized risk factor analysis. PMID:25037488

Gender-specific risk factors for virologic failure in KwaZulu-Natal: automobile ownership and financial insecurity.

PubMed

Hare, Anna Q; Ordóñez, Claudia E; Johnson, Brent A; Del Rio, Carlos; Kearns, Rachel A; Wu, Baohua; Hampton, Jane; Wu, Peng; Sunpath, Henry; Marconi, Vincent C

2014-11-01

We sought to examine which socioeconomic indicators are risk factors for virologic failure among HIV-1 infected patients receiving antiretroviral therapy (ART) in KwaZulu-Natal, South Africa. A case-control study of virologic failure was conducted among patients recruited from the outpatient clinic at McCord Hospital in Durban, South Africa between October 1, 2010 and June 30, 2012. Cases were those failing first-line ART, defined as viral load >1,000 copies/mL. Univariate logistic regression was performed on sociodemographic data for the outcome of virologic failure. Variables found significant (p < 0.05) were used in multivariate models and all models were stratified by gender. Of 158 cases and 300 controls, 35 % were male and median age was 40 years. Gender stratification of models revealed automobile ownership was a risk factor among males, while variables of financial insecurity (unemployment, non-spouse family paying for care, staying with family) were risk factors for women. In this cohort, financial insecurity among women and automobile ownership among men were risk factors for virologic failure. Risk factor differences between genders demonstrate limitations of generalized risk factor analysis.

The current contribution of molecular factors to risk estimation in neuroblastoma patients.

PubMed

Berthold, F; Sahin, K; Hero, B; Christiansen, H; Gehring, M; Harms, D; Horz, S; Lampert, F; Schwab, M; Terpe, J

1997-10-01

The association of molecular characteristics with prognosis has been reported, but not their relationship with each other and their impact in the context of known clinical risk factors. In this study, data of 1249 consecutive intent-to-treat-neuroblastoma patients with more than 1 year follow-up were examined by multivariate analysis using loglinear and Cox proportional hazard regression models on a stage-related basis (stages 1-3: 600, 4S: 116, 4: 533). In a first step, risk factors were identified from 18 selected clinical variables, and risk groups defined. The second step investigated whether molecular characteristics (MYCN, LOH 1p, del 1p, CD44, N-ras, NGF-R, bcl-2, APO-1 (CD95)) contributed additional prognostic information to the model. The loglinear model demonstrated several interactions between clinical factors. By the Cox regression model, seven independent clinical risk factors were found for stages 1-3, seven for stage 4 and two for stage 4S. By subsequent introduction of all molecular variables, MYCN amplification only added significant prognostic information to the clinical factors in localised and stage 4 neuroblastoma. The models allowed the definition of risk groups for stages 1-3 patients by age (e beta = 5.09) and MYCN (e beta = 4.26), for stage 4 by MYCN (e beta = 2.78) and number of symptoms (e beta = 2.44) and for stage 4S by platelet count (e beta = 3.91) and general condition (e beta = 2.99). Molecular factors and in particular MYCN contribute significantly to risk estimation. In conjunction with clinical factors, they are powerful tools to define risk groups in neuroblastoma.

Combining Knowledge and Data Driven Insights for Identifying Risk Factors using Electronic Health Records

PubMed Central

Sun, Jimeng; Hu, Jianying; Luo, Dijun; Markatou, Marianthi; Wang, Fei; Edabollahi, Shahram; Steinhubl, Steven E.; Daar, Zahra; Stewart, Walter F.

2012-01-01

Background: The ability to identify the risk factors related to an adverse condition, e.g., heart failures (HF) diagnosis, is very important for improving care quality and reducing cost. Existing approaches for risk factor identification are either knowledge driven (from guidelines or literatures) or data driven (from observational data). No existing method provides a model to effectively combine expert knowledge with data driven insight for risk factor identification. Methods: We present a systematic approach to enhance known knowledge-based risk factors with additional potential risk factors derived from data. The core of our approach is a sparse regression model with regularization terms that correspond to both knowledge and data driven risk factors. Results: The approach is validated using a large dataset containing 4,644 heart failure cases and 45,981 controls. The outpatient electronic health records (EHRs) for these patients include diagnosis, medication, lab results from 2003–2010. We demonstrate that the proposed method can identify complementary risk factors that are not in the existing known factors and can better predict the onset of HF. We quantitatively compare different sets of risk factors in the context of predicting onset of HF using the performance metric, the Area Under the ROC Curve (AUC). The combined risk factors between knowledge and data significantly outperform knowledge-based risk factors alone. Furthermore, those additional risk factors are confirmed to be clinically meaningful by a cardiologist. Conclusion: We present a systematic framework for combining knowledge and data driven insights for risk factor identification. We demonstrate the power of this framework in the context of predicting onset of HF, where our approach can successfully identify intuitive and predictive risk factors beyond a set of known HF risk factors. PMID:23304365

A Multiple Risk Factors Model of the Development of Aggression among Early Adolescents from Urban Disadvantaged Neighborhoods

ERIC Educational Resources Information Center

Kim, Sangwon; Orpinas, Pamela; Kamphaus, Randy; Kelder, Steven H.

2011-01-01

This study empirically derived a multiple risk factors model of the development of aggression among middle school students in urban, low-income neighborhoods, using Hierarchical Linear Modeling (HLM). Results indicated that aggression increased from sixth to eighth grade. Additionally, the influences of four risk domains (individual, family,…

Testing a Gender Additive Model: The Role of Body Image in Adolescent Depression

ERIC Educational Resources Information Center

Bearman, Sarah Kate; Stice, Eric

2008-01-01

Despite consistent evidence that adolescent girls are at greater risk of developing depression than adolescent boys, risk factor models that account for this difference have been elusive. The objective of this research was to examine risk factors proposed by the "gender additive" model of depression that attempts to partially explain the increased…

Structural equation model of interactions between risk factors and work-related musculoskeletal complaints among Iranian hospital nurses.

PubMed

Mehralizadeh, Semira; Dehdashti, Alireza; Motalebi Kashani, Masoud

2017-01-01

Statistics indicate a high risk of developing work-related musculoskeletal disorders among hospital nurses. The challenge is to understand the associations between musculoskeletal symptoms and various individual and occupational risk factors. This study examined the direct and indirect interactions of various risk factors with musculoskeletal complaints in hospital nurses. In a cross-sectional design, Iranian hospital nurses from Semnan University of Medical Sciences participated in a questionnaire survey reporting their perceived perceptions of various work-related risk factors and musculoskeletal symptoms. We tested our proposed structural equation model to evaluate the relations between latent and observed concepts and the relative importance and strength of exogenous variables in explaining endogenous musculoskeletal complaints. Measurement model fits the data relatively acceptable. Our findings showed direct effects of psychological, role-related and work posture stressors on musculoskeletal complaints. Fatigue mediated the adverse indirect relations of psychological, role-related, work posture and individual factors with musculoskeletal complaints. Structural equation modeling may provide methodological opportunities in occupational health research with a potential to explain the complexity of interactions among risk factors. Prevention of work-related musculoskeletal disorders among nurses must account for physical and psychosocial conditions.

Modeling the Diagnostic Criteria for Alcohol Dependence with Genetic Animal Models

PubMed Central

Kendler, Kenneth S.; Hitzemann, Robert J.

2012-01-01

A diagnosis of alcohol dependence (AD) using the DSM-IV-R is categorical, based on an individual’s manifestation of three or more symptoms from a list of seven. AD risk can be traced to both genetic and environmental sources. Most genetic studies of AD risk implicitly assume that an AD diagnosis represents a single underlying genetic factor. We recently found that the criteria for an AD diagnosis represent three somewhat distinct genetic paths to individual risk. Specifically, heavy use and tolerance versus withdrawal and continued use despite problems reflected separate genetic factors. However, some data suggest that genetic risk for AD is adequately described with a single underlying genetic risk factor. Rodent animal models for alcohol-related phenotypes typically target discrete aspects of the complex human AD diagnosis. Here, we review the literature derived from genetic animal models in an attempt to determine whether they support a single-factor or multiple-factor genetic structure. We conclude that there is modest support in the animal literature that alcohol tolerance and withdrawal reflect distinct genetic risk factors, in agreement with our human data. We suggest areas where more research could clarify this attempt to align the rodent and human data. PMID:21910077

Geographic Profiling to Assess the Risk of Rare Plant Poaching in Natural Areas

NASA Astrophysics Data System (ADS)

Young, John A.; van Manen, Frank T.; Thatcher, Cindy A.

2011-09-01

We demonstrate the use of an expert-assisted spatial model to examine geographic factors influencing the poaching risk of a rare plant (American ginseng, Panax quinquefolius L.) in Shenandoah National Park, Virginia, USA. Following principles of the analytic hierarchy process (AHP), we identified a hierarchy of 11 geographic factors deemed important to poaching risk and requested law enforcement personnel of the National Park Service to rank those factors in a series of pair-wise comparisons. We used those comparisons to determine statistical weightings of each factor and combined them into a spatial model predicting poaching risk. We tested the model using 69 locations of previous poaching incidents recorded by law enforcement personnel. These locations occurred more frequently in areas predicted by the model to have a higher risk of poaching than random locations. The results of our study can be used to evaluate resource protection strategies and to target law enforcement activities.

Improved performance of epidemiologic and genetic risk models for rheumatoid arthritis serologic phenotypes using family history

PubMed Central

Sparks, Jeffrey A.; Chen, Chia-Yen; Jiang, Xia; Askling, Johan; Hiraki, Linda T.; Malspeis, Susan; Klareskog, Lars; Alfredsson, Lars; Costenbader, Karen H.; Karlson, Elizabeth W.

2014-01-01

Objective To develop and validate rheumatoid arthritis (RA) risk models based on family history, epidemiologic factors, and known genetic risk factors. Methods We developed and validated models for RA based on known RA risk factors, among women in two cohorts: the Nurses’ Health Study (NHS, 381 RA cases and 410 controls) and the Epidemiological Investigation of RA (EIRA, 1244 RA cases and 971 controls). Model discrimination was evaluated using the area under the receiver operating characteristic curve (AUC) in logistic regression models for the study population and for those with positive family history. The joint effect of family history with genetics, smoking, and body mass index (BMI) was evaluated using logistic regression models to estimate odds ratios (OR) for RA. Results The complete model including family history, epidemiologic risk factors, and genetics demonstrated AUCs of 0.74 for seropositive RA in NHS and 0.77 for anti-citrullinated protein antibody (ACPA)-positive RA in EIRA. Among women with positive family history, discrimination was excellent for complete models for seropositive RA in NHS (AUC 0.82) and ACPA-positive RA in EIRA (AUC 0.83). Positive family history, high genetic susceptibility, smoking, and increased BMI had an OR of 21.73 for ACPA-positive RA. Conclusions We developed models for seropositive and seronegative RA phenotypes based on family history, epidemiologic and genetic factors. Among those with positive family history, models utilizing epidemiologic and genetic factors were highly discriminatory for seropositive and seronegative RA. Assessing epidemiological and genetic factors among those with positive family history may identify individuals suitable for RA prevention strategies. PMID:24685909

Accounting for individualized competing mortality risks in estimating postmenopausal breast cancer risk.

PubMed

Schonberg, Mara A; Li, Vicky W; Eliassen, A Heather; Davis, Roger B; LaCroix, Andrea Z; McCarthy, Ellen P; Rosner, Bernard A; Chlebowski, Rowan T; Hankinson, Susan E; Marcantonio, Edward R; Ngo, Long H

2016-12-01

Accurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death. We included 73,066 women who completed the 2004 Nurses' Health Study (NHS) questionnaire (all ≥57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behaviors, demographics, family history, reproductive factors) and 7 risk factors for non-breast cancer death (comorbidities, functional dependency) and mammography use. We used competing risk regression to identify factors independently associated with breast cancer. We validated the final model by examining calibration (expected-to-observed ratio of breast cancer incidence, E/O) and discrimination (c-statistic) using 74,887 subjects from the Women's Health Initiative Extension Study (WHI-ES; all were ≥55 years and followed for 5 years). Within 5 years, 1.8 % of NHS participants were diagnosed with breast cancer (vs. 2.0 % in WHI-ES, p = 0.02), and 6.6 % experienced non-breast cancer death (vs. 5.2 % in WHI-ES, p < 0.001). Using a model selection procedure which incorporated the Akaike Information Criterion, c-statistic, statistical significance, and clinical judgement, our final model included 9 breast cancer risk factors, 5 comorbidities, functional dependency, and mammography use. The model's c-statistic was 0.61 (95 % CI [0.60-0.63]) in NHS and 0.57 (0.55-0.58) in WHI-ES. On average, our model under predicted breast cancer in WHI-ES (E/O 0.92 [0.88-0.97]). We developed a novel prediction model that factors in postmenopausal women's individualized competing risks of non-breast cancer death when estimating breast cancer risk.

A Bayesian network model for predicting type 2 diabetes risk based on electronic health records

NASA Astrophysics Data System (ADS)

Xie, Jiang; Liu, Yan; Zeng, Xu; Zhang, Wu; Mei, Zhen

2017-07-01

An extensive, in-depth study of diabetes risk factors (DBRF) is of crucial importance to prevent (or reduce) the chance of suffering from type 2 diabetes (T2D). Accumulation of electronic health records (EHRs) makes it possible to build nonlinear relationships between risk factors and diabetes. However, the current DBRF researches mainly focus on qualitative analyses, and the inconformity of physical examination items makes the risk factors likely to be lost, which drives us to study the novel machine learning approach for risk model development. In this paper, we use Bayesian networks (BNs) to analyze the relationship between physical examination information and T2D, and to quantify the link between risk factors and T2D. Furthermore, with the quantitative analyses of DBRF, we adopt EHR and propose a machine learning approach based on BNs to predict the risk of T2D. The experiments demonstrate that our approach can lead to better predictive performance than the classical risk model.

Risk factors for pressure ulcer development in critically Ill patients: a conceptual model to guide research.

PubMed

Benoit, Richard; Mion, Lorraine

2012-08-01

This paper presents a proposed conceptual model to guide research on pressure ulcer risk in critically ill patients, who are at high risk for pressure ulcer development. However, no conceptual model exists that guides risk assessment in this population. Results from a review of prospective studies were evaluated for design quality and level of statistical reporting. Multivariate findings from studies having high or medium design quality by the National Institute of Health and Clinical Excellence standards were conceptually grouped. The conceptual groupings were integrated into Braden and Bergstrom's (Braden and Bergstrom [1987] Rehabilitation Nursing, 12, 8-12, 16) conceptual model, retaining their original constructs and augmenting their concept of intrinsic factors for tissue tolerance. The model could enhance consistency in research on pressure ulcer risk factors. Copyright © 2012 Wiley Periodicals, Inc.

Using decision tree analysis to identify risk factors for relapse to smoking

PubMed Central

Piper, Megan E.; Loh, Wei-Yin; Smith, Stevens S.; Japuntich, Sandra J.; Baker, Timothy B.

2010-01-01

This research used classification tree analysis and logistic regression models to identify risk factors related to short- and long-term abstinence. Baseline and cessation outcome data from two smoking cessation trials, conducted from 2001 to 2002, in two Midwestern urban areas, were analyzed. There were 928 participants (53.1% women, 81.8% white) with complete data. Both analyses suggest that relapse risk is produced by interactions of risk factors and that early and late cessation outcomes reflect different vulnerability factors. The results illustrate the dynamic nature of relapse risk and suggest the importance of efficient modeling of interactions in relapse prediction. PMID:20397871

Do recent epidemiologic observations impact who and how we should screen for CRC?

PubMed

Bortniker, Ethan; Anderson, Joseph C

2015-03-01

Colorectal cancer (CRC) screening is recommended to begin at age 50 for those patients with no significant family history of CRC. However, even within this group of average-risk patients, there is data to suggest that there may be variation in CRC risk. These observations suggest that perhaps CRC screening should be tailored to target those patients at higher risk for earlier or more invasive screening as compared to those individuals at lower risk. The strategy of how to identify those higher-risk patients may not be straightforward. One method might be to use single risk factors such as smoking or elevated BMI as has been suggested in the recent American College of Gastroenterology CRC screening guidelines. Another paradigm involves the use of models which incorporate several risk factors to stratify patients by risk. This article will highlight recent large studies that examine recognized CRC risk factors as well as review recently developed CRC risk models. There will also be a discussion of the application of these factors and models in an effort to make CRC screening more efficient.

A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study.

PubMed

Haghighi, Mona; Johnson, Suzanne Bennett; Qian, Xiaoning; Lynch, Kristian F; Vehik, Kendra; Huang, Shuai

2016-08-26

Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions.

The cardiovascular event reduction tool (CERT)--a simplified cardiac risk prediction model developed from the West of Scotland Coronary Prevention Study (WOSCOPS).

PubMed

L'Italien, G; Ford, I; Norrie, J; LaPuerta, P; Ehreth, J; Jackson, J; Shepherd, J

2000-03-15

The clinical decision to treat hypercholesterolemia is premised on an awareness of patient risk, and cardiac risk prediction models offer a practical means of determining such risk. However, these models are based on observational cohorts where estimates of the treatment benefit are largely inferred. The West of Scotland Coronary Prevention Study (WOSCOPS) provides an opportunity to develop a risk-benefit prediction model from the actual observed primary event reduction seen in the trial. Five-year Cox model risk estimates were derived from all WOSCOPS subjects (n = 6,595 men, aged 45 to 64 years old at baseline) using factors previously shown to be predictive of definite fatal coronary heart disease or nonfatal myocardial infarction. Model risk factors included age, diastolic blood pressure, total cholesterol/ high-density lipoprotein ratio (TC/HDL), current smoking, diabetes, family history of fatal coronary heart disease, nitrate use or angina, and treatment (placebo/ 40-mg pravastatin). All risk factors were expressed as categorical variables to facilitate risk assessment. Risk estimates were incorporated into a simple, hand-held slide rule or risk tool. Risk estimates were identified for 5-year age bands (45 to 65 years), 4 categories of TC/HDL ratio (<5.5, 5.5 to <6.5, 6.5 to <7.5, > or = 7.5), 2 levels of diastolic blood pressure (<90, > or = 90 mm Hg), from 0 to 3 additional risk factors (current smoking, diabetes, family history of premature fatal coronary heart disease, nitrate use or angina), and pravastatin treatment. Five-year risk estimates ranged from 2% in very low-risk subjects to 61% in the very high-risk subjects. Risk reduction due to pravastatin treatment averaged 31%. Thus, the Cardiovascular Event Reduction Tool (CERT) is a risk prediction model derived from the WOSCOPS trial. Its use will help physicians identify patients who will benefit from cholesterol reduction.

The estimation of time-varying risks in asset pricing modelling using B-Spline method

NASA Astrophysics Data System (ADS)

Nurjannah; Solimun; Rinaldo, Adji

2017-12-01

Asset pricing modelling has been extensively studied in the past few decades to explore the risk-return relationship. The asset pricing literature typically assumed a static risk-return relationship. However, several studies found few anomalies in the asset pricing modelling which captured the presence of the risk instability. The dynamic model is proposed to offer a better model. The main problem highlighted in the dynamic model literature is that the set of conditioning information is unobservable and therefore some assumptions have to be made. Hence, the estimation requires additional assumptions about the dynamics of risk. To overcome this problem, the nonparametric estimators can also be used as an alternative for estimating risk. The flexibility of the nonparametric setting avoids the problem of misspecification derived from selecting a functional form. This paper investigates the estimation of time-varying asset pricing model using B-Spline, as one of nonparametric approach. The advantages of spline method is its computational speed and simplicity, as well as the clarity of controlling curvature directly. The three popular asset pricing models will be investigated namely CAPM (Capital Asset Pricing Model), Fama-French 3-factors model and Carhart 4-factors model. The results suggest that the estimated risks are time-varying and not stable overtime which confirms the risk instability anomaly. The results is more pronounced in Carhart’s 4-factors model.

Normalisation theory: Does it accurately describe temporal changes in adolescent drunkenness and smoking?

PubMed

Sznitman, Sharon R; Zlotnick, Cheryl; Harel-Fisch, Yossi

2016-07-01

The multiple risk model postulates that accumulating risk factors increase adolescent drunkenness and smoking. The normalisation theory adds to this by arguing that the relation between accumulative risk and drunkenness and smoking is dependent on the distribution of these behaviours in the larger population. More concretely, normalisation theory predicts that: (i) when population level use increases, low risk adolescents will be more likely to use alcohol and cigarettes; and (ii) adolescents facing multiple risk factors will be equally likely to use alcohol and cigarettes, regardless of trends in population level use. The current study empirically tests these assumptions on five waves of nationally representative samples of Israeli Jewish youth. Five cross-sectional waves of data from the Israeli Health Behaviour in School-aged Children survey for Jewish 10th graders were used. Logistic regression models measured the impact of changes in population level use across waves on drunkenness and smoking, and their association with differing levels of risk factors. Between zero and two risk factors, the risk of drunkenness and smoking increases for each additional risk factor. When reaching two risk factors, added risk does not significantly increase the likelihood of smoking and drunkenness. Changes in population level drunkenness and smoking did not systematically relate to changes in the individual level relationship between risk factors and smoking and drunkenness. The pattern of results in this study provides strong evidence for the multiple risk factor model and inconsistent evidence for the normalisation theory. [Sznitman SR, Zlotnick C, Harel-Fisch Y. Normalisation theory: Does it accurately describe temporal changes in adolescent drunkenness and smoking? Drug Alcohol Rev 2016;35:424-432]. © 2015 Australasian Professional Society on Alcohol and other Drugs.

Critical factors and paths influencing construction workers' safety risk tolerances.

PubMed

Wang, Jiayuan; Zou, Patrick X W; Li, Penny P

2016-08-01

While workers' safety risk tolerances have been regarded as a main reason for their unsafe behaviors, little is known about why different people have different risk tolerances even when confronting the same situation. The aim of this research is to identify the critical factors and paths that influence workers' safety risk tolerance and to explore how they contribute to accident causal model from a system thinking perceptive. A number of methods were carried out to analyze the data collected through interviews and questionnaire surveys. In the first and second steps of the research, factor identification, factor ranking and factor analysis were carried out, and the results show that workers' safety risk tolerance can be influenced by four groups of factors, namely: (1) personal subjective perception; (2) work knowledge and experiences; (3) work characteristics; and (4) safety management. In the third step of the research, hypothetical influencing path model was developed and tested by using structural equation modeling (SEM). It is found that the effects of external factors (safety management and work characteristics) on risk tolerance are larger than that of internal factors (personal subjective perception and work knowledge & experiences). Specifically, safety management contributes the most to workers' safety risk tolerance through its direct effect and indirect effect; while personal subjective perception comes the second and can act as an intermedia for work characteristics. This research provides an in-depth insight of workers' unsafe behaviors by depicting the contributing factors as shown in the accident causal model developed in this research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Interaction of Occupational and Personal Risk Factors in Workforce Health and Safety

PubMed Central

Pandalai, Sudha; Wulsin, Victoria; Chun, HeeKyoung

2012-01-01

Most diseases, injuries, and other health conditions experienced by working people are multifactorial, especially as the workforce ages. Evidence supporting the role of work and personal risk factors in the health of working people is frequently underused in developing interventions. Achieving a longer, healthy working life requires a comprehensive preventive approach. To help develop such an approach, we evaluated the influence of both occupational and personal risk factors on workforce health. We present 32 examples illustrating 4 combinatorial models of occupational hazards and personal risk factors (genetics, age, gender, chronic disease, obesity, smoking, alcohol use, prescription drug use). Models that address occupational and personal risk factors and their interactions can improve our understanding of health hazards and guide research and interventions. PMID:22021293

Validation of a multifactorial risk factor model used for predicting future caries risk with Nevada adolescents.

PubMed

Ditmyer, Marcia M; Dounis, Georgia; Howard, Katherine M; Mobley, Connie; Cappelli, David

2011-05-20

The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting. This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model. Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%. Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.

Coronary Heart Disease and Stroke Attributable to Major Risk Factors is Similar in Argentina and the United States: the Coronary Heart Disease Policy Model

PubMed Central

Moran, Andrew; DeGennaro, Vincent; Ferrante, Daniel; Coxson, Pamela G.; Palmas, Walter; Mejia, Raul; Perez-Stable, Eliseo J.; Goldman, Lee

2011-01-01

Background Cardiovascular disease is the leading cause of death in Argentina and the U.S. Argentina is 92% urban, with cardiovascular disease risk factor levels approximating the U.S. Methods The Coronary Heart Disease (CHD) Policy Model is a national-scale computer model of CHD and stroke. Risk factor data were obtained from the Cardiovascular Risk Factor Multiple Evaluation in Latin America Study (2003–04), Argentina National Risk Factor Survey (2005) and U.S. national surveys. Proportions of cardiovascular events over 2005–2015 attributable to risk factors were simulated by setting risk factors to optimal exposure levels [systolic blood pressure (SBP) 115 mm Hg, low-density lipoprotein cholesterol (LDL) 2.00 mmol/l (78 mg/dl), high-density lipoprotein cholesterol (HDL) 1.03 mmol/l (60 mg/dl), absence of diabetes, and smoking]. Cardiovascular disease attributable to body mass index (BMI) > 21 kg/m2 was assumed mediated through SBP, LDL, HDL, and diabetes. Results Cardiovascular disease attributable to major risk factors was similar between Argentina and the U.S., except for elevated SBP in men (CHD 8 % points higher in Argentine men, 6% higher for stroke). CHD attributable to BMI > 21 kg/m2 was substantially higher in the U.S. (men 10–11 % points higher; women CHD 13–14% higher). Conclusions Projected cardiovascular disease attributable to major risk factors appeared similar in Argentina and the U.S., though elevated BMI may be responsible for more of U.S. cardiovascular disease. A highly urbanized middle-income nation can have cardiovascular disease rates and risk factor levels comparable to a high income nation, but fewer resources for fighting the epidemic. PMID:21550675

Risk behaviours among early adolescents: risk and protective factors.

PubMed

Wang, Ruey-Hsia; Hsu, Hsiu-Yueh; Lin, Shu-Yuan; Cheng, Chung-Ping; Lee, Shu-Li

2010-02-01

This paper is a report of a study conducted to examine the influence of risk/protective factors on risk behaviours of early adolescents and whether protective factors moderate their impact. An understanding of how risk and protective factors operate to influence risk behaviours of early adolescents will better prepare nurses to perform interventions appropriately to reduce risk behaviours of early adolescents. A cross-sectional study was carried out, based on a sample of public junior high schools (from 7th to 9th grades) in one city and one county in Taiwan. An anonymous questionnaire designed to measure five risk factors, six protective factors and risk behaviours was administered from October 2006 to March 2007. Data from 878 students were used for the present analysis. Pearson's correlations, anova with random effect models, and generalized linear models were used to analyse the statistically significant explanatory variables for risk behaviours. Gender, perceived father's risk behaviour, perceived mother's risk behaviour, health self-efficacy, interaction of health self-efficacy and perceived peers' risk behaviour, and interaction of emotional regulation and perceived peers' risk behaviour were statistically significant explanatory variables of risk behaviours. Health self-efficacy and emotional regulation moderated the negative effects of peers' perceived risk behaviour on risk behaviours. All protective factors were negative statistically correlated with risk behaviours, and all risk factors positively statistically correlated with risk behaviours. Male adolescents should be considered an at-risk group for risk behaviour intervention. Nurses could provide early adolescents with training regarding health self-efficacy improvement, self-esteem enhancement, emotional regulation skills to reduce their risk behaviours.

Job strain (demands and control model) as a predictor of cardiovascular risk factors among petrochemical personnel

PubMed Central

Habibi, Ehsanollah; Poorabdian, Siamak; Shakerian, Mahnaz

2015-01-01

Background: One of the practical models for the assessment of stressful working conditions due to job strain is job demand and control model, which explains how physical and psychological adverse consequences, including cardiovascular risk factors can be established due to high work demands (the amount of workload, in addition to time limitations to complete that work) and low control of the worker on his/her work (lack of decision making) in the workplace. The aim of this study was to investigate how certain cardiovascular risk factors (including body mass index [BMI], heart rate, blood pressure, cholesterol and smoking) and the job demand and job control are related to each other. Materials and Methods: This prospective cohort study was conducted on 500 workers of the petrochemical industry in south of Iran, 2009. The study population was selected using simple random statistical method. They completed job demand and control questionnaire. The cardiovascular risk factors data was extracted from the workers hygiene profiles. Chi-square (χ2) test and hypothesis test (η) were used to assess the possible relationship between different quantified variables, individual demographic and cardiovascular risk factors. Results: The results of this study revealed that a significant relationship can be found between job demand control model and cardiovascular risk factors. Chi-square test result for the heart rate showed the highest (χ2 = 145.078) relationship, the corresponding results for smoking and BMI were χ2 = 85.652 and χ2 = 30.941, respectively. Subsequently, hypothesis testing results for cholesterol and hypertension was 0.469 and 0.684, respectively. Discussion: Job strain is likely to be associated with an increased risk of cardiovascular risk factors among male staff in a petrochemical company in Iran. The parameters illustrated in the Job demands and control model can act as acceptable predictors for the probability of job stress occurrence followed by showing a high trend of CVD risk factors. PMID:25861661

Risk factors for invasive fungal disease in critically ill adult patients: a systematic review.

PubMed

Muskett, Hannah; Shahin, Jason; Eyres, Gavin; Harvey, Sheila; Rowan, Kathy; Harrison, David

2011-01-01

Over 5,000 cases of invasive Candida species infections occur in the United Kingdom each year, and around 40% of these cases occur in critical care units. Invasive fungal disease (IFD) in critically ill patients is associated with increased morbidity and mortality at a cost to both the individual and the National Health Service. In this paper, we report the results of a systematic review performed to identify and summarise the important risk factors derived from published multivariable analyses, risk prediction models and clinical decision rules for IFD in critically ill adult patients to inform the primary data collection for the Fungal Infection Risk Evaluation Study. An internet search was performed to identify articles which investigated risk factors, risk prediction models or clinical decisions rules for IFD in critically ill adult patients. Eligible articles were identified in a staged process and were assessed by two investigators independently. The methodological quality of the reporting of the eligible articles was assessed using a set of questions addressing both general and statistical methodologies. Thirteen articles met the inclusion criteria, of which eight articles examined risk factors, four developed a risk prediction model or clinical decision rule and one evaluated a clinical decision rule. Studies varied in terms of objectives, risk factors, definitions and outcomes. The following risk factors were found in multiple studies to be significantly associated with IFD: surgery, total parenteral nutrition, fungal colonisation, renal replacement therapy, infection and/or sepsis, mechanical ventilation, diabetes, and Acute Physiology and Chronic Health Evaluation II (APACHE II) or APACHE III score. Several other risk factors were also found to be statistically significant in single studies only. Risk factor selection process and modelling strategy also varied across studies, and sample sizes were inadequate for obtaining reliable estimates. This review shows a number of risk factors to be significantly associated with the development of IFD in critically ill adults. Methodological limitations were identified in the design and conduct of studies in this area, and caution should be used in their interpretation.

Risk factors for invasive fungal disease in critically ill adult patients: a systematic review

PubMed Central

2011-01-01

Introduction Over 5,000 cases of invasive Candida species infections occur in the United Kingdom each year, and around 40% of these cases occur in critical care units. Invasive fungal disease (IFD) in critically ill patients is associated with increased morbidity and mortality at a cost to both the individual and the National Health Service. In this paper, we report the results of a systematic review performed to identify and summarise the important risk factors derived from published multivariable analyses, risk prediction models and clinical decision rules for IFD in critically ill adult patients to inform the primary data collection for the Fungal Infection Risk Evaluation Study. Methods An internet search was performed to identify articles which investigated risk factors, risk prediction models or clinical decisions rules for IFD in critically ill adult patients. Eligible articles were identified in a staged process and were assessed by two investigators independently. The methodological quality of the reporting of the eligible articles was assessed using a set of questions addressing both general and statistical methodologies. Results Thirteen articles met the inclusion criteria, of which eight articles examined risk factors, four developed a risk prediction model or clinical decision rule and one evaluated a clinical decision rule. Studies varied in terms of objectives, risk factors, definitions and outcomes. The following risk factors were found in multiple studies to be significantly associated with IFD: surgery, total parenteral nutrition, fungal colonisation, renal replacement therapy, infection and/or sepsis, mechanical ventilation, diabetes, and Acute Physiology and Chronic Health Evaluation II (APACHE II) or APACHE III score. Several other risk factors were also found to be statistically significant in single studies only. Risk factor selection process and modelling strategy also varied across studies, and sample sizes were inadequate for obtaining reliable estimates. Conclusions This review shows a number of risk factors to be significantly associated with the development of IFD in critically ill adults. Methodological limitations were identified in the design and conduct of studies in this area, and caution should be used in their interpretation. PMID:22126425

Percent Mammographic Density and Dense Area as Risk Factors for Breast Cancer.

PubMed

Rauh, C; Hack, C C; Häberle, L; Hein, A; Engel, A; Schrauder, M G; Fasching, P A; Jud, S M; Ekici, A B; Loehberg, C R; Meier-Meitinger, M; Ozan, S; Schulz-Wendtland, R; Uder, M; Hartmann, A; Wachter, D L; Beckmann, M W; Heusinger, K

2012-08-01

Purpose: Mammographic characteristics are known to be correlated to breast cancer risk. Percent mammographic density (PMD), as assessed by computer-assisted methods, is an established risk factor for breast cancer. Along with this assessment the absolute dense area (DA) of the breast is reported as well. Aim of this study was to assess the predictive value of DA concerning breast cancer risk in addition to other risk factors and in addition to PMD. Methods: We conducted a case control study with hospital-based patients with a diagnosis of invasive breast cancer and healthy women as controls. A total of 561 patients and 376 controls with available mammographic density were included into this study. We describe the differences concerning the common risk factors BMI, parital status, use of hormone replacement therapy (HRT) and menopause between cases and controls and estimate the odds ratios for PMD and DA, adjusted for the mentioned risk factors. Furthermore we compare the prediction models with each other to find out whether the addition of DA improves the model. Results: Mammographic density and DA were highly correlated with each other. Both variables were as well correlated to the commonly known risk factors with an expected direction and strength, however PMD (ρ = -0.56) was stronger correlated to BMI than DA (ρ = -0.11). The group of women within the highest quartil of PMD had an OR of 2.12 (95 % CI: 1.25-3.62). This could not be seen for the fourth quartile concerning DA. However the assessment of breast cancer risk could be improved by including DA in a prediction model in addition to common risk factors and PMD. Conclusions: The inclusion of the parameter DA into a prediction model for breast cancer in addition to established risk factors and PMD could improve the breast cancer risk assessment. As DA is measured together with PMD in the process of computer-assisted assessment of PMD it might be considered to include it as one additional breast cancer risk factor that is obtained from breast imaging.

Social appearance anxiety, perfectionism, and fear of negative evaluation: Distinct or shared risk factors for social anxiety and eating disorders?

PubMed Central

Levinson, Cheri A.; Rodebaugh, Thomas L.; White, Emily K.; Menatti, Andrew; Weeks, Justin W.; Iacovino, Juliette M.; Warren, Cortney S.

2013-01-01

Social anxiety and eating disorders are highly comorbid. Social appearance anxiety (i.e., fear of negative evaluation of one's appearance), general fear of negative evaluation, and perfectionism have each been proposed as risk factors for both social anxiety disorder and the eating disorders. However, no research to date has examined all three factors simultaneously. Using structural equation modeling in two diverse samples (N = 236; N = 136) we tested a model in which each of these risk factors were uniquely associated with social anxiety and eating disorder symptoms. We found support for social appearance anxiety as a shared risk factor between social anxiety and eating disorder symptoms, whereas fear of negative evaluation was a risk factor only for social anxiety symptoms. Despite significant zero-order relationships, two facets of perfectionism (high standards and maladaptive perfectionism) did not emerge as a risk factor for either disorder when all constructs were considered. These results were maintained when gender, body mass index, trait negative affect, and depression were included in the model. It is possible that treating negative appearance evaluation fears may reduce both eating disorder and social anxiety symptoms. PMID:23583741

Biomechanical, psychosocial and individual risk factors predicting low back functional impairment among furniture distribution employees

PubMed Central

Ferguson, Sue A.; Allread, W. Gary; Burr, Deborah L.; Heaney, Catherine; Marras, William S.

2013-01-01

Background Biomechanical, psychosocial and individual risk factors for low back disorder have been studied extensively however few researchers have examined all three risk factors. The objective of this was to develop a low back disorder risk model in furniture distribution workers using biomechanical, psychosocial and individual risk factors. Methods This was a prospective study with a six month follow-up time. There were 454 subjects at 9 furniture distribution facilities enrolled in the study. Biomechanical exposure was evaluated using the American Conference of Governmental Industrial Hygienists (2001) lifting threshold limit values for low back injury risk. Psychosocial and individual risk factors were evaluated via questionnaires. Low back health functional status was measured using the lumbar motion monitor. Low back disorder cases were defined as a loss of low back functional performance of −0.14 or more. Findings There were 92 cases of meaningful loss in low back functional performance and 185 non cases. A multivariate logistic regression model included baseline functional performance probability, facility, perceived workload, intermediated reach distance number of exertions above threshold limit values, job tenure manual material handling, and age combined to provide a model sensitivity of 68.5% and specificity of 71.9%. Interpretation: The results of this study indicate which biomechanical, individual and psychosocial risk factors are important as well as how much of each risk factor is too much resulting in increased risk of low back disorder among furniture distribution workers. PMID:21955915

Accounting for individualized competing mortality risks in estimating postmenopausal breast cancer risk

PubMed Central

Schonberg, Mara A.; Li, Vicky W.; Eliassen, A. Heather; Davis, Roger B.; LaCroix, Andrea Z.; McCarthy, Ellen P.; Rosner, Bernard A.; Chlebowski, Rowan T.; Hankinson, Susan E.; Marcantonio, Edward R.; Ngo, Long H.

2016-01-01

Purpose Accurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death. Methods We included 73,066 women who completed the 2004 Nurses’ Health Study (NHS) questionnaire (all ≥57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behaviors, demographics, family history, reproductive factors), 7 risk factors for non-breast cancer death (comorbidities, functional dependency), and mammography use. We used competing risk regression to identify factors independently associated with breast cancer. We validated the final model by examining calibration (expected-to-observed ratio of breast cancer incidence, E/O) and discrimination (c-statistic) using 74,887 subjects from the Women’s Health Initiative Extension Study (WHI-ES; all were ≥55 years and followed for 5 years). Results Within 5 years, 1.8% of NHS participants were diagnosed with breast cancer (vs. 2.0% in WHI-ES, p=0.02) and 6.6% experienced non-breast cancer death (vs. 5.2% in WHI-ES, p<0.001). Using a model selection procedure which incorporated the Akaike Information Criterion, c-statistic, statistical significance, and clinical judgement, our final model included 9 breast cancer risk factors, 5 comorbidities, functional dependency, and mammography use. The model’s c-statistic was 0.61 (95% CI [0.60–0.63]) in NHS and 0.57 (0.55–0.58) in WHI-ES. On average our model under predicted breast cancer in WHI-ES (E/O 0.92 [0.88–0.97]). Conclusions We developed a novel prediction model that factors in postmenopausal women’s individualized competing risks of non-breast cancer death when estimating breast cancer risk. PMID:27770283

Improved performance of epidemiologic and genetic risk models for rheumatoid arthritis serologic phenotypes using family history.

PubMed

Sparks, Jeffrey A; Chen, Chia-Yen; Jiang, Xia; Askling, Johan; Hiraki, Linda T; Malspeis, Susan; Klareskog, Lars; Alfredsson, Lars; Costenbader, Karen H; Karlson, Elizabeth W

2015-08-01

To develop and validate rheumatoid arthritis (RA) risk models based on family history, epidemiologic factors and known genetic risk factors. We developed and validated models for RA based on known RA risk factors, among women in two cohorts: the Nurses' Health Study (NHS, 381 RA cases and 410 controls) and the Epidemiological Investigation of RA (EIRA, 1244 RA cases and 971 controls). Model discrimination was evaluated using the area under the receiver operating characteristic curve (AUC) in logistic regression models for the study population and for those with positive family history. The joint effect of family history with genetics, smoking and body mass index (BMI) was evaluated using logistic regression models to estimate ORs for RA. The complete model including family history, epidemiologic risk factors and genetics demonstrated AUCs of 0.74 for seropositive RA in NHS and 0.77 for anti-citrullinated protein antibody (ACPA)-positive RA in EIRA. Among women with positive family history, discrimination was excellent for complete models for seropositive RA in NHS (AUC 0.82) and ACPA-positive RA in EIRA (AUC 0.83). Positive family history, high genetic susceptibility, smoking and increased BMI had an OR of 21.73 for ACPA-positive RA. We developed models for seropositive and seronegative RA phenotypes based on family history, epidemiological and genetic factors. Among those with positive family history, models using epidemiologic and genetic factors were highly discriminatory for seropositive and seronegative RA. Assessing epidemiological and genetic factors among those with positive family history may identify individuals suitable for RA prevention strategies. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Co-occurring risk factors for current cigarette smoking in a U.S. nationally representative sample

PubMed Central

Higgins, Stephen T.; Kurti, Allison N.; Redner, Ryan; White, Thomas J.; Keith, Diana R.; Gaalema, Diann E.; Sprague, Brian L.; Stanton, Cassandra A.; Roberts, Megan E.; Doogan, Nathan J.; Priest, Jeff S.

2016-01-01

Introduction Relatively little has been reported characterizing cumulative risk associated with co-occurring risk factors for cigarette smoking. The purpose of the present study was to address that knowledge gap in a U.S. nationally representative sample. Methods Data were obtained from 114,426 adults (≥ 18 years) in the U.S. National Survey on Drug Use and Health (years 2011–13). Multiple logistic regression and classification and regression tree (CART) modeling were used to examine risk of current smoking associated with eight co-occurring risk factors (age, gender, race/ethnicity, educational attainment, poverty, drug abuse/dependence, alcohol abuse/dependence, mental illness). Results Each of these eight risk factors was independently associated with significant increases in the odds of smoking when concurrently present in a multiple logistic regression model. Effects of risk-factor combinations were typically summative. Exceptions to that pattern were in the direction of less-than-summative effects when one of the combined risk factors was associated with generally high or low rates of smoking (e.g., drug abuse/dependence, age ≥65). CART modeling identified subpopulation risk profiles wherein smoking prevalence varied from a low of 11% to a high of 74% depending on particular risk factor combinations. Being a college graduate was the strongest independent predictor of smoking status, classifying 30% of the adult population. Conclusions These results offer strong evidence that the effects associated with common risk factors for cigarette smoking are independent, cumulative, and generally summative. The results also offer potentially useful insights into national population risk profiles around which U.S. tobacco policies can be developed or refined. PMID:26902875

Risk factors for breast cancer in postmenopausal Caucasian and Chinese-Canadian women.

PubMed

Tam, Carolyn Y; Martin, Lisa J; Hislop, Gregory; Hanley, Anthony J; Minkin, Salomon; Boyd, Norman F

2010-01-01

Striking differences exist between countries in the incidence of breast cancer. The causes of these differences are unknown, but because incidence rates change in migrants, they are thought to be due to lifestyle rather than genetic differences. The goal of this cross-sectional study was to examine breast cancer risk factors in populations with different risks for breast cancer. We compared breast cancer risk factors among three groups of postmenopausal Canadian women at substantially different risk of developing breast cancer - Caucasians (N = 413), Chinese women born in the West or who migrated to the West before age 21 (N = 216), and recent Chinese migrants (N = 421). Information on risk factors and dietary acculturation were collected by telephone interviews using questionnaires, and anthropometric measurements were taken at a home visit. Compared to Caucasians, recent Chinese migrants weighed on average 14 kg less, were 6 cm shorter, had menarche a year later, were more often parous, less often had a family history of breast cancer or a benign breast biopsy, a higher Chinese dietary score, and a lower Western dietary score. For most of these variables, Western born Chinese and early Chinese migrants had values intermediate between those of Caucasians and recent Chinese migrants. We estimated five-year absolute risks for breast cancer using the Gail Model and found that risk estimates in Caucasians would be reduced by only 11% if they had the risk factor profile of recent Chinese migrants for the risk factors in the Gail Model. Our results suggest that in addition to the risk factors in the Gail Model, there likely are other factors that also contribute to the large difference in breast cancer risk between Canada and China.

The impact of race on metabolic disease risk factors in women with and without posttraumatic stress disorder.

PubMed

Dedert, Eric A; Harper, Leia A; Calhoun, Patrick S; Dennis, Michelle F; Beckham, Jean C

2013-03-01

The literature on PTSD and metabolic disease risk factors has been limited by lacking investigation of the potential influence of commonly comorbid disorders and the role of race. In this study data were provided by a sample of 134 women (63 PTSD and 71 without PTSD). Separate sets of models examining associations of psychiatric disorder classifications with metabolic disease risk factors were used. Each model included race (African American or Caucasian), psychiatric disorder, and their interaction. There was an interaction of race and PTSD on body mass index, abdominal obesity, and triglycerides. While PTSD was not generally associated with deleterious health effects in African American participants, PTSD was related to worse metabolic disease risk factors in Caucasians. MDD was associated with metabolic disease risk factors, but there were no interactions with race. Results support the importance of race in the relationship between PTSD and metabolic disease risk factors. Future research would benefit from analysis of cultural factors to explain how race might influence metabolic disease risk factors in PTSD.

Integrating etiological models of social anxiety and depression in youth: evidence for a cumulative interpersonal risk model.

PubMed

Epkins, Catherine C; Heckler, David R

2011-12-01

Models of social anxiety and depression in youth have been developed separately, and they contain similar etiological influences. Given the high comorbidity of social anxiety and depression, we examine whether the posited etiological constructs are a correlate of, or a risk factor for, social anxiety and/or depression at the symptom level and the diagnostic level. We find core risk factors of temperament, genetics, and parent psychopathology (i.e., depression and anxiety) are neither necessary nor sufficient for the development of social anxiety and/or depression. Instead, aspects of children's relationships with parents and/or peers either mediates (i.e., explains) or moderates (i.e., interacts with) these core risks being related to social anxiety and/or depression. We then examine various parent- and peer-related constructs contained in the separate models of social anxiety and depression (i.e., parent-child attachment, parenting, social skill deficits, peer acceptance and rejection, peer victimization, friendships, and loneliness). Throughout our review, we report evidence for a Cumulative Interpersonal Risk model that incorporates both core risk factors and specific interpersonal risk factors. Most studies fail to consider comorbidity, thus little is known about the specificity of these various constructs to depression and/or social anxiety. However, we identify shared, differential, and cumulative risks, correlates, consequences, and protective factors. We then put forth demonstrated pathways for the development of depression, social anxiety, and their comorbidity. Implications for understanding comorbidity are highlighted throughout, as are theoretical and research directions for developing and refining models of social anxiety, depression, and their comorbidity. Prevention and treatment implications are also noted.

Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.

PubMed

Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C

2014-03-01

To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Cognitive risk factors explain the relations between neuroticism and social anxiety for males and females.

PubMed

Allan, Nicholas P; Oglesby, Mary E; Uhl, Aubree; Schmidt, Norman B

2017-04-01

The hierarchical model of vulnerabilities to emotional distress contextualizes the relation between neuroticism and social anxiety as occurring indirectly through cognitive risk factors. In particular, inhibitory intolerance of uncertainty (IU; difficulty in uncertain circumstances), fear of negative evaluation (FNE; fear of being judged negatively), and anxiety sensitivity (AS) social concerns (fear of outwardly observable anxiety) are related to social anxiety. It is unclear whether these risk factors uniquely relate to social anxiety, and whether they account for the relations between neuroticism and social anxiety. The indirect relations between neuroticism and social anxiety through these and other risk factors were examined using structural equation modeling in a sample of 462 individuals (M age = 36.56, SD = 12.93; 64.3% female). Results indicated that the relations between neuroticism and social anxiety could be explained through inhibitory IU, FNE, and AS social concerns. No gender differences were found. These findings provide support for the hierarchical model of vulnerabilities to emotional distress disorders, although the cognitive risk factors accounted for variance beyond their contribution to the relation between neuroticism and social anxiety, suggesting a more complex model than that expressed in the hierarchical model of vulnerabilities.

The contribution of an animal model toward uncovering biological risk factors for PTSD.

PubMed

Cohen, Hagit; Matar, Michael A; Richter-Levin, Gal; Zohar, Joseph

2006-07-01

Clinical studies of posttraumatic stress disorder (PTSD) have elicited proposed risk factors for developing PTSD in the aftermath of stress exposure. Generally, these risk factors have arisen from retrospective analysis of premorbid characteristics of study populations. A valid animal model of PTSD can complement clinical studies and help to elucidate issues, such as the contribution of proposed risk factors, in ways which are not practicable in the clinical arena. Important qualities of animal models include the possibility to conduct controlled prospective studies, easy access to postmortem brains, and the availability of genetically manipulated subjects, which can be tailored to specific needs. When these qualities are further complemented by an approach which defines phenomenologic criteria to address the variance in individual response pattern and magnitude, enabling the animal subjects to be classified into definable groups for focused study, the model acquires added validity. This article presents an overview of a series of studies in such an animal model which examine the contribution of two proposed risk factors and the value of two early postexposure pharmacological manipulations on the prevalence rates of subjects displaying an extreme magnitude of behavioral response to a predator stress paradigm.

Patient- and cohort-specific dose and risk estimation for abdominopelvic CT: a study based on 100 patients

NASA Astrophysics Data System (ADS)

Tian, Xiaoyu; Li, Xiang; Segars, W. Paul; Frush, Donald P.; Samei, Ehsan

2012-03-01

The purpose of this work was twofold: (a) to estimate patient- and cohort-specific radiation dose and cancer risk index for abdominopelvic computer tomography (CT) scans; (b) to evaluate the effects of patient anatomical characteristics (size, age, and gender) and CT scanner model on dose and risk conversion coefficients. The study included 100 patient models (42 pediatric models, 58 adult models) and multi-detector array CT scanners from two commercial manufacturers (LightSpeed VCT, GE Healthcare; SOMATOM Definition Flash, Siemens Healthcare). A previously-validated Monte Carlo program was used to simulate organ dose for each patient model and each scanner, from which DLP-normalized-effective dose (k factor) and DLP-normalized-risk index values (q factor) were derived. The k factor showed exponential decrease with increasing patient size. For a given gender, q factor showed exponential decrease with both increasing patient size and patient age. The discrepancies in k and q factors across scanners were on average 8% and 15%, respectively. This study demonstrates the feasibility of estimating patient-specific organ dose and cohort-specific effective dose and risk index in abdominopelvic CT requiring only the knowledge of patient size, gender, and age.

Risk Factors Predicting Infectious Lactational Mastitis: Decision Tree Approach versus Logistic Regression Analysis.

PubMed

Fernández, Leónides; Mediano, Pilar; García, Ricardo; Rodríguez, Juan M; Marín, María

2016-09-01

Objectives Lactational mastitis frequently leads to a premature abandonment of breastfeeding; its development has been associated with several risk factors. This study aims to use a decision tree (DT) approach to establish the main risk factors involved in mastitis and to compare its performance for predicting this condition with a stepwise logistic regression (LR) model. Methods Data from 368 cases (breastfeeding women with mastitis) and 148 controls were collected by a questionnaire about risk factors related to medical history of mother and infant, pregnancy, delivery, postpartum, and breastfeeding practices. The performance of the DT and LR analyses was compared using the area under the receiver operating characteristic (ROC) curve. Sensitivity, specificity and accuracy of both models were calculated. Results Cracked nipples, antibiotics and antifungal drugs during breastfeeding, infant age, breast pumps, familial history of mastitis and throat infection were significant risk factors associated with mastitis in both analyses. Bottle-feeding and milk supply were related to mastitis for certain subgroups in the DT model. The areas under the ROC curves were similar for LR and DT models (0.870 and 0.835, respectively). The LR model had better classification accuracy and sensitivity than the DT model, but the last one presented better specificity at the optimal threshold of each curve. Conclusions The DT and LR models constitute useful and complementary analytical tools to assess the risk of lactational infectious mastitis. The DT approach identifies high-risk subpopulations that need specific mastitis prevention programs and, therefore, it could be used to make the most of public health resources.

Which hemostatic markers add to the predictive value of conventional risk factors for coronary heart disease and ischemic stroke? The Caerphilly Study.

PubMed

Smith, Ann; Patterson, Chris; Yarnell, John; Rumley, Ann; Ben-Shlomo, Yoav; Lowe, Gordon

2005-11-15

Few studies have examined whether hemostatic markers contribute to risk of coronary disease and ischemic stroke independently of conventional risk factors. This study examines 11 hemostatic markers that reflect different aspects of the coagulation process to determine which have prognostic value after accounting for conventional risk factors. A total of 2398 men aged 49 to 65 years were examined in 1984 to 1988, and the majority gave a fasting blood sample for assay of lipids and hemostatic markers. Men were followed up for a median of 13 years, and cardiovascular disease (CVD) events were recorded. There were 486 CVD events in total, 353 with prospective coronary disease and 133 with prospective ischemic stroke. On univariable analysis, fibrinogen, low activated protein C ratio, D-dimer, tissue plasminogen activator (tPA), and plasminogen activator inhibitor-1 (PAI-1) were associated significantly with risk of CVD. On multivariable analyses with conventional risk factors forced into the proportional hazards model, fibrinogen, D-dimer, and PAI-1 were significantly associated with risk of CVD, whereas factor VIIc showed an inverse association (P=0.001). In a model that contained the conventional risk factors, the hazard ratio for subsequent CVD in the top third of the distribution of predicted risk relative to the bottom third was 2.7 for subjects without preexisting CVD. This ratio increased to 3.7 for the model that also contained the 4 hemostatic factors. Fibrinogen, D-dimer, PAI-1 activity, and factor VIIc each has potential to increase the prediction of coronary disease/ischemic stroke in middle-aged men, in addition to conventional risk factors.

A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance.

PubMed

Meads, Catherine; Ahmed, Ikhlaaq; Riley, Richard D

2012-04-01

A risk prediction model is a statistical tool for estimating the probability that a currently healthy individual with specific risk factors will develop a condition in the future such as breast cancer. Reliably accurate prediction models can inform future disease burdens, health policies and individual decisions. Breast cancer prediction models containing modifiable risk factors, such as alcohol consumption, BMI or weight, condom use, exogenous hormone use and physical activity, are of particular interest to women who might be considering how to reduce their risk of breast cancer and clinicians developing health policies to reduce population incidence rates. We performed a systematic review to identify and evaluate the performance of prediction models for breast cancer that contain modifiable factors. A protocol was developed and a sensitive search in databases including MEDLINE and EMBASE was conducted in June 2010. Extensive use was made of reference lists. Included were any articles proposing or validating a breast cancer prediction model in a general female population, with no language restrictions. Duplicate data extraction and quality assessment were conducted. Results were summarised qualitatively, and where possible meta-analysis of model performance statistics was undertaken. The systematic review found 17 breast cancer models, each containing a different but often overlapping set of modifiable and other risk factors, combined with an estimated baseline risk that was also often different. Quality of reporting was generally poor, with characteristics of included participants and fitted model results often missing. Only four models received independent validation in external data, most notably the 'Gail 2' model with 12 validations. None of the models demonstrated consistently outstanding ability to accurately discriminate between those who did and those who did not develop breast cancer. For example, random-effects meta-analyses of the performance of the 'Gail 2' model showed the average C statistic was 0.63 (95% CI 0.59-0.67), and the expected/observed ratio of events varied considerably across studies (95% prediction interval for E/O ratio when the model was applied in practice was 0.75-1.19). There is a need for models with better predictive performance but, given the large amount of work already conducted, further improvement of existing models based on conventional risk factors is perhaps unlikely. Research to identify new risk factors with large additionally predictive ability is therefore needed, alongside clearer reporting and continual validation of new models as they develop.

Geographic profiling to assess the risk of rare plant poaching in natural areas

USGS Publications Warehouse

Young, J.A.; Van Manen, F.T.; Thatcher, C.A.

2011-01-01

We demonstrate the use of an expert-assisted spatial model to examine geographic factors influencing the poaching risk of a rare plant (American ginseng, Panax quinquefolius L.) in Shenandoah National Park, Virginia, USA. Following principles of the analytic hierarchy process (AHP), we identified a hierarchy of 11 geographic factors deemed important to poaching risk and requested law enforcement personnel of the National Park Service to rank those factors in a series of pair-wise comparisons. We used those comparisons to determine statistical weightings of each factor and combined them into a spatial model predicting poaching risk. We tested the model using 69 locations of previous poaching incidents recorded by law enforcement personnel. These locations occurred more frequently in areas predicted by the model to have a higher risk of poaching than random locations. The results of our study can be used to evaluate resource protection strategies and to target law enforcement activities. ?? Springer Science+Business Media, LLC (outside the USA) 2011.

Elder Abuse by Adult Children: An Applied Ecological Framework for Understanding Contextual Risk Factors and the Intergenerational Character of Quality of Life.

ERIC Educational Resources Information Center

Schiamberg, Lawrence B.; Gans, Daphna

2000-01-01

Using an applied ecological model, this study focuses on contextual risk factors of elder abuse. Five levels of environment were used to interpret existing research on risk factors. Configuration of risk factors provides a framework for understanding the intergenerational character of quality of life for older adults, developing recommendations…

Violent video games and delinquent behavior in adolescents: A risk factor perspective.

PubMed

Exelmans, Liese; Custers, Kathleen; Van den Bulck, Jan

2015-05-01

Over the years, criminological research has identified a number of risk factors that contribute to the development of aggressive and delinquent behavior. Although studies have identified media violence in general and violent video gaming in particular as significant predictors of aggressive behavior, exposure to violent video games has been largely omitted from the risk factor literature on delinquent behavior. This cross-sectional study therefore investigates the relationship between violent video game play and adolescents' delinquent behavior using a risk factor approach. An online survey was completed by 3,372 Flemish adolescents, aged 12-18 years old. Data were analyzed by means of negative binomial regression modelling. Results indicated a significant contribution of violent video games in delinquent behavior over and beyond multiple known risk variables (peer delinquency, sensation seeking, prior victimization, and alienation). Moreover, the final model that incorporated the gaming genres proved to be significantly better than the model without the gaming genres. Results provided support for a cumulative and multiplicative risk model for delinquent behavior. Aggr. Behav. 41:267-279, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Shared Risk Factors for the Perpetration of Physical Dating Violence, Bullying, and Sexual Harassment Among Adolescents Exposed to Domestic Violence.

PubMed

Foshee, Vangie A; McNaughton Reyes, H Luz; Chen, May S; Ennett, Susan T; Basile, Kathleen C; DeGue, Sarah; Vivolo-Kantor, Alana M; Moracco, Kathryn E; Bowling, J Michael

2016-04-01

The high risk of perpetrating physical dating violence, bullying, and sexual harassment by adolescents exposed to domestic violence points to the need for programs to prevent these types of aggression among this group. This study of adolescents exposed to domestic violence examined whether these forms of aggression share risk factors that could be targeted for change in single programs designed to prevent all three types of aggression. Analyses were conducted on 399 mother victims of domestic violence and their adolescents, recruited through community advertising. The adolescents ranged in age from 12 to 16 years; 64 % were female. Generalized estimating equations was used to control for the covariation among the aggression types when testing for shared risk factors. Approximately 70 % of the adolescents reported perpetrating at least one of the three forms of aggression. In models examining one risk factor at a time, but controlling for demographics, adolescent acceptance of sexual violence, mother-adolescent discord, family conflict, low maternal monitoring, low mother-adolescent closeness, low family cohesion, depressed affect, feelings of anger, and anger reactivity were shared across all three aggression types. In multivariable models, which included all of the risk factors examined and the demographic variables, low maternal monitoring, depressed affect and anger reactivity remained significant shared risk factors. Our findings suggest that programs targeting these risk factors for change have the potential to prevent all three forms of aggression. In multivariable models, poor conflict management skills was a risk for bullying and sexual harassment, but not dating violence; acceptance of dating violence was a risk for dating violence and bullying, but not sexual harassment; and none of the examined risk factors were unique to aggression type. The study's implications for the development of interventions and future research are discussed.

Biopsychosocial risk factors of persistent fatigue after acute infection: A systematic review to inform interventions.

PubMed

Hulme, Katrin; Hudson, Joanna L; Rojczyk, Philine; Little, Paul; Moss-Morris, Rona

2017-08-01

Fatigue is a prevalent and debilitating symptom, preceded by an acute infectious episode in some patients. This systematic review aimed to identify risk factors for the development of persistent fatigue after an acute infection, to develop an evidence-based working model of post-infectious fatigue. Electronic databases (Medline, PsycINFO and EMBASE) were searched, from inception to March 2016, for studies which investigated biopsychosocial risk factors of on-going fatigue after an acute infection. Inclusion criteria were: prospective design; biological, psychological or social risk factors; standardised measure of post-infectious fatigue (self-report scales or clinical diagnosis). Studies were excluded if the sample had a pre-existing medical condition, infection was conceptualised as 'vaccination' or they were intervention trials. A narrative synthesis was performed. Eighty-one full texts were screened, of which seventeen were included in the review. Over half included glandular fever populations. Other infections included dengue fever, 'general'/'viral' and Q-fever. Risk factors were summarised under biological, social, behavioural, cognitive and emotional subthemes. Patients' cognitive and behavioural responses to the acute illness, and pre-infection or baseline distress and fatigue were the most consistent risk factors for post-infectious fatigue. An empirical summary model is provided, highlighting the risk factors most consistently associated with persistent fatigue. The components of the model, the possible interaction of risk factors and implications for understanding the fatigue trajectory and informing preventative treatments are discussed. Copyright © 2017. Published by Elsevier Inc.

Risk factors for gambling and substance use among recent college students.

PubMed

Caldeira, Kimberly M; Arria, Amelia M; O'Grady, Kevin E; Vincent, Kathryn B; Robertson, Carl; Welsh, Christopher J

2017-10-01

While it is well known that substance use and gambling overlap, the degree to which this overlap can be explained by shared risk factors has not been fully explored. This study aimed to identify common and unique risk factors for gambling and substance use among young adults. Young adults (n=1,019) in a longitudinal study since college entry were interviewed annually. Past-year frequency of seven gambling activities was assessed once (Year 5). Structural equation models evaluated suspected risk factors in two models, one for gambling with substance use as an intermediary variable, and one for substance use with gambling as the intermediary variable. Sixty percent gambled; 6% gambled weekly or more. Examination of the two structural models supported the existence of significant paths (a) from two of the five substance use variables (alcohol, drugs) to gambling frequency, and (b) from gambling frequency to all five substance use variables. Every risk factor associated with gambling was also associated with one or more substance use variables. Risk factors common to gambling and substance use were sex, race/ethnicity, extracurricular involvement (fraternity/sorority, athletics), impulsive sensation-seeking, and behavioral dysregulation. Risk factors unique to substance use were conduct problems, anxiety, and parent's history of alcohol and mental health problems. Gambling and substance use are interrelated, but with incomplete overlap in their respective risk factors. Results underscore the need for longitudinal research to elucidate their distinct etiologies. Copyright © 2017 Elsevier B.V. All rights reserved.

Breakthrough seizures—Further analysis of the Standard versus New Antiepileptic Drugs (SANAD) study

PubMed Central

Powell, Graham A.; Tudur Smith, Catrin; Marson, Anthony G.

2017-01-01

Objectives To develop prognostic models for risk of a breakthrough seizure, risk of seizure recurrence after a breakthrough seizure, and likelihood of achieving 12-month remission following a breakthrough seizure. A breakthrough seizure is one that occurs following at least 12 months remission whilst on treatment. Methods We analysed data from the SANAD study. This long-term randomised trial compared treatments for participants with newly diagnosed epilepsy. Multivariable Cox models investigated how clinical factors affect the probability of each outcome. Best fitting multivariable models were produced with variable reduction by Akaike’s Information Criterion. Risks associated with combinations of risk factors were calculated from each multivariable model. Results Significant factors in the multivariable model for risk of a breakthrough seizure following 12-month remission were number of tonic-clonic seizures by achievement of 12-month remission, time taken to achieve 12-month remission, and neurological insult. Significant factors in the model for risk of seizure recurrence following a breakthrough seizure were total number of drugs attempted to achieve 12-month remission, time to achieve 12-month remission prior to breakthrough seizure, and breakthrough seizure treatment decision. Significant factors in the model for likelihood of achieving 12-month remission after a breakthrough seizure were gender, age at breakthrough seizure, time to achieve 12-month remission prior to breakthrough, and breakthrough seizure treatment decision. Conclusions This is the first analysis to consider risk of a breakthrough seizure and subsequent outcomes. The described models can be used to identify people most likely to have a breakthrough seizure, a seizure recurrence following a breakthrough seizure, and to achieve 12-month remission following a breakthrough seizure. The results suggest that focussing on achieving 12-month remission swiftly represents the best therapeutic aim to reduce the risk of a breakthrough seizure and subsequent negative outcomes. This will aid individual patient risk stratification and the design of future epilepsy trials. PMID:29267375

Predicting Time to Hospital Discharge for Extremely Preterm Infants

PubMed Central

Hintz, Susan R.; Bann, Carla M.; Ambalavanan, Namasivayam; Cotten, C. Michael; Das, Abhik; Higgins, Rosemary D.

2010-01-01

As extremely preterm infant mortality rates have decreased, concerns regarding resource utilization have intensified. Accurate models to predict time to hospital discharge could aid in resource planning, family counseling, and perhaps stimulate quality improvement initiatives. Objectives For infants <27 weeks estimated gestational age (EGA), to develop, validate and compare several models to predict time to hospital discharge based on time-dependent covariates, and based on the presence of 5 key risk factors as predictors. Patients and Methods This was a retrospective analysis of infants <27 weeks EGA, born 7/2002-12/2005 and surviving to discharge from a NICHD Neonatal Research Network site. Time to discharge was modeled as continuous (postmenstrual age at discharge, PMAD), and categorical variables (“Early” and “Late” discharge). Three linear and logistic regression models with time-dependent covariate inclusion were developed (perinatal factors only, perinatal+early neonatal factors, perinatal+early+later factors). Models for Early and Late discharge using the cumulative presence of 5 key risk factors as predictors were also evaluated. Predictive capabilities were compared using coefficient of determination (R2) for linear models, and AUC of ROC curve for logistic models. Results Data from 2254 infants were included. Prediction of PMAD was poor, with only 38% of variation explained by linear models. However, models incorporating later clinical characteristics were more accurate in predicting “Early” or “Late” discharge (full models: AUC 0.76-0.83 vs. perinatal factor models: AUC 0.56-0.69). In simplified key risk factors models, predicted probabilities for Early and Late discharge compared favorably with observed rates. Furthermore, the AUC (0.75-0.77) were similar to those of models including the full factor set. Conclusions Prediction of Early or Late discharge is poor if only perinatal factors are considered, but improves substantially with knowledge of later-occurring morbidities. Prediction using a few key risk factors is comparable to full models, and may offer a clinically applicable strategy. PMID:20008430

Alcohol and cigarette use among Warsaw adolescents: Factors associated with risk and resilience

PubMed Central

Pisarska, Agnieszka; Eisman, Andria; Ostaszewski, Krzysztof; Zimmerman, Marc A.

2016-01-01

Background Youth in Poland are at notable risk for substance use. Guided by resiliency theory, we examine if developmental risk and promotive factors are associated with substance abuse risk. Objectives We examined the association between adolescent cigarette and alcohol use and related risk and promotive factors including maternal support, neighbours’ informal social control, friends’ acceptance of substance use, and alcohol and cigarette use by nonparental adults. Method Data were collected from a random sample of 13–14-year old students attending Warsaw middle schools (N=3029). We used hierarchical regression models and examined compensatory and protective models of resilience, controlling for sociodemograhic factors. Results Our results indicated that friends’ acceptance of substance use and perceived drug use among nonparental adults was associated with increased risk cigarette and alcohol use among youth. We found that maternal support moderated the relationship between friends’ acceptance of substance use and cigarette use (protective model of resilience). Thus, maternal support buffered the negative effects of friends’ acceptance of use on youths’ cigarette use. Neighbor’s informal social control and maternal support were associated with reduced risk of alcohol use (compensatory model of resilience). Conclusion Collectively, results of the study support compensatory and protective models of resilience in a large representative sample of Warsaw adolescents. PMID:27223142

Method for assessing coal-floor water-inrush risk based on the variable-weight model and unascertained measure theory

NASA Astrophysics Data System (ADS)

Wu, Qiang; Zhao, Dekang; Wang, Yang; Shen, Jianjun; Mu, Wenping; Liu, Honglei

2017-11-01

Water inrush from coal-seam floors greatly threatens mining safety in North China and is a complex process controlled by multiple factors. This study presents a mathematical assessment system for coal-floor water-inrush risk based on the variable-weight model (VWM) and unascertained measure theory (UMT). In contrast to the traditional constant-weight model (CWM), which assigns a fixed weight to each factor, the VWM varies with the factor-state value. The UMT employs the confidence principle, which is more effective in ordered partition problems than the maximum membership principle adopted in the former mathematical theory. The method is applied to the Datang Tashan Coal Mine in North China. First, eight main controlling factors are selected to construct the comprehensive evaluation index system. Subsequently, an incentive-penalty variable-weight model is built to calculate the variable weights of each factor. Then, the VWM-UMT model is established using the quantitative risk-grade divide of each factor according to the UMT. On this basis, the risk of coal-floor water inrush in Tashan Mine No. 8 is divided into five grades. For comparison, the CWM is also adopted for the risk assessment, and a differences distribution map is obtained between the two methods. Finally, the verification of water-inrush points indicates that the VWM-UMT model is powerful and more feasible and reasonable. The model has great potential and practical significance in future engineering applications.

Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Cancer.gov

These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.

Breast Cancer Risk Prediction and Mammography Biopsy Decisions

PubMed Central

Armstrong, Katrina; Handorf, Elizabeth A.; Chen, Jinbo; Demeter, Mirar N. Bristol

2012-01-01

Background Controversy continues about screening mammography, in part because of the risk of false-negative and false-positive mammograms. Pre-test breast cancer risk factors may improve the positive and negative predictive value of screening. Purpose To create a model that estimates the potential impact of pre-test risk prediction using clinical and genomic information on the reclassification of women with abnormal mammograms (BI-RADS3 and BI-RADS4 [Breast Imaging-Reporting and Data System]) above and below the threshold for breast biopsy. Methods The current study modeled 1-year breast cancer risk in women with abnormal screening mammograms using existing data on breast cancer risk factors, 12 validated breast cancer single nucleotide polymorphisms (SNPs), and probability of cancer given the BI-RADS category. Examination was made of reclassification of women above and below biopsy thresholds of 1%, 2%, and 3% risk. The Breast Cancer Surveillance Consortium data were collected from 1996 to 2002. Data analysis was conducted in 2010 and 2011. Results Using a biopsy risk threshold of 2% and the standard risk factor model, 5% of women with a BI-RADS3 mammogram had a risk above the threshold, and 3% of women with BIRADS4A mammograms had a risk below the threshold. The addition of 12 SNPs in the model resulted in 8% of women with a BI-RADS3 mammogram above the threshold for biopsy and 7% of women with BI-RADS4A mammograms below the threshold. Conclusions The incorporation of pre-test breast cancer risk factors could change biopsy decisions for a small proportion of women with abnormal mammograms. The greatest impact comes from standard breast cancer risk factors. PMID:23253645

Major psychological factors affecting acceptance of gene-recombination technology.

PubMed

Tanaka, Yutaka

2004-12-01

The purpose of this study was to verify the validity of a causal model that was made to predict the acceptance of gene-recombination technology. A structural equation model was used as a causal model. First of all, based on preceding studies, the factors of perceived risk, perceived benefit, and trust were set up as important psychological factors determining acceptance of gene-recombination technology in the structural equation model. An additional factor, "sense of bioethics," which I consider to be important for acceptance of biotechnology, was added to the model. Based on previous studies, trust was set up to have an indirect influence on the acceptance of gene-recombination technology through perceived risk and perceived benefit in the model. Participants were 231 undergraduate students in Japan who answered a questionnaire with a 5-point bipolar scale. The results indicated that the proposed model fits the data well, and showed that acceptance of gene-recombination technology is explained largely by four factors, that is, perceived risk, perceived benefit, trust, and sense of bioethics, whether the technology is applied to plants, animals, or human beings. However, the relative importance of the four factors was found to vary depending on whether the gene-recombination technology was applied to plants, animals, or human beings. Specifically, the factor of sense of bioethics is the most important factor in acceptance of plant gene-recombination technology and animal gene-recombination technology, and the factors of trust and perceived risk are the most important factors in acceptance of human being gene-recombination technology.

Lifetime risks for aneurysmal subarachnoid haemorrhage: multivariable risk stratification.

PubMed

Vlak, Monique H M; Rinkel, Gabriel J E; Greebe, Paut; Greving, Jacoba P; Algra, Ale

2013-06-01

The overall incidence of aneurysmal subarachnoid haemorrhage (aSAH) in western populations is around 9 per 100 000 person-years, which confers to a lifetime risk of around half per cent. Risk factors for aSAH are usually expressed as relative risks and suggest that absolute risks vary considerably according to risk factor profiles, but such estimates are lacking. We aimed to estimate incidence and lifetime risks of aSAH according to risk factor profiles. We used data from 250 patients admitted with aSAH and 574 sex-matched and age-matched controls, who were randomly retrieved from general practitioners files. We determined independent prognostic factors with multivariable logistic regression analyses and assessed discriminatory performance using the area under the receiver operating characteristic curve. Based on the prognostic model we predicted incidences and lifetime risks of aSAH for different risk factor profiles. The four strongest independent predictors for aSAH, namely current smoking (OR 6.0; 95% CI 4.1 to 8.6), a positive family history for aSAH (4.0; 95% CI 2.3 to 7.0), hypertension (2.4; 95% CI 1.5 to 3.8) and hypercholesterolaemia (0.2; 95% CI 0.1 to 0.4), were used in the final prediction model. This model had an area under the receiver operating characteristic curve of 0.73 (95% CI 0.69 to 0.76). Depending on sex, age and the four predictors, the incidence of aSAH ranged from 0.4/100 000 to 298/100 000 person-years and lifetime risk between 0.02% and 7.2%. The incidence and lifetime risk of aSAH in the general population varies widely according to risk factor profiles. Whether persons with high risks benefit from screening should be assessed in cost-effectiveness studies.

Stress and anger as contextual factors and preexisting cognitive schemas: predicting parental child maltreatment risk.

PubMed

Rodriguez, Christina M; Richardson, Michael J

2007-11-01

Progress in the child maltreatment field depends on refinements in leading models. This study examines aspects of social information processing theory (Milner, 2000) in predicting physical maltreatment risk in a community sample. Consistent with this theory, selected preexisting schema (external locus-of-control orientation, inappropriate developmental expectations, low empathic perspective-taking ability, and low perceived attachment relationship to child) were expected to predict child abuse risk beyond contextual factors (parenting stress and anger expression). Based on 115 parents' self-report, results from this study support cognitive factors that predict abuse risk (with locus of control, perceived attachment, or empathy predicting different abuse risk measures, but not developmental expectations), although the broad contextual factors involving negative affectivity and stress were consistent predictors across abuse risk markers. Findings are discussed with regard to implications for future model evaluations, with indications the model may apply to other forms of maltreatment, such as psychological maltreatment or neglect.

Predictors of non-vertebral fracture in older Chinese males and females: Mr. OS and Ms. OS (Hong Kong).

PubMed

Kwok, Timothy Chi Yui; Su, Yi; Khoo, Chyi Chyi; Leung, Jason; Kwok, Anthony; Orwoll, Eric; Woo, Jean; Leung, Ping Chung

2017-05-01

Clinical risk factors to predict fracture are useful in guiding management of patients with osteoporosis or falls. Clinical predictors may however be population specific because of differences in lifestyle, environment and ethnicity. Four thousand community-dwelling Chinese males and females with average ages of 72.4 and 72.6 years were followed up for incident fractures, with an average of 6.5 and 8.8 years, respectively. Clinical information was collected, and bone mineral density (BMD) measurements were carried out at baseline. Stepwise Cox regression models were used to identify risk factors of nonvertebral fractures, with BMD as covariate. Areas under the receiver-operating characteristic (ROC) curve (AUC) were compared among different risk models. The incidence rates of nonvertebral fractures were 10.3 and 20.5 per 1000 person years in males and females, respectively. In males, age ≥80, history of a fall in the past year, fracture history, chronic obstructive pulmonary disease, impaired visual depth perception and low physical health-related quality of life were significant fracture risk factors, independent of BMD. In females, the significant factors were fracture history, low visual acuity and slow narrow walking speed. The clinical risk factors had a significant influence on fracture risk irrespective of osteoporosis status, even having a better risk discrimination than BMD alone, especially in males. The best risk prediction model consisted both BMD and clinical risk factors. Clinical risk factors have additive value to hip BMD in predicting nonvertebral fractures in older Chinese people and may predict them better than BMD alone in older Chinese males.

Depressive symptoms and inflammation are independent risk factors of fatigue in breast cancer survivors.

PubMed

Xiao, C; Miller, A H; Felger, J; Mister, D; Liu, T; Torres, M A

2017-07-01

Psychosocial and inflammatory factors have been associated with fatigue in breast cancer survivors. Nevertheless, the relative contribution and/or interaction of these factors with cancer-related fatigue have not been well documented. This cross-sectional study enrolled 111 stage 0-III breast cancer patients treated with breast surgery followed by whole breast radiotherapy. Fatigue was measured by the total score of the Multidimensional Fatigue Inventory-20. Potential risk factors included inflammatory markers (plasma cytokines and their receptors and C-reactive protein; CRP), depressive symptoms (as assessed by the Inventory of Depressive Symptomatology-Self Reported), sleep (as assessed by the Pittsburgh Sleep Quality Index) and perceived stress (as assessed by the Perceived Stress Scale) as well as age, race, marital status, smoking history, menopause status, endocrine treatment, chemotherapy and cancer stage. Linear regression modeling was employed to examine risk factors of fatigue. Only risk factors with a significance level <0.10 were included in the initial regression model. A post-hoc mediation model using PROCESS SPSS was conducted to examine the association among depressive symptoms, sleep problems, stress, inflammation and fatigue. At 1 year post-radiotherapy, depressive symptoms (p<0.0001) and inflammatory markers (CRP: p = 0.015; interleukin-1 receptor antagonist: p = 0.014; soluble tumor necrosis factor receptor-2: p = 0.009 in separate models) were independent risk factors of fatigue. Mediation analysis showed that depressive symptoms also mediated the associations of fatigue with sleep and stress. Depressive symptoms and inflammation were independent risk factors for cancer-related fatigue at 1 year post-radiotherapy, and thus represent independent treatment targets for this debilitating symptom.

Risk of Mortality after Spinal Cord Injury: An 8-year Prospective Study

PubMed Central

Krause, James S.; Zhai, Yusheng; Saunders, Lee L.; Carter, Rickey E.

2011-01-01

Objective To evaluate a theoretical model for mortality after spinal cord injury (SCI) by sequentially analyzing 4 sets of risk factors in relation to mortality (i.e., adding 1 set of factors to the regression equation at a time). Design Prospective cohort study of data collected in late 1997 and early 1998 with mortality status ascertained in December 2005. We evaluated the significance of 4 successive sets of predictors (biographic and injury, psychologic and environmental, behavioral, health and secondary conditions) using Cox proportional hazards modeling and built a full model based on the optimal predictors. Setting A specialty hospital. Participants 1,386 adults with traumatic SCI, at least 1 year post-injury, participated. There were 224 deaths. After eliminating cases with missing data, there were 1,209 participants, with 179 deceased at follow-up. Interventions N/A. Main Outcome Measures Mortality status was determined using the National Death Index and the Social Security Death Index. Results The final model included one environmental variable (poverty), 2 behavioral factors (prescription medication use, binge drinking), and 4 health factors or secondary conditions (hospitalizations, fractures/amputations, surgeries for pressure ulcers, probable major depression). Conclusions The results supported the major premise of the theoretical model that risk factors are more important the more proximal they are in a theoretical chain of events leading to mortality. According to this model, mortality results from declining health, precipitated by high-risk behaviors. These findings may be used to target individuals who are at high risk for early mortality as well as directing interventions to the particular risk factor. PMID:19801060

Depression and Anxiety Symptoms in Mothers of Newborns Hospitalized on the Neonatal Intensive Care Unit

PubMed Central

Segre, Lisa S.; McCabe, Jennifer E.; Chuffo-Siewert, Rebecca; O’Hara, Michael W.

2014-01-01

Background Mothers of infants hospitalized in the neonatal intensive care unit (NICU) are at risk for clinically significant levels of depression and anxiety symptoms; however, the maternal/infant characteristics that predict risk have been difficult to determine. Previous studies have conceptualized depression and anxiety symptoms separately, ignoring their comorbidity. Moreover, risk factors for these symptoms have not been assessed together in one study sample. Objectives The primary aim of this study was to determine whether a diagnostic classification approach or a common-factor model better explained the pattern of symptoms reported by NICU mothers, including depression, generalized anxiety, panic, and trauma. A secondary aim was to assess risk factors of aversive emotional states in NICU mothers based on the supported conceptual model. Method In this cross-sectional study, a nonprobability convenience sample of 200 NICU mothers completed questionnaires assessing maternal demographic and infant health characteristics, as well as maternal depression and anxiety symptoms. Structural equation modeling was used to test a diagnostic classification model, and a common-factor model of aversive emotional states and the risk factors of aversive emotional states in mothers in the NICU. Results Maximum likelihood estimates indicated that examining symptoms of depression and anxiety disorders as separate diagnostic classifications did not fit the data well, whereas examining the common factor of negative emotionality rendered an adequate fit to the data, and identified a history of depression, infant illness, and infant prematurity as significant risk factors. Discussion This study supports a multidimensional view of depression, and should guide both clinical practice and future research with NICU mothers. PMID:25171558

An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study

PubMed Central

Laws, Rachel A; Kemp, Lynn A; Harris, Mark F; Davies, Gawaine Powell; Williams, Anna M; Eames-Brown, Rosslyn

2009-01-01

Background Despite the effectiveness of brief lifestyle intervention delivered in primary healthcare (PHC), implementation in routine practice remains suboptimal. Beliefs and attitudes have been shown to be associated with risk factor management practices, but little is known about the process by which clinicians' perceptions shape implementation. This study aims to describe a theoretical model to understand how clinicians' perceptions shape the implementation of lifestyle risk factor management in routine practice. The implications of the model for enhancing practices will also be discussed. Methods The study analysed data collected as part of a larger feasibility project of risk factor management in three community health teams in New South Wales (NSW), Australia. This included journal notes kept through the implementation of the project, and interviews with 48 participants comprising 23 clinicians (including community nurses, allied health practitioners and an Aboriginal health worker), five managers, and two project officers. Data were analysed using grounded theory principles of open, focused, and theoretical coding and constant comparative techniques to construct a model grounded in the data. Results The model suggests that implementation reflects both clinician beliefs about whether they should (commitment) and can (capacity) address lifestyle issues. Commitment represents the priority placed on risk factor management and reflects beliefs about role responsibility congruence, client receptiveness, and the likely impact of intervening. Clinician beliefs about their capacity for risk factor management reflect their views about self-efficacy, role support, and the fit between risk factor management ways of working. The model suggests that clinicians formulate different expectations and intentions about how they will intervene based on these beliefs about commitment and capacity and their philosophical views about appropriate ways to intervene. These expectations then provide a cognitive framework guiding their risk factor management practices. Finally, clinicians' appraisal of the overall benefits versus costs of addressing lifestyle issues acts to positively or negatively reinforce their commitment to implementing these practices. Conclusion The model extends previous research by outlining a process by which clinicians' perceptions shape implementation of lifestyle risk factor management in routine practice. This provides new insights to inform the development of effective strategies to improve such practices. PMID:19825189

Predicting Barrett's Esophagus in Families: An Esophagus Translational Research Network (BETRNet) Model Fitting Clinical Data to a Familial Paradigm.

PubMed

Sun, Xiangqing; Elston, Robert C; Barnholtz-Sloan, Jill S; Falk, Gary W; Grady, William M; Faulx, Ashley; Mittal, Sumeet K; Canto, Marcia; Shaheen, Nicholas J; Wang, Jean S; Iyer, Prasad G; Abrams, Julian A; Tian, Ye D; Willis, Joseph E; Guda, Kishore; Markowitz, Sanford D; Chandar, Apoorva; Warfe, James M; Brock, Wendy; Chak, Amitabh

2016-05-01

Barrett's esophagus is often asymptomatic and only a small portion of Barrett's esophagus patients are currently diagnosed and under surveillance. Therefore, it is important to develop risk prediction models to identify high-risk individuals with Barrett's esophagus. Familial aggregation of Barrett's esophagus and esophageal adenocarcinoma, and the increased risk of esophageal adenocarcinoma for individuals with a family history, raise the necessity of including genetic factors in the prediction model. Methods to determine risk prediction models using both risk covariates and ascertained family data are not well developed. We developed a Barrett's Esophagus Translational Research Network (BETRNet) risk prediction model from 787 singly ascertained Barrett's esophagus pedigrees and 92 multiplex Barrett's esophagus pedigrees, fitting a multivariate logistic model that incorporates family history and clinical risk factors. The eight risk factors, age, sex, education level, parental status, smoking, heartburn frequency, regurgitation frequency, and use of acid suppressant, were included in the model. The prediction accuracy was evaluated on the training dataset and an independent validation dataset of 643 multiplex Barrett's esophagus pedigrees. Our results indicate family information helps to predict Barrett's esophagus risk, and predicting in families improves both prediction calibration and discrimination accuracy. Our model can predict Barrett's esophagus risk for anyone with family members known to have, or not have, had Barrett's esophagus. It can predict risk for unrelated individuals without knowing any relatives' information. Our prediction model will shed light on effectively identifying high-risk individuals for Barrett's esophagus screening and surveillance, consequently allowing intervention at an early stage, and reducing mortality from esophageal adenocarcinoma. Cancer Epidemiol Biomarkers Prev; 25(5); 727-35. ©2016 AACR. ©2016 American Association for Cancer Research.

Can theory predict the process of suicide on entry to prison? Predicting dynamic risk factors for suicide ideation in a high-risk prison population.

PubMed

Slade, Karen; Edelman, Robert

2014-01-01

Each year approximately 110,000 people are imprisoned in England and Wales and new prisoners remain one of the highest risk groups for suicide across the world. The reduction of suicide in prisoners remains difficult as assessments and interventions tend to rely on static risk factors with few theoretical or integrated models yet evaluated. To identify the dynamic factors that contribute to suicide ideation in this population based on Williams and Pollock's (2001) Cry of Pain (CoP) model. New arrivals (N = 198) into prison were asked to complete measures derived from the CoP model plus clinical and prison-specific factors. It was hypothesized that the factors of the CoP model would be predictive of suicide ideation. Support was provided for the defeat and entrapment aspects of the CoP model with previous self-harm, repeated times in prison, and suicide-permissive cognitions also key in predicting suicide ideation for prisoners on entry to prison. An integrated and dynamic model was developed that has utility in predicting suicide in early-stage prisoners. Implications for both theory and practice are discussed along with recommendations for future research.

Children, computer exposure and musculoskeletal outcomes: the development of pathway models for school and home computer-related musculoskeletal outcomes.

PubMed

Harris, Courtenay; Straker, Leon; Pollock, Clare; Smith, Anne

2015-01-01

Children's computer use is rapidly growing, together with reports of related musculoskeletal outcomes. Models and theories of adult-related risk factors demonstrate multivariate risk factors associated with computer use. Children's use of computers is different from adult's computer use at work. This study developed and tested a child-specific model demonstrating multivariate relationships between musculoskeletal outcomes, computer exposure and child factors. Using pathway modelling, factors such as gender, age, television exposure, computer anxiety, sustained attention (flow), socio-economic status and somatic complaints (headache and stomach pain) were found to have effects on children's reports of musculoskeletal symptoms. The potential for children's computer exposure to follow a dose-response relationship was also evident. Developing a child-related model can assist in understanding risk factors for children's computer use and support the development of recommendations to encourage children to use this valuable resource in educational, recreational and communication environments in a safe and productive manner. Computer use is an important part of children's school and home life. Application of this developed model, that encapsulates related risk factors, enables practitioners, researchers, teachers and parents to develop strategies that assist young people to use information technology for school, home and leisure in a safe and productive manner.

Social ecological determinants of youth violence among ethnically diverse Asian and Pacific Islander students.

PubMed

Goebert, Deborah; Chang, Janice Y; Chung-Do, Jane; Else, 'Iwalani R N; Hamagami, Fumiaki; Helm, Susana; Kinkade, Katie; Sugimoto-Matsuda, Jeanelle J

2012-01-01

This study assesses the relative fit of risk/protective and social ecological models of youth violence among predominantly Asian and Pacific Islander students. Data from a 2007 survey of two multi-ethnic high schools in Hawai'i were used. The survey assessed interpersonal youth violence, suicidality and risk and protective factors. Two models of youth violence (risk/protective and social ecological) were tested using structural equation modeling. We found good fits for the risk/protective model (χ(2) = 369.42, df = 77, P < .0001; CFI = .580; RMSEA = .066) and the ecological model (χ(2) = 1763.65, df = 292, P < .0001; CFI = .636; RMSEA = .076). The risk/protective model showed the importance of coping skills. However, the ecological model allowed examination of the interconnectivity among factors. Peer exposure to violence had no direct influence on individuals and peer influence was fully mediated by school climate. Furthermore, family factors directly contributed to peer exposure, community, and individual risk/protection. These findings have significant implications for intervention and prevention efforts and for the promotion of positive, competent, and healthy youth development. While few family and school-based programs have been developed and evaluated for adolescents, they have the greatest potential for success.

Assessment of cardiovascular risk based on a data-driven knowledge discovery approach.

PubMed

Mendes, D; Paredes, S; Rocha, T; Carvalho, P; Henriques, J; Cabiddu, R; Morais, J

2015-01-01

The cardioRisk project addresses the development of personalized risk assessment tools for patients who have been admitted to the hospital with acute myocardial infarction. Although there are models available that assess the short-term risk of death/new events for such patients, these models were established in circumstances that do not take into account the present clinical interventions and, in some cases, the risk factors used by such models are not easily available in clinical practice. The integration of the existing risk tools (applied in the clinician's daily practice) with data-driven knowledge discovery mechanisms based on data routinely collected during hospitalizations, will be a breakthrough in overcoming some of these difficulties. In this context, the development of simple and interpretable models (based on recent datasets), unquestionably will facilitate and will introduce confidence in this integration process. In this work, a simple and interpretable model based on a real dataset is proposed. It consists of a decision tree model structure that uses a reduced set of six binary risk factors. The validation is performed using a recent dataset provided by the Portuguese Society of Cardiology (11113 patients), which originally comprised 77 risk factors. A sensitivity, specificity and accuracy of, respectively, 80.42%, 77.25% and 78.80% were achieved showing the effectiveness of the approach.

Drug development costs when financial risk is measured using the Fama-French three-factor model.

PubMed

Vernon, John A; Golec, Joseph H; Dimasi, Joseph A

2010-08-01

In a widely cited article, DiMasi, Hansen, and Grabowski (2003) estimate the average pre-tax cost of bringing a new molecular entity to market. Their base case estimate, excluding post-marketing studies, was $802 million (in $US 2000). Strikingly, almost half of this cost (or $399 million) is the cost of capital (COC) used to fund clinical development expenses to the point of FDA marketing approval. The authors used an 11% real COC computed using the capital asset pricing model (CAPM). But the CAPM is a single factor risk model, and multi-factor risk models are the current state of the art in finance. Using the Fama-French three factor model we find that the cost of drug development to be higher than the earlier estimate. Copyright (c) 2009 John Wiley & Sons, Ltd.

Risk Factors in the Pediatric Ward Recognized by Students Before Pediatric Nursing Practice －Basic Data for Medical Safety Education Based on Student's Learning Readiness－.

PubMed

Hirowatari, Kanako; Nakamura, Emi

2016-09-01

The purpose of this study was to extract the risk factors recognized by students before pediatric nursing practice in order to conduct medical safety education based on student's learning readiness. Third-year nursing students of A nursing college used the P-mSHELL model to find the risk factors in a simulated pediatric hospital room, and the researchers analyzed the contents. The students recognized four categories of risk factors: "burden on the family", "characteristics of the infant", "characteristics of children with disease", and "the family's cognition and understanding". There were three categories of risk factors related to "the environment": "environment that can cause a dangerous action", "unsafe environment", and "sickroom as a living space". There were four categories of risk factors related to "the student": "students' own physical/mental condition", "anxiety caused by pediatric nursing practice", "learning process in nursing practice" and "students' understanding of pediatric nursing". The students recognized that there were various risk factors in the child, the family, and the environment, and, by the P-mSHELL model, they recognized that they themselves could become a risk factor. Based on the risk factors that students extracted, teachers should think about what kind of preparation is necessary for students in pediatric nursing practice, and it is important to conduct medical safety education.

Developing a suitable model for supplier selection based on supply chain risks: an empirical study from Iranian pharmaceutical companies.

PubMed

Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

2012-01-01

The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts' opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry.

Developing a Suitable Model for Supplier Selection Based on Supply Chain Risks: An Empirical Study from Iranian Pharmaceutical Companies

PubMed Central

Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

2012-01-01

The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts’ opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry. PMID:24250442

A model to predict the risk of lethal nasopharyngeal necrosis after re-irradiation with intensity-modulated radiotherapy in nasopharyngeal carcinoma patients.

PubMed

Yu, Ya-Hui; Xia, Wei-Xiong; Shi, Jun-Li; Ma, Wen-Juan; Li, Yong; Ye, Yan-Fang; Liang, Hu; Ke, Liang-Ru; Lv, Xing; Yang, Jing; Xiang, Yan-Qun; Guo, Xiang

2016-06-29

For patients with nasopharyngeal carcinoma (NPC) who undergo re-irradiation with intensity-modulated radiotherapy (IMRT), lethal nasopharyngeal necrosis (LNN) is a severe late adverse event. The purpose of this study was to identify risk factors for LNN and develop a model to predict LNN after radical re-irradiation with IMRT in patients with recurrent NPC. Patients who underwent radical re-irradiation with IMRT for locally recurrent NPC between March 2001 and December 2011 and who had no evidence of distant metastasis were included in this study. Clinical characteristics, including recurrent carcinoma conditions and dosimetric features, were evaluated as candidate risk factors for LNN. Logistic regression analysis was used to identify independent risk factors and construct the predictive scoring model. Among 228 patients enrolled in this study, 204 were at risk of developing LNN based on risk analysis. Of the 204 patients treated, 31 (15.2%) developed LNN. Logistic regression analysis showed that female sex (P = 0.008), necrosis before re-irradiation (P = 0.008), accumulated total prescription dose to the gross tumor volume (GTV) ≥145.5 Gy (P = 0.043), and recurrent tumor volume ≥25.38 cm(3) (P = 0.009) were independent risk factors for LNN. A model to predict LNN was then constructed that included these four independent risk factors. A model that includes sex, necrosis before re-irradiation, accumulated total prescription dose to GTV, and recurrent tumor volume can effectively predict the risk of developing LNN in NPC patients who undergo radical re-irradiation with IMRT.

Interrelationship of Cytokines, Hypothalamic-Pituitary-Adrenal Axis Hormones, and Psychosocial Variables in the Prediction of Preterm Birth

PubMed Central

Pearce, B.D.; Grove, J.; Bonney, E.A.; Bliwise, N.; Dudley, D.J.; Schendel, D.E.; Thorsen, P.

2010-01-01

Background/Aims To examine the relationship of biological mediators (cytokines, stress hormones), psychosocial, obstetric history, and demographic factors in the early prediction of preterm birth (PTB) using a comprehensive logistic regression model incorporating diverse risk factors. Methods In this prospective case-control study, maternal serum biomarkers were quantified at 9–23 weeks’ gestation in 60 women delivering at <37 weeks compared to 123 women delivering at term. Biomarker data were combined with maternal sociodemographic factors and stress data into regression models encompassing 22 preterm risk factors and 1st-order interactions. Results Among individual biomarkers, we found that macrophage migration inhibitory factor (MIF), interleukin-10, C-reactive protein (CRP), and tumor necrosis factor-α were statistically significant predictors of PTB at all cutoff levels tested (75th, 85th, and 90th percentiles). We fit multifactor models for PTB prediction at each biomarker cutoff. Our best models revealed that MIF, CRP, risk-taking behavior, and low educational attainment were consistent predictors of PTB at all biomarker cutoffs. The 75th percentile cutoff yielded the best predicting model with an area under the ROC curve of 0.808 (95% CI 0.743–0.874). Conclusion Our comprehensive models highlight the prominence of behavioral risk factors for PTB and point to MIF as a possible psychobiological mediator. PMID:20160447

Interrelationship of cytokines, hypothalamic-pituitary-adrenal axis hormones, and psychosocial variables in the prediction of preterm birth.

PubMed

Pearce, B D; Grove, J; Bonney, E A; Bliwise, N; Dudley, D J; Schendel, D E; Thorsen, P

2010-01-01

To examine the relationship of biological mediators (cytokines, stress hormones), psychosocial, obstetric history, and demographic factors in the early prediction of preterm birth (PTB) using a comprehensive logistic regression model incorporating diverse risk factors. In this prospective case-control study, maternal serum biomarkers were quantified at 9-23 weeks' gestation in 60 women delivering at <37 weeks compared to 123 women delivering at term. Biomarker data were combined with maternal sociodemographic factors and stress data into regression models encompassing 22 preterm risk factors and 1st-order interactions. Among individual biomarkers, we found that macrophage migration inhibitory factor (MIF), interleukin-10, C-reactive protein (CRP), and tumor necrosis factor-alpha were statistically significant predictors of PTB at all cutoff levels tested (75th, 85th, and 90th percentiles). We fit multifactor models for PTB prediction at each biomarker cutoff. Our best models revealed that MIF, CRP, risk-taking behavior, and low educational attainment were consistent predictors of PTB at all biomarker cutoffs. The 75th percentile cutoff yielded the best predicting model with an area under the ROC curve of 0.808 (95% CI 0.743-0.874). Our comprehensive models highlight the prominence of behavioral risk factors for PTB and point to MIF as a possible psychobiological mediator. Copyright (c) 2010 S. Karger AG, Basel.

Cumulative risk effects for the development of behaviour difficulties in children and adolescents with special educational needs and disabilities.

PubMed

Oldfield, Jeremy; Humphrey, Neil; Hebron, Judith

2015-01-01

Research has identified multiple risk factors for the development of behaviour difficulties. What have been less explored are the cumulative effects of exposure to multiple risks on behavioural outcomes, with no study specifically investigating these effects within a population of young people with special educational needs and disabilities (SEND). Furthermore, it is unclear whether a threshold or linear risk model better fits the data for this population. The sample included 2660 children and 1628 adolescents with SEND. Risk factors associated with increases in behaviour difficulties over an 18-month period were summed to create a cumulative risk score, with this explanatory variable being added into a multi-level model. A quadratic term was then added to test the threshold model. There was evidence of a cumulative risk effect, suggesting that exposure to higher numbers of risk factors, regardless of their exact nature, resulted in increased behaviour difficulties. The relationship between risk and behaviour difficulties was non-linear, with exposure to increasing risk having a disproportionate and detrimental impact on behaviour difficulties in child and adolescent models. Interventions aimed at reducing behaviour difficulties need to consider the impact of multiple risk variables. Tailoring interventions towards those exposed to large numbers of risks would be advantageous. Copyright © 2015 Elsevier Ltd. All rights reserved.

Data Sources for the Model-based Small Area Estimates of Cancer-Related Knowledge - Small Area Estimates

Cancer.gov

The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).

The Relationship Between the Genetic and Environmental Influences on Common Externalizing Psychopathology and Mental Wellbeing

PubMed Central

Kendler, Kenneth S.; Myers, John M.; Keyes, Corey L. M.

2012-01-01

To determine the relationship between the genetic and environmental risk factors for externalizing psychopathology and mental wellbeing, we examined detailed measures of emotional, social and psychological wellbeing, and a history of alcohol-related problems and smoking behavior in the last year in 1,386 individual twins from same-sex pairs from the MIDUS national US sample assessed in 1995. Cholesky decomposition analyses were performed with the Mx program. The best fit model contained one highly heritable common externalizing psychopathology factor for both substance use/abuse measures, and one strongly heritable common factor for the three wellbeing measures. Genetic and environmental risk factors for externalizing psychopathology were both negatively associated with levels of mental wellbeing and accounted for, respectively, 7% and 21% of its genetic and environmental influences. Adding internalizing psychopathology assessed in the last year to the model, genetic risk factors unique for externalizing psychopathology were now positively related to levels of mental wellbeing, although accounting for only 5% of the genetic variance. Environmental risk factors unique to externalizing psychopathology continued to be negatively associated with mental wellbeing, accounting for 26% of the environmental variance. When both internalizing psychopathology and externalizing psychopathology are associated with mental wellbeing, the strongest risk factors for low mental wellbeing are genetic factors that impact on both internalizing psychopathology and externalizing psychopathology, and environmental factors unique to externalizing psychopathology. In this model, genetic risk factors for externalizing psychopathology predict, albeit weakly, higher levels of mental wellbeing. PMID:22506307

Explaining the Cardiovascular Risk Associated with Rheumatoid Arthritis: Traditional Risk Factors Versus Markers of Rheumatoid Arthritis Severity

PubMed Central

Solomon, Daniel H.; Kremer, Joel; Curtis, Jeffrey R; Hochberg, Marc C.; Reed, George; Tsao, Peter; Farkouh, Michael E.; Setoguchi, Soko; Greenberg, Jeffrey D.

2010-01-01

Background Cardiovascular (CV) disease has a major impact on patients with rheumatoid arthritis (RA), however, the relative contributions of traditional CV risk factors and markers of RA severity are unclear. We examined the relative importance of traditional CV risk factors and RA markers in predicting CV events. Methods A prospective longitudinal cohort study was conducted in the setting of the CORRONA registry in the United States. Baseline data from subjects with RA enrolled in the CORRONA registry were examined to determine predictors of CV outcomes, including myocardial infarction (MI), stroke or transient ischemic attack (TIA). Possible predictors were of two types: traditional CV risk factors and markers of RA severity. The discriminatory value of these variables was assessed by calculating the area under the receiver operating characteristic curve (c-statistic) in logistic regression. We then assessed the incidence rate for CV events among subjects with an increasing number of traditional CV risk factors and/or RA severity markers. Results The cohort consisted of 10,156 patients with RA followed for a median of 22 months. We observed 76 primary CV events during follow-up for a composite event rate of 3.98 (95% CI 3.08 – 4.88) per 1,000 patient-years. The c-statistic improved from 0.57 for models with only CV risk factors to 0.67 for models with CV risk factors plus age and gender. The c-statistic improved further to 0.71 when markers of RA severity were also added. The incidence rate for CV events was 0 (95% CI 0 – 5.98) for persons without any CV risk factors or markers of RA severity, while in the group with two or more CV risk factors and 3 or more markers of RA severity the incidence was 7.47 (95% CI 4.21–10.73) per 1,000 person-years. Conclusions Traditional CV risk factors and markers of RA severity both contribute to models predicting CV events. Increasing numbers of both types of factors are associated with greater risk. PMID:20444756

Model Checking of a Diabetes-Cancer Model

NASA Astrophysics Data System (ADS)

Gong, Haijun; Zuliani, Paolo; Clarke, Edmund M.

2011-06-01

Accumulating evidence suggests that cancer incidence might be associated with diabetes mellitus, especially Type II diabetes which is characterized by hyperinsulinaemia, hyperglycaemia, obesity, and overexpression of multiple WNT pathway components. These diabetes risk factors can activate a number of signaling pathways that are important in the development of different cancers. To systematically understand the signaling components that link diabetes and cancer risk, we have constructed a single-cell, Boolean network model by integrating the signaling pathways that are influenced by these risk factors to study insulin resistance, cancer cell proliferation and apoptosis. Then, we introduce and apply the Symbolic Model Verifier (SMV), a formal verification tool, to qualitatively study some temporal logic properties of our diabetes-cancer model. The verification results show that the diabetes risk factors might not increase cancer risk in normal cells, but they will promote cell proliferation if the cell is in a precancerous or cancerous stage characterized by losses of the tumor-suppressor proteins ARF and INK4a.

Obesity is associated with fatal coronary heart disease independently of traditional risk factors and deprivation.

PubMed

Logue, Jennifer; Murray, Heather M; Welsh, Paul; Shepherd, James; Packard, Chris; Macfarlane, Peter; Cobbe, Stuart; Ford, Ian; Sattar, Naveed

2011-04-01

The effect of body mass index (BMI) on coronary heart disease (CHD) risk is attenuated when mediators of this risk (such as diabetes, hypertension and hyperlipidaemia) are accounted for. However, there is now evidence of a differential effect of risk factors on fatal and non-fatal CHD events, with markers of inflammation more strongly associated with fatal than non-fatal events. To describe the association with BMI separately for both fatal and non-fatal CHD risk after accounting for classical risk factors and to assess any independent effects of obesity on CHD risk. In the West of Scotland Coronary Prevention Study BMI in 6082 men (mean age 55 years) with hypercholesterolaemia, but no history of diabetes or CVD, was related to the risk of fatal and non-fatal CHD events. After excluding participants with any event in the first 2 years, 1027 non-fatal and 214 fatal CHD events occurred during 14.7 years of follow-up. A minimally adjusted model (age, sex, statin treatment) and a maximally adjusted model (including known CVD risk factors and deprivation) were compared, with BMI 25-27.4 kg/m² as referent. The risk of non-fatal events was similar across all BMI categories in both models. The risk of fatal CHD events was increased in men with BMI 30.0-39.9 kg/m² in both the minimally adjusted model (HR = 1.75 (95% CI 1.12 to 2.74)) and the maximally adjusted model (HR = 1.60 (95% CI 1.02 to 2.53)). These hypothesis generating data suggest that obesity is associated with fatal, but not non-fatal, CHD after accounting for known cardiovascular risk factors and deprivation. Clinical trial registration WOSCOPS was carried out and completed before the requirement for clinical trial registration.

Socio-Ecological Risk Factors for Prime-Age Adult Death in Two Coastal Areas of Vietnam

PubMed Central

Kim, Deok Ryun; Ali, Mohammad; Thiem, Vu Dinh; Wierzba, Thomas F.

2014-01-01

Background Hierarchical spatial models enable the geographic and ecological analysis of health data thereby providing useful information for designing effective health interventions. In this study, we used a Bayesian hierarchical spatial model to evaluate mortality data in Vietnam. The model enabled identification of socio-ecological risk factors and generation of risk maps to better understand the causes and geographic implications of prime-age (15 to less than 45 years) adult death. Methods and Findings The study was conducted in two sites: Nha Trang and Hue in Vietnam. The study areas were split into 500×500 meter cells to define neighborhoods. We first extracted socio-demographic data from population databases of the two sites, and then aggregated the data by neighborhood. We used spatial hierarchical model that borrows strength from neighbors for evaluating risk factors and for creating spatially smoothed risk map after adjusting for neighborhood level covariates. The Markov chain Monte Carlo procedure was used to estimate the parameters. Male mortality was more than twice the female mortality. The rates also varied by age and sex. The most frequent cause of mortality was traffic accidents and drowning for men and traffic accidents and suicide for women. Lower education of household heads in the neighborhood was an important risk factor for increased mortality. The mortality was highly variable in space and the socio-ecological risk factors are sensitive to study site and sex. Conclusion Our study suggests that lower education of the household head is an important predictor for prime age adult mortality. Variability in socio-ecological risk factors and in risk areas by sex make it challenging to design appropriate intervention strategies aimed at decreasing prime-age adult deaths in Vietnam. PMID:24587031

Socio-ecological risk factors for prime-age adult death in two coastal areas of Vietnam.

PubMed

Kim, Deok Ryun; Ali, Mohammad; Thiem, Vu Dinh; Wierzba, Thomas F

2014-01-01

Hierarchical spatial models enable the geographic and ecological analysis of health data thereby providing useful information for designing effective health interventions. In this study, we used a Bayesian hierarchical spatial model to evaluate mortality data in Vietnam. The model enabled identification of socio-ecological risk factors and generation of risk maps to better understand the causes and geographic implications of prime-age (15 to less than 45 years) adult death. The study was conducted in two sites: Nha Trang and Hue in Vietnam. The study areas were split into 500×500 meter cells to define neighborhoods. We first extracted socio-demographic data from population databases of the two sites, and then aggregated the data by neighborhood. We used spatial hierarchical model that borrows strength from neighbors for evaluating risk factors and for creating spatially smoothed risk map after adjusting for neighborhood level covariates. The Markov chain Monte Carlo procedure was used to estimate the parameters. Male mortality was more than twice the female mortality. The rates also varied by age and sex. The most frequent cause of mortality was traffic accidents and drowning for men and traffic accidents and suicide for women. Lower education of household heads in the neighborhood was an important risk factor for increased mortality. The mortality was highly variable in space and the socio-ecological risk factors are sensitive to study site and sex. Our study suggests that lower education of the household head is an important predictor for prime age adult mortality. Variability in socio-ecological risk factors and in risk areas by sex make it challenging to design appropriate intervention strategies aimed at decreasing prime-age adult deaths in Vietnam.

Predictors of medication nonadherence differ among black and white patients with heart failure.

PubMed

Dickson, Victoria Vaughan; Knafl, George J; Riegel, Barbara

2015-08-01

Heart failure (HF) is a global public health problem, and outcomes remain poor, especially among ethnic minority populations. Medication adherence can improve heart failure outcomes but is notoriously low. The purpose of this secondary analysis of data from a prospective cohort comparison study of adults with heart failure was to explore differences in predictors of medication nonadherence by racial group (Black vs. White) in 212 adults with heart failure. Adaptive modeling analytic methods were used to model HF patient medication nonadherence separately for Black (31.7%) and White (68.3%) participants in order to investigate differences between these two racial groups. Of the 63 Black participants, 33.3% had low medication adherence, compared to 27.5% of the 149 White participants. Among Blacks, 16 risk factors were related to adherence in bivariate analyses; four of these (more comorbidities, lower serum sodium, higher systolic blood pressure, and use of fewer activities compensating for forgetfulness) jointly predicted nonadherence. In the multiple risk factor model, the number of risk factors in Black patients ranged from 0 to 4, and 76.2% had at least one risk factor. The estimated odds ratio for medication nonadherence was increased 9.34 times with each additional risk factor. Among White participants, five risk factors were related to adherence in bivariate analyses; one of these (older age) explained the individual effects of the other four. Because Blacks with HF have different and more risk factors than Whites for low medication adherence, interventions are needed that address unique risk factors among Black patients with HF. © 2015 Wiley Periodicals, Inc.

Optimizing Surgical Quality Datasets to Care for Older Adults: Lessons from the American College of Surgeons NSQIP Geriatric Surgery Pilot.

PubMed

Berian, Julia R; Zhou, Lynn; Hornor, Melissa A; Russell, Marcia M; Cohen, Mark E; Finlayson, Emily; Ko, Clifford Y; Robinson, Thomas N; Rosenthal, Ronnie A

2017-12-01

Surgical quality datasets can be better tailored toward older adults. The American College of Surgeons (ACS) NSQIP Geriatric Surgery Pilot collected risk factors and outcomes in 4 geriatric-specific domains: cognition, decision-making, function, and mobility. This study evaluated the contributions of geriatric-specific factors to risk adjustment in modeling 30-day outcomes and geriatric-specific outcomes (postoperative delirium, new mobility aid use, functional decline, and pressure ulcers). Using ACS NSQIP Geriatric Surgery Pilot data (January 2014 to December 2016), 7 geriatric-specific risk factors were evaluated for selection in 14 logistic models (morbidities/mortality) in general-vascular and orthopaedic surgery subgroups. Hierarchical models evaluated 4 geriatric-specific outcomes, adjusting for hospitals-level effects and including Bayesian-type shrinkage, to estimate hospital performance. There were 36,399 older adults who underwent operations at 31 hospitals in the ACS NSQIP Geriatric Surgery Pilot. Geriatric-specific risk factors were selected in 10 of 14 models in both general-vascular and orthopaedic surgery subgroups. After risk adjustment, surrogate consent (odds ratio [OR] 1.5; 95% CI 1.3 to 1.8) and use of a mobility aid (OR 1.3; 95% CI 1.1 to 1.4) increased the risk for serious morbidity or mortality in the general-vascular cohort. Geriatric-specific factors were selected in all 4 geriatric-specific outcomes models. Rates of geriatric-specific outcomes were: postoperative delirium in 12.1% (n = 3,650), functional decline in 42.9% (n = 13,000), new mobility aid in 29.7% (n = 9,257), and new or worsened pressure ulcers in 1.7% (n = 527). Geriatric-specific risk factors are important for patient-centered care and contribute to risk adjustment in modeling traditional and geriatric-specific outcomes. To provide optimal patient care for older adults, surgical datasets should collect measures that address cognition, decision-making, mobility, and function. Copyright © 2017 American College of Surgeons. All rights reserved.

Multiple, but not traditional risk factors predict mortality in older people: the Concord Health and Ageing in Men Project.

PubMed

Hirani, Vasant; Naganathan, Vasi; Blyth, Fiona; Le Couteur, David G; Gnjidic, Danijela; Stanaway, Fiona F; Seibel, Markus J; Waite, Louise M; Handelsman, David J; Cumming, Robert G

2014-01-01

This study aims to identify the common risk factors for mortality in community-dwelling older men. A prospective population-based study was conducted with a median of 6.7 years of follow-up. Participants included 1705 men aged ≥70 years at baseline (2005-2007) living in the community in Sydney, Australia. Demographic information, lifestyle factors, health status, self-reported history of diseases, physical performance measures, blood pressure, height and weight, disability (activities of daily living (ADL) and instrumental ADLs, instrumental ADLs (IADLs)), cognitive status, depressive symptoms and blood analyte measures were considered. Cox regression analyses were conducted to model predictors delete time until of mortality. During follow-up, 461 men (27 %) died. Using Cox proportional hazards model, significant predictors of delete time to time to mortality included in the final model (p < 0.05) were older age, body mass index < 20 kg m(2), high white cell count, anaemia, low albumin, current smoking, history of cancer, history of myocardial infarction, history of congestive heart failure, depressive symptoms and ADL and IADL disability and impaired chair stands. We found that overweight and obesity and/or being a lifelong non-drinker of alcohol were protective against mortality. Compared to men with less than or equal to one risk factor, the hazard ratio in men with three risk factors was 2.5; with four risk factors, it was 4.0; with five risk factors, it was 4.9; and for six or more risk factors, it was 11.4, respectively. We have identified common risk factors that predict mortality that may be useful in making clinical decisions among older people living in the community. Our findings suggest that, in primary care, screening and management of multiple risk factors are important to consider for extending survival, rather than simply considering individual risk factors in isolation. Some of the "traditional" risk factors for mortality in a younger population, including high blood pressure, hypercholesterolaemia, overweight and obesity and diabetes, were not independent predictors of mortality in this population of older men.

Risk factors of suicide attempt among people with suicidal ideation in South Korea: a cross-sectional study.

PubMed

Choi, Soo Beom; Lee, Wanhyung; Yoon, Jin-Ha; Won, Jong-Uk; Kim, Deok Won

2017-06-15

Suicide is a serious public health concern worldwide, and the fourth leading cause of death in Korea. Few studies have focused on risk factors for suicide attempt among people with suicidal ideation. The aim of the present study was to investigate the risk factors and develop prediction models for suicide attempt among people with suicidal ideation in the Korean population. This study included 1567 men and 3726 women aged 20 years and older who had suicidal ideation from the Korea National Health and Nutrition Examination Survey from 2007 to 2012. Among them, 106 men and 188 women attempted suicide. Multivariate logistic regression analysis with backward stepwise elimination was performed to find risk factors for suicide attempt. Sub-group analysis, dividing participants into under 50 and at least 50 years old was also performed. Among people with suicidal ideation, age, education, cancer, and depressive disorder were selected as risk factors for suicide attempt in men. Age, education, national basic livelihood security, daily activity limitation, depressive disorder, stress, smoking, and regular exercise were selected in women. Area under curves of our prediction models in men and women were 0.728 and 0.716, respectively. It is important to pay attention to populations with suicidal ideation and the risk factors mentioned above. Prediction models using the determined risk factors could be useful to detect high-risk groups early for suicide attempt among people with suicidal ideation. It is necessary to develop specific action plans for these high-risk groups to prevent suicide.

Impact of covariate models on the assessment of the air pollution-mortality association in a single- and multipollutant context.

PubMed

Sacks, Jason D; Ito, Kazuhiko; Wilson, William E; Neas, Lucas M

2012-10-01

With the advent of multicity studies, uniform statistical approaches have been developed to examine air pollution-mortality associations across cities. To assess the sensitivity of the air pollution-mortality association to different model specifications in a single and multipollutant context, the authors applied various regression models developed in previous multicity time-series studies of air pollution and mortality to data from Philadelphia, Pennsylvania (May 1992-September 1995). Single-pollutant analyses used daily cardiovascular mortality, fine particulate matter (particles with an aerodynamic diameter ≤2.5 µm; PM(2.5)), speciated PM(2.5), and gaseous pollutant data, while multipollutant analyses used source factors identified through principal component analysis. In single-pollutant analyses, risk estimates were relatively consistent across models for most PM(2.5) components and gaseous pollutants. However, risk estimates were inconsistent for ozone in all-year and warm-season analyses. Principal component analysis yielded factors with species associated with traffic, crustal material, residual oil, and coal. Risk estimates for these factors exhibited less sensitivity to alternative regression models compared with single-pollutant models. Factors associated with traffic and crustal material showed consistently positive associations in the warm season, while the coal combustion factor showed consistently positive associations in the cold season. Overall, mortality risk estimates examined using a source-oriented approach yielded more stable and precise risk estimates, compared with single-pollutant analyses.

University of North Carolina Caries Risk Assessment Study: comparisons of high risk prediction, any risk prediction, and any risk etiologic models.

PubMed

Beck, J D; Weintraub, J A; Disney, J A; Graves, R C; Stamm, J W; Kaste, L M; Bohannan, H M

1992-12-01

The purpose of this analysis is to compare three different statistical models for predicting children likely to be at risk of developing dental caries over a 3-yr period. Data are based on 4117 children who participated in the University of North Carolina Caries Risk Assessment Study, a longitudinal study conducted in the Aiken, South Carolina, and Portland, Maine areas. The three models differed with respect to either the types of variables included or the definition of disease outcome. The two "Prediction" models included both risk factor variables thought to cause dental caries and indicator variables that are associated with dental caries, but are not thought to be causal for the disease. The "Etiologic" model included only etiologic factors as variables. A dichotomous outcome measure--none or any 3-yr increment, was used in the "Any Risk Etiologic model" and the "Any Risk Prediction Model". Another outcome, based on a gradient measure of disease, was used in the "High Risk Prediction Model". The variables that are significant in these models vary across grades and sites, but are more consistent among the Etiologic model than the Predictor models. However, among the three sets of models, the Any Risk Prediction Models have the highest sensitivity and positive predictive values, whereas the High Risk Prediction Models have the highest specificity and negative predictive values. Considerations in determining model preference are discussed.

Individual risk of cutaneous melanoma in New Zealand: developing a clinical prediction aid.

PubMed

Sneyd, Mary Jane; Cameron, Claire; Cox, Brian

2014-05-22

New Zealand and Australia have the highest melanoma incidence rates worldwide. In New Zealand, both the incidence and thickness have been increasing. Clinical decisions require accurate risk prediction but a simple list of genetic, phenotypic and behavioural risk factors is inadequate to estimate individual risk as the risk factors for melanoma have complex interactions. In order to offer tailored clinical management strategies, we developed a New Zealand prediction model to estimate individual 5-year absolute risk of melanoma. A population-based case-control study (368 cases and 270 controls) of melanoma risk factors provided estimates of relative risks for fair-skinned New Zealanders aged 20-79 years. Model selection techniques and multivariate logistic regression were used to determine the important predictors. The relative risks for predictors were combined with baseline melanoma incidence rates and non-melanoma mortality rates to calculate individual probabilities of developing melanoma within 5 years. For women, the best model included skin colour, number of moles > =5 mm on the right arm, having a 1st degree relative with large moles, and a personal history of non-melanoma skin cancer (NMSC). The model correctly classified 68% of participants; the C-statistic was 0.74. For men, the best model included age, place of occupation up to age 18 years, number of moles > =5 mm on the right arm, birthplace, and a history of NMSC. The model correctly classified 67% of cases; the C-statistic was 0.71. We have developed the first New Zealand risk prediction model that calculates individual absolute 5-year risk of melanoma. This model will aid physicians to identify individuals at high risk, allowing them to individually target surveillance and other management strategies, and thereby reduce the high melanoma burden in New Zealand.

Multimethod Prediction of Physical Parent-Child Aggression Risk in Expectant Mothers and Fathers with Social Information Processing Theory

PubMed Central

Rodriguez, Christina M.; Smith, Tamika L.; Silvia, Paul J.

2015-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants’ own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. PMID:26631420

Subgroup identification of early preterm birth (ePTB): informing a future prospective enrichment clinical trial design.

PubMed

Zhang, Chuanwu; Garrard, Lili; Keighley, John; Carlson, Susan; Gajewski, Byron

2017-01-10

Despite the widely recognized association between the severity of early preterm birth (ePTB) and its related severe diseases, little is known about the potential risk factors of ePTB and the sub-population with high risk of ePTB. Moreover, motivated by a future confirmatory clinical trial to identify whether supplementing pregnant women with docosahexaenoic acid (DHA) has a different effect on the risk subgroup population or not in terms of ePTB prevalence, this study aims to identify potential risk subgroups and risk factors for ePTB, defined as babies born less than 34 weeks of gestation. The analysis data (N = 3,994,872) were obtained from CDC and NCHS' 2014 Natality public data file. The sample was split into independent training and validation cohorts for model generation and model assessment, respectively. Logistic regression and CART models were used to examine potential ePTB risk predictors and their interactions, including mothers' age, nativity, race, Hispanic origin, marital status, education, pre-pregnancy smoking status, pre-pregnancy BMI, pre-pregnancy diabetes status, pre-pregnancy hypertension status, previous preterm birth status, infertility treatment usage status, fertility enhancing drug usage status, and delivery payment source. Both logistic regression models with either 14 or 10 ePTB risk factors produced the same C-index (0.646) based on the training cohort. The C-index of the logistic regression model based on 10 predictors was 0.645 for the validation cohort. Both C-indexes indicated a good discrimination and acceptable model fit. The CART model identified preterm birth history and race as the most important risk factors, and revealed that the subgroup with a preterm birth history and a race designation as Black had the highest risk for ePTB. The c-index and misclassification rate were 0.579 and 0.034 for the training cohort, and 0.578 and 0.034 for the validation cohort, respectively. This study revealed 14 maternal characteristic variables that reliably identified risk for ePTB through either logistic regression model and/or a CART model. Moreover, both models efficiently identify risk subgroups for further enrichment clinical trial design.

Model-based risk assessment and public health analysis to prevent Lyme disease

PubMed Central

Sabounchi, Nasim S.; Roome, Amanda; Spathis, Rita; Garruto, Ralph M.

2017-01-01

The number of Lyme disease (LD) cases in the northeastern United States has been dramatically increasing with over 300 000 new cases each year. This is due to numerous factors interacting over time including low public awareness of LD, risk behaviours and clothing choices, ecological and climatic factors, an increase in rodents within ecologically fragmented peri-urban built environments and an increase in tick density and infectivity in such environments. We have used a system dynamics (SD) approach to develop a simulation tool to evaluate the significance of risk factors in replicating historical trends of LD cases, and to investigate the influence of different interventions, such as increasing awareness, controlling clothing risk and reducing mouse populations, in reducing LD risk. The model accurately replicates historical trends of LD cases. Among several interventions tested using the simulation model, increasing public awareness most significantly reduces the number of LD cases. This model provides recommendations for LD prevention, including further educational programmes to raise awareness and control behavioural risk. This model has the potential to be used by the public health community to assess the risk of exposure to LD. PMID:29291075

Development and External Validation of a Melanoma Risk Prediction Model Based on Self-assessed Risk Factors.

PubMed

Vuong, Kylie; Armstrong, Bruce K; Weiderpass, Elisabete; Lund, Eiliv; Adami, Hans-Olov; Veierod, Marit B; Barrett, Jennifer H; Davies, John R; Bishop, D Timothy; Whiteman, David C; Olsen, Catherine M; Hopper, John L; Mann, Graham J; Cust, Anne E; McGeechan, Kevin

2016-08-01

Identifying individuals at high risk of melanoma can optimize primary and secondary prevention strategies. To develop and externally validate a risk prediction model for incident first-primary cutaneous melanoma using self-assessed risk factors. We used unconditional logistic regression to develop a multivariable risk prediction model. Relative risk estimates from the model were combined with Australian melanoma incidence and competing mortality rates to obtain absolute risk estimates. A risk prediction model was developed using the Australian Melanoma Family Study (629 cases and 535 controls) and externally validated using 4 independent population-based studies: the Western Australia Melanoma Study (511 case-control pairs), Leeds Melanoma Case-Control Study (960 cases and 513 controls), Epigene-QSkin Study (44 544, of which 766 with melanoma), and Swedish Women's Lifestyle and Health Cohort Study (49 259 women, of which 273 had melanoma). We validated model performance internally and externally by assessing discrimination using the area under the receiver operating curve (AUC). Additionally, using the Swedish Women's Lifestyle and Health Cohort Study, we assessed model calibration and clinical usefulness. The risk prediction model included hair color, nevus density, first-degree family history of melanoma, previous nonmelanoma skin cancer, and lifetime sunbed use. On internal validation, the AUC was 0.70 (95% CI, 0.67-0.73). On external validation, the AUC was 0.66 (95% CI, 0.63-0.69) in the Western Australia Melanoma Study, 0.67 (95% CI, 0.65-0.70) in the Leeds Melanoma Case-Control Study, 0.64 (95% CI, 0.62-0.66) in the Epigene-QSkin Study, and 0.63 (95% CI, 0.60-0.67) in the Swedish Women's Lifestyle and Health Cohort Study. Model calibration showed close agreement between predicted and observed numbers of incident melanomas across all deciles of predicted risk. In the external validation setting, there was higher net benefit when using the risk prediction model to classify individuals as high risk compared with classifying all individuals as high risk. The melanoma risk prediction model performs well and may be useful in prevention interventions reliant on a risk assessment using self-assessed risk factors.

Theory-Based Cartographic Risk Model Development and Application for Home Fire Safety.

PubMed

Furmanek, Stephen; Lehna, Carlee; Hanchette, Carol

There is a gap in the use of predictive risk models to identify areas at risk for home fires and burn injury. The purpose of this study was to describe the creation, validation, and application of such a model using a sample from an intervention study with parents of newborns in Jefferson County, KY, as an example. Performed was a literature search to identify risk factors for home fires and burn injury in the target population. Obtained from the American Community Survey at the census tract level and synthesized to create a predictive cartographic risk model was risk factor data. Model validation was performed through correlation, regression, and Moran's I with fire incidence data from open records. Independent samples t-tests were used to examine the model in relation to geocoded participant addresses. Participant risk level for fire rate was determined and proximity to fire station service areas and hospitals. The model showed high and severe risk clustering in the northwest section of the county. Strongly correlated with fire rate was modeled risk; the best predictive model for fire risk contained home value (low), race (black), and non high school graduates. Applying the model to the intervention sample, the majority of participants were at lower risk and mostly within service areas closest to a fire department and hospital. Cartographic risk models were useful in identifying areas at risk and analyzing participant risk level. The methods outlined in this study are generalizable to other public health issues.

Prognostic stratification model for patients with stage I non-small cell lung cancer adenocarcinoma treated with surgical resection without adjuvant therapies using metabolic features measured on F-18 FDG PET and postoperative pathologic factors.

PubMed

Kang, Yeon-Koo; Song, Yoo Sung; Cho, Sukki; Jheon, Sanghoon; Lee, Won Woo; Kim, Kwhanmien; Kim, Sang Eun

2018-05-01

In the management of non-small cell lung cancer (NSCLC), the prognostic stratification of stage I tumors without indication of adjuvant therapy, remains to be elucidated in order to better select patients who can benefit from additional therapies. We aimed to stratify the prognosis of patients with stage I NSCLC adenocarcinoma using clinicopathologic factors and F-18 FDG PET. We retrospectively enrolled 128 patients with stage I NSCLC without any high-risk factors, who underwent curative surgical resection without adjuvant therapies. Preoperative clinical and postoperative pathologic factors were evaluated by medical record review. Standardized uptake value corrected with lean body mass (SUL max ) was measured on F-18 FDG PET. Among the factors, independent predictors for recurrence-free survival (RFS) were selected using univariate and stepwise multivariate survival analyses. A prognostic stratification model for RFS was designed using the selected factors. Tumors recurred in nineteen patients (14.8%). Among the investigated clinicopathologic and FDG PET factors, SUL max on PET and spread through air spaces (STAS) on pathologic review were determined to be independent prognostic factors for RFS. A prognostic model was designed using these two factors in the following manner: (1) Low-risk: SUL max  ≤ 1.9 and no STAS, (2) intermediate-risk: neither low-risk nor high-risk, (3) high-risk: SUL max> 1.9 and observed STAS. This model exhibited significant predictive power for RFS. We showed that FDG uptake and STAS are significant prognostic markers in stage I NSCLC adenocarcinoma treated with surgical resection without adjuvant therapies. Copyright © 2018 Elsevier B.V. All rights reserved.

Applying Latent Class Analysis to Risk Stratification for Perioperative Mortality in Patients Undergoing Intraabdominal General Surgery.

PubMed

Kim, Minjae; Wall, Melanie M; Li, Guohua

2016-07-01

Perioperative risk stratification is often performed using individual risk factors without consideration of the syndemic of these risk factors. We used latent class analysis (LCA) to identify the classes of comorbidities and risk factors associated with perioperative mortality in patients presenting for intraabdominal general surgery. The 2005 to 2010 American College of Surgeons National Surgical Quality Improvement Program was used to obtain a cohort of patients undergoing intraabdominal general surgery. Risk factors and comorbidities were entered into LCA models to identify the latent classes, and individuals were assigned to a class based on the highest posterior probability of class membership. Relative risk regression was used to determine the associations between the latent classes and 30-day mortality, with adjustments for procedure. A 9-class model was fit using LCA on 466,177 observations. After combining classes with similar adjusted mortality risks, 5 risk classes were obtained. Compared with the class with average mortality risk (class 4), the risk ratios (95% confidence interval) ranged from 0.020 (0.014-0.027) in the lowest risk class (class 1) to 6.75 (6.46-7.02) in the highest risk class. After adjusting for procedure and ASA physical status, the latent classes remained significantly associated with 30-day mortality. The addition of the risk class variable to a model containing ASA physical status and surgical procedure demonstrated a significant increase in the area under the receiver operator characteristic curve (0.892 vs 0.915; P < 0.0001). Latent classes of risk factors and comorbidities in patients undergoing intraabdominal surgery are predictive of 30-day mortality independent of the ASA physical status and improve risk prediction with the ASA physical status.

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs.

PubMed

Ganga, G M D; Esposto, K F; Braatz, D

2012-01-01

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Lifetime competing risks between coronary heart disease mortality and other causes of death during 50years of follow-up.

PubMed

Puddu, Paolo Emilio; Piras, Paolo; Menotti, Alessandro

2017-02-01

To study coronary heart disease (CHD) death versus 11 other causes of death using the cumulative incidence function (CIF) and the competing risks procedures to disentangle the differential role of risk factors for different end-points. Standard Cox and Fine-Gray models among 1712 middle-aged men were compared during 50years of follow-up. CHD death was the primary event, while deaths from 11 selected causes, mutually exclusive from the primary end-point, were considered as secondary events. Reverse solutions were also performed. We considered 10 selected risk factors. CHD death risk was the second highest among 12 mostly specific causes of death. Some risk factors were specific: serum cholesterol for CHD death whereas, systolic blood pressure, cigarette smoking and age may have a differential role in other causes of death. Application of the Fine-Gray model based on CIF enabled to dissect, at least in part, the respective role that baseline covariates may have to segregate the probabilities of two types of death in contrast from each other. They also point to the absence of contributing significance for some of the selected risk factors and this calls for a parsimonious approach in predictions. The relative rarity of competing risk challenges when defining the risk factors role at long-term needs now be corrected since we have clearly shown, with Fine-Gray model, at direct or reverse use, that comparing different end-points heavily influences the risk factor predictive capacity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Psychosocial predictors of cannabis use in adolescents at risk.

PubMed

Hüsler, Gebhard; Plancherel, Bernard; Werlen, Egon

2005-09-01

This research has tested a social disintegration model in conjunction with risk and protection factors that have the power to differentiate relative, weighted interactions among variables in different socially disintegrated groups. The model was tested in a cross-sectional sample of 1082 at-risk youth in Switzerland. Structural equation analyses show significant differences between the social disintegration (low, moderate, high) groups and gender, indicating that the model works differently for groups and for gender. For the highly disintegrated adolescents results clearly show that the risk factors (negative mood, peer network, delinquency) are more important than the protective factors (family relations, secure sense of self). Family relations lose all protective value against negative peer influence, but personal variables, such as secure self, gain protective power.

Variance computations for functional of absolute risk estimates.

PubMed

Pfeiffer, R M; Petracci, E

2011-07-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

Variance computations for functional of absolute risk estimates

PubMed Central

Pfeiffer, R.M.; Petracci, E.

2011-01-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates. PMID:21643476

Language Delay in Severely Neglected Children: A Cumulative or Specific Effect of Risk Factors?

ERIC Educational Resources Information Center

Sylvestre, Audette; Merette, Chantal

2010-01-01

Objectives: This research sought to determine if the language delay (LD) of severely neglected children under 3 years old was better explained by a cumulative risk model or by the specificity of risk factors. The objective was also to identify the risk factors with the strongest impact on LD among various biological, psychological, and…

The effects of cumulative risks and promotive factors on urban adolescent alcohol and other drug use: a longitudinal study of resiliency.

PubMed

Ostaszewski, Krzysztof; Zimmerman, Marc A

2006-12-01

Resiliency theory provides a conceptual framework for studying why some youth exposed to risk factors do not develop the negative behaviors they predict. The purpose of this study was to test compensatory and protective models of resiliency in a longitudinal sample of urban adolescents (80% African American). The data were from Years 1 (9th grade) and 4 (12th grade). The study examined effects of cumulative risk and promotive factors on adolescent polydrug use including alcohol, tobacco and marijuana. Cumulative measures of risk/promotive factors represented individual characteristics, peer influence, and parental/familial influences. After controlling for demographics, results of multiple regression of polydrug use support the compensatory model of resiliency both cross-sectionally and longitudinally. Promotive factors were also found to have compensatory effects on change in adolescent polydrug use. The protective model of resiliency evidenced cross-sectionally was not supported in longitudinal analysis. The findings support resiliency theory and the use of cumulative risk/promotive measures in resiliency research. Implications focused on utilizing multiple assets and resources in prevention programming are discussed.

Risk Prediction for Epithelial Ovarian Cancer in 11 United States–Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci

PubMed Central

Clyde, Merlise A.; Palmieri Weber, Rachel; Iversen, Edwin S.; Poole, Elizabeth M.; Doherty, Jennifer A.; Goodman, Marc T.; Ness, Roberta B.; Risch, Harvey A.; Rossing, Mary Anne; Terry, Kathryn L.; Wentzensen, Nicolas; Whittemore, Alice S.; Anton-Culver, Hoda; Bandera, Elisa V.; Berchuck, Andrew; Carney, Michael E.; Cramer, Daniel W.; Cunningham, Julie M.; Cushing-Haugen, Kara L.; Edwards, Robert P.; Fridley, Brooke L.; Goode, Ellen L.; Lurie, Galina; McGuire, Valerie; Modugno, Francesmary; Moysich, Kirsten B.; Olson, Sara H.; Pearce, Celeste Leigh; Pike, Malcolm C.; Rothstein, Joseph H.; Sellers, Thomas A.; Sieh, Weiva; Stram, Daniel; Thompson, Pamela J.; Vierkant, Robert A.; Wicklund, Kristine G.; Wu, Anna H.; Ziogas, Argyrios; Tworoger, Shelley S.; Schildkraut, Joellen M.

2016-01-01

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted. PMID:27698005

The risk factors of laryngeal pathology in Korean adults using a decision tree model.

PubMed

Byeon, Haewon

2015-01-01

The purpose of this study was to identify risk factors affecting laryngeal pathology in the Korean population and to evaluate the derived prediction model. Cross-sectional study. Data were drawn from the 2008 Korea National Health and Nutritional Examination Survey. The subjects were 3135 persons (1508 male and 2114 female) aged 19 years and older living in the community. The independent variables were age, sex, occupation, smoking, alcohol drinking, and self-reported voice problems. A decision tree analysis was done to identify risk factors for predicting a model of laryngeal pathology. The significant risk factors of laryngeal pathology were age, gender, occupation, smoking, and self-reported voice problem in decision tree model. Four significant paths were identified in the decision tree model for the prediction of laryngeal pathology. Those identified as high risk groups for laryngeal pathology included those who self-reported a voice problem, those who were males in their 50s who did not recognize a voice problem, those who were not economically active males in their 40s, and male workers aged 19 and over and under 50 or 60 and over who currently smoked. The results of this study suggest that individual risk factors, such as age, sex, occupation, health behavior, and self-reported voice problem, affect the onset of laryngeal pathology in a complex manner. Based on the results of this study, early management of the high-risk groups is needed for the prevention of laryngeal pathology. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Analyzing musculoskeletal neck pain, measured as present pain and periods of pain, with three different regression models: a cohort study.

PubMed

Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats

2009-06-19

In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session > or = 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors.

Analyzing musculoskeletal neck pain, measured as present pain and periods of pain, with three different regression models: a cohort study

PubMed Central

Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats

2009-01-01

Background In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Methods Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Results Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session ≥ 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). Conclusion By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors. PMID:19545386

Reconstruction of the Foot and Ankle Using Pedicled or Free Flaps: Perioperative Flap Survival Analysis

PubMed Central

Li, Xiucun; Cui, Jianli; Maharjan, Suraj; Lu, Laijin; Gong, Xu

2016-01-01

Objective The purpose of this study is to determine the correlation between non-technical risk factors and the perioperative flap survival rate and to evaluate the choice of skin flap for the reconstruction of foot and ankle. Methods This was a clinical retrospective study. Nine variables were identified. The Kaplan-Meier method coupled with a log-rank test and a Cox regression model was used to predict the risk factors that influence the perioperative flap survival rate. The relationship between postoperative wound infection and risk factors was also analyzed using a logistic regression model. Results The overall flap survival rate was 85.42%. The necrosis rates of free flaps and pedicled flaps were 5.26% and 20.69%, respectively. According to the Cox regression model, flap type (hazard ratio [HR] = 2.592; 95% confidence interval [CI] (1.606, 4.184); P < 0.001) and postoperative wound infection (HR = 0.266; 95% CI (0.134, 0.529); P < 0.001) were found to be statistically significant risk factors associated with flap necrosis. Based on the logistic regression model, preoperative wound bed inflammation (odds ratio [OR] = 11.371,95% CI (3.117, 41.478), P < 0.001) was a statistically significant risk factor for postoperative wound infection. Conclusion Flap type and postoperative wound infection were both independent risk factors influencing the flap survival rate in the foot and ankle. However, postoperative wound infection was a risk factor for the pedicled flap but not for the free flap. Microvascular anastomosis is a major cause of free flap necrosis. To reconstruct complex or wide soft tissue defects of the foot or ankle, free flaps are safer and more reliable than pedicled flaps and should thus be the primary choice. PMID:27930679

Individual risk factors for deep infection and compromised fracture healing after intramedullary nailing of tibial shaft fractures: a single centre experience of 480 patients.

PubMed

Metsemakers, W-J; Handojo, K; Reynders, P; Sermon, A; Vanderschot, P; Nijs, S

2015-04-01

Despite modern advances in the treatment of tibial shaft fractures, complications including nonunion, malunion, and infection remain relatively frequent. A better understanding of these injuries and its complications could lead to prevention rather than treatment strategies. A retrospective study was performed to identify risk factors for deep infection and compromised fracture healing after intramedullary nailing (IMN) of tibial shaft fractures. Between January 2000 and January 2012, 480 consecutive patients with 486 tibial shaft fractures were enrolled in the study. Statistical analysis was performed to determine predictors of deep infection and compromised fracture healing. Compromised fracture healing was subdivided in delayed union and nonunion. The following independent variables were selected for analysis: age, sex, smoking, obesity, diabetes, American Society of Anaesthesiologists (ASA) classification, polytrauma, fracture type, open fractures, Gustilo type, primary external fixation (EF), time to nailing (TTN) and reaming. As primary statistical evaluation we performed a univariate analysis, followed by a multiple logistic regression model. Univariate regression analysis revealed similar risk factors for delayed union and nonunion, including fracture type, open fractures and Gustilo type. Factors affecting the occurrence of deep infection in this model were primary EF, a prolonged TTN, open fractures and Gustilo type. Multiple logistic regression analysis revealed polytrauma as the single risk factor for nonunion. With respect to delayed union, no risk factors could be identified. In the same statistical model, deep infection was correlated with primary EF. The purpose of this study was to evaluate risk factors of poor outcome after IMN of tibial shaft fractures. The univariate regression analysis showed that the nature of complications after tibial shaft nailing could be multifactorial. This was not confirmed in a multiple logistic regression model, which only revealed polytrauma and primary EF as risk factors for nonunion and deep infection, respectively. Future strategies should focus on prevention in high-risk populations such as polytrauma patients treated with EF. Copyright © 2014 Elsevier Ltd. All rights reserved.

A case-control study of rheumatoid arthritis revealed abdominal obesity and environmental risk factor interactions in northern China.

PubMed

Fu, Lingyu; Zhang, Jianming; Jin, Lei; Zhang, Yao; Cui, Saisai; Chen, Meng

2018-03-01

The aim of this study was to evaluate new and previously hypothesized environmental risk factors and their interaction with rheumatoid arthritis (RA). Four hundred patients recently diagnosed with RA and 400 controls frequency-matched by gender and birth year using Propensity Score Matching (PSM) were selected from northern China. Investigation was performed using self-reported data from interviewer-administered surveys. Associations between exposure variables and risk of RA were evaluated using multifactor non-conditional logistic regression. It showed that damp localities, draft indoor, abdominal obesity (AO), and family history of RA among first-degree relatives were independent risk factors and drinking of milk was independent protective factors for RA. Besides these risk factors, in women, infrequent delivery times, early age at menopause, and late age at menarche were also independent risk factors for RA. Both the additive model and the multiplication model suggested that there was an interaction relationship between AO and damp localities (p < .001), and only the additive model suggested that there was interaction relationship between AO and no milk drinking (p < .001) in our study population. In women, there was interaction relationship between AO and damp localities (p < .001) and between AO and age at menopause (p < .001). In northern China, damp localities, draft indoor, AO, family history of RA among first-degree relatives, and no milk drinking may be important risk factors of RA patients.

Epidemiology and Long-term Clinical and Biologic Risk Factors for Pneumonia in Community-Dwelling Older Americans

PubMed Central

Alvarez, Karina; Loehr, Laura; Folsom, Aaron R.; Newman, Anne B.; Weissfeld, Lisa A.; Wunderink, Richard G.; Kritchevsky, Stephen B.; Mukamal, Kenneth J.; London, Stephanie J.; Harris, Tamara B.; Bauer, Doug C.; Angus, Derek C.

2013-01-01

Background: Preventing pneumonia requires better understanding of incidence, mortality, and long-term clinical and biologic risk factors, particularly in younger individuals. Methods: This was a cohort study in three population-based cohorts of community-dwelling individuals. A derivation cohort (n = 16,260) was used to determine incidence and survival and develop a risk prediction model. The prediction model was validated in two cohorts (n = 8,495). The primary outcome was 10-year risk of pneumonia hospitalization. Results: The crude and age-adjusted incidences of pneumonia were 6.71 and 9.43 cases/1,000 person-years (10-year risk was 6.15%). The 30-day and 1-year mortality were 16.5% and 31.5%. Although age was the most important risk factor (range of crude incidence rates, 1.69-39.13 cases/1,000 person-years for each 5-year increment from 45-85 years), 38% of pneumonia cases occurred in adults < 65 years of age. The 30-day and 1-year mortality were 12.5% and 25.7% in those < 65 years of age. Although most comorbidities were associated with higher risk of pneumonia, reduced lung function was the most important risk factor (relative risk = 6.61 for severe reduction based on FEV1 by spirometry). A clinical risk prediction model based on age, smoking, and lung function predicted 10-year risk (area under curve [AUC] = 0.77 and Hosmer-Lemeshow [HL] C statistic = 0.12). Model discrimination and calibration were similar in the internal validation cohort (AUC = 0.77; HL C statistic, 0.65) but lower in the external validation cohort (AUC = 0.62; HL C statistic, 0.45). The model also calibrated well in blacks and younger adults. C-reactive protein and IL-6 were associated with higher pneumonia risk but did not improve model performance. Conclusions: Pneumonia hospitalization is common and associated with high mortality, even in younger healthy adults. Long-term risk of pneumonia can be predicted in community-dwelling adults with a simple clinical risk prediction model. PMID:23744106

Low Impact of Traditional Risk Factors on Carotid Intima-Media Thickness: The ELSA-Brasil Cohort.

PubMed

Santos, Itamar S; Alencar, Airlane P; Rundek, Tatjana; Goulart, Alessandra C; Barreto, Sandhi M; Pereira, Alexandre C; Benseñor, Isabela M; Lotufo, Paulo A

2015-09-01

There is little information about how much traditional cardiovascular risk factors explain common carotid artery intima-media thickness (CCA-IMT) variance. We aimed to study to which extent CCA-IMT values are determined by traditional risk factors and which commonly used measurements of blood pressure, glucose metabolism, lipid profile, and adiposity contribute the most to this determination in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) cohort baseline. We analyzed 9792 individuals with complete data and CCA-IMT measurements. We built multiple linear regression models using mean left and right CCA-IMT as the dependent variable. All models were stratified by sex. We also analyzed individuals stratified by 10-year coronary heart disease risk and, in separate, those with no traditional risk factors. Main models' R(2) varied between 0.141 and 0.373. The major part of the explained variance in CCA-IMT was because of age and race. Indicators of blood pressure, lipid profile, and adiposity that most frequently composed the best models were pulse pressure, low-density lipoprotein/high-density lipoprotein ratio, and neck circumference. The association between neck circumference and CCA-IMT persisted significant even after further adjustment for vessel sizes and body mass index. Indicators of glucose metabolism had smaller contribution. We found that >60% of CCA-IMT were not explained by demographic and traditional cardiovascular risk factors, which highlights the need to study novel risk factors. Pulse pressure, low-density lipoprotein/high-density lipoprotein ratio, and neck circumference were the most consistent contributors. © 2015 American Heart Association, Inc.

Shared Risk Factors for the Perpetration of Physical Dating Violence, Bullying, and Sexual Harassment Among Adolescents Exposed to Domestic Violence

PubMed Central

McNaughton Reyes, H. Luz; Chen, May S.; Ennett, Susan T.; Basile, Kathleen C.; DeGue, Sarah; Vivolo-Kantor, Alana M.; Moracco, Kathryn E.; Bowling, J. Michael

2016-01-01

The high risk of perpetrating physical dating violence, bullying, and sexual harassment by adolescents exposed to domestic violence points to the need for programs to prevent these types of aggression among this group. This study of adolescents exposed to domestic violence examined whether these forms of aggression share risk factors that could be targeted for change in single programs designed to prevent all three types of aggression. Analyses were conducted on 399 mother victims of domestic violence and their adolescents, recruited through community advertising. The adolescents ranged in age from 12 to 16 years; 64 % were female. Generalized estimating equations was used to control for the covariation among the aggression types when testing for shared risk factors. Approximately 70 % of the adolescents reported perpetrating at least one of the three forms of aggression. In models examining one risk factor at a time, but controlling for demographics, adolescent acceptance of sexual violence, mother–adolescent discord, family conflict, low maternal monitoring, low mother–adolescent closeness, low family cohesion, depressed affect, feelings of anger, and anger reactivity were shared across all three aggression types. In multivariable models, which included all of the risk factors examined and the demographic variables, low maternal monitoring, depressed affect and anger reactivity remained significant shared risk factors. Our findings suggest that programs targeting these risk factors for change have the potential to prevent all three forms of aggression. In multivariable models, poor conflict management skills was a risk for bullying and sexual harassment, but not dating violence; acceptance of dating violence was a risk for dating violence and bullying, but not sexual harassment; and none of the examined risk factors were unique to aggression type. The study’s implications for the development of interventions and future research are discussed. PMID:26746242

Application of Bayesian networks in a hierarchical structure for environmental risk assessment: a case study of the Gabric Dam, Iran.

PubMed

Malekmohammadi, Bahram; Tayebzadeh Moghadam, Negar

2018-04-13

Environmental risk assessment (ERA) is a commonly used, effective tool applied to reduce adverse effects of environmental risk factors. In this study, ERA was investigated using the Bayesian network (BN) model based on a hierarchical structure of variables in an influence diagram (ID). ID facilitated ranking of the different alternatives under uncertainty that were then used to evaluate comparisons of the different risk factors. BN was used to present a new model for ERA applicable to complicated development projects such as dam construction. The methodology was applied to the Gabric Dam, in southern Iran. The main environmental risk factors in the region, presented by the Gabric Dam, were identified based on the Delphi technique and specific features of the study area. These included the following: flood, water pollution, earthquake, changes in land use, erosion and sedimentation, effects on the population, and ecosensitivity. These risk factors were then categorized based on results from the output decision node of the BN, including expected utility values for risk factors in the decision node. ERA was performed for the Gabric Dam using the analytical hierarchy process (AHP) method to compare results of BN modeling with those of conventional methods. Results determined that a BN-based hierarchical structure to ERA present acceptable and reasonable risk assessment prioritization in proposing suitable solutions to reduce environmental risks and can be used as a powerful decision support system for evaluating environmental risks.

The Role of Body Image and Disordered Eating as Risk Factors for Depression and Suicidal Ideation in Adolescents

ERIC Educational Resources Information Center

Brausch, Amy M.; Gutierrez, Peter M.

2009-01-01

There is much empirical literature on factors for adolescent suicide risk, but body image and disordered eating are rarely included in these models. In the current study, disordered eating and body image were examined as risk factors for suicide ideation since these factors are prevalent in adolescence, particularly for females. It was…

A comparison of risk assessment models for term and preterm low birthweight.

PubMed

Michielutte, R; Ernest, J M; Moore, M L; Meis, P J; Sharp, P C; Wells, H B; Buescher, P A

1992-01-01

Most epidemiological research dealing with the assessment of risk for low birthweight has focused on all low birthweight births. Studies that have attempted to distinguish between term and preterm low birthweights have tended to examine preterm low birthweight, since the risk of perinatal mortality and morbidity is greatest for this group of infants. This study uses data from 25,408 singleton births in a 20-county region in North Carolina to identify and compare risk factors for term and preterm low birthweights, and also examines the usefulness of separate multivariate risk assessment systems for term and preterm low birthweights that could be used in the clinical setting. Risk factors that overlap as significant predictors of both types of low birthweight include race, no previous live births, smoking, weight under 100 lb, and previous preterm or low birthweight birth. Age also is a significant predictor of both types of low birthweight, but in opposite directions. Younger age is associated with reduced risk of term low birthweight and increased risk of pattern low birthweight. Comparison of all risk factors indicates that different multivariate models are needed to understand the epidemiology of preterm and term low birthweights. In terms of clinical value, a general risk assessment model that combines all low birthweight births is as effective as the separate models.

Determining Risk of Barrett's Esophagus and Esophageal Adenocarcinoma Based on Epidemiologic Factors and Genetic Variants.

PubMed

Dong, Jing; Buas, Matthew F; Gharahkhani, Puya; Kendall, Bradley J; Onstad, Lynn; Zhao, Shanshan; Anderson, Lesley A; Wu, Anna H; Ye, Weimin; Bird, Nigel C; Bernstein, Leslie; Chow, Wong-Ho; Gammon, Marilie D; Liu, Geoffrey; Caldas, Carlos; Pharoah, Paul D; Risch, Harvey A; Iyer, Prasad G; Reid, Brian J; Hardie, Laura J; Lagergren, Jesper; Shaheen, Nicholas J; Corley, Douglas A; Fitzgerald, Rebecca C; Whiteman, David C; Vaughan, Thomas L; Thrift, Aaron P

2018-04-01

We developed comprehensive models to determine risk of Barrett's esophagus (BE) or esophageal adenocarcinoma (EAC) based on genetic and non-genetic factors. We used pooled data from 3288 patients with BE, 2511 patients with EAC, and 2177 individuals without either (controls) from participants in the international Barrett's and EAC consortium as well as the United Kingdom's BE gene study and stomach and esophageal cancer study. We collected data on 23 genetic variants associated with risk for BE or EAC, and constructed a polygenic risk score (PRS) for cases and controls by summing the risk allele counts for the variants weighted by their natural log-transformed effect estimates (odds ratios) extracted from genome-wide association studies. We also collected data on demographic and lifestyle factors (age, sex, smoking, body mass index, use of nonsteroidal anti-inflammatory drugs) and symptoms of gastroesophageal reflux disease (GERD). Risk models with various combinations of non-genetic factors and the PRS were compared for their accuracy in identifying patients with BE or EAC using the area under the receiver operating characteristic curve (AUC) analysis. Individuals in the highest quartile of risk, based on genetic factors (PRS), had a 2-fold higher risk of BE (odds ratio, 2.22; 95% confidence interval, 1.89-2.60) or EAC (odds ratio, 2.46; 95% confidence interval, 2.07-2.92) than individual in the lowest quartile of risk based on PRS. Risk models developed based on only demographic or lifestyle factors or GERD symptoms identified patients with BE or EAC with AUC values ranging from 0.637 to 0.667. Combining data on demographic or lifestyle factors with data on GERD symptoms identified patients with BE with an AUC of 0.793 and patients with EAC with an AUC of 0.745. Including PRSs with these data only minimally increased the AUC values for BE (to 0.799) and EAC (to 0.754). Including the PRSs in the model developed based on non-genetic factors resulted in a net reclassification improvement for BE of 3.0% and for EAC of 5.6%. We used data from 3 large databases of patients from studies of BE or EAC to develop a risk prediction model based on genetic, clinical, and demographic/lifestyle factors. We identified a PRS that increases discrimination and net reclassification of individuals with vs without BE and EAC. However, the absolute magnitude of improvement is not sufficient to justify its clinical use. Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.

Latent variable model for suicide risk in relation to social capital and socio-economic status.

PubMed

Congdon, Peter

2012-08-01

There is little evidence on the association between suicide outcomes (ideation, attempts, self-harm) and social capital. This paper investigates such associations using a structural equation model based on health survey data, and allowing for both individual and contextual risk factors. Social capital and other major risk factors for suicide, namely socioeconomic status and social isolation, are modelled as latent variables that are proxied (or measured) by observed indicators or question responses for survey subjects. These latent scales predict suicide risk in the structural component of the model. Also relevant to explaining suicide risk are contextual variables, such as area deprivation and region of residence, as well as the subject's demographic status. The analysis is based on the 2007 Adult Psychiatric Morbidity Survey and includes 7,403 English subjects. A Bayesian modelling strategy is used. Models with and without social capital as a predictor of suicide risk are applied. A benefit to statistical fit is demonstrated when social capital is added as a predictor. Social capital varies significantly by geographic context variables (neighbourhood deprivation, region), and this impacts on the direct effects of these contextual variables on suicide risk. In particular, area deprivation is not confirmed as a distinct significant influence. The model develops a suicidality risk score incorporating social capital, and the success of this risk score in predicting actual suicide events is demonstrated. Social capital as reflected in neighbourhood perceptions is a significant factor affecting risks of different types of self-harm and may mediate the effects of other contextual variables such as area deprivation.

An analysis of security price risk and return among publicly traded pharmacy corporations.

PubMed

Gilligan, Adrienne M; Skrepnek, Grant H

2013-01-01

Community pharmacies have been subject to intense and increasing competition in the past several decades. To determine the security price risk and rate of return of publicly traded pharmacy corporations present on the major U.S. stock exchanges from 1930 to 2009. The Center of Research in Security Prices (CRSP) database was used to examine monthly security-level stock market prices in this observational retrospective study. The primary outcome of interest was the equity risk premium, with analyses focusing upon financial metrics associated with risk and return based upon modern portfolio theory (MPT) including: abnormal returns (i.e., alpha), volatility (i.e., beta), and percentage of returns explained (i.e., adjusted R(2)). Three equilibrium models were estimated using random-effects generalized least squares (GLS): 1) the Capital Asset Pricing Model (CAPM); 2) Fama-French Three-Factor Model; and 3) Carhart Four-Factor Model. Seventy-five companies were examined from 1930 to 2009, with overall adjusted R(2) values ranging from 0.13 with the CAPM to 0.16 with the Four-Factor model. Alpha was not significant within any of the equilibrium models across the entire 80-year time period, though was found from 1999 to 2009 in the Three- and Four-Factor models to be associated with a large, significant, and negative risk-adjusted abnormal returns of -33.84%. Volatility varied across specific time periods based upon the financial model employed. This investigation of risk and return within publicly listed pharmacy corporations from 1930 to 2009 found that substantial losses were incurred particularly from 1999 to 2009, with risk-adjusted security valuations decreasing by one-third. Copyright © 2013 Elsevier Inc. All rights reserved.

Alternative models of DSM-5 PTSD: Examining diagnostic implications.

PubMed

Murphy, Siobhan; Hansen, Maj; Elklit, Ask; Yong Chen, Yoke; Raudzah Ghazali, Siti; Shevlin, Mark

2018-04-01

The factor structure of DSM-5 posttraumatic stress disorder (PTSD) has been extensively debated with evidence supporting the recently proposed seven-factor Hybrid model. However, despite myriad studies examining PTSD symptom structure few have assessed the diagnostic implications of these proposed models. This study aimed to generate PTSD prevalence estimates derived from the 7 alternative factor models and assess whether pre-established risk factors associated with PTSD (e.g., transportation accidents and sexual victimisation) produce consistent risk estimates. Seven alternative models were estimated within a confirmatory factor analytic framework using the PTSD Checklist for DSM-5 (PCL-5). Data were analysed from a Malaysian adolescent community sample (n = 481) of which 61.7% were female, with a mean age of 17.03 years. The results indicated that all models provided satisfactory model fit with statistical superiority for the Externalising Behaviours and seven-factor Hybrid models. The PTSD prevalence estimates varied substantially ranging from 21.8% for the DSM-5 model to 10.0% for the Hybrid model. Estimates of risk associated with PTSD were inconsistent across the alternative models, with substantial variation emerging for sexual victimisation. These findings have important implications for research and practice and highlight that more research attention is needed to examine the diagnostic implications emerging from the alternative models of PTSD. Copyright © 2017 Elsevier B.V. All rights reserved.

Behavioural Outcomes of Four-Year-Old Children Prenatally Exposed to Methadone or Buprenorphine: A Test of Three Risk Models

ERIC Educational Resources Information Center

Konijnenberg, Carolien; Lund, Ingunn Olea; Melinder, Annika

2015-01-01

It is still under debate whether the reported effects of opioid maintenance therapy (OMT) on child behaviour are a direct effect of prenatal exposure, or whether other factors are involved. This prospective cohort study investigated three models: the teratogenic risk model, the maternal risk model, and a combined risk model in a group of 35…

A simulation model to investigate the impact of cardiovascular risk in renal transplantation.

PubMed

McLean, D R; Jardine, A G

2005-06-01

Premature cardiovascular (CV) disease is the leading cause of death following renal transplantation and, as a consequence of death with a functioning graft, it is a major cause of graft loss. Renal transplant recipients have a high prevalence of CV risk factors that influence both patient and graft survival. We used data on the relationship between CV risk factors and graft and patient survivals to develop a discrete event simulation model to study the possible impact of CV risk factor reduction on transplant outcome. The simulation was based on a renal unit in a population that has the risk factor profile of patients from the West of Scotland. We studied the dynamic between patient numbers on the waiting list compared to the transplanted list. After establishing results pertinent to the renal unit, we investigated in what way potential changes to transplant policy affected patient numbers. These perturbations included changing the number of transplants performed, changing the incidence of acute rejection, and interventional policies where patients on the waiting list were selectively transplanted taking into account their CV risk factor profiles. Overall, the model predicts that reducing CV risk in the population with end-stage renal failure awaiting kidney transplantation will have comparable benefits to foreseeable developments in immunosuppression or attainable increases in transplant numbers. Moreover, addressing CV risk has benefits for all patients regardless of whether or not they ultimately receive a kidney transplant.

Are elements of the chronic care model associated with cardiovascular risk factor control in type 2 diabetes?

PubMed

Parchman, Michael; Kaissi, Amer A

2009-03-01

Control of modifiable risk factors for cardiovascular (CV) disease, the most common cause of morbidity and mortality among people with Type 2 diabetes is dependent on both patient self-care behaviors and the characteristics of the clinic in which care is delivered. The relationship between control of CV risk factors, patient self-care behaviors, and the presence of CCM (Chronic Care Model) components across multiple primary care clinic settings was examined. Thirty consecutive patients presenting with Type 2 diabetes were enrolled from each of 20 primary care clinics from across South Texas. Patients were asked about their stage of change for four self-care behaviors: diet, exercise, glucose monitoring, and medication adherence. CV risk factors included the most recent values of glycosolated hemoglobin (A1C), blood pressure, and (low-density lipoprotein) cholesterol. Clinicians in each clinic completed the Assessment of Chronic Illness Care (ACIC) survey, a validated measure of the CCM components. Hierarchical logistic regression models were used. Only 25 (13%) of the 618 patients had good control of all three CV risk factors. Good control of these risk factors was positively associated with community linkages and delivery system design but was inversely associated with clinical information systems. Patients who were in the maintenance stage of change for all four self-care behaviors were more likely to have all three risk factors well controlled. Risk factors for CV disease among patients with diabetes are associated with the structure and design of the clinical microsystem where care is delivered. In addition to focusing on clinician knowledge, future interventions should address the clinical microsystem's structure and design to reduce the burden of CV disease among patients with Type 2 diabetes.

Multivariate logistic regression analysis of postoperative complications and risk model establishment of gastrectomy for gastric cancer: A single-center cohort report.

PubMed

Zhou, Jinzhe; Zhou, Yanbing; Cao, Shougen; Li, Shikuan; Wang, Hao; Niu, Zhaojian; Chen, Dong; Wang, Dongsheng; Lv, Liang; Zhang, Jian; Li, Yu; Jiao, Xuelong; Tan, Xiaojie; Zhang, Jianli; Wang, Haibo; Zhang, Bingyuan; Lu, Yun; Sun, Zhenqing

2016-01-01

Reporting of surgical complications is common, but few provide information about the severity and estimate risk factors of complications. If have, but lack of specificity. We retrospectively analyzed data on 2795 gastric cancer patients underwent surgical procedure at the Affiliated Hospital of Qingdao University between June 2007 and June 2012, established multivariate logistic regression model to predictive risk factors related to the postoperative complications according to the Clavien-Dindo classification system. Twenty-four out of 86 variables were identified statistically significant in univariate logistic regression analysis, 11 significant variables entered multivariate analysis were employed to produce the risk model. Liver cirrhosis, diabetes mellitus, Child classification, invasion of neighboring organs, combined resection, introperative transfusion, Billroth II anastomosis of reconstruction, malnutrition, surgical volume of surgeons, operating time and age were independent risk factors for postoperative complications after gastrectomy. Based on logistic regression equation, p=Exp∑BiXi / (1+Exp∑BiXi), multivariate logistic regression predictive model that calculated the risk of postoperative morbidity was developed, p = 1/(1 + e((4.810-1.287X1-0.504X2-0.500X3-0.474X4-0.405X5-0.318X6-0.316X7-0.305X8-0.278X9-0.255X10-0.138X11))). The accuracy, sensitivity and specificity of the model to predict the postoperative complications were 86.7%, 76.2% and 88.6%, respectively. This risk model based on Clavien-Dindo grading severity of complications system and logistic regression analysis can predict severe morbidity specific to an individual patient's risk factors, estimate patients' risks and benefits of gastric surgery as an accurate decision-making tool and may serve as a template for the development of risk models for other surgical groups.

Anthropogenic factors and the risk of highly pathogenic avian influenza H5N1: prospects from a spatial-based model.

PubMed

Paul, Mathilde; Tavornpanich, Saraya; Abrial, David; Gasqui, Patrick; Charras-Garrido, Myriam; Thanapongtharm, Weerapong; Xiao, Xiangming; Gilbert, Marius; Roger, Francois; Ducrot, Christian

2010-01-01

Beginning in 2003, highly pathogenic avian influenza (HPAI) H5N1 virus spread across Southeast Asia, causing unprecedented epidemics. Thailand was massively infected in 2004 and 2005 and continues today to experience sporadic outbreaks. While research findings suggest that the spread of HPAI H5N1 is influenced primarily by trade patterns, identifying the anthropogenic risk factors involved remains a challenge. In this study, we investigated which anthropogenic factors played a role in the risk of HPAI in Thailand using outbreak data from the "second wave" of the epidemic (3 July 2004 to 5 May 2005) in the country. We first performed a spatial analysis of the relative risk of HPAI H5N1 at the subdistrict level based on a hierarchical Bayesian model. We observed a strong spatial heterogeneity of the relative risk. We then tested a set of potential risk factors in a multivariable linear model. The results confirmed the role of free-grazing ducks and rice-cropping intensity but showed a weak association with fighting cock density. The results also revealed a set of anthropogenic factors significantly linked with the risk of HPAI. High risk was associated strongly with densely populated areas, short distances to a highway junction, and short distances to large cities. These findings highlight a new explanatory pattern for the risk of HPAI and indicate that, in addition to agro-environmental factors, anthropogenic factors play an important role in the spread of H5N1. To limit the spread of future outbreaks, efforts to control the movement of poultry products must be sustained. INRA, EDP Sciences, 2010.

Risk assessment of maize damage by wireworms (Coleoptera: Elateridae) as the first step in implementing IPM and in reducing the environmental impact of soil insecticides.

PubMed

Furlan, L; Contiero, B; Chiarini, F; Colauzzi, M; Sartori, E; Benvegnù, I; Fracasso, F; Giandon, P

2017-01-01

A survey of maize fields was conducted in northeast Italy from 1986 to 2014, resulting in a dataset of 1296 records including information on wireworm damage to maize, plant-attacking species, agronomic characteristics, landscape and climate. Three wireworm species, Agriotes brevis Candeze, A. sordidus Illiger and A. ustulatus Schäller, were identified as the dominant pest species in maize fields. Over the 29-year period surveyed, no yield reduction was observed when wireworm plant damage was below 15 % of the stand. A preliminary univariate analysis of risk assessment was applied to identify the main factors influencing the occurrence of damage. A multifactorial model was then applied by using the significant factors identified. This model allowed the research to highlight the strongest factors and to analyse how the main factors together influenced damage risk. The strongest factors were: A. brevis as prevalent damaging species, soil organic matter content >5 %, rotation including meadows and/or double crops, A. sordidus as prevalent damaging species, and surrounding landscape mainly meadows, uncultivated grass and double crops. The multifactorial model also showed how the simultaneous occurrence of two or more of the aforementioned risk factors can conspicuously increase the risk of wireworm damage to maize crops, while the probability of damage to a field with no-risk factors is always low (<1 %). These results make it possible to draw risk maps to identify low-risk and high-risk areas, a first step in implementing bespoke IPM procedures in an attempt to reduce the impact of soil insecticides significantly.

Spatial Variability of Geriatric Depression Risk in a High-Density City: A Data-Driven Socio-Environmental Vulnerability Mapping Approach.

PubMed

Ho, Hung Chak; Lau, Kevin Ka-Lun; Yu, Ruby; Wang, Dan; Woo, Jean; Kwok, Timothy Chi Yui; Ng, Edward

2017-08-31

Previous studies found a relationship between geriatric depression and social deprivation. However, most studies did not include environmental factors in the statistical models, introducing a bias to estimate geriatric depression risk because the urban environment was found to have significant associations with mental health. We developed a cross-sectional study with a binomial logistic regression to examine the geriatric depression risk of a high-density city based on five social vulnerability factors and four environmental measures. We constructed a socio-environmental vulnerability index by including the significant variables to map the geriatric depression risk in Hong Kong, a high-density city characterized by compact urban environment and high-rise buildings. Crude and adjusted odds ratios (ORs) of the variables were significantly different, indicating that both social and environmental variables should be included as confounding factors. For the comprehensive model controlled by all confounding factors, older adults who were of lower education had the highest geriatric depression risks (OR: 1.60 (1.21, 2.12)). Higher percentage of residential area and greater variation in building height within the neighborhood also contributed to geriatric depression risk in Hong Kong, while average building height had negative association with geriatric depression risk. In addition, the socio-environmental vulnerability index showed that higher scores were associated with higher geriatric depression risk at neighborhood scale. The results of mapping and cross-section model suggested that geriatric depression risk was associated with a compact living environment with low socio-economic conditions in historical urban areas in Hong Kong. In conclusion, our study found a significant difference in geriatric depression risk between unadjusted and adjusted models, suggesting the importance of including environmental factors in estimating geriatric depression risk. We also developed a framework to map geriatric depression risk across a city, which can be used for identifying neighborhoods with higher risk for public health surveillance and sustainable urban planning.

Spatial Variability of Geriatric Depression Risk in a High-Density City: A Data-Driven Socio-Environmental Vulnerability Mapping Approach

PubMed Central

Lau, Kevin Ka-Lun; Yu, Ruby; Wang, Dan; Kwok, Timothy Chi Yui; Ng, Edward

2017-01-01

Previous studies found a relationship between geriatric depression and social deprivation. However, most studies did not include environmental factors in the statistical models, introducing a bias to estimate geriatric depression risk because the urban environment was found to have significant associations with mental health. We developed a cross-sectional study with a binomial logistic regression to examine the geriatric depression risk of a high-density city based on five social vulnerability factors and four environmental measures. We constructed a socio-environmental vulnerability index by including the significant variables to map the geriatric depression risk in Hong Kong, a high-density city characterized by compact urban environment and high-rise buildings. Crude and adjusted odds ratios (ORs) of the variables were significantly different, indicating that both social and environmental variables should be included as confounding factors. For the comprehensive model controlled by all confounding factors, older adults who were of lower education had the highest geriatric depression risks (OR: 1.60 (1.21, 2.12)). Higher percentage of residential area and greater variation in building height within the neighborhood also contributed to geriatric depression risk in Hong Kong, while average building height had negative association with geriatric depression risk. In addition, the socio-environmental vulnerability index showed that higher scores were associated with higher geriatric depression risk at neighborhood scale. The results of mapping and cross-section model suggested that geriatric depression risk was associated with a compact living environment with low socio-economic conditions in historical urban areas in Hong Kong. In conclusion, our study found a significant difference in geriatric depression risk between unadjusted and adjusted models, suggesting the importance of including environmental factors in estimating geriatric depression risk. We also developed a framework to map geriatric depression risk across a city, which can be used for identifying neighborhoods with higher risk for public health surveillance and sustainable urban planning. PMID:28858265

Depression and Anxiety Symptoms: Onset, Developmental Course and Risk Factors during Early Childhood

ERIC Educational Resources Information Center

Cote, Sylvana M.; Boivin, Michel; Liu, Xuecheng; Nagin, Daniel S.; Zoccolillo, Mark; Tremblay, Richard E.

2009-01-01

Background: Depressive and anxiety disorders are among the top ten leading causes of disabilities. We know little, however, about the onset, developmental course and early risk factors for depressive and anxiety symptoms (DAS). Objective: Model the developmental trajectories of DAS during early childhood and to identify risk factors for atypically…

Using agent-based modeling to study multiple risk factors and multiple health outcomes at multiple levels.

PubMed

Yang, Yong

2017-11-01

Most health studies focus on one health outcome and examine the influence of one or multiple risk factors. However, in reality, various pathways, interactions, and associations exist not only between risk factors and health outcomes but also among the risk factors and among health outcomes. The advance of system science methods, Big Data, and accumulated knowledge allows us to examine how multiple risk factors influence multiple health outcomes at multiple levels (termed a 3M study). Using the study of neighborhood environment and health as an example, I elaborate on the significance of 3M studies. 3M studies may lead to a significantly deeper understanding of the dynamic interactions among risk factors and outcomes and could help us design better interventions that may be of particular relevance for upstream interventions. Agent-based modeling (ABM) is a promising method in the 3M study, although its potentials are far from being fully explored. Future challenges include the gap of epidemiologic knowledge and evidence, lack of empirical data sources, and the technical challenges of ABM. © 2017 New York Academy of Sciences.

A multi-level approach for investigating socio-economic and agricultural risk factors associated with rates of reported cases of Escherichia coli O157 in humans in Alberta, Canada.

PubMed

Pearl, D L; Louie, M; Chui, L; Doré, K; Grimsrud, K M; Martin, S W; Michel, P; Svenson, L W; McEwen, S A

2009-10-01

Using negative binomial and multi-level Poisson models, the authors determined the statistical significance of agricultural and socio-economic risk factors for rates of reported disease associated with Escherichia coli O157 in census subdivisions (CSDs) in Alberta, Canada, 2000-2002. Variables relating to population stability, aboriginal composition of the CSDs, and the economic relationship between CSDs and urban centres were significant risk factors. The percentage of individuals living in low-income households was not a statistically significant risk factor for rates of disease. The statistical significance of cattle density, recorded at a higher geographical level, depended on the method used to correct for overdispersion, the number of levels included in the multi-level models, and the choice of using all reported cases or only sporadic cases. Our results highlight the importance of local socio-economic risk factors in determining rates of disease associated with E. coli O157, but their relationship with individual risk factors requires further evaluation.

Wild Fire Risk Map in the Eastern Steppe of Mongolia Using Spatial Multi-Criteria Analysis

NASA Astrophysics Data System (ADS)

Nasanbat, Elbegjargal; Lkhamjav, Ochirkhuyag

2016-06-01

Grassland fire is a cause of major disturbance to ecosystems and economies throughout the world. This paper investigated to identify risk zone of wildfire distributions on the Eastern Steppe of Mongolia. The study selected variables for wildfire risk assessment using a combination of data collection, including Social Economic, Climate, Geographic Information Systems, Remotely sensed imagery, and statistical yearbook information. Moreover, an evaluation of the result is used field validation data and assessment. The data evaluation resulted divided by main three group factors Environmental, Social Economic factor, Climate factor and Fire information factor into eleven input variables, which were classified into five categories by risk levels important criteria and ranks. All of the explanatory variables were integrated into spatial a model and used to estimate the wildfire risk index. Within the index, five categories were created, based on spatial statistics, to adequately assess respective fire risk: very high risk, high risk, moderate risk, low and very low. Approximately more than half, 68 percent of the study area was predicted accuracy to good within the very high, high risk and moderate risk zones. The percentages of actual fires in each fire risk zone were as follows: very high risk, 42 percent; high risk, 26 percent; moderate risk, 13 percent; low risk, 8 percent; and very low risk, 11 percent. The main overall accuracy to correct prediction from the model was 62 percent. The model and results could be support in spatial decision making support system processes and in preventative wildfire management strategies. Also it could be help to improve ecological and biodiversity conservation management.

Accuracy, calibration and clinical performance of the EuroSCORE: can we reduce the number of variables?

PubMed

Ranucci, Marco; Castelvecchio, Serenella; Menicanti, Lorenzo; Frigiola, Alessandro; Pelissero, Gabriele

2010-03-01

The European system for cardiac operative risk evaluation (EuroSCORE) is currently used in many institutions and is considered a reference tool in many countries. We hypothesised that too many variables were included in the EuroSCORE using limited patient series. We tested different models using a limited number of variables. A total of 11150 adult patients undergoing cardiac operations at our institution (2001-2007) were retrospectively analysed. The 17 risk factors composing the EuroSCORE were separately analysed and ranked for accuracy of prediction of hospital mortality. Seventeen models were created by progressively including one factor at a time. The models were compared for accuracy with a receiver operating characteristics (ROC) analysis and area under the curve (AUC) evaluation. Calibration was tested with Hosmer-Lemeshow statistics. Clinical performance was assessed by comparing the predicted with the observed mortality rates. The best accuracy (AUC 0.76) was obtained using a model including only age, left ventricular ejection fraction, serum creatinine, emergency operation and non-isolated coronary operation. The EuroSCORE AUC (0.75) was not significantly different. Calibration and clinical performance were better in the five-factor model than in the EuroSCORE. Only in high-risk patients were 12 factors needed to achieve a good performance. Including many factors in multivariable logistic models increases the risk for overfitting, multicollinearity and human error. A five-factor model offers the same level of accuracy but demonstrated better calibration and clinical performance. Models with a limited number of factors may work better than complex models when applied to a limited number of patients. Copyright (c) 2009 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

Fetal Substance Exposure and Cumulative Environmental Risk in an African American Cohort

ERIC Educational Resources Information Center

Yumoto, Chie; Jacobson, Sandra W.; Jacobson, Joseph L.

2008-01-01

Two models of vulnerability to socioenvironmental risk were examined in 337 African American children (M = 7.8 years) recruited to overrepresent prenatal alcohol or cocaine exposure: The cumulative risk model predicted synergistic effects from exposure to multiple risk factors, and the fetal patterning of disease model predicted that prenatal…

Data mining model using simple and readily available factors could identify patients at high risk for hepatocellular carcinoma in chronic hepatitis C.

PubMed

Kurosaki, Masayuki; Hiramatsu, Naoki; Sakamoto, Minoru; Suzuki, Yoshiyuki; Iwasaki, Manabu; Tamori, Akihiro; Matsuura, Kentaro; Kakinuma, Sei; Sugauchi, Fuminaka; Sakamoto, Naoya; Nakagawa, Mina; Izumi, Namiki

2012-03-01

Assessment of the risk of hepatocellular carcinoma (HCC) development is essential for formulating personalized surveillance or antiviral treatment plan for chronic hepatitis C. We aimed to build a simple model for the identification of patients at high risk of developing HCC. Chronic hepatitis C patients followed for at least 5 years (n=1003) were analyzed by data mining to build a predictive model for HCC development. The model was externally validated using a cohort of 1072 patients (472 with sustained virological response (SVR) and 600 with nonSVR to PEG-interferon plus ribavirin therapy). On the basis of factors such as age, platelet, albumin, and aspartate aminotransferase, the HCC risk prediction model identified subgroups with high-, intermediate-, and low-risk of HCC with a 5-year HCC development rate of 20.9%, 6.3-7.3%, and 0-1.5%, respectively. The reproducibility of the model was confirmed through external validation (r(2)=0.981). The 10-year HCC development rate was also significantly higher in the high-and intermediate-risk group than in the low-risk group (24.5% vs. 4.8%; p<0.0001). In the high-and intermediate-risk group, the incidence of HCC development was significantly reduced in patients with SVR compared to those with nonSVR (5-year rate, 9.5% vs. 4.5%; p=0.040). The HCC risk prediction model uses simple and readily available factors and identifies patients at a high risk of HCC development. The model allows physicians to identify patients requiring HCC surveillance and those who benefit from IFN therapy to prevent HCC. Copyright © 2011 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Quantifying cardiometabolic risk using modifiable non-self-reported risk factors.

PubMed

Marino, Miguel; Li, Yi; Pencina, Michael J; D'Agostino, Ralph B; Berkman, Lisa F; Buxton, Orfeu M

2014-08-01

Sensitive general cardiometabolic risk assessment tools of modifiable risk factors would be helpful and practical in a range of primary prevention interventions or for preventive health maintenance. To develop and validate a cumulative general cardiometabolic risk score that focuses on non-self-reported modifiable risk factors such as glycosylated hemoglobin (HbA1c) and BMI so as to be sensitive to small changes across a span of major modifiable risk factors, which may not individually cross clinical cut-off points for risk categories. We prospectively followed 2,359 cardiovascular disease (CVD)-free subjects from the Framingham offspring cohort over a 14-year follow-up. Baseline (fifth offspring examination cycle) included HbA1c and cholesterol measurements. Gender-specific Cox proportional hazards models were considered to evaluate the effects of non-self-reported modifiable risk factors (blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking, BMI, and HbA1c) on general CVD risk. We constructed 10-year general cardiometabolic risk score functions and evaluated its predictive performance in 2012-2013. HbA1c was significantly related to general CVD risk. The proposed cardiometabolic general CVD risk model showed good predictive performance as determined by cross-validated discrimination (male C-index=0.703, 95% CI=0.668, 0.734; female C-index=0.762, 95% CI=0.726, 0.801) and calibration (lack-of-fit chi-square=9.05 [p=0.338] and 12.54 [p=0.128] for men and women, respectively). This study presents a risk factor algorithm that provides a convenient and informative way to quantify cardiometabolic risk on the basis of modifiable risk factors that can motivate an individual's commitment to prevention and intervention. Copyright © 2014 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Quantifying Cardiometabolic Risk Using Modifiable Non–Self-Reported Risk Factors

PubMed Central

Marino, Miguel; Li, Yi; Pencina, Michael J.; D’Agostino, Ralph B.; Berkman, Lisa F.; Buxton, Orfeu M.

2014-01-01

Background Sensitive general cardiometabolic risk assessment tools of modifiable risk factors would be helpful and practical in a range of primary prevention interventions or for preventive health maintenance. Purpose To develop and validate a cumulative general cardiometabolic risk score that focuses on non–self-reported modifiable risk factors such as glycosylated hemoglobin (HbA1c) and BMI so as to be sensitive to small changes across a span of major modifiable risk factors, which may not individually cross clinical cut off points for risk categories. Methods We prospectively followed 2,359 cardiovascular disease (CVD)-free subjects from the Framingham offspring cohort over a 14–year follow-up. Baseline (fifth offspring examination cycle) included HbA1c and cholesterol measurements. Gender–specific Cox proportional hazards models were considered to evaluate the effects of non–self-reported modifiable risk factors (blood pressure, total cholesterol, high–density lipoprotein cholesterol, smoking, BMI, and HbA1c) on general CVD risk. We constructed 10–year general cardiometabolic risk score functions and evaluated its predictive performance in 2012–2013. Results HbA1c was significantly related to general CVD risk. The proposed cardiometabolic general CVD risk model showed good predictive performance as determined by cross-validated discrimination (male C-index=0.703, 95% CI=0.668, 0.734; female C-index=0.762, 95% CI=0.726, 0.801) and calibration (lack-of-fit χ2=9.05 [p=0.338] and 12.54 [p=0.128] for men and women, respectively). Conclusions This study presents a risk factor algorithm that provides a convenient and informative way to quantify cardiometabolic risk based on modifiable risk factors that can motivate an individual’s commitment to prevention and intervention. PMID:24951039

Surface and subsurface geologic risk factors to ground water affecting brownfield redevelopment potential.

PubMed

Kaufman, Martin M; Murray, Kent S; Rogers, Daniel T

2003-01-01

A model is created for assessing the redevelopment potential of brownfields. The model is derived from a space and time conceptual framework that identifies and measures the surface and subsurface risk factors present at brownfield sites. The model then combines these factors with a contamination extent multiplier at each site to create an index of redevelopment potential. Results from the application of the model within an urbanized watershed demonstrate clear differences between the redevelopment potential present within five different near-surface geologic units, with those units containing clay being less vulnerable to subsurface contamination. With and without the extent multiplier, the total risk present at the brownfield sites within all the geologic units is also strongly correlated to the actual costs of remediation. Thus, computing the total surface and subsurface risk within a watershed can help guide the remediation efforts at broad geographic scales, and prioritize the locations for redevelopment.

A measurement model of perinatal stressors: identifying risk for postnatal emotional distress in mothers of high-risk infants.

PubMed

DeMier, R L; Hynan, M T; Hatfield, R F; Varner, M W; Harris, H B; Manniello, R L

2000-01-01

A measurement model of perinatal stressors was first evaluated for reliability and then used to identify risk factors for postnatal emotional distress in high-risk mothers. In Study 1, six measures (gestational age of the baby, birthweight, length of the baby's hospitalization, a postnatal complications rating for the infant, and Apgar scores at 1 and 5 min) were obtained from chart reviews of preterm births at two different hospitals. Confirmatory factor analyses revealed that the six measures could be accounted for by three factors: (a) Infant Maturity, (b) Apgar Ratings, and (c) Complications. In Study 2, a modified measurement model indicated that Infant Maturity and Complications were significant predictors of postnatal emotional distress in an additional sample of mothers. This measurement model may also be useful in predicting (a) other measures of psychological distress in parents, and (b) measures of cognitive and motor development in infants.

A Review on Automatic Mammographic Density and Parenchymal Segmentation

PubMed Central

He, Wenda; Juette, Arne; Denton, Erika R. E.; Oliver, Arnau

2015-01-01

Breast cancer is the most frequently diagnosed cancer in women. However, the exact cause(s) of breast cancer still remains unknown. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective way to tackle breast cancer. There are more than 70 common genetic susceptibility factors included in the current non-image-based risk prediction models (e.g., the Gail and the Tyrer-Cuzick models). Image-based risk factors, such as mammographic densities and parenchymal patterns, have been established as biomarkers but have not been fully incorporated in the risk prediction models used for risk stratification in screening and/or measuring responsiveness to preventive approaches. Within computer aided mammography, automatic mammographic tissue segmentation methods have been developed for estimation of breast tissue composition to facilitate mammographic risk assessment. This paper presents a comprehensive review of automatic mammographic tissue segmentation methodologies developed over the past two decades and the evidence for risk assessment/density classification using segmentation. The aim of this review is to analyse how engineering advances have progressed and the impact automatic mammographic tissue segmentation has in a clinical environment, as well as to understand the current research gaps with respect to the incorporation of image-based risk factors in non-image-based risk prediction models. PMID:26171249

A discriminant analysis prediction model of non-syndromic cleft lip with or without cleft palate based on risk factors.

PubMed

Li, Huixia; Luo, Miyang; Luo, Jiayou; Zheng, Jianfei; Zeng, Rong; Du, Qiyun; Fang, Junqun; Ouyang, Na

2016-11-23

A risk prediction model of non-syndromic cleft lip with or without cleft palate (NSCL/P) was established by a discriminant analysis to predict the individual risk of NSCL/P in pregnant women. A hospital-based case-control study was conducted with 113 cases of NSCL/P and 226 controls without NSCL/P. The cases and the controls were obtained from 52 birth defects' surveillance hospitals in Hunan Province, China. A questionnaire was administered in person to collect the variables relevant to NSCL/P by face to face interviews. Logistic regression models were used to analyze the influencing factors of NSCL/P, and a stepwise Fisher discriminant analysis was subsequently used to construct the prediction model. In the univariate analysis, 13 influencing factors were related to NSCL/P, of which the following 8 influencing factors as predictors determined the discriminant prediction model: family income, maternal occupational hazards exposure, premarital medical examination, housing renovation, milk/soymilk intake in the first trimester of pregnancy, paternal occupational hazards exposure, paternal strong tea drinking, and family history of NSCL/P. The model had statistical significance (lambda = 0.772, chi-square = 86.044, df = 8, P < 0.001). Self-verification showed that 83.8 % of the participants were correctly predicted to be NSCL/P cases or controls with a sensitivity of 74.3 % and a specificity of 88.5 %. The area under the receiver operating characteristic curve (AUC) was 0.846. The prediction model that was established using the risk factors of NSCL/P can be useful for predicting the risk of NSCL/P. Further research is needed to improve the model, and confirm the validity and reliability of the model.

Testing the Hypothesis of the Multidimensional Model of Anorexia Nervosa in Adolescents.

ERIC Educational Resources Information Center

Lyon, Maureen; Chatoor, Irene; Atkins, Darlene; Silber, Tomas; Mosimann, James; Gray, James

1997-01-01

Tested six hypothesized risk factors of a model for anorexia nervosa. Results confirmed three of the risk factors: family history of depression, feelings of ineffectiveness, and poor interceptive awareness. Alcohol and drug abuse also figured prominently in the family history of patients with anorexia nervosa. (RJM)

Consumer risk perceptions toward agricultural biotechnology, self-protection, and food demand: the case of milk in the United States.

PubMed

Zepeda, Lydia; Douthitt, Robin; You, So-Ye

2003-10-01

This study is an econometric systems approach to modeling the factors and linkages affecting risk perceptions toward agricultural biotechnology, self-protection actions, and food demand. This model is applied to milk in the United States, but it can be adapted to other products as well as other categories of risk perceptions. The contribution of this formulation is the ability to examine how explanatory factors influence risk perceptions and whether they translate into behavior and ultimately what impact this has on aggregate markets. Hadden's outrage factors on heightening risk perceptions are among the factors examined. In particular, the article examines the role of labeling as a means of permitting informed consent to mitigate outrage factors. The effects of attitudinal, economic, and demographic factors on risk perceptions are also explored, as well as the linkage between risk perceptions, consumer behavior, and food demand. Because risk perceptions and self-protection actions are categorical variables and demand is a continuous variable, the model is estimated as a two-stage mixed system with a covariance correction procedure suggested by Amemiya. The findings indicate that it is the availability of labeling, not the price difference, between that labeled milk and milk produced with recombinant bovine Somatotropin (rbST) that significantly affects consumer's selection of rbST-free milk. The results indicate that greater availability of labeled milk would not only significantly increase the proportion of consumers who purchased labeled milk, its availability would also reduce the perception of risk associated with rbST, whether consumers purchase it or not. In other words, availability of rbST-free milk translates into lower risk perceptions toward milk produced with rbST.

Predictions of space radiation fatality risk for exploration missions

NASA Astrophysics Data System (ADS)

Cucinotta, Francis A.; To, Khiet; Cacao, Eliedonna

2017-05-01

In this paper we describe revisions to the NASA Space Cancer Risk (NSCR) model focusing on updates to probability distribution functions (PDF) representing the uncertainties in the radiation quality factor (QF) model parameters and the dose and dose-rate reduction effectiveness factor (DDREF). We integrate recent heavy ion data on liver, colorectal, intestinal, lung, and Harderian gland tumors with other data from fission neutron experiments into the model analysis. In an earlier work we introduced distinct QFs for leukemia and solid cancer risk predictions, and here we consider liver cancer risks separately because of the higher RBE's reported in mouse experiments compared to other tumors types, and distinct risk factors for liver cancer for astronauts compared to the U.S. population. The revised model is used to make predictions of fatal cancer and circulatory disease risks for 1-year deep space and International Space Station (ISS) missions, and a 940 day Mars mission. We analyzed the contribution of the various model parameter uncertainties to the overall uncertainty, which shows that the uncertainties in relative biological effectiveness (RBE) factors at high LET due to statistical uncertainties and differences across tissue types and mouse strains are the dominant uncertainty. NASA's exposure limits are approached or exceeded for each mission scenario considered. Two main conclusions are made: 1) Reducing the current estimate of about a 3-fold uncertainty to a 2-fold or lower uncertainty will require much more expansive animal carcinogenesis studies in order to reduce statistical uncertainties and understand tissue, sex and genetic variations. 2) Alternative model assumptions such as non-targeted effects, increased tumor lethality and decreased latency at high LET, and non-cancer mortality risks from circulatory diseases could significantly increase risk estimates to several times higher than the NASA limits.

Making predictions of mangrove deforestation: a comparison of two methods in Kenya.

PubMed

Rideout, Alasdair J R; Joshi, Neha P; Viergever, Karin M; Huxham, Mark; Briers, Robert A

2013-11-01

Deforestation of mangroves is of global concern given their importance for carbon storage, biogeochemical cycling and the provision of other ecosystem services, but the links between rates of loss and potential drivers or risk factors are rarely evaluated. Here, we identified key drivers of mangrove loss in Kenya and compared two different approaches to predicting risk. Risk factors tested included various possible predictors of anthropogenic deforestation, related to population, suitability for land use change and accessibility. Two approaches were taken to modelling risk; a quantitative statistical approach and a qualitative categorical ranking approach. A quantitative model linking rates of loss to risk factors was constructed based on generalized least squares regression and using mangrove loss data from 1992 to 2000. Population density, soil type and proximity to roads were the most important predictors. In order to validate this model it was used to generate a map of losses of Kenyan mangroves predicted to have occurred between 2000 and 2010. The qualitative categorical model was constructed using data from the same selection of variables, with the coincidence of different risk factors in particular mangrove areas used in an additive manner to create a relative risk index which was then mapped. Quantitative predictions of loss were significantly correlated with the actual loss of mangroves between 2000 and 2010 and the categorical risk index values were also highly correlated with the quantitative predictions. Hence, in this case the relatively simple categorical modelling approach was of similar predictive value to the more complex quantitative model of mangrove deforestation. The advantages and disadvantages of each approach are discussed, and the implications for mangroves are outlined. © 2013 Blackwell Publishing Ltd.

The road traffic crashes as a neglected public health concern; an observational study from Iranian population.

PubMed

Bakhtiyari, Mahmood; Delpisheh, Ali; Monfared, Ayad Bahadori; Kazemi-Galougahi, Mohammad Hassan; Mehmandar, Mohammad Reza; Riahi, Mohammad; Salehi, Masoud; Mansournia, Mohammad Ali

2015-01-01

Traffic crashes are multifactorial events caused by human factors, technical issues, and environmental conditions. The present study aimed to determine the role of human factors in traffic crashes in Iran using the proportional odds regression model. The database of all traffic crashes in Iran in 2010 (n = 592, 168) registered through the "COM.114" police forms was investigated. Human risk factors leading to traffic crashes were determined and the odds ratio (OR) of each risk factor was estimated using an ordinal regression model and adjusted for potential confounding factors such as age, gender, and lighting status within and outside of cities. The drivers' mean age ± standard deviation was 34.1 ± 14.0 years. The most prevalent risk factors leading to death within cities were disregarding traffic rules and regulations (45%), driver rushing (31%), and alcohol consumption (12.3%). Using the proportional odds regression model, alcohol consumption was the most significant human risk factor in traffic crashes within cities (OR = 6.5, 95% confidence interval [CI], 4.88-8.65) and outside of cities (OR = 1.73, 95% CI, 1.22-3.29). Public health strategies and preventive policies should be focused on more common human risk factors such as disregarding traffic rules and regulations, drivers' rushing, and alcohol consumption due to their greater population attributable fraction and more intuitive impacts on society.

A Patient Risk Model of Chemotherapy-Induced Febrile Neutropenia: Lessons Learned From the ANC Study Group.

PubMed

Lyman, Gary H; Poniewierski, Marek S

2017-12-01

Neutropenia and its complications, including febrile neutropenia (FN), represent major toxicities associated with cancer chemotherapy, resulting in considerable morbidity, mortality, and costs. The myeloid growth factors such as granulocyte colony-stimulating factor (G-CSF) have been shown to reduce the risk of neutropenia complications while enabling safe and effective chemotherapy dose intensity. Concerns about the high costs of these agents along with limited physician adherence to clinical practice guidelines, resulting in both overuse and underuse, has stimulated interest in models for individual patient risk assessment to guide appropriate use of G-CSF. In a model developed and validated by the ANC Study Group, half of patients were classified as high risk and half as low risk based on patient-, disease-, and treatment-related factors. This model has been further validated in an independent patient population. Physician-assessed risk of FN, as well as the decision to use prophylactic CSF, has been shown to correlate poorly with the FN risk estimated by the model. Additional modeling efforts in both adults and children receiving cancer treatment have been reported. Identification of patients at a high individual risk for FN and its consequences may offer the potential for optimal chemotherapy delivery and patient outcomes. Likewise, identification of patients at low risk for neutropenic events may reduce costs when such supportive care is not warranted. This article reviews and summarizes FN modeling studies and the opportunities for personalizing supportive care in patients receiving chemotherapy. Copyright © 2017 by the National Comprehensive Cancer Network.

Multimethod prediction of physical parent-child aggression risk in expectant mothers and fathers with Social Information Processing theory.

PubMed

Rodriguez, Christina M; Smith, Tamika L; Silvia, Paul J

2016-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants' own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Violent reinjury risk assessment instrument (VRRAI) for hospital-based violence intervention programs.

PubMed

Kramer, Erik J; Dodington, James; Hunt, Ava; Henderson, Terrell; Nwabuo, Adaobi; Dicker, Rochelle; Juillard, Catherine

2017-09-01

Violent injury is the second most common cause of death among 15- to 24-year olds in the US. Up to 58% of violently injured youth return to the hospital with a second violent injury. Hospital-based violence intervention programs (HVIPs) have been shown to reduce injury recidivism through intensive case management. However, no validated guidelines for risk assessment strategies in the HVIP setting have been reported. We aimed to use qualitative methods to investigate the key components of risk assessments employed by HVIP case managers and to propose a risk assessment model based on this qualitative analysis. An established academic hospital-affiliated HVIP served as the nexus for this research. Thematic saturation was reached with 11 semi-structured interviews and two focus groups conducted with HVIP case managers and key informants identified through snowball sampling. Interactions were analyzed by a four-member team using Nvivo 10, employing the constant comparison method. Risk factors identified were used to create a set of models presented in two follow-up HVIP case managers and leadership focus groups. Eighteen key themes within seven domains (environment, identity, mental health, behavior, conflict, indicators of lower risk, and case management) and 141 potential risk factors for use in the risk assessment framework were identified. The most salient factors were incorporated into eight models that were presented to the HVIP case managers. A 29-item algorithmic structured professional judgment model was chosen. We identified four tiers of risk factors for violent reinjury that were incorporated into a proposed risk assessment instrument, VRRAI. Copyright © 2017 Elsevier Inc. All rights reserved.

Examination of Substance Use, Risk Factors, and Protective Factors on Student Academic Test Score Performance.

PubMed

Arthur, Michael W; Brown, Eric C; Briney, John S; Hawkins, J David; Abbott, Robert D; Catalano, Richard F; Becker, Linda; Langer, Michael; Mueller, Martin T

2015-08-01

School administrators and teachers face difficult decisions about how best to use school resources to meet academic achievement goals. Many are hesitant to adopt prevention curricula that are not focused directly on academic achievement. Yet, some have hypothesized that prevention curricula can remove barriers to learning and, thus, promote achievement. We examined relationships among school levels of student substance use and risk and protective factors that predict adolescent problem behaviors and achievement test performance. Hierarchical generalized linear models were used to predict associations involving school-averaged levels of substance use and risk and protective factors and students' likelihood of meeting achievement test standards on the Washington Assessment of Student Learning, statistically controlling for demographic and economic factors known to be associated with achievement. Levels of substance use and risk/protective factors predicted the academic test score performance of students. Many of these effects remained significant even after controlling for model covariates. Implementing prevention programs that target empirically identified risk and protective factors has the potential to have a favorable effect on students' academic achievement. © 2015, American School Health Association.

Effects of the Communities That Care Model in Pennsylvania on Change in Adolescent Risk and Problem Behaviors

PubMed Central

Jones, Damon; Greenberg, Mark T.; Osgood, D. Wayne; Bontempo, Daniel

2015-01-01

Despite the public health burden of adolescent substance use, delinquency, and other problem behavior, few comprehensive models of disseminating evidence-based prevention programs to communities have demonstrated positive youth outcomes at a population level, capacity to maintain program fidelity, and sustainability. We examined whether the Communities That Care (CTC; Hawkins and Catalano 1992) model had a positive impact on risk/protective factors and academic and behavioral outcomes among adolescents in a quasi-experimental effectiveness study. We conducted a longitudinal study of CTC in Pennsylvania utilizing biannual surveillance data collected through anonymous in-school student surveys. We utilized multilevel models to examine CTC impact on change in risk/protective factors, grades, delinquency, and substance use over time. Youth in CTC communities demonstrated less growth in delinquency, but not substance use, than youth in non-CTC communities. Levels of risk factors increased more slowly, and protective factors and academic performance decreased more slowly, among CTC community grade-cohorts that were exposed to evidence-based, universal prevention programs than comparison grade cohorts. Community coalitions can affect adolescent risk and protective behaviors at a population level when evidence-based programs are utilized. CTC represents an effective model for disseminating such programs. PMID:20020209

An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes.

PubMed

Shapira, Stav; Novack, Lena; Bar-Dayan, Yaron; Aharonson-Daniel, Limor

2016-01-01

A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities' preparedness and response capabilities and to mitigate future consequences. An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model's algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel. the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard. The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties.

The cardiovascular robustness hypothesis: Unmasking young adults' hidden risk for premature cardiovascular death.

PubMed

Kraushaar, Lutz E; Dressel, Alexander

2018-03-01

An undetected high risk for premature death of cardiovascular disease (CVD) among individuals with low-to-moderate risk factor levels is an acknowledged obstacle to CVD prevention. In this paper, we present the hypothesis that the vasculature's robustness against risk factor load will complement conventional risk factor models as a novel stratifier of risk. Figuratively speaking, mortality risk prediction without robustness scoring is akin to predicting the breaking risk of a lake's ice sheet considering load only while disregarding the sheet's bearing strength. Taking the cue from systems biology, which defines robustness as the ability to maintain function against internal and external challenges, we develop a robustness score from the physical parameters that comprehensively quantitate cardiovascular function. We derive the functional parameters using a recently introduced novel system, VascAssist 2 (iSYMED GmbH, Butzbach, Germany). VascAssist 2 (VA) applies the electronic-hydraulic analogy to a digital model of the arterial tree, replicating non-invasively acquired pule pressure waves by modulating the electronic equivalents of the physical parameters that describe in vivo arterial hemodynamics. As the latter is also subject to aging-associated degeneration which (a) progresses at inter-individually different rates, and which (b) affects the biomarker-mortality association, we express the robustness score as a correction factor to calendar age (CA), the dominant risk factor in all CVD risk factor models. We then propose a method for the validation of the score against known time-to-event data in reference populations. Our conceptualization of robustness implies that risk factor-challenged individuals with low robustness scores will face preferential elimination from the population resulting in a significant robustness-CA correlation in this strata absent in the unchallenged stratum. Hence, we also present an outline of a cross-sectional study design suitable to test this hypothesis. We finally discuss the objections that may validly be raised against our robustness hypothesis, and how available evidence encourages us to refute these objections. Copyright © 2018 Elsevier Ltd. All rights reserved.

Media Violence and Other Aggression Risk Factors in Seven Nations.

PubMed

Anderson, Craig A; Suzuki, Kanae; Swing, Edward L; Groves, Christopher L; Gentile, Douglas A; Prot, Sara; Lam, Chun Pan; Sakamoto, Akira; Horiuchi, Yukiko; Krahé, Barbara; Jelic, Margareta; Liuqing, Wei; Toma, Roxana; Warburton, Wayne A; Zhang, Xue-Min; Tajima, Sachi; Qing, Feng; Petrescu, Poesis

2017-07-01

Cultural generality versus specificity of media violence effects on aggression was examined in seven countries (Australia, China, Croatia, Germany, Japan, Romania, the United States). Participants reported aggressive behaviors, media use habits, and several other known risk and protective factors for aggression. Across nations, exposure to violent screen media was positively associated with aggression. This effect was partially mediated by aggressive cognitions and empathy. The media violence effect on aggression remained significant even after statistically controlling a number of relevant risk and protective factors (e.g., abusive parenting, peer delinquency), and was similar in magnitude to effects of other risk factors. In support of the cumulative risk model, joint effects of different risk factors on aggressive behavior in each culture were larger than effects of any individual risk factor.

Structural Model of psychological risk and protective factors affecting on quality of life in patients with coronary heart disease: A psychocardiology model

PubMed Central

Nekouei, Zohreh Khayyam; Yousefy, Alireza; Doost, Hamid Taher Neshat; Manshaee, Gholamreza; Sadeghei, Masoumeh

2014-01-01

Background: Conducted researches show that psychological factors may have a very important role in the etiology, continuity and consequences of coronary heart diseases. This study has drawn the psychological risk and protective factors and their effects in patients with coronary heart diseases (CHD) in a structural model. It aims to determine the structural relations between psychological risk and protective factors with quality of life in patients with coronary heart disease. Materials and Methods: The present cross-sectional and correlational studies were conducted using structural equation modeling. The study sample included 398 patients of coronary heart disease in the university referral Hospital, as well as other city health care centers in Isfahan city. They were selected based on random sampling method. Then, in case, they were executed the following questionnaires: Coping with stressful situations (CISS- 21), life orientation (LOT-10), general self-efficacy (GSE-10), depression, anxiety and stress (DASS-21), perceived stress (PSS-14), multidimensional social support (MSPSS-12), alexithymia (TAS-20), spiritual intelligence (SQ-23) and quality of life (WHOQOL-26). Results: The results showed that protective and risk factors could affect the quality of life in patients with CHD with factor loadings of 0.35 and −0.60, respectively. Moreover, based on the values of the framework of the model such as relative chi-square (CMIN/DF = 3.25), the Comparative Fit Index (CFI = 0.93), the Parsimony Comparative Fit Index (PCFI = 0.68), the Root Mean Square Error of Approximation (RMSEA = 0.07) and details of the model (significance of the relationships) it has been confirmed that the psychocardiological structural model of the study is the good fitting model. Conclusion: This study was among the first to research the different psychological risk and protective factors of coronary heart diseases in the form of a structural model. The results of this study have emphasized the necessity of noticing the psychological factors in primary prevention by preventive programs and in secondary prevention by rehabilitation centers to improve the quality of life of the people with heart diseases. PMID:24778660

General principles of institutional risks influence on pension systems

NASA Astrophysics Data System (ADS)

Nepp, A. N.; Shilkov, A. A.; Sheveleva, A. Y.; Mamedbakov, M. R.

2016-12-01

This paper examines the tools used to study the influence of institutional factors on investment returns. The research object are the tools used in the evaluation of institutional risks in the pension system, in particular, the correlation model of factors impacting on the `anti-director' index, econometric estimates combining the different determinants of savings, the model of endogenous institutional change, etc. Research work focusing on issues of institutional factors affecting pension systems (authored by La Porta, Guiso, Gianetti, El-Mekkaouide Freitas, Neyapti B., and others) is reviewed. The model is examined in terms of the impact of institutional risks on pension systems, especially with regard to the funded part. The study identified the following factors that affect financial institutions, including pension institutions: management quality, regulation quality, rule of law, political stability, and corruption control.

[Study on the infectious risk model of AIDS among men who have sex with men in Guangzhou].

PubMed

Hu, Pei; Zhong, Fei; Cheng, Wei-Bin; Xu, Hui-Fang; Ling, Li

2012-07-01

To develop a human immune deficiency virus (HIV) infection risk appraisal model suitable for men who has sex with men (MSM) in Guangzhou, and to provide tools for follow-up the outcomes on health education and behavior intervention. A cros-sectional study was conducted in Guangzhou from 2008 to 2010. Based on the HIV surveillance data, the main risk factors of HIV infection among MSM were screened by means of logistic regression. Degree on relative risk was transformed into risk scores by adopting the statistics models. Individual risk scores, group risk scores and individual infection risk in comparison with usual MSM groups could then be calculated according to the rate of exposure on those risk factors appeared in data from the surveillance programs. Risk factors related to HIV infection among MSM and the quantitative assessment standard (risk scores and risk scores table of population groups) for those factors were set up by multiple logistic regression, including age, location of registered residence, monthly income, major location for finding their sexual partners, HIV testing in the past year, age when having the first sexual intercourse, rate of condom use in the past six months, symptoms related to sexually transmitted diseases (STDs) and syphilis in particular. The average risk score of population was 6.06, with risk scores for HIV positive and negative as 3.10 and 18.08 respectively (P < 0.001). The rates of HIV infection for different score groups were 0.9%, 2.0%, 7.0%, 14.4% and 33.3%, respectively. The sensitivity and specificity on the prediction of scores were 54.4% and 75.4% respectively, with the accuracy rate as 74.2%. HIV infection risk model could be used to quantify and classify the individual's infectious status and related factors among MSM more directly and effectively, so as to help the individuals to identify their high-risk behaviors as well as lifestyles. We felt that it could also serve as an important tool used for personalized HIV health education and behavior intervention programs.

Does the Outcome of a First Pregnancy Predict Depression, Suicidal Ideation, or Lower Self-esteem? Data from the National Comorbidity Survey

PubMed Central

Steinberg, Julia R.; Becker, Davida; Henderson, Jillian T.

2010-01-01

The present study examines the risk of depression, suicidal ideation, and lower self-esteem following an abortion versus delivery, adjusting for important correlates. Using the National Comorbidity Survey, we examined how first pregnancy outcome (abortion versus delivery) related to subsequent major depression, suicidal ideation, and self-esteem. Models controlling for risk factors, such as background and economic factors, pre-pregnancy violence experience, and pre-pregnancy mental health, as well as a model with all risk factors, were examined. When no risk factors were entered in the model, women who had abortions were more likely to have subsequent depression (OR = 1.53, CI 1.05-2.22) and suicidal ideation (OR = 2.02, CI 1.40-2.92), but not more likely to have lower self-esteem (B = -.02). When all risk factors were entered, pregnancy outcome was not significantly related to later depression (OR = .87, CI .54-1.37) and suicidal ideation (OR = 1.19, CI .70-2.02); predictors of mental health following abortion and delivery included pre-pregnancy depression, suicidal ideation, and sexual violence. Policies and practices implemented in response to the claim that abortion hurts women are not supported by our findings. Efforts to support women’s mental health should focus on known risk factors, such as programs to address gender-based violence, rather than abortion history. PMID:21486261

Risk Factors for Unidirectional and Bidirectional Intimate Partner Violence among Young Adults

ERIC Educational Resources Information Center

Renner, Lynette M.; Whitney, Stephen D.

2012-01-01

Objective: The purpose of this study was to identify common and unique risk factors for intimate partner violence (IPV) among young adults in relationships. Guided by two models of IPV, the same set of risk factors was used to examine outcomes of unidirectional (perpetration or victimization) and bidirectional (reciprocal) IPV separately for males…

Developmental Pathway Modeling in Considering Behavior Problems in Young Russian Children

ERIC Educational Resources Information Center

Ruchkin, Vladislav; Gilliam, Walter S.; Mayes, Linda

2008-01-01

In planning interventions it is essential to understand how adverse risk factors in early childhood are associated with child mental health problems, whether some types of problems can be better explained by the specific risk factors, and whether early risk factors are differently related to different types of child behavior problems. A community…

Development of a risk assessment tool for projecting individualized probabilities of developing breast cancer for Chinese women.

PubMed

Wang, Yuan; Gao, Ying; Battsend, Munkhzul; Chen, Kexin; Lu, Wenli; Wang, Yaogang

2014-11-01

The optimal approach regarding breast cancer screening for Chinese women is unclear due to the relative low incidence rate. A risk assessment tool may be useful for selection of high-risk subsets of population for mammography screening in low-incidence and resource-limited developing country. The odd ratios for six main risk factors of breast cancer were pooled by review manager after a systematic research of literature. Health risk appraisal (HRA) model was developed to predict an individual's risk of developing breast cancer in the next 5 years from current age. The performance of this HRA model was assessed based on a first-round screening database. Estimated risk of breast cancer increased with age. Increases in the 5-year risk of developing breast cancer were found with the existence of any of included risk factors. When individuals who had risk above median risk (3.3‰) were selected from the validation database, the sensitivity is 60.0% and the specificity is 47.8%. The unweighted area under the curve (AUC) was 0.64 (95% CI = 0.50-0.78). The risk-prediction model reported in this article is based on a combination of risk factors and shows good overall predictive power, but it is still weak at predicting which particular women will develop the disease. It would be very helpful for the improvement of a current model if more population-based prospective follow-up studies were used for the validation.

A multiple biomarker risk score for guiding clinical decisions using a decision curve approach.

PubMed

Hughes, Maria F; Saarela, Olli; Blankenberg, Stefan; Zeller, Tanja; Havulinna, Aki S; Kuulasmaa, Kari; Yarnell, John; Schnabel, Renate B; Tiret, Laurence; Salomaa, Veikko; Evans, Alun; Kee, Frank

2012-08-01

We assessed whether a cardiovascular risk model based on classic risk factors (e.g. cholesterol, blood pressure) could refine disease prediction if it included novel biomarkers (C-reactive protein, N-terminal pro-B-type natriuretic peptide, troponin I) using a decision curve approach which can incorporate clinical consequences. We evaluated whether a model including biomarkers and classic risk factors could improve prediction of 10 year risk of cardiovascular disease (CVD; chronic heart disease and ischaemic stroke) against a classic risk factor model using a decision curve approach in two prospective MORGAM cohorts. This included 7739 men and women with 457 CVD cases from the FINRISK97 cohort; and 2524 men with 259 CVD cases from PRIME Belfast. The biomarker model improved disease prediction in FINRISK across the high-risk group (20-40%) but not in the intermediate risk group, at the 23% risk threshold net benefit was 0.0033 (95% CI 0.0013-0.0052). However, in PRIME Belfast the net benefit of decisions guided by the decision curve was improved across intermediate risk thresholds (10-20%). At p(t) = 10% in PRIME, the net benefit was 0.0059 (95% CI 0.0007-0.0112) with a net increase in 6 true positive cases per 1000 people screened and net decrease of 53 false positive cases per 1000 potentially leading to 5% fewer treatments in patients not destined for an event. The biomarker model improves 10-year CVD prediction at intermediate and high-risk thresholds and in particular, could be clinically useful at advising middle-aged European males of their CVD risk.

Risk factors for in-hospital post-hip fracture mortality.

PubMed

Frost, Steven A; Nguyen, Nguyen D; Black, Deborah A; Eisman, John A; Nguyen, Tuan V

2011-09-01

Approximately 10% of hip fracture patients die during hospitalization; however, it is not clear what risk factors contribute to the excess mortality. This study sought to examine risk factors of, and to develop prognostic model for, predicting in-hospital mortality among hip fracture patients. We studied outcomes among 410 men and 1094 women with a hip fracture who were admitted to a major-teaching-hospital in Sydney (Australia) between 1997 and 2007. Clinical data, including concomitant illnesses, were obtained from inpatient data. The primary outcome of the study was in-hospital mortality regardless of length of stay. A Log-binomial regression model was used to identify risk factors for in-hospital mortality. Using the identified risk factors, prognostic nomograms were developed for predicting short term risk of mortality for an individual. The median duration of hospitalization was 9 days. During hospitalization, the risk of mortality was higher in men (9%) than in women (4%). After adjusting for multiple risk factors, increased risk of in-hospital mortality was associated with advancing age (rate ratio [RR] for each 10-year increase in age: 1.91 95% confidence interval [CI]: 1.47 to 2.49), in men (RR 2.13; 95% CI 1.41 to 3.22), and the presence of comorbid conditions on admission (RR for one or more comorbid conditions vs. none: 2.30; 95% CI 1.52 to 3.48). Specifically, the risk of mortality was increased in patients with a pre-existing congestive heart failure (RR 3.02; 95% CI: 1.65 to 5.54), and liver disease (RR 4.75; 95% CI: 1.87 to 12.1). These factors collectively accounted for 69% of the risk for in-hospital mortality. A nomogram was developed from these risk factors to individualize the risk of in-hospital death following a hip fracture. The area under the receiver operating characteristic curve of the final model containing age, sex and comorbid conditions was 0.76. These data suggest that among hip fracture patients, advancing age, gender (men), and pre-existing concomitant diseases such as congestive heart failure and liver disease were the main risk factors for in-hospital mortality. The nomogram developed from this study can be used to convey useful prognostic information to help guide treatment decisions. Copyright © 2011 Elsevier Inc. All rights reserved.

Risk factors of non-specific spinal pain in childhood.

PubMed

Szita, Julia; Boja, Sara; Szilagyi, Agnes; Somhegyi, Annamaria; Varga, Peter Pal; Lazary, Aron

2018-05-01

Non-specific spinal pain can occur at all ages and current evidence suggests that pediatric non-specific spinal pain is predictive for adult spinal conditions. A 5-year long, prospective cohort study was conducted to identify the lifestyle and environmental factors leading to non-specific spinal pain in childhood. Data were collected from school children aged 7-16 years, who were randomly selected from three different geographic regions in Hungary. The risk factors were measured with a newly developed patient-reported questionnaire (PRQ). The quality of the instrument was assessed by the reliability with the test-retest method. Test (N = 952) and validity (N = 897) datasets were randomly formed. Risk factors were identified with uni- and multivariate logistic regression models and the predictive performance of the final model was evaluated using the receiver operating characteristic (ROC) method. The final model was built up by seven risk factors for spinal pain for days; age > 12 years, learning or watching TV for more than 2 h/day, uncomfortable school-desk, sleeping problems, general discomfort and positive familiar medical history (χ 2  = 101.07; df = 8; p < 0.001). The probabilistic performance was confirmed with ROC analysis on the test and validation cohorts (AUC = 0.76; 0.71). A simplified risk scoring system showed increasing possibility for non-specific spinal pain depending on the number of the identified risk factors (χ 2  = 65.0; df = 4; p < 0.001). Seven significant risk factors of non-specific spinal pain in childhood were identified using the new, easy to use and reliable PRQ which makes it possible to stratify the children according to their individual risk. These slides can be retrieved under Electronic Supplementary Material.

Prediction of acute kidney injury within 30 days of cardiac surgery.

PubMed

Ng, Shu Yi; Sanagou, Masoumeh; Wolfe, Rory; Cochrane, Andrew; Smith, Julian A; Reid, Christopher Michael

2014-06-01

To predict acute kidney injury after cardiac surgery. The study included 28,422 cardiac surgery patients who had had no preoperative renal dialysis from June 2001 to June 2009 in 18 hospitals. Logistic regression analyses were undertaken to identify the best combination of risk factors for predicting acute kidney injury. Two models were developed, one including the preoperative risk factors and another including the pre-, peri-, and early postoperative risk factors. The area under the receiver operating characteristic curve was calculated, using split-sample internal validation, to assess model discrimination. The incidence of acute kidney injury was 5.8% (1642 patients). The mortality for patients who experienced acute kidney injury was 17.4% versus 1.6% for patients who did not. On validation, the area under the curve for the preoperative model was 0.77, and the Hosmer-Lemeshow goodness-of-fit P value was .06. For the postoperative model area under the curve was 0.81 and the Hosmer-Lemeshow P value was .6. Both models had good discrimination and acceptable calibration. Acute kidney injury after cardiac surgery can be predicted using preoperative risk factors alone or, with greater accuracy, using pre-, peri-, and early postoperative risk factors. The ability to identify high-risk individuals can be useful in preoperative patient management and for recruitment of appropriate patients to clinical trials. Prediction in the early stages of postoperative care can guide subsequent intensive care of patients and could also be the basis of a retrospective performance audit tool. Copyright © 2014 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.

A developmental etiological model for drug abuse in men.

PubMed

Kendler, Kenneth S; Ohlsson, Henrik; Edwards, Alexis C; Sundquist, Jan; Sundquist, Kristina

2017-10-01

We attempt to develop a relatively comprehensive structural model of risk factors for drug abuse (DA) in Swedish men that illustrates developmental and mediational processes. We examined 20 risk factors for DA in 48,369 men undergoing conscription examinations in 1969-70 followed until 2011 when 2.34% (n=1134) of them had DA ascertained in medical, criminal and pharmacy registries. Risk factors were organized into four developmental tiers reflecting i) birth, ii) childhood/early adolescence, iii) late adolescence, and iv) young adulthood. Structural equational model fitting was performed using Mplus. The best fitting model explained 47.8% of the variance in DA. The most prominent predictors, in order, were: early adolescent externalizing behavior, early adult criminal behavior, early adolescent internalizing behavior, early adult unemployment, early adult alcohol use disorder, and late adolescent drug use. Two major inter-connecting pathways emerged reflecting i) genetic/familial risk and ii) family dysfunction and psychosocial adversity. Generated on a first and tested on a second random half of the sample, a model from these variables predicted DA with an ROC area under the curve of 83.6%. Fifty-nine percent of DA cases arose from subjects in the top decile of risk. DA in men is a highly multifactorial syndrome with risk arising from familial-genetic, psychosocial, behavioral and psychological factors acting and interacting over development. Among the multiple predisposing factors for DA, a range of psychosocial adversities, externalizing psychopathology and lack of social constraints in early adulthood are predominant. Copyright © 2017 Elsevier B.V. All rights reserved.

Endometrial cancer risk prediction including serum-based biomarkers: results from the EPIC cohort.

PubMed

Fortner, Renée T; Hüsing, Anika; Kühn, Tilman; Konar, Meric; Overvad, Kim; Tjønneland, Anne; Hansen, Louise; Boutron-Ruault, Marie-Christine; Severi, Gianluca; Fournier, Agnès; Boeing, Heiner; Trichopoulou, Antonia; Benetou, Vasiliki; Orfanos, Philippos; Masala, Giovanna; Agnoli, Claudia; Mattiello, Amalia; Tumino, Rosario; Sacerdote, Carlotta; Bueno-de-Mesquita, H B As; Peeters, Petra H M; Weiderpass, Elisabete; Gram, Inger T; Gavrilyuk, Oxana; Quirós, J Ramón; Maria Huerta, José; Ardanaz, Eva; Larrañaga, Nerea; Lujan-Barroso, Leila; Sánchez-Cantalejo, Emilio; Butt, Salma Tunå; Borgquist, Signe; Idahl, Annika; Lundin, Eva; Khaw, Kay-Tee; Allen, Naomi E; Rinaldi, Sabina; Dossus, Laure; Gunter, Marc; Merritt, Melissa A; Tzoulaki, Ioanna; Riboli, Elio; Kaaks, Rudolf

2017-03-15

Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were selected into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including etiologic markers on independent pathways and genetic markers may further improve discrimination. © 2016 UICC.

Taste phenotype associates with cardiovascular disease risk factors via diet quality in multivariate modeling.

PubMed

Sharafi, Mastaneh; Rawal, Shristi; Fernandez, Maria Luz; Huedo-Medina, Tania B; Duffy, Valerie B

2018-05-08

Sensations from foods and beverages drive dietary choices, which in turn, affect risk of diet-related diseases. Perception of these sensation varies with environmental and genetic influences. This observational study aimed to examine associations between chemosensory phenotype, diet and cardiovascular disease (CVD) risk. Reportedly healthy women (n = 110, average age 45 ± 9 years) participated in laboratory-based measures of chemosensory phenotype (taste and smell function, propylthiouracil (PROP) bitterness) and CVD risk factors (waist circumference, blood pressure, serum lipids). Diet variables included preference and intake of sweet/high-fat foods, dietary restraint, and diet quality based on reported preference (Healthy Eating Preference Index-HEPI) and intake (Healthy Eating Index-HEI). We found that females who reported high preference yet low consumption of sweet/high-fat foods had the highest dietary restraint and depressed quinine taste function. PROP nontasters were more likely to report lower diet quality; PROP supertasters more likely to consume but not like a healthy diet. Multivariate structural models were fitted to identify predictors of CVD risk factors. Reliable latent taste (quinine taste function, PROP tasting) and smell (odor intensity) variables were identified, with taste explaining more variance in the CVD risk factors. Lower bitter taste perception was associated with elevated risk. In multivariate models, the HEPI completely mediated the taste-adiposity and taste-HDL associations and partially mediated the taste-triglyceride or taste-systolic blood pressure associations. The taste-LDL pathway was significant and direct. The HEI could not replace HEPI in adequate models. However, using a latent diet quality variable with HEPI and HEI, increased the strength of association between diet quality and adiposity or CVD risk factors. In conclusion, bitter taste phenotype was associated with CVD risk factors via diet quality, particularly when assessed by level of food liking/disliking. Copyright © 2018 Elsevier Inc. All rights reserved.

Air pollution and health risks due to vehicle traffic.

PubMed

Zhang, Kai; Batterman, Stuart

2013-04-15

Traffic congestion increases vehicle emissions and degrades ambient air quality, and recent studies have shown excess morbidity and mortality for drivers, commuters and individuals living near major roadways. Presently, our understanding of the air pollution impacts from congestion on roads is very limited. This study demonstrates an approach to characterize risks of traffic for on- and near-road populations. Simulation modeling was used to estimate on- and near-road NO2 concentrations and health risks for freeway and arterial scenarios attributable to traffic for different traffic volumes during rush hour periods. The modeling used emission factors from two different models (Comprehensive Modal Emissions Model and Motor Vehicle Emissions Factor Model version 6.2), an empirical traffic speed-volume relationship, the California Line Source Dispersion Model, an empirical NO2-NOx relationship, estimated travel time changes during congestion, and concentration-response relationships from the literature, which give emergency doctor visits, hospital admissions and mortality attributed to NO2 exposure. An incremental analysis, which expresses the change in health risks for small increases in traffic volume, showed non-linear effects. For a freeway, "U" shaped trends of incremental risks were predicted for on-road populations, and incremental risks are flat at low traffic volumes for near-road populations. For an arterial road, incremental risks increased sharply for both on- and near-road populations as traffic increased. These patterns result from changes in emission factors, the NO2-NOx relationship, the travel delay for the on-road population, and the extended duration of rush hour for the near-road population. This study suggests that health risks from congestion are potentially significant, and that additional traffic can significantly increase risks, depending on the type of road and other factors. Further, evaluations of risk associated with congestion must consider travel time, the duration of rush-hour, congestion-specific emission estimates, and uncertainties. Copyright © 2013 Elsevier B.V. All rights reserved.

Air pollution and health risks due to vehicle traffic

PubMed Central

Zhang, Kai; Batterman, Stuart

2014-01-01

Traffic congestion increases vehicle emissions and degrades ambient air quality, and recent studies have shown excess morbidity and mortality for drivers, commuters and individuals living near major roadways. Presently, our understanding of the air pollution impacts from congestion on roads is very limited. This study demonstrates an approach to characterize risks of traffic for on- and near-road populations. Simulation modeling was used to estimate on- and near-road NO2 concentrations and health risks for freeway and arterial scenarios attributable to traffic for different traffic volumes during rush hour periods. The modeling used emission factors from two different models (Comprehensive Modal Emissions Model and Motor Vehicle Emissions Factor Model version 6.2), an empirical traffic speed–volume relationship, the California Line Source Dispersion Model, an empirical NO2–NOx relationship, estimated travel time changes during congestion, and concentration–response relationships from the literature, which give emergency doctor visits, hospital admissions and mortality attributed to NO2 exposure. An incremental analysis, which expresses the change in health risks for small increases in traffic volume, showed non-linear effects. For a freeway, “U” shaped trends of incremental risks were predicted for on-road populations, and incremental risks are flat at low traffic volumes for near-road populations. For an arterial road, incremental risks increased sharply for both on- and near-road populations as traffic increased. These patterns result from changes in emission factors, the NO2–NOx relationship, the travel delay for the on-road population, and the extended duration of rush hour for the near-road population. This study suggests that health risks from congestion are potentially significant, and that additional traffic can significantly increase risks, depending on the type of road and other factors. Further, evaluations of risk associated with congestion must consider travel time, the duration of rush-hour, congestion-specific emission estimates, and uncertainties. PMID:23500830

Contribution of biopsychosocial risk factors to nonspecific neck pain in office workers: A path analysis model.

PubMed

Paksaichol, Arpalak; Lawsirirat, Chaipat; Janwantanakul, Prawit

2015-01-01

The etiology of nonspecific neck pain is widely accepted to be multifactorial. Each risk factor has not only direct effects on neck pain but may also exert effects indirectly through other risk factors. This study aimed to test this hypothesized model in office workers. A one-year prospective cohort study of 559 healthy office workers was conducted. At baseline, a self-administered questionnaire and standardized physical examination were employed to gather biopsychosocial data. Follow-up data were collected every month for the incidence of neck pain. A regression model was built to analyze factors predicting the onset of neck pain. Path analysis was performed to examine direct and indirect associations between identified risk factors and neck pain. The onset of neck pain was predicted by female gender, having a history of neck pain, monitor position not being level with the eyes, and frequently perceived muscular tension, of which perceived muscular tension was the strongest effector on the onset of neck pain. Gender, history of neck pain, and monitor height had indirect effects on neck pain that were mediated through perceived muscular tension. History of neck pain was the most influential effector on perceived muscular tension. The results of this study support the hypothesis that each risk factors may contribute to the development of neck pain both directly and indirectly. The combination of risk factors necessary to cause neck pain is likely occupation specific. Perceived muscular tension is hypothesized to be an early sign of musculoskeletal symptoms.

Inability to predict postpartum hemorrhage: insights from Egyptian intervention data

PubMed Central

2011-01-01

Background Knowledge on how well we can predict primary postpartum hemorrhage (PPH) can help policy makers and health providers design current delivery protocols and PPH case management. The purpose of this paper is to identify risk factors and determine predictive probabilities of those risk factors for primary PPH among women expecting singleton vaginal deliveries in Egypt. Methods From a prospective cohort study, 2510 pregnant women were recruited over a six-month period in Egypt in 2004. PPH was defined as blood loss ≥ 500 ml. Measures of blood loss were made every 20 minutes for the first 4 hours after delivery using a calibrated under the buttocks drape. Using all variables available in the patients' charts, we divided them in ante-partum and intra-partum factors. We employed logistic regression to analyze socio-demographic, medical and past obstetric history, and labor and delivery outcomes as potential PPH risk factors. Post-model predicted probabilities were estimated using the identified risk factors. Results We found a total of 93 cases of primary PPH. In multivariate models, ante-partum hemoglobin, history of previous PPH, labor augmentation and prolonged labor were significantly associated with PPH. Post model probability estimates showed that even among women with three or more risk factors, PPH could only be predicted in 10% of the cases. Conclusions The predictive probability of ante-partum and intra-partum risk factors for PPH is very low. Prevention of PPH to all women is highly recommended. PMID:22123123

Temperament factors and dimensional, latent bifactor models of child psychopathology: Transdiagnostic and specific associations in two youth samples.

PubMed

Hankin, Benjamin L; Davis, Elysia Poggi; Snyder, Hannah; Young, Jami F; Glynn, Laura M; Sandman, Curt A

2017-06-01

Common emotional and behavioral symptoms co-occur and are associated with core temperament factors. This study investigated links between temperament and dimensional, latent psychopathology factors, including a general common psychopathology factor (p factor) and specific latent internalizing and externalizing liabilities, as captured by a bifactor model, in two independent samples of youth. Specifically, we tested the hypothesis that temperament factors of negative affectivity (NA), positive affectivity (PA), and effortful control (EC) could serve as both transdiagnostic and specific risks in relation to recent bifactor models of child psychopathology. Sample 1 included 571 youth (average age 13.6, SD =2.37, range 9.3-17.5) with both youth and parent report. Sample 2 included 554 preadolescent children (average age 7.7, SD =1.35, range =5-11 years) with parent report. Structural equation modeling showed that the latent bifactor models fit in both samples. Replicated in both samples, the p factor was associated with lower EC and higher NA (transdiagnostic risks). Several specific risks replicated in both samples after controlling for co-occurring symptoms via the p factor: internalizing was associated with higher NA and lower PA, lower EC related to externalizing problems. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Retinopathy of prematurity: a review of risk factors and their clinical significance.

PubMed

Kim, Sang Jin; Port, Alexander D; Swan, Ryan; Campbell, J Peter; Chan, R V Paul; Chiang, Michael F

2018-04-19

Retinopathy of prematurity (ROP) is a retinal vasoproliferative disease that affects premature infants. Despite improvements in neonatal care and management guidelines, ROP remains a leading cause of childhood blindness worldwide. Current screening guidelines are primarily based on two risk factors: birth weight and gestational age; however, many investigators have suggested other risk factors, including maternal factors, prenatal and perinatal factors, demographics, medical interventions, comorbidities of prematurity, nutrition, and genetic factors. We review the existing literature addressing various possible ROP risk factors. Although there have been contradictory reports, and the risk may vary between different populations, understanding ROP risk factors is essential to develop predictive models, to gain insights into pathophysiology of retinal vascular diseases and diseases of prematurity, and to determine future directions in management of and research in ROP. Copyright © 2018 Elsevier Inc. All rights reserved.

Comparison of the risk factors effects between two populations: two alternative approaches illustrated by the analysis of first and second kidney transplant recipients

PubMed Central

2013-01-01

Background Whereas the prognosis of second kidney transplant recipients (STR) compared to the first ones has been frequently analyzed, no study has addressed the issue of comparing the risk factor effects on graft failure between both groups. Methods Here, we propose two alternative strategies to study the heterogeneity of risk factors between two groups of patients: (i) a multiplicative-regression model for relative survival (MRS) and (ii) a stratified Cox model (SCM) specifying the graft rank as strata and assuming subvectors of the explicatives variables. These developments were motivated by the analysis of factors associated with time to graft failure (return-to-dialysis or patient death) in second kidney transplant recipients (STR) compared to the first ones. Estimation of the parameters was based on partial likelihood maximization. Monte-Carlo simulations associated with bootstrap re-sampling was performed to calculate the standard deviations for the MRS. Results We demonstrate, for the first time in renal transplantation, that: (i) male donor gender is a specific risk factor for STR, (ii) the adverse effect of recipient age is enhanced for STR and (iii) the graft failure risk related to donor age is attenuated for STR. Conclusion While the traditional Cox model did not provide original results based on the renal transplantation literature, the proposed relative and stratified models revealed new findings that are useful for clinicians. These methodologies may be of interest in other medical fields when the principal objective is the comparison of risk factors between two populations. PMID:23915191

Stroke risk perception among participants of a stroke awareness campaign

PubMed Central

Kraywinkel, Klaus; Heidrich, Jan; Heuschmann, Peter U; Wagner, Markus; Berger, Klaus

2007-01-01

Background Subjective risk factor perception is an important component of the motivation to change unhealthy life styles. While prior studies assessed cardiovascular risk factor knowledge, little is known about determinants of the individual perception of stroke risk. Methods Survey by mailed questionnaire among 1483 participants of a prior public stroke campaign in Germany. Participants had been informed about their individual stroke risk based on the Framingham stroke risk score. Stroke risk factor knowledge, perception of lifetime stroke risk and risk factor status were included in the questionnaire, and the determinants of good risk factor knowledge and high stroke risk perception were identified using logistic regression models. Results Overall stroke risk factor knowledge was good with 67–96% of the participants recognizing established risk factors. The two exceptions were diabetes (recognized by 49%) and myocardial infarction (57%). Knowledge of a specific factor was superior among those affected by it. 13% of all participants considered themselves of having a high stroke risk, 55% indicated a moderate risk. All major risk factors contributed significantly to the perception of being at high stroke risk, but the effects of age, sex and education were non-significant. Poor self-rated health was additionally associated with high individual stroke risk perception. Conclusion Stroke risk factor knowledge was high in this study. The self perception of an increased stroke risk was associated with established risk factors as well as low perception of general health. PMID:17371603

Combining quantitative and qualitative breast density measures to assess breast cancer risk.

PubMed

Kerlikowske, Karla; Ma, Lin; Scott, Christopher G; Mahmoudzadeh, Amir P; Jensen, Matthew R; Sprague, Brian L; Henderson, Louise M; Pankratz, V Shane; Cummings, Steven R; Miglioretti, Diana L; Vachon, Celine M; Shepherd, John A

2017-08-22

Accurately identifying women with dense breasts (Breast Imaging Reporting and Data System [BI-RADS] heterogeneously or extremely dense) who are at high breast cancer risk will facilitate discussions of supplemental imaging and primary prevention. We examined the independent contribution of dense breast volume and BI-RADS breast density to predict invasive breast cancer and whether dense breast volume combined with Breast Cancer Surveillance Consortium (BCSC) risk model factors (age, race/ethnicity, family history of breast cancer, history of breast biopsy, and BI-RADS breast density) improves identifying women with dense breasts at high breast cancer risk. We conducted a case-control study of 1720 women with invasive cancer and 3686 control subjects. We calculated ORs and 95% CIs for the effect of BI-RADS breast density and Volpara™ automated dense breast volume on invasive cancer risk, adjusting for other BCSC risk model factors plus body mass index (BMI), and we compared C-statistics between models. We calculated BCSC 5-year breast cancer risk, incorporating the adjusted ORs associated with dense breast volume. Compared with women with BI-RADS scattered fibroglandular densities and second-quartile dense breast volume, women with BI-RADS extremely dense breasts and third- or fourth-quartile dense breast volume (75% of women with extremely dense breasts) had high breast cancer risk (OR 2.87, 95% CI 1.84-4.47, and OR 2.56, 95% CI 1.87-3.52, respectively), whereas women with extremely dense breasts and first- or second-quartile dense breast volume were not at significantly increased breast cancer risk (OR 1.53, 95% CI 0.75-3.09, and OR 1.50, 95% CI 0.82-2.73, respectively). Adding continuous dense breast volume to a model with BCSC risk model factors and BMI increased discriminatory accuracy compared with a model with only BCSC risk model factors (C-statistic 0.639, 95% CI 0.623-0.654, vs. C-statistic 0.614, 95% CI 0.598-0.630, respectively; P < 0.001). Women with dense breasts and fourth-quartile dense breast volume had a BCSC 5-year risk of 2.5%, whereas women with dense breasts and first-quartile dense breast volume had a 5-year risk ≤ 1.8%. Risk models with automated dense breast volume combined with BI-RADS breast density may better identify women with dense breasts at high breast cancer risk than risk models with either measure alone.

Risk factors for lower extremity injuries among half marathon and marathon runners of the Lage Landen Marathon Eindhoven 2012: A prospective cohort study in the Netherlands.

PubMed

van Poppel, D; de Koning, J; Verhagen, A P; Scholten-Peeters, G G M

2016-02-01

To determine risk factors for running injuries during the Lage Landen Marathon Eindhoven 2012. Prospective cohort study. Population-based study. This study included 943 runners. Running injuries after the Lage Landen Marathon. Sociodemographic and training-related factors as well as lifestyle factors were considered as potential risk factors and assessed in a questionnaire 1 month before the running event. The association between potential risk factors and injuries was determined, per running distance separately, using univariate and multivariate logistic regression analysis. In total, 154 respondents sustained a running injury. Among the marathon runners, in the univariate model, body mass index ≥ 26 kg/m(2), ≤ 5 years of running experience, and often performing interval training, were significantly associated with running injuries, whereas in the multivariate model only ≤ 5 years of running experience and not performing interval training on a regular basis were significantly associated with running injuries. Among marathon runners, no multivariate model could be created because of the low number of injuries and participants. This study indicates that interval training on a regular basis may be recommended to marathon runners to reduce the risk of injury. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Graphs to estimate an individualized risk of breast cancer.

PubMed

Benichou, J; Gail, M H; Mulvihill, J J

1996-01-01

Clinicians who counsel women about their risk for developing breast cancer need a rapid method to estimate individualized risk (absolute risk), as well as the confidence limits around that point. The Breast Cancer Detection Demonstration Project (BCDDP) model (sometimes called the Gail model) assumes no genetic model and simultaneously incorporates five risk factors, but involves cumbersome calculations and interpolations. This report provides graphs to estimate the absolute risk of breast cancer from the BCDDP model. The BCDDP recruited 280,000 women from 1973 to 1980 who were monitored for 5 years. From this cohort, 2,852 white women developed breast cancer and 3,146 controls were selected, all with complete risk-factor information. The BCDDP model, previously developed from these data, was used to prepare graphs that relate a specific summary relative-risk estimate to the absolute risk of developing breast cancer over intervals of 10, 20, and 30 years. Once a summary relative risk is calculated, the appropriate graph is chosen that shows the 10-, 20-, or 30-year absolute risk of developing breast cancer. A separate graph gives the 95% confidence limits around the point estimate of absolute risk. Once a clinician rules out a single gene trait that predisposes to breast cancer and elicits information on age and four risk factors, the tables and figures permit an estimation of a women's absolute risk of developing breast cancer in the next three decades. These results are intended to be applied to women who undergo regular screening. They should be used only in a formal counseling program to maximize a woman's understanding of the estimates and the proper use of them.

Global importation and population risk factors for measles in New Zealand: a case study for highly immunized populations.

PubMed

Hayman, D T S; Marshall, J C; French, N P; Carpenter, T E; Roberts, M G; Kiedrzynski, T

2017-07-01

As endemic measles is eliminated through immunization, countries must determine the risk factors for the importation of measles into highly immunized populations to target control measures. Despite eliminating endemic measles, New Zealand suffers from outbreaks after introductions from abroad, enabling us to use it as a model for measles introduction risk. We used a generalized linear model to analyze risk factors for 1137 measles cases from 2007 to June 2014, provide estimates of national immunity levels, and model measles importation risk. People of European ethnicity made up the majority of measles cases. Age is a positive risk factor, particularly 0-2-year-olds and 5-17-year-old Europeans, along with increased wealth. Pacific islanders were also at greater risk, but due to 0-2-year-old cases. Despite recent high measles, mumps, and rubella vaccine immunization coverage, overall population immunity against measles remains ~90% and is lower in people born between 1982 and 2005. Greatest measles importation risk is during December, and countries predicted to be sources have historical connections and highest travel rates (Australia and UK), followed by Asian countries with high travel rates and higher measles incidences. Our results suggest measles importation due to travel is seeding measles outbreaks, and immunization levels are insufficient to continue to prevent outbreaks because of heterogeneous immunity in the population, leaving particular age groups at risk.

Changes in diet, cardiovascular risk factors and modelled cardiovascular risk following diagnosis of diabetes: 1-year results from the ADDITION-Cambridge trial cohort.

PubMed

Savory, L A; Griffin, S J; Williams, K M; Prevost, A T; Kinmonth, A-L; Wareham, N J; Simmons, R K

2014-02-01

To describe change in self-reported diet and plasma vitamin C, and to examine associations between change in diet and cardiovascular disease risk factors and modelled 10-year cardiovascular disease risk in the year following diagnosis of Type 2 diabetes. Eight hundred and sixty-seven individuals with screen-detected diabetes underwent assessment of self-reported diet, plasma vitamin C, cardiovascular disease risk factors and modelled cardiovascular disease risk at baseline and 1 year (n = 736) in the ADDITION-Cambridge trial. Multivariable linear regression was used to quantify the association between change in diet and cardiovascular disease risk at 1 year, adjusting for change in physical activity and cardio-protective medication. Participants reported significant reductions in energy, fat and sodium intake, and increases in fruit, vegetable and fibre intake over 1 year. The reduction in energy was equivalent to an average-sized chocolate bar; the increase in fruit was equal to one plum per day. There was a small increase in plasma vitamin C levels. Increases in fruit intake and plasma vitamin C were associated with small reductions in anthropometric and metabolic risk factors. Increased vegetable intake was associated with an increase in BMI and waist circumference. Reductions in fat, energy and sodium intake were associated with reduction in HbA1c , waist circumference and total cholesterol/modelled cardiovascular disease risk, respectively. Improvements in dietary behaviour in this screen-detected population were associated with small reductions in cardiovascular disease risk, independently of change in cardio-protective medication and physical activity. Dietary change may have a role to play in the reduction of cardiovascular disease risk following diagnosis of diabetes. © 2013 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.

Risk factors for intimate partner violence in women in the Rakai Community Cohort Study, Uganda, from 2000 to 2009

PubMed Central

2013-01-01

Background Intimate partner violence (IPV) is a significant public health problem. There is a lack of data on IPV risk factors from longitudinal studies and from low and middle income countries. Identifying risk factors is needed to inform the design of appropriate IPV interventions. Methods Data were from the Rakai Community Cohort Study annual surveys between 2000 and 2009. Female participants who had at least one sexual partner during this period and had data on IPV over the study period were included in analyses (N = 15081). Factors from childhood and early adulthood as well as contemporary factors were considered in separate models. Logistic regression was used to assess early risk factors for IPV during the study period. Longitudinal data analysis was used to assess contemporary risk factors in the past year for IPV in the current year, using a population-averaged multivariable logistic regression model. Results Risk factors for IPV from childhood and early adulthood included sexual abuse in childhood or adolescence, earlier age at first sex, lower levels of education, and forced first sex. Contemporary risk factors included younger age, being married, relationships of shorter duration, having a partner who is the same age or younger, alcohol use before sex by women and by their partners, and thinking that violence is acceptable. HIV infection and pregnancy were not associated with an increased odds of IPV. Conclusions Using longitudinal data, this study identified a number of risk factors for IPV. These findings are useful for the development of prevention strategies to prevent and mitigate IPV in women. PMID:23759123

Accounting for Selection Bias in Studies of Acute Cardiac Events.

PubMed

Banack, Hailey R; Harper, Sam; Kaufman, Jay S

2018-06-01

In cardiovascular research, pre-hospital mortality represents an important potential source of selection bias. Inverse probability of censoring weights are a method to account for this source of bias. The objective of this article is to examine and correct for the influence of selection bias due to pre-hospital mortality on the relationship between cardiovascular risk factors and all-cause mortality after an acute cardiac event. The relationship between the number of cardiovascular disease (CVD) risk factors (0-5; smoking status, diabetes, hypertension, dyslipidemia, and obesity) and all-cause mortality was examined using data from the Atherosclerosis Risk in Communities (ARIC) study. To illustrate the magnitude of selection bias, estimates from an unweighted generalized linear model with a log link and binomial distribution were compared with estimates from an inverse probability of censoring weighted model. In unweighted multivariable analyses the estimated risk ratio for mortality ranged from 1.09 (95% confidence interval [CI], 0.98-1.21) for 1 CVD risk factor to 1.95 (95% CI, 1.41-2.68) for 5 CVD risk factors. In the inverse probability of censoring weights weighted analyses, the risk ratios ranged from 1.14 (95% CI, 0.94-1.39) to 4.23 (95% CI, 2.69-6.66). Estimates from the inverse probability of censoring weighted model were substantially greater than unweighted, adjusted estimates across all risk factor categories. This shows the magnitude of selection bias due to pre-hospital mortality and effect on estimates of the effect of CVD risk factors on mortality. Moreover, the results highlight the utility of using this method to address a common form of bias in cardiovascular research. Copyright © 2018 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.

Conceptual heuristic models of the interrelationships between obesity and the occupational environment

PubMed Central

Pandalai, Sudha P; Schulte, Paul A; Miller, Diane B

2015-01-01

Objective Research and interventions targeting the relationship between work, its attendant occupational hazards, and obesity are evolving but merit further consideration in the public health arena. In this discussion paper, conceptual heuristic models are described examining the role of obesity as both a risk factor and health outcome in the occupational setting. Methods PubMed was searched using specific criteria from 2000 and onwards for evidence to support conceptual models in which obesity serves as a risk factor for occupational disease or an outcome of occupational exposures. Nine models are presented: four where obesity is a risk factor and five where it is an adverse effect. Results A broad range of work-related health effects are associated with obesity including musculoskeletal disorders, asthma, liver disease, and cardiovascular disease, among others. Obesity can be associated with occupational hazards such as shift work, sedentary work, job stress, and exposure to some chemicals. Conclusion Identification of combinations of risk factors pertinent to obesity in the occupational environment will provide important guidance for research and prevention. PMID:23588858

A Moderator Model of Alcohol Use and Dating Aggression among Young Adults.

PubMed

Collibee, Charlene; Furman, Wyndol

2018-03-01

Dating aggression has been identified as a priority public health concern. Although alcohol use is a known robust risk factor for dating aggression involvement, such usage is neither necessary nor sufficient for dating aggression involvement. As such, a growing topic of interest is a better understanding of when, and for whom, alcohol use increases risk. A theoretical moderator model posits that associations between alcohol use and dating aggression involvement vary depending on both background (e.g., psychopathology) and situational (e.g., relationship characteristics) risk factors. Alcohol use is thought to be more strongly associated with dating aggression in the context of these other risk factors. Using an intensive longitudinal design, we collected six waves of data spanning 6 months from 120 participants (60 females; M age W1 = 22.44). Alcohol use and relationship risk were both associated with increases in dating aggression involvement. Consistent with a moderator model, interactions emerged between alcohol use and relationship risk for subsequent dating aggression involvement. The findings underscore the importance of alcohol use and relationship risk for the development of intervention and prevention programs.

High-sensitive factor I and C-reactive protein based biomarkers for coronary artery disease.

PubMed

Zhao, Qing; Du, Jian-Shi; Han, Dong-Mei; Ma, Ying

2014-01-01

An analysis of high-sensitive factor I and C-reactive proteins as biomarkers for coronary artery disease has been performed from 19 anticipated cohort studies that included 21,567 participants having no information about coronary artery disease. Besides, the clinical implications of statin therapy initiated due to assessment of factor I and C-reactive proteins have also been modeled during studies. The measure of risk discrimination (C-index) was increased (by 0.0101) as per the prognostic model for coronary artery disease with respect to sex, smoking status, age, blood pressure, total cholesterol level along with diabetic history characteristic parameters. The C-index was further raised by 0.0045 and 0.0053 when factor I and C-reactive proteins based information were added, respectively which finally predicted 10-year risk categories as: high (> 20%), medium (10% to < 20%), and low (< 10%) risks. We found 2,254 persons (among 15,000 adults (age ≥ 45 years)) would initially be classified as being at medium risk for coronary artery disease when only conventional risk factors were used as calculated risk. Besides, persons with a predicted risk of more than 20% as well as for persons suffering from other risk factors (i.e. diabetes), statin therapy was initiated (irrespective of their decade old predicted risk). We conclude that under current treatment guidelines assessment of factor I and C-reactive proteins levels (as biomarker) in people at medium risk for coronary artery disease could prevent one additional coronary artery disease risk over a period a decade for every 390-500 people screened.

Theoretical Risk and Prevention Model for Secondary Health Conditions and Mortality After SCI: 15 Years of Research

PubMed Central

Krause, James S.; Saunders, Lee L.; DiPiro, Nicole D.; Reed, Karla S.

2013-01-01

Background: To successfully prevent secondary health conditions (SHCs) and promote longevity after spinal cord injury (SCI), we must first understand the risk factors precipitating their occurrence and develop strategies to address these risk factors. Conceptual models may aid in identifying the nature of SHCs and guide research, clinical practice, and the development of prevention strategies. Objective: Our purpose is to review and refine an existing theoretical risk and prevention model (TRPM) as a means of classifying risk and protective factors for SHCs and mortality after SCI and for identifying points of intervention. Methods: We describe conceptual work within the field of SCI research and SHCs, including a description of the TRPM, a review of research using the TRPM, and conceptual enhancements to the TRPM based on previous research. Conclusions: The enhanced TRPM directs research to the timing and chronicity of the SHCs and their relationship with overall health and physiologic decline. Future research should identify differences in the nature of SHCs, the extent to which they relate to risk and protective factors, and the degree to which they may be prevented with appropriate research-based strategies. PMID:23459002

Improving Global Vascular Risk Prediction with Behavioral and Anthropometric Factors: The Multi-ethnic Northern Manhattan Cohort Study

PubMed Central

Sacco, Ralph L.; Khatri, Minesh; Rundek, Tatjana; Xu, Qiang; Gardener, Hannah; Boden-Albala, Bernadette; Di Tullio, Marco R.; Homma, Shunichi; Elkind, Mitchell SV; Paik, Myunghee C

2010-01-01

Objective To improve global vascular risk prediction with behavioral and anthropometric factors. Background Few cardiovascular risk models are designed to predict the global vascular risk of MI, stroke, or vascular death in multi-ethnic individuals, and existing schemes do not fully include behavioral risk factors. Methods A randomly-derived, population-based, prospective cohort of 2737 community participants free of stroke and coronary artery disease were followed annually for a median of 9.0 years in the Northern Manhattan Study (mean age 69 years; 63.2% women; 52.7% Hispanic, 24.9% African-American, 19.9% white). A global vascular risk score (GVRS) predictive of stroke, myocardial infarction, or vascular death was developed by adding variables to the traditional Framingham cardiovascular variables based on the likelihood ratio criterion. Model utility was assessed through receiver operating characteristics, calibration, and effect on reclassification of subjects. Results Variables which significantly added to the traditional Framingham profile included waist circumference, alcohol consumption, and physical activity. Continuous measures for blood pressure and fasting blood sugar were used instead of hypertension and diabetes. Ten -year event-free probabilities were 0.95 for the first quartile of GVRS, 0.89 for the second quartile, 0.79 for the third quartile, and 0.56 for the fourth quartile. The addition of behavioral factors in our model improved prediction of 10 -year event rates compared to a model restricted to the traditional variables. Conclusion A global vascular risk score that combines both traditional, behavioral, and anthropometric risk factors, uses continuous variables for physiological parameters, and is applicable to non-white subjects could improve primary prevention strategies. PMID:19958966

Development of prognostic model for predicting survival after retrograde placement of ureteral stent in advanced gastrointestinal cancer patients and its evaluation by decision curve analysis.

PubMed

Kawano, Shingo; Komai, Yoshinobu; Ishioka, Junichiro; Sakai, Yasuyuki; Fuse, Nozomu; Ito, Masaaki; Kihara, Kazunori; Saito, Norio

2016-10-01

The aim of this study was to determine risk factors for survival after retrograde placement of ureteral stents and develop a prognostic model for advanced gastrointestinal tract (GIT: esophagus, stomach, colon and rectum) cancer patients. We examined the clinical records of 122 patients who underwent retrograde placement of a ureteral stent against malignant extrinsic ureteral obstruction. A prediction model for survival after stenting was developed. We compared its clinical usefulness with our previous model based on the results from nephrostomy cases by decision curve analysis. Median follow-up period was 201 days (8-1490) and 97 deaths occurred. The 1-year survival rate in this cohort was 29%. Based on multivariate analysis, primary site of colon origin, absence of retroperitoneal lymph node metastasis and serum albumin >3g/dL were significantly associated with a prolonged survival time. To develop a prognostic model, we divided the patients into 3 risk groups of favorable: 0-1 factors (N.=53), intermediate: 2 risk factors (N.=54), and poor: 3 risk factors (N.=15). There were significant differences in the survival profiles of these 3 risk groups (P<0.0001). Decision curve analyses revealed that the current model has a superior net benefit than our previous model for most of the examined probabilities. We have developed a novel prognostic model for GIT cancer patients who were treated with retrograde placement of a ureteral stent. The current model should help urologists and medical oncologists to predict survival in cases of malignant extrinsic ureteral obstruction.

Time Factor in the Theory of Anthropogenic Risk Prediction in Complex Dynamic Systems

NASA Astrophysics Data System (ADS)

Ostreikovsky, V. A.; Shevchenko, Ye N.; Yurkov, N. K.; Kochegarov, I. I.; Grishko, A. K.

2018-01-01

The article overviews the anthropogenic risk models that take into consideration the development of different factors in time that influence the complex system. Three classes of mathematical models have been analyzed for the use in assessing the anthropogenic risk of complex dynamic systems. These models take into consideration time factor in determining the prospect of safety change of critical systems. The originality of the study is in the analysis of five time postulates in the theory of anthropogenic risk and the safety of highly important objects. It has to be stressed that the given postulates are still rarely used in practical assessment of equipment service life of critically important systems. That is why, the results of study presented in the article can be used in safety engineering and analysis of critically important complex technical systems.

Algorithms for the prediction of retinopathy of prematurity based on postnatal weight gain.

PubMed

Binenbaum, Gil

2013-06-01

Current ROP screening guidelines represent a simple risk model with two dichotomized factors, birth weight and gestational age at birth. Pioneering work has shown that tracking postnatal weight gain, a surrogate for low insulin-like growth factor 1, may capture the influence of many other ROP risk factors and improve risk prediction. Models including weight gain, such as WINROP, ROPScore, and CHOP ROP, have demonstrated accurate ROP risk assessment and a potentially large reduction in ROP examinations, compared to current guidelines. However, there is a need for larger studies, and generalizability is limited in countries with developing neonatal care systems. Copyright © 2013 Elsevier Inc. All rights reserved.

The Society of Thoracic Surgeons Congenital Heart Surgery Database Mortality Risk Model: Part 1—Statistical Methodology

PubMed Central

O’Brien, Sean M.; Jacobs, Jeffrey P.; Pasquali, Sara K.; Gaynor, J. William; Karamlou, Tara; Welke, Karl F.; Filardo, Giovanni; Han, Jane M.; Kim, Sunghee; Shahian, David M.; Jacobs, Marshall L.

2016-01-01

Background This study’s objective was to develop a risk model incorporating procedure type and patient factors to be used for case-mix adjustment in the analysis of hospital-specific operative mortality rates after congenital cardiac operations. Methods Included were patients of all ages undergoing cardiac operations, with or without cardiopulmonary bypass, at centers participating in The Society of Thoracic Surgeons Congenital Heart Surgery Database during January 1, 2010, to December 31, 2013. Excluded were isolated patent ductus arteriosus closures in patients weighing less than or equal to 2.5 kg, centers with more than 10% missing data, and patients with missing data for key variables. Data from the first 3.5 years were used for model development, and data from the last 0.5 year were used for assessing model discrimination and calibration. Potential risk factors were proposed based on expert consensus and selected after empirically comparing a variety of modeling options. Results The study cohort included 52,224 patients from 86 centers with 1,931 deaths (3.7%). Covariates included in the model were primary procedure, age, weight, and 11 additional patient factors reflecting acuity status and comorbidities. The C statistic in the validation sample was 0.858. Plots of observed-vs-expected mortality rates revealed good calibration overall and within subgroups, except for a slight overestimation of risk in the highest decile of predicted risk. Removing patient preoperative factors from the model reduced the C statistic to 0.831 and affected the performance classification for 12 of 86 hospitals. Conclusions The risk model is well suited to adjust for case mix in the analysis and reporting of hospital-specific mortality for congenital heart operations. Inclusion of patient factors added useful discriminatory power and reduced bias in the calculation of hospital-specific mortality metrics. PMID:26245502

Specificity of genetic and environmental risk factors for symptoms of cannabis, cocaine, alcohol, caffeine, and nicotine dependence.

PubMed

Kendler, Kenneth S; Myers, John; Prescott, Carol A

2007-11-01

Although genetic risk factors have been found to contribute to dependence on both licit and illicit psychoactive substances, we know little of how these risk factors interrelate. To clarify the structure of genetic and environmental risk factors for symptoms of dependence on cannabis, cocaine, alcohol, caffeine, and nicotine in males and females. Lifetime history by structured clinical interview. General community. Four thousand eight hundred sixty-five members of male-male and female-female pairs from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. Main Outcome Measure Lifetime symptoms of abuse of and dependence on cannabis, cocaine, alcohol, caffeine, and nicotine. Controlling for greater symptom prevalence in males, genetic and environmental parameters could be equated across sexes. Two models explained the data well. The best-fit exploratory model contained 2 genetic factors and 1 individual environmental factor contributing to all substances. The first genetic factor loaded strongly on cocaine and cannabis dependence; the second, on alcohol and nicotine dependence. Nicotine and caffeine had high substance-specific genetic effects. A confirmatory model, which also fit well, contained 1 illicit drug genetic factor--loading only on cannabis and cocaine--and 1 licit drug genetic factor loading on alcohol, caffeine, and nicotine. However, these factors were highly intercorrelated (r = + 0.82). Large substance-specific genetic effects remained for nicotine and caffeine. The pattern of genetic and environmental risk factors for psychoactive substance dependence was similar in males and females. Genetic risk factors for dependence on common psychoactive substances cannot be explained by a single factor. Rather, 2 genetic factors-one predisposing largely to illicit drug dependence, the other primarily to licit drug dependence-are needed. Furthermore, a large proportion of the genetic influences on nicotine and particularly caffeine dependence appear to be specific to those substances.

A Process Model for Assessing Adolescent Risk for Suicide.

ERIC Educational Resources Information Center

Stoelb, Matt; Chiriboga, Jennifer

1998-01-01

This comprehensive assessment process model includes primary, secondary, and situational risk factors and their combined implications and significance in determining an adolescent's level or risk for suicide. Empirical data and clinical intuition are integrated to form a working client model that guides the professional in continuously reassessing…

Precursors of Adolescent Substance Use from Early Childhood and Early Adolescence: Testing a Developmental Cascade Model

PubMed Central

Sitnick, Stephanie; Shaw, Daniel S.; Hyde, Luke

2013-01-01

This study examined developmentally-salient risk and protective factors of adolescent substance use assessed during early childhood and early adolescence using a sample of 310 low-income boys. Child problem behavior and proximal family risk and protective factors (i.e., parenting, maternal depression) during early childhood, as well as child and family factors and peer deviant behavior during adolescence were explored as potential precursors to later substance use during adolescence using structural equation modeling. Results revealed that early childhood risk and protective factors (i.e., child externalizing problems, mothers’ depressive symptomatology, and nurturant parenting) were indirectly related to substance use at the age of 17 via risk and protective factors during early and middle adolescence (i.e., parental knowledge and externalizing problems). The implications of these findings for early prevention and intervention are discussed. PMID:24029248

Developing physical exposure-based back injury risk models applicable to manual handling jobs in distribution centers.

PubMed

Lavender, Steven A; Marras, William S; Ferguson, Sue A; Splittstoesser, Riley E; Yang, Gang

2012-01-01

Using our ultrasound-based "Moment Monitor," exposures to biomechanical low back disorder risk factors were quantified in 195 volunteers who worked in 50 different distribution center jobs. Low back injury rates, determined from a retrospective examination of each company's Occupational Safety and Health Administration (OSHA) 300 records over the 3-year period immediately prior to data collection, were used to classify each job's back injury risk level. The analyses focused on the factors differentiating the high-risk jobs (those having had 12 or more back injuries/200,000 hr of exposure) from the low-risk jobs (those defined as having no back injuries in the preceding 3 years). Univariate analyses indicated that measures of load moment exposure and force application could distinguish between high (n = 15) and low (n = 15) back injury risk distribution center jobs. A three-factor multiple logistic regression model capable of predicting high-risk jobs with very good sensitivity (87%) and specificity (73%) indicated that risk could be assessed using the mean across the sampled lifts of the peak forward and or lateral bending dynamic load moments that occurred during each lift, the mean of the peak push/pull forces across the sampled lifts, and the mean duration of the non-load exposure periods. A surrogate model, one that does not require the Moment Monitor equipment to assess a job's back injury risk, was identified although with some compromise in model sensitivity relative to the original model.

Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort.

PubMed

Abdullah, N; Abdul Murad, N A; Mohd Haniff, E A; Syafruddin, S E; Attia, J; Oldmeadow, C; Kamaruddin, M A; Abd Jalal, N; Ismail, N; Ishak, M; Jamal, R; Scott, R J; Holliday, E G

2017-08-01

Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R 2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. The models including environmental risk factors only had pseudo R 2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10 -4 -4.83 × 10 -12 ) and increased the pseudo R 2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection. Copyright © 2017 The Royal Society for Public Health. All rights reserved.

Youth misperceptions of peer substance use norms: a hidden risk factor in state and community prevention.

PubMed

Wambeam, Rodney A; Canen, Eric L; Linkenbach, Jeff; Otto, Jay

2014-02-01

Effective community prevention of substance abuse involves the integration of policies and programs to address many different risk and protective factors across the social ecology. This study sought to examine whether youth perceptions of peer substance use norms were operating as a risk factor at the same level as other known risk factors in a statewide community prevention effort. Several different analytical techniques were employed to examine the self-reported data from a sample of over 8,000 students in grades 6, 8, 10, and 12 from across Wyoming using a survey based on a risk and protective factor model. The findings of this study revealed that youth misperception of peer substance use norms operate at a level of significance similar to other known risk factors, and these misperceptions are a risk factor that should be measured in order to estimate its relationship with substance use. The measurement of this risk factor has important strategic implications for community prevention.

Testing a cognitive model to predict posttraumatic stress disorder following childbirth.

PubMed

King, Lydia; McKenzie-McHarg, Kirstie; Horsch, Antje

2017-01-14

One third of women describes their childbirth as traumatic and between 0.8 and 6.9% goes on to develop posttraumatic stress disorder (PTSD). The cognitive model of PTSD has been shown to be applicable to a range of trauma samples. However, childbirth is qualitatively different to other trauma types and special consideration needs to be taken when applying it to this population. Previous studies have investigated some cognitive variables in isolation but no study has so far looked at all the key processes described in the cognitive model. This study therefore aimed to investigate whether theoretically-derived variables of the cognitive model explain unique variance in postnatal PTSD symptoms when key demographic, obstetric and clinical risk factors are controlled for. One-hundred and fifty-seven women who were between 1 and 12 months post-partum (M = 6.5 months) completed validated questionnaires assessing PTSD and depressive symptoms, childbirth experience, postnatal social support, trauma memory, peritraumatic processing, negative appraisals, dysfunctional cognitive and behavioural strategies and obstetric as well as demographic risk factors in an online survey. A PTSD screening questionnaire suggested that 5.7% of the sample might fulfil diagnostic criteria for PTSD. Overall, risk factors alone predicted 43% of variance in PTSD symptoms and cognitive behavioural factors alone predicted 72.7%. A final model including both risk factors and cognitive behavioural factors explained 73.7% of the variance in PTSD symptoms, 37.1% of which was unique variance predicted by cognitive factors. All variables derived from Ehlers and Clark's cognitive model significantly explained variance in PTSD symptoms following childbirth, even when clinical, demographic and obstetric were controlled for. Our findings suggest that the CBT model is applicable and useful as a way of understanding and informing the treatment of PTSD following childbirth.

Cumulative impact of common genetic variants and other risk factors on colorectal cancer risk in 42,103 individuals

PubMed Central

Dunlop, Malcolm G.; Tenesa, Albert; Farrington, Susan M.; Ballereau, Stephane; Brewster, David H.; Pharoah, Paul DP.; Schafmayer, Clemens; Hampe, Jochen; Völzke, Henry; Chang-Claude, Jenny; Hoffmeister, Michael; Brenner, Hermann; von Holst, Susanna; Picelli, Simone; Lindblom, Annika; Jenkins, Mark A.; Hopper, John L.; Casey, Graham; Duggan, David; Newcomb, Polly; Abulí, Anna; Bessa, Xavier; Ruiz-Ponte, Clara; Castellví-Bel, Sergi; Niittymäki, Iina; Tuupanen, Sari; Karhu, Auli; Aaltonen, Lauri; Zanke, Brent W.; Hudson, Thomas J.; Gallinger, Steven; Barclay, Ella; Martin, Lynn; Gorman, Maggie; Carvajal-Carmona, Luis; Walther, Axel; Kerr, David; Lubbe, Steven; Broderick, Peter; Chandler, Ian; Pittman, Alan; Penegar, Steven; Campbell, Harry; Tomlinson, Ian; Houlston, Richard S.

2016-01-01

Objective Colorectal cancer (CRC) has a substantial heritable component. Common genetic variation has been shown to contribute to CRC risk. In a large, multi-population study, we set out to assess the feasibility of CRC risk prediction using common genetic variant data, combined with other risk factors. We built a risk prediction model and applied it to the Scottish population using available data. Design Nine populations of European descent were studied to develop and validate colorectal cancer risk prediction models. Binary logistic regression was used to assess the combined effect of age, gender, family history (FH) and genotypes at 10 susceptibility loci that individually only modestly influence colorectal cancer risk. Risk models were generated from case-control data incorporating genotypes alone (n=39,266), and in combination with gender, age and family history (n=11,324). Model discriminatory performance was assessed using 10-fold internal cross-validation and externally using 4,187 independent samples. 10-year absolute risk was estimated by modelling genotype and FH with age- and gender-specific population risks. Results Median number of risk alleles was greater in cases than controls (10 vs 9, p<2.2×10−16), confirmed in external validation sets (Sweden p=1.2×10−6, Finland p=2×10−5). Mean per-allele increase in risk was 9% (OR 1.09; 95% CI 1.05–1.13). Discriminative performance was poor across the risk spectrum (area under curve (AUC) for genotypes alone - 0.57; AUC for genotype/age/gender/FH - 0.59). However, modelling genotype data, FH, age and gender with Scottish population data shows the practicalities of identifying a subgroup with >5% predicted 10-year absolute risk. Conclusion We show that genotype data provides additional information that complements age, gender and FH as risk factors. However, individualized genetic risk prediction is not currently feasible. Nonetheless, the modelling exercise suggests public health potential, since it is possible to stratify the population into CRC risk categories, thereby informing targeted prevention and surveillance. PMID:22490517

Does consideration of either psychological or material disadvantage improve coronary risk prediction? Prospective observational study of Scottish men.

PubMed

Macleod, John; Metcalfe, Chris; Smith, George Davey; Hart, Carole

2007-09-01

To assess the value of psychosocial risk factors in discriminating between individuals at higher and lower risk of coronary heart disease, using risk prediction equations. Prospective observational study. Scotland. 5191 employed men aged 35 to 64 years and free of coronary heart disease at study enrollment Area under receiver operating characteristic (ROC) curves for risk prediction equations including different risk factors for coronary heart disease. During the first 10 years of follow up, 203 men died of coronary heart disease and a further 200 were admitted to hospital with this diagnosis. Area under the ROC curve for the standard Framingham coronary risk factors was 74.5%. Addition of "vital exhaustion" and psychological stress led to areas under the ROC curve of 74.5% and 74.6%, respectively. Addition of current social class and lifetime social class to the standard Framingham equation gave areas under the ROC curve of 74.6% and 74.9%, respectively. In no case was there strong evidence for improved discrimination of the model containing the novel risk factor over the standard model. Consideration of psychosocial risk factors, including those that are strong independent predictors of heart disease, does not substantially influence the ability of risk prediction tools to discriminate between individuals at higher and lower risk of coronary heart disease.

Shared and Unique Risk Factors Underlying Mathematical Disability and Reading and Spelling Disability.

PubMed

Slot, Esther M; van Viersen, Sietske; de Bree, Elise H; Kroesbergen, Evelyn H

2016-01-01

High comorbidity rates have been reported between mathematical learning disabilities (MD) and reading and spelling disabilities (RSD). Research has identified skills related to math, such as number sense (NS) and visuospatial working memory (visuospatial WM), as well as to literacy, such as phonological awareness (PA), rapid automatized naming (RAN) and verbal short-term memory (Verbal STM). In order to explain the high comorbidity rates between MD and RSD, 7-11-year-old children were assessed on a range of cognitive abilities related to literacy (PA, RAN, Verbal STM) and mathematical ability (visuospatial WM, NS). The group of children consisted of typically developing (TD) children (n = 32), children with MD (n = 26), children with RSD (n = 29), and combined MD and RSD (n = 43). It was hypothesized that, in line with the multiple deficit view on learning disorders, at least one unique predictor for both MD and RSD and a possible shared cognitive risk factor would be found to account for the comorbidity between the symptom dimensions literacy and math. Secondly, our hypotheses were that (a) a probabilistic multi-factorial risk factor model would provide a better fit to the data than a deterministic single risk factor model and (b) that a shared risk factor model would provide a better fit than the specific multi-factorial model. All our hypotheses were confirmed. NS and visuospatial WM were identified as unique cognitive predictors for MD, whereas PA and RAN were both associated with RSD. Also, a shared risk factor model with PA as a cognitive predictor for both RSD and MD fitted the data best, indicating that MD and RSD might co-occur due to a shared underlying deficit in phonological processing. Possible explanations are discussed in the context of sample selection and composition. This study shows that different cognitive factors play a role in mathematics and literacy, and that a phonological processing deficit might play a role in the occurrence of MD and RSD.

Risk factors for tuberculosis in Greenland: case-control study.

PubMed

Ladefoged, K; Rendal, T; Skifte, T; Andersson, M; Søborg, B; Koch, A

2011-01-01

Despite several efforts aiming at disease control, the incidence of tuberculosis (TB) remains high in Greenland, averaging 131 per 100,000 population during the period 1998-2007. The purpose of the present study was to disclose risk factors for TB. A case-control study was performed among 146 patients diagnosed with TB in the period 2004-2006. For each patient, four healthy age- and sex-matched control persons living in the same district were included. All participants completed a questionnaire regarding socio-demographic and lifestyle factors. Risk factor analyses were carried out using logistic regression models. Factors associated with TB were Inuit ethnicity, living in a small settlement, unemployment, no access to tap water, no bathroom or flushing toilet, underweight, smoking, frequent intake of alcohol and immunosuppressive treatment. The multivariate model showed that Inuit ethnicity (OR 15.3), living in a settlement (OR 5.1), being unemployed (OR 4.1) and frequent alcohol use (OR 3.1) were independent determinants of risk. Unemployment was associated with the highest population-attributable risk (29%). Risk factors associated with living in a settlement should be further explored and an investigation of genetic susceptibility is warranted.

Association Between Cardiovascular Disease Risk Factors and Rotator Cuff Tendinopathy: A Cross-Sectional Study.

PubMed

Applegate, Kara Arnold; Thiese, Matthew S; Merryweather, Andrew S; Kapellusch, Jay; Drury, David L; Wood, Eric; Kendall, Richard; Foster, James; Garg, Arun; Hegmann, Kurt T

2017-02-01

Recent evidence has found potential associations between cardiovascular disease (CVD) risk factors and common musculoskeletal disorders. We evaluated possible associations between risk factors and both glenohumeral joint pain and rotator cuff tendinopathy. Data from WISTAH hand study participants (n = 1226) were assessed for associations between Framingham Heart Study CVD risk factors and both health outcomes. A strong association was observed between CVD risk scores and both glenohumeral joint pain and rotator cuff tendinopathy. Peak odds ratios (ORs) of the adjusted models were 4.55 [95% confidence interval (95% CI) 1.97 to 10.31] and 5.97 (95% CI 2.12 to 16.83), respectively. The results show a dose-response trend of increasing risk. Individual risk factors were associated with both outcomes. Combined, CVD risk factors demonstrated a strong correlation with glenohumeral joint pain and an even stronger correlation with rotator cuff tendinopathy. Results suggest a potentially modifiable disease mechanism.

Patient-specific risk factors are predictive for postoperative adverse events in colorectal surgery: an American College of Surgeons National Surgical Quality Improvement Program-based analysis.

PubMed

Kohut, Adrian Y; Liu, James J; Stein, David E; Sensenig, Richard; Poggio, Juan L

2015-02-01

Pay-for-performance measures incorporate surgical site infection rates into reimbursement algorithms without accounting for patient-specific risk factors predictive for surgical site infections and other adverse postoperative outcomes. Using American College of Surgeons National Surgical Quality Improvement Program data of 67,445 colorectal patients, multivariable logistic regression was performed to determine independent risk factors associated with various measures of adverse postoperative outcomes. Notable patient-specific factors included (number of models containing predictor variable; range of odds ratios [ORs] from all models): American Society of Anesthesiologists class 3, 4, or 5 (7 of 7 models; OR 1.25 to 1.74), open procedures (7 of 7 models; OR .51 to 4.37), increased body mass index (6 of 7 models; OR 1.15 to 2.19), history of COPD (6 of 7 models; OR 1.19 to 1.64), smoking (6 of 7 models; OR 1.15 to 1.61), wound class 3 or 4 (6 of 7 models; OR 1.22 to 1.56), sepsis (6 of 7 models; OR 1.14 to 1.89), corticosteroid administration (5 of 7 models; OR 1.11 to 2.24), and operation duration more than 3 hours (5 of 7 models; OR 1.41 to 1.76). These findings may be used to pre-emptively identify colorectal surgery patients at increased risk of experiencing adverse outcomes. Copyright © 2015 Elsevier Inc. All rights reserved.

Space Radiation Cancer Risk Projections and Uncertainties - 2010

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Kim, Myung-Hee Y.; Chappell, Lori J.

2011-01-01

Uncertainties in estimating health risks from galactic cosmic rays greatly limit space mission lengths and potential risk mitigation evaluations. NASA limits astronaut exposures to a 3% risk of exposure-induced death and protects against uncertainties using an assessment of 95% confidence intervals in the projection model. Revisions to this model for lifetime cancer risks from space radiation and new estimates of model uncertainties are described here. We review models of space environments and transport code predictions of organ exposures, and characterize uncertainties in these descriptions. We summarize recent analysis of low linear energy transfer radio-epidemiology data, including revision to Japanese A-bomb survivor dosimetry, longer follow-up of exposed cohorts, and reassessments of dose and dose-rate reduction effectiveness factors. We compare these projections and uncertainties with earlier estimates. Current understanding of radiation quality effects and recent data on factors of relative biological effectiveness and particle track structure are reviewed. Recent radiobiology experiment results provide new information on solid cancer and leukemia risks from heavy ions. We also consider deviations from the paradigm of linearity at low doses of heavy ions motivated by non-targeted effects models. New findings and knowledge are used to revise the NASA risk projection model for space radiation cancer risks.

Predictors of re-entry into the child protection system in Singapore: a cumulative ecological-transactional risk model.

PubMed

Li, Dongdong; Chu, Chi Meng; Ng, Wei Chern; Leong, Wai

2014-11-01

This study examines the risk factors of re-entry for 1,750 child protection cases in Singapore using a cumulative ecological-transactional risk model. Using administrative data, the present study found that the overall percentage of Child Protection Service (CPS) re-entry in Singapore is 10.5% based on 1,750 cases, with a range from 3.9% (within 1 year) to 16.5% (within 8 years after case closure). One quarter of the re-entry cases were observed to occur within 9 months from case closure. Seventeen risk factors, as identified from the extant literature, were tested for their utility to predict CPS re-entry in this study using a series of Cox regression analyses. A final list of seven risk factors (i.e., children's age at entry, case type, case closure result, duration of case, household income, family size, and mother's employment status) was used to create a cumulative risk score. The results supported the cumulative risk model in that higher risk score is related to higher risk of CPS re-entry. Understanding the prevalence of CPS re-entry and the risk factors associated with re-entry is the key to informing practice and policy in a culturally relevant way. The results from this study could then be used to facilitate critical case management decisions in order to enhance positive outcomes of families and children in Singapore's care system. Copyright © 2014 Elsevier Ltd. All rights reserved.

What does my patient's coronary artery calcium score mean? Combining information from the coronary artery calcium score with information from conventional risk factors to estimate coronary heart disease risk

PubMed Central

Pletcher, Mark J; Tice, Jeffrey A; Pignone, Michael; McCulloch, Charles; Callister, Tracy Q; Browner, Warren S

2004-01-01

Background The coronary artery calcium (CAC) score is an independent predictor of coronary heart disease. We sought to combine information from the CAC score with information from conventional cardiac risk factors to produce post-test risk estimates, and to determine whether the score may add clinically useful information. Methods We measured the independent cross-sectional associations between conventional cardiac risk factors and the CAC score among asymptomatic persons referred for non-contrast electron beam computed tomography. Using the resulting multivariable models and published CAC score-specific relative risk estimates, we estimated post-test coronary heart disease risk in a number of different scenarios. Results Among 9341 asymptomatic study participants (age 35–88 years, 40% female), we found that conventional coronary heart disease risk factors including age, male sex, self-reported hypertension, diabetes and high cholesterol were independent predictors of the CAC score, and we used the resulting multivariable models for predicting post-test risk in a variety of scenarios. Our models predicted, for example, that a 60-year-old non-smoking non-diabetic women with hypertension and high cholesterol would have a 47% chance of having a CAC score of zero, reducing her 10-year risk estimate from 15% (per Framingham) to 6–9%; if her score were over 100, however (a 17% chance), her risk estimate would be markedly higher (25–51% in 10 years). In low risk scenarios, the CAC score is very likely to be zero or low, and unlikely to change management. Conclusion Combining information from the CAC score with information from conventional risk factors can change assessment of coronary heart disease risk to an extent that may be clinically important, especially when the pre-test 10-year risk estimate is intermediate. The attached spreadsheet makes these calculations easy. PMID:15327691

A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models

NASA Astrophysics Data System (ADS)

Thomas, Ian; Murphy, Paul; Fenton, Owen; Shine, Oliver; Mellander, Per-Erik; Dunlop, Paul; Jordan, Phil

2015-04-01

A new phosphorus index (PI) tool is presented which aims to improve the identification of critical source areas (CSAs) of phosphorus (P) losses from agricultural land to surface waters. In a novel approach, the PI incorporates topographic indices rather than watercourse proximity as proxies for runoff risk, to account for the dominant control of topography on runoff-generating areas and P transport pathways. Runoff propensity and hydrological connectivity are modelled using the Topographic Wetness Index (TWI) and Network Index (NI) respectively, utilising high resolution digital elevation models (DEMs) derived from Light Detection and Ranging (LiDAR) to capture the influence of micro-topographic features on runoff pathways. Additionally, the PI attempts to improve risk estimates of particulate P losses by incorporating an erosion factor that accounts for fine-scale topographic variability within fields. Erosion risk is modelled using the Unit Stream Power Erosion Deposition (USPED) model, which integrates DEM-derived upslope contributing area and Universal Soil Loss Equation (USLE) factors. The PI was developed using field, sub-field and sub-catchment scale datasets of P source, mobilisation and transport factors, for four intensive agricultural catchments in Ireland representing different agri-environmental conditions. Datasets included soil test P concentrations, degree of P saturation, soil attributes, land use, artificial subsurface drainage locations, and 2 m resolution LiDAR DEMs resampled from 0.25 m resolution data. All factor datasets were integrated within a Geographical Information System (GIS) and rasterised to 2 m resolution. For each factor, values were categorised and assigned relative risk scores which ranked P loss potential. Total risk scores were calculated for each grid cell using a component formulation, which summed the products of weighted factor risk scores for runoff and erosion pathways. Results showed that the new PI was able to predict in-field risk variability and hence was able to identify CSAs at the sub-field scale. PI risk estimates and component scores were analysed at catchment and subcatchment scales, and validated using measured dissolved, particulate and total P losses at subcatchment snapshot sites and gauging stations at catchment outlets. The new PI provides CSA delineations at higher precision compared to conventional PIs, and more robust P transport risk estimates. The tool can be used to target cost-effective mitigation measures for P management within single farm units and wider catchments.

Inferring the risk factors behind the geographical spread and transmission of Zika in the Americas.

PubMed

Gardner, Lauren M; Bóta, András; Gangavarapu, Karthik; Kraemer, Moritz U G; Grubaugh, Nathan D

2018-01-01

An unprecedented Zika virus epidemic occurred in the Americas during 2015-2016. The size of the epidemic in conjunction with newly recognized health risks associated with the virus attracted significant attention across the research community. Our study complements several recent studies which have mapped epidemiological elements of Zika, by introducing a newly proposed methodology to simultaneously estimate the contribution of various risk factors for geographic spread resulting in local transmission and to compute the risk of spread (or re-introductions) between each pair of regions. The focus of our analysis is on the Americas, where the set of regions includes all countries, overseas territories, and the states of the US. We present a novel application of the Generalized Inverse Infection Model (GIIM). The GIIM model uses real observations from the outbreak and seeks to estimate the risk factors driving transmission. The observations are derived from the dates of reported local transmission of Zika virus in each region, the network structure is defined by the passenger air travel movements between all pairs of regions, and the risk factors considered include regional socioeconomic factors, vector habitat suitability, travel volumes, and epidemiological data. The GIIM relies on a multi-agent based optimization method to estimate the parameters, and utilizes a data driven stochastic-dynamic epidemic model for evaluation. As expected, we found that mosquito abundance, incidence rate at the origin region, and human population density are risk factors for Zika virus transmission and spread. Surprisingly, air passenger volume was less impactful, and the most significant factor was (a negative relationship with) the regional gross domestic product (GDP) per capita. Our model generates country level exportation and importation risk profiles over the course of the epidemic and provides quantitative estimates for the likelihood of introduced Zika virus resulting in local transmission, between all origin-destination travel pairs in the Americas. Our findings indicate that local vector control, rather than travel restrictions, will be more effective at reducing the risks of Zika virus transmission and establishment. Moreover, the inverse relationship between Zika virus transmission and GDP suggests that Zika cases are more likely to occur in regions where people cannot afford to protect themselves from mosquitoes. The modeling framework is not specific for Zika virus, and could easily be employed for other vector-borne pathogens with sufficient epidemiological and entomological data.

A Risk Score Model for Evaluation and Management of Patients with Thyroid Nodules.

PubMed

Zhang, Yongwen; Meng, Fanrong; Hong, Lianqing; Chu, Lanfang

2018-06-12

The study is aimed to establish a simplified and practical tool for analyzing thyroid nodules. A novel risk score model was designed, risk factors including patient history, patient characteristics, physical examination, symptoms of compression, thyroid function, ultrasonography (US) of thyroid and cervical lymph nodes were evaluated and classified into high risk factors, intermediate risk factors, and low risk factors. A total of 243 thyroid nodules in 162 patients were assessed with risk score system and Thyroid Imaging-Reporting and Data System (TI-RADS). The diagnostic performance of risk score system and TI-RADS was compared. The accuracy in the diagnosis of thyroid nodules was 89.3% for risk score system, 74.9% for TI-RADS respectively. The specificity, accuracy and positive predictive value (PPV) of risk score system were significantly higher than the TI-RADS system (χ 2 =26.287, 17.151, 11.983; p <0.05), statistically significant differences were not observed in the sensitivity and negative predictive value (NPV) between the risk score system and TI-RADS (χ 2 =1.276, 0.290; p>0.05). The area under the curve (AUC) for risk score diagnosis system was 0.963, standard error 0.014, 95% confidence interval (CI)=0.934-0.991, the AUC for TI-RADS diagnosis system was 0.912 with standard error 0.021, 95% CI=0.871-0.953, the AUC for risk score system was significantly different from that of TI-RADS (Z=2.02; p <0.05). Risk score model is a reliable, simplified and cost-effective diagnostic tool used in diagnosis of thyroid cancer. The higher the score is, the higher the risk of malignancy will be. © Georg Thieme Verlag KG Stuttgart · New York.

Capturing ecology in modeling approaches applied to environmental risk assessment of endocrine active chemicals in fish.

PubMed

Mintram, Kate S; Brown, A Ross; Maynard, Samuel K; Thorbek, Pernille; Tyler, Charles R

2018-02-01

Endocrine active chemicals (EACs) are widespread in freshwater environments and both laboratory and field based studies have shown reproductive effects in fish at environmentally relevant exposures. Environmental risk assessment (ERA) seeks to protect wildlife populations and prospective assessments rely on extrapolation from individual-level effects established for laboratory fish species to populations of wild fish using arbitrary safety factors. Population susceptibility to chemical effects, however, depends on exposure risk, physiological susceptibility, and population resilience, each of which can differ widely between fish species. Population models have significant potential to address these shortfalls and to include individual variability relating to life-history traits, demographic and density-dependent vital rates, and behaviors which arise from inter-organism and organism-environment interactions. Confidence in population models has recently resulted in the EU Commission stating that results derived from reliable models may be considered when assessing the relevance of adverse effects of EACs at the population level. This review critically assesses the potential risks posed by EACs for fish populations, considers the ecological factors influencing these risks and explores the benefits and challenges of applying population modeling (including individual-based modeling) in ERA for EACs in fish. We conclude that population modeling offers a way forward for incorporating greater environmental relevance in assessing the risks of EACs for fishes and for identifying key risk factors through sensitivity analysis. Individual-based models (IBMs) allow for the incorporation of physiological and behavioral endpoints relevant to EAC exposure effects, thus capturing both direct and indirect population-level effects.

Breast cancer risk prediction using a clinical risk model and polygenic risk score.

PubMed

Shieh, Yiwey; Hu, Donglei; Ma, Lin; Huntsman, Scott; Gard, Charlotte C; Leung, Jessica W T; Tice, Jeffrey A; Vachon, Celine M; Cummings, Steven R; Kerlikowske, Karla; Ziv, Elad

2016-10-01

Breast cancer risk assessment can inform the use of screening and prevention modalities. We investigated the performance of the Breast Cancer Surveillance Consortium (BCSC) risk model in combination with a polygenic risk score (PRS) comprised of 83 single nucleotide polymorphisms identified from genome-wide association studies. We conducted a nested case-control study of 486 cases and 495 matched controls within a screening cohort. The PRS was calculated using a Bayesian approach. The contributions of the PRS and variables in the BCSC model to breast cancer risk were tested using conditional logistic regression. Discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve (AUROC). Increasing quartiles of the PRS were positively associated with breast cancer risk, with OR 2.54 (95 % CI 1.69-3.82) for breast cancer in the highest versus lowest quartile. In a multivariable model, the PRS, family history, and breast density remained strong risk factors. The AUROC of the PRS was 0.60 (95 % CI 0.57-0.64), and an Asian-specific PRS had AUROC 0.64 (95 % CI 0.53-0.74). A combined model including the BCSC risk factors and PRS had better discrimination than the BCSC model (AUROC 0.65 versus 0.62, p = 0.01). The BCSC-PRS model classified 18 % of cases as high-risk (5-year risk ≥3 %), compared with 7 % using the BCSC model. The PRS improved discrimination of the BCSC risk model and classified more cases as high-risk. Further consideration of the PRS's role in decision-making around screening and prevention strategies is merited.

Breast Cancer Risk Prediction Using a Clinical Risk Model and Polygenic Risk Score

PubMed Central

Shieh, Yiwey; Hu, Donglei; Ma, Lin; Huntsman, Scott; Gard, Charlotte C.; Leung, Jessica W.T.; Tice, Jeffrey A.; Vachon, Celine M.; Cummings, Steven R.; Kerlikowske, Karla; Ziv, Elad

2016-01-01

Purpose Breast cancer risk assessment can inform the use of screening and prevention modalities. We investigated the performance of the Breast Cancer Surveillance Consortium (BCSC) risk model in combination with a polygenic risk score (PRS) comprised of 83 single nucleotide polymorphisms identified from genome wide association studies. Methods We conducted a nested case-control study of 486 cases and 495 matched controls within a screening cohort. The PRS was calculated using a Bayesian approach. The contributions of the PRS and variables in the BCSC model to breast cancer risk were tested using conditional logistic regression. Discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve (AUROC). Results Increasing quartiles of the PRS were positively associated with breast cancer risk, with OR 2.54 (95% CI 1.69-3.82) for breast cancer in the highest versus lowest quartile. In a multivariable model, the PRS, family history, and breast density remained strong risk factors. The AUROC of the PRS was 0.60 (95% CI 0.57-0.64), and an Asian-specific PRS had AUROC 0.64 (95% CI 0.53-0.74). A combined model including the BCSC risk factors and PRS had better discrimination than the BCSC model (AUROC 0.65 versus 0.62, p = 0.01). The BCSC-PRS model classified 18% of cases as high-risk (5-year risk ≥ 3%), compared with 7% using the BCSC model. Conclusion The PRS improved discrimination of the BCSC risk model and classified more cases as high-risk. Impact Further consideration of the PRS's role in decision-making around screening and prevention strategies is merited. PMID:27565998

Multifactorial disease risk calculator: Risk prediction for multifactorial disease pedigrees.

PubMed

Campbell, Desmond D; Li, Yiming; Sham, Pak C

2018-03-01

Construction of multifactorial disease models from epidemiological findings and their application to disease pedigrees for risk prediction is nontrivial for all but the simplest of cases. Multifactorial Disease Risk Calculator is a web tool facilitating this. It provides a user-friendly interface, extending a reported methodology based on a liability-threshold model. Multifactorial disease models incorporating all the following features in combination are handled: quantitative risk factors (including polygenic scores), categorical risk factors (including major genetic risk loci), stratified age of onset curves, and the partition of the population variance in disease liability into genetic, shared, and unique environment effects. It allows the application of such models to disease pedigrees. Pedigree-related outputs are (i) individual disease risk for pedigree members, (ii) n year risk for unaffected pedigree members, and (iii) the disease pedigree's joint liability distribution. Risk prediction for each pedigree member is based on using the constructed disease model to appropriately weigh evidence on disease risk available from personal attributes and family history. Evidence is used to construct the disease pedigree's joint liability distribution. From this, lifetime and n year risk can be predicted. Example disease models and pedigrees are provided at the website and are used in accompanying tutorials to illustrate the features available. The website is built on an R package which provides the functionality for pedigree validation, disease model construction, and risk prediction. Website: http://grass.cgs.hku.hk:3838/mdrc/current. © 2017 WILEY PERIODICALS, INC.

Boosting structured additive quantile regression for longitudinal childhood obesity data.

PubMed

Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

2013-07-25

Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

Combining PubMed knowledge and EHR data to develop a weighted bayesian network for pancreatic cancer prediction.

PubMed

Zhao, Di; Weng, Chunhua

2011-10-01

In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. Copyright © 2011 Elsevier Inc. All rights reserved.

Combining PubMed Knowledge and EHR Data to Develop a Weighted Bayesian Network for Pancreatic Cancer Prediction

PubMed Central

Zhao, Di; Weng, Chunhua

2011-01-01

In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. PMID:21642013

Determinants of sick-leave duration: a tool for managers?

PubMed

Flach, Peter A; Krol, Boudien; Groothoff, Johan W

2008-09-01

To provide managers with tools to manage episodes of sick-leave of their employees, the influence of factors such as age, gender, duration of tenure, working full-time or part-time, cause and history of sick-leave, salary and education on sick-leave duration was studied. In a cross-sectional study, data derived from the 2005 sick-leave files of a Dutch university were examined. Odds ratios of the single risk factors were calculated for short spells (or=91 days) of sick-leave. Next, these factors were studied in multiple regression models. Age, gender, duration of employment, cause and history of sick-leave, salary and membership of scientific staff, studied as single factors, have a significant influence on sick-leave duration. In multiple models, this influence remains for gender, salary, age, and history and cause of sick-leave. Only in medium or long spells and regarding the risk for a long or an extended spell do the predictive values of models consisting of psychological factors, work-related factors, salary and gender become reasonable. The predictive value of the risk factors used in this study is limited, and varies with the duration of the sick-leave spell. Only the risk for an extended spell of sick-leave as compared to a medium or long spell is reasonably predicted. Factors contributing to this risk may be used as tools in decision-making.

Community-Engaged Modeling of Geographic and Demographic Patterns of Multiple Public Health Risk Factors

PubMed Central

Basra, Komal; Fabian, M. Patricia; Holberger, Raymond R.; French, Robert

2017-01-01

Many health risk factors are intervention targets within communities, but information regarding high-risk subpopulations is rarely available at a geographic resolution that is relevant for community-scale interventions. Researchers and community partners in New Bedford, Massachusetts (USA) collaboratively identified high-priority behaviors and health outcomes of interest available in the Behavioral Risk Factor Surveillance System (BRFSS). We developed multivariable regression models from the BRFSS explaining variability in exercise, fruit and vegetable consumption, body mass index, and diabetes prevalence as a function of demographic and behavioral characteristics, and linked these models with population microdata developed using spatial microsimulation to characterize high-risk populations and locations. Individuals with lower income and educational attainment had lower rates of multiple health-promoting behaviors (e.g., fruit and vegetable consumption and exercise) and higher rates of self-reported diabetes. Our models in combination with the simulated population microdata identified census tracts with an elevated percentage of high-risk subpopulations, information community partners can use to prioritize funding and intervention programs. Multi-stressor modeling using data from public databases and microsimulation methods for characterizing high-resolution spatial patterns of population attributes, coupled with strong community partner engagement, can provide significant insight for intervention. Our methodology is transferrable to other communities. PMID:28684710

Longitudinal associations between BMI, waist circumference, and cardiometabolic risk in US youth: monitoring implications.

PubMed

Jago, R; Mendoza, J A; Chen, T; Baranowski, T

2013-03-01

This study examined whether change in body mass index (BMI) or waist circumference (WC) is associated with change in cardiometabolic risk factors and differences between cardiovascular disease specific and diabetes specific risk factors among adolescents. We also sought to examine any differences by gender or baseline body mass status. The article is a longitudinal analysis of pre- and post-data collected in the HEALTHY trial. Participants were 4,603 ethnically diverse adolescents who provided complete data at 6th and 8th grade assessments. The main outcome measures were percent change in the following cardiometabolic risk factors: fasting triglycerides, systolic and diastolic blood pressure, high density lipoprotein cholesterol, and glucose as well as a clustered metabolic risk score. Main exposures were change in BMI or WC z-score. Models were run stratified by gender; secondary models were additionally stratified by baseline BMI group (normal, overweight, or obese). Analysis showed that when cardiometabolic risk factors were treated as continuous variables, there was strong evidence (P < 0.001) that change in BMI z-score was associated with change in the majority of the cardiovascular risk factors, except fasting glucose and the combined risk factor score for both boys and girls. There was some evidence that change in WC z-score was associated with some cardiovascular risk factors, but change in WC z-score was consistently associated with changes in fasting glucose. In conclusion, routine monitoring of BMI should be continued by health professionals, but additional information on disease risk may be provided by assessing WC. Copyright © 2013 The Obesity Society.

Gout in African Americans.

PubMed

Krishnan, Eswar

2014-09-01

African Americans have a substantially higher prevalence of risk factors for gout than Caucasians. The aim of the present study was to compare the risk for incident gout among African Americans and Caucasians. Incidence rates of physician-diagnosed gout among 11,559 Caucasian men and 931 African American men aged 35 to 57 years and at high cardiovascular risk, observed for 7 years as a part of the Multiple Risk Factor Intervention Trial, were analyzed. Cox regression models were used to account for potential confounding by age, body mass index, diuretic use, hypertension and diabetes status, aspirin and alcohol consumption, and kidney disease. At baseline, after accounting for risk factors, African Americans had a 14% lower prevalence of hyperuricemia than Caucasians. Incidence of gout increased with increasing prevalence of risk factors in both Caucasians and African Americans. Ethnic disparities in incidence rates were most apparent among those without other risk factors for gout. In separate Cox regression models, after accounting for risk factors, African American ethnicity was associated with a hazard ratio of 0.78 (95% confidence interval [CI], 0.66-0.93) for physician-diagnosed gout and 0.88 (95% CI, 0.85-0.90) for incident hyperuricemia. Significant interactions were observed; the association was the strongest (hazard ratio 0.47; 0.37-0.60). These associations were unaffected by addition of serum urate as a covariate or by using alternate case definitions for gout. After accounting for the higher prevalence of risk factors, African American ethnicity is associated with a significantly lower risk for gout and hyperuricemia compared with Caucasian ethnicity. Copyright © 2014 Elsevier Inc. All rights reserved.

Mothers of Children with Externalizing Behavior Problems: Cognitive Risk Factors for Abuse Potential and Discipline Style and Practices

ERIC Educational Resources Information Center

McElroy, Erika M.; Rodriguez, Christina M.

2008-01-01

Objective: Utilizing the conceptual framework of the Social Information Processing (SIP) model ([Milner, 1993] and [Milner, 2000]), associations between cognitive risk factors and child physical abuse risk and maladaptive discipline style and practices were examined in an at-risk population. Methods: Seventy-three mothers of 5-12-year-old…

Evidence for the Trait-Impulsivity Etiological Model in a Clinical Sample: Bifactor Structure and Its Relation to Impairment and Environmental Risk.

PubMed

Rodenacker, Klaas; Hautmann, Christopher; Görtz-Dorten, Anja; Döpfner, Manfred

2018-05-01

The trait-impulsivity etiological model assumes that a general factor (trait-impulsivity) underlies attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and other externalizing disorders. We investigated the plausibility of this assumption by testing the factor structure of ADHD and ODD in a bifactor framework for a clinical sample of 1420 children between 6 and 18 years of age (M = 9.99, SD = 3.34; 85% male). Further, the trait-impulsivity etiological model assumes that ODD emerges only if environmental risk factors are present. Our results support the validity of the trait-impulsivity etiological model, as they confirm that ADHD and ODD share a strong general factor of disruptive behavior (DB) in this clinical sample. Furthermore, unlike the subdimensions of ADHD, we found that the specific ODD factor explained as much true score variance as the general DB factor. This suggests that a common scale of ADHD and ODD may prove to be as important as a separate ODD subscale to assess externalizing problems in school-age children. However, all other subscales of ADHD may not explain sufficient true score variance once the impact of the general DB factor has been taken into consideration. In accordance with the trait-impulsivity model, we also showed that all factors, but predominantly the general factor and specific inattention factor, predicted parent-rated impairment, and that predominantly ODD and impulsivity are predicted by environmental risk factors.

Applying GIS to develop a model for forest fire risk: A case study in Espírito Santo, Brazil.

PubMed

Eugenio, Fernando Coelho; dos Santos, Alexandre Rosa; Fiedler, Nilton Cesar; Ribeiro, Guido Assunção; da Silva, Aderbal Gomes; dos Santos, Áureo Banhos; Paneto, Greiciane Gaburro; Schettino, Vitor Roberto

2016-05-15

A forest fire risk map is a basic element for planning and protecting forested areas. The main goal of this study was to develop a statistical model for preparing a forest fire risk map using GIS. Such model is based on assigning weights to nine variables divided into two classes: physical factors of the site (terrain slope, land-use/occupation, proximity to roads, terrain orientation, and altitude) and climatic factors (precipitation, temperature, water deficit, and evapotranspiration). In regions where the climate is different from the conditions of this study, the model will require an adjustment of the variables weights according to the local climate. The study area, Espírito Santo State, exhibited approximately 3.81% low risk, 21.18% moderate risk, 30.10% high risk, 41.50% very high risk, and 3.40% extreme risk of forest fire. The areas classified as high risk, very high and extreme, contemplated a total of 78.92% of heat spots. Copyright © 2016 Elsevier Ltd. All rights reserved.

Measuring Treasury Bond Portfolio Risk and Portfolio Optimization with a Non-Gaussian Multivariate Model

NASA Astrophysics Data System (ADS)

Dong, Yijun

The research about measuring the risk of a bond portfolio and the portfolio optimization was relatively rare previously, because the risk factors of bond portfolios are not very volatile. However, this condition has changed recently. The 2008 financial crisis brought high volatility to the risk factors and the related bond securities, even if the highly rated U.S. treasury bonds. Moreover, the risk factors of bond portfolios show properties of fat-tailness and asymmetry like risk factors of equity portfolios. Therefore, we need to use advanced techniques to measure and manage risk of bond portfolios. In our paper, we first apply autoregressive moving average generalized autoregressive conditional heteroscedasticity (ARMA-GARCH) model with multivariate normal tempered stable (MNTS) distribution innovations to predict risk factors of U.S. treasury bonds and statistically demonstrate that MNTS distribution has the ability to capture the properties of risk factors based on the goodness-of-fit tests. Then based on empirical evidence, we find that the VaR and AVaR estimated by assuming normal tempered stable distribution are more realistic and reliable than those estimated by assuming normal distribution, especially for the financial crisis period. Finally, we use the mean-risk portfolio optimization to minimize portfolios' potential risks. The empirical study indicates that the optimized bond portfolios have better risk-adjusted performances than the benchmark portfolios for some periods. Moreover, the optimized bond portfolios obtained by assuming normal tempered stable distribution have improved performances in comparison to the optimized bond portfolios obtained by assuming normal distribution.

Cumulative risk effects in the bullying of children and young people with autism spectrum conditions.

PubMed

Hebron, Judith; Oldfield, Jeremy; Humphrey, Neil

2017-04-01

Students with autism are more likely to be bullied than their typically developing peers. However, several studies have shown that their likelihood of being bullied increases in the context of exposure to certain risk factors (e.g. behaviour difficulties and poor peer relationships). This study explores vulnerability to bullying from a cumulative risk perspective, where the number of risks rather than their nature is considered. A total of 722 teachers and 119 parents of young people with autism spectrum conditions participated in the study. Established risk factors were summed to form a cumulative risk score in teacher and parent models. There was evidence of a cumulative risk effect in both models, suggesting that as the number of risks increased, so did exposure to bullying. A quadratic effect was found in the teacher model, indicating that there was a disproportionate increase in the likelihood of being bullied in relation to the number of risk factors to which a young person was exposed. In light of these findings, it is proposed that more attention needs to be given to the number of risks to which children and young people with autism spectrum conditions are exposed when planning interventions and providing a suitable educational environment.

Conscious worst case definition for risk assessment, part I: a knowledge mapping approach for defining most critical risk factors in integrative risk management of chemicals and nanomaterials.

PubMed

Sørensen, Peter B; Thomsen, Marianne; Assmuth, Timo; Grieger, Khara D; Baun, Anders

2010-08-15

This paper helps bridge the gap between scientists and other stakeholders in the areas of human and environmental risk management of chemicals and engineered nanomaterials. This connection is needed due to the evolution of stakeholder awareness and scientific progress related to human and environmental health which involves complex methodological demands on risk management. At the same time, the available scientific knowledge is also becoming more scattered across multiple scientific disciplines. Hence, the understanding of potentially risky situations is increasingly multifaceted, which again challenges risk assessors in terms of giving the 'right' relative priority to the multitude of contributing risk factors. A critical issue is therefore to develop procedures that can identify and evaluate worst case risk conditions which may be input to risk level predictions. Therefore, this paper suggests a conceptual modelling procedure that is able to define appropriate worst case conditions in complex risk management. The result of the analysis is an assembly of system models, denoted the Worst Case Definition (WCD) model, to set up and evaluate the conditions of multi-dimensional risk identification and risk quantification. The model can help optimize risk assessment planning by initial screening level analyses and guiding quantitative assessment in relation to knowledge needs for better decision support concerning environmental and human health protection or risk reduction. The WCD model facilitates the evaluation of fundamental uncertainty using knowledge mapping principles and techniques in a way that can improve a complete uncertainty analysis. Ultimately, the WCD is applicable for describing risk contributing factors in relation to many different types of risk management problems since it transparently and effectively handles assumptions and definitions and allows the integration of different forms of knowledge, thereby supporting the inclusion of multifaceted risk components in cumulative risk management. Copyright 2009 Elsevier B.V. All rights reserved.

Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status.

PubMed

Hüsing, Anika; Canzian, Federico; Beckmann, Lars; Garcia-Closas, Montserrat; Diver, W Ryan; Thun, Michael J; Berg, Christine D; Hoover, Robert N; Ziegler, Regina G; Figueroa, Jonine D; Isaacs, Claudine; Olsen, Anja; Viallon, Vivian; Boeing, Heiner; Masala, Giovanna; Trichopoulos, Dimitrios; Peeters, Petra H M; Lund, Eiliv; Ardanaz, Eva; Khaw, Kay-Tee; Lenner, Per; Kolonel, Laurence N; Stram, Daniel O; Le Marchand, Loïc; McCarty, Catherine A; Buring, Julie E; Lee, I-Min; Zhang, Shumin; Lindström, Sara; Hankinson, Susan E; Riboli, Elio; Hunter, David J; Henderson, Brian E; Chanock, Stephen J; Haiman, Christopher A; Kraft, Peter; Kaaks, Rudolf

2012-09-01

There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumours with different hormone receptor status. Within the Breast and Prostate Cancer Cohort Consortium, we analysed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age adjusted and cohort-adjusted concordance statistic (AUROC(a)). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement was used to measure improvements in risk prediction. We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROC(a) going from 2.7% to 4%). Discriminatory ability for all models varied strongly by hormone receptor status. Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor-positive cases, but the gain in discriminatory quality is not sufficient for clinical application.

Claims-based risk model for first severe COPD exacerbation.

PubMed

Stanford, Richard H; Nag, Arpita; Mapel, Douglas W; Lee, Todd A; Rosiello, Richard; Schatz, Michael; Vekeman, Francis; Gauthier-Loiselle, Marjolaine; Merrigan, J F Philip; Duh, Mei Sheng

2018-02-01

To develop and validate a predictive model for first severe chronic obstructive pulmonary disease (COPD) exacerbation using health insurance claims data and to validate the risk measure of controller medication to total COPD treatment (controller and rescue) ratio (CTR). A predictive model was developed and validated in 2 managed care databases: Truven Health MarketScan database and Reliant Medical Group database. This secondary analysis assessed risk factors, including CTR, during the baseline period (Year 1) to predict risk of severe exacerbation in the at-risk period (Year 2). Patients with COPD who were 40 years or older and who had at least 1 COPD medication dispensed during the year following COPD diagnosis were included. Subjects with severe exacerbations in the baseline year were excluded. Risk factors in the baseline period were included as potential predictors in multivariate analysis. Performance was evaluated using C-statistics. The analysis included 223,824 patients. The greatest risk factors for first severe exacerbation were advanced age, chronic oxygen therapy usage, COPD diagnosis type, dispensing of 4 or more canisters of rescue medication, and having 2 or more moderate exacerbations. A CTR of 0.3 or greater was associated with a 14% lower risk of severe exacerbation. The model performed well with C-statistics, ranging from 0.711 to 0.714. This claims-based risk model can predict the likelihood of first severe COPD exacerbation. The CTR could also potentially be used to target populations at greatest risk for severe exacerbations. This could be relevant for providers and payers in approaches to prevent severe exacerbations and reduce costs.

Study on quantitative risk assessment model of the third party damage for natural gas pipelines based on fuzzy comprehensive assessment

NASA Astrophysics Data System (ADS)

Qiu, Zeyang; Liang, Wei; Wang, Xue; Lin, Yang; Zhang, Meng

2017-05-01

As an important part of national energy supply system, transmission pipelines for natural gas are possible to cause serious environmental pollution, life and property loss in case of accident. The third party damage is one of the most significant causes for natural gas pipeline system accidents, and it is very important to establish an effective quantitative risk assessment model of the third party damage for reducing the number of gas pipelines operation accidents. Against the third party damage accident has the characteristics such as diversity, complexity and uncertainty, this paper establishes a quantitative risk assessment model of the third party damage based on Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE). Firstly, risk sources of third party damage should be identified exactly, and the weight of factors could be determined via improved AHP, finally the importance of each factor is calculated by fuzzy comprehensive evaluation model. The results show that the quantitative risk assessment model is suitable for the third party damage of natural gas pipelines and improvement measures could be put forward to avoid accidents based on the importance of each factor.

Aviation Safety Risk Modeling: Lessons Learned From Multiple Knowledge Elicitation Sessions

NASA Technical Reports Server (NTRS)

Luxhoj, J. T.; Ancel, E.; Green, L. L.; Shih, A. T.; Jones, S. M.; Reveley, M. S.

2014-01-01

Aviation safety risk modeling has elements of both art and science. In a complex domain, such as the National Airspace System (NAS), it is essential that knowledge elicitation (KE) sessions with domain experts be performed to facilitate the making of plausible inferences about the possible impacts of future technologies and procedures. This study discusses lessons learned throughout the multiple KE sessions held with domain experts to construct probabilistic safety risk models for a Loss of Control Accident Framework (LOCAF), FLightdeck Automation Problems (FLAP), and Runway Incursion (RI) mishap scenarios. The intent of these safety risk models is to support a portfolio analysis of NASA's Aviation Safety Program (AvSP). These models use the flexible, probabilistic approach of Bayesian Belief Networks (BBNs) and influence diagrams to model the complex interactions of aviation system risk factors. Each KE session had a different set of experts with diverse expertise, such as pilot, air traffic controller, certification, and/or human factors knowledge that was elicited to construct a composite, systems-level risk model. There were numerous "lessons learned" from these KE sessions that deal with behavioral aggregation, conditional probability modeling, object-oriented construction, interpretation of the safety risk results, and model verification/validation that are presented in this paper.

Protective Factors, Risk Indicators, and Contraceptive Consistency Among College Women.

PubMed

Morrison, Leslie F; Sieving, Renee E; Pettingell, Sandra L; Hellerstedt, Wendy L; McMorris, Barbara J; Bearinger, Linda H

2016-01-01

To explore risk and protective factors associated with consistent contraceptive use among emerging adult female college students and whether effects of risk indicators were moderated by protective factors. Secondary analysis of National Longitudinal Study of Adolescent to Adult Health Wave III data. Data collected through in-home interviews in 2001 and 2002. National sample of 18- to 25-year-old women (N = 842) attending 4-year colleges. We examined relationships between protective factors, risk indicators, and consistent contraceptive use. Consistent contraceptive use was defined as use all of the time during intercourse in the past 12 months. Protective factors included external supports of parental closeness and relationship with caring nonparental adult and internal assets of self-esteem, confidence, independence, and life satisfaction. Risk indicators included heavy episodic drinking, marijuana use, and depression symptoms. Multivariable logistic regression models were used to evaluate relationships between protective factors and consistent contraceptive use and between risk indicators and contraceptive use. Self-esteem, confidence, independence, and life satisfaction were significantly associated with more consistent contraceptive use. In a final model including all internal assets, life satisfaction was significantly related to consistent contraceptive use. Marijuana use and depression symptoms were significantly associated with less consistent use. With one exception, protective factors did not moderate relationships between risk indicators and consistent use. Based on our findings, we suggest that risk and protective factors may have largely independent influences on consistent contraceptive use among college women. A focus on risk and protective factors may improve contraceptive use rates and thereby reduce unintended pregnancy among college students. Copyright © 2016 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses. Published by Elsevier Inc. All rights reserved.

Prediction of concurrent endometrial carcinoma in women with endometrial hyperplasia.

PubMed

Matsuo, Koji; Ramzan, Amin A; Gualtieri, Marc R; Mhawech-Fauceglia, Paulette; Machida, Hiroko; Moeini, Aida; Dancz, Christina E; Ueda, Yutaka; Roman, Lynda D

2015-11-01

Although a fraction of endometrial hyperplasia cases have concurrent endometrial carcinoma, patient characteristics associated with concurrent malignancy are not well described. The aim of our study was to identify predictive clinico-pathologic factors for concurrent endometrial carcinoma among patients with endometrial hyperplasia. A case-control study was conducted to compare endometrial hyperplasia in both preoperative endometrial biopsy and hysterectomy specimens (n=168) and endometrial carcinoma in hysterectomy specimen but endometrial hyperplasia in preoperative endometrial biopsy (n=43). Clinico-pathologic factors were examined to identify independent risk factors of concurrent endometrial carcinoma in a multivariate logistic regression model. The most common histologic subtype in preoperative endometrial biopsy was complex hyperplasia with atypia [CAH] (n=129) followed by complex hyperplasia without atypia (n=58) and simple hyperplasia with or without atypia (n=24). The majority of endometrial carcinomas were grade 1 (86.0%) and stage I (83.7%). In multivariate analysis, age 40-59 (odds ratio [OR] 3.07, p=0.021), age≥60 (OR 6.65, p=0.005), BMI≥35kg/m(2) (OR 2.32, p=0.029), diabetes mellitus (OR 2.51, p=0.019), and CAH (OR 9.01, p=0.042) were independent predictors of concurrent endometrial carcinoma. The risk of concurrent endometrial carcinoma rose dramatically with increasing number of risk factors identified in multivariate model (none 0%, 1 risk factor 7.0%, 2 risk factors 17.6%, 3 risk factors 35.8%, and 4 risk factors 45.5%, p<0.001). Hormonal treatment was associated with decreased risk of concurrent endometrial cancer in those with ≥3 risk factors. Older age, obesity, diabetes mellitus, and CAH are predictive of concurrent endometrial carcinoma in endometrial hyperplasia patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Clinical Utility of Five Genetic Variants for Predicting Prostate Cancer Risk and Mortality

PubMed Central

Salinas, Claudia A.; Koopmeiners, Joseph S.; Kwon, Erika M.; FitzGerald, Liesel; Lin, Daniel W.; Ostrander, Elaine A.; Feng, Ziding; Stanford, Janet L.

2009-01-01

Background A recent report suggests that the combination of five single-nucleotide polymorphisms (SNPs) at 8q24, 17q12, 17q24.3 and a family history of the disease may predict risk of prostate cancer. The present study tests the performance of these factors in prediction models for prostate cancer risk and prostate cancer-specific mortality. Methods SNPs were genotyped in population-based samples from Caucasians in King County, Washington. Incident cases (n=1308), aged 35–74, were compared to age-matched controls (n=1266) using logistic regression to estimate odds ratios (OR) associated with genotypes and family history. Cox proportional hazards models estimated hazard ratios for prostate cancer-specific mortality according to genotypes. Results The combination of SNP genotypes and family history was significantly associated with prostate cancer risk (ptrend=1.5 × 10−20). Men with ≥ five risk factors had an OR of 4.9 (95% CI 1.6 to 18.5) compared to men with none. However, this combination of factors did not improve the ROC curve after accounting for known risk predictors (i.e., age, serum PSA, family history). Neither the individual nor combined risk factors was associated with prostate cancer-specific mortality. Conclusion Genotypes for five SNPs plus family history are associated with a significant elevation in risk for prostate cancer and may explain up to 45% of prostate cancer in our population. However, they do not improve prediction models for assessing who is at risk of getting or dying from the disease, once known risk or prognostic factors are taken into account. Thus, this SNP panel may have limited clinical utility. PMID:19058137

Academic Risk Factors and Deficits of Learned Hopelessness: A Longitudinal Study of Hong Kong Secondary School Students

ERIC Educational Resources Information Center

Au, Raymond C. P.; Watkins, David A.; Hattie, John A. C.

2010-01-01

The aim of the present study is to explore a causal model of academic achievement and learning-related personal variables by testing the nature of relationships between learned hopelessness, its risk factors and hopelessness deficits as proposed in major theories in this area. The model investigates affective-motivational characteristics of…

Characterizing the Solid-Solution Coefficient and Plant Uptake Factor of As, Cd and Pb in California Croplands

USDA-ARS?s Scientific Manuscript database

In risk assessment models, the solid-solution partition coefficient (Kd), and plant uptake factor (PUF), are often employed to model the fate and transport of trace elements in soils. The trustworthiness of risk assessments depends on the reliability of the parameters used. In this study, we exami...

Investigation of Profiles of Risk Factors for Adolescent Psychopathology: A Person-Centered Approach

ERIC Educational Resources Information Center

Parra, Gilbert R.; DuBois, David L.; Sher, Kenneth J.

2006-01-01

Latent variable mixture modeling was used to identify subgroups of adolescents with distinct profiles of risk factors from individual, family, peer, and broader contextual domains. Data were drawn from the National Longitudinal Study of Adolescent Health. Four-class models provided the most theoretically meaningful solutions for both 7th (n = 907;…

Evaluating Determinants of Environmental Risk Perception for Risk Management in Contaminated Sites

PubMed Central

Janmaimool, Piyapong; Watanabe, Tsunemi

2014-01-01

Understanding the differences in the risk judgments of residents of industrial communities potentially provides insights into how to develop appropriate risk communication strategies. This study aimed to explore citizens’ fundamental understanding of risk-related judgments and to identify the factors contributing to perceived risks. An exploratory model was created to investigate the public’s risk judgments. In this model, the relationship between laypeople’s perceived risks and the factors related to the physical nature of risks (such as perceived probability of environmental contamination, probability of receiving impacts, and severity of catastrophic consequences) were examined by means of multiple regression analysis. Psychological factors, such as the ability to control the risks, concerns, experiences, and perceived benefits of industrial development were also included in the analysis. The Maptaphut industrial area in Rayong Province, Thailand was selected as a case study. A survey of 181 residents of communities experiencing different levels of hazardous gas contamination revealed rational risk judgments by inhabitants of high-risk and moderate-risk communities, based on their perceived probability of contamination, probability of receiving impacts, and perceived catastrophic consequences. However, risks assessed by people in low-risk communities could not be rationally explained and were influenced by their collective experiences. PMID:24937530

Fire risk in San Diego County, California: A weighted Bayesian model approach

USGS Publications Warehouse

Kolden, Crystal A.; Weigel, Timothy J.

2007-01-01

Fire risk models are widely utilized to mitigate wildfire hazards, but models are often based on expert opinions of less understood fire-ignition and spread processes. In this study, we used an empirically derived weights-of-evidence model to assess what factors produce fire ignitions east of San Diego, California. We created and validated a dynamic model of fire-ignition risk based on land characteristics and existing fire-ignition history data, and predicted ignition risk for a future urbanization scenario. We then combined our empirical ignition-risk model with a fuzzy fire behavior-risk model developed by wildfire experts to create a hybrid model of overall fire risk. We found that roads influence fire ignitions and that future growth will increase risk in new rural development areas. We conclude that empirically derived risk models and hybrid models offer an alternative method to assess current and future fire risk based on management actions.

[Debating disease: the risk factor concept in political economic and scientific consideration, 1968 to 1986].

PubMed

Madarász, Jeannette

2009-01-01

The risk factor concept was developed in American epidemiological studies ongoing since the 1940s researching the causes of chronic cardiovascular diseases. By looking at the depiction of this model in a variety of media in Germany between 1968 and 1986 we can put its close interaction with contemporary socio-political debates under scrutiny. Thereby, a strong connection between the various agents' political and economic interests on the one hand and the incorporation of the risk factor concept into their specific agendas will become apparent. The risk factor concept was not fundamentally changed in the process but it was adapted to contemporary conditions and political constellations. Thereby, so it will be argued, the medical uses of the model, especially regarding the prevention of chronic cardiovascular disease, were forced into the background of public debates.

Examination of Substance Use, Risk Factors, and Protective Factors on Student Academic Test Score Performance

PubMed Central

Arthur, Michael W.; Brown, Eric C.; Briney, John S.; Hawkins, J. David; Abbott, Robert D.; Catalano, Richard F.; Becker, Linda; Langer, Michael; Mueller, Martin T.

2016-01-01

BACKGROUND School administrators and teachers face difficult decisions about how best to use school resources in order to meet academic achievement goals. Many are hesitant to adopt prevention curricula that are not focused directly on academic achievement. Yet, some have hypothesized that prevention curricula can remove barriers to learning and, thus, promote achievement. This study examined relationships between school levels of student substance use and risk and protective factors that predict adolescent problem behaviors and achievement test performance in Washington State. METHODS Hierarchical Generalized Linear Models were used to examine predictive associations between school-averaged levels of substance use and risk and protective factors and Washington State students’ likelihood of meeting achievement test standards on the Washington Assessment of Student Learning, statistically controlling for demographic and economic factors known to be associated with achievement. RESULTS Results indicate that levels of substance use and risk/protective factors predicted the academic test score performance of students. Many of these effects remained significant even after controlling for model covariates. CONCLUSIONS The findings suggest that implementing prevention programs that target empirically identified risk and protective factors have the potential to positively affect students’ academic achievement. PMID:26149305

Does the outcome of a first pregnancy predict depression, suicidal ideation, or lower self-esteem? Data from the National Comorbidity Survey.

PubMed

Steinberg, Julia R; Becker, Davida; Henderson, Jillian T

2011-04-01

This study examines the risk of depression, suicidal ideation, and lower self-esteem following an abortion versus a delivery, with and without adjusting for important correlates. Using the National Comorbidity Survey, we tested how first pregnancy outcome (abortion vs. delivery) related to subsequent major depression, suicidal ideation, and self-esteem. Models controlling for risk factors, such as background and economic factors, prepregnancy violence experience, and prepregnancy mental health, as well as a model with all risk factors, were examined. When no risk factors were entered in the model, women who had abortions were more likely to have subsequent depression, OR=1.53, 95% CI [1.05-2.22], and suicidal ideation, OR=2.02, 95% CI [1.40-2.92], but they were not more likely to have lower self-esteem, B=-.02. When all risk factors were entered, pregnancy outcome was not significantly related to later depression, OR=0.87, 95% CI [0.54-1.37], and suicidal ideation, OR=1.19, 95% CI [0.70-2.02]. Predictors of mental health following abortion and delivery included prepregnancy depression, suicidal ideation, and sexual violence. Policies and practices implemented in response to the claim that abortion hurts women are not supported by our findings. Efforts to support women's mental health should focus on known risk factors, such as gender-based violence and prior mental health problems, rather than abortion history. © 2011 American Orthopsychiatric Association.

Eating disorder-specific risk factors moderate the relationship between negative urgency and binge eating: A behavioral genetic investigation.

PubMed

Racine, Sarah E; VanHuysse, Jessica L; Keel, Pamela K; Burt, S Alexandra; Neale, Michael C; Boker, Steven; Klump, Kelly L

2017-07-01

Theoretical models of binge eating and eating disorders include both transdiagnostic and eating disorder-specific risk factors. Negative urgency (i.e., the tendency to act impulsively when distressed) is a critical transdiagnostic risk factor for binge eating, but limited research has examined interactions between negative urgency and disorder-specific variables. Investigating these interactions can help identify the circumstances under which negative urgency is most strongly associated with binge eating. We examined whether prominent risk factors (i.e., appearance pressures, thin-ideal internalization, body dissatisfaction, dietary restraint) specified in well-established etiologic models of eating disorders moderate negative urgency-binge eating associations. Further, we investigated whether phenotypic moderation effects were due to genetic and/or environmental associations between negative urgency and binge eating. Participants were 988 female twins aged 11-25 years from the Michigan State University Twin Registry. Appearance pressures, thin-ideal internalization, and body dissatisfaction, but not dietary restraint, significantly moderated negative urgency-binge eating associations, with high levels of these risk factors and high negative urgency associated with the greatest binge eating. Twin moderation models revealed that genetic, but not environmental, sharing between negative urgency and binge eating was enhanced at higher levels of these eating disorder-specific variables. Future longitudinal research should investigate whether eating disorder risk factors shape genetic influences on negative urgency into manifesting as binge eating. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

[Multiple risk factors models of patients with acute coronary syndromes of different genders].

PubMed

Sun, Wanglexian; Hu, Tiemin; Huang, Xiansheng; Zhang, Ying; Guo, Jinrui; Wang, Wenfeng; Shi, Fei; Wang, Pengfei; Wang, Huarong; Sun, Jing; Li, Chunhua

2014-12-23

To establish the multiple risk factors models for patients with acute coronary syndromes (ACS) of different genders and quantitatively assess the pathopoiesis of all factors. A total of 2 308 consecutive ACS inpatients and a control group of 256 cases with normal coronary artery from January 2010 to December 2012 were enrolled and divided into 4 groups of female ACS (n = 970), male ACS (n = 1 338), female control (n = 136) and male control (n = 120). All demographic and clinical data were collected by the physicians and master degree candidates in the division of cardiology. The Logistic regression models of multiple risk factors were established for ACS by different genders. More than 45 years of age, dyslipidemia, type 2 diabetes mellitus, obesity and hypertension were all independent risk factors of ACS for different genders (P < 0.05). However, the same risk factors had different pathogenic effects on ACS between genders. The odds ratio (OR) was markedly different for females and males: per 5-year increase aged over 45 years (1.45 vs 1.13), dyslipidemia (3.45 vs 1.68), type 2 diabetes mellitus (4.06 vs 2.33), obesity (2.93 vs 1.91) and hypertension (1.78 vs 3.80) respectively (all P < 0.05). In addition, current smoking increased the risk of ACS attack in males by 5.49 (P < 0.05) while not statistically significant in females. Particularly cerebral ischemic stroke increased the risk of ACS attack by 5.49 folds in males other than females (P < 0.05). Type 2 diabetes mellitus, dyslipidemia and obesity may present higher risks of ACS attack for females than males. And smoking and hypertension are much more dangerous for males. Males with cerebral infarction are more susceptible for ACS than females.

Using chronic disease risk factors to adjust Medicare capitation payments

PubMed Central

Schauffler, Helen Halpin; Howland, Jonathan; Cobb, Janet

1992-01-01

This study evaluates the use of risk factors for chronic disease as health status adjusters for Medicare's capitation formula, the average adjusted per capita costs (AAPCC). Risk factor data for the surviving members of the Framingham Study cohort who were examined in 1982-83 were merged with 100 percent Medicare payment data for 1984 and 1985, matching on Social Security number and sex. Seven different AAPCC models were estimated to assess the independent contributions of risk factors and measures of prior utilization and disability in increasing the explanatory power of AAPCC. The findings suggest that inclusion of risk factors for chronic disease as health status adjusters can improve substantially the predictive accuracy of AAPCC. PMID:10124441

Mental Models of Cause and Inheritance for Type 2 Diabetes Among Unaffected Individuals Who Have a Positive Family History.

PubMed

Daack-Hirsch, Sandra; Shah, Lisa L; Cady, Alyssa D

2018-03-01

Using the familial risk perception (FRP) model as a framework, we elicited causal and inheritance explanations for type 2 diabetes (T2D) from people who do not have T2D but have a family history for it. We identified four composite mental models for cause of T2D: (a) purely genetic; (b) purely behavioral/environmental; (c) direct multifactorial, in which risk factors interact and over time directly lead to T2D; and (d) indirect multifactorial, in which risk factors interact and over time cause a precursor health condition (such as obesity or metabolic syndrome) that leads to T2D. Interestingly, participants described specific risk factors such as genetics, food habits, lifestyle, weight, and culture as "running in the family." Our findings provide insight into lay beliefs about T2D that can be used by clinicians to anticipate or make sense of responses to questions they pose to patients about mental models for T2D.

Dental Students' Perceptions of Risk Factors for Musculoskeletal Disorders: Adapting the Job Factors Questionnaire for Dentistry.

PubMed

Presoto, Cristina D; Wajngarten, Danielle; Domingos, Patrícia A S; Campos, Juliana A D B; Garcia, Patrícia P N S

2018-01-01

The aims of this study were to adapt the Job Factors Questionnaire to the field of dentistry, evaluate its psychometric properties, evaluate dental students' perceptions of work/study risk factors for musculoskeletal disorders, and determine the influence of gender and academic level on those perceptions. All 580 students enrolled in two Brazilian dental schools in 2015 were invited to participate in the study. A three-factor structure (Repetitiveness, Work Posture, and External Factors) was tested through confirmatory factor analysis. Convergent validity was estimated using the average variance extracted (AVE), discriminant validity was based on the correlational analysis of the factors, and reliability was assessed. A causal model was created using structural equation modeling to evaluate the influence of gender and academic level on students' perceptions. A total of 480 students completed the questionnaire for an 83% response rate. The responding students' average age was 21.6 years (SD=2.98), and 74.8% were women. Higher scores were observed on the Work Posture factor items. The refined model presented proper fit to the studied sample. Convergent validity was compromised only for External Factors (AVE=0.47), and discriminant validity was compromised for Work Posture and External Factors (r 2 =0.69). Reliability was adequate. Academic level did not have a significant impact on the factors, but the women students exhibited greater perception. Overall, the adaptation resulted in a useful instrument for assessing perceptions of risk factors for musculoskeletal disorders. Gender was found to significantly influence all three factors, with women showing greater perception of the risk factors.

Characterizing environmental risk factors for West Nile virus in Quebec, Canada, using clinical data in humans and serology in pet dogs.

PubMed

Rocheleau, J P; Michel, P; Lindsay, L R; Drebot, M; Dibernardo, A; Ogden, N H; Fortin, A; Arsenault, J

2017-10-01

The identification of specific environments sustaining emerging arbovirus amplification and transmission to humans is a key component of public health intervention planning. This study aimed at identifying environmental factors associated with West Nile virus (WNV) infections in southern Quebec, Canada, by modelling and jointly interpreting aggregated clinical data in humans and serological data in pet dogs. Environmental risk factors were estimated in humans by negative binomial regression based on a dataset of 191 human WNV clinical cases reported in the study area between 2011 and 2014. Risk factors for infection in dogs were evaluated by logistic and negative binomial models based on a dataset including WNV serological results from 1442 dogs sampled from the same geographical area in 2013. Forested lands were identified as low-risk environments in humans. Agricultural lands represented higher risk environments for dogs. Environments identified as impacting risk in the current study were somewhat different from those identified in other studies conducted in north-eastern USA, which reported higher risk in suburban environments. In the context of the current study, combining human and animal data allowed a more comprehensive and possibly a more accurate view of environmental WNV risk factors to be obtained than by studying aggregated human data alone.

Detection of Cardiovascular Disease Risk's Level for Adults Using Naive Bayes Classifier.

PubMed

Miranda, Eka; Irwansyah, Edy; Amelga, Alowisius Y; Maribondang, Marco M; Salim, Mulyadi

2016-07-01

The number of deaths caused by cardiovascular disease and stroke is predicted to reach 23.3 million in 2030. As a contribution to support prevention of this phenomenon, this paper proposes a mining model using a naïve Bayes classifier that could detect cardiovascular disease and identify its risk level for adults. The process of designing the method began by identifying the knowledge related to the cardiovascular disease profile and the level of cardiovascular disease risk factors for adults based on the medical record, and designing a mining technique model using a naïve Bayes classifier. Evaluation of this research employed two methods: accuracy, sensitivity, and specificity calculation as well as an evaluation session with cardiologists and internists. The characteristics of cardiovascular disease are identified by its primary risk factors. Those factors are diabetes mellitus, the level of lipids in the blood, coronary artery function, and kidney function. Class labels were assigned according to the values of these factors: risk level 1, risk level 2 and risk level 3. The evaluation of the classifier performance (accuracy, sensitivity, and specificity) in this research showed that the proposed model predicted the class label of tuples correctly (above 80%). More than eighty percent of respondents (including cardiologists and internists) who participated in the evaluation session agree till strongly agreed that this research followed medical procedures and that the result can support medical analysis related to cardiovascular disease. The research showed that the proposed model achieves good performance for risk level detection of cardiovascular disease.

Predicting risk for childhood asthma by pre-pregnancy, perinatal, and postnatal factors.

PubMed

Wen, Hui-Ju; Chiang, Tung-Liang; Lin, Shio-Jean; Guo, Yue Leon

2015-05-01

Symptoms of atopic disease start early in human life. Predicting risk for childhood asthma by early-life exposure would contribute to disease prevention. A birth cohort study was conducted to investigate early-life risk factors for childhood asthma and to develop a predictive model for the development of asthma. National representative samples of newborn babies were obtained by multistage stratified systematic sampling from the 2005 Taiwan Birth Registry. Information on potential risk factors and children's health was collected by home interview when babies were 6 months old and 5 yr old, respectively. Backward stepwise regression analysis was used to identify the risk factors of childhood asthma for predictive models that were used to calculate the probability of childhood asthma. A total of 19,192 children completed the study satisfactorily. Physician-diagnosed asthma was reported in 6.6% of 5-yr-old children. Pre-pregnancy factors (parental atopy and socioeconomic status), perinatal factors (place of residence, exposure to indoor mold and painting/renovations during pregnancy), and postnatal factors (maternal postpartum depression and the presence of atopic dermatitis before 6 months of age) were chosen for the predictive models, and the highest predicted probability of asthma in 5-yr-old children was 68.1% in boys and 78.1% in girls; the lowest probability in boys and girls was 4.1% and 3.2%, respectively. This investigation provides a technique for predicting risk of childhood asthma that can be used to developing a preventive strategy against asthma. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Relationship Risks in Context: A Cumulative Risk Approach to Understanding Relationship Satisfaction

PubMed Central

Rauer, Amy J.; Karney, Benjamin R.; Garvan, Cynthia W.; Hou, Wei

2009-01-01

Risks associated with less satisfying intimate relationships often co-occur within individuals, raising questions about approaches that consider only their independent impact. Utilizing the cumulative risk model, which acknowledges the natural covariation of risk factors, this study examined individuals in intimate relationships using the Florida Family Formation Survey (n = 2,876) and a replication sample (n = 1,048). Analyses confirmed that not only was relationship satisfaction lower among those with more risks, but the cumulative risk score was predictive above and beyond the individual risk factors. Furthermore, experiencing multiple risks exacerbated the negative associations between individual risks and relationship satisfaction, suggesting that the operation of a risk factor in a relationship is moderated by the presence or absence of other risks. PMID:19587840

Association between Suicide Ideation and Attempts and Being an Immigrant among Adolescents, and the Role of Socioeconomic Factors and School, Behavior, and Health-Related Difficulties.

PubMed

Chau, Kénora; Kabuth, Bernard; Chau, Nearkasen

2016-11-01

The risk of suicide behaviors in immigrant adolescents varies across countries and remains partly understood. We conducted a study in France to examine immigrant adolescents' likelihood of experiencing suicide ideation in the last 12 months (SI) and lifetime suicide attempts (SA) compared with their native counterparts, and the contribution of socioeconomic factors and school, behavior, and health-related difficulties. Questionnaires were completed by 1559 middle-school adolescents from north-eastern France including various risk factors, SI, SA, and their first occurrence over adolescent's life course (except SI). Data were analyzed using logistic regression models for SI and Cox regression models for SA (retaining only school, behavior, and health-related difficulties that started before SA). Immigrant adolescents had a two-time higher risk of SI and SA than their native counterparts. Using nested models, the excess SI risk was highly explained by socioeconomic factors (27%) and additional school, behavior, and health-related difficulties (24%) but remained significant. The excess SA risk was more highly explained by these issues (40% and 85%, respectively) and became non-significant. These findings demonstrate the risk patterns of SI and SA and the prominent confounding roles of socioeconomic factors and school, behavior, and health-related difficulties. They may be provided to policy makers, schools, carers, and various organizations interested in immigrant, adolescent, and suicide-behavior problems.

A GIS-based approach for comparative analysis of potential fire risk assessment

NASA Astrophysics Data System (ADS)

Sun, Ying; Hu, Lieqiu; Liu, Huiping

2007-06-01

Urban fires are one of the most important sources of property loss and human casualty and therefore it is necessary to assess the potential fire risk with consideration of urban community safety. Two evaluation models are proposed, both of which are integrated with GIS. One is the single factor model concerning the accessibility of fire passage and the other is grey clustering approach based on the multifactor system. In the latter model, fourteen factors are introduced and divided into four categories involving security management, evacuation facility, construction resistance and fire fighting capability. A case study on campus of Beijing Normal University is presented to express the potential risk assessment models in details. A comparative analysis of the two models is carried out to validate the accuracy. The results are approximately consistent with each other. Moreover, modeling with GIS promotes the efficiency the potential risk assessment.

An Explanatory Model of Dating Violence Risk Factors in Spanish Adolescents.

PubMed

Aizpitarte, Alazne; Alonso-Arbiol, Itziar; Van de Vijver, Fons J R

2017-12-01

Dating violence is a serious public health issue that needs further understanding in terms of risk factors that may be involved in it. The main goal of this study was to test a mediational model of dating violence risk factors. The sample was composed of 477 secondary and college students from Spain (59% females). A dynamic developmental explanatory model considering aggressiveness, insecure attachment, interparental conflict, and peer dating violence was tested using a multigroup structural equation model. Aggressiveness partially mediated the relation between anxious attachment and dating violence and fully mediated the association between interparental conflict resolution and dating violence. Furthermore, perceived peer dating violence was a direct predictor of dating violence. Implications for prevention and intervention plans are discussed. © 2017 The Authors. Journal of Research on Adolescence © 2017 Society for Research on Adolescence.

Manifold implications of obesity in ischemic heart disease among Japanese patients according to covariance structure analysis: Low reactivity of B-type natriuretic peptide as an intervening risk factor.

PubMed

Tsutsumi, Joshi; Minai, Kosuke; Kawai, Makoto; Ogawa, Kazuo; Inoue, Yasunori; Morimoto, Satoshi; Tanaka, Toshikazu; Nagoshi, Tomohisa; Ogawa, Takayuki; Yoshimura, Michihiro

2017-01-01

Obesity is believed to be one of the major risk factors for cardiovascular disease in Western countries. However, the effects of obesity should be continuously examined in the Japanese population because the average bodily habitus differs among countries. In this study, we collectively examined the significance of obesity and obesity-triggered risk factors including the low reactivity of B-type natriuretic peptide (BNP), for ischemic heart disease (IHD) in Japanese patients. The study patients consisted of 1252 subjects (IHD: n = 970; non-IHD: n = 282). Multiple logistic regression analysis revealed that dyslipidemia, hypertension, diabetes, and the low reactivity of BNP were significant risk factors for IHD, but body mass index (BMI) was not. A theoretical path model was proposed by positioning BMI at the top of the hierarchical model. Exploratory factor analysis revealed that BMI did not play a causative role in IHD (P = NS). BMI was causatively linked to other risk factors (P<0.001 for hypertension; P<0.001 for dyslipidemia; P<0.001 for HbA1c; P<0.001 for LogBNP), and these factors played a causative role in IHD (P<0.001 for hypertension; P<0.001 for dyslipidemia; P<0.001 for HbA1c; P<0.001 for LogBNP). The intrinsic power of the low reactivity of BNP induced by high BMI on the promotion of IHD was fairly potent. This study demonstrated that obesity per se is not a strong risk factor for IHD in Japanese patients. However, several important risk factors triggered by obesity exhibited a causative role for IHD. The low reactivity of BNP is a substantial risk factor for IHD.

Eating disorders and non-suicidal self-injury: Structural equation modelling of a conceptual model.

PubMed

Vieira, Ana Isabel; Machado, Bárbara C; Moreira, Célia S; Machado, Paulo P P; Brandão, Isabel; Roma-Torres, António; Gonçalves, Sónia

2018-06-14

Evidence suggests several risk factors for both eating disorders (ED) and nonsuicidal self-injury (NSSI), but the relationships between these factors are not well understood. Considering our previous work and a conceptual model, this cross-sectional study aimed to assess the relationships among distal and proximal factors for the presence of NSSI in ED. We assessed 245 ED patients with the Oxford Risk Factor Interview for ED. Structural equation modelling revealed that both distal and proximal factors were related to the presence of NSSI in ED, disclosing a mediating role of the proximal factors. Stressful life events mediated the relationship between childhood sexual abuse, peer aggression, and both ED and NSSI. Childhood physical abuse was related to ED and NSSI via substance use, negative self-evaluation, and suicide attempts. Findings provided support for the conceptual model and highlight the possible mechanisms by which psychosocial factors may lead to ED and NSSI. Copyright © 2018 John Wiley & Sons, Ltd and Eating Disorders Association.

New prognostic model for extranodal natural killer/T cell lymphoma, nasal type.

PubMed

Cai, Qingqing; Luo, Xiaolin; Zhang, Guanrong; Huang, Huiqiang; Huang, Hui; Lin, Tongyu; Jiang, Wenqi; Xia, Zhongjun; Young, Ken H

2014-09-01

Extranodal natural killer/T cell lymphoma, nasal type (ENKTL) is an aggressive disease with a poor prognosis, requiring risk stratification in affected patients. We designed a new prognostic model specifically for ENKTL to identify high-risk patients who need more aggressive therapy. We retrospectively reviewed 158 patients who were newly diagnosed with ENKTL. The estimated 5-year overall survival rate was 39.4 %. Independent prognostic factors included total protein (TP) <60 g/L, fasting blood glucose (FBG) >100 mg/dL, and Korean Prognostic Index (KPI) score ≥2. We constructed a new prognostic model by combining these prognostic factors: group 1 (64 cases (41.0 %)), no adverse factors; group 2 (58 cases (37.2 %)), one adverse factor; and group 3 (34 cases (21.8 %)), two or three adverse factors. The 5-year overall survival (OS) rates of these groups were 66.7, 23.0, and 5.9 %, respectively (p < 0.001). Our new prognostic model had a better prognostic value than did the KPI model alone (p < 0.001). Our proposed prognostic model for ENKTL, including the newly identified prognostic indicators, TP and FBG, demonstrated a balanced distribution of patients into different risk groups with better prognostic discrimination compared with the KPI model alone.

Use of surrogate indicators for the evaluation of potential health risks due to poor urban water quality: A Bayesian Network approach.

PubMed

Wijesiri, Buddhi; Deilami, Kaveh; McGree, James; Goonetilleke, Ashantha

2018-02-01

Urban water pollution poses risks of waterborne infectious diseases. Therefore, in order to improve urban liveability, effective pollution mitigation strategies are required underpinned by predictions generated using water quality models. However, the lack of reliability in current modelling practices detrimentally impacts planning and management decision making. This research study adopted a novel approach in the form of Bayesian Networks to model urban water quality to better investigate the factors that influence risks to human health. The application of Bayesian Networks was found to enhance the integration of quantitative and qualitative spatially distributed data for analysing the influence of environmental and anthropogenic factors using three surrogate indicators of human health risk, namely, turbidity, total nitrogen and fats/oils. Expert knowledge was found to be of critical importance in assessing the interdependent relationships between health risk indicators and influential factors. The spatial variability maps of health risk indicators developed enabled the initial identification of high risk areas in which flooding was found to be the most significant influential factor in relation to human health risk. Surprisingly, population density was found to be less significant in influencing health risk indicators. These high risk areas in turn can be subjected to more in-depth investigations instead of the entire region, saving time and resources. It was evident that decision making in relation to the design of pollution mitigation strategies needs to account for the impact of landscape characteristics on water quality, which can be related to risk to human health. Copyright © 2017 Elsevier Ltd. All rights reserved.

Transmission Risks of Schistosomiasis Japonica: Extraction from Back-propagation Artificial Neural Network and Logistic Regression Model

PubMed Central

Xu, Jun-Fang; Xu, Jing; Li, Shi-Zhu; Jia, Tia-Wu; Huang, Xi-Bao; Zhang, Hua-Ming; Chen, Mei; Yang, Guo-Jing; Gao, Shu-Jing; Wang, Qing-Yun; Zhou, Xiao-Nong

2013-01-01

Background The transmission of schistosomiasis japonica in a local setting is still poorly understood in the lake regions of the People's Republic of China (P. R. China), and its transmission patterns are closely related to human, social and economic factors. Methodology/Principal Findings We aimed to apply the integrated approach of artificial neural network (ANN) and logistic regression model in assessment of transmission risks of Schistosoma japonicum with epidemiological data collected from 2339 villagers from 1247 households in six villages of Jiangling County, P.R. China. By using the back-propagation (BP) of the ANN model, 16 factors out of 27 factors were screened, and the top five factors ranked by the absolute value of mean impact value (MIV) were mainly related to human behavior, i.e. integration of water contact history and infection history, family with past infection, history of water contact, infection history, and infection times. The top five factors screened by the logistic regression model were mainly related to the social economics, i.e. village level, economic conditions of family, age group, education level, and infection times. The risk of human infection with S. japonicum is higher in the population who are at age 15 or younger, or with lower education, or with the higher infection rate of the village, or with poor family, and in the population with more than one time to be infected. Conclusion/Significance Both BP artificial neural network and logistic regression model established in a small scale suggested that individual behavior and socioeconomic status are the most important risk factors in the transmission of schistosomiasis japonica. It was reviewed that the young population (≤15) in higher-risk areas was the main target to be intervened for the disease transmission control. PMID:23556015

Identifying gender specific risk/need areas for male and female juvenile offenders: Factor analyses with the Structured Assessment of Violence Risk in Youth (SAVRY).

PubMed

Hilterman, Ed L B; Bongers, Ilja; Nicholls, Tonia L; van Nieuwenhuizen, Chijs

2016-02-01

By constructing risk assessment tools in which the individual items are organized in the same way for male and female juvenile offenders it is assumed that these items and subscales have similar relevance across males and females. The identification of criminogenic needs that vary in relevance for 1 of the genders, could contribute to more meaningful risk assessments, especially for female juvenile offenders. In this study, exploratory factor analyses (EFA) on a construction sample of male (n = 3,130) and female (n = 466) juvenile offenders were used to aggregate the 30 items of the Structured Assessment of Violence Risk in Youth (SAVRY) into empirically based risk/need factors and explore differences between genders. The factor models were cross-validated through confirmatory factor analyses (CFA) on a validation sample of male (n = 2,076) and female (n = 357) juvenile offenders. In both the construction sample and the validation sample, 5 factors were identified: (a) Antisocial behavior; (b) Family functioning; (c) Personality traits; (d) Social support; and (e) Treatability. The male and female models were significantly different and the internal consistency of the factors was good, both in the construction sample and the validation sample. Clustering risk/need items for male and female juvenile offenders into meaningful factors may guide clinicians in the identification of gender-specific treatment interventions. PsycINFO Database Record (c) 2016 APA, all rights reserved.

Discriminative value of FRAX for fracture prediction in a cohort of Chinese postmenopausal women.

PubMed

Cheung, E Y N; Bow, C H; Cheung, C L; Soong, C; Yeung, S; Loong, C; Kung, A

2012-03-01

We followed 2,266 postmenopausal Chinese women for 4.5 years to determine which model best predicts osteoporotic fracture. A model that contains ethnic-specific risk factors, some of which reflect frailty, performed as well as or better than the well-established FRAX model. Clinical risk assessment, with or without T-score, can predict fractures in Chinese postmenopausal women although it is unknown which combination of clinical risk factors is most effective. This prospective study sought to compare the accuracy for fracture prediction using various models including FRAX, our ethnic-specific clinical risk factors (CRF) and other simple models. This study is part of the Hong Kong Osteoporosis Study. A total of 2,266 treatment naïve postmenopausal women underwent clinical risk factor and bone mineral density assessment. Subjects were followed up for outcome of major osteoporotic fracture and receiver operating characteristic (ROC) curves for different models were compared. The percentage of subjects in different quartiles of risk according to various models who actually fractured was also compared. The mean age at baseline was 62.1 ± 8.5 years and mean follow-up time was 4.5 ± 2.8 years. A total of 106 new major osteoporotic fractures were reported, of which 21 were hip fractures. Ethnic-specific CRF with T-score performed better than FRAX with T-score (based on both Chinese normative and National Health and Nutrition Examination Survey (NHANES) databases) in terms of AUC comparison for prediction of major osteoporotic fracture. The two models were similar in hip fracture prediction. The ethnic-specific CRF model had a 10% higher sensitivity than FRAX at a specificity of 0.8 or above. CRF related to frailty and differences in lifestyle between populations are likely to be important in fracture prediction. Further work is required to determine which and how CRF can be applied to develop a fracture prediction model in our population.

Family Maltreatment, Substance Problems, and Suicidality: Prevalence Surveillance and Ecological Risk/Protective Factors Models

DTIC Science & Technology

2010-04-01

Factors of Child Abuse in A Large Survey Sample. International FamilyViolence and Child Victimization Research Conference. Portsmouth, New...manuscript in preparation). Physical child abuse in a large-scale survey of the U.S. Air Force: Risk and promotive factors. Slep, A. M. S., Snarr, J...D., Heyman, R. E., & Foran, H. M. (manuscript in preparation). Risk and promotive factors for emotional child abuse among active duty U.S. Air

Risk factors.

PubMed

Robbins, Catherine J; Connors, K C; Sheehan, Timothy J; Vaughan, James S

2005-06-01

Minimize surprises on your financial statement by adopting a model for integrated risk management that: Examines interrelationships among operations, investments, and financing. Incorporates concepts of the capital asset pricing model to manage unexpected volatility

Mammographic breast density as a risk factor for breast cancer: awareness in a recently screened clinical sample.

PubMed

O'Neill, Suzanne C; Leventhal, Kara Grace; Scarles, Marie; Evans, Chalanda N; Makariou, Erini; Pien, Edward; Willey, Shawna

2014-01-01

Breast density is an established, independent risk factor for breast cancer. Despite this, density has not been included in standard risk models or routinely disclosed to patients. However, this is changing in the face of legal mandates and advocacy efforts. Little information exists regarding women's awareness of density as a risk factor, their personal risk, and risk management options. We assessed awareness of density as a risk factor and whether sociodemographic variables, breast cancer risk factors. and perceived breast cancer risk were associated with awareness in 344 women with a recent screening mammogram at a tertiary care center. Overall, 62% of women had heard about density as a risk factor and 33% had spoken to a provider about breast density. Of the sample, 18% reported that their provider indicated that they had high breast density. Awareness of density as a risk factor was greater among White women and those with other breast cancer risk factors. Our results suggest that although a growing number of women are aware of breast density as a risk factor, this awareness varies. Growing mandates for disclosure suggest the need for patient education interventions for women at increased risk for the disease and to ensure all women are equally aware of their risks. Copyright © 2014 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

Parent-child communication processes: preventing children's health-risk behavior.

PubMed

Riesch, Susan K; Anderson, Lori S; Krueger, Heather A

2006-01-01

Review individual, family, and environmental factors that predict health-risk behavior among children and to propose parent-child communication processes as a mechanism to mediate them. Improving parent-child communication processes may: reduce individual risk factors, such as poor academic achievement or self-esteem; modify parenting practices such as providing regulation and structure and acting as models of health behavior; and facilitate discussion about factors that lead to involvement in health-risk behaviors. Assessment strategies to identify youth at risk for health-risk behavior are recommended and community-based strategies to improve communication among parents and children need development.

The asset pricing model of musharakah factors

NASA Astrophysics Data System (ADS)

Simon, Shahril; Omar, Mohd; Lazam, Norazliani Md

2015-02-01

The existing three-factor model developed by Fama and French for conventional investment was formulated based on risk-free rates element in which contradict with Shariah principles. We note that the underlying principles that govern Shariah investment were mutual risk and profit sharing between parties, the assurance of fairness for all and that transactions were based on an underlying asset. In addition, the three-factor model did not exclude stock that was not permissible by Shariah such as financial services based on riba (interest), gambling operator, manufacture or sale of non-halal products or related products and other activities deemed non-permissible according to Shariah. Our approach to construct the factor model for Shariah investment was based on the basic tenets of musharakah in tabulating the factors. We start by noting that Islamic stocks with similar characteristics should have similar returns and risks. This similarity between Islamic stocks was defined by the similarity of musharakah attributes such as business, management, profitability and capital. These attributes define factor exposures (or betas) to factors. The main takeaways were that musharakah attributes we chose had explain stock returns well in cross section and were significant in different market environments. The management factor seemed to be responsible for the general dynamics of the explanatory power.

Relationship between FEV1 and Cardiovascular Risk Factors in General Population without Airflow Limitation.

PubMed

Lee, Jeong Hyeon; Kang, Yun-Seong; Jeong, Yun-Jeong; Yoon, Young-Soon; Kwack, Won Gun; Oh, Jin Young

2016-01-01

Purpose. We aimed to determine the value of lung function measurement for predicting cardiovascular (CV) disease by evaluating the association between FEV1 (%) and CV risk factors in general population. Materials and Methods. This was a cross-sectional, retrospective study of subjects above 18 years of age who underwent health examinations. The relationship between FEV1 (%) and presence of carotid plaque and thickened carotid IMT (≥0.8 mm) was analyzed by multiple logistic regression, and the relationship between FEV1 (%) and PWV (%), and serum uric acid was analyzed by multiple linear regression. Various factors were adjusted by using Model 1 and Model 2. Results. 1,003 subjects were enrolled in this study and 96.7% ( n = 970) of the subjects were men. In both models, the odds ratio of the presence of carotid plaque and thickened carotid IMT had no consistent trend and statistical significance. In the analysis of the PWV (%) and uric acid, there was no significant relationship with FEV1 (%) in both models. Conclusion. FEV1 had no significant relationship with CV risk factors. The result suggests that FEV1 may have no association with CV risk factors or may be insensitive to detecting the association in general population without airflow limitation.

A sudden death risk score specifically for hypertension: based on 25 648 individual patient data from six randomized controlled trials.

PubMed

Le, Hai-Ha; Subtil, Fabien; Cerou, Marc; Marchant, Ivanny; Al-Gobari, Muaamar; Fall, Mor; Mimouni, Yanis; Kassaï, Behrouz; Lindholm, Lars; Thijs, Lutgarde; Gueyffier, François

2017-11-01

To construct a sudden death risk score specifically for hypertension (HYSUD) patients with or without cardiovascular history. Data were collected from six randomized controlled trials of antihypertensive treatments with 8044 women and 17 604 men differing in age ranges and blood pressure eligibility criteria. In total, 345 sudden deaths (1.35%) occurred during a mean follow-up of 5.16 years. Risk factors of sudden death were examined using a multivariable Cox proportional hazards model adjusted on trials. The model was transformed to an integer system, with points added for each factor according to its association with sudden death risk. Antihypertensive treatment was not associated with a reduction of the sudden death risk and had no interaction with other factors, allowing model development on both treatment and placebo groups. A risk score of sudden death in 5 years was built with seven significant risk factors: age, sex, SBP, serum total cholesterol, cigarette smoking, diabetes, and history of myocardial infarction. In terms of discrimination performance, HYSUD model was adequate with areas under the receiver operating characteristic curve of 77.74% (confidence interval 95%, 74.13-81.35) for the derivation set, of 77.46% (74.09-80.83) for the validation set, and of 79.17% (75.94-82.40) for the whole population. Our work provides a simple risk-scoring system for sudden death prediction in hypertension, using individual data from six randomized controlled trials of antihypertensive treatments. HYSUD score could help assessing a hypertensive individual's risk of sudden death and optimizing preventive therapeutic strategies for these patients.

Construction of a model predicting the risk of tube feeding intolerance after gastrectomy for gastric cancer based on 225 cases from a single Chinese center

PubMed Central

Xiaoyong, Wu; Xuzhao, Li; Deliang, Yu; Pengfei, Yu; Zhenning, Hang; Bin, Bai; zhengyan, Li; Fangning, Pang; Shiqi, Wang; Qingchuan, Zhao

2017-01-01

Identifying patients at high risk of tube feeding intolerance (TFI) after gastric cancer surgery may prevent the occurrence of TFI; however, a predictive model is lacking. We therefore analyzed the incidence of TFI and its associated risk factors after gastric cancer surgery in 225 gastric cancer patients divided into without-TFI (n = 114) and with-TFI (n = 111) groups. A total of 49.3% of patients experienced TFI after gastric cancer. Multivariate analysis identified a history of functional constipation (FC), a preoperative American Society of Anesthesiologists (ASA) score of III, a high pain score at 6-hour postoperation, and a high white blood cell (WBC) count on the first day after surgery as independent risk factors for TFI. The area under the curve (AUC) was 0.756, with an optimal cut-off value of 0.5410. In order to identify patients at high risk of TFI after gastric cancer surgery, we constructed a predictive nomogram model based on the selected independent risk factors to indicate the probability of developing TFI. Use of our predictive nomogram model in screening, if a probability > 0.5410, indicated a high-risk patients would with a 70.1% likelihood of developing TFI. These high-risk individuals should take measures to prevent TFI before feeding with enteral nutrition. PMID:29245951

Utilization of the NSQIP-Pediatric Database in Development and Validation of a New Predictive Model of Pediatric Postoperative Wound Complications.

PubMed

Maizlin, Ilan I; Redden, David T; Beierle, Elizabeth A; Chen, Mike K; Russell, Robert T

2017-04-01

Surgical wound classification, introduced in 1964, stratifies the risk of surgical site infection (SSI) based on a clinical estimate of the inoculum of bacteria encountered during the procedure. Recent literature has questioned the accuracy of predicting SSI risk based on wound classification. We hypothesized that a more specific model founded on specific patient and perioperative factors would more accurately predict the risk of SSI. Using all observations from the 2012 to 2014 pediatric National Surgical Quality Improvement Program-Pediatric (NSQIP-P) Participant Use File, patients were randomized into model creation and model validation datasets. Potential perioperative predictive factors were assessed with univariate analysis for each of 4 outcomes: wound dehiscence, superficial wound infection, deep wound infection, and organ space infection. A multiple logistic regression model with a step-wise backwards elimination was performed. A receiver operating characteristic curve with c-statistic was generated to assess the model discrimination for each outcome. A total of 183,233 patients were included. All perioperative NSQIP factors were evaluated for clinical pertinence. Of the original 43 perioperative predictive factors selected, 6 to 9 predictors for each outcome were significantly associated with postoperative SSI. The predictive accuracy level of our model compared favorably with the traditional wound classification in each outcome of interest. The proposed model from NSQIP-P demonstrated a significantly improved predictive ability for postoperative SSIs than the current wound classification system. This model will allow providers to more effectively counsel families and patients of these risks, and more accurately reflect true risks for individual surgical patients to hospitals and payers. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Toward a cumulative ecological risk model for the etiology of child maltreatment

PubMed Central

MacKenzie, Michael J.; Kotch, Jonathan B.; Lee, Li-Ching

2011-01-01

The purpose of the current study was to further the integration of cumulative risk models with empirical research on the etiology of child maltreatment. Despite the well-established literature supporting the importance of the accumulation of ecological risk, this perspective has had difficulty infiltrating empirical maltreatment research and its tendency to focus on more limited risk factors. Utilizing a sample of 842 mother-infant dyads, we compared the capacity of individual risk factors and a cumulative index to predict maltreatment reports in a prospective longitudinal investigation over the first sixteen years of life. The total load of risk in early infancy was found to be related to maternal cognitions surrounding her new role, measures of social support and well-being, and indicators of child cognitive functioning. After controlling for total level of cumulative risk, most single factors failed to predict later maltreatment reports and no single variable provided odd-ratios as powerful as the predictive power of a cumulative index. Continuing the shift away from simplistic causal models toward an appreciation for the cumulative nature of risk would be an important step forward in the way we conceptualize intervention and support programs, concentrating them squarely on alleviating the substantial risk facing so many of society’s families. PMID:24817777

Risk Transfer Formula for Individual and Small Group Markets Under the Affordable Care Act

PubMed Central

Pope, Gregory C; Bachofer, Henry; Pearlman, Andrew; Kautter, John; Hunter, Elizabeth; Miller, Daniel; Keenan, Patricia

2014-01-01

The Affordable Care Act provides for a program of risk adjustment in the individual and small group health insurance markets in 2014 as Marketplaces are implemented and new market reforms take effect. The purpose of risk adjustment is to lessen or eliminate the influence of risk selection on the premiums that plans charge. The risk adjustment methodology includes the risk adjustment model and the risk transfer formula. This article is the third of three in this issue of the Medicare & Medicaid Research Review that describe the ACA risk adjustment methodology and focuses on the risk transfer formula. In our first companion article, we discussed the key issues and choices in developing the methodology. In our second companion paper, we described the risk adjustment model that is used to calculate risk scores. In this article we present the risk transfer formula. We first describe how the plan risk score is combined with factors for the plan allowable premium rating, actuarial value, induced demand, geographic cost, and the statewide average premium in a formula that calculates transfers among plans. We then show how each plan factor is determined, as well as how the factors relate to each other in the risk transfer formula. The goal of risk transfers is to offset the effects of risk selection on plan costs while preserving premium differences due to factors such as actuarial value differences. Illustrative numerical simulations show the risk transfer formula operating as anticipated in hypothetical scenarios. PMID:25352994

Gender Differential Influences of Early Adolescent Risk Factors for the Development of Depressive Affect.

ERIC Educational Resources Information Center

Stemmler, Mark; Petersen, Anne C.

2005-01-01

Based on a model by Cyranowski, J., et al. (2000), Arch. Gen. Psychiatry 57: 21-27, adolescents at-risk for the development of depressive symptoms were identified. Adolescents were considered at-risk if they had 2 or more of the following early adolescent risk factors: (1) insecure parental attachment, (2) anxious/inhibited temperament, (3) low…

Risk Factors for Venous Thromboembolism in Pediatric Trauma Patients and Validation of a Novel Scoring System: The Risk of Clots in Kids with Trauma (ROCKIT score)

PubMed Central

Yen, Jennifer; Van Arendonk, Kyle J.; Streiff, Michael B.; McNamara, LeAnn; Stewart, F. Dylan; Conner G, Kim G; Thompson, Richard E.; Haut, Elliott R.; Takemoto, Clifford M.

2017-01-01

OBJECTIVES Identify risk factors for venous thromboembolism (VTE) and develop a VTE risk assessment model for pediatric trauma patients. DESIGN, SETTING, AND PATIENTS We performed a retrospective review of patients 21 years and younger who were hospitalized following traumatic injuries at the John Hopkins level 1 adult and pediatric trauma center (1987-2011). The clinical characteristics of patients with and without VTE were compared, and multivariable logistic regression analysis was used to identify independent risk factors for VTE. Weighted risk assessment scoring systems were developed based on these and previously identified factors from patients in the National Trauma Data Bank (NTDB 2008-2010); the scoring systems were validated in this cohort from Johns Hopkins as well as a cohort of pediatric admissions from the NTDB (2011-2012). MAIN RESULTS Forty-nine of 17,366 pediatric trauma patients (0.28%) were diagnosed with VTE after admission to our trauma center. After adjusting for potential confounders, VTE was independently associated with older age, surgery, blood transfusion, higher Injury Severity Score (ISS), and lower Glasgow Coma Scale (GCS) score. These and additional factors were identified in 402,329 pediatric patients from the NTDB from 2008-2010; independent risk factors from the logistic regression analysis of this NTDB cohort were selected and incorporated into weighted risk assessment scoring systems. Two models were developed and were cross-validated in 2 separate pediatric trauma cohorts: 1) 282,535 patients in the NTDB from 2011 to 2012 2) 17,366 patients from Johns Hopkins. The receiver operator curve using these models in the validation cohorts had area under the curves that ranged 90% to 94%. CONCLUSIONS VTE is infrequent after trauma in pediatric patients. We developed weighted scoring systems to stratify pediatric trauma patients at risk for VTE. These systems may have potential to guide risk-appropriate VTE prophylaxis in children after trauma. PMID:26963757

Incremental Value of Repeated Risk Factor Measurements for Cardiovascular Disease Prediction in Middle-Aged Korean Adults: Results From the NHIS-HEALS (National Health Insurance System-National Health Screening Cohort).

PubMed

Cho, In-Jeong; Sung, Ji Min; Chang, Hyuk-Jae; Chung, Namsik; Kim, Hyeon Chang

2017-11-01

Increasing evidence suggests that repeatedly measured cardiovascular disease (CVD) risk factors may have an additive predictive value compared with single measured levels. Thus, we evaluated the incremental predictive value of incorporating periodic health screening data for CVD prediction in a large nationwide cohort with periodic health screening tests. A total of 467 708 persons aged 40 to 79 years and free from CVD were randomly divided into development (70%) and validation subcohorts (30%). We developed 3 different CVD prediction models: a single measure model using single time point screening data; a longitudinal average model using average risk factor values from periodic screening data; and a longitudinal summary model using average values and the variability of risk factors. The development subcohort included 327 396 persons who had 3.2 health screenings on average and 25 765 cases of CVD over 12 years. The C statistics (95% confidence interval [CI]) for the single measure, longitudinal average, and longitudinal summary models were 0.690 (95% CI, 0.682-0.698), 0.695 (95% CI, 0.687-0.703), and 0.752 (95% CI, 0.744-0.760) in men and 0.732 (95% CI, 0.722-0.742), 0.735 (95% CI, 0.725-0.745), and 0.790 (95% CI, 0.780-0.800) in women, respectively. The net reclassification index from the single measure model to the longitudinal average model was 1.78% in men and 1.33% in women, and the index from the longitudinal average model to the longitudinal summary model was 32.71% in men and 34.98% in women. Using averages of repeatedly measured risk factor values modestly improves CVD predictability compared with single measurement values. Incorporating the average and variability information of repeated measurements can lead to great improvements in disease prediction. URL: https://www.clinicaltrials.gov. Unique identifier: NCT02931500. © 2017 American Heart Association, Inc.

An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes

PubMed Central

Shapira, Stav; Novack, Lena; Bar-Dayan, Yaron; Aharonson-Daniel, Limor

2016-01-01

Background A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities’ preparedness and response capabilities and to mitigate future consequences. Methods An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model’s algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel. Results the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard. Conclusion The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties. PMID:26959647

Modeling metabolic syndrome and its association with cognition: the Northern Manhattan study.

PubMed

Levin, Bonnie E; Llabre, Maria M; Dong, Chuanhui; Elkind, Mitchell S V; Stern, Yaakov; Rundek, Tatjana; Sacco, Ralph L; Wright, Clinton B

2014-11-01

Metabolic syndrome (MetS) is a clustering of vascular risk factors and is associated with increased risk of cardiovascular disease. Less is known about the relationship between MetS and cognition. We examined component vascular risk factors of MetS as correlates of different cognitive domains. The Northern Manhattan Study (NOMAS) includes 1290 stroke-free participants from a largely Hispanic multi-ethnic urban community. We used structural equation modeling (SEM) to model latent variables of MetS, assessed at baseline and an average of 10 years later, at which time participants also underwent a full cognitive battery. The two four-factor models, of the metabolic syndrome (blood pressure, lipid levels, obesity, and fasting glucose) and of cognition (language, executive function, psychomotor, and memory), were each well supported (CFI=0.97 and CFI=0.95, respectively). When the two models were combined, the correlation between metabolic syndrome and cognition was -.31. Among the metabolic syndrome components, only blood pressure uniquely predicted all four cognitive domains. After adjusting for age, gender, race/ethnicity, education, smoking, alcohol, and risk factor treatment variables, blood pressure remained a significant correlate of all domains except memory. In this stroke-free race/ethnically diverse community-based cohort, MetS was associated with cognitive function suggesting that MetS and its components may be important predictors of cognitive outcomes. After adjusting for sociodemographic and vascular risk factors, blood pressure was the strongest correlate of cognitive performance. Findings suggest MetS, and in particular blood pressure, may represent markers of vascular or neurodegenerative damage in aging populations.

Sunlight exposure and cardiovascular risk factors in the REGARDS study: a cross-sectional split-sample analysis

PubMed Central

2014-01-01

Background Previous research has suggested that vitamin D and sunlight are related to cardiovascular outcomes, but associations between sunlight and risk factors have not been investigated. We examined whether increased sunlight exposure was related to improved cardiovascular risk factor status. Methods Residential histories merged with satellite, ground monitor, and model reanalysis data were used to determine previous-year sunlight radiation exposure for 17,773 black and white participants aged 45+ from the US. Exploratory and confirmatory analyses were performed by randomly dividing the sample into halves. Logistic regression models were used to examine relationships with cardiovascular risk factors. Results The lowest, compared to the highest quartile of insolation exposure was associated with lower high-density lipoprotein levels in adjusted exploratory (−2.7 mg/dL [95% confidence interval: −4.2, −1.2]) and confirmatory (−1.5 mg/dL [95% confidence interval: −3.0, −0.1]) models. The lowest, compared to the highest quartile of insolation exposure was associated with higher systolic blood pressure levels in unadjusted exploratory and confirmatory, as well as the adjusted exploratory model (2.3 mmHg [95% confidence interval: 0.8, 3.8]), but not the adjusted confirmatory model (1.6 mg/dL [95% confidence interval: −0.5, 3.7]). Conclusions The results of this study suggest that lower long-term sunlight exposure has an association with lower high-density lipoprotein levels. However, all associations were weak, thus it is not known if insolation may affect cardiovascular outcomes through these risk factors. PMID:24946776

Hazardous drinking and military community functioning: identifying mediating risk factors.

PubMed

Foran, Heather M; Heyman, Richard E; Slep, Amy M Smith

2011-08-01

Hazardous drinking is a serious societal concern in military populations. Efforts to reduce hazardous drinking among military personnel have been limited in effectiveness. There is a need for a deeper understanding of how community-based prevention models apply to hazardous drinking in the military. Community-wide prevention efforts may be most effective in targeting community functioning (e.g., support from formal agencies, community cohesion) that impacts hazardous drinking via other proximal risk factors. The goal of the current study is to inform community-wide prevention efforts by testing a model of community functioning and mediating risk factors of hazardous drinking among active duty U.S. Air Force personnel. A large, representative survey sample of U.S. Air Force active duty members (N = 52,780) was collected at 82 bases worldwide. Hazardous drinking was assessed with the widely used Alcohol Use Disorders Identification Test (Saunders, Aasland, Babor, de la Fuente, & Grant, 1993). A variety of individual, family, and community measures were also assessed. Structural equation modeling was used to test a hypothesized model of community functioning, mediating risk factors and hazardous drinking. Depressive symptoms, perceived financial stress, and satisfaction with the U.S. Air Force were identified as significant mediators of the link between community functioning and hazardous drinking for men and women. Relationship satisfaction was also identified as a mediator for men. These results provide a framework for further community prevention research and suggest that prevention efforts geared at increasing aspects of community functioning (e.g., the U.S. Air Force Community Capacity model) may indirectly lead to reductions in hazardous drinking through other proximal risk factors.

The Joint Effects of Lifestyle Factors and Comorbidities on the Risk of Colorectal Cancer: A Large Chinese Retrospective Case-Control Study

PubMed Central

Hu, Hai; Zhou, Yangyang; Ren, Shujuan; Wu, Jiajin; Zhu, Meiying; Chen, Donghui; Yang, Haiyan; Wang, Liwei

2015-01-01

Background Colorectal cancer (CRC) is a major cause of cancer morbidity and mortality. In previous epidemiologic studies, the respective correlation between lifestyle factors and comorbidity and CRC has been extensively studied. However, little is known about their joint effects on CRC. Methods We conducted a retrospective case-control study of 1,144 diagnosed CRC patients and 60,549 community controls. A structured questionnaire was administered to the participants about their socio-demographic factors, anthropometric measures, comorbidity history and lifestyle factors. Logistic regression model was used to calculate the odds ratio (ORs) and 95% confidence intervals (95%CIs) for each factor. According to the results from logistic regression model, we further developed healthy lifestyle index (HLI) and comorbidity history index (CHI) to investigate their independent and joint effects on CRC risk. Results Four lifestyle factors (including physical activities, sleep, red meat and vegetable consumption) and four types of comorbidity (including diabetes, hyperlipidemia, history of inflammatory bowel disease and polyps) were found to be independently associated with the risk of CRC in multivariant logistic regression model. Intriguingly, their combined pattern- HLI and CHI demonstrated significant correlation with CRC risk independently (ORHLI: 3.91, 95%CI: 3.13–4.88; ORCHI: 2.49, 95%CI: 2.11–2.93) and jointly (OR: 10.33, 95%CI: 6.59–16.18). Conclusions There are synergistic effects of lifestyle factors and comorbidity on the risk of colorectal cancer in the Chinese population. PMID:26710070

Predictions of space radiation fatality risk for exploration missions.

PubMed

Cucinotta, Francis A; To, Khiet; Cacao, Eliedonna

2017-05-01

In this paper we describe revisions to the NASA Space Cancer Risk (NSCR) model focusing on updates to probability distribution functions (PDF) representing the uncertainties in the radiation quality factor (QF) model parameters and the dose and dose-rate reduction effectiveness factor (DDREF). We integrate recent heavy ion data on liver, colorectal, intestinal, lung, and Harderian gland tumors with other data from fission neutron experiments into the model analysis. In an earlier work we introduced distinct QFs for leukemia and solid cancer risk predictions, and here we consider liver cancer risks separately because of the higher RBE's reported in mouse experiments compared to other tumors types, and distinct risk factors for liver cancer for astronauts compared to the U.S. The revised model is used to make predictions of fatal cancer and circulatory disease risks for 1-year deep space and International Space Station (ISS) missions, and a 940 day Mars mission. We analyzed the contribution of the various model parameter uncertainties to the overall uncertainty, which shows that the uncertainties in relative biological effectiveness (RBE) factors at high LET due to statistical uncertainties and differences across tissue types and mouse strains are the dominant uncertainty. NASA's exposure limits are approached or exceeded for each mission scenario considered. Two main conclusions are made: 1) Reducing the current estimate of about a 3-fold uncertainty to a 2-fold or lower uncertainty will require much more expansive animal carcinogenesis studies in order to reduce statistical uncertainties and understand tissue, sex and genetic variations. 2) Alternative model assumptions such as non-targeted effects, increased tumor lethality and decreased latency at high LET, and non-cancer mortality risks from circulatory diseases could significantly increase risk estimates to several times higher than the NASA limits. Copyright © 2017 The Committee on Space Research (COSPAR). Published by Elsevier Ltd. All rights reserved.

[Risk factors on the recurrence of ischemic stroke and the establishment of a Cox's regression model].

PubMed

An, Ya-chen; Chen, Yun-xia; Wang, Yu-xun; Zhao, Xiao-jing; Wang, Yan; Zhang, Jiang; Li, Chun-ling; Peng, Yan-bo; Gao, Su-ling; Chang, Li-sha; Zhang, Li; Xue, Xin-hong; Chen, Rui-ying; Wang, Da-li

2011-08-01

To investigate the risk factors and establish the Cox's regression model on the recurrence of ischemic stroke. We retrospectively reviewed consecutive patients with ischemic stroke admitted to the Neurology Department of the Hebei United University Affiliated Hospital between January 1, 2008 and December 31, 2009. Cases had been followed since the onset of ischemic stroke. The follow-up program was finished in June 30, 2010. Kaplan-Meier methods were used to describe the recurrence rate. Monovariant and multivariate Cox's proportional hazard regression model were used to analyze the risk factors associated to the episodes of recurrence. And then, a recurrence model was set up. During the period of follow-up program, 79 cases were relapsed, with the recurrence rates as 12.75% in one year and 18.87% in two years. Monovariant and multivariate Cox's proportional hazard regression model showed that the independent risk factors that were associated with the recurrence appeared to be age (X₁) (RR = 1.025, 95%CI: 1.003 - 1.048), history of hypertension (X₂) (RR = 1.976, 95%CI: 1.014 - 3.851), history of family strokes (X₃) (RR = 2.647, 95%CI: 1.175 - 5.961), total cholesterol amount (X₄) (RR = 1.485, 95%CI: 1.214 - 1.817), ESRS total scores (X₅) (RR = 1.327, 95%CI: 1.057 - 1.666) and progression of the disease (X₆) (RR = 1.889, 95%CI: 1.123 - 3.178). Personal prognosis index (PI) of the recurrence model was as follows: PI = 0.025X₁ + 0.681X₂ + 0.973X₃ + 0.395X₄ + 0.283X₅ + 0.636X₆. The smaller the personal prognosis index was, the lower the recurrence risk appeared, while the bigger the personal prognosis index was, the higher the recurrence risk appeared. Age, history of hypertension, total cholesterol amount, total scores of ESRS, together with the disease progression were the independent risk factors associated with the recurrence episodes of ischemic stroke. Both recurrence model and the personal prognosis index equation were successful constructed.

Avoidable Burden of Risk Factors for Serious Road Traffic Crashes in Iran: A Modeling Study.

PubMed

Khosravi Shadmani, Fatemeh; Mansori, Kamyar; Karami, Manoochehr; Zayeri, Farid; Shadman, Reza Khosravi; Hanis, Shiva Mansouri; Soori, Hamid

2017-03-01

The aim of this study was to model the avoidable burden of the risk factors of road traffic crashes in Iran and to prioritize interventions to reduce that burden. The prevalence and the effect size of the risk factors were obtained from data documented by the traffic police of Iran in 2013. The effect size was estimated using an ordinal regression model. The potential impact fraction index was applied to calculate the avoidable burden in order to prioritize interventions. This index was calculated for theoretical, plausible, and feasible minimum risk level scenarios. The joint effects of the risk factors were then estimated for all the scenarios. The highest avoidable burdens in the theoretical, plausible, and feasible minimum risk level scenarios for the non-use of child restraints on urban roads were 52.25, 28.63, and 46.67, respectively. In contrast, the value of this index for speeding was 76.24, 37.00, and 62.23, respectively, for rural roads. On the basis of the different scenarios considered in this research, we suggest focusing on future interventions to decrease the prevalence of speeding, the non-use of child restraints, the use of cell phones while driving, and helmet disuse, and the laws related to these items should be considered seriously.

Comparison of cluster-based and source-attribution methods for estimating transmission risk using large HIV sequence databases.

PubMed

Le Vu, Stéphane; Ratmann, Oliver; Delpech, Valerie; Brown, Alison E; Gill, O Noel; Tostevin, Anna; Fraser, Christophe; Volz, Erik M

2018-06-01

Phylogenetic clustering of HIV sequences from a random sample of patients can reveal epidemiological transmission patterns, but interpretation is hampered by limited theoretical support and statistical properties of clustering analysis remain poorly understood. Alternatively, source attribution methods allow fitting of HIV transmission models and thereby quantify aspects of disease transmission. A simulation study was conducted to assess error rates of clustering methods for detecting transmission risk factors. We modeled HIV epidemics among men having sex with men and generated phylogenies comparable to those that can be obtained from HIV surveillance data in the UK. Clustering and source attribution approaches were applied to evaluate their ability to identify patient attributes as transmission risk factors. We find that commonly used methods show a misleading association between cluster size or odds of clustering and covariates that are correlated with time since infection, regardless of their influence on transmission. Clustering methods usually have higher error rates and lower sensitivity than source attribution method for identifying transmission risk factors. But neither methods provide robust estimates of transmission risk ratios. Source attribution method can alleviate drawbacks from phylogenetic clustering but formal population genetic modeling may be required to estimate quantitative transmission risk factors. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Can demographic, clinical and treatment-related factors available at hormonal therapy initiation predict non-persistence in women with stage I-III breast cancer?

PubMed

Cahir, Caitriona; Barron, Thomas I; Sharp, Linda; Bennett, Kathleen

2017-03-01

To investigate whether demographic, clinical and treatment-related risk factors known at treatment initiation can be used to reliably predict future hormonal therapy non-persistence in women with breast cancer, and to inform intervention development. Women with stage I-III breast cancer diagnosed 2000-2012 and prescribed hormonal therapy were identified from the National Cancer Registry Ireland (NCRI) and linked to pharmacy claims data from Ireland's Primary Care Reimbursement Services (PCRS). Non-persistence was defined as a treatment gap of ≥180 days within 5 years of initiation. Seventeen demographic, clinical and treatment-related risk factors, identified from a systematic review, were abstracted from the NCRI-PCRS dataset. Multivariate binomial models were used to estimate relative risks (RR) and risk differences (RD) for associations between risk factors and non-persistence. Calibration and discriminative performance of the models were assessed. The analysis was repeated for early non-persistence (<1 year of initiation). Within 5 years of treatment initiation 680 women (19.9%) were non-persistent. Women aged <50 years (adjusted RR 1.41, 95% CI 1.16-1.70) and those prescribed antidepressants (RR 1.22, 95% CI 1.04-1.45) had increased risk of non-persistence. Married women (RR 0.82 95% CI 0.71-0.94) and those with prior medication use (RR 0.62 95% CI 0.51-0.75) had reduced risk of non-persistence. The area under the receiver-operating characteristic (ROC) curve for non-persistence was 0.61. Findings were similar for early non-persistence. The risk prediction model did not discriminate well between women at higher and lower risk of non-persistence at treatment initiation. Future studies should consider other factors, such as psychological characteristics and experience of side-effects.

A Model to Estimate the Risk of Breast Cancer-Related Lymphedema: Combinations of Treatment-Related Factors of the Number of Dissected Axillary Nodes, Adjuvant Chemotherapy, and Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Myungsoo; Kim, Seok Won; Lee, Sung Uk

2013-07-01

Purpose: The development of breast cancer-related lymphedema (LE) is closely related to the number of dissected axillary lymph nodes (N-ALNs), chemotherapy, and radiation therapy. In this study, we attempted to estimate the risk of LE based on combinations of these treatment-related factors. Methods and Materials: A total of 772 patients with breast cancer, who underwent primary surgery with axillary lymph node dissection from 2004 to 2009, were retrospectively analyzed. Adjuvant chemotherapy (ACT) was performed in 677 patients (88%). Among patients who received radiation therapy (n=675), 274 (35%) received supraclavicular radiation therapy (SCRT). Results: At a median follow-up of 5.1 yearsmore » (range, 3.0-8.3 years), 127 patients had developed LE. The overall 5-year cumulative incidence of LE was 17%. Among the 127 affected patients, LE occurred within 2 years after surgery in 97 (76%) and within 3 years in 115 (91%) patients. Multivariate analysis showed that N-ALN (hazard ratio [HR], 2.81; P<.001), ACT (HR, 4.14; P=.048), and SCRT (HR, 3.24; P<.001) were independent risk factors for LE. The total number of risk factors correlated well with the incidence of LE. Patients with no risk or 1 risk factor showed a significantly lower 5-year probability of LE (3%) than patients with 2 (19%) or 3 risk factors (38%) (P<.001). Conclusions: The risk factors associated with LE were N-ALN, ACT, and SCRT. A simple model using combinations of these factors may help clinicians predict the risk of LE.« less

The role of burnout syndrome as a mediator for the effect of psychosocial risk factors on the intensity of musculoskeletal disorders: a structural equation modeling approach.

PubMed

Gholami, Tahereh; Pahlavian, Ahmad Heidari; Akbarzadeh, Mahdi; Motamedzade, Majid; Moghaddam, Rashid Heidari

2016-01-01

This study examined the hypothesis that burnout syndrome mediates effects of psychosocial risk factors and intensity of musculoskeletal disorders (MSDs) among hospital nurses. The sample was composed of 415 nurses from various wards across five hospitals of Iran's Hamedan University of Medical Sciences. Data were collected through three questionnaires: job content questionnaire, Maslach burnout inventory and visual analogue scale. Results of structural equation modeling with a mediating effect showed that psychosocial risk factors were significantly related to changes in burnout, which in turn affects intensity of MSDs.

Spatial Patterns and Impacts of Environmental and Climatic Factors on Canine Sinonasal Aspergillosis in Northern California

PubMed Central

Magro, Monise; Sykes, Jane; Vishkautsan, Polina; Martínez-López, Beatriz

2017-01-01

Sinonasal aspergillosis (SNA) causes chronic nasal discharge in dogs and has a worldwide distribution, although most reports of SNA in North America originate from the western USA. SNA is mainly caused by Aspergillus fumigatus, a ubiquitous saprophytic filamentous fungus. Infection is thought to follow inhalation of spores. SNA is a disease of the nasal cavity and/or sinuses with variable degrees of local invasion and destruction. While some host factors appear to predispose to SNA (such as belonging to a dolichocephalic breed), environmental risk factors have been scarcely studied. Because A. fumigatus is also the main cause of invasive aspergillosis in humans, unraveling the distribution and the environmental and climatic risk factors for this agent in dogs would be of great benefit for public health studies, advancing understanding of both distribution and risk factors in humans. In this study, we reviewed electronic medical records of 250 dogs diagnosed with SNA between 1990 and 2014 at the University of California Davis Veterinary Medical Teaching Hospital (VMTH). A 145-mile radius catchment area around the VMTH was selected. Data were aggregated by zip code and incorporated into a multivariate logistic regression model. The logistic regression model was compared to an autologistic regression model to evaluate the effect of spatial autocorrelation. Traffic density, active composting sites, and environmental and climatic factors related with wind and temperature were significantly associated with increase in disease occurrence in dogs. Results provide valuable information about the risk factors and spatial distribution of SNA in dogs in Northern California. Our ultimate goal is to utilize the results to investigate risk-based interventions, promote awareness, and serve as a model for further studies of aspergillosis in humans. PMID:28717638

Spatial Patterns and Impacts of Environmental and Climatic Factors on Canine Sinonasal Aspergillosis in Northern California.

PubMed

Magro, Monise; Sykes, Jane; Vishkautsan, Polina; Martínez-López, Beatriz

2017-01-01

Sinonasal aspergillosis (SNA) causes chronic nasal discharge in dogs and has a worldwide distribution, although most reports of SNA in North America originate from the western USA. SNA is mainly caused by Aspergillus fumigatus , a ubiquitous saprophytic filamentous fungus. Infection is thought to follow inhalation of spores. SNA is a disease of the nasal cavity and/or sinuses with variable degrees of local invasion and destruction. While some host factors appear to predispose to SNA (such as belonging to a dolichocephalic breed), environmental risk factors have been scarcely studied. Because A. fumigatus is also the main cause of invasive aspergillosis in humans, unraveling the distribution and the environmental and climatic risk factors for this agent in dogs would be of great benefit for public health studies, advancing understanding of both distribution and risk factors in humans. In this study, we reviewed electronic medical records of 250 dogs diagnosed with SNA between 1990 and 2014 at the University of California Davis Veterinary Medical Teaching Hospital (VMTH). A 145-mile radius catchment area around the VMTH was selected. Data were aggregated by zip code and incorporated into a multivariate logistic regression model. The logistic regression model was compared to an autologistic regression model to evaluate the effect of spatial autocorrelation. Traffic density, active composting sites, and environmental and climatic factors related with wind and temperature were significantly associated with increase in disease occurrence in dogs. Results provide valuable information about the risk factors and spatial distribution of SNA in dogs in Northern California. Our ultimate goal is to utilize the results to investigate risk-based interventions, promote awareness, and serve as a model for further studies of aspergillosis in humans.

A prospective examination of the path from child abuse and neglect to illicit drug use in middle adulthood: the potential mediating role of four risk factors.

PubMed

Wilson, Helen W; Widom, Cathy Spatz

2009-03-01

This study examines prostitution, homelessness, delinquency and crime, and school problems as potential mediators of the relationship between childhood abuse and neglect (CAN) and illicit drug use in middle adulthood. Children with documented cases of physical and sexual abuse and neglect (ages 0-11) during 1967-1971 were matched with non-maltreated children and followed into middle adulthood (approximate age 39). Mediators were assessed in young adulthood (approximate age 29) through in-person interviews between 1989 and 1995 and official arrest records through 1994 (N = 1,196). Drug use was assessed via self-reports of past year use of marijuana, psychedelics, cocaine, and/or heroin during 2000-2002 (N = 896). Latent variable structural equation modeling (SEM) was used to test: (1) a four-factor model with separate pathways from CAN to illicit drug use through each of the mediating risk factors and (2) a second-order model with a single mediating risk factor comprised of prostitution, homelessness, delinquency and crime, and poor school performance. Analyses were performed separately for women and men, controlling for race/ethnicity and early drug use. In the four-factor model for both men and women, CAN was significantly related to each of the mediators, but no paths from the mediators to drug use were significant. For women, the second-order risk factor mediated the relationship between CAN and illicit drug use in middle adulthood. For men, neither child abuse and neglect nor the second-order risk factor predicted drug use in middle adulthood. These results suggest that for women, the path from CAN to middle adulthood drug use is part of a general "problem behavior syndrome" evident earlier in life.

Utility of genetic and non-genetic risk factors in predicting coronary heart disease in Singaporean Chinese.

PubMed

Chang, Xuling; Salim, Agus; Dorajoo, Rajkumar; Han, Yi; Khor, Chiea-Chuen; van Dam, Rob M; Yuan, Jian-Min; Koh, Woon-Puay; Liu, Jianjun; Goh, Daniel Yt; Wang, Xu; Teo, Yik-Ying; Friedlander, Yechiel; Heng, Chew-Kiat

2017-01-01

Background Although numerous phenotype based equations for predicting risk of 'hard' coronary heart disease are available, data on the utility of genetic information for such risk prediction is lacking in Chinese populations. Design Case-control study nested within the Singapore Chinese Health Study. Methods A total of 1306 subjects comprising 836 men (267 incident cases and 569 controls) and 470 women (128 incident cases and 342 controls) were included. A Genetic Risk Score comprising 156 single nucleotide polymorphisms that have been robustly associated with coronary heart disease or its risk factors ( p < 5 × 10 -8 ) in at least two independent cohorts of genome-wide association studies was built. For each gender, three base models were used: recalibrated Adult Treatment Panel III (ATPIII) Model (M 1 ); ATP III model fitted using Singapore Chinese Health Study data (M 2 ) and M 3 : M 2 + C-reactive protein + creatinine. Results The Genetic Risk Score was significantly associated with incident 'hard' coronary heart disease ( p for men: 1.70 × 10 -10 -1.73 × 10 -9 ; p for women: 0.001). The inclusion of the Genetic Risk Score in the prediction models improved discrimination in both genders (c-statistics: 0.706-0.722 vs. 0.663-0.695 from base models for men; 0.788-0.790 vs. 0.765-0.773 for women). In addition, the inclusion of the Genetic Risk Score also improved risk classification with a net gain of cases being reclassified to higher risk categories (men: 12.4%-16.5%; women: 10.2% (M 3 )), while not significantly reducing the classification accuracy in controls. Conclusions The Genetic Risk Score is an independent predictor for incident 'hard' coronary heart disease in our ethnic Chinese population. Inclusion of genetic factors into coronary heart disease prediction models could significantly improve risk prediction performance.

Incorporating Single-nucleotide Polymorphisms Into the Lyman Model to Improve Prediction of Radiation Pneumonitis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tucker, Susan L., E-mail: sltucker@mdanderson.org; Li Minghuan; Xu Ting

2013-01-01

Purpose: To determine whether single-nucleotide polymorphisms (SNPs) in genes associated with DNA repair, cell cycle, transforming growth factor-{beta}, tumor necrosis factor and receptor, folic acid metabolism, and angiogenesis can significantly improve the fit of the Lyman-Kutcher-Burman (LKB) normal-tissue complication probability (NTCP) model of radiation pneumonitis (RP) risk among patients with non-small cell lung cancer (NSCLC). Methods and Materials: Sixteen SNPs from 10 different genes (XRCC1, XRCC3, APEX1, MDM2, TGF{beta}, TNF{alpha}, TNFR, MTHFR, MTRR, and VEGF) were genotyped in 141 NSCLC patients treated with definitive radiation therapy, with or without chemotherapy. The LKB model was used to estimate the risk ofmore » severe (grade {>=}3) RP as a function of mean lung dose (MLD), with SNPs and patient smoking status incorporated into the model as dose-modifying factors. Multivariate analyses were performed by adding significant factors to the MLD model in a forward stepwise procedure, with significance assessed using the likelihood-ratio test. Bootstrap analyses were used to assess the reproducibility of results under variations in the data. Results: Five SNPs were selected for inclusion in the multivariate NTCP model based on MLD alone. SNPs associated with an increased risk of severe RP were in genes for TGF{beta}, VEGF, TNF{alpha}, XRCC1 and APEX1. With smoking status included in the multivariate model, the SNPs significantly associated with increased risk of RP were in genes for TGF{beta}, VEGF, and XRCC3. Bootstrap analyses selected a median of 4 SNPs per model fit, with the 6 genes listed above selected most often. Conclusions: This study provides evidence that SNPs can significantly improve the predictive ability of the Lyman MLD model. With a small number of SNPs, it was possible to distinguish cohorts with >50% risk vs <10% risk of RP when they were exposed to high MLDs.« less

Cardiorespiratory fitness and classification of risk of cardiovascular disease mortality.

PubMed

Gupta, Sachin; Rohatgi, Anand; Ayers, Colby R; Willis, Benjamin L; Haskell, William L; Khera, Amit; Drazner, Mark H; de Lemos, James A; Berry, Jarett D

2011-04-05

Cardiorespiratory fitness (fitness) is associated with cardiovascular disease (CVD) mortality. However, the extent to which fitness improves risk classification when added to traditional risk factors is unclear. Fitness was measured by the Balke protocol in 66 371 subjects without prior CVD enrolled in the Cooper Center Longitudinal Study between 1970 and 2006; follow-up was extended through 2006. Cox proportional hazards models were used to estimate the risk of CVD mortality with a traditional risk factor model (age, sex, systolic blood pressure, diabetes mellitus, total cholesterol, and smoking) with and without the addition of fitness. The net reclassification improvement and integrated discrimination improvement were calculated at 10 and 25 years. Ten-year risk estimates for CVD mortality were categorized as <1%, 1% to <5%, and ≥5%, and 25-year risk estimates were categorized as <8%, 8% to 30%, and ≥30%. During a median follow-up period of 16 years, there were 1621 CVD deaths. The addition of fitness to the traditional risk factor model resulted in reclassification of 10.7% of the men, with significant net reclassification improvement at both 10 years (net reclassification improvement=0.121) and 25 years (net reclassification improvement=0.041) (P<0.001 for both). The integrated discrimination improvement was 0.010 at 10 years (P<0.001), and the relative integrated discrimination improvement was 29%. Similar findings were observed for women at 25 years. A single measurement of fitness significantly improves classification of both short-term (10-year) and long-term (25-year) risk for CVD mortality when added to traditional risk factors.

Risk Factors for Hispanic Male Intimate Partner Violence Perpetration.

PubMed

Mancera, Bibiana M; Dorgo, Sandor; Provencio-Vasquez, Elias

2017-07-01

The literature review analyzed 24 studies that explored male intimate partner violence (IPV) perpetration risk factors among men, in particular Hispanics, using the socioecological model framework composed of four socioecological levels for violence prevention. Six databases were reviewed within the EBSCO search engine for articles published from 2000 to 2014. Articles reviewed were specific to risk factors for IPV perpetration among Hispanic men, focusing particularly on Mexican American men. Many key factors have previously been associated with risk for IPV perpetration; however, certain determinants are unique to Hispanics such as acculturation, acculturation stress, and delineated gender roles that include Machismo and Marianismo. These risk factors should be incorporated in future targeted prevention strategies and efforts and capitalize on the positive aspects of each to serve as protective factors.

Risk Factors for Hispanic Male Intimate Partner Violence Perpetration

PubMed Central

Mancera, Bibiana M.; Dorgo, Sandor; Provencio-Vasquez, Elias

2015-01-01

The literature review analyzed 24 studies that explored male intimate partner violence (IPV) perpetration risk factors among men, in particular Hispanics, using the socioecological model framework composed of four socioecological levels for violence prevention. Six databases were reviewed within the EBSCO search engine for articles published from 2000 to 2014. Articles reviewed were specific to risk factors for IPV perpetration among Hispanic men, focusing particularly on Mexican American men. Many key factors have previously been associated with risk for IPV perpetration; however, certain determinants are unique to Hispanics such as acculturation, acculturation stress, and delineated gender roles that include Machismo and Marianismo. These risk factors should be incorporated in future targeted prevention strategies and efforts and capitalize on the positive aspects of each to serve as protective factors. PMID:25891392

An antenatal prediction model for adverse birth outcomes in an urban population: The contribution of medical and non-medical risks.

PubMed

Posthumus, A G; Birnie, E; van Veen, M J; Steegers, E A P; Bonsel, G J

2016-07-01

in the Netherlands the perinatal mortality rate is high compared to other European countries. Around eighty percent of perinatal mortality cases is preceded by being small for gestational age (SGA), preterm birth and/or having a low Apgar-score at 5 minutes after birth. Current risk detection in pregnancy focusses primarily on medical risks. However, non-medical risk factors may be relevant too. Both non-medical and medical risk factors are incorporated in the Rotterdam Reproductive Risk Reduction (R4U) scorecard. We investigated the associations between R4U risk factors and preterm birth, SGA and a low Apgar score. a prospective cohort study under routine practice conditions. six midwifery practices and two hospitals in Rotterdam, the Netherlands. 836 pregnant women. the R4U scorecard was filled out at the booking visit. after birth, the follow-up data on pregnancy outcomes were collected. Multivariate logistic regression was used to fit models for the prediction of any adverse outcome (preterm birth, SGA and/or a low Apgar score), stratified for ethnicity and socio-economic status (SES). factors predicting any adverse outcome for Western women were smoking during the first trimester and over-the-counter medication. For non-Western women risk factors were teenage pregnancy, advanced maternal age and an obstetric history of SGA. Risk factors for high SES women were low family income, no daily intake of vegetables and a history of preterm birth. For low SES women risk factors appeared to be low family income, non-Western ethnicity, smoking during the first trimester and a history of SGA. the presence of both medical and non-medical risk factors early in pregnancy predict the occurrence of adverse outcomes at birth. Furthermore the risk profiles for adverse outcomes differed according to SES and ethnicity. to optimise effective risk selection, both medical and non-medical risk factors should be taken into account in midwifery and obstetric care at the booking visit. Copyright © 2016. Published by Elsevier Ltd.

Prognostic factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia: a systematic review and meta-analysis.

PubMed

Lee, Yee Mei; Lang, Dora; Lockwood, Craig

Increasing numbers of studies identify new prognostic factors for categorising chemotherapy-induced febrile neutropenia adult cancer patients into high- or low-risk groups for adverse outcomes. These groupings are used to tailor therapy according to level of risk. However many emerging factors with prognostic significance remain controversial, being based on single studies only. A systematic review was conducted to determine the strength of association of all identified factors associated with the outcomes of chemotherapy-induced febrile neutropenia patients. The participants included were adults of 15 years old and above, with a cancer diagnosis and who underwent cancer treatment.The review focused on clinical factors and their association with the outcomes of cancer patients with chemotherapy-induced febrile neutropenia at presentation of fever.All quantitative studies published in English which investigated clinical factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia were considered.The primary outcome of interest was to identify the clinical factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia. Electronic databases searched from their respective inception date up to December 2011 include MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, Science-Direct, Scopus and Mednar. The quality of the included studies was subjected to assessment by two independent reviewers. The standardised critical appraisal tool from the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) was used to assess the following criteria: representativeness of study population; clearly defined prognostic factors and outcomes; whether potential confounders were addressed and appropriate statistical analysis was undertaken for the study design. Data extraction was performed using a modified version of the standardised extraction tool from the JBI-MAStARI. Prognostic factors and the accompanying odds ratio reported for the significance of these factors that were identified by multivariate regression, were extracted from each included study. Studies results were pooled in statistical meta-analysis using Review Manager 5.1. Where statistical pooling was not possible, the findings were presented in narrative form. Seven studies (four prospective cohort and three retrospective cohort) investigating 22 factors in total were included. Fixed effects meta-analysis showed: hypotension [OR=1.66, 95%CI, 1.14-2.41, p=0.008] and thrombocytopenia [OR=3.92, 95%CI, 2.19-7.01, p<0.00001)] were associated with high-risk of adverse outcomes for febrile neutropenia. Other factors that were statistically significant from single studies included: age of patients, clinical presentation at fever onset, presence or absence of co-morbidities, infections, duration and severity of neutropenia state. Five prognostic factors failed to demonstrate an association between the variables and the outcomes measured and they include: presence of pneumonia, total febrile days, median days to fever, recovery from neutropenia and presence of moderate clinical symptoms in association with Gram-negative bacteraemia. Despite the overall limitations identified in the included studies, this review has provided a synthesis of the best available evidence for the prognostic factors used in risk stratification of febrile neutropenia patients. However, the dynamic aspects of prognostic model development, validation and utilisation have not been addressed adequately thus far. Given the findings of this review, it is timely to address these issues and improve the utilisation of prognostic models in the management of febrile neutropenia patients. The identified factors are similar to the factors in current prognostic models. However, additional factors that were reported to be statistically significant in this review (thrombocytopenia, presence of central venous catheter, and duration and severity of neutropenia) have not previously been included in prognostic models. This review has found these factors may improve the performance of current models by adding or replacing some of the factors. The role of risk stratification of chemotherapy-induced febrile neutropenia patients continues to evolve as the practice of risk-based therapy has been demonstrated to be beneficial to patients, clinicians and health care organisations. Further research to identify new factors /markers is needed to develop a new model which is reliable and accurate for these patients, regardless of cancer types. A robust and well-validated prognostic model is the key to enhance patient safety in the risk-based management of cancer patients with chemotherapy-induced febrile neutropenia.

Risk Factors for Substance Misuse and Adolescents’ Symptoms of Depression

PubMed Central

Siennick, Sonja E.; Widdowson, Alex O.; Woessner, Mathew K.; Feinberg, Mark E.; Spoth, Richard L.

2016-01-01

Purpose Depressive symptoms during adolescence are positively associated with peer-related beliefs, perceptions, and experiences that are known risk factors for substance misuse. These same risk factors are targeted by many universal substance misuse prevention programs. This study examined whether a multicomponent universal substance misuse intervention for middle schoolers reduced the associations between depressive symptoms, these risk factors, and substance misuse. Methods The study used data from a place-randomized trial of the PROSPER (PROmoting School-Community-University Partnerships to Enhance Resilience) model for delivery of evidence-based substance misuse programs for middle schoolers. Three-level within-person regression models were applied to four waves of survey and social network data from 636 adolescents followed from 6th through 9th grades. Results When adolescents in control school districts had more symptoms of depression, they believed more strongly that substance use had social benefits, perceived higher levels of substance misuse among their peers and friends, and had more friends who misused substances, although they were not more likely to use substances themselves. Many of the positive associations of depressive symptoms with peer-related risk factors were significantly weaker or not present among adolescents in intervention school districts. Conclusions The PROSPER interventions reduced the positive associations of adolescent symptoms of depression with peer-related risk factors for substance misuse. PMID:27751712

Control beliefs and risk for 4-year mortality in older adults: a prospective cohort study.

PubMed

Duan-Porter, Wei; Hastings, Susan Nicole; Neelon, Brian; Van Houtven, Courtney Harold

2017-01-11

Control beliefs are important psychological factors that likely contribute to heterogeneity in health outcomes for older adults. We evaluated whether control beliefs are associated with risk for 4-year mortality, after accounting for established "classic" biomedical risk factors. We also determined if an enhanced risk model with control beliefs improved identification of individuals with low vs. high mortality risk. We used nationally representative data from the Health and Retirement Study (2006-2012) for adults 50 years or older in 2006 (n = 7313) or 2008 (n = 6301). We assessed baseline perceived global control (measured as 2 dimensions-"constraints" and "mastery"), and health-specific control. We also obtained baseline data for 12 established biomedical risk factors of 4-year mortality: age, sex, 4 medical conditions (diabetes mellitus, cancer, lung disease and heart failure), body mass index less than 25 kg/m 2 , smoking, and 4 functional difficulties (with bathing, managing finances, walking several blocks and pushing or pulling heavy objects). Deaths within 4 years of follow-up were determined through interviews with respondents' family and the National Death Index. After accounting for classic biomedical risk factors, perceived constraints were significantly associated with higher mortality risk (third quartile scores odds ratio [OR] 1.37, 95% CI 1.03-1.81; fourth quartile scores OR 1.45, 95% CI, 1.09-1.92), while health-specific control was significantly associated with lower risk (OR 0.69-0.78 for scores above first quartile). Higher perceived mastery scores were not consistently associated with decreased risk. The enhanced model with control beliefs found an additional 3.5% of participants (n = 222) with low predicted risk of 4-year mortality (i.e., 4% or less); observed mortality for these individuals was 1.8% during follow-up. Compared with participants predicted to have low mortality risk only by the classic biomedical model, individuals identified by only the enhanced model were older, had higher educational status, higher income, and higher prevalence of diabetes mellitus and cancer. Control beliefs were significantly associated with risk for 4-year mortality; accounting for these factors improved identification of low-risk individuals. More work is needed to determine how assessment of control beliefs could enable targeting of clinical interventions to support at-risk older adults.

[Quantitative risk model for verocytotoxigenic Escherichia coli cross-contamination during homemade hamburger preparation].

PubMed

Signorini, M L; Frizzo, L S

2009-01-01

The objective of this study was to develop a quantitative risk model for verocytotoxigenic Escherichia coil (VTEC) cross-contamination during hamburger preparation at home. Published scientific information about the disease was considered for the elaboration of the model, which included a number of routines performed during food preparation in kitchens. The associated probabilities of bacterial transference between food items and kitchen utensils which best described each stage of the process were incorporated into the model by using @Risk software. Handling raw meat before preparing ready-to-eat foods (Odds ratio, OR, 6.57), as well as hand (OR = 12.02) and cutting board (OR = 5.02) washing habits were the major risk factors of VTEC cross-contamination from meat to vegetables. The information provided by this model should be considered when designing public information campaigns on hemolytic uremic syndrome risk directed to food handlers, in order to stress the importance of the above mentioned factors in disease transmission.

Prediction of HIV Sexual Risk Behaviors among Disadvantaged African American Adults using a Syndemic Conceptual Framework

PubMed Central

Nehl, Eric J.; Klein, Hugh; Sterk, Claire E.; Elifson, Kirk W.

2015-01-01

The focus of this paper is on HIV sexual risk taking among a community-based sample of disadvantaged African American adults. The objective is to examine multiple factors associated with sexual HIV risk behaviors within a syndemic conceptual framework. Face-to-face, computer-assisted, structured interviews were conducted with 1,535 individuals in Atlanta, Georgia. Bivariate analyses indicated a high level of relationships among the HIV sexual risks and other factors. Results from multivariate models indicated that gender, sexual orientation, relationship status, self-esteem, condom use self-efficacy, sex while the respondent was high, and sex while the partner was high were significant predictors of condomless sex. Additionally, a multivariate additive model of risk behaviors indicated that the number of health risks significantly increased the risk of condomless sex. This intersection of HIV sexual risk behaviors and their associations with various other behavioral, socio-demographics, and psychological functioning factors helps explain HIV risk-taking among this sample of African American adults and highlights the need for research and practice that accounts for multiple health behaviors and problems. PMID:26188618

Competing risks models and time-dependent covariates

PubMed Central

Barnett, Adrian; Graves, Nick

2008-01-01

New statistical models for analysing survival data in an intensive care unit context have recently been developed. Two models that offer significant advantages over standard survival analyses are competing risks models and multistate models. Wolkewitz and colleagues used a competing risks model to examine survival times for nosocomial pneumonia and mortality. Their model was able to incorporate time-dependent covariates and so examine how risk factors that changed with time affected the chances of infection or death. We briefly explain how an alternative modelling technique (using logistic regression) can more fully exploit time-dependent covariates for this type of data. PMID:18423067

Associations between dietary and lifestyle risk factors and colorectal cancer in the Scottish population.

PubMed

Theodoratou, Evropi; Farrington, Susan M; Tenesa, Albert; McNeill, Geraldine; Cetnarskyj, Roseanne; Korakakis, Emmanouil; Din, Farhat V N; Porteous, Mary E; Dunlop, Malcolm G; Campbell, Harry

2014-01-01

Colorectal cancer (CRC) accounts for 9.7% of all cancer cases and for 8% of all cancer-related deaths. Established risk factors include personal or family history of CRC as well as lifestyle and dietary factors. We investigated the relationship between CRC and demographic, lifestyle, food and nutrient risk factors through a case-control study that included 2062 patients and 2776 controls from Scotland. Forward and backward stepwise regression was applied and the stability of the models was assessed in 1000 bootstrap samples. The variables that were automatically selected to be included by the forward or backward stepwise regression and whose selection was verified by bootstrap sampling in the current study were family history, dietary energy, 'high-energy snack foods', eggs, juice, sugar-sweetened beverages and white fish (associated with an increased CRC risk) and NSAIDs, coffee and magnesium (associated with a decreased CRC risk). Application of forward and backward stepwise regression in this CRC study identified some already established as well as some novel potential risk factors. Bootstrap findings suggest that examination of the stability of regression models by bootstrap sampling is useful in the interpretation of study findings. 'High-energy snack foods' and high-energy drinks (including sugar-sweetened beverages and fruit juices) as risk factors for CRC have not been reported previously and merit further investigation as such snacks and beverages are important contributors in European and North American diets.

The association of corporate work environment factors, health risks, and medical conditions with presenteeism among Australian employees.

PubMed

Musich, Shirley; Hook, Dan; Baaner, Stephanie; Spooner, Michelle; Edington, Dee W

2006-01-01

To investigate the impact of selected corporate environment factors, health risks, and medical conditions on job performance using a self-reported measure of presenteeism. A cross-sectional survey utilizing health risk appraisal (HRA) data merging presenteeism with corporate environment factors, health risks, and medical conditions. Approximately 8000 employees across ten diverse Australian corporations. Employees (N = 1523; participation rate, 19%) who completed an HRA questionnaire. Self-reported HRA data were used to test associations of defined adverse corporate environment factors with presenteeism. Stepwise multivariate logistic regression modeling assessed the relative associations of corporate environment factors, health risks, and medical conditions with increased odds of any presenteeism. Increased presenteeism was significantly associated with poor working conditions, ineffective management/leadership, and work/life imbalance (adjusting for age, gender, health risks, and medical conditions). In multivariate logistic regression models, work/life imbalance, poor working conditions, life dissatisfaction, high stress, back pain, allergies, and younger age were significantly associated with presenteeism. Although the study has some limitations, including a possible response bias caused by the relatively low participation rate across the corporations, the study does demonstrate significant associations between corporate environment factors, health risks, and medical conditions and self-reported presenteeism. The study provides initial evidence that health management programming may benefit on-the-job productivity outcomes if expanded to include interventions targeting work environments.

Real time forest fire warning and forest fire risk zoning: a Vietnamese case study

NASA Astrophysics Data System (ADS)

Chu, T.; Pham, D.; Phung, T.; Ha, A.; Paschke, M.

2016-12-01

Forest fire occurs seriously in Vietnam and has been considered as one of the major causes of forest lost and degradation. Several studies of forest fire risk warning were conducted using Modified Nesterov Index (MNI) but remaining shortcomings and inaccurate predictions that needs to be urgently improved. In our study, several important topographic and social factors such as aspect, slope, elevation, distance to residential areas and road system were considered as "permanent" factors while meteorological data were updated hourly using near-real-time (NRT) remotely sensed data (i.e. MODIS Terra/Aqua and TRMM) for the prediction and warning of fire. Due to the limited number of weather stations in Vietnam, data from all active stations (i.e. 178) were used with the satellite data to calibrate and upscale meteorological variables. These data with finer resolution were then used to generate MNI. The only significant "permanent" factors were selected as input variables based on the correlation coefficients that computed from multi-variable regression among true fire-burning (collected from 1/2007) and its spatial characteristics. These coefficients also used to suggest appropriate weight for computing forest fire risk (FR) model. Forest fire risk model was calculated from the MNI and the selected factors using fuzzy regression models (FRMs) and GIS based multi-criteria analysis. By this approach, the FR was slightly modified from MNI by the integrated use of various factors in our fire warning and prediction model. Multifactor-based maps of forest fire risk zone were generated from classifying FR into three potential danger levels. Fire risk maps were displayed using webgis technology that is easy for managing data and extracting reports. Reported fire-burnings thereafter have been used as true values for validating the forest fire risk. Fire probability has strong relationship with potential danger levels (varied from 5.3% to 53.8%) indicating that the higher potential risk, the more chance of fire happen. By adding spatial factors to continuous daily updated remote sensing based meteo-data, results are valuable for both mapping forest fire risk zones in short and long-term and real time fire warning in Vietnam. Key words: Near-real-time, forest fire warning, fuzzy regression model, remote sensing.

Factors associated with suicide: Case-control study in South Tyrol.

PubMed

Giupponi, Giancarlo; Innamorati, Marco; Baldessarini, Ross J; De Leo, Diego; de Giovannelli, Francesca; Pycha, Roger; Conca, Andreas; Girardi, Paolo; Pompili, Maurizio

2018-01-01

As suicide is related to many factors in addition to psychiatric illness, broad and comprehensive risk-assessment for risk of suicide is required. This study aimed to differentiate nondiagnostic risk factors among suicides versus comparable psychiatric patients without suicidal behavior. We carried out a pilot, case-control comparison of 131 cases of suicide in South Tyrol matched for age and sex with 131 psychiatric controls, using psychological autopsy methods to evaluate differences in clinically assessed demographic, social, and clinical factors, using bivariate conditional Odds Risk comparisons followed by conditional regression modeling controlled for ethnicity. Based on multivariable conditional regression modeling, suicides were significantly more likely to have experienced risk factors, ranking as: [a] family history of suicide or attempt≥[b] recent interpersonal stressors≥[c] childhood traumatic events≥[d] lack of recent clinician contacts≥[e] previous suicide attempt≥[f] non-Italian ethnicity, but did not differ in education, marital status, living situation, or employment, nor by psychiatric or substance-abuse diagnoses. Both recent and early factors were associated with suicide, including lack of recent clinical care, non-Italian cultural subgroup-membership, familial suicidal behavior, and recent interpersonal distress. Copyright © 2017 Elsevier Inc. All rights reserved.

Inclusion of Functional Status Measures in the Risk Adjustment of 30-Day Mortality After Transcatheter Aortic Valve Replacement: A Report From the Society of Thoracic Surgeons/American College of Cardiology TVT Registry.

PubMed

Arnold, Suzanne V; O'Brien, Sean M; Vemulapalli, Sreekanth; Cohen, David J; Stebbins, Amanda; Brennan, J Matthew; Shahian, David M; Grover, Fred L; Holmes, David R; Thourani, Vinod H; Peterson, Eric D; Edwards, Fred H

2018-03-26

The aim of this study was to develop and validate a risk adjustment model for 30-day mortality after transcatheter aortic valve replacement (TAVR) that accounted for both standard clinical factors and pre-procedural health status and frailty. Assessment of risk for TAVR is important both for patient selection and provider comparisons. Prior efforts for risk adjustment have focused on in-hospital mortality, which is easily obtainable but can be biased because of early discharge of ill patients. Using data from patients who underwent TAVR as part of the Society of Thoracic Surgeons/American College of Cardiology TVT (Transcatheter Valve Therapy) Registry (June 2013 to May 2016), a hierarchical logistic regression model to estimate risk for 30-day mortality after TAVR based only on pre-procedural factors and access site was developed and internally validated. The model included factors from the original TVT Registry in-hospital mortality model but added the Kansas City Cardiomyopathy Questionnaire (health status) and gait speed (5-m walk test). Among 21,661 TAVR patients at 188 sites, 1,025 (4.7%) died within 30 days. Independent predictors of 30-day death included older age, low body weight, worse renal function, peripheral artery disease, home oxygen, prior myocardial infarction, left main coronary artery disease, tricuspid regurgitation, nonfemoral access, worse baseline health status, and inability to walk. The predicted 30-day mortality risk ranged from 1.1% (lowest decile of risk) to 13.8% (highest decile of risk). The model was able to stratify risk on the basis of patient factors with good discrimination (C = 0.71 [derivation], C = 0.70 [split-sample validation]) and excellent calibration, both overall and in key patient subgroups. A clinical risk model was developed for 30-day death after TAVR that included clinical data as well as health status and frailty. This model will facilitate tracking outcomes over time as TAVR expands to lower risk patients and to less experienced sites and will allow an objective comparison of short-term mortality rates across centers. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Risk and Protective Factors for Psychological Adjustment among Low-Income, African American Children

ERIC Educational Resources Information Center

Gabalda, Megan K.; Thompson, Martie P.; Kaslow, Nadine J.

2010-01-01

This investigation identifies unique risk and protective factors for internalizing and externalizing problems among 8- to 12-year-old, low-income, African American children and tests cumulative risk and protective models. A total of 152 mother-child dyads complete questionnaires. Receipt of food stamps, mother's distress, and child maltreatment…

Risk-Based Decision Model for Determining the Applicability of an Earned Value Management System in Construction

DTIC Science & Technology

2006-03-01

1989) present an innovative approach to quantifying risk . Their approach is to utilize linguistic terms or words and to systematically assign a...Together, these 15 factors were a first step in the problem of quantifying risk . These factors, and the four categories within which they fall, are

Risk assessment and risk scores in the management of aortic aneurysms.

PubMed

Von Meijenfeldt, Gerdine C I; Van Der Laan, Maarten J; Zeebregts, Clark J; Balm, Ron; Verhagen, Hence J M

2016-04-01

The decision whether to operate a patient or not can be challenging for a clinician for both ruptured abdominal aortic aneurysms (AAAs) as well as elective AAAs. Prior to surgical intervention it would be preferable that the clinician exactly knows which clinical variables lower or increase the chances of morbidity and mortality postintervention. To help in the preoperative counselling and shared decision making several clinical variables can be identified as risk factors and with these, risk models can be developed. An ideal risk score for aneurysm repair includes routinely obtained physiological and anatomical variables, has excellent discrimination and calibration, and is validated in different geographical areas. For elective AAA repair, several risk scores are available, for ruptured AAA treatment, these scores are far less well developed. In this manuscript, we describe the designs and results of published risk scores for elective and open repair. Also, suggestions for uniformly reporting of risk factors and their statistical analyses are described. Furthermore, the preliminary results of a new risk model for ruptured aortic aneurysm will be discussed. This score identifies age, hemoglobin, cardiopulmonary resuscitation and preoperative systolic blood pressure as risk factors after multivariate regression analysis. This new risk score can help to identify patients that would not benefit from repair, but it can also potentially identify patients who would benefit and therefore lower turndown rates. The challenge for further research is to expand on validation of already existing promising risk scores in order to come to a risk model with optimal discrimination and calibration.

Modeling an internal gear pump

NASA Astrophysics Data System (ADS)

Chen, Zongbin; Xu, Rongwu; He, Lin; Liao, Jian

2018-05-01

Considering the nature and characteristics of construction waste piles, this paper analyzed the factors affecting the stability of the slope of construction waste piles, and established the system of the assessment indexes for the slope failure risks of construction waste piles. Based on the basic principles and methods of fuzzy mathematics, the factor set and the remark set were established. The membership grade of continuous factor indexes is determined using the "ridge row distribution" function, while that for the discrete factor indexes was determined by the Delphi Method. For the weight of factors, the subjective weight was determined by the Analytic Hierarchy Process (AHP) and objective weight by the entropy weight method. And the distance function was introduced to determine the combination coefficient. This paper established a fuzzy comprehensive assessment model of slope failure risks of construction waste piles, and assessed pile slopes in the two dimensions of hazard and vulnerability. The root mean square of the hazard assessment result and vulnerability assessment result was the final assessment result. The paper then used a certain construction waste pile slope as the example for analysis, assessed the risks of the four stages of a landfill, verified the assessment model and analyzed the slope's failure risks and preventive measures against a slide.

Cross-sectional study to assess the association of population density with predicted breast cancer risk.

PubMed

Lee, Jeannette Y; Klimberg, Suzanne; Bondurant, Kristina L; Phillips, Martha M; Kadlubar, Susan A

2014-01-01

The Gail and CARE models estimate breast cancer risk for white and African-American (AA) women, respectively. The aims of this study were to compare metropolitan and nonmetropolitan women with respect to predicted breast cancer risks based on known risk factors, and to determine if population density was an independent risk factor for breast cancer risk. A cross-sectional survey was completed by 15,582 women between 35 and 85 years of age with no history of breast cancer. Metropolitan and nonmetropolitan women were compared with respect to risk factors, and breast cancer risk estimates, using general linear models adjusted for age. For both white and AA women, tisk factors used to estimate breast cancer risk included age at menarche, history of breast biopsies, and family history. For white women, age at first childbirth was an additional risk factor. In comparison to their nonmetropolitan counterparts, metropolitan white women were more likely to report having a breast biopsy, have family history of breast cancer, and delay childbirth. Among white metropolitan and nonmetropolitan women, mean estimated 5-year risks were 1.44% and 1.32% (p < 0.001), and lifetime risks of breast cancer were 10.81% and 10.01% (p < 0.001), respectively. AA metropolitan residents were more likely than those from nonmetropolitan areas to have had a breast biopsy. Among AA metropolitan and nonmetropolitan women, mean estimated 5-year risks were 1.16% and 1.12% (p = 0.039) and lifetime risks were 8.94%, and 8.85% (p = 0.344). Metropolitan residence was associated with higher predicted breast cancer risks for white women. Among AA women, metropolitan residence was associated with a higher predicted breast cancer risk at 5 years, but not over a lifetime. Population density was not an independent risk factor for breast cancer. © 2014 Wiley Periodicals, Inc.

A Biopsychosocial Conceptual Framework of Postpartum Depression Risk in Immigrant and U.S.-born Latina Mothers in the United States.

PubMed

Lara-Cinisomo, Sandraluz; Girdler, Susan S; Grewen, Karen; Meltzer-Brody, Samantha

2016-01-01

In this review, we offer a conceptual framework that identifies risk factors of postpartum depression (PPD) in immigrant and U.S.-born Latinas in the United States by focusing on psychosocial and neuroendocrine factors. Although the evidence of the impact psychosocial stressors have on the development of PPD has been well-documented, less is known about the biological etiology of PPD or how these complex stressors jointly increase the risk of PPD in immigrant and U.S.-born Latinas in the United States. Using PubMed, CINAHL, and Embase, we reviewed the literature from 2000 to 2015 regarding psychosocial and physiological risk factors associated with PPD to develop a conceptual model for Latinas. Our search yielded 16 relevant studies. Based on our review of the literature, we developed a biopsychosocial conceptual model of PPD for Latinas in the United States. We make arguments for an integrated model designed to assess psychosocial and physiological risk factors and PPD in a high-risk population. Our framework describes the hypothesized associations between culturally and contextually relevant psychosocial stressors, neurobiological factors (e.g., hypothalamic-pituitary-adrenal [HPA] axis response system and oxytocin signaling), and PPD in Latinas in the United States. Future studies should evaluate prospectively the impact psychosocial stressors identified here have on the development of PPD in both immigrant and U.S-born Latinas while examining neuroendocrine function, such as the HPA axis and oxytocin signaling. Our conceptual framework will allow for the reporting of main and indirect effects of psychosocial risk factors and biomarkers (e.g., HPA axis and oxytocin function) on PPD in foreign- and U.S.-born postpartum Latinas. Copyright © 2016 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

Associations between waist circumference, metabolic risk and executive function in adolescents: A cross-sectional mediation analysis.

PubMed

Bugge, Anna; Möller, Sören; Westfall, Daniel R; Tarp, Jakob; Gejl, Anne K; Wedderkopp, Niels; Hillman, Charles H

2018-01-01

The main objective of this study was to investigate the associations between waist circumference, metabolic risk factors, and executive function in adolescents. The study was cross-sectional and included 558 adolescents (mean age 14.2 years). Anthropometrics and systolic blood pressure (sysBP) were measured and fasting blood samples were analyzed for metabolic risk factors. A metabolic risk factor cluster score (MetS-cluster score) was computed from the sum of standardized sysBP, triglycerides (TG), inverse high-density lipid cholesterol (HDLc) and insulin resistance (homeostasis model assessment). Cognitive control was measured with a modified flanker task. Regression analyses indicated that after controlling for demographic variables, HDLc exhibited a negative and TG a positive association with flanker reaction time (RT). Waist circumference did not demonstrate a statistically significant total association with the cognitive outcomes. In structural equation modeling, waist circumference displayed an indirect positive association with incongruent RT through a higher MetS-cluster score and through lower HDLc. The only statistically significant direct association between waist circumference and the cognitive outcomes was for incongruent RT in the model including HDLc as mediator. These findings are consonant with the previous literature reporting an adverse association between certain metabolic risk factors and cognitive control. Accordingly, these results suggest specificity between metabolic risk factors and cognitive control outcomes. Further, results of the present study, although cross-sectional, provide new evidence that specific metabolic risk factors may mediate an indirect association between adiposity and cognitive control in adolescents, even though a direct association between these variables was not observed. However, taking the cross-sectional study design into consideration, these results should be interpreted with caution and future longitudinal or experimental studies should verify the findings of this study.

Language delay in severely neglected children: a cumulative or specific effect of risk factors?

PubMed

Sylvestre, Audette; Mérette, Chantal

2010-06-01

This research sought to determine if the language delay (LD) of severely neglected children under 3 years old was better explained by a cumulative risk model or by the specificity of risk factors. The objective was also to identify the risk factors with the strongest impact on LD among various biological, psychological, and environmental factors. Sixty-eight severely neglected children and their mothers participated in this cross-sectional study. Children were between 2 and 36 months of age. Data included information about the child's language development and biological, psychological, and environmental risk factors. Prevalence of LD is significantly higher in this subgroup of children than in the population as a whole. Although we observed that the risk of LD significantly increased with an increase in the cumulative count of the presence of the child's biological-psychological risk factors, the one-by-one analysis of the individual factors revealed that the cumulative effect mainly reflected the specific impact of the child's cognitive development. When we considered also the environmental risk factors, multivariate logistic regression established that cognitive development, the mother's own physical and emotional abuse experience as a child, and the mother's low acceptability level towards her child are linked to LD in severely neglected children. Language development is the result of a complex interaction between risk factors. LD in severely neglected children is better explained by the specificity of risk factors than by the cumulative risk model. Most prevention and early intervention programs promote and target an increase in the quantity and quality of language stimulation offered to the child. Our results suggest that particular attention should be given to other environmental factors, specifically the mother's psychological availability and her sensitivity towards the child. It is essential to suggest interventions targeting various ecological dimensions of neglectful mothers to help break the intergenerational neglect transmission cycle. It is also important to develop government policies and ensure that efforts among the various response networks are concerted since in-depth changes to neglect situations can only come about when all interested parties become involved. Copyright 2010 Elsevier Ltd. All rights reserved.

Development of an Algorithm for Stroke Prediction: A National Health Insurance Database Study in Korea.

PubMed

Min, Seung Nam; Park, Se Jin; Kim, Dong Joon; Subramaniyam, Murali; Lee, Kyung-Sun

2018-01-01

Stroke is the second leading cause of death worldwide and remains an important health burden both for the individuals and for the national healthcare systems. Potentially modifiable risk factors for stroke include hypertension, cardiac disease, diabetes, and dysregulation of glucose metabolism, atrial fibrillation, and lifestyle factors. We aimed to derive a model equation for developing a stroke pre-diagnosis algorithm with the potentially modifiable risk factors. We used logistic regression for model derivation, together with data from the database of the Korea National Health Insurance Service (NHIS). We reviewed the NHIS records of 500,000 enrollees. For the regression analysis, data regarding 367 stroke patients were selected. The control group consisted of 500 patients followed up for 2 consecutive years and with no history of stroke. We developed a logistic regression model based on information regarding several well-known modifiable risk factors. The developed model could correctly discriminate between normal subjects and stroke patients in 65% of cases. The model developed in the present study can be applied in the clinical setting to estimate the probability of stroke in a year and thus improve the stroke prevention strategies in high-risk patients. The approach used to develop the stroke prevention algorithm can be applied for developing similar models for the pre-diagnosis of other diseases. © 2018 S. Karger AG, Basel.

Predicting preterm birth among participants of North Carolina’s Pregnancy Medical Home Program

PubMed Central

Tucker, Christine M.; Berrien, Kate; Menard, M. Kathryn; Herring, Amy H.; Daniels, Julie; Rowley, Diane L.; Halpern, Carolyn Tucker

2016-01-01

Objective To determine which combination of risk factors from Community Care of North Carolina’s (CCNC) Pregnancy Medical Home (PMH) risk screening form was most predictive of preterm birth (PTB) by parity and race/ethnicity. Methods This retrospective cohort included pregnant Medicaid patients screened by the PMH program before 24 weeks gestation who delivered a live birth in North Carolina between September 2011-September 2012 (N=15,428). Data came from CCNC’s Case Management Information System, Medicaid claims, and birth certificates. Logistic regression with backward stepwise elimination was used to arrive at the final models. To internally validate the predictive model, we used bootstrapping techniques. Results The prevalence of PTB was 11%. Multifetal gestation, a previous PTB, cervical insufficiency, diabetes, renal disease, and hypertension were the strongest risk factors with odds ratios ranging from 2.34 to 10.78. Non-Hispanic black race, underweight, smoking during pregnancy, asthma, other chronic conditions, nulliparity, and a history of a low birth weight infant or fetal death/second trimester loss were additional predictors in the final predictive model. About half of the risk factors prioritized by the PMH program remained in our final model (ROC=0.66). The odds of PTB associated with food insecurity and obesity differed by parity. The influence of unsafe or unstable housing and short interpregnancy interval on PTB differed by race/ethnicity. Conclusions Evaluation of the PMH risk screen provides insight to ensure women at highest risk are prioritized for care management. Using multiple data sources, salient risk factors for PTB were identified, allowing for better-targeted approaches for PTB prevention. PMID:26112751

Mothers of children with externalizing behavior problems: cognitive risk factors for abuse potential and discipline style and practices.

PubMed

McElroy, Erika M; Rodriguez, Christina M

2008-08-01

Utilizing the conceptual framework of the Social Information Processing (SIP) model (Milner, 1993, 2000), associations between cognitive risk factors and child physical abuse risk and maladaptive discipline style and practices were examined in an at-risk population. Seventy-three mothers of 5-12-year-old children, who were identified by their therapist as having an externalizing behavior problem, responded to self-report measures pertaining to cognitive risk factors (empathic perspective taking, frustration tolerance, developmental expectations, parenting locus of control), abuse risk, and discipline style and practices. The Child Behavior Checklist (CBCL) provided a confirmation of the child's externalizing behaviors independent of the therapist's assessment. The results of this study suggest several cognitive risk factors significantly predict risk of parental aggression toward children. A parent's ability to empathize and take the perspective of their child, parental locus of control, and parental level of frustration tolerance were significant predictors of abuse potential (accounting for 63% of the variance) and inappropriate discipline practices (accounting for 55% of the variance). Findings of the present study provide support for processes theorized in the SIP model. Specifically, results underscore the potential role of parents' frustration tolerance, developmental expectations, locus of control, and empathy as predictive of abuse potential and disciplinary style in an at-risk sample.

Immunodeficiency, AIDS-related pneumonia, and risk of lung cancer among HIV-infected individuals.

PubMed

Marcus, Julia L; Leyden, Wendy A; Chao, Chun R; Horberg, Michael A; Klein, Daniel B; Quesenberry, Charles P; Towner, William J; Silverberg, Michael J

2017-04-24

The objective is to clarify the role of immunodeficiency and pneumonia in elevated lung cancer risk among HIV-infected individuals. Cohort study of HIV-infected and HIV-uninfected adults in a large integrated healthcare system in California during 1996-2011. We used Poisson models to obtain rate ratios for lung cancer associated with HIV infection, overall and stratified by recent CD4 cells/μl (HIV-uninfected as reference group), with χ tests for trends across CD4 strata. Fully adjusted models included demographics, cancer risk factors (smoking, drug/alcohol abuse, overweight/obesity), and prior pneumonia. Among 24 768 HIV-infected and 257 600 HIV-uninfected individuals, the lung cancer rate per 100 000 person-years was 66 (n = 80 events) for HIV-infected and 33 (n = 506 events) for HIV-uninfected individuals [rate ratio 2.0, 95% confidence interval (CI): 1.7-2.2]. Overall, HIV-infected individuals were at increased risk of lung cancer after adjustment for demographics and cancer risk factors (rate ratio 1.4, 95% CI: 1.1-1.7), but not after additional adjustment for pneumonia (rate ratio 1.2, 95% CI: 0.9-1.6). Lower CD4 cell counts were associated with higher risk of lung cancer in unadjusted and demographics-adjusted models (P < 0.001 for all), but this trend did not remain after adjustment for cancer risk factors and pneumonia. Compared with HIV-uninfected individuals, HIV-infected individuals with CD4 less than 200 cells/μl were not at increased risk of lung cancer in fully adjusted models. The increased lung cancer risk among HIV patients is attributable to differences in demographics, risk factors such as smoking, and history of pneumonia. Immunodeficiency does not appear to have an independent effect on lung cancer risk.

The relationship of family characteristics and bipolar disorder using causal-pie models.

PubMed

Chen, Y-C; Kao, C-F; Lu, M-K; Yang, Y-K; Liao, S-C; Jang, F-L; Chen, W J; Lu, R-B; Kuo, P-H

2014-01-01

Many family characteristics were reported to increase the risk of bipolar disorder (BPD). The development of BPD may be mediated through different pathways, involving diverse risk factor profiles. We evaluated the associations of family characteristics to build influential causal-pie models to estimate their contributions on the risk of developing BPD at the population level. We recruited 329 clinically diagnosed BPD patients and 202 healthy controls to collect information in parental psychopathology, parent-child relationship, and conflict within family. Other than logistic regression models, we applied causal-pie models to identify pathways involved with different family factors for BPD. The risk of BPD was significantly increased with parental depression, neurosis, anxiety, paternal substance use problems, and poor relationship with parents. Having a depressed mother further predicted early onset of BPD. Additionally, a greater risk for BPD was observed with higher numbers of paternal/maternal psychopathologies. Three significant risk profiles were identified for BPD, including paternal substance use problems (73.0%), maternal depression (17.6%), and through poor relationship with parents and conflict within the family (6.3%). Our findings demonstrate that different aspects of family characteristics elicit negative impacts on bipolar illness, which can be utilized to target specific factors to design and employ efficient intervention programs. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

An Ecological Risk Model for Early Childhood Anxiety: The Importance of Early Child Symptoms and Temperament

ERIC Educational Resources Information Center

Mian, Nicholas D.; Wainwright, Laurel; Briggs-Gowan, Margaret J.; Carter, Alice S.

2011-01-01

Childhood anxiety is impairing and associated with later emotional disorders. Studying risk factors for child anxiety may allow earlier identification of at-risk children for prevention efforts. This study applied an ecological risk model to address how early childhood anxiety symptoms, child temperament, maternal anxiety and depression symptoms,…

Exposure to Community Violence: Processes That Increase the Risk for Inner-City Middle School Children

ERIC Educational Resources Information Center

Salzinger, Suzanne; Ng-Mak, Daisy S.; Feldman, Richard S.; Kam, Chi-Ming; Rosario, Margaret

2006-01-01

An ecologically framed model is presented describing processes accounting for early adolescents' exposure to community violence in high-risk neighborhoods as a function of risk factors in four ecological domains assessed in the prior year. The model was tested for hypothesized pathways along which the combined domains of risk might operate. The…

Future cardiovascular disease in China: Markov model and risk factor scenario projections from the Coronary Heart Disease Policy Model-China

PubMed Central

Moran, Andrew; Gu, Dongfeng; Zhao, Dong; Coxson, Pamela; Wang, Y. Claire; Chen, Chung-Shiuan; Liu, Jing; Cheng, Jun; Bibbins-Domingo, Kirsten; Shen, Yu-Ming; He, Jiang; Goldman, Lee

2010-01-01

Background The relative effects of individual and combined risk factor trends on future cardiovascular disease in China have not been quantified in detail. Methods and Results Future risk factor trends in China were projected based on prior trends. Cardiovascular disease (coronary heart disease and stroke) in adults ages 35 to 84 years was projected from 2010 to 2030 using the Coronary Heart Disease Policy Model–China, a Markov computer simulation model. With risk factor levels held constant, projected annual cardiovascular events increased by >50% between 2010 and 2030 based on population aging and growth alone. Projected trends in blood pressure, total cholesterol, diabetes (increases), and active smoking (decline) would increase annual cardiovascular disease events by an additional 23%, an increase of approximately 21.3 million cardiovascular events and 7.7 million cardiovascular deaths over 2010 to 2030. Aggressively reducing active smoking in Chinese men to 20% prevalence in 2020 and 10% prevalence in 2030 or reducing mean systolic blood pressure by 3.8 mm Hg in men and women would counteract adverse trends in other risk factors by preventing cardiovascular events and 2.9 to 5.7 million total deaths over 2 decades. Conclusions Aging and population growth will increase cardiovascular disease by more than a half over the coming 20 years, and projected unfavorable trends in blood pressure, total cholesterol, diabetes, and body mass index may accelerate the epidemic. National policy aimed at controlling blood pressure, smoking, and other risk factors would counteract the expected future cardiovascular disease epidemic in China. PMID:20442213

Enhanced risk prediction model for emergency department use and hospitalizations in patients in a primary care medical home.

PubMed

Takahashi, Paul Y; Heien, Herbert C; Sangaralingham, Lindsey R; Shah, Nilay D; Naessens, James M

2016-07-01

With the advent of healthcare payment reform, identifying high-risk populations has become more important to providers. Existing risk-prediction models often focus on chronic conditions. This study sought to better understand other factors to improve identification of the highest risk population. A retrospective cohort study of a paneled primary care population utilizing 2010 data to calibrate a risk prediction model of hospital and emergency department (ED) use in 2011. Data were randomly split into development and validation data sets. We compared the enhanced model containing the additional risk predictors with the Minnesota medical tiering model. The study was conducted in the primary care practice of an integrated delivery system at an academic medical center in Rochester, Minnesota. The study focus was primary care medical home patients in 2010 and 2011 (n = 84,752), with the primary outcome of subsequent hospitalization or ED visit. A total of 42,384 individuals derived the enhanced risk-prediction model and 42,368 individuals validated the model. Predictors included Adjusted Clinical Groups-based Minnesota medical tiering, patient demographics, insurance status, and prior year healthcare utilization. Additional variables included specific mental and medical conditions, use of high-risk medications, and body mass index. The area under the curve in the enhanced model was 0.705 (95% CI, 0.698-0.712) compared with 0.662 (95% CI, 0.656-0.669) in the Minnesota medical tiering-only model. New high-risk patients in the enhanced model were more likely to have lack of health insurance, presence of Medicaid, diagnosed depression, and prior ED utilization. An enhanced model including additional healthcare-related factors improved the prediction of risk of hospitalization or ED visit.

Assessment of Yellow Fever Epidemic Risk: An Original Multi-criteria Modeling Approach

PubMed Central

Briand, Sylvie; Beresniak, Ariel; Nguyen, Tim; Yonli, Tajoua; Duru, Gerard; Kambire, Chantal; Perea, William

2009-01-01

Background Yellow fever (YF) virtually disappeared in francophone West African countries as a result of YF mass vaccination campaigns carried out between 1940 and 1953. However, because of the failure to continue mass vaccination campaigns, a resurgence of the deadly disease in many African countries began in the early 1980s. We developed an original modeling approach to assess YF epidemic risk (vulnerability) and to prioritize the populations to be vaccinated. Methods and Findings We chose a two-step assessment of vulnerability at district level consisting of a quantitative and qualitative assessment per country. Quantitative assessment starts with data collection on six risk factors: five risk factors associated with “exposure” to virus/vector and one with “susceptibility” of a district to YF epidemics. The multiple correspondence analysis (MCA) modeling method was specifically adapted to reduce the five exposure variables to one aggregated exposure indicator. Health districts were then projected onto a two-dimensional graph to define different levels of vulnerability. Districts are presented on risk maps for qualitative analysis in consensus groups, allowing the addition of factors, such as population migrations or vector density, that could not be included in MCA. The example of rural districts in Burkina Faso show five distinct clusters of risk profiles. Based on this assessment, 32 of 55 districts comprising over 7 million people were prioritized for preventive vaccination campaigns. Conclusion This assessment of yellow fever epidemic risk at the district level includes MCA modeling and consensus group modification. MCA provides a standardized way to reduce complexity. It supports an informed public health decision-making process that empowers local stakeholders through the consensus group. This original approach can be applied to any disease with documented risk factors. PMID:19597548

Assessment of yellow fever epidemic risk: an original multi-criteria modeling approach.

PubMed

Briand, Sylvie; Beresniak, Ariel; Nguyen, Tim; Yonli, Tajoua; Duru, Gerard; Kambire, Chantal; Perea, William

2009-07-14

Yellow fever (YF) virtually disappeared in francophone West African countries as a result of YF mass vaccination campaigns carried out between 1940 and 1953. However, because of the failure to continue mass vaccination campaigns, a resurgence of the deadly disease in many African countries began in the early 1980s. We developed an original modeling approach to assess YF epidemic risk (vulnerability) and to prioritize the populations to be vaccinated. We chose a two-step assessment of vulnerability at district level consisting of a quantitative and qualitative assessment per country. Quantitative assessment starts with data collection on six risk factors: five risk factors associated with "exposure" to virus/vector and one with "susceptibility" of a district to YF epidemics. The multiple correspondence analysis (MCA) modeling method was specifically adapted to reduce the five exposure variables to one aggregated exposure indicator. Health districts were then projected onto a two-dimensional graph to define different levels of vulnerability. Districts are presented on risk maps for qualitative analysis in consensus groups, allowing the addition of factors, such as population migrations or vector density, that could not be included in MCA. The example of rural districts in Burkina Faso show five distinct clusters of risk profiles. Based on this assessment, 32 of 55 districts comprising over 7 million people were prioritized for preventive vaccination campaigns. This assessment of yellow fever epidemic risk at the district level includes MCA modeling and consensus group modification. MCA provides a standardized way to reduce complexity. It supports an informed public health decision-making process that empowers local stakeholders through the consensus group. This original approach can be applied to any disease with documented risk factors.

An epidemiological survey on road traffic crashes in Iran: application of the two logistic regression models.

PubMed

Bakhtiyari, Mahmood; Mehmandar, Mohammad Reza; Mirbagheri, Babak; Hariri, Gholam Reza; Delpisheh, Ali; Soori, Hamid

2014-01-01

Risk factors of human-related traffic crashes are the most important and preventable challenges for community health due to their noteworthy burden in developing countries in particular. The present study aims to investigate the role of human risk factors of road traffic crashes in Iran. Through a cross-sectional study using the COM 114 data collection forms, the police records of almost 600,000 crashes occurred in 2010 are investigated. The binary logistic regression and proportional odds regression models are used. The odds ratio for each risk factor is calculated. These models are adjusted for known confounding factors including age, sex and driving time. The traffic crash reports of 537,688 men (90.8%) and 54,480 women (9.2%) are analysed. The mean age is 34.1 ± 14 years. Not maintaining eyes on the road (53.7%) and losing control of the vehicle (21.4%) are the main causes of drivers' deaths in traffic crashes within cities. Not maintaining eyes on the road is also the most frequent human risk factor for road traffic crashes out of cities. Sudden lane excursion (OR = 9.9, 95% CI: 8.2-11.9) and seat belt non-compliance (OR = 8.7, CI: 6.7-10.1), exceeding authorised speed (OR = 17.9, CI: 12.7-25.1) and exceeding safe speed (OR = 9.7, CI: 7.2-13.2) are the most significant human risk factors for traffic crashes in Iran. The high mortality rate of 39 people for every 100,000 population emphasises on the importance of traffic crashes in Iran. Considering the important role of human risk factors in traffic crashes, struggling efforts are required to control dangerous driving behaviours such as exceeding speed, illegal overtaking and not maintaining eyes on the road.

Initial Risk Analysis and Decision Making Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Engel, David W.

2012-02-01

Commercialization of new carbon capture simulation initiative (CCSI) technology will include two key elements of risk management, namely, technical risk (will process and plant performance be effective, safe, and reliable) and enterprise risk (can project losses and costs be controlled within the constraints of market demand to maintain profitability and investor confidence). Both of these elements of risk are incorporated into the risk analysis subtask of Task 7. Thus far, this subtask has developed a prototype demonstration tool that quantifies risk based on the expected profitability of expenditures when retrofitting carbon capture technology on a stylized 650 MW pulverized coalmore » electric power generator. The prototype is based on the selection of specific technical and financial factors believed to be important determinants of the expected profitability of carbon capture, subject to uncertainty. The uncertainty surrounding the technical performance and financial variables selected thus far is propagated in a model that calculates the expected profitability of investments in carbon capture and measures risk in terms of variability in expected net returns from these investments. Given the preliminary nature of the results of this prototype, additional work is required to expand the scope of the model to include additional risk factors, additional information on extant and proposed risk factors, the results of a qualitative risk factor elicitation process, and feedback from utilities and other interested parties involved in the carbon capture project. Additional information on proposed distributions of these risk factors will be integrated into a commercial implementation framework for the purpose of a comparative technology investment analysis.« less

Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic

PubMed Central

de Groot, Maartje H.; van Campen, Jos P.; Beijnen, Jos H.; Hortobágyi, Tibor; Vuillerme, Nicolas; Lamoth, Claudine C. J.

2017-01-01

Fall prediction in geriatric patients remains challenging because the increased fall risk involves multiple, interrelated factors caused by natural aging and/or pathology. Therefore, we used a multi-factorial statistical approach to model categories of modifiable fall risk factors among geriatric patients to identify fallers with highest sensitivity and specificity with a focus on gait performance. Patients (n = 61, age = 79; 41% fallers) underwent extensive screening in three categories: (1) patient characteristics (e.g., handgrip strength, medication use, osteoporosis-related factors) (2) cognitive function (global cognition, memory, executive function), and (3) gait performance (speed-related and dynamic outcomes assessed by tri-axial trunk accelerometry). Falls were registered prospectively (mean follow-up 8.6 months) and one year retrospectively. Principal Component Analysis (PCA) on 11 gait variables was performed to determine underlying gait properties. Three fall-classification models were then built using Partial Least Squares–Discriminant Analysis (PLS-DA), with separate and combined analyses of the fall risk factors. PCA identified ‘pace’, ‘variability’, and ‘coordination’ as key properties of gait. The best PLS-DA model produced a fall classification accuracy of AUC = 0.93. The specificity of the model using patient characteristics was 60% but reached 80% when cognitive and gait outcomes were added. The inclusion of cognition and gait dynamics in fall classification models reduced misclassification. We therefore recommend assessing geriatric patients’ fall risk using a multi-factorial approach that incorporates patient characteristics, cognition, and gait dynamics. PMID:28575126

Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic.

PubMed

Kikkert, Lisette H J; de Groot, Maartje H; van Campen, Jos P; Beijnen, Jos H; Hortobágyi, Tibor; Vuillerme, Nicolas; Lamoth, Claudine C J

2017-01-01

Fall prediction in geriatric patients remains challenging because the increased fall risk involves multiple, interrelated factors caused by natural aging and/or pathology. Therefore, we used a multi-factorial statistical approach to model categories of modifiable fall risk factors among geriatric patients to identify fallers with highest sensitivity and specificity with a focus on gait performance. Patients (n = 61, age = 79; 41% fallers) underwent extensive screening in three categories: (1) patient characteristics (e.g., handgrip strength, medication use, osteoporosis-related factors) (2) cognitive function (global cognition, memory, executive function), and (3) gait performance (speed-related and dynamic outcomes assessed by tri-axial trunk accelerometry). Falls were registered prospectively (mean follow-up 8.6 months) and one year retrospectively. Principal Component Analysis (PCA) on 11 gait variables was performed to determine underlying gait properties. Three fall-classification models were then built using Partial Least Squares-Discriminant Analysis (PLS-DA), with separate and combined analyses of the fall risk factors. PCA identified 'pace', 'variability', and 'coordination' as key properties of gait. The best PLS-DA model produced a fall classification accuracy of AUC = 0.93. The specificity of the model using patient characteristics was 60% but reached 80% when cognitive and gait outcomes were added. The inclusion of cognition and gait dynamics in fall classification models reduced misclassification. We therefore recommend assessing geriatric patients' fall risk using a multi-factorial approach that incorporates patient characteristics, cognition, and gait dynamics.

Development of innovative methods for risk assessment in high-rise construction based on clustering of risk factors

NASA Astrophysics Data System (ADS)

Okolelova, Ella; Shibaeva, Marina; Shalnev, Oleg

2018-03-01

The article analyses risks in high-rise construction in terms of investment value with account of the maximum probable loss in case of risk event. The authors scrutinized the risks of high-rise construction in regions with various geographic, climatic and socio-economic conditions that may influence the project environment. Risk classification is presented in general terms, that includes aggregated characteristics of risks being common for many regions. Cluster analysis tools, that allow considering generalized groups of risk depending on their qualitative and quantitative features, were used in order to model the influence of the risk factors on the implementation of investment project. For convenience of further calculations, each type of risk is assigned a separate code with the number of the cluster and the subtype of risk. This approach and the coding of risk factors makes it possible to build a risk matrix, which greatly facilitates the task of determining the degree of impact of risks. The authors clarified and expanded the concept of the price risk, which is defined as the expected value of the event, 105 which extends the capabilities of the model, allows estimating an interval of the probability of occurrence and also using other probabilistic methods of calculation.

Development of a Melanoma Risk Prediction Model Incorporating MC1R Genotype and Indoor Tanning Exposure: Impact of Mole Phenotype on Model Performance

PubMed Central

Penn, Lauren A.; Qian, Meng; Zhang, Enhan; Ng, Elise; Shao, Yongzhao; Berwick, Marianne; Lazovich, DeAnn; Polsky, David

2014-01-01

Background Identifying individuals at increased risk for melanoma could potentially improve public health through targeted surveillance and early detection. Studies have separately demonstrated significant associations between melanoma risk, melanocortin receptor (MC1R) polymorphisms, and indoor ultraviolet light (UV) exposure. Existing melanoma risk prediction models do not include these factors; therefore, we investigated their potential to improve the performance of a risk model. Methods Using 875 melanoma cases and 765 controls from the population-based Minnesota Skin Health Study we compared the predictive ability of a clinical melanoma risk model (Model A) to an enhanced model (Model F) using receiver operating characteristic (ROC) curves. Model A used self-reported conventional risk factors including mole phenotype categorized as “none”, “few”, “some” or “many” moles. Model F added MC1R genotype and measures of indoor and outdoor UV exposure to Model A. We also assessed the predictive ability of these models in subgroups stratified by mole phenotype (e.g. nevus-resistant (“none” and “few” moles) and nevus-prone (“some” and “many” moles)). Results Model A (the reference model) yielded an area under the ROC curve (AUC) of 0.72 (95% CI = 0.69, 0.74). Model F was improved with an AUC = 0.74 (95% CI = 0.71–0.76, p<0.01). We also observed substantial variations in the AUCs of Models A & F when examined in the nevus-prone and nevus-resistant subgroups. Conclusions These results demonstrate that adding genotypic information and environmental exposure data can increase the predictive ability of a clinical melanoma risk model, especially among nevus-prone individuals. PMID:25003831

Images of smokers and willingness to smoke among African American pre-adolescents: an application of the prototype/willingness model of adolescent health risk behavior to smoking initiation.

PubMed

Gerrard, Meg; Gibbons, Frederick X; Stock, Michelle L; Lune, Linda S Vande; Cleveland, Michael J

2005-06-01

This study used the prototype/willingness model of adolescent health risk behavior to examine factors related to onset of smoking. Two waves of data were collected from a panel of 742 African American children (mean age=10.5 at Wave 1) and their primary caregivers. Measures included cognitions outlined by the prototype model as well as self-reports of smoking by the parent and child. Structural equation modeling revealed a pattern consistent with expectations generated by the prototype model. The relation between contextual, familial, and dispositional factors-including neighborhood risk, parental smoking, and children's academic orientation-and the initiation of smoking at Wave 2, two years later, was mediated by the children's cognitions. Primary among these cognitions were the children's images of smokers and children's willingness to smoke. Smoking cognitions mediate the impact of important distal factors (such as context, family environment, and disposition) on the onset of smoking in children. Perhaps more important, it is possible to predict onset of smoking in African American children as young as age 10 by assessing the cognitive factors suggested by the prototype model.

Inferring the risk factors behind the geographical spread and transmission of Zika in the Americas

PubMed Central

Bóta, András; Gangavarapu, Karthik; Kraemer, Moritz U. G.; Grubaugh, Nathan D.

2018-01-01

Background An unprecedented Zika virus epidemic occurred in the Americas during 2015-2016. The size of the epidemic in conjunction with newly recognized health risks associated with the virus attracted significant attention across the research community. Our study complements several recent studies which have mapped epidemiological elements of Zika, by introducing a newly proposed methodology to simultaneously estimate the contribution of various risk factors for geographic spread resulting in local transmission and to compute the risk of spread (or re-introductions) between each pair of regions. The focus of our analysis is on the Americas, where the set of regions includes all countries, overseas territories, and the states of the US. Methodology/Principal findings We present a novel application of the Generalized Inverse Infection Model (GIIM). The GIIM model uses real observations from the outbreak and seeks to estimate the risk factors driving transmission. The observations are derived from the dates of reported local transmission of Zika virus in each region, the network structure is defined by the passenger air travel movements between all pairs of regions, and the risk factors considered include regional socioeconomic factors, vector habitat suitability, travel volumes, and epidemiological data. The GIIM relies on a multi-agent based optimization method to estimate the parameters, and utilizes a data driven stochastic-dynamic epidemic model for evaluation. As expected, we found that mosquito abundance, incidence rate at the origin region, and human population density are risk factors for Zika virus transmission and spread. Surprisingly, air passenger volume was less impactful, and the most significant factor was (a negative relationship with) the regional gross domestic product (GDP) per capita. Conclusions/Significance Our model generates country level exportation and importation risk profiles over the course of the epidemic and provides quantitative estimates for the likelihood of introduced Zika virus resulting in local transmission, between all origin-destination travel pairs in the Americas. Our findings indicate that local vector control, rather than travel restrictions, will be more effective at reducing the risks of Zika virus transmission and establishment. Moreover, the inverse relationship between Zika virus transmission and GDP suggests that Zika cases are more likely to occur in regions where people cannot afford to protect themselves from mosquitoes. The modeling framework is not specific for Zika virus, and could easily be employed for other vector-borne pathogens with sufficient epidemiological and entomological data. PMID:29346387

A multidomain approach to understanding risk for underage drinking: converging evidence from 5 data sets.

PubMed

Jones, Damon E; Feinberg, Mark E; Cleveland, Michael J; Cooper, Brittany Rhoades

2012-11-01

We examined the independent and combined influence of major risk and protective factors on youths' alcohol use. Five large data sets provided similar measures of alcohol use and risk or protective factors. We carried out analyses within each data set, separately for boys and girls in 8th and 10th grades. We included interaction and curvilinear predictive terms in final models if results were robust across data sets. We combined results using meta-analytic techniques. Individual, family, and peer risk factors and a community protective factor moderately predicted youths' alcohol use. Family and school protective factors did not predict alcohol use when combined with other factors. Youths' antisocial attitudes were more strongly associated with alcohol use for those also reporting higher levels of peer or community risk. For certain risk factors, the association with alcohol use varied across different risk levels. Efforts toward reducing youths' alcohol use should be based on robust estimates of the relative influence of risk and protective factors across adolescent environment domains. Public health advocates should focus on context (e.g., community factors) as a strategy for curbing underage alcohol use.

A systematic review of risk and protective factors associated with family related violence in refugee families.

PubMed

Timshel, Isabelle; Montgomery, Edith; Dalgaard, Nina Thorup

2017-08-01

The current systematic review summarizes the evidence from studies examining the risk and protective factors associated with family related violence in refugee families. Data included 15 peer-reviewed qualitative and quantitative studies. In order to gain an overview of the identified risk and protective factors an ecological model was used to structure the findings. At the individual level, parental trauma experiences/mental illness, substance abuse and history of child abuse were found to be risk factors. Family level risk factors included parent-child interaction, family structure and family acculturation stress. At the societal level low socioeconomic status was identified as a risk factor. Cultural level risk factors included patriarchal beliefs. Positive parental coping strategies were a protective factor. An ecological analysis of the results suggests that family related violence in refugee families is a result of accumulating, multiple risk factors on the individual, familial, societal and cultural level. The findings suggest that individual trauma and exile related stress do not only affect the individual but have consequences at a family level. Thus, interventions targeting family related violence should not only include the individual, but the family. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative influence of risk factors on blood glucose level.

PubMed

Chen, Songjing; Luo, Senlin; Pan, Limin; Zhang, Tiemei; Han, Longfei; Zhao, Haixiu

2014-01-01

The aim of this study is to quantitatively analyze the influence of risk factors on the blood glucose level, and to provide theory basis for understanding the characteristics of blood glucose change and confirming the intervention index for type 2 diabetes. The quantitative method is proposed to analyze the influence of risk factors on blood glucose using back propagation (BP) neural network. Ten risk factors are screened first. Then the cohort is divided into nine groups by gender and age. According to the minimum error principle, nine BP models are trained respectively. The quantitative values of the influence of different risk factors on the blood glucose change can be obtained by sensitivity calculation. The experiment results indicate that weight is the leading cause of blood glucose change (0.2449). The second factors are cholesterol, age and triglyceride. The total ratio of these four factors reaches to 77% of the nine screened risk factors. And the sensitivity sequences can provide judgment method for individual intervention. This method can be applied to risk factors quantitative analysis of other diseases and potentially used for clinical practitioners to identify high risk populations for type 2 diabetes as well as other disease.

A cumulative risk factor model for early identification of academic difficulties in premature and low birth weight infants.

PubMed

Roberts, G; Bellinger, D; McCormick, M C

2007-03-01

Premature and low birth weight children have a high prevalence of academic difficulties. This study examines a model comprised of cumulative risk factors that allows early identification of these difficulties. This is a secondary analysis of data from a large cohort of premature (<37 weeks gestation) and LBW (<2500 g) children. The study subjects were 8 years of age and 494 had data available for reading achievement and 469 for mathematics. Potential predictor variables were categorized into 4 domains: sociodemographic, neonatal, maternal mental health and early childhood (ages 3 and 5). Regression analysis was used to create a model to predict reading and mathematics scores. Variables from all domains were significant in the model, predicting low achievement scores in reading (R (2) of 0.49, model p-value < .0001) and mathematics (R (2) of 0.44, model p-value < .0001). Significant risk factors for lower reading scores, were: lower maternal education and income, and Black or Hispanic race (sociodemographic); lower birth weight and male gender (neonatal); lower maternal responsivity (maternal mental health); lower intelligence, visual-motor skill and higher behavioral disturbance scores (early childhood). Lower mathematics scores were predicted by lower maternal education, income and age and Black or Hispanic race (sociodemographic); lower birth weight and higher head circumference (neonatal); lower maternal responsivity (maternal mental health); lower intelligence, visual-motor skill and higher behavioral disturbance scores (early childhood). Sequential early childhood risk factors in premature and LBW children lead to a cumulative risk for academic difficulties and can be used for early identification.

[Case finding in early prevention networks - a heuristic for ambulatory care settings].

PubMed

Barth, Michael; Belzer, Florian

2016-06-01

One goal of early prevention is the support of families with small children up to three years who are exposed to psychosocial risks. The identification of these cases is often complex and not well-directed, especially in the ambulatory care setting. Development of a model of a feasible and empirical based strategy for case finding in ambulatory care. Based on the risk factors of postpartal depression, lack of maternal responsiveness, parental stress with regulation disorders and poverty a lexicographic and non-compensatory heuristic model with simple decision rules, will be constructed and empirically tested. Therefore the original data set from an evaluation of the pediatric documentary form on psychosocial issues of families with small children in well-child visits will be used and reanalyzed. The first diagnostic step in the non-compensatory and hierarchical classification process is the assessment of postpartal depression followed by maternal responsiveness, parental stress and poverty. The classification model identifies 89.0 % cases from the original study. Compared to the original study the decision process becomes clearer and more concise. The evidence-based and data-driven model exemplifies a strategy for the assessment of psychosocial risk factors in ambulatory care settings. It is based on four evidence-based risk factors and offers a quick and reliable classification. A further advantage of this model is that after a risk factor is identified the diagnostic procedure will be stopped and the counselling process can commence. For further validation of the model studies, in well suited early prevention networks are needed.

Association between Suicide Ideation and Attempts and Being an Immigrant among Adolescents, and the Role of Socioeconomic Factors and School, Behavior, and Health-Related Difficulties

PubMed Central

Chau, Kénora; Kabuth, Bernard; Chau, Nearkasen

2016-01-01

The risk of suicide behaviors in immigrant adolescents varies across countries and remains partly understood. We conducted a study in France to examine immigrant adolescents’ likelihood of experiencing suicide ideation in the last 12 months (SI) and lifetime suicide attempts (SA) compared with their native counterparts, and the contribution of socioeconomic factors and school, behavior, and health-related difficulties. Questionnaires were completed by 1559 middle-school adolescents from north-eastern France including various risk factors, SI, SA, and their first occurrence over adolescent’s life course (except SI). Data were analyzed using logistic regression models for SI and Cox regression models for SA (retaining only school, behavior, and health-related difficulties that started before SA). Immigrant adolescents had a two-time higher risk of SI and SA than their native counterparts. Using nested models, the excess SI risk was highly explained by socioeconomic factors (27%) and additional school, behavior, and health-related difficulties (24%) but remained significant. The excess SA risk was more highly explained by these issues (40% and 85%, respectively) and became non-significant. These findings demonstrate the risk patterns of SI and SA and the prominent confounding roles of socioeconomic factors and school, behavior, and health-related difficulties. They may be provided to policy makers, schools, carers, and various organizations interested in immigrant, adolescent, and suicide-behavior problems. PMID:27809296

Risk Factors for Pressure Ulcers Including Suspected Deep Tissue Injury in Nursing Home Facility Residents: Analysis of National Minimum Data Set 3.0.

PubMed

Ahn, Hyochol; Cowan, Linda; Garvan, Cynthia; Lyon, Debra; Stechmiller, Joyce

2016-04-01

To provide information on risk factors associated with pressure ulcers (PrUs), including suspected deep tissue injury (sDTI), in nursing home residents in the United States. This continuing education activity is intended for physicians and nurses with an interest in skin and wound care. After participating in this educational activity, the participant should be better able to:1. Examine the literature related to risk factors for the development of PrUs.2. Compare risk factors associated with the prevalence of PrUs and sDTI from the revised Minimum Data Set 3.0 2012 using a modified Defloor's conceptual model of PrUs as a theoretical framework. This study aims to characterize and compare risk factors associated with pressure ulcers (PrUs), including suspected deep tissue injury (sDTI), in nursing home (NH) residents in the United States. Secondary analysis of the 2012 Minimum Data Set (MDS 3.0). Medicare- or Medicaid-certified NHs in the United States. Nursing home residents (n = 2,936,146) 18 years or older with complete PrU data, who received comprehensive assessments from January to December 2012. Pressure ulcer by stage was the outcome variable. Explanatory variables (age, gender, race and ethnicity, body mass index, skin integrity, system failure, disease, infection, mobility, and cognition) from the MDS 3.0 were aligned with the 4 elements of Defloor's conceptual model: compressive forces, shearing forces, tissue tolerance for pressure, and tissue tolerance for oxygen. Of 2,936,146 NH residents who had complete data for PrU, 89.9% had no PrU; 8.4% had a Stage 2, 3, or 4 or unstagable PrU; and 1.7% had an sDTI. The MDS variables corresponding to the 4 elements of Defloor's model were significantly predictive of both PrU and sDTI. Black residents had the highest risk of any-stage PrU, and Hispanic residents had the highest risk of sDTI. Skin integrity, system failure, infection, and disease risk factors had larger effect sizes for sDTI than for other PrU stages. The MDS data support Defloor's model and inform clinicians, educators, researchers, and policymakers on risk factors associated with PrUs and sDTI in NH residents in the United States participating in Medicare and Medicaid.

Estrogen in cardiovascular disease during systemic lupus erythematosus.

PubMed

Gilbert, Emily L; Ryan, Michael J

2014-12-01

Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease that disproportionately affects women during their childbearing years. Cardiovascular disease is the leading cause of mortality in this patient population at an age when women often have low cardiovascular risk. Hypertension is a major cardiovascular disease risk factor, and its prevalence is markedly increased in women with SLE. Estrogen has traditionally been implicated in SLE disease progression because of the prevalence of the disease in women; however, its role in cardiovascular risk factors such as hypertension is unclear. The objective of this review is to discuss evidence for the role of estrogen in both human and murine SLE with emphasis on the effect of estrogen on cardiovascular risk factors, including hypertension. PubMed was used to search for articles with terms related to estradiol and SLE. The references of retrieved publications were also reviewed. The potential permissive role of estrogen in SLE development is supported by studies from experimental animal models of lupus in which early removal of estrogen or its effects leads to attenuation of SLE disease parameters, including autoantibody production and renal injury. However, data about the role of estrogens in human SLE are much less clear, with most studies not reaching firm conclusions about positive or negative outcomes after hormonal manipulations involving estrogen during SLE (ie, oral contraceptives, hormone therapy). Significant gaps in knowledge remain about the effect of estrogen on cardiovascular risk factors during SLE. Studies in women with SLE were not designed to determine the effect of estrogen or hormone therapy on blood pressure even though hypertension is highly prevalent, and risk of premature ovarian failure could necessitate use of hormone therapy in women with SLE. Recent evidence from an experimental animal model of lupus found that estrogen may protect against cardiovascular risk factors in adulthood. In addition, increasing evidence suggests that estrogen may have distinct temporal effects on cardiovascular risk factors during SLE. Data from experimental models of lupus suggest that estrogens may have an important permissive role for developing SLE early in life. However, their role in adulthood remains unclear, particularly for the effect on cardiovascular disease and its risk factors. Additional work is needed to understand the effect of estrogens in human SLE, and preclinical studies in experimental models of SLE may contribute important mechanistic insight to further advance the field. Copyright © 2014 Elsevier HS Journals, Inc. All rights reserved.

Estrogen in Cardiovascular Disease during Systemic Lupus Erythematosus

PubMed Central

Gilbert, Emily L.; Ryan, Michael J.

2015-01-01

Purpose Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease that disproportionately affects women during their childbearing years. Cardiovascular disease is the leading cause of mortality in this patient population at an age when women often have low cardiovascular risk. Hypertension is a major cardiovascular disease risk factor, and its prevalence is markedly increased in women with SLE. Estrogen has traditionally been implicated in SLE disease progression because of the prevalence of the disease in women; however, its role in cardiovascular risk factors such as hypertension is unclear. The objective of this review is to discuss evidence for the role of estrogen in both human and murine SLE with emphasis on the effect of estrogen on cardiovascular risk factors, including hypertension. Methods PubMed was used to search for articles with terms related to estradiol and SLE. The references of retrieved publications were also reviewed. Findings The potential permissive role of estrogen in SLE development is supported by studies from experimental animal models of lupus in which early removal of estrogen or its effects leads to attenuation of SLE disease parameters, including autoantibody production and renal injury. However, data about the role of estrogens in human SLE are much less clear, with most studies not reaching firm conclusions about positive or negative outcomes after hormonal manipulations involving estrogen during SLE (ie, oral contraceptives, hormone therapy). Significant gaps in knowledge remain about the effect of estrogen on cardiovascular risk factors during SLE. Studies in women with SLE were not designed to determine the effect of estrogen or hormone therapy on blood pressure even though hypertension is highly prevalent, and risk of premature ovarian failure could necessitate use of hormone therapy in women with SLE. Recent evidence from an experimental animal model of lupus found that estrogen may protect against cardiovascular risk factors in adulthood. In addition, increasing evidence suggests that estrogen may have distinct temporal effects on cardiovascular risk factors during SLE. Implications Data from experimental models of lupus suggest that estrogens may have an important permissive role for developing SLE early in life. However, their role in adulthood remains unclear, particularly for the effect on cardiovascular disease and its risk factors. Additional work is needed to understand the effect of estrogens in human SLE, and preclinical studies in experimental models of SLE may contribute important mechanistic insight to further advance the field. PMID:25194860

Simple new risk score model for adult cardiac extracorporeal membrane oxygenation: simple cardiac ECMO score.

PubMed

Peigh, Graham; Cavarocchi, Nicholas; Keith, Scott W; Hirose, Hitoshi

2015-10-01

Although the use of cardiac extracorporeal membrane oxygenation (ECMO) is increasing in adult patients, the field lacks understanding of associated risk factors. While standard intensive care unit risk scores such as SAPS II (simplified acute physiology score II), SOFA (sequential organ failure assessment), and APACHE II (acute physiology and chronic health evaluation II), or disease-specific scores such as MELD (model for end-stage liver disease) and RIFLE (kidney risk, injury, failure, loss of function, ESRD) exist, they may not apply to adult cardiac ECMO patients as their risk factors differ from variables used in these scores. Between 2010 and 2014, 73 ECMOs were performed for cardiac support at our institution. Patient demographics and survival were retrospectively analyzed. A new easily calculated score for predicting ECMO mortality was created using identified risk factors from univariate and multivariate analyses, and model discrimination was compared with other scoring systems. Cardiac ECMO was performed on 73 patients (47 males and 26 females) with a mean age of 48 ± 14 y. Sixty-four percent of patients (47/73) survived ECMO support. Pre-ECMO SAPS II, SOFA, APACHE II, MELD, RIFLE, PRESERVE, and ECMOnet scores, were not correlated with survival. Univariate analysis of pre-ECMO risk factors demonstrated that increased lactate, renal dysfunction, and postcardiotomy cardiogenic shock were risk factors for death. Applying these data into a new simplified cardiac ECMO score (minimal risk = 0, maximal = 5) predicted patient survival. Survivors had a lower risk score (1.8 ± 1.2) versus the nonsurvivors (3.0 ± 0.99), P < 0.0001. Common intensive care unit or disease-specific risk scores calculated for cardiac ECMO patients did not correlate with ECMO survival, whereas a new simplified cardiac ECMO score provides survival predictability. Copyright © 2015 Elsevier Inc. All rights reserved.

Contributions of Genes and Environment to Developmental Change in Alcohol Use.

PubMed

Long, E C; Verhulst, B; Aggen, S H; Kendler, K S; Gillespie, N A

2017-09-01

The precise nature of how genetic and environmental risk factors influence changes in alcohol use (AU) over time has not yet been investigated. Therefore, the aim of the present study is to examine the nature of longitudinal changes in these risk factors to AU from mid-adolescence through young adulthood. Using a large sample of male twins, we compared five developmental models that each makes different predictions regarding the longitudinal changes in genetic and environmental risks for AU. The best-fitting model indicated that genetic influences were consistent with a gradual growth in the liability to AU, whereas unique environmental risk factors were consistent with an accumulation of risks across time. These results imply that two distinct processes influence adolescent AU between the ages of 15-25. Genetic effects influence baseline levels of AU and rates of change across time, while unique environmental effects are more cumulative.

A risk factor-based predictive model of outcomes in carotid endarterectomy: the National Surgical Quality Improvement Program 2005-2010.

PubMed

Bekelis, Kimon; Bakhoum, Samuel F; Desai, Atman; Mackenzie, Todd A; Goodney, Philip; Labropoulos, Nicos

2013-04-01

Accurate knowledge of individualized risks and benefits is crucial to the surgical management of patients undergoing carotid endarterectomy (CEA). Although large randomized trials have determined specific cutoffs for the degree of stenosis, precise delineation of patient-level risks remains a topic of debate, especially in real world practice. We attempted to create a risk factor-based predictive model of outcomes in CEA. We performed a retrospective cohort study involving patients who underwent CEAs from 2005 to 2010 and were registered in the American College of Surgeons National Quality Improvement Project database. Of the 35 698 patients, 20 015 were asymptomatic (56.1%) and 15 683 were symptomatic (43.9%). These patients demonstrated a 1.64% risk of stroke, 0.69% risk of myocardial infarction, and 0.75% risk of death within 30 days after CEA. Multivariate analysis demonstrated that increasing age, male sex, history of chronic obstructive pulmonary disease, myocardial infarction, angina, congestive heart failure, peripheral vascular disease, previous stroke or transient ischemic attack, and dialysis were independent risk factors associated with an increased risk of the combined outcome of postoperative stroke, myocardial infarction, or death. A validated model for outcome prediction based on individual patient characteristics was developed. There was a steep effect of age on the risk of myocardial infarction and death. This national study confirms that that risks of CEA vary dramatically based on patient-level characteristics. Because of limited discrimination, it cannot be used for individual patient risk assessment. However, it can be used as a baseline for improvement and development of more accurate predictive models based on other databases or prospective studies.

Towards a New Explicative Model of Antisocial Behaviour

ERIC Educational Resources Information Center

Justicia, Fernando; Benitez, Juan Luis; Pichardo, Maria Carmen; Fernandez, Eduardo; Fernandez, Trinidad Garcia y Maria

2006-01-01

Antisocial behavior has been the object of investigation in many studies seeking to establish its etiological factors as well as risk factors which help to perpetuate such behavior over the course of the individual's life. In this paper, we seek to classify and clarify risk factors underlying the origin and development of antisocial behaviors from…

Challenges of developing a cardiovascular risk calculator for patients with rheumatoid arthritis.

PubMed

Crowson, Cynthia S; Rollefstad, Silvia; Kitas, George D; van Riel, Piet L C M; Gabriel, Sherine E; Semb, Anne Grete

2017-01-01

Cardiovascular disease (CVD) risk calculators designed for use in the general population do not accurately predict the risk of CVD among patients with rheumatoid arthritis (RA), who are at increased risk of CVD. The process of developing risk prediction models involves numerous issues. Our goal was to develop a CVD risk calculator for patients with RA. Thirteen cohorts of patients with RA originating from 10 different countries (UK, Norway, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico) were combined. CVD risk factors and RA characteristics at baseline, in addition to information on CVD outcomes were collected. Cox models were used to develop a CVD risk calculator, considering traditional CVD risk factors and RA characteristics. Model performance was assessed using measures of discrimination and calibration with 10-fold cross-validation. A total of 5638 RA patients without prior CVD were included (mean age: 55 [SD: 14] years, 76% female). During a mean follow-up of 5.8 years (30139 person years), 389 patients developed a CVD event. Event rates varied between cohorts, necessitating inclusion of high and low risk strata in the models. The multivariable analyses revealed 2 risk prediction models including either a disease activity score including a 28 joint count and erythrocyte sedimentation rate (DAS28ESR) or a health assessment questionnaire (HAQ) along with age, sex, presence of hypertension, current smoking and ratio of total cholesterol to high-density lipoprotein cholesterol. Unfortunately, performance of these models was similar to general population CVD risk calculators. Efforts to develop a specific CVD risk calculator for patients with RA yielded 2 potential models including RA disease characteristics, but neither demonstrated improved performance compared to risk calculators designed for use in the general population. Challenges encountered and lessons learned are discussed in detail.

Ranking malaria risk factors to guide malaria control efforts in African highlands.

PubMed

Protopopoff, Natacha; Van Bortel, Wim; Speybroeck, Niko; Van Geertruyden, Jean-Pierre; Baza, Dismas; D'Alessandro, Umberto; Coosemans, Marc

2009-11-25

Malaria is re-emerging in most of the African highlands exposing the non immune population to deadly epidemics. A better understanding of the factors impacting transmission in the highlands is crucial to improve well targeted malaria control strategies. A conceptual model of potential malaria risk factors in the highlands was built based on the available literature. Furthermore, the relative importance of these factors on malaria can be estimated through "classification and regression trees", an unexploited statistical method in the malaria field. This CART method was used to analyse the malaria risk factors in the Burundi highlands. The results showed that Anopheles density was the best predictor for high malaria prevalence. Then lower rainfall, no vector control, higher minimum temperature and houses near breeding sites were associated by order of importance to higher Anopheles density. In Burundi highlands monitoring Anopheles densities when rainfall is low may be able to predict epidemics. The conceptual model combined with the CART analysis is a decision support tool that could provide an important contribution toward the prevention and control of malaria by identifying major risk factors.

To what extent is the familial risk of rheumatoid arthritis explained by established rheumatoid arthritis risk factors?

PubMed

Jiang, Xia; Frisell, Thomas; Askling, Johan; Karlson, Elizabeth W; Klareskog, Lars; Alfredsson, Lars; Källberg, Henrik

2015-02-01

Family history of rheumatoid arthritis (RA) is one of the strongest risk factors for developing RA, and information on family history is, therefore, routinely collected in clinical practice. However, as more genetic and environmental risk factors shared by relatives are identified, the importance of family history may diminish. The aim of this study was to determine how much of the familial risk of RA can be explained by established genetic and nongenetic risk factors. History of RA among first-degree relatives of individuals in the Epidemiological Investigation of Rheumatoid Arthritis case-control study was assessed through linkage to the Swedish Multigeneration Register and the Swedish Patient Register. We used logistic regression models to investigate the decrease in familial risk after successive adjustment for combinations of nongenetic risk factors (smoking, alcohol intake, parity, silica exposure, body mass index, fatty fish consumption, and education), and genetic risk factors (shared epitope [SE] and 76 single-nucleotide polymorphisms [SNPs]). Established nongenetic risk factors did not explain familial risk of either seropositive or seronegative RA to any significant degree. Genetic risk factors accounted for a limited proportion of the familial risk of seropositive RA (unadjusted odds ratio [OR] 4.10, SE-adjusted OR 3.72, SNP-adjusted OR 3.46, and SE and SNP-adjusted OR 3.35). Established risk factors only provided an explanation for familial risk of RA in minor part, suggesting that many (familial) risk factors remain to be identified, in particular for seronegative RA. Family history of RA therefore remains an important clinical risk factor for RA, the value of which has not yet been superseded by other information. There is thus a need for further etiologic studies of both seropositive and seronegative RA. Copyright © 2015 by the American College of Rheumatology.

Stress increases the risk of type 2 diabetes onset in women: A 12-year longitudinal study using causal modelling

PubMed Central

Oldmeadow, Christopher; Hure, Alexis; Luu, Judy; Loxton, Deborah

2017-01-01

Background Type 2 diabetes is associated with significant morbidity and mortality. Modifiable risk factors have been found to contribute up to 60% of type 2 diabetes risk. However, type 2 diabetes continues to rise despite implementation of interventions based on traditional risk factors. There is a clear need to identify additional risk factors for chronic disease prevention. The aim of this study was to examine the relationship between perceived stress and type 2 diabetes onset, and partition the estimates into direct and indirect effects. Methods and findings Women born in 1946–1951 (n = 12,844) completed surveys for the Australian Longitudinal Study on Women’s Health in 1998, 2001, 2004, 2007 and 2010. The total causal effect was estimated using logistic regression and marginal structural modelling. Controlled direct effects were estimated through conditioning in the regression model. A graded association was found between perceived stress and all mediators in the multivariate time lag analyses. A significant association was found between hypertension, as well as physical activity and body mass index, and diabetes, but not smoking or diet quality. Moderate/high stress levels were associated with a 2.3-fold increase in the odds of diabetes three years later, for the total estimated effect. Results were only slightly attenuated when the direct and indirect effects of perceived stress on diabetes were partitioned, with the mediators only explaining 10–20% of the excess variation in diabetes. Conclusions Perceived stress is a strong risk factor for type 2 diabetes. The majority of the effect estimate of stress on diabetes risk is not mediated by the traditional risk factors of hypertension, physical activity, smoking, diet quality, and body mass index. This gives a new pathway for diabetes prevention trials and clinical practice. PMID:28222165

Obesity during childhood and adolescence increases susceptibility to multiple sclerosis after accounting for established genetic and environmental risk factors.

PubMed

Gianfrancesco, Milena A; Acuna, Brigid; Shen, Ling; Briggs, Farren B S; Quach, Hong; Bellesis, Kalliope H; Bernstein, Allan; Hedstrom, Anna K; Kockum, Ingrid; Alfredsson, Lars; Olsson, Tomas; Schaefer, Catherine; Barcellos, Lisa F

2014-01-01

To investigate the association between obesity and multiple sclerosis (MS) while accounting for established genetic and environmental risk factors. Participants included members of Kaiser Permanente Medical Care Plan, Northern California Region (KPNC) (1235 MS cases and 697 controls). Logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (95% CI). Body mass index (BMI) or body size was the primary predictor of each model. Both incident and prevalent MS cases were studied. In analyses stratified by gender, being overweight at ages 10 and 20 were associated with MS in females (p<0.01). Estimates trended in the same direction for males, but were not significant. BMI in 20s demonstrated a linear relationship with MS (p-trend=9.60×10(-4)), and a twofold risk of MS for females with a BMI≥30kg/m(2) was observed (OR=2.15, 95% CI 1.18, 3.92). Significant associations between BMI in 20s and MS in males were not observed. Multivariate modelling demonstrated that significant associations between BMI or body size with MS in females persisted after adjusting for history of infectious mononucleosis and genetic risk factors, including HLA-DRB1*15:01 and established non-HLA risk alleles. Results show that childhood and adolescence obesity confer increased risk of MS in females beyond established heritable and environmental risk factors. Strong evidence for a dose-effect of BMI in 20s and MS was observed. The magnitude of BMI association with MS is as large as other known MS risk factors. Copyright © 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Alcohol consumption and all-cause mortality.

PubMed

Duffy, J C

1995-02-01

Prospective studies of alcohol and mortality in middle-aged men almost universally find a U-shaped relationship between alcohol consumption and risk of mortality. This review demonstrates the extent to which different studies lead to different risk estimates, analyses the putative influence of abstention as a risk factor and uses available data to produce point and interval estimates of the consumption level apparently associated with minimum risk from two studies in the UK. Data from a number of studies are analysed by means of logistic-linear modelling, taking account of the possible influence of abstention as a special risk factor. Separate analysis of British data is performed. Logistic-linear modelling demonstrates large and highly significant differences between the studies considered in the relationship between alcohol consumption and all-cause mortality. The results support the identification of abstention as a special risk factor for mortality, but do not indicate that this alone explains the apparent U-shaped relationship. Separate analysis of two British studies indicates minimum risk of mortality in this population at a consumption level of about 26 (8.5 g) units of alcohol per week. The analysis supports the view that abstention may be a specific risk factor for all-cause mortality, but is not an adequate explanation of the apparent protective effect of alcohol consumption against all-cause mortality. Future analyses might better be performed on a case-by-case basis, using a change-point model to estimate the parameters of the relationship. The current misinterpretation of the sensible drinking level of 21 units per week for men in the UK as a limit is not justified, and the data suggest that alcohol consumption is a net preventive factor against premature death in this population.

Rates and risk factors of injury in CrossFitTM: a prospective cohort study.

PubMed

Moran, Sebastian; Booker, Harry; Staines, Jacob; Williams, Sean

2017-09-01

CrossFitTM is a strength and conditioning program that has gained widespread popularity since its inception approximately 15 years ago. However, at present little is known about the level of injury risk associated with this form of training. Movement competency, assessed using the Functional Movement ScreenTM (FMS), has been identified as a risk factor for injury in numerous athletic populations, but its role in CrossFit participants is currently unclear. The aim of this study was to evaluate the level of injury risk associated with CrossFit training, and examine the influence of a number of potential risk factors (including movement competency). A cohort of 117 CrossFit participants were followed prospectively for 12 weeks. Participants' characteristics, previous injury history and training experience were recorded at baseline, and an FMS assessment was conducted. The overall injury incidence rate was 2.10 per 1000 training hours (90% confidence limits: 1.32-3.33). A multivariate Poisson regression model identified males (rate ratio [RR]: 4.44 ×/÷ 3.30, very likely harmful) and those with previous injuries (RR: 2.35 ×/÷ 2.37, likely harmful) as having a higher injury risk. Inferences relating to FMS variables were unclear in the multivariate model, although number of asymmetries was a clear risk factor in a univariate model (RR per two additional asymmetries: 2.62 ×/÷ 1.53, likely harmful). The injury incidence rate associated with CrossFit training was low, and comparable to other forms of recreational fitness activities. Previous injury and gender were identified as risk factors for injury, whilst the role of movement competency in this setting warrants further investigation.

Obesity during childhood and adolescence increases susceptibility to multiple sclerosis after accounting for established genetic and environmental risk factors

PubMed Central

Gianfrancesco, Milena A.; Acuna, Brigid; Shen, Ling; Briggs, Farren B.S.; Quach, Hong; Bellesis, Kalliope H.; Bernstein, Allan; Hedstrom, Anna K.; Kockum, Ingrid; Alfredsson, Lars; Olsson, Tomas; Schaefer, Catherine; Barcellos, Lisa F.

2014-01-01

Objective To investigate the association between obesity and multiple sclerosis (MS) while accounting for established genetic and environmental risk factors. Methods Participants included members of Kaiser Permanente Medical Care Plan, Northern California Region (KPNC) (1,235 MS cases and 697 controls). Logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (95% CI). Body mass index (BMI) or body size was the primary predictor of each model. Both incident and prevalent MS cases were studied. Results In analyses stratified by gender, being overweight at age 10 and 20 were associated with MS in females (p<0.01). Estimates trended in the same direction for males, but were not significant. BMI in 20’s demonstrated a linear relationship with MS (p-trend=9.60 × 10−4), and a twofold risk of MS for females with a BMI ≥ 30 kg/m2 was observed (OR = 2.15, 95% CI 1.18, 3.92). Significant associations between BMI in 20’s and MS in males were not observed. Multivariate modeling demonstrated that significant associations between BMI or body size with MS in females persisted after adjusting for history of infectious mononucleosis and genetic risk factors, including HLA-DRB1*15:01 and established non-HLA risk alleles. Interpretation Results show that childhood and adolescence obesity confer increased risk of MS in females beyond established heritable and environmental risk factors. Strong evidence for a dose-effect of BMI in 20’s and MS was observed. The magnitude of BMI association with MS is as large as other known MS risk factors. PMID:25263833

One vs. Two Breast Density Measures to Predict 5- and 10- Year Breast Cancer Risk

PubMed Central

Kerlikowske, Karla; Gard, Charlotte C.; Sprague, Brian L.; Tice, Jeffrey A.; Miglioretti, Diana L.

2015-01-01

Background One measure of Breast Imaging Reporting and Data System (BI-RADS) breast density improves 5-year breast cancer risk prediction, but the value of sequential measures is unknown. We determined if two BI-RADS density measures improves the predictive accuracy of the Breast Cancer Surveillance Consortium 5-year risk model compared to one measure. Methods We included 722,654 women aged 35–74 years with two mammograms with BI-RADS density measures on average 1.8 years apart; 13,715 developed invasive breast cancer. We used Cox regression to estimate the relative hazards of breast cancer for age, race/ethnicity, family history of breast cancer, history of breast biopsy, and one or two density measures. We developed a risk prediction model by combining these estimates with 2000–2010 Surveillance, Epidemiology, and End Results incidence and 2010 vital statistics for competing risk of death. Results The two-measure density model had marginally greater discriminatory accuracy than the one-measure model (AUC=0.640 vs. 0.635). Of 18.6% of women (134,404/722,654) who decreased density categories, 15.4% (20,741/134,404) of women whose density decreased from heterogeneously or extremely dense to a lower density category with one other risk factor had a clinically meaningful increase in 5-year risk from <1.67% with the one-density model to ≥1.67% with the two-density model. Conclusion The two-density model has similar overall discrimination to the one-density model for predicting 5-year breast cancer risk and improves risk classification for women with risk factors and a decrease in density. Impact A two-density model should be considered for women whose density decreases when calculating breast cancer risk. PMID:25824444

One versus Two Breast Density Measures to Predict 5- and 10-Year Breast Cancer Risk.

PubMed

Kerlikowske, Karla; Gard, Charlotte C; Sprague, Brian L; Tice, Jeffrey A; Miglioretti, Diana L

2015-06-01

One measure of Breast Imaging Reporting and Data System (BI-RADS) breast density improves 5-year breast cancer risk prediction, but the value of sequential measures is unknown. We determined whether two BI-RADS density measures improve the predictive accuracy of the Breast Cancer Surveillance Consortium 5-year risk model compared with one measure. We included 722,654 women of ages 35 to 74 years with two mammograms with BI-RADS density measures on average 1.8 years apart; 13,715 developed invasive breast cancer. We used Cox regression to estimate the relative hazards of breast cancer for age, race/ethnicity, family history of breast cancer, history of breast biopsy, and one or two density measures. We developed a risk prediction model by combining these estimates with 2000-2010 Surveillance, Epidemiology, and End Results incidence and 2010 vital statistics for competing risk of death. The two-measure density model had marginally greater discriminatory accuracy than the one-measure model (AUC, 0.640 vs. 0.635). Of 18.6% of women (134,404 of 722,654) who decreased density categories, 15.4% (20,741 of 134,404) of women whose density decreased from heterogeneously or extremely dense to a lower density category with one other risk factor had a clinically meaningful increase in 5-year risk from <1.67% with the one-density model to ≥1.67% with the two-density model. The two-density model has similar overall discrimination to the one-density model for predicting 5-year breast cancer risk and improves risk classification for women with risk factors and a decrease in density. A two-density model should be considered for women whose density decreases when calculating breast cancer risk. ©2015 American Association for Cancer Research.

The Prime Diabetes Model: Novel Methods for Estimating Long-Term Clinical and Cost Outcomes in Type 1 Diabetes Mellitus.

PubMed

Valentine, William J; Pollock, Richard F; Saunders, Rhodri; Bae, Jay; Norrbacka, Kirsi; Boye, Kristina

Recent publications describing long-term follow-up from landmark trials and diabetes registries represent an opportunity to revisit modeling options in type 1 diabetes mellitus (T1DM). To develop a new product-independent model capable of predicting long-term clinical and cost outcomes. After a systematic literature review to identify clinical trial and registry data, a model was developed (the PRIME Diabetes Model) to simulate T1DM progression and complication onset. The model runs as a patient-level simulation, making use of covariance matrices for cohort generation and risk factor progression, and simulating myocardial infarction, stroke, angina, heart failure, nephropathy, retinopathy, macular edema, neuropathy, amputation, hypoglycemia, ketoacidosis, mortality, and risk factor evolution. Several approaches novel to T1DM modeling were used, including patient characteristics and risk factor covariance, a glycated hemoglobin progression model derived from patient-level data, and model averaging approaches to evaluate complication risk. Validation analyses comparing modeled outcomes with published studies demonstrated that the PRIME Diabetes Model projects long-term patient outcomes consistent with those reported for a number of long-term studies. Macrovascular end points were reliably reproduced across five different populations and microvascular complication risk was accurately predicted on the basis of comparisons with landmark studies and published registry data. The PRIME Diabetes Model is product-independent, available online, and has been developed in line with good practice guidelines. Validation has indicated that outcomes from long-term studies can be reliably reproduced. The model offers new approaches to long-standing challenges in diabetes modeling and may become a valuable tool for informing health care policy. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Predictors of formal home health care use in elderly patients after hospitalization.

PubMed

Solomon, D H; Wagner, D R; Marenberg, M E; Acampora, D; Cooney, L M; Inouye, S K

1993-09-01

To prospectively study the incidence of and risk factors for home health care (HHC) use in a cohort of elderly medical and surgical patients discharged from acute care. Although HHC is commonly received by patients in this group, its predictors have not been well studied. Prospective cohort study. Medical and surgical wards at a university teaching hospital, followed by 23 Medicare-certified HHC agencies in the study catchment area. 226 medical and surgical patients aged 70 years and older immediately after discharge from acute care. HHC initiated within 14 days after hospital discharge, measured by direct review of HHC agency records. The incidence of HHC initiated within 2 weeks post-discharge was 75/226 (34%). The median duration of service was 30 days (range 3-483) with a median of 3 visits per week. Four independent predictors of HHC were identified through multivariate analysis: educational level < or = 12 years (relative risk (RR) 3.3; 95% confidence interval (CI) 1.6 to 6.6); less accessible social support (RR, 1.7; CI 0.9 to 3.1); impairment in at least one instrumental activity of daily living (RR, 1.9; CI, 1.0, 3.4); and prior HHC use (RR, 2.1; CI, 1.2 to 3.6). Risk strata were created by adding one point for each risk factor present: with 0-1 risk factors, 8% used HHC; with two risk factors, 28%; with three risk factors, 45%, with four risk factors, 76%. This trend was statistically significant (P < 0.001). HHC use is common among elderly patients after discharge from acute care. A simple predictive model based on four risk factors can be used on admission to predict HHC use. This model may be useful for discharge planning and health care utilization planning for the elderly population.

Cardio-respiratory outcomes associated with exposure to wildfire smoke are modified by measures of community health

PubMed Central

2012-01-01

Background Characterizing factors which determine susceptibility to air pollution is an important step in understanding the distribution of risk in a population and is critical for setting appropriate policies. We evaluate general and specific measures of community health as modifiers of risk for asthma and congestive heart failure following an episode of acute exposure to wildfire smoke. Methods A population-based study of emergency department visits and daily concentrations of fine particulate matter during a wildfire in North Carolina was performed. Determinants of community health defined by County Health Rankings were evaluated as modifiers of the relative risk. A total of 40 mostly rural counties were included in the study. These rankings measure factors influencing health: health behaviors, access and quality of clinical care, social and economic factors, and physical environment, as well as, the outcomes of health: premature mortality and morbidity. Pollutant concentrations were obtained from a mathematically modeled smoke forecasting system. Estimates of relative risk for emergency department visits were based on Poisson mixed effects regression models applied to daily visit counts. Results For asthma, the strongest association was observed at lag day 0 with excess relative risk of 66%(28,117). For congestive heart failure the excess relative risk was 42%(5,93). The largest difference in risk was observed after stratifying on the basis of Socio-Economic Factors. Difference in risk between bottom and top ranked counties by Socio-Economic Factors was 85% and 124% for asthma and congestive heart failure respectively. Conclusions The results indicate that Socio-Economic Factors should be considered as modifying risk factors in air pollution studies and be evaluated in the assessment of air pollution impacts. PMID:23006928

Risk factors for epistaxis in jump racing in Great Britain (2001-2009).

PubMed

Reardon, Richard J M; Boden, Lisa A; Mellor, Dominic J; Love, Sandy; Newton, Richard J; Stirk, Anthony J; Parkin, Timothy D

2015-07-01

The aim of this study was to evaluate risk factors associated with developing epistaxis in jump racing in Great Britain (GB). A retrospective analysis of records from horses running in all hurdle and steeplechase races in GB between 2001 and 2009 identified diagnoses of epistaxis whilst still at the racecourse. Data were used from 603 starts resulting in epistaxis (event) and 169,065 starts resulting in no epistaxis (non-event) in hurdle racing, and from 550 event starts and 102,344 non-event starts in steeplechase racing. Two multivariable logistic regression models to evaluate risk factors associated with epistaxis were produced. The potential effect of clustering of data (within horse, horse dam, horse sire, trainer, jockey, course, race and race meet) on the associations between risk factors and epistaxis was examined using mixed-effects models. Multiple factors associated with increased risk of epistaxis were identified. Those identified in both types of jump racing included running on firmer ground; horses with >75% of career starts in flat racing and a previous episode of epistaxis recorded during racing. Risk factors identified only in hurdle racing included racing in the spring and increased age at first race; and those identified only in steeplechase racing included running in a claiming race and more starts in the previous 3-6 months. The risk factors identified provide important information about the risk of developing epistaxis. Multiple avenues for further investigation are highlighted, including unmeasured variables at the level of the racecourse. The results of this study can be used to guide the development of interventions to minimise the risk of epistaxis in jump racing. Copyright © 2015. Published by Elsevier Ltd.

Cardio-respiratory outcomes associated with exposure to wildfire smoke are modified by measures of community health.

PubMed

Rappold, Ana G; Cascio, Wayne E; Kilaru, Vasu J; Stone, Susan L; Neas, Lucas M; Devlin, Robert B; Diaz-Sanchez, David

2012-09-24

Characterizing factors which determine susceptibility to air pollution is an important step in understanding the distribution of risk in a population and is critical for setting appropriate policies. We evaluate general and specific measures of community health as modifiers of risk for asthma and congestive heart failure following an episode of acute exposure to wildfire smoke. A population-based study of emergency department visits and daily concentrations of fine particulate matter during a wildfire in North Carolina was performed. Determinants of community health defined by County Health Rankings were evaluated as modifiers of the relative risk. A total of 40 mostly rural counties were included in the study. These rankings measure factors influencing health: health behaviors, access and quality of clinical care, social and economic factors, and physical environment, as well as, the outcomes of health: premature mortality and morbidity. Pollutant concentrations were obtained from a mathematically modeled smoke forecasting system. Estimates of relative risk for emergency department visits were based on Poisson mixed effects regression models applied to daily visit counts. For asthma, the strongest association was observed at lag day 0 with excess relative risk of 66% (28,117). For congestive heart failure the excess relative risk was 42% (5,93). The largest difference in risk was observed after stratifying on the basis of Socio-Economic Factors. Difference in risk between bottom and top ranked counties by Socio-Economic Factors was 85% and 124% for asthma and congestive heart failure respectively. The results indicate that Socio-Economic Factors should be considered as modifying risk factors in air pollution studies and be evaluated in the assessment of air pollution impacts.

Novel coronary heart disease risk factors at 60–64 years and life course socioeconomic position: The 1946 British birth cohort

PubMed Central

Jones, Rebecca; Hardy, Rebecca; Sattar, Naveed; Deanfield, John E.; Hughes, Alun; Kuh, Diana; Murray, Emily T.; Whincup, Peter H.; Thomas, Claudia

2015-01-01

Social disadvantage across the life course is associated with a greater risk of coronary heart disease (CHD) and with established CHD risk factors, but less is known about whether novel CHD risk factors show the same patterns. The Medical Research Council National Survey of Health and Development was used to investigate associations between occupational socioeconomic position during childhood, early adulthood and middle age and markers of inflammation (C-reactive protein, interleukin-6), endothelial function (E-selectin, tissue-plasminogen activator), adipocyte function (leptin, adiponectin) and pancreatic beta cell function (proinsulin) measured at 60–64 years. Life course models representing sensitive periods, accumulation of risk and social mobility were compared with a saturated model to ascertain the nature of the relationship between social class across the life course and each of these novel CHD risk factors. For interleukin-6 and leptin, low childhood socioeconomic position alone was associated with high risk factor levels at 60–64 years, while for C-reactive protein and proinsulin, cumulative effects of low socioeconomic position in both childhood and early adulthood were associated with higher (adverse) risk factor levels at 60–64 years. No associations were observed between socioeconomic position at any life period with either endothelial marker or adiponectin. Associations for C-reactive protein, interleukin-6, leptin and proinsulin were reduced considerably by adjustment for body mass index and, to a lesser extent, cigarette smoking. In conclusion, socioeconomic position in early life is an important determinant of several novel CHD risk factors. Body mass index may be an important mediator of these relationships. PMID:25437893

Comparison of direct measures of adiposity with indirect measures for assessing cardiometabolic risk factors in preadolescent girls.

PubMed

Hetherington-Rauth, Megan; Bea, Jennifer W; Lee, Vinson R; Blew, Robert M; Funk, Janet; Lohman, Timothy G; Going, Scott B

2017-02-23

Childhood overweight and obesity remains high, contributing to cardiometabolic risk factors at younger ages. It is unclear which measures of adiposity serve as the best proxies for identifying children at metabolic risk. This study assessed whether DXA-derived direct measures of adiposity are more strongly related to cardiometabolic risk factors in children than indirect measures. Anthropometric and DXA measures of adiposity and a comprehensive assessment of cardiometabolic risk factors were obtained in 288, 9-12 year old girls, most being of Hispanic ethnicity. Multiple regression models for each metabolic parameter were run against each adiposity measure while controlling for maturation and ethnicity. In addition, regression models including both indirect and direct measures were developed to assess whether using direct measures of adiposity could provide a better prediction of the cardiometabolic risk factors beyond that of using indirect measures alone. Measures of adiposity were significantly correlated with cardiometabolic risk factors (p < 0.05) except fasting glucose. After adjusting for maturation and ethnicity, indirect measures of adiposity accounted for 29-34% in HOMA-IR, 10-13% in TG, 14-17% in HDL-C, and 5-8% in LDL-C while direct measures accounted for 29-34% in HOMA-IR, 10-12% in TG, 13-16% in HDL-C, and 5-6% in LDL-C. The addition of direct measures of adiposity to indirect measures added significantly to the variance explained for HOMA-IR (p = 0.04). Anthropometric measures may perform as well as the more precise direct DXA-derived measures of adiposity for assessing most CVD risk factors in preadolescent girls. The use of DXA-derived adiposity measures together with indirect measures may be advantageous for predicting insulin resistance risk. NCT02654262 . Retrospectively registered 11 January 2016.

Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

PubMed

Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

2018-05-12

Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

Novel risk score of contrast-induced nephropathy after percutaneous coronary intervention.

PubMed

Ji, Ling; Su, XiaoFeng; Qin, Wei; Mi, XuHua; Liu, Fei; Tang, XiaoHong; Li, Zi; Yang, LiChuan

2015-08-01

Contrast-induced nephropathy (CIN) post-percutaneous coronary intervention (PCI) is a major cause of acute kidney injury. In this study, we established a comprehensive risk score model to assess risk of CIN after PCI procedure, which could be easily used in a clinical environment. A total of 805 PCI patients, divided into analysis cohort (70%) and validation cohort (30%), were enrolled retrospectively in this study. Risk factors for CIN were identified using univariate analysis and multivariate logistic regression in the analysis cohort. Risk score model was developed based on multiple regression coefficients. Sensitivity and specificity of the new risk score system was validated in the validation cohort. Comparisons between the new risk score model and previous reported models were applied. The incidence of post-PCI CIN in the analysis cohort (n = 565) was 12%. Considerably high CIN incidence (50%) was observed in patients with chronic kidney disease (CKD). Age >75, body mass index (BMI) >25, myoglobin level, cardiac function level, hypoalbuminaemia, history of chronic kidney disease (CKD), Intra-aortic balloon pump (IABP) and peripheral vascular disease (PVD) were identified as independent risk factors of post-PCI CIN. A novel risk score model was established using multivariate regression coefficients, which showed highest sensitivity and specificity (0.917, 95%CI 0.877-0.957) compared with previous models. A new post-PCI CIN risk score model was developed based on a retrospective study of 805 patients. Application of this model might be helpful to predict CIN in patients undergoing PCI procedure. © 2015 Asian Pacific Society of Nephrology.

Stroke survivors' endorsement of a "stress belief model" of stroke prevention predicts control of risk factors for recurrent stroke.

PubMed

Phillips, L Alison; Tuhrim, Stanley; Kronish, Ian M; Horowitz, Carol R

2014-01-01

Perceptions that stress causes and stress-reduction controls hypertension have been associated with poorer blood pressure (BP) control in hypertension populations. The current study investigated these "stress-model perceptions" in stroke survivors regarding prevention of recurrent stroke and the influence of these perceptions on patients' stroke risk factor control. Stroke and transient ischemic attack survivors (N=600) participated in an in-person interview in which they were asked about their beliefs regarding control of future stroke; BP and cholesterol were measured directly after the interview. Counter to expectations, patients who endorsed a "stress-model" but not a "medication-model" of stroke prevention were in better control of their stroke risk factors (BP and cholesterol) than those who endorsed a medication-model but not a stress-model of stroke prevention (OR for poor control=.54, Wald statistic=6.07, p=.01). This result was not explained by between group differences in patients' reported medication adherence. The results have implications for theory and practice, regarding the role of stress belief models and acute cardiac events, compared to chronic hypertension.

The Association between Triglyceride/High-Density Lipoprotein Cholesterol Ratio and All-Cause Mortality in Acute Coronary Syndrome after Coronary Revascularization

PubMed Central

Wan, Ke; Zhao, Jianxun; Huang, Hao; Zhang, Qing; Chen, Xi; Zeng, Zhi; Zhang, Li; Chen, Yucheng

2015-01-01

Aims High triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C) are cardiovascular risk factors. A positive correlation between elevated TG/HDL-C ratio and all-cause mortality and cardiovascular events exists in women. However, utility of TG to HDL-C ratio for prediction is unknown among acute coronary syndrome (ACS). Methods Fasting lipid profiles, detailed demographic data, and clinical data were obtained at baseline from 416 patients with ACS after coronary revascularization. Subjects were stratified into three levels of TG/HDL-C. We constructed multivariate Cox-proportional hazard models for all-cause mortality over a median follow-up of 3 years using log TG to HDL-C ratio as a predictor variable and analyzing traditional cardiovascular risk factors. We constructed a logistic regression model for major adverse cardiovascular events (MACEs) to prove that the TG/HDL-C ratio is a risk factor. Results The subject’s mean age was 64 ± 11 years; 54.5% were hypertensive, 21.8% diabetic, and 61.0% current or prior smokers. TG/HDL-C ratio ranged from 0.27 to 14.33. During the follow-up period, there were 43 deaths. In multivariate Cox models after adjusting for age, smoking, hypertension, diabetes, and severity of angiographic coronary disease, patients in the highest tertile of ACS had a 5.32-fold increased risk of mortality compared with the lowest tertile. After adjusting for conventional coronary heart disease risk factors by the logistic regression model, the TG/HDL-C ratio was associated with MACEs. Conclusion The TG to HDL-C ratio is a powerful independent predictor of all-cause mortality and is a risk factor of cardiovascular events. PMID:25880982

Social and Behavioral Risk Marker Clustering Associated with Biological Risk Factors for Coronary Heart Disease: NHANES 2001–2004

PubMed Central

Everage, Nicholas J.; Linkletter, Crystal D.; Gjelsvik, Annie; McGarvey, Stephen T.; Loucks, Eric B.

2014-01-01

Background. Social and behavioral risk markers (e.g., physical activity, diet, smoking, and socioeconomic position) cluster; however, little is known whether clustering is associated with coronary heart disease (CHD) risk. Objectives were to determine if sociobehavioral clustering is associated with biological CHD risk factors (total cholesterol, HDL cholesterol, systolic blood pressure, body mass index, waist circumference, and diabetes) and whether associations are independent of individual clustering components. Methods. Participants included 4,305 males and 4,673 females aged ≥20 years from NHANES 2001–2004. Sociobehavioral Risk Marker Index (SRI) included a summary score of physical activity, fruit/vegetable consumption, smoking, and educational attainment. Regression analyses evaluated associations of SRI with aforementioned biological CHD risk factors. Receiver operator curve analyses assessed independent predictive ability of SRI. Results. Healthful clustering (SRI = 0) was associated with improved biological CHD risk factor levels in 5 of 6 risk factors in females and 2 of 6 risk factors in males. Adding SRI to models containing age, race, and individual SRI components did not improve C-statistics. Conclusions. Findings suggest that healthful sociobehavioral risk marker clustering is associated with favorable CHD risk factor levels, particularly in females. These findings should inform social ecological interventions that consider health impacts of addressing social and behavioral risk factors. PMID:24719858

Risk terrain modeling predicts child maltreatment.

PubMed

Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

2016-12-01

As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Risk factors for unintentional poisoning in children aged 1-3 years in NSW Australia: a case-control study.

PubMed

Schmertmann, Marcia; Williamson, Ann; Black, Deborah; Wilson, Leigh

2013-05-24

Unintentional poisoning in young children is an important public health issue. Age pattern studies have demonstrated that children aged 1-3 years have the highest levels of poisoning risk among children aged 0-4 years, yet little research has been conducted regarding risk factors specific to this three-year age group and the methodologies employed varied greatly. The purpose of the current study is to investigate a broad range of potential risk factors for unintentional poisoning in children aged 1-3 years using appropriate methodologies. Four groups of children, one case group (children who had experienced a poisoning event) and three control groups (children who had been 'injured', 'sick' or who were 'healthy'), and their mothers (mother-child dyads) were enrolled into a case-control study. All mother-child dyads participated in a 1.5-hour child developmental screening and observation, with mothers responding to a series of questionnaires at home. Data were analysed as three case-control pairs with multivariate analyses used to control for age and sex differences between child cases and controls. Five risk factors were included in the final multivariate models for one or more case-control pairs. All three models found that children whose mothers used more positive control in their interactions during a structured task had higher odds of poisoning. Two models showed that maternal psychiatric distress increased poisoning risk (poisoning-injury and poisoning-healthy). Individual models identified the following variables as risk factors: less proximal maternal supervision during risk taking activities (poisoning-injury), medicinal substances stored in more accessible locations in bathrooms (poisoning-sick) and lower total parenting stress (poisoning-healthy). The findings of this study indicate that the nature of the caregiver-child relationship and caregiver attributes play an important role in influencing poisoning risk. Further research is warranted to explore the link between caregiver-child relationships and unintentional poisoning risk. Caregiver education should focus on the benefits of close interaction with their child as a prevention measure.

Risk factors for unintentional poisoning in children aged 1–3 years in NSW Australia: a case–control study

PubMed Central

2013-01-01

Background Unintentional poisoning in young children is an important public health issue. Age pattern studies have demonstrated that children aged 1–3 years have the highest levels of poisoning risk among children aged 0–4 years, yet little research has been conducted regarding risk factors specific to this three-year age group and the methodologies employed varied greatly. The purpose of the current study is to investigate a broad range of potential risk factors for unintentional poisoning in children aged 1–3 years using appropriate methodologies. Methods Four groups of children, one case group (children who had experienced a poisoning event) and three control groups (children who had been ‘injured’, ‘sick’ or who were ‘healthy’), and their mothers (mother-child dyads) were enrolled into a case–control study. All mother-child dyads participated in a 1.5-hour child developmental screening and observation, with mothers responding to a series of questionnaires at home. Data were analysed as three case–control pairs with multivariate analyses used to control for age and sex differences between child cases and controls. Results Five risk factors were included in the final multivariate models for one or more case–control pairs. All three models found that children whose mothers used more positive control in their interactions during a structured task had higher odds of poisoning. Two models showed that maternal psychiatric distress increased poisoning risk (poisoning-injury and poisoning-healthy). Individual models identified the following variables as risk factors: less proximal maternal supervision during risk taking activities (poisoning-injury), medicinal substances stored in more accessible locations in bathrooms (poisoning-sick) and lower total parenting stress (poisoning-healthy). Conclusions The findings of this study indicate that the nature of the caregiver-child relationship and caregiver attributes play an important role in influencing poisoning risk. Further research is warranted to explore the link between caregiver-child relationships and unintentional poisoning risk. Caregiver education should focus on the benefits of close interaction with their child as a prevention measure. PMID:23705679

Pathways from childhood intelligence and socioeconomic status to late-life cardiovascular disease risk.

PubMed

Hagger-Johnson, Gareth; Mõttus, René; Craig, Leone C A; Starr, John M; Deary, Ian J

2012-07-01

C-reactive protein (CRP) is an acute-phase marker of systemic inflammation and considered an established risk marker for cardiovascular disease (CVD) in old age. Previous studies have suggested that low childhood intelligence, lower socioeconomic status (SES) in childhood or in later life, unhealthy behaviors, poor wellbeing, and high body mass index (BMI) are associated with inflammation. Life course models that simultaneously incorporate all these risk factors can explain how CVD risks accumulate over time, from childhood to old age. Using the data from 1,091 Scottish adults (Lothian Birth Cohort Study, 1936), a path model was constructed to predict CRP at age 70 from concurrent health behaviors, self-perceived quality of life, and BMI and adulthood SES as mediating variables, and from parental SES and childhood intelligence as distal risk factors. A well-fitting path model (CFI = .92, SRMR = .05) demonstrated significant indirect effects from childhood intelligence and parental social class to inflammation via BMI, health behaviors and quality of life (all ps < .05). Low childhood intelligence, unhealthy behaviors, and higher BMI were also direct predictors of CRP. The life course model illustrated how CVD risks may accumulate over time, beginning in childhood and being both direct and transmitted indirectly via low adult SES, unhealthy behaviors, impaired quality of life, and high BMI. Knowledge on the childhood risk factors and their pathways to poor health can be used to identify high-risk individuals for more intensive and tailored behavior change interventions, and to develop effective public health policies.

A multiphase non-linear mixed effects model: An application to spirometry after lung transplantation.

PubMed

Rajeswaran, Jeevanantham; Blackstone, Eugene H

2017-02-01

In medical sciences, we often encounter longitudinal temporal relationships that are non-linear in nature. The influence of risk factors may also change across longitudinal follow-up. A system of multiphase non-linear mixed effects model is presented to model temporal patterns of longitudinal continuous measurements, with temporal decomposition to identify the phases and risk factors within each phase. Application of this model is illustrated using spirometry data after lung transplantation using readily available statistical software. This application illustrates the usefulness of our flexible model when dealing with complex non-linear patterns and time-varying coefficients.

Effect of Precede-Proceed Model on Preventive Behaviors for Type 2 Diabetes Mellitus in High-Risk Individuals.

PubMed

Moshki, Mahdi; Dehnoalian, Atefeh; Alami, Ali

2017-04-01

This study sought to assess the effect of precede-proceed model on preventive behaviors for type 2 diabetes mellitus (DM) in high-risk individuals. In this semi-experimental study, 164 high-risk individuals for type 2 DM were selected and were randomly divided into two groups of intervention and control ( n = 85). Educational intervention was performed as a single session face-to-face instruction for 1.5 hr for the intervention group participants. Data were collected before (baseline) and immediately and 1 month after the intervention in the two groups. The mean score of predisposing (knowledge) factors ( p = .001), reinforcing factors ( p = .001), and enabling factors ( p = .02) were significantly different at baseline and 1 month after the intervention in the intervention group compared with the control group ( p < .05). A significant improvement occurred in the nutritional habits of high-risk participants in the intervention group at 1 month after the intervention compared with controls ( p = .001). The precede-proceed model can be effective for promoting the preventive behaviors for type 2 DM in high-risk individuals.

Neonatal Candidiasis: Epidemiology, Risk Factors, and Clinical Judgment

PubMed Central

Benjamin, Daniel K.; Stoll, Barbara J.; Gantz, Marie G.; Walsh, Michele C.; Sanchez, Pablo J.; Das, Abhik; Shankaran, Seetha; Higgins, Rosemary D.; Auten, Kathy J.; Miller, Nancy A.; Walsh, Thomas J.; Laptook, Abbot R.; Carlo, Waldemar A.; Kennedy, Kathleen A.; Finer, Neil N.; Duara, Shahnaz; Schibler, Kurt; Chapman, Rachel L.; Van Meurs, Krisa P.; Frantz, Ivan D.; Phelps, Dale L.; Poindexter, Brenda B.; Bell, Edward F.; O’Shea, T. Michael; Watterberg, Kristi L.; Goldberg, Ronald N.

2011-01-01

OBJECTIVE Invasive candidiasis is a leading cause of infection-related morbidity and mortality in extremely low-birth-weight (<1000 g) infants. We quantify risk factors predicting infection in high-risk premature infants and compare clinical judgment with a prediction model of invasive candidiasis. METHODS The study involved a prospective observational cohort of infants <1000 g birth weight at 19 centers of the NICHD Neonatal Research Network. At each sepsis evaluation, clinical information was recorded, cultures obtained, and clinicians prospectively recorded their estimate of the probability of invasive candidiasis. Two models were generated with invasive candidiasis as their outcome: 1) potentially modifiable risk factors and 2) a clinical model at time of blood culture to predict candidiasis. RESULTS Invasive candidiasis occurred in 137/1515 (9.0%) infants and was documented by positive culture from ≥ 1 of these sources: blood (n=96), cerebrospinal fluid (n=9), urine obtained by catheterization (n=52), or other sterile body fluid (n=10). Mortality was not different from infants who had positive blood culture compared to those with isolated positive urine culture. Incidence varied from 2–28% at the 13 centers enrolling ≥ 50 infants. Potentially modifiable risk factors (model 1) included central catheter, broad-spectrum antibiotics (e.g., third-generation cephalosporins), intravenous lipid emulsion, endotracheal tube, and antenatal antibiotics. The clinical prediction model (model 2) had an area under the receiver operating characteristic curve of 0.79, and was superior to clinician judgment (0.70) in predicting subsequent invasive candidiasis. Performance of clinical judgment did not vary significantly with level of training. CONCLUSION Prior antibiotics, presence of a central catheter, endotracheal tube, and center were strongly associated with invasive candidiasis. Modeling was more accurate in predicting invasive candidiasis than clinical judgment. PMID:20876174

Can shoulder dystocia be reliably predicted?

PubMed

Dodd, Jodie M; Catcheside, Britt; Scheil, Wendy

2012-06-01

To evaluate factors reported to increase the risk of shoulder dystocia, and to evaluate their predictive value at a population level. The South Australian Pregnancy Outcome Unit's population database from 2005 to 2010 was accessed to determine the occurrence of shoulder dystocia in addition to reported risk factors, including age, parity, self-reported ethnicity, presence of diabetes and infant birth weight. Odds ratios (and 95% confidence interval) of shoulder dystocia was calculated for each risk factor, which were then incorporated into a logistic regression model. Test characteristics for each variable in predicting shoulder dystocia were calculated. As a proportion of all births, the reported rate of shoulder dystocia increased significantly from 0.95% in 2005 to 1.38% in 2010 (P = 0.0002). Using a logistic regression model, induction of labour and infant birth weight greater than both 4000 and 4500 g were identified as significant independent predictors of shoulder dystocia. The value of risk factors alone and when incorporated into the logistic regression model was poorly predictive of the occurrence of shoulder dystocia. While there are a number of factors associated with an increased risk of shoulder dystocia, none are of sufficient sensitivity or positive predictive value to allow their use clinically to reliably and accurately identify the occurrence of shoulder dystocia. © 2012 The Authors ANZJOG © 2012 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.

ICARUSS, the Integrated Care for the Reduction of Secondary Stroke trial: rationale and design of a randomized controlled trial of a multimodal intervention to prevent recurrent stroke in patients with a recent cerebrovascular event, ACTRN = 12611000264987.

PubMed

Joubert, J; Davis, S M; Hankey, G J; Levi, C; Olver, J; Gonzales, G; Donnan, G A

2015-07-01

The majority of strokes, both ischaemic and haemorrhagic, are attributable to a relatively small number of risk factors which are readily manageable in primary care setting. Implementation of best-practice recommendations for risk factor management is calculated to reduce stroke recurrence by around 80%. However, risk factor management in stroke survivors has generally been poor at primary care level. A model of care that supports long-term effective risk factor management is needed. To determine whether the model of Integrated Care for the Reduction of Recurrent Stroke (ICARUSS) will, through promotion of implementation of best-practice recommendations for risk factor management reduce the combined incidence of stroke, myocardial infarction and vascular death in patients with recent stroke or transient ischaemic attack (TIA) of the brain or eye. A prospective, Australian, multicentre, randomized controlled trial. Academic stroke units in Melbourne, Perth and the John Hunter Hospital, New South Wales. 1000 stroke survivors recruited as from March 2007 with a recent (<3 months) stroke (ischaemic or haemorrhagic) or a TIA (brain or eye). Randomization and data collection are performed by means of a central computer generated telephone system (IVRS). Exposure to the ICARUSS model of integrated care or usual care. The composite of stroke, MI or death from any vascular cause, whichever occurs first. Risk factor management in the community, depression, quality of life, disability and dementia. With 1000 patients followed up for a median of one-year, with a recurrence rate of 7-10% per year in patients exposed to usual care, the study will have at least 80% power to detect a significant reduction in primary end-points The ICARUSS study aims to recruit and follow up patients between 2007 and 2013 and demonstrate the effectiveness of exposure to the ICARUSS model in stroke survivors to reduce recurrent stroke or vascular events and promote the implementation of best practice risk factor management at primary care level. © 2015 World Stroke Organization.

Risk factors for the development of heterotopic ossification in seriously burned adults: A National Institute on Disability, Independent Living and Rehabilitation Research burn model system database analysis.

PubMed

Levi, Benjamin; Jayakumar, Prakash; Giladi, Avi; Jupiter, Jesse B; Ring, David C; Kowalske, Karen; Gibran, Nicole S; Herndon, David; Schneider, Jeffrey C; Ryan, Colleen M

2015-11-01

Heterotopic ossification (HO) is a debilitating complication of burn injury; however, incidence and risk factors are poorly understood. In this study, we use a multicenter database of adults with burn injuries to identify and analyze clinical factors that predict HO formation. Data from six high-volume burn centers, in the Burn Injury Model System Database, were analyzed. Univariate logistic regression models were used for model selection. Cluster-adjusted multivariate logistic regression was then used to evaluate the relationship between clinical and demographic data and the development of HO. Of 2,979 patients in the database with information on HO that addressed risk factors for development of HO, 98 (3.5%) developed HO. Of these 98 patients, 97 had arm burns, and 96 had arm grafts. When controlling for age and sex in a multivariate model, patients with greater than 30% total body surface area burn had 11.5 times higher odds of developing HO (p < 0.001), and those with arm burns that required skin grafting had 96.4 times higher odds of developing HO (p = 0.04). For each additional time a patient went to the operating room, odds of HO increased by 30% (odds ratio, 1.32; p < 0.001), and each additional ventilator day increased odds by 3.5% (odds ratio, 1.035; p < 0.001). Joint contracture, inhalation injury, and bone exposure did not significantly increase odds of HO. Risk factors for HO development include greater than 30% total body surface area burn, arm burns, arm grafts, ventilator days, and number of trips to the operating room. Future studies can use these results to identify highest-risk patients to guide deployment of prophylactic and experimental treatments. Prognostic study, level III.

Risk Factors for the Development of Heterotopic Ossification in Seriously Burned Adults: A NIDRR Burn Model System Database Analysis

PubMed Central

Levi, Benjamin; Jayakumar, Prakash; Giladi, Avi; Jupiter, Jesse B.; Ring, David C.; Kowalske, Karen; Gibran, Nicole S.; Herndon, David; Schneider, Jeffrey C.; Ryan, Colleen M.

2015-01-01

Purpose Heterotopic ossification (HO) is a debilitating complication of burn injury; however, incidence and risk factors are poorly understood. In this study we utilize a multicenter database of adults with burn injuries to identify and analyze clinical factors that predict HO formation. Methods Data from 6 high-volume burn centers, in the Burn Injury Model System Database, were analyzed. Univariate logistic regression models were used for model selection. Cluster-adjusted multivariate logistic regression was then used to evaluate the relationship between clinical and demographic data and the development of HO. Results Of 2,979 patients in the database with information on HO that addressed risk factors for development of HO, 98 (3.5%) developed HO. Of these 98 patients, 97 had arm burns, and 96 had arm grafts. Controlling for age and sex in a multivariate model, patients with >30% total body surface area (TBSA) burn had 11.5x higher odds of developing HO (p<0.001), and those with arm burns that required skin grafting had 96.4x higher odds of developing HO (p=0.04). For each additional time a patient went to the operating room, odds of HO increased 30% (OR 1.32, p<0.001), and each additional ventilator day increase odds 3.5% (OR 1.035, p<0.001). Joint contracture, inhalation injury, and bone exposure did not significantly increase odds of HO. Conclusion Risk factors for HO development include >30% TBSA burn, arm burns, arm grafts, ventilator days, and number of trips to the operating room. Future studies can use these results to identify highest-risk patients to guide deployment of prophylactic and experimental treatments. PMID:26496115

An empirical assessment of driver motivation and emotional states in perceived safety margins under varied driving conditions.

PubMed

Zhang, Yu; Kaber, David B

2013-01-01

Motivation models in driving behaviour postulate that driver motives and emotional states dictate risk tolerance under various traffic conditions. The present study used time and driver performance-based payment systems to manipulate motivation and risk-taking behaviour. Ten participants drove to a predefined location in a simulated driving environment. Traffic patterns (density and velocity) were manipulated to cause driver behaviour adjustments due to the need to conform with the social norms of the roadway. The driving environment complexity was investigated as a mediating factor in risk tolerance. Results revealed the performance-based payment system to closely relate to risk-taking behaviour as compared with the time-based payment system. Drivers conformed with social norms associated with specific traffic patterns. Higher roadway complexity led to a more conservative safety margins and speeds. This research contributes to the further development of motivational models of driver behaviour. This study provides empirical justification for two motivation factors in driver risk-taking decisions, including compliance with social norm and emotions triggered by incentives. Environment complexity was identified as a mediating factor in motivational behaviour model. This study also recommended safety margin measures sensitive to changes in driver risk tolerance.

Development of a Risk Assessment Tool to Predict Fall-Related Severe Injuries Occurring in a Hospital

PubMed Central

Toyabe, Shin-ichi

2014-01-01

Inpatient falls are the most common adverse events that occur in a hospital, and about 3 to 10% of falls result in serious injuries such as bone fractures and intracranial haemorrhages. We previously reported that bone fractures and intracranial haemorrhages were two major fall-related injuries and that risk assessment score for osteoporotic bone fracture was significantly associated not only with bone fractures after falls but also with intracranial haemorrhage after falls. Based on the results, we tried to establish a risk assessment tool for predicting fall-related severe injuries in a hospital. Possible risk factors related to fall-related serious injuries were extracted from data on inpatients that were admitted to a tertiary-care university hospital by using multivariate Cox’ s regression analysis and multiple logistic regression analysis. We found that fall risk score and fracture risk score were the two significant factors, and we constructed models to predict fall-related severe injuries incorporating these factors. When the prediction model was applied to another independent dataset, the constructed model could detect patients with fall-related severe injuries efficiently. The new assessment system could identify patients prone to severe injuries after falls in a reproducible fashion. PMID:25168984

The Lack of Utility of Circulating Biomarkers of Inflammation and Endothelial Dysfunction for Type 2 Diabetes Risk Prediction Among Postmenopausal Women

PubMed Central

Chao, Chun; Song, Yiqing; Cook, Nancy; Tseng, Chi-Hong; Manson, JoAnn E.; Eaton, Charles; Margolis, Karen L.; Rodriguez, Beatriz; Phillips, Lawrence S.; Tinker, Lesley F.; Liu, Simin

2011-01-01

Background Recent studies have linked plasma markers of inflammation and endothelial dysfunction to type 2 diabetes mellitus (DM) development. However, the utility of these novel biomarkers for type 2 DM risk prediction remains uncertain. Methods The Women’s Health Initiative Observational Study (WHIOS), a prospective cohort, and a nested case-control study within the WHIOS of 1584 incident type 2 DM cases and 2198 matched controls were used to evaluate the utility of plasma markers of inflammation and endothelial dysfunction for type 2 DM risk prediction. Between September 1994 and December 1998, 93 676 women aged 50 to 79 years were enrolled in the WHIOS. Fasting plasma levels of glucose, insulin, white blood cells, tumor necrosis factor receptor 2, interleukin 6, high-sensitivity C-reactive protein, E-selectin, soluble intercellular adhesion molecule 1, and vascular cell adhesion molecule 1 were measured using blood samples collected at baseline. A series of prediction models including traditional risk factors and novel plasma markers were evaluated on the basis of global model fit, model discrimination, net reclassification improvement, and positive and negative predictive values. Results Although white blood cell count and levels of interleukin 6, high-sensitivity C-reactive protein, and soluble intercellular adhesion molecule 1 significantly enhanced model fit, none of the inflammatory and endothelial dysfunction markers improved the ability of model discrimination (area under the receiver operating characteristic curve, 0.93 vs 0.93), net reclassification, or predictive values (positive, 0.22 vs 0.24; negative, 0.99 vs 0.99 [using 15% 6-year type 2 DM risk as the cutoff]) compared with traditional risk factors. Similar results were obtained in ethnic-specific analyses. Conclusion Beyond traditional risk factors, measurement of plasma markers of systemic inflammation and endothelial dysfunction contribute relatively little additional value in clinical type 2 DM risk prediction in a multiethnic cohort of postmenopausal women. PMID:20876407

Risk forewarning model for rice grain Cd pollution based on Bayes theory.

PubMed

Wu, Bo; Guo, Shuhai; Zhang, Lingyan; Li, Fengmei

2018-03-15

Cadmium (Cd) pollution of rice grain caused by Cd-contaminated soils is a common problem in southwest and central south China. In this study, utilizing the advantages of the Bayes classification statistical method, we established a risk forewarning model for rice grain Cd pollution, and put forward two parameters (the prior probability factor and data variability factor). The sensitivity analysis of the model parameters illustrated that sample size and standard deviation influenced the accuracy and applicable range of the model. The accuracy of the model was improved by the self-renewal of the model through adding the posterior data into the priori data. Furthermore, this method can be used to predict the risk probability of rice grain Cd pollution under similar soil environment, tillage and rice varietal conditions. The Bayes approach thus represents a feasible method for risk forewarning of heavy metals pollution of agricultural products caused by contaminated soils. Copyright © 2017 Elsevier B.V. All rights reserved.

Explaining the low risk of preterm birth among arab americans in the United States: an analysis of 617451 births.

PubMed

El-Sayed, Abdulrahman M; Galea, Sandro

2009-03-01

Arab Americans have a lower risk for preterm birth than white Americans. We assessed factors that may contribute to the association between ethnicity and preterm birth risk in Michigan, the state with the largest concentration of Arab Americans in the United States. Factors assessed as potential contributors to the ethnicity/preterm birth risk association were maternal age, parity, education, marital status, tobacco use, and maternal birthplace. Data were collected about all births in Michigan between 2000 and 2005. Stratified analyses, trivariate analyses, and manual stepwise logistic regression model building were used to assess potential contributors to the ethnicity/preterm birth risk association. Arab ethnicity was associated with lower preterm birth risk compared with non-Arab white subjects in the unadjusted model. Maternal birthplace inside or outside the United States explained 0.17 of the difference in preterm birth risk between Arab ethnicity and non-Arab white mothers; ethnic differences in marital status and tobacco use explained less of the observed ethnic difference in preterm birth risk. In the final model adjusted for all explanatory variables, Arab ethnicity was no longer associated with preterm birth risk. Maternal birthplace, marital status, and tobacco use may contribute to the preterm birth risk difference between Arab ethnicity and non-Arab white mothers. Additional work is needed to consider the mechanisms relating factors such as maternal birthplace and marital status to ethnic differences in preterm birth risk.

Latent Model Analysis of Substance Use and HIV Risk Behaviors among High-Risk Minority Adults

ERIC Educational Resources Information Center

Wang, Min Qi; Matthew, Resa F.; Chiu, Yu-Wen; Yan, Fang; Bellamy, Nikki D.

2007-01-01

Objectives: This study evaluated substance use and HIV risk profile using a latent model analysis based on ecological theory, inclusive of a risk and protective factor framework, in sexually active minority adults (N=1,056) who participated in a federally funded substance abuse and HIV prevention health initiative from 2002 to 2006. Methods: Data…

External validation and comparison with other models of the International Metastatic Renal-Cell Carcinoma Database Consortium prognostic model: a population-based study

PubMed Central

Heng, Daniel Y C; Xie, Wanling; Regan, Meredith M; Harshman, Lauren C; Bjarnason, Georg A; Vaishampayan, Ulka N; Mackenzie, Mary; Wood, Lori; Donskov, Frede; Tan, Min-Han; Rha, Sun-Young; Agarwal, Neeraj; Kollmannsberger, Christian; Rini, Brian I; Choueiri, Toni K

2014-01-01

Summary Background The International Metastatic Renal-Cell Carcinoma Database Consortium model offers prognostic information for patients with metastatic renal-cell carcinoma. We tested the accuracy of the model in an external population and compared it with other prognostic models. Methods We included patients with metastatic renal-cell carcinoma who were treated with first-line VEGF-targeted treatment at 13 international cancer centres and who were registered in the Consortium’s database but had not contributed to the initial development of the Consortium Database model. The primary endpoint was overall survival. We compared the Database Consortium model with the Cleveland Clinic Foundation (CCF) model, the International Kidney Cancer Working Group (IKCWG) model, the French model, and the Memorial Sloan-Kettering Cancer Center (MSKCC) model by concordance indices and other measures of model fit. Findings Overall, 1028 patients were included in this study, of whom 849 had complete data to assess the Database Consortium model. Median overall survival was 18·8 months (95% 17·6–21·4). The predefined Database Consortium risk factors (anaemia, thrombocytosis, neutrophilia, hypercalcaemia, Karnofsky performance status <80%, and <1 year from diagnosis to treatment) were independent predictors of poor overall survival in the external validation set (hazard ratios ranged between 1·27 and 2·08, concordance index 0·71, 95% CI 0·68–0·73). When patients were segregated into three risk categories, median overall survival was 43·2 months (95% CI 31·4–50·1) in the favourable risk group (no risk factors; 157 patients), 22·5 months (18·7–25·1) in the intermediate risk group (one to two risk factors; 440 patients), and 7·8 months (6·5–9·7) in the poor risk group (three or more risk factors; 252 patients; p<0·0001; concordance index 0·664, 95% CI 0·639–0·689). 672 patients had complete data to test all five models. The concordance index of the CCF model was 0·662 (95% CI 0·636–0·687), of the French model 0·640 (0·614–0·665), of the IKCWG model 0·668 (0·645–0·692), and of the MSKCC model 0·657 (0·632–0·682). The reported versus predicted number of deaths at 2 years was most similar in the Database Consortium model compared with the other models. Interpretation The Database Consortium model is now externally validated and can be applied to stratify patients by risk in clinical trials and to counsel patients about prognosis. PMID:23312463

[Clustering patterns of behavioral risk factors linked to chronic disease among young adults in two localities in Bogota, Colombia: importance of sex differences].

PubMed

Gómez Gutiérrez, Luis Fernando; Lucumí Cuesta, Diego Iván; Girón Vargas, Sandra Lorena; Espinosa García, Gladys

2004-01-01

The characterization of clustering behavioral risk factors may be used as a guideline for interventions aimed at preventing chronic diseases. This study determined the clustering patterns of some behavioral risk factors in young adults aged 18 to 29 years and established the factors associated with having two or more of them. Patterns of clustering by gender were established in four behavioral risk factors (low consumption of fruits and vegetables, physical inactivity in leisure time, current tobacco consumption and acute alcohol consumption), in 1465 young adults participants through a multistage probabilistic sample. Regression models identified the sociodemografic variables associated with having two or more of the aforementioned behavioral risk factors. Having one, 32.9% two and 17.7% three or four. Acute alcohol consumption was the risk factor most frequent in the combined risk factor patterns among males; physical inactivity during leisure time being the most frequent among females. Among the females, having two or more behavioral risk factors was linked to be separated or divorced, this having been linked to work having been the main activity over the past 30 days among males. The combinations of behavioral risk factors studied and the factors associated with clustering show different patterns among males and females. These findings stressed the need of designing interventions sensitive to gender differences.

Integrating eating disorder-specific risk factors into the acquired preparedness model of dysregulated eating: A moderated mediation analysis.

PubMed

Racine, Sarah E; Martin, Shelby J

2017-01-01

Tests of the acquired preparedness model demonstrate that the personality trait of negative urgency (i.e., the tendency to act impulsively when distressed) predicts the expectation that eating alleviates negative affect, and this eating expectancy subsequently predicts dysregulated eating. Although recent data indicate that eating disorder-specific risk factors (i.e., appearance pressures, thin-ideal internalization, body dissatisfaction, dietary restraint) strengthen negative urgency-dysregulated eating associations, it is unclear whether these risk factors impact associations directly or indirectly (i.e., through eating expectancies). The current study used latent moderated structural equation modeling to test moderated mediation hypotheses in a sample of 313 female college students. Eating expectancies mediated the association between negative urgency and dysregulated eating, and the indirect effect of negative urgency on dysregulated eating through eating expectancies was conditional on level of each eating disorder risk factor. Appearance pressures, thin-ideal internalization, body dissatisfaction, and dietary restraint significantly moderated the association between eating expectancies and dysregulated eating, while only dietary restraint moderated the direct effect of negative urgency on dysregulated eating. Findings suggest that the development of high-risk eating expectancies among individuals with negative urgency, combined with sociocultural pressures for thinness and their consequences, is associated with the greatest risk for dysregulated eating. Copyright © 2016 Elsevier Ltd. All rights reserved.

Risk factors for Apgar score using artificial neural networks.

PubMed

Ibrahim, Doaa; Frize, Monique; Walker, Robin C

2006-01-01

Artificial Neural Networks (ANNs) have been used in identifying the risk factors for many medical outcomes. In this paper, the risk factors for low Apgar score are introduced. This is the first time, to our knowledge, that the ANNs are used for Apgar score prediction. The medical domain of interest used is the perinatal database provided by the Perinatal Partnership Program of Eastern and Southeastern Ontario (PPPESO). The ability of the feed forward back propagation ANNs to generate strong predictive model with the most influential variables is tested. Finally, minimal sets of variables (risk factors) that are important in predicting Apgar score outcome without degrading the ANN performance are identified.

[Ecological Correlates of Cardiovascular Disease Risk in Korean Blue-collar Workers: A Multi-level Study].

PubMed

Hwang, Won Ju; Park, Yunhee

2015-12-01

The purpose of this study was to investigate individual and organizational level of cardiovascular disease (CVD) risk factors associated with CVD risk in Korean blue-collar workers working in small sized companies. Self-report questionnaires and blood sampling for lipid and glucose were collected from 492 workers in 31 small sized companies in Korea. Multilevel modeling was conducted to estimate effects of related factors at the individual and organizational level. Multilevel regression analysis showed that workers in the workplace having a cafeteria had 1.81 times higher CVD risk after adjusting for factors at the individual level (p=.022). The explanatory power of variables related to organizational level variances in CVD risk was 17.1%. The results of this study indicate that differences in the CVD risk were related to organizational factors. It is necessary to consider not only individual factors but also organizational factors when planning a CVD risk reduction program. The factors caused by having cafeteria in the workplace can be reduced by improvement in the CVD-related risk environment, therefore an organizational-level intervention approach should be available to reduce CVD risk of workers in small sized companies in Korea.

Examining the association of abortion history and current mental health: A reanalysis of the National Comorbidity Survey using a common-risk-factors model.

PubMed

Steinberg, Julia R; Finer, Lawrence B

2011-01-01

Using the US National Comorbidity Survey (NCS), Coleman, Coyle, Shuping, and Rue (2009) published an analysis indicating that compared to women who had never had an abortion, women who had reported an abortion were at an increased risk of several anxiety, mood, and substance use disorders. Here, we show that those results are not replicable. That is, using the same data, sample, and codes as indicated by those authors, it is not possible to replicate the simple bivariate statistics testing the relationship of ever having had an abortion to each mental health disorder when no factors were controlled for in analyses (Table 2 in Coleman et al., 2009). Furthermore, among women with prior pregnancies in the NCS, we investigated whether having zero, one, or multiple abortions (abortion history) was associated with having a mood, anxiety, or substance use disorder at the time of the interview. In doing this, we tested two competing frameworks: the abortion-as-trauma versus the common-risk-factors approach. Our results support the latter framework. In the bivariate context when no other factors were included in models, abortion history was not related to having a mood disorder, but it was related to having an anxiety or substance use disorder. When prior mental health and violence experience were controlled in our models, no significant relation was found between abortion history and anxiety disorders. When these same risk factors and other background factors were controlled, women who had multiple abortions remained at an increased risk of having a substance use disorder compared to women who had no abortions, likely because we were unable to control for other risk factors associated with having an abortion and substance use. Policy, practice, and research should focus on assisting women at greatest risk of having unintended pregnancies and having poor mental health-those with violence in their lives and prior mental health problems. Copyright © 2010 Elsevier Ltd. All rights reserved.

Evaluating risk factors for endemic human Salmonella Enteritidis infections with different phage types in Ontario, Canada using multinomial logistic regression and a case-case study approach

PubMed Central

2012-01-01

Background Identifying risk factors for Salmonella Enteritidis (SE) infections in Ontario will assist public health authorities to design effective control and prevention programs to reduce the burden of SE infections. Our research objective was to identify risk factors for acquiring SE infections with various phage types (PT) in Ontario, Canada. We hypothesized that certain PTs (e.g., PT8 and PT13a) have specific risk factors for infection. Methods Our study included endemic SE cases with various PTs whose isolates were submitted to the Public Health Laboratory-Toronto from January 20th to August 12th, 2011. Cases were interviewed using a standardized questionnaire that included questions pertaining to demographics, travel history, clinical symptoms, contact with animals, and food exposures. A multinomial logistic regression method using the Generalized Linear Latent and Mixed Model procedure and a case-case study design were used to identify risk factors for acquiring SE infections with various PTs in Ontario, Canada. In the multinomial logistic regression model, the outcome variable had three categories representing human infections caused by SE PT8, PT13a, and all other SE PTs (i.e., non-PT8/non-PT13a) as a referent category to which the other two categories were compared. Results In the multivariable model, SE PT8 was positively associated with contact with dogs (OR=2.17, 95% CI 1.01-4.68) and negatively associated with pepper consumption (OR=0.35, 95% CI 0.13-0.94), after adjusting for age categories and gender, and using exposure periods and health regions as random effects to account for clustering. Conclusions Our study findings offer interesting hypotheses about the role of phage type-specific risk factors. Multinomial logistic regression analysis and the case-case study approach are novel methodologies to evaluate associations among SE infections with different PTs and various risk factors. PMID:23057531

Building a Values-Informed Mental Model for New Orleans Climate Risk Management.

PubMed

Bessette, Douglas L; Mayer, Lauren A; Cwik, Bryan; Vezér, Martin; Keller, Klaus; Lempert, Robert J; Tuana, Nancy

2017-10-01

Individuals use values to frame their beliefs and simplify their understanding when confronted with complex and uncertain situations. The high complexity and deep uncertainty involved in climate risk management (CRM) lead to individuals' values likely being coupled to and contributing to their understanding of specific climate risk factors and management strategies. Most mental model approaches, however, which are commonly used to inform our understanding of people's beliefs, ignore values. In response, we developed a "Values-informed Mental Model" research approach, or ViMM, to elicit individuals' values alongside their beliefs and determine which values people use to understand and assess specific climate risk factors and CRM strategies. Our results show that participants consistently used one of three values to frame their understanding of risk factors and CRM strategies in New Orleans: (1) fostering a healthy economy, wealth, and job creation, (2) protecting and promoting healthy ecosystems and biodiversity, and (3) preserving New Orleans' unique culture, traditions, and historically significant neighborhoods. While the first value frame is common in analyses of CRM strategies, the latter two are often ignored, despite their mirroring commonly accepted pillars of sustainability. Other values like distributive justice and fairness were prioritized differently depending on the risk factor or strategy being discussed. These results suggest that the ViMM method could be a critical first step in CRM decision-support processes and may encourage adoption of CRM strategies more in line with stakeholders' values. © 2017 Society for Risk Analysis.

Personality disorder risk factors for suicide attempts over 10 years of follow-up.

PubMed

Ansell, Emily B; Wright, Aidan G C; Markowitz, John C; Sanislow, Charles A; Hopwood, Christopher J; Zanarini, Mary C; Yen, Shirley; Pinto, Anthony; McGlashan, Thomas H; Grilo, Carlos M

2015-04-01

Identifying personality disorder (PD) risk factors for suicide attempts is an important consideration for research and clinical care alike. However, most prior research has focused on single PDs or categorical PD diagnoses without considering unique influences of different PDs or of severity (sum) of PD criteria on the risk for suicide-related outcomes. This has usually been done with cross-sectional or retrospective assessment methods. Rarely are dimensional models of PDs examined in longitudinal, naturalistic prospective designs. In addition, it is important to consider divergent risk factors in predicting the risk of ever making a suicide attempt versus the risk of making an increasing number of attempts within the same model. This study examined 431 participants who were followed for 10 years in the Collaborative Longitudinal Personality Disorders Study. Baseline assessments of personality disorder criteria were summed as dimensional counts of personality pathology and examined as predictors of suicide attempts reported at annual interviews throughout the 10-year follow-up period. We used univariate and multivariate zero-inflated Poisson regression models to simultaneously evaluate PD risk factors for ever attempting suicide and for increasing numbers of attempts among attempters. Consistent with prior research, borderline PD was uniquely associated with ever attempting. However, only narcissistic PD was uniquely associated with an increasing number of attempts. These findings highlight the relevance of both borderline and narcissistic personality pathology as unique contributors to suicide-related outcomes. (c) 2015 APA, all rights reserved).

[Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

PubMed

Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

2011-11-01

To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P < 0.0001) based on testing by the Lagrangemultiplier. Therefore, the over-dispersion dispersed data using a modified Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

Assessing risk factors for periodontitis using regression

NASA Astrophysics Data System (ADS)

Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa

2013-10-01

Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.

A Regularized Deep Learning Approach for Clinical Risk Prediction of Acute Coronary Syndrome Using Electronic Health Records.

PubMed

Huang, Zhengxing; Dong, Wei; Duan, Huilong; Liu, Jiquan

2018-05-01

Acute coronary syndrome (ACS), as a common and severe cardiovascular disease, is a leading cause of death and the principal cause of serious long-term disability globally. Clinical risk prediction of ACS is important for early intervention and treatment. Existing ACS risk scoring models are based mainly on a small set of hand-picked risk factors and often dichotomize predictive variables to simplify the score calculation. This study develops a regularized stacked denoising autoencoder (SDAE) model to stratify clinical risks of ACS patients from a large volume of electronic health records (EHR). To capture characteristics of patients at similar risk levels, and preserve the discriminating information across different risk levels, two constraints are added on SDAE to make the reconstructed feature representations contain more risk information of patients, which contribute to a better clinical risk prediction result. We validate our approach on a real clinical dataset consisting of 3464 ACS patient samples. The performance of our approach for predicting ACS risk remains robust and reaches 0.868 and 0.73 in terms of both AUC and accuracy, respectively. The obtained results show that the proposed approach achieves a competitive performance compared to state-of-the-art models in dealing with the clinical risk prediction problem. In addition, our approach can extract informative risk factors of ACS via a reconstructive learning strategy. Some of these extracted risk factors are not only consistent with existing medical domain knowledge, but also contain suggestive hypotheses that could be validated by further investigations in the medical domain.

Downscaling Pest Risk Analyses: Identifying Current and Future Potentially Suitable Habitats for Parthenium hysterophorus with Particular Reference to Europe and North Africa

PubMed Central

Kriticos, Darren J.; Brunel, Sarah; Ota, Noboru; Fried, Guillaume; Oude Lansink, Alfons G. J. M.; Panetta, F. Dane; Prasad, T. V. Ramachandra; Shabbir, Asad; Yaacoby, Tuvia

2015-01-01

Pest Risk Assessments (PRAs) routinely employ climatic niche models to identify endangered areas. Typically, these models consider only climatic factors, ignoring the ‘Swiss Cheese’ nature of species ranges due to the interplay of climatic and habitat factors. As part of a PRA conducted for the European and Mediterranean Plant Protection Organization, we developed a climatic niche model for Parthenium hysterophorus, explicitly including the effects of irrigation where it was known to be practiced. We then downscaled the climatic risk model using two different methods to identify the suitable habitat types: expert opinion (following the EPPO PRA guidelines) and inferred from the global spatial distribution. The PRA revealed a substantial risk to the EPPO region and Central and Western Africa, highlighting the desirability of avoiding an invasion by P. hysterophorus. We also consider the effects of climate change on the modelled risks. The climate change scenario indicated the risk of substantial further spread of P. hysterophorus in temperate northern hemisphere regions (North America, Europe and the northern Middle East), and also high elevation equatorial regions (Western Brazil, Central Africa, and South East Asia) if minimum temperatures increase substantially. Downscaling the climate model using habitat factors resulted in substantial (approximately 22–53%) reductions in the areas estimated to be endangered. Applying expert assessments as to suitable habitat classes resulted in the greatest reduction in the estimated endangered area, whereas inferring suitable habitats factors from distribution data identified more land use classes and a larger endangered area. Despite some scaling issues with using a globally conformal Land Use Systems dataset, the inferential downscaling method shows promise as a routine addition to the PRA toolkit, as either a direct model component, or simply as a means of better informing an expert assessment of the suitable habitat types. PMID:26325680

Synergistic Association of Genetic Variants with Environmental Risk Factors in Susceptibility to Essential Hypertension.

PubMed

Sousa, Ana Célia; Mendonça, Maria I; Pereira, Andreia; Gouveia, Sara; Freitas, Ana I; Guerra, Graça; Rodrigues, Mariana; Henriques, Eva; Freitas, Sónia; Borges, Sofia; Pereira, Décio; Brehm, António; Palma Dos Reis, Roberto

2017-10-01

Essential hypertension (EH) is a disease in which both environment and genes have an important role. This study was designed to identify the interaction model between genetic variants and environmental risk factors that most highly potentiates EH development. We performed a case-control study with 1641 participants (mean age 50.6 ± 8.1 years), specifically 848 patients with EH and 793 controls, adjusted for gender and age. Traditional risk factors, biochemical and genetic parameters, including the genotypic discrimination of 14 genetic variants previously associated with EH, were investigated. Multifactorial dimensionality reduction (MDR) software was used to analyze gene-environment interactions. Validation was performed using logistic regression analysis with environmental risk factors, significant genetic variants, and the best MDR model. The best model indicates that the interactions among the ADD1 rs4961 640T allele, diabetes, and obesity (body mass index ≥30) increase approximately four-fold the risk of EH (odds ratio = 3.725; 95% confidence interval: 2.945-4.711; p < 0.0001). This work showed that the interaction between the ADD1 rs4961 variant, obesity, and the presence of diabetes increased the susceptibility to EH four-fold. In these circumstances, lifestyle adjustment and diabetes control should be intensified in patients who carry the ADD1 variant.

Risk Assessment of Groundwater Contamination: A Multilevel Fuzzy Comprehensive Evaluation Approach Based on DRASTIC Model

PubMed Central

Zhang, Yan; Zhong, Ming

2013-01-01

Groundwater contamination is a serious threat to water supply. Risk assessment of groundwater contamination is an effective way to protect the safety of groundwater resource. Groundwater is a complex and fuzzy system with many uncertainties, which is impacted by different geological and hydrological factors. In order to deal with the uncertainty in the risk assessment of groundwater contamination, we propose an approach with analysis hierarchy process and fuzzy comprehensive evaluation integrated together. Firstly, the risk factors of groundwater contamination are identified by the sources-pathway-receptor-consequence method, and a corresponding index system of risk assessment based on DRASTIC model is established. Due to the complexity in the process of transitions between the possible pollution risks and the uncertainties of factors, the method of analysis hierarchy process is applied to determine the weights of each factor, and the fuzzy sets theory is adopted to calculate the membership degrees of each factor. Finally, a case study is presented to illustrate and test this methodology. It is concluded that the proposed approach integrates the advantages of both analysis hierarchy process and fuzzy comprehensive evaluation, which provides a more flexible and reliable way to deal with the linguistic uncertainty and mechanism uncertainty in groundwater contamination without losing important information. PMID:24453883

Risk Factors for Substance Misuse and Adolescents' Symptoms of Depression.

PubMed

Siennick, Sonja E; Widdowson, Alex O; Woessner, Mathew K; Feinberg, Mark E; Spoth, Richard L

2017-01-01

Depressive symptoms during adolescence are positively associated with peer-related beliefs, perceptions, and experiences that are known risk factors for substance misuse. These same risk factors are targeted by many universal substance misuse prevention programs. This study examined whether a multicomponent universal substance misuse intervention for middle schoolers reduced the associations between depressive symptoms, these risk factors, and substance misuse. The study used data from a place-randomized trial of the Promoting School-Community-University Partnerships to Enhance Resilience model for delivery of evidence-based substance misuse programs for middle schoolers. Three-level within-person regression models were applied to four waves of survey, and social network data from 636 adolescents followed from sixth through ninth grades. When adolescents in control school districts had more symptoms of depression, they believed more strongly that substance use had social benefits, perceived higher levels of substance misuse among their peers and friends, and had more friends who misused substances, although they were not more likely to use substances themselves. Many of the positive associations of depressive symptoms with peer-related risk factors were significantly weaker or not present among adolescents in intervention school districts. The Promoting School-Community-University Partnerships to Enhance Resilience interventions reduced the positive associations of adolescent symptoms of depression with peer-related risk factors for substance misuse. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Breast arterial calcification is associated with reproductive factors in asymptomatic postmenopausal women.

PubMed

Bielak, Lawrence F; Whaley, Dana H; Sheedy, Patrick F; Peyser, Patricia A

2010-09-01

The etiology of breast arterial calcification (BAC) is not well understood. We examined reproductive history and cardiovascular disease (CVD) risk factor associations with the presence of detectable BAC in asymptomatic postmenopausal women. Reproductive history and CVD risk factors were obtained in 240 asymptomatic postmenopausal women from a community-based research study who had a screening mammogram within 2 years of their participation in the study. The mammograms were reviewed for the presence of detectable BAC. Age-adjusted logistic regression models were fit to assess the association between each risk factor and the presence of BAC. Multiple variable logistic regression models were used to identify the most parsimonious model for the presence of BAC. The prevalence of BAC increased with increased age (p < 0.0001). The most parsimonious logistic regression model for BAC presence included age at time of examination, increased parity (p = 0.01), earlier age at first birth (p = 0.002), weight, and an age-by-weight interaction term (p = 0.004). Older women with a smaller body size had a higher probability of having BAC than women of the same age with a larger body size. The presence or absence of BAC at mammography may provide an assessment of a postmenopausal woman's lifetime estrogen exposure and indicate women who could be at risk for hormonally related conditions.

Time-specific ecologic niche models forecast the risk of hemorrhagic fever with renal syndrome in Dongting Lake district, China, 2005-2010.

PubMed

Liu, Hai-Ning; Gao, Li-Dong; Chowell, Gerardo; Hu, Shi-Xiong; Lin, Xiao-Ling; Li, Xiu-Jun; Ma, Gui-Hua; Huang, Ru; Yang, Hui-Suo; Tian, Huaiyu; Xiao, Hong

2014-01-01

Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne infectious disease, is one of the most serious public health threats in China. Increasing our understanding of the spatial and temporal patterns of HFRS infections could guide local prevention and control strategies. We employed statistical models to analyze HFRS case data together with environmental data from the Dongting Lake district during 2005-2010. Specifically, time-specific ecologic niche models (ENMs) were used to quantify and identify risk factors associated with HFRS transmission as well as forecast seasonal variation in risk across geographic areas. Results showed that the Maximum Entropy model provided the best predictive ability (AUC = 0.755). Time-specific Maximum Entropy models showed that the potential risk areas of HFRS significantly varied across seasons. High-risk areas were mainly found in the southeastern and southwestern areas of the Dongting Lake district. Our findings based on models focused on the spring and winter seasons showed particularly good performance. The potential risk areas were smaller in March, May and August compared with those identified for June, July and October to December. Both normalized difference vegetation index (NDVI) and land use types were found to be the dominant risk factors. Our findings indicate that time-specific ENMs provide a useful tool to forecast the spatial and temporal risk of HFRS.

Relation of aortic valve calcium to chronic kidney disease (from the Chronic Renal Insufficiency Cohort Study).

PubMed

Guerraty, Marie A; Chai, Boyang; Hsu, Jesse Y; Ojo, Akinlolu O; Gao, Yanlin; Yang, Wei; Keane, Martin G; Budoff, Matthew J; Mohler, Emile R

2015-05-01

Although subjects with chronic kidney disease (CKD) are at markedly increased risk for cardiovascular mortality, the relation between CKD and aortic valve calcification has not been fully elucidated. Also, few data are available on the relation of aortic valve calcification and earlier stages of CKD. We sought to assess the relation of aortic valve calcium (AVC) with estimated glomerular filtration rate (eGFR), traditional and novel cardiovascular risk factors, and markers of bone metabolism in the Chronic Renal Insufficiency Cohort (CRIC) Study. All patients who underwent aortic valve scanning in the CRIC study were included. The relation between AVC and eGFR, traditional and novel cardiovascular risk factors, and markers of calcium metabolism were analyzed using both unadjusted and adjusted regression models. A total of 1,964 CRIC participants underwent computed tomography for AVC quantification. Decreased renal function was independently associated with increased levels of AVC (eGFR 47.11, 44.17, and 39 ml/min/1.73 m2, respectively, p<0.001). This association persisted after adjusting for traditional, but not novel, AVC risk factors. Adjusted regression models identified several traditional and novel risk factors for AVC in patients with CKD. There was a difference in AVC risk factors between black and nonblack patients. In conclusion, our study shows that eGFR is associated in a dose-dependent manner with AVC in patients with CKD, and this association is independent of traditional cardiovascular risk factors. Copyright © 2015 Elsevier Inc. All rights reserved.

A risk-model for hospital mortality among patients with severe sepsis or septic shock based on German national administrative claims data

PubMed Central

Fleischmann-Struzek, Carolin; Rüddel, Hendrik; Reinhart, Konrad; Thomas-Rüddel, Daniel O.

2018-01-01

Background Sepsis is a major cause of preventable deaths in hospitals. Feasible and valid methods for comparing quality of sepsis care between hospitals are needed. The aim of this study was to develop a risk-adjustment model suitable for comparing sepsis-related mortality between German hospitals. Methods We developed a risk-model using national German claims data. Since these data are available with a time-lag of 1.5 years only, the stability of the model across time was investigated. The model was derived from inpatient cases with severe sepsis or septic shock treated in 2013 using logistic regression with backward selection and generalized estimating equations to correct for clustering. It was validated among cases treated in 2015. Finally, the model development was repeated in 2015. To investigate secular changes, the risk-adjusted trajectory of mortality across the years 2010–2015 was analyzed. Results The 2013 deviation sample consisted of 113,750 cases; the 2015 validation sample consisted of 134,851 cases. The model developed in 2013 showed good validity regarding discrimination (AUC = 0.74), calibration (observed mortality in 1st and 10th risk-decile: 11%-78%), and fit (R2 = 0.16). Validity remained stable when the model was applied to 2015 (AUC = 0.74, 1st and 10th risk-decile: 10%-77%, R2 = 0.17). There was no indication of overfitting of the model. The final model developed in year 2015 contained 40 risk-factors. Between 2010 and 2015 hospital mortality in sepsis decreased from 48% to 42%. Adjusted for risk-factors the trajectory of decrease was still significant. Conclusions The risk-model shows good predictive validity and stability across time. The model is suitable to be used as an external algorithm for comparing risk-adjusted sepsis mortality among German hospitals or regions based on administrative claims data, but secular changes need to be taken into account when interpreting risk-adjusted mortality. PMID:29558486

A risk-model for hospital mortality among patients with severe sepsis or septic shock based on German national administrative claims data.

PubMed

Schwarzkopf, Daniel; Fleischmann-Struzek, Carolin; Rüddel, Hendrik; Reinhart, Konrad; Thomas-Rüddel, Daniel O

2018-01-01

Sepsis is a major cause of preventable deaths in hospitals. Feasible and valid methods for comparing quality of sepsis care between hospitals are needed. The aim of this study was to develop a risk-adjustment model suitable for comparing sepsis-related mortality between German hospitals. We developed a risk-model using national German claims data. Since these data are available with a time-lag of 1.5 years only, the stability of the model across time was investigated. The model was derived from inpatient cases with severe sepsis or septic shock treated in 2013 using logistic regression with backward selection and generalized estimating equations to correct for clustering. It was validated among cases treated in 2015. Finally, the model development was repeated in 2015. To investigate secular changes, the risk-adjusted trajectory of mortality across the years 2010-2015 was analyzed. The 2013 deviation sample consisted of 113,750 cases; the 2015 validation sample consisted of 134,851 cases. The model developed in 2013 showed good validity regarding discrimination (AUC = 0.74), calibration (observed mortality in 1st and 10th risk-decile: 11%-78%), and fit (R2 = 0.16). Validity remained stable when the model was applied to 2015 (AUC = 0.74, 1st and 10th risk-decile: 10%-77%, R2 = 0.17). There was no indication of overfitting of the model. The final model developed in year 2015 contained 40 risk-factors. Between 2010 and 2015 hospital mortality in sepsis decreased from 48% to 42%. Adjusted for risk-factors the trajectory of decrease was still significant. The risk-model shows good predictive validity and stability across time. The model is suitable to be used as an external algorithm for comparing risk-adjusted sepsis mortality among German hospitals or regions based on administrative claims data, but secular changes need to be taken into account when interpreting risk-adjusted mortality.

The correlation analysis of tumor necrosis factor-alpha-308G/A polymorphism and venous thromboembolism risk: A meta-analysis.

PubMed

Gao, Quangen; Zhang, Peijin; Wang, Wei; Ma, He; Tong, Yue; Zhang, Jing; Lu, Zhaojun

2016-10-01

Venous thromboembolism is a common complex disorder, being the resultant of gene-gene and gene-environment interactions. Tumor necrosis factor-alpha is a proinflammatory cytokine which has been implicated in venous thromboembolism risk. A promoter 308G/A polymorphism in the tumor necrosis factor-alpha gene has been suggested to modulate the risk for venous thromboembolism. However, the published findings remain inconsistent. In this study, we conducted a meta-analysis of all available data regarding this issue. Eligible studies were identified through search of Pubmed, EBSCO Medline, Web of Science, and China National Knowledge Infrastructure (CNKI, Chinese) databases up to June 2014. Pooled Odd ratios (ORs) with 95% confidence intervals were applied to estimating the strength of the genetic association in the random-effects model or fixed-effects model. A total of 10 studies involving 1999 venous thromboembolism cases and 2166 controls were included in this meta-analysis to evaluate the association between tumor necrosis factor-alpha-308G/A polymorphism and venous thromboembolism risk. Overall, no significantly increased risk venous thromboembolism was observed in all comparison models when all studies were pooled into the meta-analysis. However, in stratified analyses by ethnicity, there was a pronounced association with venous thromboembolism risk among West Asians in three genetic models (A vs. G: OR = 1.82, 95%CI = 1.13-2.94; GA vs. GG: OR = 1.82, 95%CI = 1.08-3.06; AA/GA vs. GG: OR = 1.88, 95%CI = 1.12-3.16). When stratifying by source of controls, no significant result was detected in all genetic models. This meta-analysis demonstrates that tumor necrosis factor-alpha 308G/A polymorphism may contribute to susceptibility to venous thromboembolism among West Asians. Studies are needed to ascertain these findings in larger samples and different racial groups. © The Author(s) 2015.

78 FR 12127 - Self-Regulatory Organizations; Chicago Mercantile Exchange Inc.; Notice of Designation of a...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-21

... risk factor component of its credit default swap (``CDS'') margin model. CME proposes to use an index... with the liquidity risk factor component. The proposed rule change was published for comment in the... on Proposed Rule Change Related to the Liquidity Factor of CME's CDS Margin Methodology February 14...

Modelling determinants, impact, and space-time risk of age-specific mortality in rural South Africa: integrating methods to enhance policy relevance.

PubMed

Sartorius, Benn

2013-01-24

There is a lack of reliable data in developing countries to inform policy and optimise resource allocation. Health and socio-demographic surveillance sites (HDSS) have the potential to address this gap. Mortality levels and trends have previously been documented in rural South Africa. However, complex space-time clustering of mortality, determinants, and their impact has not been fully examined. To integrate advanced methods enhance the understanding of the dynamics of mortality in space-time, to identify mortality risk factors and population attributable impact, to relate disparities in risk factor distributions to spatial mortality risk, and thus, to improve policy planning and resource allocation. Agincourt HDSS supplied data for the period 1992-2008. Advanced spatial techniques were used to identify significant age-specific mortality 'hotspots' in space-time. Multivariable Bayesian models were used to assess the effects of the most significant covariates on mortality. Disparities in risk factor profiles in identified hotspots were assessed. Increasing HIV-related mortality and a subsequent decrease possibly attributable to antiretroviral therapy introduction are evident in this rural population. Distinct space-time clustering and variation (even in a small geographic area) of mortality were observed. Several known and novel risk factors were identified, and population impact was quantified. Significant differences in the risk factor profiles of the identified 'hotspots' included ethnicity; maternal, partner, and household deaths; household head demographics; migrancy; education; and poverty. A complex interaction of highly attributable multilevel factors continues to demonstrate differential space-time influences on mortality risk (especially for HIV). High-risk households and villages displayed differential risk factor profiles. This integrated approach could prove valuable to decision makers. Tailored interventions for specific child and adult high-risk mortality areas are needed, such as preventing vertical transmission, ensuring maternal survival, and improving water and sanitation infrastructure. This framework can be applied in other settings within the region.

Lifetime and 5 years risk of breast cancer and attributable risk factor according to Gail model in Iranian women

PubMed Central

Mohammadbeigi, Abolfazl; Mohammadsalehi, Narges; Valizadeh, Razieh; Momtaheni, Zeinab; Mokhtari, Mohsen; Ansari, Hossein

2015-01-01

Introduction: Breast cancer is the most commonly diagnosed cancers in women worldwide and in Iran. It is expected to account for 29% of all new cancers in women at 2015. This study aimed to assess the 5 years and lifetime risk of breast cancer according to Gail model, and to evaluate the effect of other additional risk factors on the Gail risk. Materials and Methods: A cross sectional study conducted on 296 women aged more than 34-year-old in Qom, Center of Iran. Breast Cancer Risk Assessment Tool calculated the Gail risk for each subject. Data were analyzed by paired t-test, independent t-test, and analysis of variance in bivariate approach to evaluate the effect of each factor on Gail risk. Multiple linear regression models with stepwise method were used to predict the effect of each variable on the Gail risk. Results: The mean age of the participants was 47.8 ± 8.8-year-old and 47% have Fars ethnicity. The 5 years and lifetime risk was 0.37 ± 0.18 and 4.48 ± 0.925%, respectively. It was lower than the average risk in same race and age women (P < 0.001). Being single, positive family history of breast cancer, positive history of biopsy, and radiotherapy as well as using nonhormonal contraceptives were related to higher lifetime risk (P < 0.05). Moreover, a significant direct correlation observed between lifetime risk and body mass index, age of first live birth, and menarche age. While an inversely correlation observed between lifetimes risk of breast cancer and total month of breast feeding duration and age. Conclusion: Based on our results, the 5 years and lifetime risk of breast cancer according to Gail model was lower than the same race and age. Moreover, by comparison with national epidemiologic indicators about morbidity and mortality of breast cancer, it seems that the Gail model overestimate the risk of breast cancer in Iranian women. PMID:26229355

Malaysian adolescent students' needs for enhancing thinking skills, counteracting risk factors and demonstrating academic resilience

PubMed Central

Kuldas, Seffetullah; Hashim, Shahabuddin; Ismail, Hairul Nizam

2015-01-01

The adolescence period of life comes along with changes and challenges in terms of physical and cognitive development. In this hectic period, many adolescents may suffer more from various risk factors such as low socioeconomic status, substance abuse, sexual abuse and teenage pregnancy. Findings indicate that such disadvantaged backgrounds of Malaysian adolescent students lead to failure or underachievement in their academic performance. This narrative review scrutinises how some of these students are able to demonstrate academic resilience, which is satisfactory performance in cognitive or academic tasks in spite of their disadvantaged backgrounds. The review stresses the need for developing a caregiving relationship model for at-risk adolescent students in Malaysia. Such a model would allow educators to meet the students' needs for enhancing thinking skills, counteracting risk factors and demonstrating academic resilience. PMID:25663734

Path analysis of risk factors leading to premature birth.

PubMed

Fields, S J; Livshits, G; Sirotta, L; Merlob, P

1996-01-01

The present study tested whether various sociodemographic, anthropometric, behavioral, and medical/physiological factors act in a direct or indirect manner on the risk of prematurity using path analysis on a sample of Israeli births. The path model shows that medical complications, primarily toxemia, chorioammionitis, and a previous low birth weight delivery directly and significantly act on the risk of prematurity as do low maternal pregnancy weight gain and ethnicity. Other medical complications, including chronic hypertension, preclampsia, and placental abruption, although significantly correlated with prematurity, act indirectly on prematurity through toxemia. The model further shows that the commonly accepted sociodemographic, anthropometric, and behavioral risk factors act by modifying the development of medical complications that lead to prematurity as opposed to having a direct effect on premature delivery. © 1996 Wiley-Liss, Inc. Copyright © 1996 Wiley-Liss, Inc.

Bullying involvement and adolescent substance use: A multilevel investigation of individual and neighbourhood risk factors.

PubMed

Lambe, Laura J; Craig, Wendy M

2017-09-01

Youth involved with school bullying are vulnerable to many negative outcomes, including substance use. Research has yet to examine how this vulnerability operates in the context of other individual and neighbourhood differences. The current study aimed to fill this gap by using multilevel modeling to investigate both the individual and neighbourhood risk factors associated with frequent drunkenness and frequent cannabis use among adolescents. Data from the 2010 Canadian Health Behaviours in School-Aged Children (HBSC) survey were analyzed. Participants consisted of 8971 students from 173 neighbourhoods across Canada. Multilevel modeling was used to examine both individual (age, gender, bullying, victimization, peer deviancy, negative affect) and neighbourhood (socioeconomic status, crime, physical neighbourhood disorder, residential instability) risk factors. We tested whether the links between bullying involvement and frequent substance use were mediated by other risk factors. Both individual and neighbourhood risk factors were associated with an increased likelihood of frequent substance use. Specifically, bullying served as a unique risk factor for frequent substance use over and above more traditional risk factors. A cross-level interaction was observed between residential instability and peer deviancy, such that the link between peer deviancy and frequent drunkenness was stronger in more residentially-unstable neighbourhoods. Peer deviancy partially mediated the link between bullying and both types of frequent substance use, whereas both peer deviancy and negative affect mediated the link between victimization and both types of frequent substance use. Youth who bully others are vulnerable to frequent substance use across peer and neighbourhood contexts. Copyright © 2017 Elsevier B.V. All rights reserved.

Race/Ethnic Differences in the Associations of the Framingham Risk Factors with Carotid IMT and Cardiovascular Events

PubMed Central

Hoefer, Imo E.; Eijkemans, Marinus J. C.; Asselbergs, Folkert W.; Anderson, Todd J.; Britton, Annie R.; Dekker, Jacqueline M.; Engström, Gunnar; Evans, Greg W.; de Graaf, Jacqueline; Grobbee, Diederick E.; Hedblad, Bo; Holewijn, Suzanne; Ikeda, Ai; Kitagawa, Kazuo; Kitamura, Akihiko; de Kleijn, Dominique P. V.; Lonn, Eva M.; Lorenz, Matthias W.; Mathiesen, Ellisiv B.; Nijpels, Giel; Okazaki, Shuhei; O’Leary, Daniel H.; Pasterkamp, Gerard; Peters, Sanne A. E.; Polak, Joseph F.; Price, Jacqueline F.; Robertson, Christine; Rembold, Christopher M.; Rosvall, Maria; Rundek, Tatjana; Salonen, Jukka T.; Sitzer, Matthias; Stehouwer, Coen D. A.; Bots, Michiel L.; den Ruijter, Hester M.

2015-01-01

Background Clinical manifestations and outcomes of atherosclerotic disease differ between ethnic groups. In addition, the prevalence of risk factors is substantially different. Primary prevention programs are based on data derived from almost exclusively White people. We investigated how race/ethnic differences modify the associations of established risk factors with atherosclerosis and cardiovascular events. Methods We used data from an ongoing individual participant meta-analysis involving 17 population-based cohorts worldwide. We selected 60,211 participants without cardiovascular disease at baseline with available data on ethnicity (White, Black, Asian or Hispanic). We generated a multivariable linear regression model containing risk factors and ethnicity predicting mean common carotid intima-media thickness (CIMT) and a multivariable Cox regression model predicting myocardial infarction or stroke. For each risk factor we assessed how the association with the preclinical and clinical measures of cardiovascular atherosclerotic disease was affected by ethnicity. Results Ethnicity appeared to significantly modify the associations between risk factors and CIMT and cardiovascular events. The association between age and CIMT was weaker in Blacks and Hispanics. Systolic blood pressure associated more strongly with CIMT in Asians. HDL cholesterol and smoking associated less with CIMT in Blacks. Furthermore, the association of age and total cholesterol levels with the occurrence of cardiovascular events differed between Blacks and Whites. Conclusion The magnitude of associations between risk factors and the presence of atherosclerotic disease differs between race/ethnic groups. These subtle, yet significant differences provide insight in the etiology of cardiovascular disease among race/ethnic groups. These insights aid the race/ethnic-specific implementation of primary prevention. PMID:26134404

Race/Ethnic Differences in the Associations of the Framingham Risk Factors with Carotid IMT and Cardiovascular Events.

PubMed

Gijsberts, Crystel M; Groenewegen, Karlijn A; Hoefer, Imo E; Eijkemans, Marinus J C; Asselbergs, Folkert W; Anderson, Todd J; Britton, Annie R; Dekker, Jacqueline M; Engström, Gunnar; Evans, Greg W; de Graaf, Jacqueline; Grobbee, Diederick E; Hedblad, Bo; Holewijn, Suzanne; Ikeda, Ai; Kitagawa, Kazuo; Kitamura, Akihiko; de Kleijn, Dominique P V; Lonn, Eva M; Lorenz, Matthias W; Mathiesen, Ellisiv B; Nijpels, Giel; Okazaki, Shuhei; O'Leary, Daniel H; Pasterkamp, Gerard; Peters, Sanne A E; Polak, Joseph F; Price, Jacqueline F; Robertson, Christine; Rembold, Christopher M; Rosvall, Maria; Rundek, Tatjana; Salonen, Jukka T; Sitzer, Matthias; Stehouwer, Coen D A; Bots, Michiel L; den Ruijter, Hester M

2015-01-01

Clinical manifestations and outcomes of atherosclerotic disease differ between ethnic groups. In addition, the prevalence of risk factors is substantially different. Primary prevention programs are based on data derived from almost exclusively White people. We investigated how race/ethnic differences modify the associations of established risk factors with atherosclerosis and cardiovascular events. We used data from an ongoing individual participant meta-analysis involving 17 population-based cohorts worldwide. We selected 60,211 participants without cardiovascular disease at baseline with available data on ethnicity (White, Black, Asian or Hispanic). We generated a multivariable linear regression model containing risk factors and ethnicity predicting mean common carotid intima-media thickness (CIMT) and a multivariable Cox regression model predicting myocardial infarction or stroke. For each risk factor we assessed how the association with the preclinical and clinical measures of cardiovascular atherosclerotic disease was affected by ethnicity. Ethnicity appeared to significantly modify the associations between risk factors and CIMT and cardiovascular events. The association between age and CIMT was weaker in Blacks and Hispanics. Systolic blood pressure associated more strongly with CIMT in Asians. HDL cholesterol and smoking associated less with CIMT in Blacks. Furthermore, the association of age and total cholesterol levels with the occurrence of cardiovascular events differed between Blacks and Whites. The magnitude of associations between risk factors and the presence of atherosclerotic disease differs between race/ethnic groups. These subtle, yet significant differences provide insight in the etiology of cardiovascular disease among race/ethnic groups. These insights aid the race/ethnic-specific implementation of primary prevention.

Dating violence among college students: the risk and protective factors.

PubMed

Kaukinen, Catherine

2014-10-01

The research review synthesizes the knowledge base on risk and protective factors for dating violence while highlighting its relevance to violence against college women. In particular, the review highlights the personal, family, relationship, and behavioral factors that heighten the risk of dating violence victimization and perpetration while also noting the methodological limitations of the current body of empirical research and identifying directions for future academic work. Researchers have identified the correlation between risky health and behavioral factors and dating violence, most often modeling these as part of the etiology of dating violence among college students. Less often have scholars explored these as co-occurring risk factors. This approach to dating violence may be used to develop meaningful and impactful interventions to reduce the incidence and prevalence of college dating violence while also addressing the other health risk behaviors that impact academic success and place students' well-being at risk. © The Author(s) 2014.

Population-Attributable Risk Proportion of Clinical Risk Factors for Breast Cancer.

PubMed

Engmann, Natalie J; Golmakani, Marzieh K; Miglioretti, Diana L; Sprague, Brian L; Kerlikowske, Karla

2017-09-01

Many established breast cancer risk factors are used in clinical risk prediction models, although the proportion of breast cancers explained by these factors is unknown. To determine the population-attributable risk proportion (PARP) for breast cancer associated with clinical breast cancer risk factors among premenopausal and postmenopausal women. Case-control study with 1:10 matching on age, year of risk factor assessment, and Breast Cancer Surveillance Consortium (BCSC) registry. Risk factor data were collected prospectively from January 1, 1996, through October 31, 2012, from BCSC community-based breast imaging facilities. A total of 18 437 women with invasive breast cancer or ductal carcinoma in situ were enrolled as cases and matched to 184 309 women without breast cancer, with a total of 58 146 premenopausal and 144 600 postmenopausal women enrolled in the study. Breast Imaging Reporting and Data System (BI-RADS) breast density (heterogeneously or extremely dense vs scattered fibroglandular densities), first-degree family history of breast cancer, body mass index (>25 vs 18.5-25), history of benign breast biopsy, and nulliparity or age at first birth (≥30 years vs <30 years). Population-attributable risk proportion of breast cancer. Of the 18 437 women with breast cancer, the mean (SD) age was 46.3 (3.7) years among premenopausal women and 61.7 (7.2) years among the postmenopausal women. Overall, 4747 (89.8%) premenopausal and 12 502 (95.1%) postmenopausal women with breast cancer had at least 1 breast cancer risk factor. The combined PARP of all risk factors was 52.7% (95% CI, 49.1%-56.3%) among premenopausal women and 54.7% (95% CI, 46.5%-54.7%) among postmenopausal women. Breast density was the most prevalent risk factor for both premenopausal and postmenopausal women and had the largest effect on the PARP; 39.3% (95% CI, 36.6%-42.0%) of premenopausal and 26.2% (95% CI, 24.4%-28.0%) of postmenopausal breast cancers could potentially be averted if all women with heterogeneously or extremely dense breasts shifted to scattered fibroglandular breast density. Among postmenopausal women, 22.8% (95% CI, 18.3%-27.3%) of breast cancers could potentially be averted if all overweight and obese women attained a body mass index of less than 25. Most women with breast cancer have at least 1 breast cancer risk factor routinely documented at the time of mammography, and more than half of premenopausal and postmenopausal breast cancers are explained by these factors. These easily assessed risk factors should be incorporated into risk prediction models to stratify breast cancer risk and promote risk-based screening and targeted prevention efforts.

The associations between a polygenic score, reproductive and menstrual risk factors and breast cancer risk.

PubMed

Warren Andersen, Shaneda; Trentham-Dietz, Amy; Gangnon, Ronald E; Hampton, John M; Figueroa, Jonine D; Skinner, Halcyon G; Engelman, Corinne D; Klein, Barbara E; Titus, Linda J; Newcomb, Polly A

2013-07-01

We evaluated whether 13 single nucleotide polymorphisms (SNPs) identified in genome-wide association studies interact with one another and with reproductive and menstrual risk factors in association with breast cancer risk. DNA samples and information on parity, breastfeeding, age at menarche, age at first birth, and age at menopause were collected through structured interviews from 1,484 breast cancer cases and 1,307 controls who participated in a population-based case-control study conducted in three US states. A polygenic score was created as the sum of risk allele copies multiplied by the corresponding log odds estimate. Logistic regression was used to test the associations between SNPs, the score, reproductive and menstrual factors, and breast cancer risk. Nonlinearity of the score was assessed by the inclusion of a quadratic term for polygenic score. Interactions between the aforementioned variables were tested by including a cross-product term in models. We confirmed associations between rs13387042 (2q35), rs4973768 (SLC4A7), rs10941679 (5p12), rs2981582 (FGFR2), rs3817198 (LSP1), rs3803662 (TOX3), and rs6504950 (STXBP4) with breast cancer. Women in the score's highest quintile had 2.2-fold increased risk when compared to women in the lowest quintile (95 % confidence interval: 1.67-2.88). The quadratic polygenic score term was not significant in the model (p = 0.85), suggesting that the established breast cancer loci are not associated with increased risk more than the sum of risk alleles. Modifications of menstrual and reproductive risk factors associations with breast cancer risk by polygenic score were not observed. Our results suggest that the interactions between breast cancer susceptibility loci and reproductive factors are not strong contributors to breast cancer risk.

Modified social ecological model: a tool to guide the assessment of the risks and risk contexts of HIV epidemics.

PubMed

Baral, Stefan; Logie, Carmen H; Grosso, Ashley; Wirtz, Andrea L; Beyrer, Chris

2013-05-17

Social and structural factors are now well accepted as determinants of HIV vulnerabilities. These factors are representative of social, economic, organizational and political inequities. Associated with an improved understanding of multiple levels of HIV risk has been the recognition of the need to implement multi-level HIV prevention strategies. Prevention sciences research and programming aiming to decrease HIV incidence requires epidemiologic studies to collect data on multiple levels of risk to inform combination HIV prevention packages. Proximal individual-level risks, such as sharing injection devices and unprotected penile-vaginal or penile-anal sex, are necessary in mediating HIV acquisition and transmission. However, higher order social and structural-level risks can facilitate or reduce HIV transmission on population levels. Data characterizing these risks is often far more actionable than characterizing individual-level risks. We propose a modified social ecological model (MSEM) to help visualize multi-level domains of HIV infection risks and guide the development of epidemiologic HIV studies. Such a model may inform research in epidemiology and prevention sciences, particularly for key populations including men who have sex with men (MSM), people who inject drugs (PID), and sex workers. The MSEM builds on existing frameworks by examining multi-level risk contexts for HIV infection and situating individual HIV infection risks within wider network, community, and public policy contexts as well as epidemic stage. The utility of the MSEM is demonstrated with case studies of HIV risk among PID and MSM. The MSEM is a flexible model for guiding epidemiologic studies among key populations at risk for HIV in diverse sociocultural contexts. Successful HIV prevention strategies for key populations require effective integration of evidence-based biomedical, behavioral, and structural interventions. While the focus of epidemiologic studies has traditionally been on describing individual-level risk factors, the future necessitates comprehensive epidemiologic data characterizing multiple levels of HIV risk.

Prediction of presence of kidney disease in a general patient population undergoing intravenous iodinated contrast enhanced computed tomography.

PubMed

Moos, Shira I; Stoker, Jaap; Nagan, Gajenthiran; de Weijert, Roderick S; van Vemde, David N H; Bipat, Shandra

2014-06-01

To assess which risk factors can be used to reduce superfluous estimated glomerular filtration rate (eGFR) measurements before intravenous contrast medium administration. In consecutive patients, all decreased eGFR risk factors were assessed: diabetes mellitus (DM), history of urologic/nephrologic disease (HUND), nephrotoxic medication, cardiovascular disease, hypertension, age > 60 years, anaemia, malignancy and multiple myeloma/M. Waldenström. We studied four models: (1) all risk factors, (2) DM, HUND, hypertension, age > 60 years; (3) DM, HUND, cardiovascular disease, hypertension; (4) DM, HUND, age > 75 years and congestive heart failure. For each model, association with eGFR < 60 ml/min/1.73 m(2) or eGFR < 45 ml/min/1.73 m(2) was studied. A total of 998 patients, mean age 59.94 years were included; 112 with eGFR < 60 ml/min/1.73 m(2) and 30 with eGFR < 45 ml/min/1.73 m(2). Model 1 detected 816 patients: 108 with eGFR < 60 ml/min/1.73 m(2) and all 30 with eGFR < 45 ml/min/1.73 m(2). Model 2 detected 745 patients: 108 with eGFR < 60 ml/min/1.73 m(2) and all 30 with eGFR < 45 ml/min/1.73 m(2). Model 3 detected 622 patients: 100 with eGFR < 60 ml/min/1.73 m(2) and all 30 with eGFR < 45 ml/min/1.73 m(2). Model 4 detected 440 patients: 86 with eGFR < 60 ml/min/1.73 m(2) and all 30 with eGFR < 45 ml/min/1.73 m(2). Associations were significant (p < 0.001). Model 4 is most effective, resulting in the lowest proportion of superfluous eGFR measurements while detecting all patients with eGFR < 45 ml/min/1.73 m(2) and most with eGFR < 60 ml/min/1.73 m(2). A major risk factor for contrast-induced nephropathy (CIN) is kidney disease. Risk factors are used to identify patients with pre-existent kidney disease. Evidence for risk factors to identify patients with kidney disease is limited. The number of eGFR measurements to detect kidney disease can be reduced.

A microRNA-based prediction model for lymph node metastasis in hepatocellular carcinoma.

PubMed

Zhang, Li; Xiang, Zuo-Lin; Zeng, Zhao-Chong; Fan, Jia; Tang, Zhao-You; Zhao, Xiao-Mei

2016-01-19

We developed an efficient microRNA (miRNA) model that could predict the risk of lymph node metastasis (LNM) in hepatocellular carcinoma (HCC). We first evaluated a training cohort of 192 HCC patients after hepatectomy and found five LNM associated predictive factors: vascular invasion, Barcelona Clinic Liver Cancer stage, miR-145, miR-31, and miR-92a. The five statistically independent factors were used to develop a predictive model. The predictive value of the miRNA-based model was confirmed in a validation cohort of 209 consecutive HCC patients. The prediction model was scored for LNM risk from 0 to 8. The cutoff value 4 was used to distinguish high-risk and low-risk groups. The model sensitivity and specificity was 69.6 and 80.2%, respectively, during 5 years in the validation cohort. And the area under the curve (AUC) for the miRNA-based prognostic model was 0.860. The 5-year positive and negative predictive values of the model in the validation cohort were 30.3 and 95.5%, respectively. Cox regression analysis revealed that the LNM hazard ratio of the high-risk versus low-risk groups was 11.751 (95% CI, 5.110-27.021; P < 0.001) in the validation cohort. In conclusion, the miRNA-based model is reliable and accurate for the early prediction of LNM in patients with HCC.

Security risk assessment: applying the concepts of fuzzy logic.

PubMed

Bajpai, Shailendra; Sachdeva, Anish; Gupta, J P

2010-01-15

Chemical process industries (CPI) handling hazardous chemicals in bulk can be attractive targets for deliberate adversarial actions by terrorists, criminals and disgruntled employees. It is therefore imperative to have comprehensive security risk management programme including effective security risk assessment techniques. In an earlier work, it has been shown that security risk assessment can be done by conducting threat and vulnerability analysis or by developing Security Risk Factor Table (SRFT). HAZOP type vulnerability assessment sheets can be developed that are scenario based. In SRFT model, important security risk bearing factors such as location, ownership, visibility, inventory, etc., have been used. In this paper, the earlier developed SRFT model has been modified using the concepts of fuzzy logic. In the modified SRFT model, two linguistic fuzzy scales (three-point and four-point) are devised based on trapezoidal fuzzy numbers. Human subjectivity of different experts associated with previous SRFT model is tackled by mapping their scores to the newly devised fuzzy scale. Finally, the fuzzy score thus obtained is defuzzyfied to get the results. A test case of a refinery is used to explain the method and compared with the earlier work.

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

PubMed Central

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-01-01

Background: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6–12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. Results: The prevalence of anemia was 12.60% with a range of 3.47%–40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities. PMID:27174328

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China.

PubMed

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-05-20

In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6-12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. The prevalence of anemia was 12.60% with a range of 3.47%-40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities.

Using a syndemics theory approach to study HIV risk taking in a population of men who use the internet to find partners for unprotected sex.

PubMed

Klein, Hugh

2011-11-01

This study examines the value of using syndemics theory as a model for understanding HIV risk taking in a population of men who are at great risk for acquiring and/or transmitting HIV. The principal aim is to provide an empirical test of the applicability of the theory to sexual risk behaviors in this particular research population. The study was based on a national random sample of 332 men who have sex with men, or MSM, who use the Internet to seek men with whom they can engage in unprotected sex. Data collection was conducted via telephone interviews between January 2008 and May 2009. As hypothesized in the syndemics theory model, attitudes toward condom use were central to understanding men's involvement in risky sex. As hypothesized, these attitudes depended on various demographic, psychological/psychosocial functioning, and sex-related preference measures. Also as hypothesized, psychological and psychosocial functioning were found to be very important to the overall model, and as expected, these factors were shaped greatly by factors such as demographic characteristics and childhood maltreatment experiences. The structural equation assessing the fit of the overall model indicated solid support for the syndemics theory approach. Overall, syndemics theory seems to apply fairly well to understanding the complexity of the factors that underlie men's risk-taking practices. The complicated interplay among factors such as attitudes toward condom use, childhood maltreatment experiences, psychological and psychosocial functioning, and substance use and abuse-all of which are central to a syndemics theory approach to studying risk-was demonstrated.

A Test of an Integrative Model Using Social Factors and Personality Traits: Prediction on the Delinquency of South Korean Youth.

PubMed

Yun, Minwoo; Kim, Eunyoung; Park, Woong-Sub

2017-08-01

To more fully comprehend juvenile delinquency, it is necessary to take an integrative approach, with consideration of both personality traits of social risk factors. Many scholars argue the necessity and strength of integrative approach on the ground that juvenile delinquency is an outcome of interplay of individual and social factors. The present study examines the general applicability of an integrative model of personal traits and social risk factors to youth delinquency in the South Korean context. The empirical results show that the delinquency predictors in the current South Korean sample are closely aligned to Loeber and Farrington's theoretical propositions and that found in Western nations. Perhaps this is because South Korea has undergone rapid Westernization for the last decades. Because the correlates in this sample and Western theoretical propositions and studies overlap, an integrative model of personality trait and social risk factors is indeed generally applicable to South Korea. This finding also depicts the extent of Westernization in the South Korean society at least among adolescents. Limitations of the present study and directions for the future study are discussed.

Applicability of the Social Development Model to Urban Ethnic Minority Youth: Examining the Relationship between External Constraints, Family Socialization, and Problem Behaviors

PubMed Central

Choi, Yoonsun; Harachi, Tracy W.; Gillmore, Mary Rogers; Catalano, Richard F.

2011-01-01

The development of preventive interventions targeting adolescent problem behaviors requires a thorough understanding of risk and protective factors for such behaviors. However, few studies examine whether different cultural and ethnic groups share these factors. This study is an attempt to fill a gap in research by examining similarities and differences in risk factors across racial and ethnic groups. The social development model has shown promise in organizing predictors of problem behaviors. This article investigates whether a version of that model can be generalized to youth in different racial and ethnic groups (N = 2,055, age range from 11 to 15), including African American (n = 478), Asian Pacific Islander (API) American (n = 491), multiracial (n = 442), and European American (n = 644) youth. The results demonstrate that common risk factors can be applied to adolescents, regardless of their race and ethnicity. The findings also demonstrate that there are racial and ethnic differences in the magnitudes of relationships among factors that affect problem behaviors. Further study is warranted to develop a better understanding of these differential magnitudes. PMID:21625351

Left ventricular mass, blood pressure, and lowered cognitive performance in the Framingham offspring.

PubMed

Elias, Merrill F; Sullivan, Lisa M; Elias, Penelope K; D'Agostino, Ralph B; Wolf, Philip A; Seshadri, Sudha; Au, Rhoda; Benjamin, Emelia J; Vasan, Ramachandran S

2007-03-01

The purpose of this study was to determine whether echocardiographic left ventricular mass is related to cognitive performance beyond casual blood pressure adjusting for the influence of other vascular risk factors. We used multivariable regression analyses to relate left ventricular mass assessed at a routine examination (1995-1998) to measures of cognitive ability obtained routinely (1998-2001) in 1673 Framingham Offspring Study participants (56% women; mean age: 57 years) free from stroke, transient ischemic attack, and dementia. We adjusted for the following covariates hierarchically: (1) age, education, sex, body weight, height, interval between left ventricular mass measurement and neuropsychological testing (basic model); (2) basic model+blood pressure+treatment for hypertension; and (3) basic model+blood pressure+treatment for hypertension+vascular risk factors and prevalent cardiovascular disease. For the basic model, left ventricular mass was inversely associated with abstract reasoning (similarities), visual-spatial memory and organization, and verbal memory. For the basic model+blood pressure+treatment for hypertension, left ventricular mass was inversely associated with similarities and visual-spatial memory and organization. For the basic+blood pressure+treatment for hypertension+risk factors+cardiovascular disease model, no significant associations were observed. Echocardiographic left ventricular mass is associated with cognitive performance beyond casual and time-averaged systolic blood pressure, but this association is attenuated and rendered nonsignificant with additional adjustment for cardiovascular risk factors and cardiovascular disease, thus suggesting that these variables play an important role in mediating the association between left ventricular mass and cognition.

Bovine respiratory syncytial virus and bovine coronavirus antibodies in bulk tank milk - risk factors and spatial analysis.

PubMed

Toftaker, Ingrid; Sanchez, Javier; Stokstad, Maria; Nødtvedt, Ane

2016-10-01

Bovine respiratory syncytial virus (BRSV) and bovine coronavirus (BCoV) are considered widespread among cattle in Norway and worldwide. This cross-sectional study was conducted based on antibody-ELISA of bulk tank milk (BTM) from 1347 herds in two neighboring counties in western Norway. The study aims were to determine the seroprevalence at herd level, to evaluate risk factors for BRSV and BCoV seropositivity, and to assess how these factors were associated with the spatial distribution of positive herds. The overall prevalence of BRSV and BCoV positive herds in the region was 46.2% and 72.2%, respectively. Isopleth maps of the prevalence risk distribution showed large differences in prevalence risk across the study area, with the highest prevalence in the northern region. Common risk factors of importance for both viruses were herd size, geographic location, and proximity to neighbors. Seropositivity for one virus was associated with increased odds of seropositivity for the other virus. Purchase of livestock was an additional risk factor for BCoV seropositivity, included in the model as in-degree, which was defined as the number of incoming movements from individual herds, through animal purchase, over a period of five years. Local dependence and the contribution of risk factors to this effect were assessed using the residuals from two logistic regression models for each virus. One model contained only the x- and y- coordinates as predictors, the other had all significant predictors included. Spatial clusters of high values of residuals were detected using the normal model of the spatial scan statistic and visualized on maps. Adjusting for the risk factors in the final models had different impact on the spatial clusters for the two viruses: For BRSV the number of clusters was reduced from six to four, for BCoV the number of clusters remained the same, however the log-likelihood ratios changed notably. This indicates that geographical differences in proximity to neighbors, herd size and animal movements explain some of the spatial clusters of BRSV- and BCoV seropositivity, but far from all. The remaining local dependence in the residuals show that the antibody status of one herd is influenced by the antibody status of its neighbors, indicating the importance of indirect transmission and that increased biosecurity routines might be an important preventive strategy. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Assessing the Risk of Crew Injury Due to Dynamic Loads During Spaceflight

NASA Technical Reports Server (NTRS)

Somers, J. T.; Gernhardt, M.; Newby, N.

2014-01-01

Spaceflight requires tremendous amounts of energy to achieve Earth orbit and to attain escape velocity for interplanetary missions. Although the majority of the energy is managed in such a way as to limit the accelerations on the crew, several mission phases may result in crew exposure to dynamic loads. In the automotive industry, risk of serious injury can be tolerated because the probability of a crash is remote each time a person enters a vehicle, resulting in a low total risk of injury. For spaceflight, the level of acceptable injury risk must be lower to achieve a low total risk of injury because the dynamic loads are expected on each flight. To mitigate the risk of injury due to dynamic loads, the NASA Human Research Program has developed a research plan to inform the knowledge gaps and develop relevant tools for assessing injury risk. The risk of injury due to dynamic loads can be further subdivided into extrinsic and intrinsic risk factors. Extrinsic risk factors include the vehicle dynamic profile, seat and restraint design, and spacesuit design. Human tolerance to loads varies considerably depending on the direction, amplitude, and rise-time of acceleration therefore the orientation of the body to the dynamic vector is critical to determining crew risk of injury. Although a particular vehicle dynamic profile may be safe for a particular design, the seat, restraint, and suit designs can affect the risk of injury due to localized effects. In addition, characteristics intrinsic to the crewmember may also contribute to the risk of injury, such as crewmember sex, age, anthropometry, and deconditioning due to spaceflight, and each astronaut may have a different risk profile because of these factors. The purpose of the research plan is to address any knowledge gaps in the risk factors to mitigate injury risk. Methods for assessing injury risk have been well documented in other analogous industries and include human volunteer testing, human exposure to dynamic environments, post-mortem human subject (PMHS) testing, animal testing, anthropomorphic test devices (ATD), dynamic models of the human, numerical models of ATDs, and numerical models of the human. Each has inherent strengths and limitations. For example, human volunteer testing is advantageous because a population can be selected that is similar to the astronaut corps; however, because of the inherent ethical limitations, only sub-injurious conditions can be tested. PMHSs can be tested in a variety of conditions including injurious levels, but the responses are not completely analogous to living human subjects. In addition, it is exceedingly difficult to select a PMHS population that is similar to the astronaut corps. ATDs are currently widely used in the automotive industry and military because they are highly repeatable and durable. Unfortunately, because they are mechanical models of the human body, the biofidelity of the responses are limited to dynamic conditions used to validate the ATD. Numerical models of the ATD, in addition to the strengths and limitations for ATDs, are easy to use for a variety of designs before a design is fabricated, but also have additional limitations for ATDs, are easy to use for a variety of designs before a design is fabricated, but also have additional uncertainty. Dynamic models are simple and easy to use, but do not account for localized effects of the seat and suit. Finally, numerical models of the human have the potential to have the most advantages; however, the current models are not validated for the conditions expected during spaceflight. To properly assess spaceflight conditions with numerical human models, human data would be needed to optimize the model responses for those conditions. Using the appropriate assessment method with the knowledge gained for each risk factor, an appropriate approach for mitigating the risk of injury due to dynamic loads can be developed ensuring crew safety in future NASA vehicles.

Design of psychosocial factors questionnaires: a systematic measurement approach

PubMed Central

Vargas, Angélica; Felknor, Sarah A

2012-01-01

Background Evaluation of psychosocial factors requires instruments that measure dynamic complexities. This study explains the design of a set of questionnaires to evaluate work and non-work psychosocial risk factors for stress-related illnesses. Methods The measurement model was based on a review of literature. Content validity was performed by experts and cognitive interviews. Pilot testing was carried out with a convenience sample of 132 workers. Cronbach’s alpha evaluated internal consistency and concurrent validity was estimated by Spearman correlation coefficients. Results Three questionnaires were constructed to evaluate exposure to work and non-work risk factors. Content validity improved the questionnaires coherence with the measurement model. Internal consistency was adequate (α=0.85–0.95). Concurrent validity resulted in moderate correlations of psychosocial factors with stress symptoms. Conclusions Questionnaires´ content reflected a wide spectrum of psychosocial factors sources. Cognitive interviews improved understanding of questions and dimensions. The structure of the measurement model was confirmed. PMID:22628068

Risk factors for low receptive vocabulary abilities in the preschool and early school years in the longitudinal study of Australian children.

PubMed

Christensen, Daniel; Zubrick, Stephen R; Lawrence, David; Mitrou, Francis; Taylor, Catherine L

2014-01-01

Receptive vocabulary development is a component of the human language system that emerges in the first year of life and is characterised by onward expansion throughout life. Beginning in infancy, children's receptive vocabulary knowledge builds the foundation for oral language and reading skills. The foundations for success at school are built early, hence the public health policy focus on reducing developmental inequalities before children start formal school. The underlying assumption is that children's development is stable, and therefore predictable, over time. This study investigated this assumption in relation to children's receptive vocabulary ability. We investigated the extent to which low receptive vocabulary ability at 4 years was associated with low receptive vocabulary ability at 8 years, and the predictive utility of a multivariate model that included child, maternal and family risk factors measured at 4 years. The study sample comprised 3,847 children from the first nationally representative Longitudinal Study of Australian Children (LSAC). Multivariate logistic regression was used to investigate risks for low receptive vocabulary ability from 4-8 years and sensitivity-specificity analysis was used to examine the predictive utility of the multivariate model. In the multivariate model, substantial risk factors for receptive vocabulary delay from 4-8 years, in order of descending magnitude, were low receptive vocabulary ability at 4 years, low maternal education, and low school readiness. Moderate risk factors, in order of descending magnitude, were low maternal parenting consistency, socio-economic area disadvantage, low temperamental persistence, and NESB status. The following risk factors were not significant: One or more siblings, low family income, not reading to the child, high maternal work hours, and Aboriginal or Torres Strait Islander ethnicity. The results of the sensitivity-specificity analysis showed that a well-fitted multivariate model featuring risks of substantive magnitude does not do particularly well in predicting low receptive vocabulary ability from 4-8 years.

The contributions of breast density and common genetic variation to breast cancer risk.

PubMed

Vachon, Celine M; Pankratz, V Shane; Scott, Christopher G; Haeberle, Lothar; Ziv, Elad; Jensen, Matthew R; Brandt, Kathleen R; Whaley, Dana H; Olson, Janet E; Heusinger, Katharina; Hack, Carolin C; Jud, Sebastian M; Beckmann, Matthias W; Schulz-Wendtland, Ruediger; Tice, Jeffrey A; Norman, Aaron D; Cunningham, Julie M; Purrington, Kristen S; Easton, Douglas F; Sellers, Thomas A; Kerlikowske, Karla; Fasching, Peter A; Couch, Fergus J

2015-05-01

We evaluated whether a 76-locus polygenic risk score (PRS) and Breast Imaging Reporting and Data System (BI-RADS) breast density were independent risk factors within three studies (1643 case patients, 2397 control patients) using logistic regression models. We incorporated the PRS odds ratio (OR) into the Breast Cancer Surveillance Consortium (BCSC) risk-prediction model while accounting for its attributable risk and compared five-year absolute risk predictions between models using area under the curve (AUC) statistics. All statistical tests were two-sided. BI-RADS density and PRS were independent risk factors across all three studies (P interaction = .23). Relative to those with scattered fibroglandular densities and average PRS (2(nd) quartile), women with extreme density and highest quartile PRS had 2.7-fold (95% confidence interval [CI] = 1.74 to 4.12) increased risk, while those with low density and PRS had reduced risk (OR = 0.30, 95% CI = 0.18 to 0.51). PRS added independent information (P < .001) to the BCSC model and improved discriminatory accuracy from AUC = 0.66 to AUC = 0.69. Although the BCSC-PRS model was well calibrated in case-control data, independent cohort data are needed to test calibration in the general population. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Predicting the Risk of Breakthrough Urinary Tract Infections: Primary Vesicoureteral Reflux.

PubMed

Hidas, Guy; Billimek, John; Nam, Alexander; Soltani, Tandis; Kelly, Maryellen S; Selby, Blake; Dorgalli, Crystal; Wehbi, Elias; McAleer, Irene; McLorie, Gordon; Greenfield, Sheldon; Kaplan, Sherrie H; Khoury, Antoine E

2015-11-01

We constructed a risk prediction instrument stratifying patients with primary vesicoureteral reflux into groups according to their 2-year probability of breakthrough urinary tract infection. Demographic and clinical information was retrospectively collected in children diagnosed with primary vesicoureteral reflux and followed for 2 years. Bivariate and binary logistic regression analyses were performed to identify factors associated with breakthrough urinary tract infection. The final regression model was used to compute an estimation of the 2-year probability of breakthrough urinary tract infection for each subject. Accuracy of the binary classifier for breakthrough urinary tract infection was evaluated using receiver operator curve analysis. Three distinct risk groups were identified. The model was then validated in a prospective cohort. A total of 252 bivariate analyses showed that high grade (IV or V) vesicoureteral reflux (OR 9.4, 95% CI 3.8-23.5, p <0.001), presentation after urinary tract infection (OR 5.3, 95% CI 1.1-24.7, p = 0.034) and female gender (OR 2.6, 95% CI 0.097-7.11, p <0.054) were important risk factors for breakthrough urinary tract infection. Subgroup analysis revealed bladder and bowel dysfunction was a significant risk factor more pronounced in low grade (I to III) vesicoureteral reflux (OR 2.8, p = 0.018). The estimation model was applied for prospective validation, which demonstrated predicted vs actual 2-year breakthrough urinary tract infection rates of 19% vs 21%. Stratifying the patients into 3 risk groups based on parameters in the risk model showed 2-year risk for breakthrough urinary tract infection was 8.6%, 26.0% and 62.5% in the low, intermediate and high risk groups, respectively. This proposed risk stratification and probability model allows prediction of 2-year risk of patient breakthrough urinary tract infection to better inform parents of possible outcomes and treatment strategies. Copyright © 2015 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Models of Intergenerational and Transgenerational Transmission of Risk for Psychopathology in Mice

PubMed Central

Klengel, Torsten; Dias, Brian G; Ressler, Kerry J

2016-01-01

Trajectories toward risk or resilience in psychiatric disorders are influenced by acquired and inherited factors. More recently, evidence from rodent studies suggest that acquired risk factors can be transmitted through non-genomic, epigenetic mechanisms to subsequent generations, potentially contributing to a cycle of disease and disease risk. Here, we review examples of transmission of environmental factors across generations and illustrate the difference between behavioral transmission and epigenetic inheritance. We highlight essential definitions of intergenerational and transgenerational transmission of disease risk with corresponding examples. We then explore how these phenomena may influence our understanding of psychiatric disorders leading toward new prevention and therapeutic approaches. PMID:26283147

The impact of youth, family, peer and neighborhood risk factors on developmental trajectories of risk involvement from early through middle adolescence.

PubMed

Wang, Bo; Deveaux, Lynette; Li, Xiaoming; Marshall, Sharon; Chen, Xinguang; Stanton, Bonita

2014-04-01

Few studies have analyzed the development course beginning in pre-/early adolescence of overall engagement in health-risk behaviors and associated social risk factors that place individuals in different health-risk trajectories through mid-adolescence. The current longitudinal study identified 1276 adolescents in grade six and followed them for three years to investigate their developmental trajectories of risk behaviors and to examine the association of personal and social risk factors with each trajectory. Group-based trajectory modeling was applied to identify distinctive trajectory patterns of risk behaviors. Multivariate multinomial logistic regression analyses were performed to examine the effects of the personal and social risk factors on adolescents' trajectories. Three gender-specific behavioral trajectories were identified for males (55.3% low-risk, 37.6% moderate-risk, increasing, and 7.1% high-risk, increasing) and females (41.4% no-risk, 53.4% low-risk, increasing and 5.2% moderate to high-risk, increasing). Sensation-seeking, family, peer, and neighborhood factors at baseline predicted following the moderate-risk, increasing trajectory and the high-risk, increasing trajectory in males; these risk factors predicted following the moderate to high-risk, increasing trajectory in females. The presence of all three social risk factors (high-risk neighborhood, high-risk peers and low parental monitoring) had a dramatic impact on increased probability of being in a high-risk trajectory group. These findings highlight the developmental significance of early personal and social risk factors on subsequent risk behaviors in early to middle adolescence. Future adolescent health behavior promotion interventions might consider offering additional prevention resources to pre- and early adolescent youth who are exposed to multiple contextual risk factors (even in the absence of risk behaviors) or youth who are early-starters of delinquency and substance use behaviors in early adolescence. Copyright © 2014. Published by Elsevier Ltd.

Tumor Volume and Patient Weight as Predictors of Outcome in Children with Intermediate Risk Rhabdomyosarcoma (RMS): A Report from the Children’s Oncology Group

PubMed Central

Rodeberg, David A.; Stoner, Julie A.; Garcia-Henriquez, Norbert; Randall, R. Lor; Spunt, Sheri L.; Arndt, Carola A.; Kao, Simon; Paidas, Charles N.; Million, Lynn; Hawkins, Douglas S.

2010-01-01

Background To compare tumor volume and patient weight vs. traditional factors of tumor diameter and patient age, to determine which parameters best discriminates outcome among intermediate risk RMS patients. Methods Complete patient information for non-metastatic RMS patients enrolled in the Children’s Oncology Group (COG) intermediate risk study D9803 (1999–2005) was available for 370 patients. The Kaplan-Meier method was used to estimate survival distributions. A recursive partitioning model was used to identify prognostic factors associated with event-free survival (EFS). Cox-proportional hazards regression models were used to estimate the association between patient characteristics and the risk of failure or death. Results For all intermediate risk patients with RMS, a recursive partitioning algorithm for EFS suggests that prognostic groups should optimally be defined by tumor volume (transition point 20 cm3), weight (transition point 50 kg), and embryonal histology. Tumor volume and patient weight added significant outcome information to the standard prognostic factors including tumor diameter and age (p=0.02). The ability to resect the tumor completely was not significantly associated with the size of the patient, and patient weight did not significantly modify the association between tumor volume and EFS after adjustment for standard risk factors (p=0.2). Conclusion The factors most strongly associated with EFS were tumor volume, patient weight, and histology. Based on regression modeling, volume and weight are superior predictors of outcome compared to tumor diameter and patient age in children with intermediate risk RMS. Prognostic performance of tumor volume and patient weight should be assessed in an independent prospective study. PMID:24048802

Life course socioeconomic conditions, adulthood risk factors and cardiovascular mortality among men and women: a 17-year follow up of the GLOBE study.

PubMed

Kamphuis, Carlijn B M; Turrell, Gavin; Giskes, Katrina; Mackenbach, Johan P; van Lenthe, Frank J

2013-10-03

Our goal was to study associations between childhood socioeconomic position (SEP), adulthood SEP, adulthood risk factors and cardiovascular disease (CVD) mortality, by investigating the critical period and pathway models. The prospective GLOBE study in the Netherlands, with baseline data from 1991, was linked with cause of death register data from Statistics Netherlands in 2007. At baseline, respondents reported information on childhood SEP (i.e. occupational level of respondent's father), adulthood SEP (educational level), and adulthood risk factors (health behaviours, material circumstances, and psychosocial factors). Analyses included 4894 men and 5572 women. Data were analysed by Cox proportional hazard ratios (HR) with CVD mortality as the outcome. Childhood SEP was associated with CVD mortality among men with the lowest childhood SEP only (HR 1.32, 95% CI 1.00-1.74), and not among women. The majority of childhood SEP inequalities in CVD mortality among men (88%) were explained by material, behavioural and psychosocial risk factors in adulthood, and adulthood SEP. This was mostly due to the association of childhood SEP with adulthood SEP, and the interrelations of adulthood SEP with risk factors, and partly via the direct association of childhood SEP with adulthood risk factors, independent of adulthood SEP. This study supports the pathway model for men, but found no evidence that socioeconomic conditions in childhood are critical for CVD mortality in later life independent of adulthood conditions. Developing effective methods to reduce material and behavioural risk factors among lower socioeconomic groups should be a top priority in cardiovascular disease prevention. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.