Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Camilleri, Liberato; Cefai, Carmel

2013-01-01

Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

Predictors of Employment Outcomes for Vocational Rehabilitation Consumers With HIV/AIDS: 2002-2007

ERIC Educational Resources Information Center

Jung, Youngoh; Bellini, James L.

2011-01-01

This study examined the predictability of two employment outcomes--employment status and weekly earnings at closure--from consumer demographic, medical, and service variables for multiple groups of vocational rehabilitation (VR) consumers with HIV/AIDS retrieved from the RSA-911 data for fiscal years 2002 through 2007. A logistic regression…

Hispanic Community College Students: Acculturation, Family Support, Perceived Educational Barriers, and Vocational Planning

ERIC Educational Resources Information Center

Fiebig, Jennifer Nepper; Braid, Barbara L.; Ross, Patricia A.; Tom, Matthew A.; Prinzo, Cara

2010-01-01

A multiple logistic regression model was used to determine the associations between the role of acculturation, perception of educational barriers, need for family kin support, vocational planning, and expectations for attaining future vocational goals against the demographic variables (gender, age, being the oldest child, the first to attend…

Vitamin D levels and their associations with survival and major disease outcomes in a large cohort of patients with chronic graft-vs-host disease

PubMed Central

Katić, Mašenjka; Pirsl, Filip; Steinberg, Seth M.; Dobbin, Marnie; Curtis, Lauren M.; Pulanić, Dražen; Desnica, Lana; Titarenko, Irina; Pavletic, Steven Z.

2016-01-01

Aim To identify the factors associated with vitamin D status in patients with chronic graft-vs-host disease (cGVHD) and evaluate the association between serum vitamin D (25(OH)D) levels and cGVHD characteristics and clinical outcomes defined by the National Institutes of Health (NIH) criteria. Methods 310 cGVHD patients enrolled in the NIH cGVHD natural history study (clinicaltrials.gov: NCT00092235) were analyzed. Univariate analysis and multiple logistic regression were used to determine the associations between various parameters and 25(OH)D levels, dichotomized into categorical variables: ≤20 and >20 ng/mL, and as a continuous parameter. Multiple logistic regression was used to develop a predictive model for low vitamin D. Survival analysis and association between cGVHD outcomes and 25(OH)D as a continuous as well as categorical variable: ≤20 and >20 ng/mL; <50 and ≥50 ng/mL, and among three ordered categories: ≤20, 20-50, and ≥50 ng/mL, was performed. PMID:27374829

Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.

PubMed

Seaman, Shaun R; Hughes, Rachael A

2018-06-01

Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution when the conditional models of full-conditional specification are compatible with that joint model. We show that this asymptotic equivalence of imputation distributions does not imply that joint model multiple imputation and full-conditional specification multiple imputation will also yield asymptotically equally efficient inference about the parameters of the model of interest, nor that they will be equally robust to misspecification of the joint model. When the conditional models used by full-conditional specification multiple imputation are linear, logistic and multinomial regressions, these are compatible with a restricted general location joint model. We show that multiple imputation using the restricted general location joint model can be substantially more asymptotically efficient than full-conditional specification multiple imputation, but this typically requires very strong associations between variables. When associations are weaker, the efficiency gain is small. Moreover, full-conditional specification multiple imputation is shown to be potentially much more robust than joint model multiple imputation using the restricted general location model to mispecification of that model when there is substantial missingness in the outcome variable.

Uncertainties in Life Cycle Greenhouse Gas Emissions from Advanced Biomass Feedstock Logistics Supply Chains in Kansas

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

Cafferty, Kara G.; Searcy, Erin M.; Nguyen, Long

To meet Energy Independence and Security Act (EISA) cellulosic biofuel mandates, the United States will require an annual domestic supply of about 242 million Mg of biomass by 2022. To improve the feedstock logistics of lignocellulosic biofuels and access available biomass resources from areas with varying yields, commodity systems have been proposed and designed to deliver on-spec biomass feedstocks at preprocessing “depots”, which densify and stabilize the biomass prior to long-distance transport and delivery to centralized biorefineries. The harvesting, preprocessing, and logistics (HPL) of biomass commodity supply chains thus could introduce spatially variable environmental impacts into the biofuel life cyclemore » due to needing to harvest, move, and preprocess biomass from multiple distances that have variable spatial density. This study examines the uncertainty in greenhouse gas (GHG) emissions of corn stover logisticsHPL within a bio-ethanol supply chain in the state of Kansas, where sustainable biomass supply varies spatially. Two scenarios were evaluated each having a different number of depots of varying capacity and location within Kansas relative to a central commodity-receiving biorefinery to test GHG emissions uncertainty. Monte Carlo simulation was used to estimate the spatial uncertainty in the HPL gate-to-gate sequence. The results show that the transport of densified biomass introduces the highest variability and contribution to the carbon footprint of the logistics HPL supply chain (0.2-13 g CO 2e/MJ). Moreover, depending upon the biomass availability and its spatial density and surrounding transportation infrastructure (road and rail), logistics HPL processes can increase the variability in life cycle environmental impacts for lignocellulosic biofuels. Within Kansas, life cycle GHG emissions could range from 24 to 41 g CO 2e/MJ depending upon the location, size and number of preprocessing depots constructed. However, this range can be minimized through optimizing the siting of preprocessing depots where ample rail infrastructure exists to supply biomass commodity to a regional biorefinery supply system« less

Uncertainties in Life Cycle Greenhouse Gas Emissions from Advanced Biomass Feedstock Logistics Supply Chains in Kansas

DOE PAGES

Cafferty, Kara G.; Searcy, Erin M.; Nguyen, Long; ...

2014-11-04

To meet Energy Independence and Security Act (EISA) cellulosic biofuel mandates, the United States will require an annual domestic supply of about 242 million Mg of biomass by 2022. To improve the feedstock logistics of lignocellulosic biofuels and access available biomass resources from areas with varying yields, commodity systems have been proposed and designed to deliver on-spec biomass feedstocks at preprocessing “depots”, which densify and stabilize the biomass prior to long-distance transport and delivery to centralized biorefineries. The harvesting, preprocessing, and logistics (HPL) of biomass commodity supply chains thus could introduce spatially variable environmental impacts into the biofuel life cyclemore » due to needing to harvest, move, and preprocess biomass from multiple distances that have variable spatial density. This study examines the uncertainty in greenhouse gas (GHG) emissions of corn stover logisticsHPL within a bio-ethanol supply chain in the state of Kansas, where sustainable biomass supply varies spatially. Two scenarios were evaluated each having a different number of depots of varying capacity and location within Kansas relative to a central commodity-receiving biorefinery to test GHG emissions uncertainty. Monte Carlo simulation was used to estimate the spatial uncertainty in the HPL gate-to-gate sequence. The results show that the transport of densified biomass introduces the highest variability and contribution to the carbon footprint of the logistics HPL supply chain (0.2-13 g CO 2e/MJ). Moreover, depending upon the biomass availability and its spatial density and surrounding transportation infrastructure (road and rail), logistics HPL processes can increase the variability in life cycle environmental impacts for lignocellulosic biofuels. Within Kansas, life cycle GHG emissions could range from 24 to 41 g CO 2e/MJ depending upon the location, size and number of preprocessing depots constructed. However, this range can be minimized through optimizing the siting of preprocessing depots where ample rail infrastructure exists to supply biomass commodity to a regional biorefinery supply system« less

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

PubMed Central

Dipnall, Joanna F.

2016-01-01

Background Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. Methods The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. Results After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). Conclusion The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin. PMID:26848571

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

PubMed

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.

A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test

NASA Technical Reports Server (NTRS)

Messer, Bradley

2007-01-01

Propulsion ground test facilities face the daily challenge of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Over the last decade NASA s propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and exceeded the capabilities of numerous test facility and test article components. A logistic regression mathematical modeling technique has been developed to predict the probability of successfully completing a rocket propulsion test. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),.., X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure of accomplishing a full duration test. The use of logistic regression modeling is not new; however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from this type of model provide project managers with insight and confidence into the effectiveness of rocket propulsion ground testing.

Sociodemographic and social contextual predictors of multiple health behavior change: data from the Healthy Directions-Small Business study.

PubMed

Harley, Amy E; Sapp, Amy L; Li, Yi; Marino, Miguel; Quintiliani, Lisa M; Sorensen, Glorian

2013-03-01

Multiple modifiable health behaviors contribute to the chronic diseases that are the leading causes of death in the USA. Disparities for meeting recommended health behavior guidelines exist across occupational classes and socioeconomic levels. The purpose of this paper was to investigate sociodemographic and social contextual predictors of multiple health behavior change in a worksite intervention. We analyzed data on four diet and exercise variables from an intervention trial with worksite-level randomization. Eight hundred forty-one employees had complete data from baseline (response rate = 84 %) and follow-up surveys (response rate = 77 %). Multilevel logistic regression estimated associations between least absolute shrinkage and selection operator-selected sociodemographic and social contextual predictor variables and the multiple health behavior change outcome (changing 2+ versus 0 behaviors). Gender, being married/partnered, and perceived discrimination were significantly associated with multiple health behavior change. Sociodemographic and social contextual factors predict multiple health behavior change and could inform the design and delivery of worksite interventions targeting multiple health behaviors.

Regression Analysis of Optical Coherence Tomography Disc Variables for Glaucoma Diagnosis.

PubMed

Richter, Grace M; Zhang, Xinbo; Tan, Ou; Francis, Brian A; Chopra, Vikas; Greenfield, David S; Varma, Rohit; Schuman, Joel S; Huang, David

2016-08-01

To report diagnostic accuracy of optical coherence tomography (OCT) disc variables using both time-domain (TD) and Fourier-domain (FD) OCT, and to improve the use of OCT disc variable measurements for glaucoma diagnosis through regression analyses that adjust for optic disc size and axial length-based magnification error. Observational, cross-sectional. In total, 180 normal eyes of 112 participants and 180 eyes of 138 participants with perimetric glaucoma from the Advanced Imaging for Glaucoma Study. Diagnostic variables evaluated from TD-OCT and FD-OCT were: disc area, rim area, rim volume, optic nerve head volume, vertical cup-to-disc ratio (CDR), and horizontal CDR. These were compared with overall retinal nerve fiber layer thickness and ganglion cell complex. Regression analyses were performed that corrected for optic disc size and axial length. Area-under-receiver-operating curves (AUROC) were used to assess diagnostic accuracy before and after the adjustments. An index based on multiple logistic regression that combined optic disc variables with axial length was also explored with the aim of improving diagnostic accuracy of disc variables. Comparison of diagnostic accuracy of disc variables, as measured by AUROC. The unadjusted disc variables with the highest diagnostic accuracies were: rim volume for TD-OCT (AUROC=0.864) and vertical CDR (AUROC=0.874) for FD-OCT. Magnification correction significantly worsened diagnostic accuracy for rim variables, and while optic disc size adjustments partially restored diagnostic accuracy, the adjusted AUROCs were still lower. Axial length adjustments to disc variables in the form of multiple logistic regression indices led to a slight but insignificant improvement in diagnostic accuracy. Our various regression approaches were not able to significantly improve disc-based OCT glaucoma diagnosis. However, disc rim area and vertical CDR had very high diagnostic accuracy, and these disc variables can serve to complement additional OCT measurements for diagnosis of glaucoma.

Multi scale habitat relationships of Martes americana in northern Idaho, U.S.A.

Treesearch

Tzeidle N. Wasserman; Samuel A. Cushman; David O. Wallin; Jim Hayden

2012-01-01

We used bivariate scaling and logistic regression to investigate multiple-scale habitat selection by American marten (Martes americana). Bivariate scaling reveals dramatic differences in the apparent nature and strength of relationships between marten occupancy and a number of habitat variables across a range of spatial scales. These differences include reversals in...

The association between insured male expatriates' knowledge of health insurance benefits and lack of access to health care in Saudi Arabia.

PubMed

Alkhamis, Abdulwahab A

2018-03-15

Insufficient knowledge of health insurance benefits could be associated with lack of access to health care, particularly for minority populations. This study aims to assess the association between expatriates' knowledge of health insurance benefits and lack of access to health care. A cross-sectional study design was conducted from March 2015 to February 2016 among 3398 insured male expatriates in Riyadh, Saudi Arabia. The dependent variable was binary and expresses access or lack of access to health care. Independent variables included perceived and validated knowledge of health insurance benefits and other variables. Data were summarized by computing frequencies and percentage of all quantities of variables. To evaluate variations in knowledge, personal and job characteristics with lack of access to health care, the Chi square test was used. Odds ratio (OR) and 95% confidence interval (CI) were recorded for each independent variable. Multiple logistic regression and stepwise logistic regression were performed and adjusted ORs were extracted. Descriptive analysis showed that 15% of participants lacked access to health care. The majority of these were unskilled laborers, usually with no education (17.5%), who had been working for less than 3 years (28.1%) in Saudi Arabia. A total of 23.3% worked for companies with less than 50 employees and 16.5% earned less than 4500 Saudi Riyals monthly ($1200). Many (20.3%) were young (< 30 years old) or older (17.9% ≥ 56 years old) and had no formal education (24.7%). Nearly half had fair or poor health status (49.5%), were uncomfortable conversing in Arabic (29.7%) or English (16.7%) and lacked previous knowledge of health insurance (18%). For perceived knowledge of health insurance, 55.2% scored 1 or 0 from total of 3. For validated knowledge, 16.9% scored 1 or 0 from total score of 4. Multiple logistic regression analysis showed that only perceived knowledge of health insurance had significant associations with lack of access to health care ((OR) = 0.393, (CI) = 0.335-0.461), but the result was insignificant for validated knowledge. Stepwise logistic regression gave similar findings. Our results confirmed that low perceived knowledge of health insurance in expatriates was associated with less access to health care.

Impact of wearing fixed orthodontic appliances on quality of life among adolescents: Case-control study.

PubMed

Costa, Andréa A; Serra-Negra, Júnia M; Bendo, Cristiane B; Pordeus, Isabela A; Paiva, Saul M

2016-01-01

To investigate the impact of wearing a fixed orthodontic appliance on oral health-related quality of life (OHRQoL) among adolescents. A case-control study (1 ∶ 2) was carried out with a population-based randomized sample of 327 adolescents aged 11 to 14 years enrolled at public and private schools in the City of Brumadinho, southeast of Brazil. The case group (n  =  109) was made up of adolescents with a high negative impact on OHRQoL, and the control group (n  =  218) was made up of adolescents with a low negative impact. The outcome variable was the impact on OHRQoL measured by the Brazilian version of the Child Perceptions Questionnaire (CPQ 11-14) - Impact Short Form (ISF:16). The main independent variable was wearing fixed orthodontic appliances. Malocclusion and the type of school were identified as possible confounding variables. Bivariate and multiple conditional logistic regressions were employed in the statistical analysis. A multiple conditional logistic regression model demonstrated that adolescents wearing fixed orthodontic appliances had a 4.88-fold greater chance of presenting high negative impact on OHRQoL (95% CI: 2.93-8.13; P < .001) than those who did not wear fixed orthodontic appliances. A bivariate conditional logistic regression demonstrated that malocclusion was significantly associated with OHRQoL (P  =  .017), whereas no statistically significant association was found between the type of school and OHRQoL (P  =  .108). Adolescents who wore fixed orthodontic appliances had a greater chance of reporting a negative impact on OHRQoL than those who did not wear such appliances.

[Prevalence and factors associated with peripheral artery disease in patients with type 2 diabetes mellitus in Primary Care].

PubMed

Montero-Monterroso, J L; Gascón-Jiménez, J A; Vargas-Rubio, M D; Quero-Salado, C; Villalba-Marín, P; Pérula-de Torres, L A

2015-01-01

Peripheral artery disease in the lower limbs (PAD) is a prevalent condition that entails high morbidity in diabetic patients; this study assesses PAD in these patients and its socio-demographic and clinic associated variables. Descriptive study in a systematic sample of diabetic patients (DM2) aged 50-80 years, in Primary Care settings. The dependent variable was the presence of PAD diagnosed by ankle-brachial index (ABI) ≤ 0.9; independent variables: socio-demographic, clinical and laboratory. bivariate and multiple logistic regression analyses were performed to determine the variables associated with low ABI. A sample of 251 patients, 52.6% women; mean age: 68.5 ±8.5. A low ABI was detected in 18.3% (95% Confidence Interval (95% CI):13.3-23.3%), with 6 subjets (2.4%) previously diagnosed as suffering PAD. Age (OR=1.07; 95% CI: 1.02-1.12) and retinopathy (OR=2.69; 95% CI: 1.06-6.81) were associated (multiple logistic regression analysis) with ABI. The percentage of patients diagnosed with PAD is very low, although PAD prevalence is high among DM2 patients attending Primary Care clinics, especially in older patients and those with retinopathy. We emphasize the recommendation of performing the ABI test in this population at risk. Copyright © 2014 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

A multiscaled model of southwestern willow flycatcher breeding habitat

USGS Publications Warehouse

Hatten, J.R.; Paradzick, C.E.

2003-01-01

The southwestern willow flycatcher (SWFL; Empidonax traillii extimus) is an endangered songbird whose habitat has declined dramatically over the last century. Understanding habitat selection patterns and the ability to identify potential breeding areas for the SWFL is crucial to the management and conservation of this species. We developed a multiscaled model of SWTL breeding habitat with a Geographic Information System (GIS), survey data, GIS variables, and multiple logistic regressions. We obtained presence and absence survey data from a riverine ecosystem and a reservoir delta in south-central Arizona, USA, in 1999. We extracted the GIS variables from satellite imagery and digital elevation models to characterize vegetation and floodplain within the project area. We used multiple logistic regressions within a cell-based (30 X 30 m) modeling environment to (1) determine associations between GIS variables and breeding-site occurrence at different spatial scales (0.09-72 ha), and (2) construct a predictive model. Our best model explained 54% of the variability in breeding-site occurrence with the following variables: vegetation density at the site (0.09 ha), proportion of dense vegetation and variability in vegetation density within a 4.5-ha neighborhood, and amount of floodplain or flat terrain within a 41-ha neighborhood. The density of breeding sites was highest in areas that the model predicted to be most suitable within the project area and at an external test site 200 km away. Conservation efforts must focus on protecting not only occupied patches, but also surrounding riparian forests and floodplain to ensure long-term viability of SWTL. We will use the multiscaled model to map SWTL breeding habitat in Arizona, prioritize future survey effort, and examine changes in habitat abundance and quality over time.

Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China

NASA Astrophysics Data System (ADS)

Nong, Yu; Du, Qingyun; Wang, Kun; Miao, Lei; Zhang, Weiwei

2008-10-01

Urban growth modeling, one of the most important aspects of land use and land cover change study, has attracted substantial attention because it helps to comprehend the mechanisms of land use change thus helps relevant policies made. This study applied multinomial logistic regression to model urban growth in the Jiayu county of Hubei province, China to discover the relationship between urban growth and the driving forces of which biophysical and social-economic factors are selected as independent variables. This type of regression is similar to binary logistic regression, but it is more general because the dependent variable is not restricted to two categories, as those previous studies did. The multinomial one can simulate the process of multiple land use competition between urban land, bare land, cultivated land and orchard land. Taking the land use type of Urban as reference category, parameters could be estimated with odds ratio. A probability map is generated from the model to predict where urban growth will occur as a result of the computation.

Using Multiple Indicators of Cognitive State in Logistic Models that Predict Individual Performance in Machine-Mediated Learning Environments.

ERIC Educational Resources Information Center

Hancock, Thomas E.; And Others

1995-01-01

In machine-mediated learning environments, there is a need for more reliable methods of calculating the probability that a learner's response will be correct in future trials. A combination of domain-independent response-state measures of cognition along with two instructional variables for maximum predictive ability are demonstrated. (Author/LRW)

Can we "predict" long-term outcome for ambulatory transcutaneous electrical nerve stimulation in patients with chronic pain?

PubMed

Köke, Albère J; Smeets, Rob J E M; Perez, Roberto S; Kessels, Alphons; Winkens, Bjorn; van Kleef, Maarten; Patijn, Jacob

2015-03-01

Evidence for effectiveness of transcutaneous electrical nerve stimulation (TENS) is still inconclusive. As heterogeneity of chronic pain patients might be an important factor for this lack of efficacy, identifying factors for a successful long-term outcome is of great importance. A prospective study was performed to identify variables with potential predictive value for 2 outcome measures on long term (6 months); (1) continuation of TENS, and (2) a minimally clinical important pain reduction of ≥ 33%. At baseline, a set of risk factors including pain-related variables, psychological factors, and disability was measured. In a multiple logistic regression analysis, higher patient's expectations, neuropathic pain, no severe pain (< 80 mm visual analogue scale [VAS]) were independently related to long-term continuation of TENS. For the outcome "minimally clinical important pain reduction," the multiple logistic regression analysis indicated that no multisited pain (> 2 pain locations) and intermittent pain were positively and independently associated with a minimally clinical important pain reduction of ≥ 33%. The results showed that factors associated with a successful outcome in the long term are dependent on definition of successful outcome. © 2014 World Institute of Pain.

Factors associated with preventable infant death: a multiple logistic regression.

PubMed

Vidal E Silva, Sandra Maria Cunha; Tuon, Rogério Antonio; Probst, Livia Fernandes; Gondinho, Brunna Verna Castro; Pereira, Antonio Carlos; Meneghim, Marcelo de Castro; Cortellazzi, Karine Laura; Ambrosano, Glaucia Maria Bovi

2018-01-01

OBJECTIVE To identify and analyze factors associated with preventable child deaths. METHODS This analytical cross-sectional study had preventable child mortality as dependent variable. From a population of 34,284 live births, we have selected a systematic sample of 4,402 children who did not die compared to 272 children who died from preventable causes during the period studied. The independent variables were analyzed in four hierarchical blocks: sociodemographic factors, the characteristics of the mother, prenatal and delivery care, and health conditions of the patient and neonatal care. We performed a descriptive statistical analysis and estimated multiple hierarchical logistic regression models. RESULTS Approximatelly 35.3% of the deaths could have been prevented with the early diagnosis and treatment of diseases during pregnancy and 26.8% of them could have been prevented with better care conditions for pregnant women. CONCLUSIONS The following characteristics of the mother are determinant for the higher mortality of children before the first year of life: living in neighborhoods with an average family income lower than four minimum wages, being aged ≤ 19 years, having one or more alive children, having a child with low APGAR level at the fifth minute of life, and having a child with low birth weight.

Modeling brook trout presence and absence from landscape variables using four different analytical methods

USGS Publications Warehouse

Steen, Paul J.; Passino-Reader, Dora R.; Wiley, Michael J.

2006-01-01

As a part of the Great Lakes Regional Aquatic Gap Analysis Project, we evaluated methodologies for modeling associations between fish species and habitat characteristics at a landscape scale. To do this, we created brook trout Salvelinus fontinalis presence and absence models based on four different techniques: multiple linear regression, logistic regression, neural networks, and classification trees. The models were tested in two ways: by application to an independent validation database and cross-validation using the training data, and by visual comparison of statewide distribution maps with historically recorded occurrences from the Michigan Fish Atlas. Although differences in the accuracy of our models were slight, the logistic regression model predicted with the least error, followed by multiple regression, then classification trees, then the neural networks. These models will provide natural resource managers a way to identify habitats requiring protection for the conservation of fish species.

Poor sleep quality and nightmares are associated with non-suicidal self-injury in adolescents.

PubMed

Liu, Xianchen; Chen, Hua; Bo, Qi-Gui; Fan, Fang; Jia, Cun-Xian

2017-03-01

Non-suicidal self-injury (NSSI) is prevalent and is associated with increased risk of suicidal behavior in adolescents. This study examined which sleep variables are associated with NSSI, independently from demographics and mental health problems in Chinese adolescents. Participants consisted of 2090 students sampled from three high schools in Shandong, China and had a mean age of 15.49 years. Participants completed a sleep and health questionnaire to report their demographic and family information, sleep duration and sleep problems, impulsiveness, hopelessness, internalizing and externalizing problems, and NSSI. A series of regression analyses were conducted to examine the associations between sleep variables and NSSI. Of the sample, 12.6 % reported having ever engaged in NSSI and 8.8 % engaged during the last year. Univariate logistic analyses demonstrated that multiple sleep variables including short sleep duration, insomnia symptoms, poor sleep quality, sleep insufficiency, unrefreshed sleep, sleep dissatisfaction, daytime sleepiness, fatigue, snoring, and nightmares were associated with increased risk of NSSI. After adjusting for demographic and mental health variables, NSSI was significantly associated with sleeping <6 h per night, poor sleep quality, sleep dissatisfaction, daytime sleepiness, and frequent nightmares. Stepwise logistic regression model demonstrated that poor sleep quality (OR = 2.18, 95 % CI = 1.37-3.47) and frequent nightmares (OR = 2.88, 95 % CI = 1.45-5.70) were significantly independently associated with NSSI. In conclusion, while multiple sleep variables are associated with NSSI, poor sleep quality and frequent nightmares are independent risk factors of NSSI. These findings may have important implications for further research of sleep self-harm mechanisms and early detection and prevention of NSSI in adolescents.

Third and Fourth Degree Perineal Injury After Vaginal Delivery: Does Race Make a Difference?

PubMed Central

de Silva, Kanoe-Lehua; Tsai, Pai-Jong Stacy; Kon, Leanne M; Kessel, Bruce; Seto, Todd; Kaneshiro, Bliss

2014-01-01

Severe perineal injury (third and fourth degree laceration) at the time of vaginal delivery increases the risk of fecal incontinence, chronic perineal pain, and dyspareunia.1–5 Studies suggest the prevalence of severe perineal injury may vary by racial group.6 The purpose of the current study was to examine rates of severe perineal injury in different Asian and Pacific Islander subgroups. A retrospective cohort study was performed among all patients who had a vaginal delivery at Queens Medical Center in Honolulu, Hawai‘i between January 1, 2002 and December 31, 2003. Demographic and health related variables were obtained for each participant. Maternal race/ethnicity (Japanese, Filipino, Chinese, other Asian, Part-Hawaiian/Hawaiian, Micronesian, other Pacific Islander, Caucasian, multiracial [non-Hawaiian], and other) was self-reported by the patient at the time admission. The significance of associations between racial/ethnic groups and demographic and health related variables was determined using chi-square tests for categorical variables and analysis of variance for continuous factors. Multiple logistic regression was performed to adjust for potential confounders when examining severe laceration rates. A total of 1842 subjects met inclusion criteria. The proportion of severe perineal lacerations did not differ significantly between racial groups. In the multiple logistic regression analysis, operative vaginal delivery was related to both race and severe perineal laceration. However, despite adjusting for this variable, race was not associated with an increased risk of having a severe laceration (P = .70). The results of this study indicate the risk of severe perineal laceration does not differ based on maternal race/ethnicity. PMID:24660124

Risk factors for low birth weight according to the multiple logistic regression model. A retrospective cohort study in José María Morelos municipality, Quintana Roo, Mexico.

PubMed

Franco Monsreal, José; Tun Cobos, Miriam Del Ruby; Hernández Gómez, José Ricardo; Serralta Peraza, Lidia Esther Del Socorro

2018-01-17

Low birth weight has been an enigma for science over time. There have been many researches on its causes and its effects. Low birth weight is an indicator that predicts the probability of a child surviving. In fact, there is an exponential relationship between weight deficit, gestational age, and perinatal mortality. Multiple logistic regression is one of the most expressive and versatile statistical instruments available for the analysis of data in both clinical and epidemiology settings, as well as in public health. To assess in a multivariate fashion the importance of 17 independent variables in low birth weight (dependent variable) of children born in the Mayan municipality of José María Morelos, Quintana Roo, Mexico. Analytical observational epidemiological cohort study with retrospective temporality. Births that met the inclusion criteria occurred in the "Hospital Integral Jose Maria Morelos" of the Ministry of Health corresponding to the Maya municipality of Jose Maria Morelos during the period from August 1, 2014 to July 31, 2015. The total number of newborns recorded was 1,147; 84 of which (7.32%) had low birth weight. To estimate the independent association between the explanatory variables (potential risk factors) and the response variable, a multiple logistic regression analysis was performed using the IBM SPSS Statistics 22 software. In ascending numerical order values of odds ratio > 1 indicated the positive contribution of explanatory variables or possible risk factors: "unmarried" marital status (1.076, 95% confidence interval: 0.550 to 2.104); age at menarche ≤ 12 years (1.08, 95% confidence interval: 0.64 to 1.84); history of abortion(s) (1.14, 95% confidence interval: 0.44 to 2.93); maternal weight < 50 kg (1.51, 95% confidence interval: 0.83 to 2.76); number of prenatal consultations ≤ 5 (1.86, 95% confidence interval: 0.94 to 3.66); maternal age ≥ 36 years (3.5, 95% confidence interval: 0.40 to 30.47); maternal age ≤ 19 years (3.59, 95% confidence interval: 0.43 to 29.87); number of deliveries = 1 (3.86, 95% confidence interval: 0.33 to 44.85); personal pathological history (4.78, 95% confidence interval: 2.16 to 10.59); pathological obstetric history (5.01, 95% confidence interval: 1.66 to 15.18); maternal height < 150 cm (5.16, 95% confidence interval: 3.08 to 8.65); number of births ≥ 5 (5.99, 95% confidence interval: 0.51 to 69.99); and smoking (15.63, 95% confidence interval: 1.07 to 227.97). Four of the independent variables (personal pathological history, obstetric pathological history, maternal stature <150 centimeters and smoking) showed a significant positive contribution, thus they can be considered as clear risk factors for low birth weight. The use of the logistic regression model in the Mayan municipality of José María Morelos, will allow estimating the probability of low birth weight for each pregnant woman in the future, which will be useful for the health authorities of the region.

Subclinical thyroid dysfunction and psychiatric disorders: cross-sectional results from the Brazilian Study of Adult Health (ELSA-Brasil).

PubMed

Benseñor, Isabela M; Nunes, Maria Angélica; Sander Diniz, Maria de Fátima; Santos, Itamar S; Brunoni, André R; Lotufo, Paulo A

2016-02-01

To evaluate the association between subclinical thyroid dysfunction and psychiatric disorders using baseline data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Cross-sectional study. The study included 12 437 participants from the ELSA-Brasil with normal thyroid function (92·8%), 193 (1·4%) with subclinical hyperthyroidism and 784 (5·8%) with subclinical hypothyroidism, totalling 13 414 participants (50·6% of women). The mental health diagnoses of participants were assessed by trained raters using the Clinical Interview Schedule - Revised (CIS-R) and grouped according to the International Classification of Diseases 10 (ICD-10). Thyroid dysfunction was assessed using TSH and FT4 as well as routine use of thyroid hormones or antithyroid medications. Logistic models were presented using psychiatric disorders as the dependent variable and subclinical thyroid disorders as the independent variable. All logistic models were corrected for multiple comparisons using Bonferroni correction. After multivariate adjustment for possible confounders, we found a direct association between subclinical hyperthyroidism and panic disorder odds ratio [OR], 2·55; 95% confidence Interval (95% CI), 1·09-5·94; and an inverse association between subclinical hypothyroidism and generalized anxiety disorder (OR, 0·75; 95% CI, 0·59-0·96). However, both lost significance after correction for multiple comparisons. Subclinical hyperthyroidism was positively associated with panic disorder and negatively associated with anxiety disorder, although not significant after adjustment for multiple comparisons. © 2015 John Wiley & Sons Ltd.

Determinants of child maltreatment in Nepal: Results from the 2014 Nepal multiple indicator cluster survey (the 2014 NMICS).

PubMed

Atteraya, Madhu Sudhan; Ebrahim, Nasser B; Gnawali, Shreejana

2018-02-01

We examined the prevalence of child maltreatment as measured by the level of physical (moderate to severe) and emotional abuse and child labor, and the associated household level determinants of child maltreatment in Nepal. We used a nationally representative data set from the fifth round of the Nepal Multiple Indicator Cluster Survey (the 2014 NMICS). The main independent variables were household level characteristics. Dependent variables included child experience of moderate to severe physical abuse, emotional abuse, and child labor (domestic work and economic activities). Bivariate analyses and logistic regressions were used to examine the associations between independent and dependent variables. The results showed that nearly half of the children (49.8%) had experienced moderate physical abuse, 21.5% experienced severe physical abuse, and 77.3% experienced emotional abuse. About 27% of the children had engaged in domestic work and 46.7% in various economic activities. At bivariate level, educational level of household's head and household wealth status had shown significant statistical association with child maltreatment (p<0.001). Results from multivariate logistic regressions showed that higher education levels and higher household wealth status protected children from moderate to severe physical abuse, emotional abuse and child labor. In general, child maltreatment is a neglected social issue in Nepal and the high rates of child maltreatment calls for mass awareness programs focusing on parents, and involving all stakeholders including governments, local, and international organizations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ventilator-associated pneumonia: the influence of bacterial resistance, prescription errors, and de-escalation of antimicrobial therapy on mortality rates.

PubMed

Souza-Oliveira, Ana Carolina; Cunha, Thúlio Marquez; Passos, Liliane Barbosa da Silva; Lopes, Gustavo Camargo; Gomes, Fabiola Alves; Röder, Denise Von Dolinger de Brito

2016-01-01

Ventilator-associated pneumonia is the most prevalent nosocomial infection in intensive care units and is associated with high mortality rates (14-70%). This study evaluated factors influencing mortality of patients with Ventilator-associated pneumonia (VAP), including bacterial resistance, prescription errors, and de-escalation of antibiotic therapy. This retrospective study included 120 cases of Ventilator-associated pneumonia admitted to the adult adult intensive care unit of the Federal University of Uberlândia. The chi-square test was used to compare qualitative variables. Student's t-test was used for quantitative variables and multiple logistic regression analysis to identify independent predictors of mortality. De-escalation of antibiotic therapy and resistant bacteria did not influence mortality. Mortality was 4 times and 3 times higher, respectively, in patients who received an inappropriate antibiotic loading dose and in patients whose antibiotic dose was not adjusted for renal function. Multiple logistic regression analysis revealed the incorrect adjustment for renal function was the only independent factor associated with increased mortality. Prescription errors influenced mortality of patients with Ventilator-associated pneumonia, underscoring the challenge of proper Ventilator-associated pneumonia treatment, which requires continuous reevaluation to ensure that clinical response to therapy meets expectations. Copyright © 2016. Published by Elsevier Editora Ltda.

Factors associated with preventable infant death: a multiple logistic regression

PubMed Central

Vidal e Silva, Sandra Maria Cunha; Tuon, Rogério Antonio; Probst, Livia Fernandes; Gondinho, Brunna Verna Castro; Pereira, Antonio Carlos; Meneghim, Marcelo de Castro; Cortellazzi, Karine Laura; Ambrosano, Glaucia Maria Bovi

2018-01-01

ABSTRACT OBJECTIVE To identify and analyze factors associated with preventable child deaths. METHODS This analytical cross-sectional study had preventable child mortality as dependent variable. From a population of 34,284 live births, we have selected a systematic sample of 4,402 children who did not die compared to 272 children who died from preventable causes during the period studied. The independent variables were analyzed in four hierarchical blocks: sociodemographic factors, the characteristics of the mother, prenatal and delivery care, and health conditions of the patient and neonatal care. We performed a descriptive statistical analysis and estimated multiple hierarchical logistic regression models. RESULTS Approximatelly 35.3% of the deaths could have been prevented with the early diagnosis and treatment of diseases during pregnancy and 26.8% of them could have been prevented with better care conditions for pregnant women. CONCLUSIONS The following characteristics of the mother are determinant for the higher mortality of children before the first year of life: living in neighborhoods with an average family income lower than four minimum wages, being aged ≤ 19 years, having one or more alive children, having a child with low APGAR level at the fifth minute of life, and having a child with low birth weight. PMID:29723389

Hip fracture in the elderly: a re-analysis of the EPIDOS study with causal Bayesian networks.

PubMed

Caillet, Pascal; Klemm, Sarah; Ducher, Michel; Aussem, Alexandre; Schott, Anne-Marie

2015-01-01

Hip fractures commonly result in permanent disability, institutionalization or death in elderly. Existing hip-fracture predicting tools are underused in clinical practice, partly due to their lack of intuitive interpretation. By use of a graphical layer, Bayesian network models could increase the attractiveness of fracture prediction tools. Our aim was to study the potential contribution of a causal Bayesian network in this clinical setting. A logistic regression was performed as a standard control approach to check the robustness of the causal Bayesian network approach. EPIDOS is a multicenter study, conducted in an ambulatory care setting in five French cities between 1992 and 1996 and updated in 2010. The study included 7598 women aged 75 years or older, in which fractures were assessed quarterly during 4 years. A causal Bayesian network and a logistic regression were performed on EPIDOS data to describe major variables involved in hip fractures occurrences. Both models had similar association estimations and predictive performances. They detected gait speed and mineral bone density as variables the most involved in the fracture process. The causal Bayesian network showed that gait speed and bone mineral density were directly connected to fracture and seem to mediate the influence of all the other variables included in our model. The logistic regression approach detected multiple interactions involving psychotropic drug use, age and bone mineral density. Both approaches retrieved similar variables as predictors of hip fractures. However, Bayesian network highlighted the whole web of relation between the variables involved in the analysis, suggesting a possible mechanism leading to hip fracture. According to the latter results, intervention focusing concomitantly on gait speed and bone mineral density may be necessary for an optimal prevention of hip fracture occurrence in elderly people.

Carotid artery intima-media complex thickening in patients with relatively long-surviving type 1 diabetes mellitus.

PubMed

Distiller, Larry A; Joffe, Barry I; Melville, Vanessa; Welman, Tania; Distiller, Greg B

2006-01-01

The factors responsible for premature coronary atherosclerosis in patients with type 1 diabetes are ill defined. We therefore assessed carotid intima-media complex thickness (IMT) in relatively long-surviving patients with type 1 diabetes as a marker of atherosclerosis and correlated this with traditional risk factors. Cross-sectional study of 148 patients with relatively long-surviving (>18 years) type 1 diabetes (76 men and 72 women) attending the Centre for Diabetes and Endocrinology, Johannesburg. The mean common carotid artery IMT and presence or absence of plaque was evaluated by high-resolution B-mode ultrasound. Their median age was 48 years and duration of diabetes 26 years (range 18-59 years). Traditional risk factors (age, duration of diabetes, glycemic control, hypertension, smoking and lipoprotein concentrations) were recorded. Three response variables were defined and modeled. Standard multiple regression was used for a continuous IMT variable, logistic regression for the presence/absence of plaque and ordinal logistic regression to model three categories of "risk." The median common carotid IMT was 0.62 mm (range 0.44-1.23 mm) with plaque detected in 28 cases. The multiple regression model found significant associations between IMT and current age (P=.001), duration of diabetes (P=.033), BMI (P=.008) and diagnosed hypertension (P=.046) with HDL showing a protective effect (P=.022). Current age (P=.001) and diagnosed hypertension (P=.004), smoking (P=.008) and retinopathy (P=.033) were significant in the logistic regression model. Current age was also significant in the ordinal logistic regression model (P<.001), as was total cholesterol/HDL ratio (P<.001) and mean HbA(1c) concentration (P=.073). The major factors influencing common carotid IMT in patients with relatively long-surviving type 1 diabetes are age, duration of diabetes, existing hypertension and HDL (protective) with a relatively minor role ascribed to relatively long-standing glycemic control.

Cross-national differences in the gender gap in subjective health in Europe: does country-level gender equality matter?

PubMed

Dahlin, Johanna; Härkönen, Juho

2013-12-01

Multiple studies have found that women report being in worse health despite living longer. Gender gaps vary cross-nationally, but relatively little is known about the causes of comparative differences. Existing literature is inconclusive as to whether gender gaps in health are smaller in more gender equal societies. We analyze gender gaps in self-rated health (SRH) and limiting longstanding illness (LLI) with five waves of European Social Survey data for 191,104 respondents from 28 countries. We use means, odds ratios, logistic regressions, and multilevel random slopes logistic regressions. Gender gaps in subjective health vary visibly across Europe. In many countries (especially in Eastern and Southern Europe), women report distinctly worse health, while in others (such as Estonia, Finland, and Great Britain) there are small or no differences. Logistic regressions ran separately for each country revealed that individual-level socioeconomic and demographic variables explain a majority of these gaps in some countries, but contribute little to their understanding in most countries. In yet other countries, men had worse health when these variables were controlled for. Cross-national variation in the gender gaps exists after accounting for individual-level factors. Against expectations, the remaining gaps are not systematically related to societal-level gender inequality in the multilevel analyses. Our findings stress persistent cross-national variability in gender gaps in health and call for further analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Development of the Sydney Falls Risk Screening Tool in brain injury rehabilitation: A multisite prospective cohort study.

PubMed

McKechnie, Duncan; Fisher, Murray J; Pryor, Julie; Bonser, Melissa; Jesus, Jhoven De

2018-03-01

To develop a falls risk screening tool (FRST) sensitive to the traumatic brain injury rehabilitation population. Falls are the most frequently recorded patient safety incident within the hospital context. The inpatient traumatic brain injury rehabilitation population is one particular population that has been identified as at high risk of falls. However, no FRST has been developed for this patient population. Consequently in the traumatic brain injury rehabilitation population, there is the real possibility that nurses are using falls risk screening tools that have a poor clinical utility. Multisite prospective cohort study. Univariate and multiple logistic regression modelling techniques (backward elimination, elastic net and hierarchical) were used to examine each variable's association with patients who fell. The resulting FRST's clinical validity was examined. Of the 140 patients in the study, 41 (29%) fell. Through multiple logistic regression modelling, 11 variables were identified as predictors for falls. Using hierarchical logistic regression, five of these were identified for inclusion in the resulting falls risk screening tool: prescribed mobility aid (such as, wheelchair or frame), a fall since admission to hospital, impulsive behaviour, impaired orientation and bladder and/or bowel incontinence. The resulting FRST has good clinical validity (sensitivity = 0.9; specificity = 0.62; area under the curve = 0.87; Youden index = 0.54). The tool was significantly more accurate (p = .037 on DeLong test) in discriminating fallers from nonfallers than the Ontario Modified STRATIFY FRST. A FRST has been developed using a comprehensive statistical framework, and evidence has been provided of this tool's clinical validity. The developed tool, the Sydney Falls Risk Screening Tool, should be considered for use in brain injury rehabilitation populations. © 2017 John Wiley & Sons Ltd.

Access to Care and Satisfaction Among Health Center Patients With Chronic Conditions.

PubMed

Shi, Leiyu; Lee, De-Chih; Haile, Geraldine Pierre; Liang, Hailun; Chung, Michelle; Sripipatana, Alek

This study examined access to care and satisfaction among health center patients with chronic conditions. Data for this study were obtained from the 2009 Health Center Patient Survey. Dependent variables of interest included 5 measures of access to and satisfaction with care, whereas the main independent variable was number of chronic conditions. Results of bivariate analysis and multiple logistic regressions showed that patients with chronic conditions had significantly higher odds of reporting access barriers than those without chronic conditions. Our results suggested that additional efforts and resources are necessary to address the needs of health center patients with chronic conditions.

Factors associated with vocal fold pathologies in teachers.

PubMed

Souza, Carla Lima de; Carvalho, Fernando Martins; Araújo, Tânia Maria de; Reis, Eduardo José Farias Borges Dos; Lima, Verônica Maria Cadena; Porto, Lauro Antonio

2011-10-01

To analyze factors associated with the prevalence of the medical diagnosis of vocal fold pathologies in teachers. A census-based epidemiological, cross-sectional study was conducted with 4,495 public primary and secondary school teachers in the city of Salvador, Northeastern Brazil, between March and April 2006. The dependent variable was the self-reported medical diagnosis of vocal fold pathologies and the independent variables were sociodemographic characteristics; professional activity; work organization/interpersonal relationships; physical work environment characteristics; frequency of common mental disorders, measured by the Self-Reporting Questionnaire-20 (SRQ-20 >7); and general health conditions. Descriptive statistical, bivariate and multiple logistic regression analysis techniques were used. The prevalence of self-reported medical diagnosis of vocal fold pathologies was 18.9%. In the logistic regression analysis, the variables that remained associated with this medical diagnosis were as follows: being female, having worked as a teacher for more than seven years, excessive voice use, reporting more than five unfavorable physical work environment characteristics and presence of common mental disorders. The presence of self-reported vocal fold pathologies was associated with factors that point out the need of actions that promote teachers' vocal health and changes in their work structure and organization.

Characteristics of acute care hospitals with diversity plans and translation services.

PubMed

Moseley, Charles B; Shen, Jay J; Ginn, Gregory O

2011-01-01

Hospitals provide diversity activities for a number of reasons. The authors examined community demand, resource availability, managed care, institutional pressure, and external orientation related variables that were associated with acute care hospital diversity plans and translation services. The authors used multiple logistic regression to analyze the data for 478 hospitals in the 2006 National Inpatient Sample (NIS) dataset that had available data on the racial and ethnic status of their discharges. We also used 2004 and 2006 American Hospital Association (AHA) data to measure the two dependent diversity variables and the other independent variables. We found that resource, managed care, and external orientation variables were associated with having a diversity plan and that resource, managed care, institutional, and external orientation variables were associated with providing translation services. The authors concluded that more evidence for diversity's impact, additional resources, and more institutional pressure may be needed to motivate more hospitals to provide diversity planning and translation services.

Prediction of performance on the RCMP physical ability requirement evaluation.

PubMed

Stanish, H I; Wood, T M; Campagna, P

1999-08-01

The Royal Canadian Mounted Police use the Physical Ability Requirement Evaluation (PARE) for screening applicants. The purposes of this investigation were to identify those field tests of physical fitness that were associated with PARE performance and determine which most accurately classified successful and unsuccessful PARE performers. The participants were 27 female and 21 male volunteers. Testing included measures of aerobic power, anaerobic power, agility, muscular strength, muscular endurance, and body composition. Multiple regression analysis revealed a three-variable model for males (70-lb bench press, standing long jump, and agility) explaining 79% of the variability in PARE time, whereas a one-variable model (agility) explained 43% of the variability for females. Analysis of the classification accuracy of the males' data was prohibited because 91% of the males passed the PARE. Classification accuracy of the females' data, using logistic regression, produced a two-variable model (agility, 1.5-mile endurance run) with 93% overall classification accuracy.

Variables Associated With Perceived Unmet Need for Mental Health Care in a Canadian Epidemiologic Catchment Area.

PubMed

Fleury, Marie-Josée; Grenier, Guy; Bamvita, Jean-Marie; Perreault, Michel; Caron, Jean

2016-01-01

This study identified variables associated with perceived partially met and unmet needs for information, medication, and counseling, as well as overall perceived unmet needs, related to mental health among 571 people in a Canadian epidemiologic catchment area. Needs were measured with the Perceived Need for Care Questionnaire and a comprehensive set of independent variables based on Andersen's behavioral model. Four models were constructed for the following dependent variables: perceived unmet needs for information, medication, and counseling (multinomial logistic regression) and overall perceived unmet needs (multiple logistic regression). The proportions reporting fully unmet need were as follows: counseling, 30%; information, 18%; and medication, 4%. Variables associated with unmet needs for information, medication, and counseling were quite distinct. Enabling factors (for example, neighborhood perception variables) were strongly associated with perceived unmet need for information. Need factors were more strongly associated with unmet need for medication, predisposing factors with unmet needs for information and medication, and health service use with unmet information and counseling needs. People whose overall needs went unmet tended to be younger, to have an addiction, and to have consulted fewer professionals. Mental health services should facilitate access to psychologists or other clinicians to better meet counseling and information needs. They should also take neighborhoods into account when assessing needs and provide more information about mental disorders and the treatments and services offered in disadvantaged areas. Finally, services should be further developed for younger people with addiction, who tend to be stigmatized and avoid using health services.

Clinical and Radiologic Predictive Factors of Rib Fractures in Outpatients With Chest Pain.

PubMed

Zhang, Liang; McMahon, Colm J; Shah, Samir; Wu, Jim S; Eisenberg, Ronald L; Kung, Justin W

To identify the clinical and radiologic predictive factors of rib fractures in stable adult outpatients presenting with chest pain and to determine the utility of dedicated rib radiographs in this population of patients. Following Institutional Review Board approval, we performed a retrospective review of 339 consecutive cases in which a frontal chest radiograph and dedicated rib series had been obtained for chest pain in the outpatient setting. The frontal chest radiograph and dedicated rib series were sequentially reviewed in consensus by two fellowship-trained musculoskeletal radiologists blinded to the initial report. The consensus interpretation of the dedicated rib series was used as the gold standard. Multiple variable logistic regression analysis assessed clinical and radiological factors associated with rib fractures. Fisher exact test was used to assess differences in medical treatment between the 2 groups. Of the 339 patients, 53 (15.6%) had at least 1 rib fracture. Only 20 of the 53 (37.7%) patients' fractures could be identified on the frontal chest radiograph. The frontal chest radiograph had a sensitivity of 38% and specificity of 100% when using the rib series as the reference standard. No pneumothorax, new mediastinal widening or pulmonary contusion was identified. Multiple variable logistic regression analysis of clinical factors associated with the presence of rib fractures revealed a significant association of trauma history (odds ratio 5.7 [p < 0.05]) and age ≥40 (odds radio 3.1 [p < 0.05]). Multiple variable logistic regression analysis of radiographic factors associated with rib fractures in this population demonstrated a significant association of pleural effusion with rib fractures (odds ratio 18.9 [p < 0.05]). Patients with rib fractures received narcotic analgesia in 47.2% of the cases, significantly more than those without rib fractures (21.3%, p < 0.05). None of the patients required hospitalization. In the stable outpatient setting, rib fractures have a higher association with a history of minor trauma and age ≥40 in the adult population. Radiographic findings associated with rib fractures include pleural effusion. The frontal chest radiograph alone has low sensitivity in detecting rib fractures. The dedicated rib series detected a greater number of rib fractures. Although no patients required hospitalization, those with rib fractures were more likely to receive narcotic analgesia. Copyright © 2018 Elsevier Inc. All rights reserved.

Interest in dietary pattern, social capital, and psychological distress: a cross-sectional study in a rural Japanese community

PubMed Central

2013-01-01

Background Among life-style factors affecting mental health, dietary habits are becoming a public health concern in their relation to psychological distress and social capital. We examined associations between interest in dietary pattern, social capital, and psychological distress with a population-based cross-sectional study in rural Japan. Methods A total of 16,996 residents of a rural town in northern Japan aged 30–79 years participated in this questionnaire survey. The questionnaire gathered data about socio-demographic variables, psychological distress, issues related to dietary habits, including interest in dietary pattern, and the social capital factors of reciprocity and sense of community belonging. Factors related to psychological distress were analyzed by using multiple logistic regression analysis. Results A high interest in dietary pattern was significantly associated with a high level of social capital. In addition, an association between interest in dietary pattern and frequencies of intake of vegetables and fruits was confirmed. The multiple logistic regression analyses showed significant associations between interest in dietary pattern, social capital, frequency of intake of vegetables, and psychological distress after adjusting for socio-demographic variables. Low interest in dietary pattern was positively associated with psychological distress after adjusting for socio-demographic variables (OR = 2.18; 95%CI: 1.69-2.81). Low levels of both reciprocity and sense of community belonging were associated with psychological distress after adjusting for socio-demographic variables (OR = 3.46 with 95%CI of 2.10–5.71 for reciprocity, and OR = 7.42 with 95%CI of 4.64–11.87 for sense of community belonging). Conclusion Low interest in dietary pattern, low frequency of intake of vegetables, and low levels of social capital were significantly associated with psychological distress after adjusting for socio-demographic variables. PMID:24099097

Correlation and simple linear regression.

PubMed

Eberly, Lynn E

2007-01-01

This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.

Psychological effects of disaster relief activities on Japan ground self-defense force personnel following the 2011 great east Japan earthquake.

PubMed

Dobashi, Kosuke; Nagamine, Masanori; Shigemura, Jun; Tsunoda, Tomoya; Shimizu, Kunio; Yoshino, Aihide; Nomura, Soichiro

2014-01-01

Disaster relief workers are potentially exposed to severe stressors on the job, resulting in a variety of psychological responses. This study aims to clarify the psychological effects of disaster relief activities on Japan Ground Self-Defense Force (JGSDF) personnel following the 2011 Great East Japan Earthquake. A self-report questionnaire was administered to 606 JGSDF personnel one month after completing the disaster relief mission. Posttraumatic stress responses and general psychological distress were assessed using the Impact of Event Scale-Revised (IES-R) and the K10 scales. Associations between outcome variables and independent variables (age, gender, military rank, length of deployment, and exposure to dead bodies) were measured with univariate analyses and subsequent multiple logistic regression analyses. The mean (± SD) IES-R score was 6.2 (± 8.1), and the mean K10 score was 12.8 (± 4.4). In the univariate analyses, exposure to dead bodies and age were identified as significant factors for IES-R and K10 scores, (p < 0.01). However, the multiple logistic regression analyses did not reveal any significant factors although body handlers' exposure approached significance for IES-R. The subjects reported very low psychological responses despite the severe nature of their disaster relief activities. Several factors may account for the low levels of psychological distress and posttraumatic symptoms observed in this study.

The effects of multiple interpersonal traumas on psychological maladjustment of sexually abused children in Korea.

PubMed

Choi, Ji Young; Oh, Kyung Ja

2013-02-01

The purpose of the present study was to explore the effects of multiple interpersonal traumas on psychiatric diagnosis and behavior problems of sexually abused children in Korea. With 495 children (ages 4-13 years) referred to a public counseling center for sexual abuse in Korea, we found significant differences in the rate of psychiatric diagnoses (r = .23) and severity of behavioral problems (internalizing d = 0.49, externalizing d = 0.40, total d = 0.52) between children who were victims of sexual abuse only (n = 362) and youth who were victims of interpersonal trauma experiences in addition to sexual abuse (n = 133). The effects of multiple interpersonal trauma experiences on single versus multiple diagnoses remained significant in the logistic regression analysis where demographic variables, family environmental factors, sexual abuse characteristics, and postincident factors were considered together, odds ratio (OR) = 0.44, 95% confidence interval (CI) = [0.25, 0.77], p < .01. Similarly, multiple regression analyses revealed a significant effect of multiple interpersonal trauma experiences on severity of behavioral problems above and beyond all aforementioned variables (internalizing β =.12, p = .019, externalizing β = .11, p = .036, total β = .14, p =.008). The results suggested that children with multiple interpersonal traumas are clearly at a greater risk for negative consequences following sexual abuse. Copyright © 2013 International Society for Traumatic Stress Studies.

[Nutritional support and risk factors of appearance of enterocutaneous fistulas].

PubMed

Llop, J M; Cobo, S; Padullés, A; Farran, L; Jódar, R; Badia, M B

2012-01-01

Among the different factors described, nutritional support has been associated to prevention and management of enterocutaneous fistulae (ECF). To assess the influence that the parameters related to nutritional, clinical status, and surgical variables have on the occurrence of ECF. An observational case/control retrospective study was performed on patients admitted to the General and Digestive Surgery Department. The parameters analyzed were: diagnosis, body mass index (BMI), pathologic personal history, number of surgical interventions (SI) and complications (previous infection, bleeding, and ischemia). In patients with SI, we analyzed: number and type of SI, time until onset of nutritional support, and type of nutritional support. We performed a multiple logistic uni- and multivariate regression analysis by using the SPSSv.19.0 software. The primary diagnoses related to the occurrence of ECF were pancreatic pathology (OR = 5.346) and inflammatory bowel disease (IBD) (OR = 9.329). The surgical variables associated to higher prevalence of ECF emergency SI (OR = 5.79) and multiple SI (OR = 4.52). Regarding the nutritional variables, the late onset of nutrition (more than three days after SI) was associated to the occurrence of ECF (OR = 3.82). In surgical patients, early nutritional support , independently of the route of administration, decreases the occurrence of fistulae. Pancreatic pathology, IBD, emergency SI, and multiple SI were associated to higher prevalence of ECF. The variable hyponutrition appears as a risk factor that should be confirmed in further studies.

Temperature variability during targeted temperature management is not associated with neurological outcomes following cardiac arrest.

PubMed

Nayeri, Arash; Bhatia, Nirmanmoh; Holmes, Benjamin; Borges, Nyal; Armstrong, William; Xu, Meng; Farber-Eger, Eric; Wells, Quinn S; McPherson, John A

2017-06-01

Recent studies on comatose survivors of cardiac arrest undergoing targeted temperature management (TTM) have shown similar outcomes at multiple target temperatures. However, details regarding core temperature variability during TTM and its prognostic implications remain largely unknown. We sought to assess the association between core temperature variability and neurological outcomes in patients undergoing TTM following cardiac arrest. We analyzed a prospectively collected cohort of 242 patients treated with TTM following cardiac arrest at a tertiary care hospital between 2007 and 2014. Core temperature variability was defined as the statistical variance (i.e. standard deviation squared) amongst all core temperature recordings during the maintenance phase of TTM. Poor neurological outcome at hospital discharge, defined as a Cerebral Performance Category (CPC) score>2, was the primary outcome. Death prior to hospital discharge was assessed as the secondary outcome. Multivariable logistic regression was used to examine the association between temperature variability and neurological outcome or death at hospital discharge. A poor neurological outcome was observed in 147 (61%) patients and 136 (56%) patients died prior to hospital discharge. In multivariable logistic regression, increased core temperature variability was not associated with increased odds of poor neurological outcomes (OR 0.38, 95% CI 0.11-1.38, p=0.142) or death (OR 0.43, 95% CI 0.12-1.53, p=0.193) at hospital discharge. In this study, individual core temperature variability during TTM was not associated with poor neurological outcomes or death at hospital discharge. Copyright © 2017 Elsevier Inc. All rights reserved.

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

Statistical Methods for Generalized Linear Models with Covariates Subject to Detection Limits.

PubMed

Bernhardt, Paul W; Wang, Huixia J; Zhang, Daowen

2015-05-01

Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study.

War-related trauma exposure and multiple risk behaviors among school-going adolescents in Northern Uganda: the mediating role of depression symptoms.

PubMed

Okello, James; Nakimuli-Mpungu, Etheldreda; Musisi, Seggane; Broekaert, Eric; Derluyn, Ilse

2013-11-01

The relationship between war-related trauma exposure, depressive symptoms and multiple risk behaviors among adolescents is less clear in sub-Saharan Africa. We analyzed data collected from a sample of school-going adolescents four years postwar. Participants completed interviews assessing various risk behaviors defined by the Youth Self Report (YSR) and a sexual risk behavior survey, and were screened for post-traumatic stress, anxiety and depression symptoms based on the Impact of Events Scale Revised (IESR) and Hopkins Symptom Checklist for Adolescents (HSCL-37A) respectively. Multivariate logistic regression was used to assess factors independently associated with multiple risk behaviors. The logistic regression model of Baron and Kenny (1986) was used to evaluate the mediating role of depression in the relationship between stressful war events and multiple risk behaviors. Of 551 participants, 139 (25%) reported multiple (three or more) risk behaviors in the past year. In the multivariate analyses, depression symptoms remained uniquely associated with multiple risk behavior after adjusting for potential confounders including socio-demographic characteristics, war-related trauma exposure variables, anxiety and post-traumatic stress symptoms. In mediation analysis, depression symptoms mediated the associations between stressful war events and multiple risk behaviors. The psychometric properties of the questionnaires used in this study are not well established in war affected African samples thus ethno cultural variation may decrease the validity of our measures. Adolescents with depression may be at a greater risk of increased engagement in multiple risk behaviors. Culturally sensitive and integrated interventions to treat and prevent depression among adolescents in post-conflict settings are urgently needed. © 2013 Elsevier B.V. All rights reserved.

Factors Associated with Falls in Community-Dwelling Older People with Focus on Participation in Sport Organizations: The Japan Gerontological Evaluation Study Project

PubMed Central

Hayashi, Takahiro; Kondo, Katsunori; Suzuki, Kayo; Yamada, Minoru; Matsumoto, Daisuke

2014-01-01

Objective. Promoting participation in sport organizations may be a population strategy for preventing falls in older people. In this study, we examined whether participation in sport organizations is associated with fewer falls in older people even after adjusting for multiple individual and environmental factors. Methods. We used the Japan Gerontological Evaluation Study data of 90,610 people (31 municipalities) who were not eligible for public long-term care. Logistic regression analysis was performed, with multiple falls over the past year as the dependent variable and participation in a sport organization as the independent variable, controlling for 13 factors. These included individual factors related to falls, such as age and sex, and environmental factors such as population density of the habitable area. Results. A total of 6,391 subjects (7.1%) had a history of multiple falls. Despite controlling for 13 variables, those who participated in a sport organization at least once a week were approximately ≥20% less likely to fall than those who did not participate at all (once a week; odds ratio = 0.82 and 95% confidence interval = 0.72–0.95). Conclusion. Participation in a sport organization at least once per week might help prevent falls in the community-dwelling older people. PMID:24955360

[Depressive symptoms among medical intern students in a Brazilian public university].

PubMed

Costa, Edméa Fontes de Oliva; Santana, Ygo Santos; Santos, Ana Teresa Rodrigues de Abreu; Martins, Luiz Antonio Nogueira; Melo, Enaldo Vieira de; Andrade, Tarcísio Matos de

2012-01-01

To estimate, among Medical School intern students, the prevalence of depressive symptoms and their severity, as well as associated factors. Cross-sectional study in May 2008, with a representative sample of medical intern students (n = 84) from Universidade Federal de Sergipe (UFS). Beck Depression Inventory (BDI) and a structured questionnaire containing information on sociodemographic variables, teaching-learning process, and personal aspects were used. The exploratory data analysis was performed by descriptive and inferential statistics. Finally, the analysis of multiple variables by logistic regression and the calculation of simple and adjusted ORs with their respective 95% confidence intervals were performed. The general prevalence was 40.5%, with 1.2% (95% CI: 0.0-6.5) of severe depressive symptoms; 4.8% (95% CI: 1.3-11.7) of moderate depressive symptoms; and 34.5% (95% CI: 24.5-45.7) of mild depressive symptoms. The logistic regression revealed the variables with a major impact associated with the emergence of depressive symptoms: thoughts of dropping out (OR 6.24; p = 0.002); emotional stress (OR 7.43;p = 0.0004); and average academic performance (OR 4.74; p = 0.0001). The high prevalence of depressive symptoms in the study population was associated with variables related to the teaching-learning process and personal aspects, suggesting immediate preemptive measures regarding Medical School graduation and student care are required.

Climate controls the distribution of a widespread invasive species: Implications for future range expansion

USGS Publications Warehouse

McDowell, W.G.; Benson, A.J.; Byers, J.E.

2014-01-01

1. Two dominant drivers of species distributions are climate and habitat, both of which are changing rapidly. Understanding the relative importance of variables that can control distributions is critical, especially for invasive species that may spread rapidly and have strong effects on ecosystems. 2. Here, we examine the relative importance of climate and habitat variables in controlling the distribution of the widespread invasive freshwater clam Corbicula fluminea, and we model its future distribution under a suite of climate scenarios using logistic regression and maximum entropy modelling (MaxEnt). 3. Logistic regression identified climate variables as more important than habitat variables in controlling Corbicula distribution. MaxEnt modelling predicted Corbicula's range expansion westward and northward to occupy half of the contiguous United States. By 2080, Corbicula's potential range will expand 25–32%, with more than half of the continental United States being climatically suitable. 4. Our combination of multiple approaches has revealed the importance of climate over habitat in controlling Corbicula's distribution and validates the climate-only MaxEnt model, which can readily examine the consequences of future climate projections. 5. Given the strong influence of climate variables on Corbicula's distribution, as well as Corbicula's ability to disperse quickly and over long distances, Corbicula is poised to expand into New England and the northern Midwest of the United States. Thus, the direct effects of climate change will probably be compounded by the addition of Corbicula and its own influences on ecosystem function.

The weighted priors approach for combining expert opinions in logistic regression experiments

DOE PAGES

Quinlan, Kevin R.; Anderson-Cook, Christine M.; Myers, Kary L.

2017-04-24

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration.more » While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.« less

The weighted priors approach for combining expert opinions in logistic regression experiments

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

Quinlan, Kevin R.; Anderson-Cook, Christine M.; Myers, Kary L.

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration.more » While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.« less

Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

NASA Astrophysics Data System (ADS)

Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

2017-06-01

A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

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.

Clinical Value of Dorsal Medulla Oblongata Involvement Detected with Conventional MRI for Prediction of Outcome in Children with Enterovirus 71-related Brainstem Encephalitis.

PubMed

Liu, Kun; Zhou, Yongjin; Cui, Shihan; Song, Jiawen; Ye, Peipei; Xiang, Wei; Huang, Xiaoyan; Chen, Yiping; Yan, Zhihan; Ye, Xinjian

2018-04-05

Brainstem encephalitis is the most common neurologic complication after enterovirus 71 infection. The involvement of brainstem, especially the dorsal medulla oblongata, can cause severe sequelae or death in children with enterovirus 71 infection. We aimed to determine the prevalence of dorsal medulla oblongata involvement in children with enterovirus 71-related brainstem encephalitis (EBE) by using conventional MRI and to evaluate the value of dorsal medulla oblongata involvement in outcome prediction. 46 children with EBE were enrolled in the study. All subjects underwent a 1.5 Tesla MR examination of the brain. The disease distribution and clinical data were collected. Dichotomized outcomes (good versus poor) at longer than 6 months were available for 28 patients. Logistic regression was used to determine whether the MRI-confirmed dorsal medulla oblongata involvement resulted in improved clinical outcome prediction when compared with other location involvement. Of the 46 patients, 35 had MRI evidence of dorsal medulla oblongata involvement, 32 had pons involvement, 10 had midbrain involvement, and 7 had dentate nuclei involvement. Patients with dorsal medulla oblongata involvement or multiple area involvement were significantly more often in the poor outcome group than in the good outcome group. Logistic regression analysis showed that dorsal medulla oblongata involvement was the most significant single variable in outcome prediction (predictive accuracy, 90.5%), followed by multiple area involvement, age, and initial glasgow coma scale score. Dorsal medulla oblongata involvement on conventional MRI correlated significantly with poor outcomes in EBE children, improved outcome prediction when compared with other clinical and disease location variables, and was most predictive when combined with multiple area involvement, glasgow coma scale score and age.

Pregnant women with the sickle cell trait are not at increased risk for developing preeclampsia.

PubMed

Stamilio, David M; Sehdev, Harish M; Macones, George A

2003-01-01

The primary objective of this study was to determine whether having the sickle cell trait is independently associated with preeclampsia. We performed a retrospective cohort study of 1998 pregnant patients who either did or did not have the sickle cell trait. All patients were screened for the sickle trait using the "Sickledex" test. Data on neonatal and maternal outcome, including preeclampsia, and potential confounding variables were abstracted from medical records. Unadjusted, stratified, and multiple logistic regression analyses were used to identify interactions, and confounding between multiple variables and the association between sickle cell trait and preeclampsia. With an anticipated 6.5% rate of preeclampsia, and alpha = 0.05, this cohort study has 80% power to detect a relative risk (RR) of 2.3 for preeclampsia. Univariate analysis revealed that the two cohorts were similar with regard to primiparity, maternal age, chronic diseases, birth weight, and gestational age at delivery, but the sickle cell trait cohort was more likely to have gestational diabetes and had a higher mean body mass index (BMI). In the univariate analysis, the sickle cell trait cohort was not at increased risk for preeclampsia [unadjusted RR = 0.5, 95% CI (0.2-1.6)]. After controlling for potential confounding variables with logistic regression analysis, sickle trait was not independently associated with preeclampsia [adjusted RR = 0.5, 95% CI (0.2- 1.6)]. In contrast to prior work, these data suggest that the sickle cell trait is not an independent risk factor for preeclampsia or postpartum complications. In fact, the data are more consistent with the sickle trait being protective for developing preeclampsia.

Geographic information systems and logistic regression for high-resolution malaria risk mapping in a rural settlement of the southern Brazilian Amazon.

PubMed

de Oliveira, Elaine Cristina; dos Santos, Emerson Soares; Zeilhofer, Peter; Souza-Santos, Reinaldo; Atanaka-Santos, Marina

2013-11-15

In Brazil, 99% of the cases of malaria are concentrated in the Amazon region, with high level of transmission. The objectives of the study were to use geographic information systems (GIS) analysis and logistic regression as a tool to identify and analyse the relative likelihood and its socio-environmental determinants of malaria infection in the Vale do Amanhecer rural settlement, Brazil. A GIS database of georeferenced malaria cases, recorded in 2005, and multiple explanatory data layers was built, based on a multispectral Landsat 5 TM image, digital map of the settlement blocks and a SRTM digital elevation model. Satellite imagery was used to map the spatial patterns of land use and cover (LUC) and to derive spectral indices of vegetation density (NDVI) and soil/vegetation humidity (VSHI). An Euclidian distance operator was applied to measure proximity of domiciles to potential mosquito breeding habitats and gold mining areas. The malaria risk model was generated by multiple logistic regression, in which environmental factors were considered as independent variables and the number of cases, binarized by a threshold value was the dependent variable. Out of a total of 336 cases of malaria, 133 positive slides were from inhabitants at Road 08, which corresponds to 37.60% of the notifications. The southern region of the settlement presented 276 cases and a greater number of domiciles in which more than ten cases/home were notified. From these, 102 (30.36%) cases were caused by Plasmodium falciparum and 174 (51.79%) cases by Plasmodium vivax. Malaria risk is the highest in the south of the settlement, associated with proximity to gold mining sites, intense land use, high levels of soil/vegetation humidity and low vegetation density. Mid-resolution, remote sensing data and GIS-derived distance measures can be successfully combined with digital maps of the housing location of (non-) infected inhabitants to predict relative likelihood of disease infection through the analysis by logistic regression. Obtained findings on the relation between malaria cases and environmental factors should be applied in the future for land use planning in rural settlements in the Southern Amazon to minimize risks of disease transmission.

Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression

NASA Astrophysics Data System (ADS)

Martínez-Fernández, J.; Chuvieco, E.; Koutsias, N.

2013-02-01

Humans are responsible for most forest fires in Europe, but anthropogenic factors behind these events are still poorly understood. We tried to identify the driving factors of human-caused fire occurrence in Spain by applying two different statistical approaches. Firstly, assuming stationary processes for the whole country, we created models based on multiple linear regression and binary logistic regression to find factors associated with fire density and fire presence, respectively. Secondly, we used geographically weighted regression (GWR) to better understand and explore the local and regional variations of those factors behind human-caused fire occurrence. The number of human-caused fires occurring within a 25-yr period (1983-2007) was computed for each of the 7638 Spanish mainland municipalities, creating a binary variable (fire/no fire) to develop logistic models, and a continuous variable (fire density) to build standard linear regression models. A total of 383 657 fires were registered in the study dataset. The binary logistic model, which estimates the probability of having/not having a fire, successfully classified 76.4% of the total observations, while the ordinary least squares (OLS) regression model explained 53% of the variation of the fire density patterns (adjusted R2 = 0.53). Both approaches confirmed, in addition to forest and climatic variables, the importance of variables related with agrarian activities, land abandonment, rural population exodus and developmental processes as underlying factors of fire occurrence. For the GWR approach, the explanatory power of the GW linear model for fire density using an adaptive bandwidth increased from 53% to 67%, while for the GW logistic model the correctly classified observations improved only slightly, from 76.4% to 78.4%, but significantly according to the corrected Akaike Information Criterion (AICc), from 3451.19 to 3321.19. The results from GWR indicated a significant spatial variation in the local parameter estimates for all the variables and an important reduction of the autocorrelation in the residuals of the GW linear model. Despite the fitting improvement of local models, GW regression, more than an alternative to "global" or traditional regression modelling, seems to be a valuable complement to explore the non-stationary relationships between the response variable and the explanatory variables. The synergy of global and local modelling provides insights into fire management and policy and helps further our understanding of the fire problem over large areas while at the same time recognizing its local character.

A nonparametric multiple imputation approach for missing categorical data.

PubMed

Zhou, Muhan; He, Yulei; Yu, Mandi; Hsu, Chiu-Hsieh

2017-06-06

Incomplete categorical variables with more than two categories are common in public health data. However, most of the existing missing-data methods do not use the information from nonresponse (missingness) probabilities. We propose a nearest-neighbour multiple imputation approach to impute a missing at random categorical outcome and to estimate the proportion of each category. The donor set for imputation is formed by measuring distances between each missing value with other non-missing values. The distance function is calculated based on a predictive score, which is derived from two working models: one fits a multinomial logistic regression for predicting the missing categorical outcome (the outcome model) and the other fits a logistic regression for predicting missingness probabilities (the missingness model). A weighting scheme is used to accommodate contributions from two working models when generating the predictive score. A missing value is imputed by randomly selecting one of the non-missing values with the smallest distances. We conduct a simulation to evaluate the performance of the proposed method and compare it with several alternative methods. A real-data application is also presented. The simulation study suggests that the proposed method performs well when missingness probabilities are not extreme under some misspecifications of the working models. However, the calibration estimator, which is also based on two working models, can be highly unstable when missingness probabilities for some observations are extremely high. In this scenario, the proposed method produces more stable and better estimates. In addition, proper weights need to be chosen to balance the contributions from the two working models and achieve optimal results for the proposed method. We conclude that the proposed multiple imputation method is a reasonable approach to dealing with missing categorical outcome data with more than two levels for assessing the distribution of the outcome. In terms of the choices for the working models, we suggest a multinomial logistic regression for predicting the missing outcome and a binary logistic regression for predicting the missingness probability.

Periodontal disease in Chinese patients with systemic lupus erythematosus.

PubMed

Zhang, Qiuxiang; Zhang, Xiaoli; Feng, Guijaun; Fu, Ting; Yin, Rulan; Zhang, Lijuan; Feng, Xingmei; Li, Liren; Gu, Zhifeng

2017-08-01

Disease of systemic lupus erythematosus (SLE) and periodontal disease (PD) shares the common multiple characteristics. The aims of the present study were to evaluate the prevalence and severity of periodontal disease in Chinese SLE patients and to determine the association between SLE features and periodontal parameters. A cross-sectional study of 108 SLE patients together with 108 age- and sex-matched healthy controls was made. Periodontal status was conducted by two dentists independently. Sociodemographic characteristics, lifestyle factors, medication use, and clinical parameters were also assessed. The periodontal status was significantly worse in SLE patients compared to controls. In univariate logistic regression, SLE had a significant 2.78-fold [95% confidence interval (CI) 1.60-4.82] increase in odds of periodontitis compared to healthy controls. Adjusted for potential risk factors, patients with SLE had 13.98-fold (95% CI 5.10-38.33) increased odds against controls. In multiple linear regression model, the independent variable negatively and significantly associated with gingival index was education (P = 0.005); conversely, disease activity (P < 0.001) and plaque index (P = 0.002) were positively associated; Age was the only variable independently associated with periodontitis of SLE in multivariate logistic regression (OR 1.348; 95% CI: 1.183-1.536, P < 0.001). Chinese SLE patients were likely to suffer from higher odds of PD. These findings confirmed the importance of early interventions in combination with medical therapy. It is necessary for a close collaboration between dentists and clinicians when treating those patients.

Prevalence of dry eye syndrome after a three-year exposure to a clean room.

PubMed

Cho, Hyun A; Cheon, Jae Jung; Lee, Jong Seok; Kim, Soo Young; Chang, Seong Sil

2014-01-01

To measure the prevalence of dry eye syndrome (DES) among clean room (relative humidity ≤1%) workers from 2011 to 2013. Three annual DES examinations were performed completely in 352 clean room workers aged 20-40 years who were working at a secondary battery factory. Each examination comprised the tear-film break-up test (TFBUT), Schirmer's test I, slit-lamp microscopic examination, and McMonnies questionnaire. DES grades were measured using the Delphi approach. The annual examination results were analyzed using a general linear model and post-hoc analysis with repeated-ANOVA (Tukey). Multiple logistic regression was performed using the examination results from 2013 (dependent variable) to analyze the effect of years spent working in the clean room (independent variable). The prevalence of DES among these workers was 14.8% in 2011, 27.1% in 2012, and 32.8% in 2013. The TFBUT and McMonnies questionnaire showed that DES grades worsened over time. Multiple logistic regression analysis indicated that the odds ratio for having dry eyes was 1.130 (95% CI 1.012-1.262) according to the findings of the McMonnies questionnaire. This 3-year trend suggests that the increased prevalence of DES was associated with longer working hours. To decrease the prevalence of DES, employees should be assigned reasonable working hours with shift assignments that include appropriate break times. Workers should also wear protective eyewear, subdivide their working process to minimize exposure, and utilize preservative-free eye drops.

Easy and low-cost identification of metabolic syndrome in patients treated with second-generation antipsychotics: artificial neural network and logistic regression models.

PubMed

Lin, Chao-Cheng; Bai, Ya-Mei; Chen, Jen-Yeu; Hwang, Tzung-Jeng; Chen, Tzu-Ting; Chiu, Hung-Wen; Li, Yu-Chuan

2010-03-01

Metabolic syndrome (MetS) is an important side effect of second-generation antipsychotics (SGAs). However, many SGA-treated patients with MetS remain undetected. In this study, we trained and validated artificial neural network (ANN) and multiple logistic regression models without biochemical parameters to rapidly identify MetS in patients with SGA treatment. A total of 383 patients with a diagnosis of schizophrenia or schizoaffective disorder (DSM-IV criteria) with SGA treatment for more than 6 months were investigated to determine whether they met the MetS criteria according to the International Diabetes Federation. The data for these patients were collected between March 2005 and September 2005. The input variables of ANN and logistic regression were limited to demographic and anthropometric data only. All models were trained by randomly selecting two-thirds of the patient data and were internally validated with the remaining one-third of the data. The models were then externally validated with data from 69 patients from another hospital, collected between March 2008 and June 2008. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of all models. Both the final ANN and logistic regression models had high accuracy (88.3% vs 83.6%), sensitivity (93.1% vs 86.2%), and specificity (86.9% vs 83.8%) to identify MetS in the internal validation set. The mean +/- SD AUC was high for both the ANN and logistic regression models (0.934 +/- 0.033 vs 0.922 +/- 0.035, P = .63). During external validation, high AUC was still obtained for both models. Waist circumference and diastolic blood pressure were the common variables that were left in the final ANN and logistic regression models. Our study developed accurate ANN and logistic regression models to detect MetS in patients with SGA treatment. The models are likely to provide a noninvasive tool for large-scale screening of MetS in this group of patients. (c) 2010 Physicians Postgraduate Press, Inc.

Unitary Response Regression Models

ERIC Educational Resources Information Center

Lipovetsky, S.

2007-01-01

The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…

Employment characteristics and socioeconomic factors associated with disparities in smoking abstinence and former smoking among U.S. workers.

PubMed

Fagan, Pebbles; Shavers, Vickie L; Lawrence, Deirdre; Gibson, James Todd; O'Connell, Mary E

2007-11-01

This study examines the associations among employment and socioeconomic factors and the outcomes, current smoking, cigarette abstinence and former smoking among adult U.S. workers ages 18-64 (n=288,813). Multivariate logistic regression was used to examine the associations among the variables using cross-sectional data from the 1998-1999 and 2001-2002 Tobacco Use Supplements to the Current Population Survey. Lower odds of current smoking was observed among part-time workers compared to those working variable hours and multiple job holders compared to persons holding one job. The self-employed, part-time workers and multiple job holders had higher odds of former smoking than comparison groups. Employment factors were not associated with short-term abstinence or 12-month abstinence from smoking, but income, education, marital status, and duration of smoking were associated with 12-month abstinence. These data suggest that while employment factors are associated with current and former smoking, socioeconomic factors are associated with long-term quitting.

Occupational and non-occupational factors associated with work-related injuries among construction workers in the USA

PubMed Central

Dong, Xiuwen Sue; Wang, Xuanwen; Largay, Julie A.

2015-01-01

Background: Many factors contribute to occupational injuries. However, these factors have been compartmentalized and isolated in most studies. Objective: To examine the relationship between work-related injuries and multiple occupational and non-occupational factors among construction workers in the USA. Methods: Data from the 1988–2000 National Longitudinal Survey of Youth, 1979 cohort (N = 12,686) were analyzed. Job exposures and health behaviors were examined and used as independent variables in four multivariate logistic regression models to identify associations with occupational injuries. Results: After controlling for demographic variables, occupational injuries were 18% (95% CI: 1.04–1.34) more likely in construction than in non-construction. Blue-collar occupations, job physical efforts, multiple jobs, and long working hours accounted for the escalated risk in construction. Smoking, obesity/overweight, and cocaine use significantly increased the risk of work-related injury when demographics and occupational factors were held constant. Conclusions: Workplace injuries are better explained by simultaneously examining occupational and non-occupational characteristics. PMID:25816923

Using Multiple and Logistic Regression to Estimate the Median WillCost and Probability of Cost and Schedule Overrun for Program Managers

DTIC Science & Technology

2017-03-23

PUBLIC RELEASE; DISTRIBUTION UNLIMITED Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and... Cost and Probability of Cost and Schedule Overrun for Program Managers Ryan C. Trudelle Follow this and additional works at: https://scholar.afit.edu...afit.edu. Recommended Citation Trudelle, Ryan C., "Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and

Variable Selection in Logistic Regression.

DTIC Science & Technology

1987-06-01

23 %. AUTIOR(.) S. CONTRACT OR GRANT NUMBE Rf.i %Z. D. Bai, P. R. Krishnaiah and . C. Zhao F49620-85- C-0008 " PERFORMING ORGANIZATION NAME AND AOORESS...d I7 IOK-TK- d 7 -I0 7’ VARIABLE SELECTION IN LOGISTIC REGRESSION Z. D. Bai, P. R. Krishnaiah and L. C. Zhao Center for Multivariate Analysis...University of Pittsburgh Center for Multivariate Analysis University of Pittsburgh Y !I VARIABLE SELECTION IN LOGISTIC REGRESSION Z- 0. Bai, P. R. Krishnaiah

The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching.

PubMed

Szekér, Szabolcs; Vathy-Fogarassy, Ágnes

2018-01-01

Logistic regression based propensity score matching is a widely used method in case-control studies to select the individuals of the control group. This method creates a suitable control group if all factors affecting the output variable are known. However, if relevant latent variables exist as well, which are not taken into account during the calculations, the quality of the control group is uncertain. In this paper, we present a statistics-based research in which we try to determine the relationship between the accuracy of the logistic regression model and the uncertainty of the dependent variable of the control group defined by propensity score matching. Our analyses show that there is a linear correlation between the fit of the logistic regression model and the uncertainty of the output variable. In certain cases, a latent binary explanatory variable can result in a relative error of up to 70% in the prediction of the outcome variable. The observed phenomenon calls the attention of analysts to an important point, which must be taken into account when deducting conclusions.

Disclosure of HIV Status and Social Support Among People Living With HIV

PubMed Central

Jorjoran Shushtari, Zahra; Sajjadi, Homeira; Forouzan, Ameneh Setareh; Salimi, Yahya; Dejman, Masoumeh

2014-01-01

Background: Disclosure of HIV is important for improving self-care behaviors, psychological well-being, commitment to the treatment, and reducing risk of transmission. One of the major benefits of disclosure is social support, which is an essential resource for effective coping with HIV infection. However, receiving any social support requires disclosing of HIV status. Objectives: This study aimed to determine the disclosure of HIV status and its related factors such as social support in addition to demographic and disease characteristics among people living with HIV in Iran. Patients and Methods: This cross-sectional study, using simple random sampling, was carried out on 175 people with HIV/AIDS who referred to Behavioral Counseling Centers. The self-administrated, Norbeck Social Support Questionnaire was used to measure social support. Disclosure of HIV status was assessed with an investigator-designed questions. Multiple logistic regression analysis with backward Likelihood Ratio method was applied to identify the adjusted odds ratio between disclosure as dependent variable and demographic variables, social support as independent variables. Results: Participants were often disclosed their HIV status to family members. But there were differences about disclosure of HIV status within the context of the family. Family members were perceived as more supportive. Multiple logistic regression analysis demonstrates that the gender (adjusted OR = 0.181; 95% CI .068-0.479), CD4 cell count (adjusted OR = 0.997; 95% CI 0.994-0.999), route of transmission (injection-drug user [adjusted OR = 9.366; 95% CI 3.358-26.123] and other routes [tattooing, mother to child, dental services, etc.], [adjusted OR = 3.752; 95% CI 1.157-12.167]), and functional support variable (adjusted OR = 1.007; 95% CI 1.001-1.013) remained in the model as significant predictors for disclosure. Conclusions: The results of this study regarding disclosure of HIV status and its relations to social support and some demographic variables can provide an understanding based on the evidence for promotion of knowledge and coping interventions about people living with HIV/AIDS and their perceived social support status. PMID:25389470

Meteorological factors and timing of the initiating event of human parturition

NASA Astrophysics Data System (ADS)

Hirsch, Emmet; Lim, Courtney; Dobrez, Deborah; Adams, Marci G.; Noble, William

2011-03-01

The aim of this study was to determine whether meteorological factors are associated with the timing of either onset of labor with intact membranes or rupture of membranes prior to labor—together referred to as `the initiating event' of parturition. All patients delivering at Evanston Hospital after spontaneous labor or rupture of membranes at ≥20 weeks of gestation over a 6-month period were studied. Logistic regression models of the initiating event of parturition using clinical variables (maternal age, gestational age, parity, multiple gestation and intrauterine infection) with and without the addition of meteorological variables (barometric pressure, temperature and humidity) were compared. A total of 1,088 patients met the inclusion criteria. Gestational age, multiple gestation and chorioamnionitis were associated with timing of initiation of parturition ( P < 0.01). The addition of meteorological to clinical variables generated a statistically significant improvement in prediction of the initiating event; however, the magnitude of this improvement was small (less than 2% difference in receiver-operating characteristic score). These observations held regardless of parity, fetal number and gestational age. Meteorological factors are associated with the timing of parturition, but the magnitude of this association is small.

A new approach for modeling patient overall radiosensitivity and predicting multiple toxicity endpoints for breast cancer patients.

PubMed

Mbah, Chamberlain; De Ruyck, Kim; De Schrijver, Silke; De Sutter, Charlotte; Schiettecatte, Kimberly; Monten, Chris; Paelinck, Leen; De Neve, Wilfried; Thierens, Hubert; West, Catharine; Amorim, Gustavo; Thas, Olivier; Veldeman, Liv

2018-05-01

Evaluation of patient characteristics inducing toxicity in breast radiotherapy, using simultaneous modeling of multiple endpoints. In 269 early-stage breast cancer patients treated with whole-breast irradiation (WBI) after breast-conserving surgery, toxicity was scored, based on five dichotomized endpoints. Five logistic regression models were fitted, one for each endpoint and the effect sizes of all variables were estimated using maximum likelihood (MLE). The MLEs are improved with James-Stein estimates (JSEs). The method combines all the MLEs, obtained for the same variable but from different endpoints. Misclassification errors were computed using MLE- and JSE-based prediction models. For associations, p-values from the sum of squares of MLEs were compared with p-values from the Standardized Total Average Toxicity (STAT) Score. With JSEs, 19 highest ranked variables were predictive of the five different endpoints. Important variables increasing radiation-induced toxicity were chemotherapy, age, SATB2 rs2881208 SNP and nodal irradiation. Treatment position (prone position) was most protective and ranked eighth. Overall, the misclassification errors were 45% and 34% for the MLE- and JSE-based models, respectively. p-Values from the sum of squares of MLEs and p-values from STAT score led to very similar conclusions, except for the variables nodal irradiation and treatment position, for which STAT p-values suggested an association with radiosensitivity, whereas p-values from the sum of squares indicated no association. Breast volume was ranked as the most significant variable in both strategies. The James-Stein estimator was used for selecting variables that are predictive for multiple toxicity endpoints. With this estimator, 19 variables were predictive for all toxicities of which four were significantly associated with overall radiosensitivity. JSEs led to almost 25% reduction in the misclassification error rate compared to conventional MLEs. Finally, patient characteristics that are associated with radiosensitivity were identified without explicitly quantifying radiosensitivity.

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

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

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test ofmore » the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.« less

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

NASA Astrophysics Data System (ADS)

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam

2015-10-01

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.

An occupational health study of emergency physicians in Japan: health assessment by immune variables (CD4, CD8, CD56, and NK cell activity) at the beginning of work.

PubMed

Okamoto, Hiroteru; Tsunoda, Tooru; Teruya, Koji; Takeda, Nobuo; Uemura, Takamoto; Matsui, Tomoko; Fukazawa, Shinji; Ichikawa, Kaoru; Takemae, Rieko; Tsuchida, Kosuke; Takashima, Yutaka

2008-01-01

This study was conducted to evaluate the occupational health of Japanese physicians in emergency medicine. Subjects participating in this study were eighty-nine physicians working at 12 medical facilities (10 critical care emergency centers) in Japan. Participants were asked to complete a questionnaire of work conditions and to provide blood samples for immune variable measurements (CD4, CD8, CD56 and natural killer cell (NK cell) activity) before commencing their work. The data collected from seventy-four of 89 participating physicians were analyzed. The traditional work group comprised of 39 emergency physicians, who were significantly overworked compared to other two groups: the shift work group and the day work group. Among these three groups, no immune variable was significantly different except lymphocyte, number of CD4, and NK cell activity; and the NK cell activity of the shift work group was significantly lower than those of the traditional work group (p<0.01) and the day work group (p<0.01) in terms of Bonferroni's multiple comparison, probably due to circadian rhythm. It was indicated that NK cell activity was significantly lower in samples collected at night versus in the morning (OR=8.34, 95%CI: 1.95-35.6, p<0.01) through multiple logistic regression analyses. NK cell activity was significantly lower in individuals taking 0-3 days off per month, as compared to those taking 4 or more days off (OR=4.65, 95%CI: 1.27-17.0, p=0.02), according to multiple logistic regression analyses. Therefore, the low NK cell activity appears to have reflected the extent of fatigue arising from physicians' overwork. Overwork would have been a potential risk for the physicians' health, resulting in a lower quality of Japanese emergency medical services than that which could have been achieved otherwise. This study suggests that it would be better for the Japanese emergency physicians to take 4 or more days off per month for their health and the quality of their services.

Self-perception and malocclusion and their relation to oral appearance and function.

PubMed

Peres, Sílvia Helena de Carvalho Sales; Goya, Suzana; Cortellazzi, Karine Laura; Ambrosano, Gláucia Maria Bovi; Meneghim, Marcelo de Castro; Pereira, Antonio Carlos

2011-10-01

The aim of this study was to evaluate the relationship between malocclusion and self-perception of oral appearance/function, in 12/15-year-old Brazilian adolescents. The cluster sample consisted of 717 teenagers attending 24 urban public (n=611) and 5 rural public (n=107) schools in Maringá/PR. Malocclusion was measured using the Dental Aesthetic Index (DAI), in accordance with WHO recommendations. A parental questionnaire was applied to collect information on esthetic perception level and oral variables related to oral health. Univariate and multiple logistic regression analyses were performed. Multiple logistic regression confirmed that for 12-year-old, missing teeth (OR=2.865) and presence of openbite (open occlusal relationship) (OR=2.865) were risk indicators for speech capability. With regard to 15-year-old, presence of mandibular overjet (horizontal overlap) (OR=4.016) was a risk indicator for speech capability and molar relationship (OR=1.661) was a risk indicator for chewing capability. The impact of malocclusion on adolescents' life was confirmed in this study. Speech and chewing capability were associated with orthodontic deviations, which should be taken into consideration in oral health planning, to identify risk groups and improve community health services.

Socio-demographic correlates of breast-feeding in urban slums of Chandigarh.

PubMed

Kumar, Dinesh; Agarwal, Neeraj; Swami, H M

2006-11-01

Whether socio-demographic factors are associated with initiation of breast-feeding in urban slums of Chandigarh. (1) To study the prevailing breast-feeding practices adopted by mothers, (2) To study the socio-demographic factors associated with initiation of breast-feeding. Cross-sectional. Mothers of infants willing to participate in the study in the selected area. A total of 270 respondents. Social and demographic characteristics like age, socioeconomic status, educational level, birth interval, parity, gender preference, natal care practices, etc.; and variables related to various aspects of breast-feeding practices like prelacteal feed, initiation of feeding, colostrum feeding, reasons of discarding colostrum, etc. Chi-square test and odd ratios along with their respective 95% confidence intervals, multiple logistic regression analysis. Out of all 270 respondents, 159 (58.9%) initiated breast-feeding within 6 h of birth, only 43 (15.9%) discarded colostrum and 108 (40.0%) mothers gave prelacteal feed. Illiterate/just literate mothers who delivered at home were found at significantly higher risk of delay in initiation of breast-feeding on the basis of multiple logistic regression analysis. Promotion of institutional deliveries and imparting health education to mothers for protecting and promoting optimal breast-feeding practices are suggested.

Cannabis use and destructive periodontal diseases among adolescents.

PubMed

López, Rodrigo; Baelum, Vibeke

2009-03-01

The aim of this experiment was to investigate the association between cannabis use and destructive periodontal disease among adolescents. Data from a population screening examination carried out among Chilean high school students from the Province of Santiago were used to determine whether there was an association between the use of cannabis and signs of periodontal diseases as defined by (1) the presence of necrotizing ulcerative gingival (NUG) lesions or (2) the presence of clinical attachment loss (CAL) > or =3 mm. The cannabis exposures variables considered were "Ever use of cannabis" (yes/no) and "Regular use of cannabis" (yes/no). The associations were investigated using multiple logistic regression analyses adjusted for age, gender, paternal income, paternal education, frequency of tooth-brushing and time since last dental visit. Multiple logistic regression analyses showed that "Ever use of cannabis" was significantly negatively associated with the presence of NUG lesions (OR=0.47 [0.2;0.9]) among non-smokers only. No significant associations were observed between the presence of CAL > or =3 mm and cannabis use in either of the smoking groups. There was no evidence to suggest that the use of cannabis is positively associated with periodontal diseases in this adolescent population.

Musculoskeletal disorders among workers in plastic manufacturing plants.

PubMed

Fernandes, Rita de Cássia Pereira; Assunção, Ada Avila; Silvany Neto, Annibal Muniz; Carvalho, Fernando Martins

2010-03-01

Epidemiological studies have indicated an association between musculoskeletal disorders (MSDs) and physical work demands. Psychosocial work demands have also been identified as possible risk factors, but findings have been inconsistent. To evaluate factors associated with upper back, neck and upper limb MSD among workers from 14 plastic manufacturing companies located in the city of Salvador, Brazil. A cross-sectional study design was used to survey a stratified proportional random sample of 577 workers. Data were collected by questionnaire interviews. Factor analysis was carried out on 11 physical demands variables. Psychosocial work demands were measured by demand, control and social support questions. The role of socio-demographic factors, lifestyle and household tasks was also examined. Multiple logistic regression was used to identify factors related to upper back, neck and upper limb MSDs. Results from multiple logistic regression showed that distal upper limb MSDs were related to manual handling, work repetitiveness, psychosocial demands, job dissatisfaction, and gender. Neck, shoulder or upper back MSDs were related to manual handling, work repetitiveness, psychosocial demands, job dissatisfaction, and physical unfitness. Reducing the prevalence of musculoskeletal disorders requires: improving the work environment, reducing biomechanical risk factors, and replanning work organization. Programs must also be aware of gender specificities related to MSDs.

Carbon emissions, logistics volume and GDP in China: empirical analysis based on panel data model.

PubMed

Guo, Xiaopeng; Ren, Dongfang; Shi, Jiaxing

2016-12-01

This paper studies the relationship among carbon emissions, GDP, and logistics by using a panel data model and a combination of statistics and econometrics theory. The model is based on the historical data of 10 typical provinces and cities in China during 2005-2014. The model in this paper adds the variability of logistics on the basis of previous studies, and this variable is replaced by the freight turnover of the provinces. Carbon emissions are calculated by using the annual consumption of coal, oil, and natural gas. GDP is the gross domestic product. The results showed that the amount of logistics and GDP have a contribution to carbon emissions and the long-term relationships are different between different cities in China, mainly influenced by the difference among development mode, economic structure, and level of logistic development. After the testing of panel model setting, this paper established a variable coefficient model of the panel. The influence of GDP and logistics on carbon emissions is obtained according to the influence factors among the variables. The paper concludes with main findings and provides recommendations toward rational planning of urban sustainable development and environmental protection for China.

Impaired executive function can predict recurrent falls in Parkinson's disease.

PubMed

Mak, Margaret K; Wong, Adrian; Pang, Marco Y

2014-12-01

To examine whether impairment in executive function independently predicts recurrent falls in people with Parkinson's disease (PD). Prospective cohort study. University motor control research laboratory. A convenience sample of community-dwelling people with PD (N=144) was recruited from a patient self-help group and movement disorders clinics. Not applicable. Executive function was assessed with the Mattis Dementia Rating Scale Initiation/Perseveration (MDRS-IP) subtest, and fear of falling (FoF) with the Activities-specific Balance Confidence (ABC) Scale. All participants were followed up for 12 months to record the number of monthly fall events. Forty-two people with PD had at least 2 falls during the follow-up period and were classified as recurrent fallers. After accounting for demographic variables and fall history (P=.001), multiple logistic regression analysis showed that the ABC scores (P=.014) and MDRS-IP scores (P=.006) were significantly associated with future recurrent falls among people with PD. The overall accuracy of the prediction was 85.9%. With the use of the significant predictors identified in multiple logistic regression analysis, a prediction model determined by the logistic function was generated: Z = 1.544 + .378 (fall history) - .045 (ABC) - .145 (MDRS-IP). Impaired executive function is a significant predictor of future recurrent falls in people with PD. Participants with executive dysfunction and greater FoF at baseline had a significantly greater risk of sustaining a recurrent fall within the subsequent 12 months. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Analysis of occlusal variables, dental attrition, and age for distinguishing healthy controls from female patients with intracapsular temporomandibular disorders.

PubMed

Seligman, D A; Pullinger, A G

2000-01-01

Confusion about the relationship of occlusion to temporomandibular disorders (TMD) persists. This study attempted to identify occlusal and attrition factors plus age that would characterize asymptomatic normal female subjects. A total of 124 female patients with intracapsular TMD were compared with 47 asymptomatic female controls for associations to 9 occlusal factors, 3 attrition severity measures, and age using classification tree, multiple stepwise logistic regression, and univariate analyses. Models were tested for accuracy (sensitivity and specificity) and total contribution to the variance. The classification tree model had 4 terminal nodes that used only anterior attrition and age. "Normals" were mainly characterized by low attrition levels, whereas patients had higher attrition and tended to be younger. The tree model was only moderately useful (sensitivity 63%, specificity 94%) in predicting normals. The logistic regression model incorporated unilateral posterior crossbite and mediotrusive attrition severity in addition to the 2 factors in the tree, but was slightly less accurate than the tree (sensitivity 51%, specificity 90%). When only occlusal factors were considered in the analysis, normals were additionally characterized by a lack of anterior open bite, smaller overjet, and smaller RCP-ICP slides. The log likelihood accounted for was similar for both the tree (pseudo R(2) = 29.38%; mean deviance = 0.95) and the multiple logistic regression (Cox Snell R(2) = 30.3%, mean deviance = 0.84) models. The occlusal and attrition factors studied were only moderately useful in differentiating normals from TMD patients.

Education level as a predictor of condom use in jail-incarcerated women, with fundamental cause analysis.

PubMed

Emerson, Amanda M; Carroll, Hsiang-Feng; Ramaswamy, Megha

2018-05-27

To model condom usage by jail-incarcerated women incarcerated in US local jails and understand results in terms of fundamental cause theory. We surveyed 102 women in an urban jail in the Midwest United States. Chi-square tests and generalized linear modeling were used to identify factors of significance for women who used condoms during last sex compared with women who did not. Stepwise multiple logistic regression was conducted to estimate the relation between the outcome variable and variables linked to condom use in the literature. Logistic regression showed that for women who completed high school odds of reporting condom use during last sex were 2.78 times higher (p = .043) than the odds for women with less than a high school education. Among women who responded no to ever having had a sexually transmitted infection, odds of using a condom during last sex were 2.597 times (p = .03) higher than odds for women who responded that they had had a sexually transmitted infection. Education is a fundamental cause of reproductive health risk among incarcerated women. We recommend interventions that creatively target distal over proximal factors. © 2018 Wiley Periodicals, Inc.

Contributions of sociodemographic factors to criminal behavior

PubMed Central

Mundia, Lawrence; Matzin, Rohani; Mahalle, Salwa; Hamid, Malai Hayati; Osman, Ratna Suriani

2016-01-01

We explored the extent to which prisoner sociodemographic variables (age, education, marital status, employment, and whether their parents were married or not) influenced offending in 64 randomly selected Brunei inmates, comprising both sexes. A quantitative field survey design ideal for the type of participants used in a prison context was employed to investigate the problem. Hierarchical multiple regression analysis with backward elimination identified prisoner marital status and age groups as significantly related to offending. Furthermore, hierarchical multinomial logistic regression analysis with backward elimination indicated that prisoners’ age, primary level education, marital status, employment status, and parental marital status as significantly related to stealing offenses with high odds ratios. All 29 nonrecidivists were false negatives and predicted to reoffend upon release. Similarly, all 33 recidivists were projected to reoffend after release. Hierarchical binary logistic regression analysis revealed age groups (24–29 years and 30–35 years), employed prisoner, and primary level education as variables with high likelihood trends for reoffending. The results suggested that prisoner interventions (educational, counseling, and psychotherapy) in Brunei should treat not only antisocial personality, psychopathy, and mental health problems but also sociodemographic factors. The study generated offending patterns, trends, and norms that may inform subsequent investigations on Brunei prisoners. PMID:27382342

Factors associated with mouth breathing in children with -developmental -disabilities.

PubMed

de Castilho, Lia Silva; Abreu, Mauro Henrique Nogueira Guimarães; de Oliveira, Renata Batista; Souza E Silva, Maria Elisa; Resende, Vera Lúcia Silva

2016-01-01

To investigate the prevalence and factors associated with mouth breathing among patients with developmental disabilities of a dental service. We analyzed 408 dental records. Mouth breathing was reported by the patients' parents and from direct observation. Other variables were as -follows: history of asthma, bronchitis, palate shape, pacifier use, thumb -sucking, nail biting, use of medications, gastroesophageal reflux, bruxism, gender, age, and diagnosis of the patient. Statistical analysis included descriptive analysis with ratio calculation and multiple logistic regression. Variables with p < 0.25 were included in the model to estimate the adjusted OR (95% CI), calculated by the forward stepwise method. Variables with p ​​< 0.05 were kept in the model. Being male (p = 0.016) and use of centrally acting drugs (p = 0.001) were the variables that remained in the model. Among patients with -developmental disabilities, boys and psychotropic drug users had a greater chance of being mouth breathers. © 2016 Special Care Dentistry Association and Wiley Periodicals, Inc.

Predictive variables for the occurrence of early clinical mastitis in primiparous Holstein cows under field conditions in France.

PubMed Central

Barnouin, J; Chassagne, M

2001-01-01

Holstein heifers from 47 dairy herds in France were enrolled in a field study to determine predictors for clinical mastitis within the first month of lactation. Precalving and calving variables (biochemical, hematological, hygienic, and disease indicators) were collected. Early clinical mastitis (ECM) predictive variables were analyzed by using a multiple logistic regression model (99 cows with ECM vs. 571 without clinical mastitis throughout the first lactation). Two variables were associated with a higher risk of ECM: a) difficult calving and b) medium and high white blood cell (WBC) counts in late gestation. Two prepartum indicators were associated with a lower ECM risk: a) medium and high serum concentrations of immunoglobulin G1 (IgG1) and b) high percentage of eosinophils among white blood cells. Calving difficulty and certain biological blood parameters (IgG1, eosinophils) could represent predictors that would merit further experimental studies, with the aim of designing programs for reducing the risk of clinical mastitis in the first lactation. PMID:11195522

Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Cao, Faxian; Yang, Zhijing; Ren, Jinchang; Ling, Wing-Kuen; Zhao, Huimin; Marshall, Stephen

2017-12-01

Although the sparse multinomial logistic regression (SMLR) has provided a useful tool for sparse classification, it suffers from inefficacy in dealing with high dimensional features and manually set initial regressor values. This has significantly constrained its applications for hyperspectral image (HSI) classification. In order to tackle these two drawbacks, an extreme sparse multinomial logistic regression (ESMLR) is proposed for effective classification of HSI. First, the HSI dataset is projected to a new feature space with randomly generated weight and bias. Second, an optimization model is established by the Lagrange multiplier method and the dual principle to automatically determine a good initial regressor for SMLR via minimizing the training error and the regressor value. Furthermore, the extended multi-attribute profiles (EMAPs) are utilized for extracting both the spectral and spatial features. A combinational linear multiple features learning (MFL) method is proposed to further enhance the features extracted by ESMLR and EMAPs. Finally, the logistic regression via the variable splitting and the augmented Lagrangian (LORSAL) is adopted in the proposed framework for reducing the computational time. Experiments are conducted on two well-known HSI datasets, namely the Indian Pines dataset and the Pavia University dataset, which have shown the fast and robust performance of the proposed ESMLR framework.

A Primer on Logistic Regression.

ERIC Educational Resources Information Center

Woldbeck, Tanya

This paper introduces logistic regression as a viable alternative when the researcher is faced with variables that are not continuous. If one is to use simple regression, the dependent variable must be measured on a continuous scale. In the behavioral sciences, it may not always be appropriate or possible to have a measured dependent variable on a…

Serum osteocalcin is significantly related to indices of obesity and lipid profile in Malaysian men.

PubMed

Chin, Kok-Yong; Ima-Nirwana, Soelaiman; Mohamed, Isa Naina; Ahmad, Fairus; Ramli, Elvy Suhana Mohd; Aminuddin, Amilia; Ngah, Wan Zurinah Wan

2014-01-01

Recent studies revealed a possible reciprocal relationship between the skeletal system and obesity and lipid metabolism, mediated by osteocalcin, an osteoblast-specific protein. This study aimed to validate the relationship between serum osteocalcin and indices of obesity and lipid parameters in a group of Malaysian men. A total of 373 men from the Malaysian Aging Male Study were included in the analysis. Data on subjects' demography, body mass index (BMI), body fat (BF) mass, waist circumference (WC), serum osteocalcin and fasting lipid levels were collected. Bioelectrical impendence (BIA) method was used to estimate BF. Multiple linear and binary logistic regression analyses were performed to analyze the association between serum osteocalcin and the aforementioned variables, with adjustment for age, ethnicity and BMI. Multiple regression results indicated that weight, BMI, BF mass, BF %, WC were significantly and negatively associated with serum osteocalcin (p < 0.001). There was a significant positive association between serum osteocalcin and high density lipoprotein (HDL) cholesterol (p = 0.032). Binary logistic results indicated that subjects with low serum osteocalcin level were more likely to be associated with high BMI (obese and overweight), high BF%, high WC and low HDL cholesterol (p < 0.05). Subjects with high osteocalcin level also demonstrated high total cholesterol level (p < 0.05) but this association was probably driven by high HDL level. These variables were not associated with serum C-terminal of telopeptide crosslinks in the subjects (p > 0.05). Serum osteocalcin is associated with indices of obesity and HDL level in men. These relationships should be validated by a longitudinal study, with comprehensive hormone profile testing.

Prevalence of Dry Eye Syndrome after a Three-Year Exposure to a Clean Room

PubMed Central

2014-01-01

Objective To measure the prevalence of dry eye syndrome (DES) among clean room (relative humidity ≤1%) workers from 2011 to 2013. Methods Three annual DES examinations were performed completely in 352 clean room workers aged 20–40 years who were working at a secondary battery factory. Each examination comprised the tear-film break-up test (TFBUT), Schirmer’s test I, slit-lamp microscopic examination, and McMonnies questionnaire. DES grades were measured using the Delphi approach. The annual examination results were analyzed using a general linear model and post-hoc analysis with repeated-ANOVA (Tukey). Multiple logistic regression was performed using the examination results from 2013 (dependent variable) to analyze the effect of years spent working in the clean room (independent variable). Results The prevalence of DES among these workers was 14.8% in 2011, 27.1% in 2012, and 32.8% in 2013. The TFBUT and McMonnies questionnaire showed that DES grades worsened over time. Multiple logistic regression analysis indicated that the odds ratio for having dry eyes was 1.130 (95% CI 1.012–1.262) according to the findings of the McMonnies questionnaire. Conclusions This 3-year trend suggests that the increased prevalence of DES was associated with longer working hours. To decrease the prevalence of DES, employees should be assigned reasonable working hours with shift assignments that include appropriate break times. Workers should also wear protective eyewear, subdivide their working process to minimize exposure, and utilize preservative-free eye drops. PMID:25339991

Comparative analysis on the probability of being a good payer

NASA Astrophysics Data System (ADS)

Mihova, V.; Pavlov, V.

2017-10-01

Credit risk assessment is crucial for the bank industry. The current practice uses various approaches for the calculation of credit risk. The core of these approaches is the use of multiple regression models, applied in order to assess the risk associated with the approval of people applying for certain products (loans, credit cards, etc.). Based on data from the past, these models try to predict what will happen in the future. Different data requires different type of models. This work studies the causal link between the conduct of an applicant upon payment of the loan and the data that he completed at the time of application. A database of 100 borrowers from a commercial bank is used for the purposes of the study. The available data includes information from the time of application and credit history while paying off the loan. Customers are divided into two groups, based on the credit history: Good and Bad payers. Linear and logistic regression are applied in parallel to the data in order to estimate the probability of being good for new borrowers. A variable, which contains value of 1 for Good borrowers and value of 0 for Bad candidates, is modeled as a dependent variable. To decide which of the variables listed in the database should be used in the modelling process (as independent variables), a correlation analysis is made. Due to the results of it, several combinations of independent variables are tested as initial models - both with linear and logistic regression. The best linear and logistic models are obtained after initial transformation of the data and following a set of standard and robust statistical criteria. A comparative analysis between the two final models is made and scorecards are obtained from both models to assess new customers at the time of application. A cut-off level of points, bellow which to reject the applications and above it - to accept them, has been suggested for both the models, applying the strategy to keep the same Accept Rate as in the current data.

Individuals with Single Versus Multiple Suicide Attempts Over 10 Years of Prospective Follow-Up

PubMed Central

Boisseau, Christina L.; Yen, Shirley; Markowitz, John C.; Grilo, Carlos M.; Sanislow, Charles A.; Shea, M. Tracie; Zanarini, Mary C.; Skodol, Andrew E.; Gunderson, John G.; Morey, Leslie C.; McGlashan, Thomas H.

2012-01-01

Background The study attempted to identify characteristics that differentiate multiple suicide attempters from single attempters in individuals with personality disorders (PDs) and/or major depression. Method Participants were 431 participants enrolled in the Collaborative Longitudinal Study of Personality Disorders from July 1996 to June 2008. Suicide attempts were assessed with the Longitudinal Interval Follow-up Evaluation at 6 and 12 months, then yearly through 10 years. Logistic regression was used to compare single attempters to multiple attempters on Axis I and II psychiatric disorders and personality trait variables. Results Twenty-one percent of participants attempted suicide during the 10 years of observation, with 39 (9.0%) reporting a single suicide attempt and 54 (12.5%) reporting multiple suicide attempts. Although no significant differences in were found in baseline Axis I disorders, multiple attempters were significantly more likely to meet criteria for borderline personality disorder and to have higher impulsivity scores than single attempters. Conclusion These results underscore the importance of considering both personality disorders and traits in the assessment of suicidality. PMID:22995448

Multiple imputation for handling missing outcome data when estimating the relative risk.

PubMed

Sullivan, Thomas R; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-09-06

Multiple imputation is a popular approach to handling missing data in medical research, yet little is known about its applicability for estimating the relative risk. Standard methods for imputing incomplete binary outcomes involve logistic regression or an assumption of multivariate normality, whereas relative risks are typically estimated using log binomial models. It is unclear whether misspecification of the imputation model in this setting could lead to biased parameter estimates. Using simulated data, we evaluated the performance of multiple imputation for handling missing data prior to estimating adjusted relative risks from a correctly specified multivariable log binomial model. We considered an arbitrary pattern of missing data in both outcome and exposure variables, with missing data induced under missing at random mechanisms. Focusing on standard model-based methods of multiple imputation, missing data were imputed using multivariate normal imputation or fully conditional specification with a logistic imputation model for the outcome. Multivariate normal imputation performed poorly in the simulation study, consistently producing estimates of the relative risk that were biased towards the null. Despite outperforming multivariate normal imputation, fully conditional specification also produced somewhat biased estimates, with greater bias observed for higher outcome prevalences and larger relative risks. Deleting imputed outcomes from analysis datasets did not improve the performance of fully conditional specification. Both multivariate normal imputation and fully conditional specification produced biased estimates of the relative risk, presumably since both use a misspecified imputation model. Based on simulation results, we recommend researchers use fully conditional specification rather than multivariate normal imputation and retain imputed outcomes in the analysis when estimating relative risks. However fully conditional specification is not without its shortcomings, and so further research is needed to identify optimal approaches for relative risk estimation within the multiple imputation framework.

Logistic Stick-Breaking Process

PubMed Central

Ren, Lu; Du, Lan; Carin, Lawrence; Dunson, David B.

2013-01-01

A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are more likely to be clustered together. The sticks in the LSBP are realized via multiple logistic regression functions, with shrinkage priors employed to favor contiguous and spatially localized segments. The LSBP is also extended for the simultaneous processing of multiple data sets, yielding a hierarchical logistic stick-breaking process (H-LSBP). The model parameters (atoms) within the H-LSBP are shared across the multiple learning tasks. Efficient variational Bayesian inference is derived, and comparisons are made to related techniques in the literature. Experimental analysis is performed for audio waveforms and images, and it is demonstrated that for segmentation applications the LSBP yields generally homogeneous segments with sharp boundaries. PMID:25258593

Tehran Survey of Potential Risk Factors for Multiple Births.

PubMed

Omani Samani, Reza; Almasi-Hashiani, Amir; Vesali, Samira; Shokri, Fatemeh; Cheraghi, Rezvaneh; Torkestani, Farahnaz; Sepidarkish, Mahdi

2017-10-01

The multiple pregnancy incidence is increasing worldwide. This increased incidence is concerning to the health care system. This study aims to determine the frequency of multiple pregnancy and identify factors that affect this frequency in Tehran, Iran. This cross-sectional study included 5170 mothers in labor between July 6-21, 2015 from 103 hospitals with Obstetrics and Gynecology Wards. The questionnaire used in this study consisted of five parts: demographic characteristics; information related to pregnancy; information related to the infant; information regarding the multiple pregnancy; and information associated with infertility. We recruited 103 trained midwives to collect data related to the questionnaire from eligible participants through an interview and medical records review. Frequencies and odds ratios (OR) for the association between multiple pregnancy and the selected characteristics (maternal age, economic status, history of multiple pregnancy in first-degree relatives, and reproductive history) were computed by multiple logistic regression. Stata software, version 13 (Stata Corp, College Station, TX, USA) was used for all statistical analyses. Multiple pregnancy had a prevalence of 1.48% [95% confidence interval (CI): 1.19-1.85]. After controlling for confounding variables, we observed a significant association between frequency of multiple pregnancy and mother's age (OR=1.04, 95% CI: 1.001-1.09, P=0.044), assisted reproductive technique (ART, OR=6.11, 95% CI: 1.7- 21.97, P=0.006), and history of multiple pregnancy in the mother's family (OR=5.49, 95% CI: 3.55-9.93, P=0.001). The frequency of multiple pregnancy approximated results reported in previous studies in Iran. Based on the results, we observed significantly greater frequency of multiple pregnancy in older women, those with a history of ART, and a history of multiple pregnancy in the mother's family compared to the other variables. Copyright© by Royan Institute. All rights reserved.

Cesarean delivery rates among family physicians versus obstetricians: a population-based cohort study using instrumental variable methods

PubMed Central

Dawe, Russell Eric; Bishop, Jessica; Pendergast, Amanda; Avery, Susan; Monaghan, Kelly; Duggan, Norah; Aubrey-Bassler, Kris

2017-01-01

Background: Previous research suggests that family physicians have rates of cesarean delivery that are lower than or equivalent to those for obstetricians, but adjustments for risk differences in these analyses may have been inadequate. We used an econometric method to adjust for observed and unobserved factors affecting the risk of cesarean delivery among women attended by family physicians versus obstetricians. Methods: This retrospective population-based cohort study included all Canadian (except Quebec) hospital deliveries by family physicians and obstetricians between Apr. 1, 2006, and Mar. 31, 2009. We excluded women with multiple gestations, and newborns with a birth weight less than 500 g or gestational age less than 20 weeks. We estimated the relative risk of cesarean delivery using instrumental-variable-adjusted and logistic regression. Results: The final cohort included 776 299 women who gave birth in 390 hospitals. The risk of cesarean delivery was 27.3%, and the mean proportion of deliveries by family physicians was 26.9% (standard deviation 23.8%). The relative risk of cesarean delivery for family physicians versus obstetricians was 0.48 (95% confidence interval [CI] 0.41-0.56) with logistic regression and 1.27 (95% CI 1.02-1.57) with instrumental-variable-adjusted regression. Interpretation: Our conventional analyses suggest that family physicians have a lower rate of cesarean delivery than obstetricians, but instrumental variable analyses suggest the opposite. Because instrumental variable methods adjust for unmeasured factors and traditional methods do not, the large discrepancy between these estimates of risk suggests that clinical and/or sociocultural factors affecting the decision to perform cesarean delivery may not be accounted for in our database. PMID:29233843

Logistic regression modeling to assess groundwater vulnerability to contamination in Hawaii, USA

NASA Astrophysics Data System (ADS)

Mair, Alan; El-Kadi, Aly I.

2013-10-01

Capture zone analysis combined with a subjective susceptibility index is currently used in Hawaii to assess vulnerability to contamination of drinking water sources derived from groundwater. In this study, we developed an alternative objective approach that combines well capture zones with multiple-variable logistic regression (LR) modeling and applied it to the highly-utilized Pearl Harbor and Honolulu aquifers on the island of Oahu, Hawaii. Input for the LR models utilized explanatory variables based on hydrogeology, land use, and well geometry/location. A suite of 11 target contaminants detected in the region, including elevated nitrate (> 1 mg/L), four chlorinated solvents, four agricultural fumigants, and two pesticides, was used to develop the models. We then tested the ability of the new approach to accurately separate groups of wells with low and high vulnerability, and the suitability of nitrate as an indicator of other types of contamination. Our results produced contaminant-specific LR models that accurately identified groups of wells with the lowest/highest reported detections and the lowest/highest nitrate concentrations. Current and former agricultural land uses were identified as significant explanatory variables for eight of the 11 target contaminants, while elevated nitrate was a significant variable for five contaminants. The utility of the combined approach is contingent on the availability of hydrologic and chemical monitoring data for calibrating groundwater and LR models. Application of the approach using a reference site with sufficient data could help identify key variables in areas with similar hydrogeology and land use but limited data. In addition, elevated nitrate may also be a suitable indicator of groundwater contamination in areas with limited data. The objective LR modeling approach developed in this study is flexible enough to address a wide range of contaminants and represents a suitable addition to the current subjective approach.

[Predicting the outcome in severe injuries: an analysis of 2069 patients from the trauma register of the German Society of Traumatology (DGU)].

PubMed

Rixen, D; Raum, M; Bouillon, B; Schlosser, L E; Neugebauer, E

2001-03-01

On hospital admission numerous variables are documented from multiple trauma patients. The value of these variables to predict outcome are discussed controversially. The aim was the ability to initially determine the probability of death of multiple trauma patients. Thus, a multivariate probability model was developed based on data obtained from the trauma registry of the Deutsche Gesellschaft für Unfallchirurgie (DGU). On hospital admission the DGU trauma registry collects more than 30 variables prospectively. In the first step of analysis those variables were selected, that were assumed to be clinical predictors for outcome from literature. In a second step a univariate analysis of these variables was performed. For all primary variables with univariate significance in outcome prediction a multivariate logistic regression was performed in the third step and a multivariate prognostic model was developed. 2069 patients from 20 hospitals were prospectively included in the trauma registry from 01.01.1993-31.12.1997 (age 39 +/- 19 years; 70.0% males; ISS 22 +/- 13; 18.6% lethality). From more than 30 initially documented variables, the age, the GCS, the ISS, the base excess (BE) and the prothrombin time were the most important prognostic factors to predict the probability of death (P(death)). The following prognostic model was developed: P(death) = 1/1 + e(-[k + beta 1(age) + beta 2(GCS) + beta 3(ISS) + beta 4(BE) + beta 5(prothrombin time)]) where: k = -0.1551, beta 1 = 0.0438 with p < 0.0001, beta 2 = -0.2067 with p < 0.0001, beta 3 = 0.0252 with p = 0.0071, beta 4 = -0.0840 with p < 0.0001 and beta 5 = -0.0359 with p < 0.0001. Each of the five variables contributed significantly to the multifactorial model. These data show that the age, GCS, ISS, base excess and prothrombin time are potentially important predictors to initially identify multiple trauma patients with a high risk of lethality. With the base excess and prothrombin time value, as only variables of this multifactorial model that can be therapeutically influenced, it might be possible to better guide early and aggressive therapy.

[Association of cardiovascular autonomic neuropathy and prolonged QT interval with cardiovascular morbidity and mortality in patients with type 2 diabetes mellitus].

PubMed

Ticse Aguirre, Ray; Villena, Jaime E

2011-03-01

In order to evaluate the relationship between cardiovascular autonomic neuropathy and corrected QT interval (QTc) with cardiovascular morbidity and mortality in patients with type 2 diabetes mellitus, we followed up for 5 years 67 patients attending the outpatient Endocrinology Service. 82% completed follow-up and cardiovascular events occurred in 16 patients. We found that long QTc interval was the only variable significantly associated with cardiovascular morbidity and mortality in the multiple logistic regression analysis (RR: 13.56, 95% CI: 2.01-91.36) (p = 0.0074).

Predicting location of recurrence using FDG, FLT, and Cu-ATSM PET in canine sinonasal tumors treated with radiotherapy

NASA Astrophysics Data System (ADS)

Bradshaw, Tyler; Fu, Rau; Bowen, Stephen; Zhu, Jun; Forrest, Lisa; Jeraj, Robert

2015-07-01

Dose painting relies on the ability of functional imaging to identify resistant tumor subvolumes to be targeted for additional boosting. This work assessed the ability of FDG, FLT, and Cu-ATSM PET imaging to predict the locations of residual FDG PET in canine tumors following radiotherapy. Nineteen canines with spontaneous sinonasal tumors underwent PET/CT imaging with radiotracers FDG, FLT, and Cu-ATSM prior to hypofractionated radiotherapy. Therapy consisted of 10 fractions of 4.2 Gy to the sinonasal cavity with or without an integrated boost of 0.8 Gy to the GTV. Patients had an additional FLT PET/CT scan after fraction 2, a Cu-ATSM PET/CT scan after fraction 3, and follow-up FDG PET/CT scans after radiotherapy. Following image registration, simple and multiple linear and logistic voxel regressions were performed to assess how well pre- and mid-treatment PET imaging predicted post-treatment FDG uptake. R2 and pseudo R2 were used to assess the goodness of fits. For simple linear regression models, regression coefficients for all pre- and mid-treatment PET images were significantly positive across the population (P < 0.05). However, there was large variability among patients in goodness of fits: R2 ranged from 0.00 to 0.85, with a median of 0.12. Results for logistic regression models were similar. Multiple linear regression models resulted in better fits (median R2 = 0.31), but there was still large variability between patients in R2. The R2 from regression models for different predictor variables were highly correlated across patients (R ≈ 0.8), indicating tumors that were poorly predicted with one tracer were also poorly predicted by other tracers. In conclusion, the high inter-patient variability in goodness of fits indicates that PET was able to predict locations of residual tumor in some patients, but not others. This suggests not all patients would be good candidates for dose painting based on a single biological target.

Predicting location of recurrence using FDG, FLT, and Cu-ATSM PET in canine sinonasal tumors treated with radiotherapy.

PubMed

Bradshaw, Tyler; Fu, Rau; Bowen, Stephen; Zhu, Jun; Forrest, Lisa; Jeraj, Robert

2015-07-07

Dose painting relies on the ability of functional imaging to identify resistant tumor subvolumes to be targeted for additional boosting. This work assessed the ability of FDG, FLT, and Cu-ATSM PET imaging to predict the locations of residual FDG PET in canine tumors following radiotherapy. Nineteen canines with spontaneous sinonasal tumors underwent PET/CT imaging with radiotracers FDG, FLT, and Cu-ATSM prior to hypofractionated radiotherapy. Therapy consisted of 10 fractions of 4.2 Gy to the sinonasal cavity with or without an integrated boost of 0.8 Gy to the GTV. Patients had an additional FLT PET/CT scan after fraction 2, a Cu-ATSM PET/CT scan after fraction 3, and follow-up FDG PET/CT scans after radiotherapy. Following image registration, simple and multiple linear and logistic voxel regressions were performed to assess how well pre- and mid-treatment PET imaging predicted post-treatment FDG uptake. R(2) and pseudo R(2) were used to assess the goodness of fits. For simple linear regression models, regression coefficients for all pre- and mid-treatment PET images were significantly positive across the population (P < 0.05). However, there was large variability among patients in goodness of fits: R(2) ranged from 0.00 to 0.85, with a median of 0.12. Results for logistic regression models were similar. Multiple linear regression models resulted in better fits (median R(2) = 0.31), but there was still large variability between patients in R(2). The R(2) from regression models for different predictor variables were highly correlated across patients (R ≈ 0.8), indicating tumors that were poorly predicted with one tracer were also poorly predicted by other tracers. In conclusion, the high inter-patient variability in goodness of fits indicates that PET was able to predict locations of residual tumor in some patients, but not others. This suggests not all patients would be good candidates for dose painting based on a single biological target.

Contrast-Enhanced Ultrasound in the Diagnosis of Gallbladder Diseases: A Multi-Center Experience

PubMed Central

Liu, Lin-Na; Xu, Hui-Xiong; Lu, Ming-De; Xie, Xiao-Yan; Wang, Wen-Ping; Hu, Bing; Yan, Kun; Ding, Hong; Tang, Shao-Shan; Qian, Lin-Xue; Luo, Bao-Ming; Wen, Yan-Ling

2012-01-01

Objective To assess the usefulness of contrast–enhanced ultrasound (CEUS) in differentiating malignant from benign gallbladder (GB) diseases. Methods This study had institutional review board approval. 192 patients with GB diseases from 9 university hospitals were studied. After intravenous bonus injection of a phospholipid-stabilized shell microbubble contrast agent, lesions were scanned with low acoustic power CEUS. A multiple logistic regression analysis was performed to identify diagnostic clues from 17 independent variables that enabled differentiation between malignant and benign GB diseases. Receiver operating characteristic (ROC) curve analysis was performed. Results Among the 17 independent variables, multiple logistic regression analysis showed that the following 4 independent variables were associated with the benign nature of the GB diseases, including the patient age, intralesional blood vessel depicted on CEUS, contrast washout time, and wall intactness depicted on CEUS (all P<0.05). ROC analysis showed that the patient age, intralesional vessels on CEUS, and the intactness of the GB wall depicted on CEUS yielded an area under the ROC curve (Az) greater than 0.8 in each and Az for the combination of the 4 significant independent variables was 0.915 [95% confidence interval (CI): 0.857–0.974]. The corresponding Az, sensitivity, and specificity for the age were 0.805 (95% CI: 0.746–0.863), 92.2%%, and 59.6%; for the intralesional vessels on CEUS were 0.813 (95% CI: 0.751–0.875), 59.8%, and 98.0%; and for the GB wall intactness were 0.857 (95% CI: 0.786–0.928), 78.4%, and 92.9%. The cut-off values for benign GB diseases were patient age <53.5 yrs, dotted intralesional vessels on CEUS and intact GB wall on CEUS. Conclusion CEUS is valuable in differentiating malignant from benign GB diseases. Branched or linear intralesional vessels and destruction of GB wall on CEUS are the CEUS features highly suggestive of GB malignancy and the patient age >53.5 yrs is also a clue for GB malignancy. PMID:23118996

Multiple mating and its relationship to brood size in pregnant fishes versus pregnant mammals and other viviparous vertebrates

PubMed Central

Avise, John C.; Liu, Jin-Xian

2011-01-01

We summarize the literature on rates of multiple paternity and sire numbers per clutch in viviparous fishes vs. mammals, two vertebrate groups in which pregnancy is common but entails very different numbers of embryos (for species surveyed, piscine broods averaged >10-fold larger than mammalian litters). As deduced from genetic parentage analyses, multiple mating by the pregnant sex proved to be common in assayed species but averaged significantly higher in fish than mammals. However, within either of these groups we found no significant correlations between brood size and genetically deduced incidence of multiple mating by females. Overall, these findings offer little support for the hypothesis that clutch size in pregnant species predicts the outcome of selection for multiple mating by brooders. Instead, whatever factors promote multiple mating by members of the gestating sex seem to do so in surprisingly similar ways in live-bearing vertebrates otherwise as different as fish and mammals. Similar conclusions emerged when we extended the survey to viviparous amphibians and reptiles. One notion consistent with these empirical observations is that although several fitness benefits probably accrue from multiple mating, logistical constraints on mate-encounter rates routinely truncate multiple mating far below levels that otherwise could be accommodated, especially in species with larger broods. We develop this concept into a “logistical constraint hypothesis” that may help to explain these mating outcomes in viviparous vertebrates. Under the logistical constraint hypothesis, propensities for multiple mating in each species register a balance between near-universal fitness benefits from multiple mating and species-idiosyncratic logistical limits on polygamy. PMID:21482777

Factors associated with active commuting to work among women.

PubMed

Bopp, Melissa; Child, Stephanie; Campbell, Matthew

2014-01-01

Active commuting (AC), the act of walking or biking to work, has notable health benefits though rates of AC remain low among women. This study used a social-ecological framework to examine the factors associated with AC among women. A convenience sample of employed, working women (n = 709) completed an online survey about their mode of travel to work. Individual, interpersonal, institutional, community, and environmental influences were assessed. Basic descriptive statistics and frequencies described the sample. Simple logistic regression models examined associations with the independent variables with AC participation and multiple logistic regression analysis determined the relative influence of social ecological factors on AC participation. The sample was primarily middle-aged (44.09±11.38 years) and non-Hispanic White (92%). Univariate analyses revealed several individual, interpersonal, institutional, community and environmental factors significantly associated with AC. The multivariable logistic regression analysis results indicated that significant factors associated with AC included number of children, income, perceived behavioral control, coworker AC, coworker AC normative beliefs, employer and community supports for AC, and traffic. The results of this study contribute to the limited body of knowledge on AC participation for women and may help to inform gender-tailored interventions to enhance AC behavior and improve health.

Risk Factors for 30-Day Complications After Thumb CMC Joint Arthroplasty: An American College of Surgeons National Surgery Quality Improvement Program Study.

PubMed

Shah, Kalpit N; Defroda, Steven F; Wang, Bo; Weiss, Arnold-Peter C

2017-12-01

The first carpometacarpal (CMC) joint is a common site of osteoarthritis, with arthroplasty being a common procedure to provide pain relief and improve function with low complications. However, little is known about risk factors that may predispose a patient for postoperative complications. All CMC joint arthroplasty from 2005 to 2015 in the prospectively collected American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database were identified. Bivariate testing and multiple logistic regressions were performed to determine which patient demographics, surgical variables and medical comorbidities were significant predictors for complications. These included wound related, cardiopulmonary, neurological and renal complications, return to the operating room (OR) and readmission. A total of 3344 patients were identified from the database. Of those, 45 patients (1.3%) experienced a complication including wound issues (0.66%), return to the OR (0.15%) and readmission (0.27%) amongst others. When performing bivariate analysis, age over 65, American Society of Anesthesiologists (ASA) Class, diabetes and renal dialysis were significant risk factors. Multiple logistic regression after adjusting for confounding factors demonstrated that insulin-dependent diabetes and ASA Class 4 had a strong trend while renal dialysis was a significant risk factor. CMC arthroplasty has a very low overall complication rate of 1.3% and wound complication rate of 0.66%. Diabetes requiring insulin and ASA Class 4 trended towards significance while renal dialysis was found to be a significant risk factors in logistic regression. This information may be useful for preoperative counseling and discussion with patients who have these risk factors.

[Retinopathy of prematurity in multiple births: risk analysis for plus disease].

PubMed

García-Serrano, J L; Ramírez-García, M C; Piñar-Molina, R

2009-04-01

To analyze the risk factors associated with plus disease in retinopathy of prematurity (ROP). Over a period of 8.5 years we carried out a prospective study of ROP in twins and triplets. Fifty-four multiple-birth infants with low birth weight (< or =1500 g) and low gestational age (32< or = weeks) were admitted to the University Hospital of Granada. Logistic regression analyses showed the following variables to be associated with an increased risk of plus disease: severe ROP, large area of avascular retina, low gestational age, low birth weight, a patent ductus arteriosus, length of mechanical ventilation, adverse events increase, low 5 min Apgar scores and poor postnatal weight gain (in the first 4 to 6 weeks of life). Using multiple logistic regression, only the grade of ROP (OR: 5.5; p < 0.009) and poor postnatal weight gain (OR: 0.58; p < 0.04) were predictive factors of development of plus disease. Infants with disease gained an average 3.9 +/- 3.1 g/day in the first 6 weeks of life, compared to a mean of 11.84 +/- 8.3 g/day for those without plus disease (p < 0.0001). Advanced ROP stages and poor weight gain were the most significant factors associated with plus disease. Twins who gained weight at more than 7 g/day in the first 4-6 weeks of life had a significantly reduced risk of plus disease. A good weight gain is an effective strategy against avoidable blindness due to ROP.

Confounder summary scores when comparing the effects of multiple drug exposures.

PubMed

Cadarette, Suzanne M; Gagne, Joshua J; Solomon, Daniel H; Katz, Jeffrey N; Stürmer, Til

2010-01-01

Little information is available comparing methods to adjust for confounding when considering multiple drug exposures. We compared three analytic strategies to control for confounding based on measured variables: conventional multivariable, exposure propensity score (EPS), and disease risk score (DRS). Each method was applied to a dataset (2000-2006) recently used to examine the comparative effectiveness of four drugs. The relative effectiveness of risedronate, nasal calcitonin, and raloxifene in preventing non-vertebral fracture, were each compared to alendronate. EPSs were derived both by using multinomial logistic regression (single model EPS) and by three separate logistic regression models (separate model EPS). DRSs were derived and event rates compared using Cox proportional hazard models. DRSs derived among the entire cohort (full cohort DRS) was compared to DRSs derived only among the referent alendronate (unexposed cohort DRS). Less than 8% deviation from the base estimate (conventional multivariable) was observed applying single model EPS, separate model EPS or full cohort DRS. Applying the unexposed cohort DRS when background risk for fracture differed between comparison drug exposure cohorts resulted in -7 to + 13% deviation from our base estimate. With sufficient numbers of exposed and outcomes, either conventional multivariable, EPS or full cohort DRS may be used to adjust for confounding to compare the effects of multiple drug exposures. However, our data also suggest that unexposed cohort DRS may be problematic when background risks differ between referent and exposed groups. Further empirical and simulation studies will help to clarify the generalizability of our findings.

Potentially Modifiable Factors Associated With Physical Activity in Individuals With Multiple Sclerosis.

PubMed

Reider, Nadia; Salter, Amber R; Cutter, Gary R; Tyry, Tuula; Marrie, Ruth Ann

2017-04-01

Physical activity levels among persons with multiple sclerosis (MS) are worryingly low. We aimed to identify the factors associated with physical activity for people with MS, with an emphasis on factors that have not been studied previously (bladder and hand dysfunction) and are potentially modifiable. This study was a secondary analysis of data collected in the spring of 2012 during the North American Research Committee on Multiple Sclerosis (NARCOMS) Registry. NARCOMS participants were surveyed regarding smoking using questions from the Behavioral Risk Factor Surveillance Survey; disability using the Patient Determined Disease Steps; fatigue, cognition, spasticity, sensory, bladder, vision and hand function using self-reported Performance Scales; health literacy using the Medical Term Recognition Test; and physical activity using questions from the Health Information National Trends Survey. We used a forward binary logistic regression to develop a predictive model in which physical activity was the outcome variable. Of 8,755 respondents, 1,707 (19.5%) were classified as active and 7,068 (80.5%) as inactive. In logistic regression, being a current smoker, moderate or severe level of disability, depression, fatigue, hand, or bladder dysfunction and minimal to mild spasticity were associated with lower odds of meeting physical activity guidelines. MS type was not linked to activity level. Several modifiable clinical and lifestyle factors influenced physical activity in MS. Prospective studies are needed to evaluate whether modification of these factors can increase physical activity participation in persons with MS. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Determination of riverbank erosion probability using Locally Weighted Logistic Regression

NASA Astrophysics Data System (ADS)

Ioannidou, Elena; Flori, Aikaterini; Varouchakis, Emmanouil A.; Giannakis, Georgios; Vozinaki, Anthi Eirini K.; Karatzas, George P.; Nikolaidis, Nikolaos

2015-04-01

Riverbank erosion is a natural geomorphologic process that affects the fluvial environment. The most important issue concerning riverbank erosion is the identification of the vulnerable locations. An alternative to the usual hydrodynamic models to predict vulnerable locations is to quantify the probability of erosion occurrence. This can be achieved by identifying the underlying relations between riverbank erosion and the geomorphological or hydrological variables that prevent or stimulate erosion. Thus, riverbank erosion can be determined by a regression model using independent variables that are considered to affect the erosion process. The impact of such variables may vary spatially, therefore, a non-stationary regression model is preferred instead of a stationary equivalent. Locally Weighted Regression (LWR) is proposed as a suitable choice. This method can be extended to predict the binary presence or absence of erosion based on a series of independent local variables by using the logistic regression model. It is referred to as Locally Weighted Logistic Regression (LWLR). Logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable (e.g. binary response) based on one or more predictor variables. The method can be combined with LWR to assign weights to local independent variables of the dependent one. LWR allows model parameters to vary over space in order to reflect spatial heterogeneity. The probabilities of the possible outcomes are modelled as a function of the independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. erosion presence or absence) for any value of the independent variables. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested. The most straightforward measure for goodness of fit is the G statistic. It is a simple and effective way to study and evaluate the Logistic Regression model efficiency and the reliability of each independent variable. The developed statistical model is applied to the Koiliaris River Basin on the island of Crete, Greece. Two datasets of river bank slope, river cross-section width and indications of erosion were available for the analysis (12 and 8 locations). Two different types of spatial dependence functions, exponential and tricubic, were examined to determine the local spatial dependence of the independent variables at the measurement locations. The results show a significant improvement when the tricubic function is applied as the erosion probability is accurately predicted at all eight validation locations. Results for the model deviance show that cross-section width is more important than bank slope in the estimation of erosion probability along the Koiliaris riverbanks. The proposed statistical model is a useful tool that quantifies the erosion probability along the riverbanks and can be used to assist managing erosion and flooding events. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

Modelling of binary logistic regression for obesity among secondary students in a rural area of Kedah

NASA Astrophysics Data System (ADS)

Kamaruddin, Ainur Amira; Ali, Zalila; Noor, Norlida Mohd.; Baharum, Adam; Ahmad, Wan Muhamad Amir W.

2014-07-01

Logistic regression analysis examines the influence of various factors on a dichotomous outcome by estimating the probability of the event's occurrence. Logistic regression, also called a logit model, is a statistical procedure used to model dichotomous outcomes. In the logit model the log odds of the dichotomous outcome is modeled as a linear combination of the predictor variables. The log odds ratio in logistic regression provides a description of the probabilistic relationship of the variables and the outcome. In conducting logistic regression, selection procedures are used in selecting important predictor variables, diagnostics are used to check that assumptions are valid which include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers and a test statistic is calculated to determine the aptness of the model. This study used the binary logistic regression model to investigate overweight and obesity among rural secondary school students on the basis of their demographics profile, medical history, diet and lifestyle. The results indicate that overweight and obesity of students are influenced by obesity in family and the interaction between a student's ethnicity and routine meals intake. The odds of a student being overweight and obese are higher for a student having a family history of obesity and for a non-Malay student who frequently takes routine meals as compared to a Malay student.

Estimating interaction on an additive scale between continuous determinants in a logistic regression model.

PubMed

Knol, Mirjam J; van der Tweel, Ingeborg; Grobbee, Diederick E; Numans, Mattijs E; Geerlings, Mirjam I

2007-10-01

To determine the presence of interaction in epidemiologic research, typically a product term is added to the regression model. In linear regression, the regression coefficient of the product term reflects interaction as departure from additivity. However, in logistic regression it refers to interaction as departure from multiplicativity. Rothman has argued that interaction estimated as departure from additivity better reflects biologic interaction. So far, literature on estimating interaction on an additive scale using logistic regression only focused on dichotomous determinants. The objective of the present study was to provide the methods to estimate interaction between continuous determinants and to illustrate these methods with a clinical example. and results From the existing literature we derived the formulas to quantify interaction as departure from additivity between one continuous and one dichotomous determinant and between two continuous determinants using logistic regression. Bootstrapping was used to calculate the corresponding confidence intervals. To illustrate the theory with an empirical example, data from the Utrecht Health Project were used, with age and body mass index as risk factors for elevated diastolic blood pressure. The methods and formulas presented in this article are intended to assist epidemiologists to calculate interaction on an additive scale between two variables on a certain outcome. The proposed methods are included in a spreadsheet which is freely available at: http://www.juliuscenter.nl/additive-interaction.xls.

Advanced colorectal neoplasia risk stratification by penalized logistic regression.

PubMed

Lin, Yunzhi; Yu, Menggang; Wang, Sijian; Chappell, Richard; Imperiale, Thomas F

2016-08-01

Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratification rules for advanced colorectal neoplasia (colorectal cancer and advanced, precancerous polyps). We use a recently completed large cohort study of subjects who underwent a first screening colonoscopy. Logistic regression models have been used in the literature to estimate the risk of advanced colorectal neoplasia based on quantifiable risk factors. However, logistic regression may be prone to overfitting and instability in variable selection. Since most of the risk factors in our study have several categories, it was tempting to collapse these categories into fewer risk groups. We propose a penalized logistic regression method that automatically and simultaneously selects variables, groups categories, and estimates their coefficients by penalizing the [Formula: see text]-norm of both the coefficients and their differences. Hence, it encourages sparsity in the categories, i.e. grouping of the categories, and sparsity in the variables, i.e. variable selection. We apply the penalized logistic regression method to our data. The important variables are selected, with close categories simultaneously grouped, by penalized regression models with and without the interactions terms. The models are validated with 10-fold cross-validation. The receiver operating characteristic curves of the penalized regression models dominate the receiver operating characteristic curve of naive logistic regressions, indicating a superior discriminative performance. © The Author(s) 2013.

Human papillomavirus in oropharyngeal cancer in Canada: analysis of 5 comprehensive cancer centres using multiple imputation

PubMed Central

Habbous, Steven; Chu, Karen P.; Lau, Harold; Schorr, Melissa; Belayneh, Mathieos; Ha, Michael N.; Murray, Scott; O’Sullivan, Brian; Huang, Shao Hui; Snow, Stephanie; Parliament, Matthew; Hao, Desiree; Cheung, Winson Y.; Xu, Wei; Liu, Geoffrey

2017-01-01

BACKGROUND: The incidence of oropharyngeal cancer has risen over the past 2 decades. This rise has been attributed to human papillomavirus (HPV), but information on temporal trends in incidence of HPV-associated cancers across Canada is limited. METHODS: We collected social, clinical and demographic characteristics and p16 protein status (p16-positive or p16-negative, using this immunohistochemistry variable as a surrogate marker of HPV status) for 3643 patients with oropharyngeal cancer diagnosed between 2000 and 2012 at comprehensive cancer centres in British Columbia (6 centres), Edmonton, Calgary, Toronto and Halifax. We used receiver operating characteristic curves and multiple imputation to estimate the p16 status for missing values. We chose a best-imputation probability cut point on the basis of accuracy in samples with known p16 status and through an independent relation between p16 status and overall survival. We used logistic and Cox proportional hazard regression. RESULTS: We found no temporal changes in p16-positive status initially, but there was significant selection bias, with p16 testing significantly more likely to be performed in males, lifetime never-smokers, patients with tonsillar or base-of-tongue tumours and those with nodal involvement (p < 0.05 for each variable). We used the following variables associated with p16-positive status for multiple imputation: male sex, tonsillar or base-of-tongue tumours, smaller tumours, nodal involvement, less smoking and lower alcohol consumption (p < 0.05 for each variable). Using sensitivity analyses, we showed that different imputation probability cut points for p16-positive status each identified a rise from 2000 to 2012, with the best-probability cut point identifying an increase from 47.3% in 2000 to 73.7% in 2012 (p < 0.001). INTERPRETATION: Across multiple centres in Canada, there was a steady rise in the proportion of oropharyngeal cancers attributable to HPV from 2000 to 2012. PMID:28808115

Plasma amino acid profile associated with fatty liver disease and co-occurrence of metabolic risk factors.

PubMed

Yamakado, Minoru; Tanaka, Takayuki; Nagao, Kenji; Imaizumi, Akira; Komatsu, Michiharu; Daimon, Takashi; Miyano, Hiroshi; Tani, Mizuki; Toda, Akiko; Yamamoto, Hiroshi; Horimoto, Katsuhisa; Ishizaka, Yuko

2017-11-03

Fatty liver disease (FLD) increases the risk of diabetes, cardiovascular disease, and steatohepatitis, which leads to fibrosis, cirrhosis, and hepatocellular carcinoma. Thus, the early detection of FLD is necessary. We aimed to find a quantitative and feasible model for discriminating the FLD, based on plasma free amino acid (PFAA) profiles. We constructed models of the relationship between PFAA levels in 2,000 generally healthy Japanese subjects and the diagnosis of FLD by abdominal ultrasound scan by multiple logistic regression analysis with variable selection. The performance of these models for FLD discrimination was validated using an independent data set of 2,160 subjects. The generated PFAA-based model was able to identify FLD patients. The area under the receiver operating characteristic curve for the model was 0.83, which was higher than those of other existing liver function-associated markers ranging from 0.53 to 0.80. The value of the linear discriminant in the model yielded the adjusted odds ratio (with 95% confidence intervals) for a 1 standard deviation increase of 2.63 (2.14-3.25) in the multiple logistic regression analysis with known liver function-associated covariates. Interestingly, the linear discriminant values were significantly associated with the progression of FLD, and patients with nonalcoholic steatohepatitis also exhibited higher values.

Depression in high voltage power line workers.

PubMed

de Souza, Suerda Fortaleza; Carvalho, Fernando Martins; de Araújo, Tânia Maria; Koifman, Sergio; Porto, Lauro Antonio

2012-06-01

To investigate the association between effort-reward imbalance and depressive symptoms among workers in high voltage power lines. A cross-sectional study among 158 workers from an electric power company in Northeast Brazil. The main independent variables were the Effort-Reward Imbalance Model (ERI) dimensions and the main dependent variable was the prevalence of depression, as measured by the Center for Epidemiologic Studies Depression (CES-D) scale. Data were analyzed by multiple logistic regression techniques. The group of low reward workers presented a depression prevalence rate 6.2 times greater than those in the high reward group. The depression prevalence rate was 3.3 greater in workers in the situation of imbalanced effort-reward than in those in effort-reward equilibrium. The prevalence of depression was strongly associated with psychosocial factors present in the work of electricity workers.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Medication adherence among patients in a chronic disease clinic.

PubMed

Tourkmani, Ayla M; Al Khashan, Hisham I; Albabtain, Monirah A; Al Harbi, Turki J; Al Qahatani, Hala B; Bakhiet, Ahmed H

2012-12-01

To assess motivation and knowledge domains of medication adherence intention, and to determine their predictors in an ambulatory setting. We conducted a cross-sectional survey study among patients attending a chronic disease clinic at the Family and Community Medicine Department, Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia between June and September 2010. Adherence intention was assessed using Modified Morisky Scale. Predictors of low motivation and/or knowledge were determined using logistic regression models. A total of 347 patients were interviewed during the study duration. Most patients (75.5%) had 2 or more chronic diseases with an average of 6.3 +/- 2.3 medications, and 6.5 +/- 2.9 pills per prescription. The frequency of adherence intention was low (4.6%), variable (37.2%), and high (58.2%). In multivariate logistic regression analysis, younger age and having asthma were significantly associated with low motivation, while male gender, single status, and not having hypertension were significantly associated with low knowledge. Single status was the only independent predictor of low adherence intention. In a population with multiple chronic diseases and high illiteracy rate, more than 40% had low/variable intention to adhere to prescribed medications. Identifying predictors of this group may help in providing group-specific interventional programs.

Internalized stigma among psychiatric outpatients: Associations with quality of life, functioning, hope and self-esteem.

PubMed

Picco, Louisa; Pang, Shirlene; Lau, Ying Wen; Jeyagurunathan, Anitha; Satghare, Pratika; Abdin, Edimansyah; Vaingankar, Janhavi Ajit; Lim, Susan; Poh, Chee Lien; Chong, Siow Ann; Subramaniam, Mythily

2016-12-30

This study aimed to: (i) determine the prevalence, socio-demographic and clinical correlates of internalized stigma and (ii) explore the association between internalized stigma and quality of life, general functioning, hope and self-esteem, among a multi-ethnic Asian population of patients with mental disorders. This cross-sectional, survey recruited adult patients (n=280) who were seeking treatment at outpatient and affiliated clinics of the only tertiary psychiatric hospital in Singapore. Internalized stigma was measured using the Internalized Stigma of Mental Illness scale. 43.6% experienced moderate to high internalized stigma. After making adjustments in multiple logistic regression analysis, results revealed there were no significant socio-demographic or clinical correlates relating to internalized stigma. Individual logistic regression models found a negative relationship between quality of life, self-esteem, general functioning and internalized stigma whereby lower scores were associated with higher internalized stigma. In the final regression model, which included all psychosocial variables together, self-esteem was the only variable significantly and negatively associated with internalized stigma. The results of this study contribute to our understanding of the role internalized stigma plays in patients with mental illness, and the impact it can have on psychosocial aspects of their lives. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Cardiovascular disease and cognitive dysfunction in systemic lupus erythematosus.

PubMed

Murray, Sara G; Yazdany, Jinoos; Kaiser, Rachel; Criswell, Lindsey A; Trupin, Laura; Yelin, Edward H; Katz, Patricia P; Julian, Laura J

2012-09-01

Cognitive dysfunction and cardiovascular disease are common and debilitating manifestations of systemic lupus erythematosus (SLE). In this study, we evaluated the relationship between cardiovascular events, traditional cardiovascular risk factors, and SLE-specific risk factors as predictors of cognitive dysfunction in a large cohort of participants with SLE. Subjects included 694 participants from the Lupus Outcomes Study (LOS), a longitudinal study of SLE outcomes based on an annual telephone survey querying demographic and clinical variables. The Hopkins Verbal Learning Test-Revised and the Controlled Oral Word Association Test were administered to assess cognitive function. Multiple logistic regression was used to identify cardiovascular events (myocardial infarction, stroke), traditional cardiovascular risk factors (hypertension, hyperlipidemia, diabetes mellitus, obesity, smoking), and SLE-specific risk factors (antiphospholipid antibodies [aPL], disease activity, disease duration) associated with cognitive impairment in year 7 of the LOS. The prevalence of cognitive impairment as measured by verbal memory and verbal fluency metrics was 15%. In adjusted multiple logistic regression analyses, aPL (odds ratio [OR] 2.10, 95% confidence interval [95% CI] 1.3-3.41), hypertension (OR 2.06, 95% CI 1.19-3.56), and a history of stroke (OR 2.27, 95% CI 1.16-4.43) were significantly associated with cognitive dysfunction. In additional analyses evaluating the association between these predictors and severity of cognitive impairment, stroke was significantly more prevalent in participants with severe impairment when compared to those with mild or moderate impairment (P = 0.036). These results suggest that the presence of aPL, hypertension, and stroke are key variables associated with cognitive impairment, which may aid in identification of patients at greatest risk. Copyright © 2012 by the American College of Rheumatology.

Personality, Driving Behavior and Mental Disorders Factors as Predictors of Road Traffic Accidents Based on Logistic Regression.

PubMed

Alavi, Seyyed Salman; Mohammadi, Mohammad Reza; Souri, Hamid; Mohammadi Kalhori, Soroush; Jannatifard, Fereshteh; Sepahbodi, Ghazal

2017-01-01

The aim of this study was to evaluate the effect of variables such as personality traits, driving behavior and mental illness on road traffic accidents among the drivers with accidents and those without road crash. In this cohort study, 800 bus and truck drivers were recruited. Participants were selected among drivers who referred to Imam Sajjad Hospital (Tehran, Iran) during 2013-2015. The Manchester driving behavior questionnaire (MDBQ), big five personality test (NEO personality inventory) and semi-structured interview (schizophrenia and affective disorders scale) were used. After two years, we surveyed all accidents due to human factors that involved the recruited drivers. The data were analyzed using the SPSS software by performing the descriptive statistics, t-test, and multiple logistic regression analysis methods. P values less than 0.05 were considered statistically significant. In terms of controlling the effective and demographic variables, the findings revealed significant differences between the two groups of drivers that were and were not involved in road accidents. In addition, it was found that depression and anxiety could increase the odds ratio (OR) of road accidents by 2.4- and 2.7-folds, respectively (P=0.04, P=0.004). It is noteworthy to mention that neuroticism alone can increase the odds of road accidents by 1.1-fold (P=0.009), but other personality factors did not have a significant effect on the equation. The results revealed that some mental disorders affect the incidence of road collisions. Considering the importance and sensitivity of driving behavior, it is necessary to evaluate multiple psychological factors influencing drivers before and after receiving or renewing their driver's license.

Personality, Driving Behavior and Mental Disorders Factors as Predictors of Road Traffic Accidents Based on Logistic Regression

PubMed Central

Alavi, Seyyed Salman; Mohammadi, Mohammad Reza; Souri, Hamid; Mohammadi Kalhori, Soroush; Jannatifard, Fereshteh; Sepahbodi, Ghazal

2017-01-01

Background: The aim of this study was to evaluate the effect of variables such as personality traits, driving behavior and mental illness on road traffic accidents among the drivers with accidents and those without road crash. Methods: In this cohort study, 800 bus and truck drivers were recruited. Participants were selected among drivers who referred to Imam Sajjad Hospital (Tehran, Iran) during 2013-2015. The Manchester driving behavior questionnaire (MDBQ), big five personality test (NEO personality inventory) and semi-structured interview (schizophrenia and affective disorders scale) were used. After two years, we surveyed all accidents due to human factors that involved the recruited drivers. The data were analyzed using the SPSS software by performing the descriptive statistics, t-test, and multiple logistic regression analysis methods. P values less than 0.05 were considered statistically significant. Results: In terms of controlling the effective and demographic variables, the findings revealed significant differences between the two groups of drivers that were and were not involved in road accidents. In addition, it was found that depression and anxiety could increase the odds ratio (OR) of road accidents by 2.4- and 2.7-folds, respectively (P=0.04, P=0.004). It is noteworthy to mention that neuroticism alone can increase the odds of road accidents by 1.1-fold (P=0.009), but other personality factors did not have a significant effect on the equation. Conclusion: The results revealed that some mental disorders affect the incidence of road collisions. Considering the importance and sensitivity of driving behavior, it is necessary to evaluate multiple psychological factors influencing drivers before and after receiving or renewing their driver’s license. PMID:28293047

Self-reported work ability and work performance in workers with chronic nonspecific musculoskeletal pain.

PubMed

de Vries, Haitze J; Reneman, Michiel F; Groothoff, Johan W; Geertzen, Jan H B; Brouwer, Sandra

2013-03-01

To assess self-reported work ability and work performance of workers who stay at work despite chronic nonspecific musculoskeletal pain (CMP), and to explore which variables were associated with these outcomes. In a cross-sectional study we assessed work ability (Work Ability Index, single item scale 0-10) and work performance (Health and Work Performance Questionnaire, scale 0-10) among 119 workers who continued work while having CMP. Scores of work ability and work performance were categorized into excellent (10), good (9), moderate (8) and poor (0-7). Hierarchical multiple regression and logistic regression analysis was used to analyze the relation of socio-demographic, pain-related, personal- and work-related variables with work ability and work performance. Mean work ability and work performance were 7.1 and 7.7 (poor to moderate). Hierarchical multiple regression analysis revealed that higher work ability scores were associated with lower age, better general health perception, and higher pain self-efficacy beliefs (R(2) = 42 %). Higher work performance was associated with lower age, higher pain self-efficacy beliefs, lower physical work demand category and part-time work (R(2) = 37 %). Logistic regression analysis revealed that work ability ≥8 was significantly explained by age (OR = 0.90), general health perception (OR = 1.04) and pain self-efficacy (OR = 1.15). Work performance ≥8 was explained by pain self-efficacy (OR = 1.11). Many workers with CMP who stay at work report poor to moderate work ability and work performance. Our findings suggest that a subgroup of workers with CMP can stay at work with high work ability and performance, especially when they have high beliefs of pain self-efficacy. Our results further show that not the pain itself, but personal and work-related factors relate to work ability and work performance.

Determinants of postnatal care utilization in urban community among women in Debre Birhan Town, Northern Shewa, Ethiopia.

PubMed

Angore, Banchalem Nega; Tufa, Efrata Girma; Bisetegen, Fithamlak Solomon

2018-04-19

Reducing maternal mortality and improving maternal health care through increased utilization of postnatal care utilization is a global and local priority. However studies that have been carried out in Ethiopia regarding determinants are limited. So This study aims to assess the magnitude of postnatal care utilization and its determinants in Debre Birhan Town, North Ethiopia. A community-based cross-sectional study was conducted from March 1 to April 25, 2015, in Debre Birhan Town. Data were collected through face-to-face interviews using structured pre-tested questionnaires. The data were entered and cleaned in Epi Info version 3.5 and analyzed using SPSS version 20. Bivariate and multiple logistic regression analyses were used. Variable with p value less than or equal to 0.2 at bivariate analysis were entered into multiple logistic regression. Significance was declared at 0.05 in multiple logistic regressions and considered to be an independent factor. From the total respondents, we found that 327 (83.3%) mothers utilized the postnatal care services. Single mothers were less likely to utilize postnatal care services than those mothers who are married and live together [adjusted odds ratio (AOR) = 0.06, 95% CI (0.01, 0.45)]. This study revealed that respondent's knowledge about postnatal care services is an important predictor of postnatal care utilization [AOR = 0.03, 95% CI (0.00, 0.44)] and mothers who delivered in a health care facility were more likely to receive PNC than mothers who did not deliver in a health care facility [AOR = 0.65, 95% CI (0.58, 0.94)]. The postnatal care utilization rate in Debre Birhan town was 83.3%. Marital status, maternal knowledge, and place of delivery were predictors of postnatal care service utilization. So specific attention should be directed towards the improvement of women's education since the perception of the need for PNC services were positively correlated with the mother's education.

Identifying predictors of childhood anaemia in north-east India.

PubMed

Dey, Sanku; Goswami, Sankar; Dey, Tanujit

2013-12-01

The objective of this study is to examine the factors that influence the occurrence of childhood anaemia in North-East India by exploring dataset of the Reproductive and Child Health-II Survey (RCH-II). The study population consisted of 10,137 children in the age-group of 0-6 year(s) from North-East India to explore the predictors of childhood anaemia by means of different background characteristics, such as place of residence, religion, household standard of living, literacy of mother, total children ever born to a mother, age of mother at marriage. Prevalence of anaemia among children was taken as a polytomous variable. The predicted probabilities of anaemia were established via multinomial logistic regression model. These probabilities provided the degree of assessment of the contribution of predictors in the prevalence of childhood anaemia. The mean haemoglobin concentration in children aged 0-6 year(s) was found to be 11.85 g/dL, with a standard deviation of 5.61 g/dL. The multiple logistic regression analysis showed that rural children were at greater risk of severe (OR = 2.035; p = 0.003) and moderate (OR = 1.23; p = 0.003) anaemia. All types of anaemia (severe, moderate, and mild) were more prevalent among Hindu children (OR = 2.971; p = 0.000), (OR = 1.195; p = 0.010), and (OR = 1.201; p = 0.011) than among children of other religions whereas moderate (OR = 1.406; p = 0.001) and mild (OR = 1.857; p=0.000) anaemia were more prevalent among Muslim children. The fecundity of the mother was found to have significant effect on anaemia. Women with multiple children were prone to greater risk of anaemia. The multiple logistic regression analysis also confirmed that children of literate mothers were comparatively at lesser risk of severe anaemia. Mother's age at marriage had a significant effect on anaemia of their children as well.

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.

Developmental Screening Referrals: Child and Family Factors that Predict Referral Completion

ERIC Educational Resources Information Center

Jennings, Danielle J.; Hanline, Mary Frances

2013-01-01

This study researched the predictive impact of developmental screening results and the effects of child and family characteristics on completion of referrals given for evaluation. Logistical and hierarchical logistic regression analyses were used to determine the significance of 10 independent variables on the predictor variable. The number of…

Predicting Social Trust with Binary Logistic Regression

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph; Hufstedler, Shirley

2015-01-01

This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…

Meta-analysis of prediction model performance across multiple studies: Which scale helps ensure between-study normality for the C-statistic and calibration measures?

PubMed

Snell, Kym Ie; Ensor, Joie; Debray, Thomas Pa; Moons, Karel Gm; Riley, Richard D

2017-01-01

If individual participant data are available from multiple studies or clusters, then a prediction model can be externally validated multiple times. This allows the model's discrimination and calibration performance to be examined across different settings. Random-effects meta-analysis can then be used to quantify overall (average) performance and heterogeneity in performance. This typically assumes a normal distribution of 'true' performance across studies. We conducted a simulation study to examine this normality assumption for various performance measures relating to a logistic regression prediction model. We simulated data across multiple studies with varying degrees of variability in baseline risk or predictor effects and then evaluated the shape of the between-study distribution in the C-statistic, calibration slope, calibration-in-the-large, and E/O statistic, and possible transformations thereof. We found that a normal between-study distribution was usually reasonable for the calibration slope and calibration-in-the-large; however, the distributions of the C-statistic and E/O were often skewed across studies, particularly in settings with large variability in the predictor effects. Normality was vastly improved when using the logit transformation for the C-statistic and the log transformation for E/O, and therefore we recommend these scales to be used for meta-analysis. An illustrated example is given using a random-effects meta-analysis of the performance of QRISK2 across 25 general practices.

Recurrent transient ischaemic attack and early risk of stroke: data from the PROMAPA study.

PubMed

Purroy, Francisco; Jiménez Caballero, Pedro Enrique; Gorospe, Arantza; Torres, María José; Alvarez-Sabin, José; Santamarina, Estevo; Martínez-Sánchez, Patricia; Cánovas, David; Freijo, María José; Egido, Jose Antonio; Ramírez-Moreno, Jose M; Alonso-Arias, Arantza; Rodríguez-Campello, Ana; Casado, Ignacio; Delgado-Mederos, Raquel; Martí-Fàbregas, Joan; Fuentes, Blanca; Silva, Yolanda; Quesada, Helena; Cardona, Pere; Morales, Ana; de la Ossa, Natalia Pérez; García-Pastor, Antonio; Arenillas, Juan F; Segura, Tomas; Jiménez, Carmen; Masjuán, Jaime

2013-06-01

Many guidelines recommend urgent intervention for patients with two or more transient ischaemic attacks (TIAs) within 7 days (multiple TIAs) to reduce the early risk of stroke. To determine whether all patients with multiple TIAs have the same high early risk of stroke. Between April 2008 and December 2009, we included 1255 consecutive patients with a TIA from 30 Spanish stroke centres (PROMAPA study). We prospectively recorded clinical characteristics. We also determined the short-term risk of stroke (at 7 and 90 days). Aetiology was categorised using the TOAST (Trial of Org 10172 in Acute Stroke Treatment) classification. Clinical variables and extracranial vascular imaging were available and assessed in 1137/1255 (90.6%) patients. 7-Day and 90-day stroke risk were 2.6% and 3.8%, respectively. Large-artery atherosclerosis (LAA) was confirmed in 190 (16.7%) patients. Multiple TIAs were seen in 274 (24.1%) patients. Duration <1 h (OR=2.97, 95% CI 2.20 to 4.01, p<0.001), LAA (OR=1.92, 95% CI 1.35 to 2.72, p<0.001) and motor weakness (OR=1.37, 95% CI 1.03 to 1.81, p=0.031) were independent predictors of multiple TIAs. The subsequent risk of stroke in these patients at 7 and 90 days was significantly higher than the risk after a single TIA (5.9% vs 1.5%, p<0.001 and 6.8% vs 3.0%, respectively). In the logistic regression model, among patients with multiple TIAs, no variables remained as independent predictors of stroke recurrence. According to our results, multiple TIAs within 7 days are associated with a greater subsequent risk of stroke than after a single TIA. Nevertheless, we found no independent predictor of stroke recurrence among these patients.

Gluten-free is not enough--perception and suggestions of celiac consumers.

PubMed

do Nascimento, Amanda Bagolin; Fiates, Giovanna Medeiros Rataichesck; dos Anjos, Adilson; Teixeira, Evanilda

2014-06-01

The present study investigated the perceptions of individuals with celiac disease about gluten-free (GF) products, their consumer behavior and which product is the most desired. A survey was used to collect information. Descriptive analysis, χ² tests and Multiple Logistic Regressions were conducted. Ninety-one questionnaires were analyzed. Limited variety and availability, the high price of products and the social restrictions imposed by the diet were the factors that caused the most dissatisfaction and difficulty. A total of 71% of the participants confirmed having moderate to high difficulty finding GF products. The logistic regression identified a significant relationship between dissatisfaction, texture and variety (p < 0.05) and between variety and difficulty of finding GF products (p < 0.05). The sensory characteristics were the most important variables considered for actual purchases. Bread was the most desired product. The participants were dissatisfaction with GF products. The desire for bread with better sensory characteristics reinforces the challenge to develop higher quality baking products.

Can additive measures add to an intersectional understanding? Experiences of gay and ethnic discrimination among HIV-positive Latino gay men.

PubMed

Reisen, Carol A; Brooks, Kelly D; Zea, Maria Cecilia; Poppen, Paul J; Bianchi, Fernanda T

2013-04-01

The current study investigated a methodological question of whether traditional, additive, quantitative data can be used to address intersectional issues, and illustrated such an approach with a sample of 301 HIV-positive, Latino gay men in the United States. Participants were surveyed using A-CASI. Hierarchical logistic set regression investigated the role of sets of variables reflecting demographic characteristics, gender nonconformity, and gay and ethnic discrimination in relation to depression and gay collective identity. Results showed the discrimination set was related to depression and to gay collective identity, as was gender nonconformity. Follow-up logistic regression showed that both types of discrimination were associated with greater depression, but gender nonconformity was not. Gay discrimination and gender nonconformity were positively associated with gay collective identity, whereas ethnic discrimination was negatively associated. Results are discussed in terms of the use of traditional quantitative data as a potential means of understanding intersectional issues, as well as of contributing to knowledge about individuals facing multiple structural inequalities.

A simple tool to predict admission at the time of triage.

PubMed

Cameron, Allan; Rodgers, Kenneth; Ireland, Alastair; Jamdar, Ravi; McKay, Gerard A

2015-03-01

To create and validate a simple clinical score to estimate the probability of admission at the time of triage. This was a multicentre, retrospective, cross-sectional study of triage records for all unscheduled adult attendances in North Glasgow over 2 years. Clinical variables that had significant associations with admission on logistic regression were entered into a mixed-effects multiple logistic model. This provided weightings for the score, which was then simplified and tested on a separate validation group by receiving operator characteristic (ROC) analysis and goodness-of-fit tests. 215 231 presentations were used for model derivation and 107 615 for validation. Variables in the final model showing clinically and statistically significant associations with admission were: triage category, age, National Early Warning Score (NEWS), arrival by ambulance, referral source and admission within the last year. The resulting 6-variable score showed excellent admission/discharge discrimination (area under ROC curve 0.8774, 95% CI 0.8752 to 0.8796). Higher scores also predicted early returns for those who were discharged: the odds of subsequent admission within 28 days doubled for every 7-point increase (log odds=+0.0933 per point, p<0.0001). This simple, 6-variable score accurately estimates the probability of admission purely from triage information. Most patients could accurately be assigned to 'admission likely', 'admission unlikely', 'admission very unlikely' etc., by setting appropriate cut-offs. This could have uses in patient streaming, bed management and decision support. It also has the potential to control for demographics when comparing performance over time or between departments. 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.

Risks of falls in subjects with multiple sclerosis.

PubMed

Cattaneo, Davide; De Nuzzo, Carmela; Fascia, Teresa; Macalli, Marco; Pisoni, Ivana; Cardini, Roldano

2002-06-01

To quantify fall risk among patients with multiple sclerosis (MS) and to report the importance of variables associated with falls. Retrospective case-control study design with a 2-group sample of convenience. A hospital and home settings in Italy. A convenience sample of 50 people with MS divided into 2 groups according to their reports of falls. Not applicable. Subjects were assessed with questionnaires for cognitive ability and were measured on their ability to maintain balance, to walk, and to perform daily life activities. Data regarding patients' strength, spasticity, and transfer skills impairment were also collected. No statistical differences were found between groups of fallers and nonfallers using variables pertaining to years after onset, age, gender, and Mini-Mental State Examination. Near statistically significant differences were found in activities of daily living and transfer skills (P<.05). Three variables were associated with fall status: balance, ability to walk, and use of a cane (P<.01). Those variables were analyzed using a logistic regression. The model was able to predict fallers with a sensitivity of 90.9% and a specificity of 58.8%. Variables pertaining to balance skills, gait impairment, and use of a cane differed between fallers and nonfallers groups and the incidence of those variables can be used as a predictive model to quantify fall risk in patients suffering from MS. These findings emphasize the multifactorial nature of falls in this patient population. Assessment of different aspects of motor impairment and the accurate determination of factors contributing to falls are necessary for individual patient management and therapy and for the development of a prevention program for falls. Copyright 2002 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation

Predicting ovarian malignancy: application of artificial neural networks to transvaginal and color Doppler flow US.

PubMed

Biagiotti, R; Desii, C; Vanzi, E; Gacci, G

1999-02-01

To compare the performance of artificial neural networks (ANNs) with that of multiple logistic regression (MLR) models for predicting ovarian malignancy in patients with adnexal masses by using transvaginal B-mode and color Doppler flow ultrasonography (US). A total of 226 adnexal masses were examined before surgery: Fifty-one were malignant and 175 were benign. The data were divided into training and testing subsets by using a "leave n out method." The training subsets were used to compute the optimum MLR equations and to train the ANNs. The cross-validation subsets were used to estimate the performance of each of the two models in predicting ovarian malignancy. At testing, three-layer back-propagation networks, based on the same input variables selected by using MLR (i.e., women's ages, papillary projections, random echogenicity, peak systolic velocity, and resistance index), had a significantly higher sensitivity than did MLR (96% vs 84%; McNemar test, p = .04). The Brier scores for ANNs were significantly lower than those calculated for MLR (Student t test for paired samples, P = .004). ANNs might have potential for categorizing adnexal masses as either malignant or benign on the basis of multiple variables related to demographic and US features.

Dental calculus is associated with death from heart infarction.

PubMed

Söder, Birgitta; Meurman, Jukka H; Söder, Per-Östen

2014-01-01

We studied whether the amount of dental calculus is associated with death from heart infarction in the dental infection-atherosclerosis paradigm. Participants were 1676 healthy young Swedes followed up from 1985 to 2011. At the beginning of the study all subjects underwent oral clinical examination including dental calculus registration scored with calculus index (CI). Outcome measure was cause of death classified according to WHO International Classification of Diseases. Unpaired t-test, Chi-square tests, and multiple logistic regressions were used. Of the 1676 participants, 2.8% had died during follow-up. Women died at a mean age of 61.5 years and men at 61.7 years. The difference in the CI index score between the survivors versus deceased patients was significant by the year 2009 (P < 0.01). In multiple regression analysis of the relationship between death from heart infarction as a dependent variable and CI as independent variable with controlling for age, gender, dental visits, dental plaque, periodontal pockets, education, income, socioeconomic status, and pack-years of smoking, CI score appeared to be associated with 2.3 times the odds ratio for cardiac death. The results confirmed our study hypothesis by showing that dental calculus indeed associated statistically with cardiac death due to infarction.

Variables influencing condom use in a cohort of gay and bisexual men.

PubMed

Valdiserri, R O; Lyter, D; Leviton, L C; Callahan, C M; Kingsley, L A; Rinaldo, C R

1988-07-01

Nine hundred fifty-five of 1,384 (69 per cent) gay and bisexual men enrolled in a prospective study of the natural history of human immunodeficiency virus (HIV) infection who reported engaging in anal intercourse in the past six months were surveyed about condom use practices for both insertive (IAI) and receptive anal intercourse (RAI). The following results were obtained: 23 per cent of the men reported that they always used condoms for IAI and 21 per cent for RAI; 32 per cent sometimes used condoms for IAI; 28 per cent sometimes used condoms for RAI; 45 per cent never used condoms for IAI; and 50 per cent never used condoms for RAI. Multiple logistic regression analysis revealed that the following variables were associated with both insertive and receptive condom use: condom acceptability; a history of multiple and/or anonymous partners in the past six months, and the number of partners with whom one is "high" (drugs/alcohol) during sex. Knowledge of positive HIV serostatus was more strongly associated with receptive than with insertive use. Condom use is a relatively complex health-related behavior, and condom promotion programs should not limit themselves to stressing the dangers of unprotected intercourse.

A cross-sectional study examining multiple mobility device use and fall status among middle-aged and older adults with multiple sclerosis.

PubMed

Finlayson, Marcia L; Peterson, Elizabeth W; Asano, Miho

2014-01-01

To document the prevalence of multiple mobility device use among adults with multiple sclerosis (MS) (≥ 55 years) and examine the association between falls status (faller/non-faller) and the number of mobility devices used. Cross-sectional data generated through telephone interviews with 353 participants was used for this secondary analysis. Descriptive statistics were used to address the first study purpose. Multiple device use was measured by the number of devices used, which ranged from 0 (never use a cane, walker, manual wheelchair, or power wheelchair/scooter) to 4 (use all four mobility devices at least some of the time). Logistic regression analysis was used to address the second purpose, with fall status used as the dependent variable (non-fallers [<1 per year] versus fallers [≥ 1 per year]). Just under 60% of participants reported the use of at least two mobility devices. For each additional mobility device used, the odds of being a faller increased by 1.47 times (95% CI = 1.14-1.90). Multiple mobility device use was common and the greater number of devices used, the greater the likelihood of being a faller. To prevent falls, this association requires further research to determine directionality.

An 8-year study of people with multiple sclerosis in Isfahan, Iran: Association between environmental air pollutants and severity of disease.

PubMed

Ashtari, Fereshte; Esmaeil, Nafiseh; Mansourian, Marjan; Poursafa, Parinaz; Mirmosayyeb, Omid; Barzegar, Mahdi; Pourgheisari, Hajar

2018-06-15

The evidence for an impact of ambient air pollution on the incidence and severity of multiple sclerosis (MS) is still limited. In the present study, we assessed the association between daily air pollution levels and MS prevalence and severity in Isfahan city, Iran. Data related to MS patients has been collected from 2008 to 2016 in a referral university clinic. The air quality index (AQI) data, were collected from 6 monitoring stations of Isfahan department of environment. The distribution map presenting the sites of air pollution monitoring stations as well as the residential address of MS patients was plotted on geographical information system (GIS). An increase in AQI level in four areas of the city (north, west, east and south) was associated with higher expanded disability status scale (EDSS) of MS patients[logistic regression odds ratio = 1.01 (95% CI = 1.008,1.012)]. Moreover, significant inverse association between the complete remission after the first attack with AQI level in total areas [logistic regression odds ratio = 0.987 (95% CI = 0.977, 0.997)] was found in crude model. However, after adjustment for confounding variables through multivariate logistic regression, AQI level was associated with degree of complete remission after first attack 1.005 (95% CI = 1.004, 1.006). The results of our study suggest that air pollution could play a role in the severity and remission of MS disease. However, more detailed studies with considering the complex involvement of different environmental factors including sunlight exposure, diet, depression and vitamin D are needed to determine the outcome of MS. Copyright © 2018 Elsevier B.V. All rights reserved.

Working hours associated with unintentional sleep at work among airline pilots

PubMed Central

Marqueze, Elaine Cristina; Nicola, Ana Carolina B; Diniz, Dag Hammarskjoeld M D; Fischer, Frida Marina

2017-01-01

ABSTRACT OBJECTIVE Tto identify factors associated with unintentional sleep at work of airline pilots. METHODS This is a cross-sectional epidemiological study conducted with 1,235 Brazilian airline pilots, who work national or international flights. Data collection has been performed online. We carried out a bivariate and multiple logistic regression analysis, having as dependent variable unintentional sleep at work. The independent variables were related to biodemographic data, characteristics of the work, lifestyle, and aspects of sleep. RESULTS The prevalence of unintentional sleep while flying the airplane was 57.8%. The factors associated with unintentional sleep at work were: flying for more than 65 hours a month, frequent technical delays, greater need for recovery after work, work ability below optimal, insufficient sleep, and excessive sleepiness. CONCLUSIONS The occurrence of unintentional sleep at work of airline pilots is associated with factors related to the organization of the work and health. PMID:28678902

Model building strategy for logistic regression: purposeful selection.

PubMed

Zhang, Zhongheng

2016-03-01

Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

Obesity and hypomagnesemia.

PubMed

Guerrero-Romero, Fernando; Flores-García, Araceli; Saldaña-Guerrero, Stephanie; Simental-Mendía, Luis E; Rodríguez-Morán, Martha

2016-10-01

Whether low serum magnesium is an epiphenomenon related with obesity or, whether obesity per se is cause of hypomagnesemia, remains to be clarified. To examine the relationship between body weight status and hypomagnesemia in apparently healthy subjects. A total of 681 healthy individuals aged 30 to 65years were enrolled in A cross-sectional study. Extreme exercise, chronic diarrhea, alcohol intake, use of diuretics, smoking, oral magnesium supplementation, diabetes, malnutrition, hypertension, liver disease, thyroid disorders, and renal damage were exclusion criteria. Based in the Body Mass Index (BMI), body weight status was defined as follows: normal weight (BMI <25kg/m 2 ); overweight (BMI ≥25<30 BMIkg/m 2 ); and obesity (BMI ≥30kg/m 2 ). Hypomagnesemia was defined by serum magnesium concentration ≤0.74mmol/L. A multiple logistic regression analysis was used to compute the odds ratio (OR) between body weight status (independent variables) and hypomagnesemia (dependent variable). The multivariate logistic regression analysis showed that dietary magnesium intake (OR 2.11; 95%CI 1.4-5.7) but no obesity (OR 1.53; 95%CI 0.9-2.5), overweight (OR 1.40; 95%CI 0.8-2.4), and normal weight (OR 0.78; 95%CI 0.6-2.09) were associated with hypomagnesemia. A subsequent logistic regression analysis adjusted by body mass index, waist circumference, total body fat, systolic and diastolic blood pressure, and triglycerides levels showed that hyperglycemia (2.19; 95%CI 1.1-7.0) and dietary magnesium intake (2.21; 95%CI 1.1-8.9) remained associated with hypomagnesemia. Our results show that body weight status is not associated with hypomagnesemia and that, irrespective of obesity, hyperglycemia is cause of hypomagnesemia in non-diabetic individuals. Copyright © 2016 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Sleep variability and fatigue in adolescents: Associations with school-related features.

PubMed

Matos, M G; Gaspar, T; Tomé, G; Paiva, T

2016-10-01

This study aims to evaluate the influences of sleep duration and sleep variability (SleepV), upon adolescents' school-related situations. The Health Behaviour in School-Aged Children (HBSC) survey is based on a self-completed questionnaire. The participants were 3164 pupils (53.7% girls), attending the 8th and 10th grades, 14.9 years old, and were inquired about subjective sleep duration during the week and weekends, SleepV, fatigue, difficulties in sleep initiation, school achievement, feelings towards schools, pressure with school work and skipping classes. Multiple regression models used, as dependent variables: (a) school achievement, (b) disliking school, (c) pressure with school work and (d) skipping classes, using as independent variables, each of the remaining school-related variables, fatigue, total sleep duration and difficulties in sleep initiation. The average sleep duration in the week and during weekdays was lower than recommended for these age groups, and almost half of students had high SleepV between weekdays and weekends. A logistic model revealed that the absence of SleepV was associated with lower perception of school work pressure, less frequent skipping classes, more infrequent fatigue and more infrequent difficulties in sleep initiation. Poor sleep quality, SleepV and insufficient sleep duration affected negatively school-related variables. © 2015 International Union of Psychological Science.

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.

Missing data treatments matter: an analysis of multiple imputation for anterior cervical discectomy and fusion procedures.

PubMed

Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Cui, Jonathan J; Basques, Bryce A; Albert, Todd J; Grauer, Jonathan N

2018-04-09

The presence of missing data is a limitation of large datasets, including the National Surgical Quality Improvement Program (NSQIP). In addressing this issue, most studies use complete case analysis, which excludes cases with missing data, thus potentially introducing selection bias. Multiple imputation, a statistically rigorous approach that approximates missing data and preserves sample size, may be an improvement over complete case analysis. The present study aims to evaluate the impact of using multiple imputation in comparison with complete case analysis for assessing the associations between preoperative laboratory values and adverse outcomes following anterior cervical discectomy and fusion (ACDF) procedures. This is a retrospective review of prospectively collected data. Patients undergoing one-level ACDF were identified in NSQIP 2012-2015. Perioperative adverse outcome variables assessed included the occurrence of any adverse event, severe adverse events, and hospital readmission. Missing preoperative albumin and hematocrit values were handled using complete case analysis and multiple imputation. These preoperative laboratory levels were then tested for associations with 30-day postoperative outcomes using logistic regression. A total of 11,999 patients were included. Of this cohort, 63.5% of patients had missing preoperative albumin and 9.9% had missing preoperative hematocrit. When using complete case analysis, only 4,311 patients were studied. The removed patients were significantly younger, healthier, of a common body mass index, and male. Logistic regression analysis failed to identify either preoperative hypoalbuminemia or preoperative anemia as significantly associated with adverse outcomes. When employing multiple imputation, all 11,999 patients were included. Preoperative hypoalbuminemia was significantly associated with the occurrence of any adverse event and severe adverse events. Preoperative anemia was significantly associated with the occurrence of any adverse event, severe adverse events, and hospital readmission. Multiple imputation is a rigorous statistical procedure that is being increasingly used to address missing values in large datasets. Using this technique for ACDF avoided the loss of cases that may have affected the representativeness and power of the study and led to different results than complete case analysis. Multiple imputation should be considered for future spine studies. Copyright © 2018 Elsevier Inc. All rights reserved.

Secondhand Smoking Is Associated with Poor Mental Health in Korean Adolescents.

PubMed

Bang, Inho; Jeong, Young-Jin; Park, Young-Yoon; Moon, Na-Yeon; Lee, Junyong; Jeon, Tae-Hee

2017-08-01

In Korea, the prevalence of depression is increasing in adolescents and the most common cause of death of adolescents has been reported as suicide. At a time of increasing predicament of mental health of adolescents, there are few studies on whether secondhand smoking is associated with mental health in adolescents. The objective of this study was to determine whether exposure to secondhand smoke is associated with mental health-related variables, such as depression, stress, and suicide, in Korean adolescents. Data from the eleventh Korea youth risk behavior web-based survey, a nationally representative survey of 62,708 participants (30,964 males and 31,744 females), were analyzed. For students of aged 12 to 18 years, extensive data including secondhand smoking, mental health, sociodemographic variables, and physical health were collected. Chi-square analysis, multiple logistic regression analysis and ordered logistic regression analysis were performed to estimate the association and dose-response relation between secondhand smoking and mental health. Compared with the non-exposed group, the odds ratios (OR) of depression, stress, suicidal ideation, suicidal planning and suicidal attempt in the secondhand smoking exposed group were 1.339, 1.192, 1.303, 1.437 and 1.505, respectively (all P < 0.001). When subjects were classified into two secondhand smoke exposure groups, with increasing secondhand smoking experience, higher was the OR for each mental health related variable, in a dose-response relation. Our findings suggest that secondhand smoking is associated with poor mental health such as depression, stress, and suicide, showing a dose-response relation in Korean adolescents.

Logistic regression modeling to assess groundwater vulnerability to contamination in Hawaii, USA.

PubMed

Mair, Alan; El-Kadi, Aly I

2013-10-01

Capture zone analysis combined with a subjective susceptibility index is currently used in Hawaii to assess vulnerability to contamination of drinking water sources derived from groundwater. In this study, we developed an alternative objective approach that combines well capture zones with multiple-variable logistic regression (LR) modeling and applied it to the highly-utilized Pearl Harbor and Honolulu aquifers on the island of Oahu, Hawaii. Input for the LR models utilized explanatory variables based on hydrogeology, land use, and well geometry/location. A suite of 11 target contaminants detected in the region, including elevated nitrate (>1 mg/L), four chlorinated solvents, four agricultural fumigants, and two pesticides, was used to develop the models. We then tested the ability of the new approach to accurately separate groups of wells with low and high vulnerability, and the suitability of nitrate as an indicator of other types of contamination. Our results produced contaminant-specific LR models that accurately identified groups of wells with the lowest/highest reported detections and the lowest/highest nitrate concentrations. Current and former agricultural land uses were identified as significant explanatory variables for eight of the 11 target contaminants, while elevated nitrate was a significant variable for five contaminants. The utility of the combined approach is contingent on the availability of hydrologic and chemical monitoring data for calibrating groundwater and LR models. Application of the approach using a reference site with sufficient data could help identify key variables in areas with similar hydrogeology and land use but limited data. In addition, elevated nitrate may also be a suitable indicator of groundwater contamination in areas with limited data. The objective LR modeling approach developed in this study is flexible enough to address a wide range of contaminants and represents a suitable addition to the current subjective approach. © 2013 Elsevier B.V. All rights reserved.

Cognitive and physical functions related to the level of supervision and dependence in the toileting of stroke patients.

PubMed

Sato, Atsushi; Okuda, Yutaka; Fujita, Takaaki; Kimura, Norihiko; Hoshina, Noriyuki; Kato, Sayaka; Tanaka, Shigenari

2016-01-01

This study aimed to clarify which cognitive and physical factors are associated with the need for toileting assistance in stroke patients and to calculate cut-off values for discriminating between independent supervision and dependent toileting ability. This cross-sectional study included 163 first-stroke patients in nine convalescent rehabilitation wards. Based on their FIM Ⓡ instrument score for toileting, the patients were divided into an independent-supervision group and a dependent group. Multiple logistic regression analysis and receiver operating characteristic analysis were performed to identify factors related to toileting performance. The Minimental State Examination (MMSE); the Stroke Impairment Assessment Set (SIAS) score for the affected lower limb, speech, and visuospatial functions; and the Functional Assessment for Control of Trunk (FACT) were analyzed as independent variables. The multiple logistic regression analysis showed that the FIM Ⓡ instrument score for toileting was associated with the SIAS score for the affected lower limb function, MMSE, and FACT. On receiver operating characteristic analysis, the SIAS score for the affected lower limb function cut-off value was 8/7 points, the MMSE cut-off value was 25/24 points, and the FACT cut-off value was 14/13 points. Affected lower limb function, cognitive function, and trunk function were related with the need for toileting assistance. These cut-off values may be useful for judging whether toileting assistance is needed in stroke patients.

Assessing landslide susceptibility by statistical data analysis and GIS: the case of Daunia (Apulian Apennines, Italy)

NASA Astrophysics Data System (ADS)

Ceppi, C.; Mancini, F.; Ritrovato, G.

2009-04-01

This study aim at the landslide susceptibility mapping within an area of the Daunia (Apulian Apennines, Italy) by a multivariate statistical method and data manipulation in a Geographical Information System (GIS) environment. Among the variety of existing statistical data analysis techniques, the logistic regression was chosen to produce a susceptibility map all over an area where small settlements are historically threatened by landslide phenomena. By logistic regression a best fitting between the presence or absence of landslide (dependent variable) and the set of independent variables is performed on the basis of a maximum likelihood criterion, bringing to the estimation of regression coefficients. The reliability of such analysis is therefore due to the ability to quantify the proneness to landslide occurrences by the probability level produced by the analysis. The inventory of dependent and independent variables were managed in a GIS, where geometric properties and attributes have been translated into raster cells in order to proceed with the logistic regression by means of SPSS (Statistical Package for the Social Sciences) package. A landslide inventory was used to produce the bivariate dependent variable whereas the independent set of variable concerned with slope, aspect, elevation, curvature, drained area, lithology and land use after their reductions to dummy variables. The effect of independent parameters on landslide occurrence was assessed by the corresponding coefficient in the logistic regression function, highlighting a major role played by the land use variable in determining occurrence and distribution of phenomena. Once the outcomes of the logistic regression are determined, data are re-introduced in the GIS to produce a map reporting the proneness to landslide as predicted level of probability. As validation of results and regression model a cell-by-cell comparison between the susceptibility map and the initial inventory of landslide events was performed and an agreement at 75% level achieved.

Selecting risk factors: a comparison of discriminant analysis, logistic regression and Cox's regression model using data from the Tromsø Heart Study.

PubMed

Brenn, T; Arnesen, E

1985-01-01

For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.

The Overall Odds Ratio as an Intuitive Effect Size Index for Multiple Logistic Regression: Examination of Further Refinements

ERIC Educational Resources Information Center

Le, Huy; Marcus, Justin

2012-01-01

This study used Monte Carlo simulation to examine the properties of the overall odds ratio (OOR), which was recently introduced as an index for overall effect size in multiple logistic regression. It was found that the OOR was relatively independent of study base rate and performed better than most commonly used R-square analogs in indexing model…

Risk factors for indications of intraoperative blood transfusion among patients undergoing surgical treatment for colorectal adenocarcinoma.

PubMed

Gonçalves, Iara; Linhares, Marcelo; Bordin, Jose; Matos, Delcio

2009-01-01

Identification of risk factors for requiring transfusions during surgery for colorectal cancer may lead to preventive actions or alternative measures, towards decreasing the use of blood components in these procedures, and also rationalization of resources use in hemotherapy services. This was a retrospective case-control study using data from 383 patients who were treated surgically for colorectal adenocarcinoma at 'Fundação Pio XII', in Barretos-SP, Brazil, between 1999 and 2003. To recognize significant risk factors for requiring intraoperative blood transfusion in colorectal cancer surgical procedures. Univariate analyses were performed using Fisher's exact test or the chi-squared test for dichotomous variables and Student's t test for continuous variables, followed by multivariate analysis using multiple logistic regression. In the univariate analyses, height (P = 0.06), glycemia (P = 0.05), previous abdominal or pelvic surgery (P = 0.031), abdominoperineal surgery (P<0.001), extended surgery (P<0.001) and intervention with radical intent (P<0.001) were considered significant. In the multivariate analysis using logistic regression, intervention with radical intent (OR = 10.249, P<0.001, 95% CI = 3.071-34.212) and abdominoperineal amputation (OR = 3.096, P = 0.04, 95% CI = 1.445-6.623) were considered to be independently significant. This investigation allows the conclusion that radical intervention and the abdominoperineal procedure in the surgical treatment of colorectal adenocarcinoma are risk factors for requiring intraoperative blood transfusion.

A simple measure of cognitive reserve is relevant for cognitive performance in MS patients.

PubMed

Della Corte, Marida; Santangelo, Gabriella; Bisecco, Alvino; Sacco, Rosaria; Siciliano, Mattia; d'Ambrosio, Alessandro; Docimo, Renato; Cuomo, Teresa; Lavorgna, Luigi; Bonavita, Simona; Tedeschi, Gioacchino; Gallo, Antonio

2018-05-04

Cognitive reserve (CR) contributes to preserve cognition despite brain damage. This theory has been applied to multiple sclerosis (MS) to explain the partial relationship between cognition and MRI markers of brain pathology. Our aim was to determine the relationship between two measures of CR and cognition in MS. One hundred and forty-seven MS patients were enrolled. Cognition was assessed using the Rao's Brief Repeatable Battery and the Stroop Test. CR was measured as the vocabulary subtest of the WAIS-R score (VOC) and the number of years of formal education (EDU). Regression analysis included raw score data on each neuropsychological (NP) test as dependent variables and demographic/clinical parameters, VOC, and EDU as independent predictors. A binary logistic regression analysis including clinical/CR parameters as covariates and absence/presence of cognitive deficits as dependent variables was performed too. VOC, but not EDU, was strongly correlated with performances at all ten NP tests. EDU was correlated with executive performances. The binary logistic regression showed that only the Expanded Disability Status Scale (EDSS) and VOC were independently correlated with the presence/absence of CD. The lower the VOC and/or the higher the EDSS, the higher the frequency of CD. In conclusion, our study supports the relevance of CR in subtending cognitive performances and the presence of CD in MS patients.

Logistic Regression: Concept and Application

ERIC Educational Resources Information Center

Cokluk, Omay

2010-01-01

The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

The use of generalised additive models (GAM) in dentistry.

PubMed

Helfenstein, U; Steiner, M; Menghini, G

1997-12-01

Ordinary multiple regression and logistic multiple regression are widely applied statistical methods which allow a researcher to 'explain' or 'predict' a response variable from a set of explanatory variables or predictors. In these models it is usually assumed that quantitative predictors such as age enter linearly into the model. During recent years these methods have been further developed to allow more flexibility in the way explanatory variables 'act' on a response variable. The methods are called 'generalised additive models' (GAM). The rigid linear terms characterising the association between response and predictors are replaced in an optimal way by flexible curved functions of the predictors (the 'profiles'). Plotting the 'profiles' allows the researcher to visualise easily the shape by which predictors 'act' over the whole range of values. The method facilitates detection of particular shapes such as 'bumps', 'U-shapes', 'J-shapes, 'threshold values' etc. Information about the shape of the association is not revealed by traditional methods. The shapes of the profiles may be checked by performing a Monte Carlo simulation ('bootstrapping'). After the presentation of the GAM a relevant case study is presented in order to demonstrate application and use of the method. The dependence of caries in primary teeth on a set of explanatory variables is investigated. Since GAMs may not be easily accessible to dentists, this article presents them in an introductory condensed form. It was thought that a nonmathematical summary and a worked example might encourage readers to consider the methods described. GAMs may be of great value to dentists in allowing visualisation of the shape by which predictors 'act' and obtaining a better understanding of the complex relationships between predictors and response.

Patient characteristics associated with multiple pharmacy use in the U.S. population: Findings from the Medical Expenditure Panel Survey.

PubMed

Look, Kevin A

2015-01-01

Multiple pharmacy use (MPU) is an important safety and quality issue, as it results in fragmented patient care. However, few studies have examined patient characteristics predicting the use of multiple pharmacies, and the findings have been inconsistent. To identify patient characteristics associated with MPU using national data. Data were obtained from the 2011 U.S. Medical Expenditure Panel Survey. The dependent variable was MPU, or the use of more than one pharmacy. The Andersen Behavioral Model of Health Service Use was used to guide the selection of independent variables, which were categorized as predisposing, enabling, and medical need related characteristics. Multivariable logistic regression analysis was conducted to identify the relationships between predisposing, enabling, and need variables and MPU in a hierarchical fashion. Point estimates were weighted to the U.S. non-institutionalized population, and to adjust standard errors to account for the complex survey design. MPU was common, with a national prevalence of 41.3%. Individuals aged 40-64 and adults 65 and older were significantly less likely to use multiple pharmacies as patients aged 18-39 years (40-64 years OR: 0.67, CI: 0.58-0.77; ≥65 years OR: 0.49, CI: 0.41-0.58). Females were significantly more likely to use multiple pharmacies than males (OR: 1.16, CI: 1.05-1.29). Individuals lacking health insurance were more likely to use multiple pharmacies as individuals with private health insurance (OR: 1.42, CI: 1.16-1.73); in contrast, individuals having drug insurance were more likely to use multiple pharmacies (OR: 1.25, CI: 1.06-1.47) relative to those without drug insurance. Any mail order use was the strongest predictor of MPU (OR: 6.94, CI: 5.90-8.18). Pharmacists and other health care providers need to be aware that their patients may be using multiple pharmacies, especially younger patients, those lacking access to health insurance, or those using mail order pharmacies. The findings from this study can be used to identify patients that may need additional monitoring to ensure safe and appropriate drug therapy, and has important implications as health care continues to shift toward performance-based reimbursement and quality ratings. Copyright © 2015 Elsevier Inc. All rights reserved.

Bacteremia in nonneutropenic pediatric oncology patients with central venous catheters in the ED.

PubMed

Moskalewicz, Risha L; Isenalumhe, Leidy L; Luu, Cindy; Wee, Choo Phei; Nager, Alan L

2017-01-01

To examine clinical characteristics associated with bacteremia in febrile nonneutropenic pediatric oncology patients with central venous catheters (CVCs) in the emergency department (ED). Fever is the primary reason pediatric oncology patients present to the ED. The literature states that 0.9% to 39% of febrile nonneutropenic oncology patients are bacteremic, yet few studies have investigated infectious risk factors in this population. This was a retrospective cohort study in a pediatric ED, reviewing medical records from 2002 to 2014. Inclusion criteria were patients with cancer, temperature at least 38°C, presence of a CVC, absolute neutrophil count greater than 500 cells/μL, and age less than 22 years. Exclusion criteria were repeat ED visits within 72 hours, bloodwork results not reported by the laboratory, and patients without oncologic history documented at the study hospital. The primary outcome measure is a positive blood culture (+BC). Other variables include age, sex, CVC type, cancer diagnosis, absolute neutrophil count, vital signs, upper respiratory infection (URI) symptoms, and amount of intravenous (IV) normal saline (NS) administered in the ED. Data were analyzed using descriptive statistics and a multiple logistic regression model. A total of 1322 ED visits were sampled, with 534 enrolled, and 39 visits had +BC (7.3%). Variables associated with an increased risk of +BC included the following: absence of URI symptoms (odds ratio [OR], 2.30; 95% CI, 1.13-4.69), neuroblastoma (OR, 3.65; 95% CI, 1.47-9.09), "other" cancer diagnosis (OR, 4.56; 95% CI, 1.93-10.76), tunneled externalized CVC (OR, 5.04; 95% CI, 2.25-11.28), and receiving at least 20 mL/kg IV NS (OR, 2.34; 95% CI, 1.2-4.55). The results of a multiple logistic regression model also showed these variables to be associated with +BC. The absence of URI symptoms, presence of an externalized CVC, neuroblastoma or other cancer diagnosis, and receiving at least 20 mL/kg IV NS in the ED are associated with increased risk of bacteremia in nonneutropenic pediatric oncology patients with a CVC. Copyright © 2016 Elsevier Inc. All rights reserved.

Bayesian adjustment for measurement error in continuous exposures in an individually matched case-control study.

PubMed

Espino-Hernandez, Gabriela; Gustafson, Paul; Burstyn, Igor

2011-05-14

In epidemiological studies explanatory variables are frequently subject to measurement error. The aim of this paper is to develop a Bayesian method to correct for measurement error in multiple continuous exposures in individually matched case-control studies. This is a topic that has not been widely investigated. The new method is illustrated using data from an individually matched case-control study of the association between thyroid hormone levels during pregnancy and exposure to perfluorinated acids. The objective of the motivating study was to examine the risk of maternal hypothyroxinemia due to exposure to three perfluorinated acids measured on a continuous scale. Results from the proposed method are compared with those obtained from a naive analysis. Using a Bayesian approach, the developed method considers a classical measurement error model for the exposures, as well as the conditional logistic regression likelihood as the disease model, together with a random-effect exposure model. Proper and diffuse prior distributions are assigned, and results from a quality control experiment are used to estimate the perfluorinated acids' measurement error variability. As a result, posterior distributions and 95% credible intervals of the odds ratios are computed. A sensitivity analysis of method's performance in this particular application with different measurement error variability was performed. The proposed Bayesian method to correct for measurement error is feasible and can be implemented using statistical software. For the study on perfluorinated acids, a comparison of the inferences which are corrected for measurement error to those which ignore it indicates that little adjustment is manifested for the level of measurement error actually exhibited in the exposures. Nevertheless, a sensitivity analysis shows that more substantial adjustments arise if larger measurement errors are assumed. In individually matched case-control studies, the use of conditional logistic regression likelihood as a disease model in the presence of measurement error in multiple continuous exposures can be justified by having a random-effect exposure model. The proposed method can be successfully implemented in WinBUGS to correct individually matched case-control studies for several mismeasured continuous exposures under a classical measurement error model.

Vehicle coordinated transportation dispatching model base on multiple crisis locations

NASA Astrophysics Data System (ADS)

Tian, Ran; Li, Shanwei; Yang, Guoying

2018-05-01

Many disastrous events are often caused after unconventional emergencies occur, and the requirements of disasters are often different. It is difficult for a single emergency resource center to satisfy such requirements at the same time. Therefore, how to coordinate the emergency resources stored by multiple emergency resource centers to various disaster sites requires the coordinated transportation of emergency vehicles. In this paper, according to the problem of emergency logistics coordination scheduling, based on the related constraints of emergency logistics transportation, an emergency resource scheduling model based on multiple disasters is established.

Is Adolescent Poly-tobacco Use Associated with Alcohol and Other Drug Use?

PubMed Central

Creamer, MeLisa R.; Portillo, Gabriela V.; Clendennen, Stephanie L.; Perry, Cheryl L.

2016-01-01

Objectives To examine associations between current multiple tobacco product use, and current use of alcohol and marijuana, binge drinking, and lifetime use of marijuana, alcohol, and other drugs among US high school students. Methods Using 2013 Youth Risk Behavior Survey data (N = 13,583 high school students), logistic regression analyses were conducted to determine if single tobacco product or multiple tobacco product users are more likely to engage in other risk behaviors than zero tobacco product users, controlling for demographic variables. Results Overall, 23% of the sample used tobacco products and 10% of students reported current use of at least 2 tobacco products. Among single tobacco product users, the odds for engaging in risk behaviors ranged from 3.3 to 9.9 compared to non-tobacco users (p < .0001). Among multiple tobacco product users, the odds ranged from 1.5 to 4.7 (p < .01) compared to single tobacco product users. Conclusions Results suggest dual users are significantly more likely to engage in risk behavior than non-users and single product users. Future interventions should consider identifying dual-users as at higher risk, and targeting multiple risk behaviors. PMID:26685820

Occlusal factors are not related to self-reported bruxism.

PubMed

Manfredini, Daniele; Visscher, Corine M; Guarda-Nardini, Luca; Lobbezoo, Frank

2012-01-01

To estimate the contribution of various occlusal features of the natural dentition that may identify self-reported bruxers compared to nonbruxers. Two age- and sex-matched groups of self-reported bruxers (n = 67) and self-reported nonbruxers (n = 75) took part in the study. For each patient, the following occlusal features were clinically assessed: retruded contact position (RCP) to intercuspal contact position (ICP) slide length (< 2 mm was considered normal), vertical overlap (< 0 mm was considered an anterior open bite; > 4 mm, a deep bite), horizontal overlap (> 4 mm was considered a large horizontal overlap), incisor dental midline discrepancy (< 2 mm was considered normal), and the presence of a unilateral posterior crossbite, mediotrusive interferences, and laterotrusive interferences. A multiple logistic regression model was used to identify the significant associations between the assessed occlusal features (independent variables) and self-reported bruxism (dependent variable). Accuracy values to predict self-reported bruxism were unacceptable for all occlusal variables. The only variable remaining in the final regression model was laterotrusive interferences (P = .030). The percentage of explained variance for bruxism by the final multiple regression model was 4.6%. This model including only one occlusal factor showed low positive (58.1%) and negative predictive values (59.7%), thus showing a poor accuracy to predict the presence of self-reported bruxism (59.2%). This investigation suggested that the contribution of occlusion to the differentiation between bruxers and nonbruxers is negligible. This finding supports theories that advocate a much diminished role for peripheral anatomical-structural factors in the pathogenesis of bruxism.

Identification of the need for home visiting nurse: development of a new assessment tool.

PubMed

Taguchi, Atsuko; Nagata, Satoko; Naruse, Takashi; Kuwahara, Yuki; Yamaguchi, Takuhiro; Murashima, Sachiyo

2014-01-01

To develop a Home Visiting Nursing Service Need Assessment Form (HVNS-NAF) to standardize the decision about the need for home visiting nursing service. The sample consisted of older adults who had received coordinated services by care managers. We defined the need for home visiting nursing service by elderly individuals as the decision of the need by a care manager so that the elderly can continue to live independently. Explanatory variables included demographic factors, medical procedure, severity of illness, and caregiver variables. Multiple logistic regression was carried out after univariate analyses to decide the variables to include and the weight of each variable in the HVNS-NAF. We then calculated the sensitivity and specificity of each cutoff value, and defined the score with the highest sensitivity and specificity as the cutoff value. Nineteen items were included in the final HVNS-NAF. When the cutoff value was 2 points, the sensitivity was 77.0%, specificity 68.5%, and positive predictive value 56.8%. HVNS-NAF is the first validated standard based on characteristics of elderly clients who required home visiting nursing service. Using the HVNS-NAF may result in reducing the unmet need for home visiting nursing service and preventing hospitalization.

Suicide attempters examined in a Parisian Emergency Department: Contrasting characteristics associated with multiple suicide attempts or with the motive to die.

PubMed

Perquier, Florence; Duroy, David; Oudinet, Camille; Maamar, Alya; Choquet, Christophe; Casalino, Enrique; Lejoyeux, Michel

2017-07-01

Among patients examined after a suicide attempt in a Parisian emergency department, we aimed to compare individual characteristics of i) first time and multiple suicide attempters, ii) attempters whose principal motive was "to die" and attempters who had any other motive. Information regarding sociodemographics, clinical characteristics, prior mental health care and outgoing referral was collected in 168 suicide attempters using a standardized form. Associations of these variables with suicide attempt repetition (yes or no) and with the motive underlying the attempt (to die or not) were examined using descriptive statistics and multivariable logistic regression models. Multiple attempters were more likely to have no occupation and to report previous mental health care: mental health follow-up, psychiatric medication or psychiatric hospitalization. The motive to die was not associated with the risk of multiple suicide attempts but related to past suicidal ideation and to some specific precipitating factors, including psychiatric disorder. Patients who intended to die were also more likely to be referred to inpatient than to outpatient psychiatric care. Multiple attempters and attempters who desire to die might represent two distinct high-risk groups regarding clinical characteristics and care pathways. They would probably not benefit from the same intervention strategies. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Econometric analysis on the impact of macroeconomic variables toward financial performance: A case of Malaysian public listed logistics companies

NASA Astrophysics Data System (ADS)

Zakariah, Sahidah; Pyeman, Jaafar; Ghazali, Rahmat; Rahman, Ibrahim A.; Rashid, Ahmad Husni Mohd; Shamsuddin, Sofian

2014-12-01

The primary concern of this study is to analyse the impact against macroeconomic variables upon the financial performance, particularly in the case of public listed logistics companies in Malaysia. This study incorporated five macroeconomic variables and four proxies of financial performance. The macroeconomic variables selected are gross domestic product (GDP), total trade (XM), foreign direct investment (FDI), inflation rate (INF), and interest rate (INT). This study is extended to the usage of ratio analysis to predict financial performance in relation to the changes upon macroeconomic variables. As such, this study selected four (4) ratios as proxies to financial performance, which is Operating Profit Margin (OPM), Net Profit Margin (NPM), Return on Asset (ROA), Return on Equity (ROE). The findings of this study may appear non-controversial to some, but it resulted in the following important consensus; (1) GDP is found to be highly impacting NPM and least of ROA, (2) XM has high positive impact on OPM and least on ROE, (3) FDI appear to have insignificant impact towards NPM, and (4) INF and INT show similar negative impact on financial performance, precisely highly negative on OPM and least on ROA. Such findings also conform to the local logistic industry settings, specifically in regards to public listed logistics companies in relation to its financial performance.

Parent’s Socioeconomic Status, Adolescents’ Disposable Income, and Adolescents’ Smoking Status in Massachusetts

PubMed Central

Soteriades, Elpidoforos S.; DiFranza, Joseph R.

2003-01-01

Objectives. This study examined the association between parental socioeconomic status (SES) and adolescent smoking. Methods. We conducted telephone interviews with a probability sample of 1308 Massachusetts adolescents aged 12 to 17 years. We used multiple-variable-adjusted logistic regression models. Results. The risk of adolescent smoking increased by 28% with each step down in parental education and increased by 30% for each step down in parental household income. These associations persisted after adjustment for age, sex, race/ethnicity, and adolescent disposable income. Parental smoking status was a mediator of these associations. Conclusions. Parental SES is inversely associated with adolescent smoking. Parental smoking is a mediator but does not fully explain the association. PMID:12835202

Knowledge, Attitudes, and Substance Use Practices Among Street Children in Western Kenya

PubMed Central

Embleton, Lonnie; Ayuku, David; Atwoli, Lukoye; Vreeman, Rachel; Braitstein, Paula

2013-01-01

The study describes the knowledge of and attitudes toward substance use among street-involved youth in Kenya, and how they relate to their substance use practices. In 2011, 146 children and youth ages 10–19 years, classified as either children on the street or children of the street were recruited to participate in a cross-sectional survey in Eldoret, Kenya. Bivariate analysis using χ2 or Fisher’s Exact Test was used to test the associations between variables, and multiple logistic regression analysis was used to identify independent covariates associated with lifetime and current drug use. The study’s limitations and source of funding are noted. PMID:22780841

Battered police: risk factors for violence against law enforcement officers.

PubMed

Covington, Michele W; Huff-Corzine, Lin; Corzine, Jay

2014-01-01

Although we hear more about violence committed by the police, violence against police officers is also a major problem in the United States. Using data collected from the Orlando, Florida Police Department files, this study examines situational variables, offender characteristics, and officer demographics that may correlate with violence directed at law enforcement officers. Logistic regression results indicate that battery against one or more police officers is significantly more likely when multiple officers are involved, when offenders are women, when offenders are larger than average as measured by body mass index (BMI), and when offenders are known to have recently consumed alcohol. We close with a discussion of policy implications and directions for future research.

Factors Associated with Clinician Participation in TF-CBT Post-workshop Training Components.

PubMed

Pemberton, Joy R; Conners-Burrow, Nicola A; Sigel, Benjamin A; Sievers, Chad M; Stokes, Lauren D; Kramer, Teresa L

2017-07-01

For proficiency in an evidence-based treatment (EBT), mental health professionals (MHPs) need training activities extending beyond a one-time workshop. Using data from 178 MHPs participating in a statewide TF-CBT dissemination project, we used five variables assessed at the workshop, via multiple and logistic regression, to predict participation in three post-workshop training components. Perceived in-workshop learning and client-treatment mismatch were predictive of consultation call participation and case presentation respectively. Attitudes toward EBTs were predictive of trauma assessment utilization, although only with non-call participants removed from analysis. Productivity requirements and confidence in TF-CBT skills were not associated with participation in post-workshop activities.

Shared decision making and serious mental illness.

PubMed

Mahone, Irma H

2008-12-01

This study examined medication decision making by 84 persons with serious mental illness, specifically examining relationships among perceived coercion, decisional capacity, preferences for involvement and actual participation, and the outcomes of medication adherence and quality of life (QoL). Multiple and logistic regression analysis were used in this cross-sectional, descriptive study, controlling for demographic, socioeconomic, and utilization variables. Appreciation was positively related to medication adherence behaviors for the past 6 months. Women, older individuals, and those living independently were more likely to have taken all their medications over the past 6 months. Neither client participation, preference, nor preference-participation agreement was found to be associated with better medication adherence or QoL.

Using Logistic Regression to Predict the Probability of Debris Flows in Areas Burned by Wildfires, Southern California, 2003-2006

USGS Publications Warehouse

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.; Michael, John A.; Helsel, Dennis R.

2008-01-01

Logistic regression was used to develop statistical models that can be used to predict the probability of debris flows in areas recently burned by wildfires by using data from 14 wildfires that burned in southern California during 2003-2006. Twenty-eight independent variables describing the basin morphology, burn severity, rainfall, and soil properties of 306 drainage basins located within those burned areas were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows soon after the 2003 to 2006 fires were delineated from data in the National Elevation Dataset using a geographic information system; (2) Data describing the basin morphology, burn severity, rainfall, and soil properties were compiled for each basin. These data were then input to a statistics software package for analysis using logistic regression; and (3) Relations between the occurrence or absence of debris flows and the basin morphology, burn severity, rainfall, and soil properties were evaluated, and five multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combinations produced the most effective models, and the multivariate models that best predicted the occurrence of debris flows were identified. Percentage of high burn severity and 3-hour peak rainfall intensity were significant variables in all models. Soil organic matter content and soil clay content were significant variables in all models except Model 5. Soil slope was a significant variable in all models except Model 4. The most suitable model can be selected from these five models on the basis of the availability of independent variables in the particular area of interest and field checking of probability maps. The multivariate logistic regression models can be entered into a geographic information system, and maps showing the probability of debris flows can be constructed in recently burned areas of southern California. This study demonstrates that logistic regression is a valuable tool for developing models that predict the probability of debris flows occurring in recently burned landscapes.

Multidimensional poverty and health: evidence from a nationwide survey in Japan.

PubMed

Oshio, Takashi; Kan, Mari

2014-12-19

It is well known that lower income is associated with poorer health, but poverty has several dimensions other than income. In the current study, we investigated the associations between multidimensional poverty and health variables. Using micro data obtained from a nationwide population survey in Japan (N = 24,905), we focused on four dimensions of poverty (income, education, social protection, and housing conditions) and three health variables (self-rated health (SRH), psychological distress, and current smoking). We examined how health variables were associated with multidimensional poverty measures, based on descriptive and multivariable logistic regression analyses. Unions as composite measures of multiple poverty dimensions were more useful for identifying individuals in poor SRH or psychological distress than a single dimension such as income. In comparison, intersections of poverty dimensions reduced the coverage of individuals considered to be in poverty and tend to be difficult to justify without any explicit policy objective. Meanwhile, education as a unidimensional poverty indicator could be useful for predicting current smoking. Results obtained from the current study confirmed the practical relevance of multidimensional poverty for health.

The goalkeeper influence on ball possession effectiveness in futsal

PubMed Central

Lago-Peñas, Carlos

2016-01-01

Abstract The aim of this study was to identify which variables were the best predictors of success in futsal ball possession when controlling for space and task related indicators, situational variables and the participation of the goalkeeper as a regular field player or not (5 vs. 4 or 4 vs. 4). The sample consisted of 326 situations of ball possession corresponding to 31 matches played by a team from the Spanish Futsal League during the 2010–2011, 2011–2012 and 2012–2013 seasons. Multidimensional qualitative data obtained from 10 ordered categorical variables were used. Data were analysed using chi-square analysis and multiple logistic regression analysis. Overall, the highest ball possession effectiveness was achieved when the goalkeeper participated as a regular field player (p<0.01), the duration of the ball possession was less than 10 s (p<0.01), the ball possession ended in the penalty area (p<0.01) and the defensive pressure was low (p<0.01). The information obtained on the relative effectiveness of offensive playing tactics can be used to improve team’s goal-scoring and goal preventing abilities. PMID:28149385

Cumulative traumas and psychosis: an analysis of the national comorbidity survey and the British Psychiatric Morbidity Survey.

PubMed

Shevlin, Mark; Houston, James E; Dorahy, Martin J; Adamson, Gary

2008-01-01

Previous research has shown that traumatic life events are associated with a diagnosis of psychosis. Rather than focus on particular events, this study aimed to estimate the effect of cumulative traumatic experiences on psychosis. The study was based on 2 large community samples (The National Comorbidity Survey [NCS], The British Psychiatric Morbidity Survey [BPMS]). All analyses were conducted using hierarchical binary logistic regression, with psychosis diagnosis as the dependent variable. Background demographic variables were included in the first block, in addition to alcohol/drug dependence and depression. A variable indicating the number of traumas experienced was entered in the second block. Experiencing 2 or more trauma types significantly predicted psychosis, and there appeared to be a dose-response type relationship. Particular traumatic experiences have been implicated in the etiology of psychosis. Consistent with previous research, molestation and physical abuse were significant predictors of psychosis using the NCS, whereas for the BPMS, serious injury or assault and violence in the home were statistically significant. This study indicated the added risk of multiple traumatic experiences.

Cumulative Traumas and Psychosis: an Analysis of the National Comorbidity Survey and the British Psychiatric Morbidity Survey

PubMed Central

Shevlin, Mark; Houston, James E.; Dorahy, Martin J.; Adamson, Gary

2008-01-01

Previous research has shown that traumatic life events are associated with a diagnosis of psychosis. Rather than focus on particular events, this study aimed to estimate the effect of cumulative traumatic experiences on psychosis. The study was based on 2 large community samples (The National Comorbidity Survey [NCS], The British Psychiatric Morbidity Survey [BPMS]). All analyses were conducted using hierarchical binary logistic regression, with psychosis diagnosis as the dependent variable. Background demographic variables were included in the first block, in addition to alcohol/drug dependence and depression. A variable indicating the number of traumas experienced was entered in the second block. Experiencing 2 or more trauma types significantly predicted psychosis, and there appeared to be a dose-response type relationship. Particular traumatic experiences have been implicated in the etiology of psychosis. Consistent with previous research, molestation and physical abuse were significant predictors of psychosis using the NCS, whereas for the BPMS, serious injury or assault and violence in the home were statistically significant. This study indicated the added risk of multiple traumatic experiences. PMID:17586579

Multinomial logistic regression in workers' health

NASA Astrophysics Data System (ADS)

Grilo, Luís M.; Grilo, Helena L.; Gonçalves, Sónia P.; Junça, Ana

2017-11-01

In European countries, namely in Portugal, it is common to hear some people mentioning that they are exposed to excessive and continuous psychosocial stressors at work. This is increasing in diverse activity sectors, such as, the Services sector. A representative sample was collected from a Portuguese Services' organization, by applying a survey (internationally validated), which variables were measured in five ordered categories in Likert-type scale. A multinomial logistic regression model is used to estimate the probability of each category of the dependent variable general health perception where, among other independent variables, burnout appear as statistically significant.

Suicidal ideation among suburban adolescents: The influence of school bullying and other mediating risk factors.

PubMed

Lardier, David T; Barrios, Veronica R; Garcia-Reid, Pauline; Reid, Robert J

2016-10-01

Prior research has identified multiple factors that influence suicidal ideation (SI) among bullied youth. The effects of school bullying on SI cannot be considered in isolation. In this study, we examined the influence of school bullying on SI, through a constellation of risks, which include depressive and anxiety symptoms, family conflict, and alcohol, tobacco, and other drug (ATOD) use. We also provide recommendations for therapists working with bullied youth. Our sample consisted of 488 adolescents (ages 10-18 years) from a northern New Jersey, United States suburban community. Students were recruited through the district's physical education and health classes. Students responded to multiple measures, which included family cohesion/conflict, ATOD use, mental health indicators, SI, and school bullying experiences. Following preliminary analyses, several logistic regression models were used to assess the direct influence of bullying on SI, as well as the unique effects of family conflict, depressive and anxiety symptoms, and substance use. In addition, a parallel multiple mediating model with the PROCESS macro in SPSS was used to further assess mediating effects. Logistic regression results indicated that school bullying increased the odds of SI among males and females and that when mediating variables were added to the model, bullying no longer had a significant influence on SI. Overall, these results display that for both males and females, school bullying was a significant contributor to SI. Results from the parallel multiple mediating model further illustrated the mediating effects that family conflict, depression, and ATOD use had between bullying and SI. Some variation was noted based on gender. This study draws attention to the multiple experiences associated with school bullying on SI, and how these results may differ by gender. The results of this study are particularly important for those working directly and indirectly with bullied youth. Therapists that engage bullied youth need to consider the multiple spheres of influence that may increase SI among male and female clients. To holistically and adequately assess SI among bullied youth, therapists must also consider how these mechanisms vary between gender groups.

Sensitivity study of Space Station Freedom operations cost and selected user resources

NASA Technical Reports Server (NTRS)

Accola, Anne; Fincannon, H. J.; Williams, Gregory J.; Meier, R. Timothy

1990-01-01

The results of sensitivity studies performed to estimate probable ranges for four key Space Station parameters using the Space Station Freedom's Model for Estimating Space Station Operations Cost (MESSOC) are discussed. The variables examined are grouped into five main categories: logistics, crew, design, space transportation system, and training. The modification of these variables implies programmatic decisions in areas such as orbital replacement unit (ORU) design, investment in repair capabilities, and crew operations policies. The model utilizes a wide range of algorithms and an extensive trial logistics data base to represent Space Station operations. The trial logistics data base consists largely of a collection of the ORUs that comprise the mature station, and their characteristics based on current engineering understanding of the Space Station. A nondimensional approach is used to examine the relative importance of variables on parameters.

Methods for identifying SNP interactions: a review on variations of Logic Regression, Random Forest and Bayesian logistic regression.

PubMed

Chen, Carla Chia-Ming; Schwender, Holger; Keith, Jonathan; Nunkesser, Robin; Mengersen, Kerrie; Macrossan, Paula

2011-01-01

Due to advancements in computational ability, enhanced technology and a reduction in the price of genotyping, more data are being generated for understanding genetic associations with diseases and disorders. However, with the availability of large data sets comes the inherent challenges of new methods of statistical analysis and modeling. Considering a complex phenotype may be the effect of a combination of multiple loci, various statistical methods have been developed for identifying genetic epistasis effects. Among these methods, logic regression (LR) is an intriguing approach incorporating tree-like structures. Various methods have built on the original LR to improve different aspects of the model. In this study, we review four variations of LR, namely Logic Feature Selection, Monte Carlo Logic Regression, Genetic Programming for Association Studies, and Modified Logic Regression-Gene Expression Programming, and investigate the performance of each method using simulated and real genotype data. We contrast these with another tree-like approach, namely Random Forests, and a Bayesian logistic regression with stochastic search variable selection.

[Metabolic syndrome in workers of a second level hospital].

PubMed

Mathiew-Quirós, Alvaro; Salinas-Martínez, Ana María; Hernández-Herrera, Ricardo Jorge; Gallardo-Vela, José Alberto

2014-01-01

People with metabolic syndrome (20-25 % of the world population) are three times more likely to suffer a heart attack or stroke and twice as likely to die from this cause. The objective of this study was to assess the prevalence of metabolic syndrome in workers of a second level hospital. This was a cross-sectional study with 160 healthcare workers in Monterrey, México. Sociodemographic, anthropometric and biochemical data were obtained to assess the prevalence of metabolic syndrome. Bivariate and multiple logistic regression analysis were carried out in order to assess the relationship between metabolic syndrome and sociodemographic and occupational variables. The prevalence of metabolic syndrome among workers was 38.1 %. Nurses were more affected with 32.8 %. Overweight and obesity were prevalent in 78 %. In the logistic regression there was a significant association between metabolic syndrome and not having partner (OR 3.98, 95 % CI [1.54-10.25]) and obesity (OR 4.69, 95 % CI [1.73-12.73]). The prevalence of metabolic syndrome and obesity is alarming. Appropriate and prompt actions must be taken in order to reduce the risk of cardiovascular disease in this population.

Neuroanatomy of pseudobulbar affect : a quantitative MRI study in multiple sclerosis.

PubMed

Ghaffar, Omar; Chamelian, Laury; Feinstein, Anthony

2008-03-01

Pseudobulbar affect (PBA) is defined as episodes of involuntary crying, laughing, or both in the absence of a matching subjective mood state. This neuropsychiatric syndrome can be found in a number of neurological disorders including multiple sclerosis (MS). The aim of this study was to identify neuroanatomical correlates of PBA in multiple sclerosis (MS) using a case-control 1.5T MRI study. MS patients with (n = 14) and without (n = 14) PBA were matched on demographic, disease course, and disability variables. Comorbid psychiatric disorders including depressive and anxiety disorders were absent. Hypo- and hyperintense lesion volumes plus measurements of atrophy were obtained and localized anatomically according to parcellated brain regions. Between-group statistical comparisons were undertaken with alpha set at 0.01 for the primary analysis. Discrete differences in lesion volume were noted in six regions: Brainstem hypointense lesions, bilateral inferior parietal and medial inferior frontal hyperintense lesions, and right medial superior frontal hyperintense lesions were all significantly higher in the PBA group. A logistic regression model identified four of these variables (brainstem hypointense, left inferior parietal hyperintense, and left and right medial inferior frontal hyperintense lesion volumes) that accounted for 70% of the variance when it came to explaining the presence of PBA. In conclusion, MS patients with PBA have a distinct distribution of brain lesions when compared to a matched MS sample without PBA. The lesion data support a widely-dispersed neural network involving frontal, parietal, and brainstem regions in the pathophysiology of PBA.

The mental health impact of 9/11 on inner-city high school students 20 miles north of Ground Zero.

PubMed

Calderoni, Michele E; Alderman, Elizabeth M; Silver, Ellen J; Bauman, Laurie J

2006-07-01

To determine the rate of post-traumatic stress disorder (PTSD) after 9/11 in a sample of New York City high school students and associations among personal exposure, loss of psychosocial resources, prior mental health treatment, and PTSD. A total of 1214 students (grades 9 through 12) attending a large community high school in Bronx County, 20 miles north of "Ground Zero," completed a 45-item questionnaire during gym class on one day eight months after 9/11. Students were primarily Hispanic (62%) and African American (29%) and lived in the surrounding neighborhood. The questionnaire included the PCL-T, a 17-item PTSD checklist supplied by the Office of Behavioral and Social Science Research of the National Institutes of Health (NIH). The PCL-T was scored following the DSM-IV criteria for PTSD requiring endorsement of at least one repeating symptom, two hyperarousal symptoms, and three avoidance symptoms. Bivariate analysis comparing PTSD with personal exposure, loss of psychosocial resources, and mental health variables was done and multiple logistic regression was used to identify significant associations. There were 7.4 % of students with the PTSD symptom cluster. Bivariate analysis showed a trend for females to have higher rates of PTSD (males [6%] vs. females [9%], p = .06] with no overall ethnic differences. Five of the six personal exposure variables, and both of the loss of psychosocial resources and mental health variables were significantly associated with PTSD symptom cluster. Multiple logistic regression analysis found one personal exposure variable (having financial difficulties after 9/11, odds ratio [OR] = 5.27; 95% confidence interval [CI] 2.9-9.7); both the loss of psychosocial resources variables (currently feeling less safe, OR = 3.58; 95% CI 1.9-6.8) and currently feeling less protected by the government, (OR = 4.04; 95% CI 2.1-7.7); and one mental health variable (use of psychotropic medication before 9/11, OR = 3.95; 95% CI 1.2-13.0) were significantly associated with PTSD symptom cluster. We found a rate of PTSD in Bronx students after 9/11 that was much higher than other large studies of PTSD in adolescents done before 9/11. Adolescents living in inner cities with high poverty and violence rates may be at high risk for PTSD after a terrorist attack. Students who still felt vulnerable and less safe eight months later and those with prior mental health treatment were four times more likely to have PTSD than those without such characteristics, highlighting the influence of personality and mental health on development of PTSD after a traumatic event.

Air pollution by particulate matter PM10 may trigger multiple sclerosis relapses.

PubMed

Roux, Jonathan; Bard, Denis; Le Pabic, Estelle; Segala, Claire; Reis, Jacques; Ongagna, Jean-Claude; de Sèze, Jérôme; Leray, Emmanuelle

2017-07-01

Seasonal variation of relapses in multiple sclerosis (MS) suggests that season-dependent factors, such as ambient air pollution, may trigger them. However, only few studies have considered possible role of air pollutants as relapse's risk factor. We investigated the effect of particulate matter of aerodynamic diameter smaller than 10µm (PM 10 ) on MS relapses. In total, 536 relapsing MS patients from Strasbourg city (France) were included, accounting for 2052 relapses over 2000-2009 period. A case-crossover design was used with cases defined as the days of relapse and controls being selected in the same patient at plus and minus 35 days. Different lags from 0 to 30 days were considered. Conditional logistic regressions, adjusted on meteorological parameters, school and public holidays, were used and exposure was considered first as a quantitative variable and second, as a binary variable. The natural logarithm of the average PM 10 concentration lagged from 1 to 3 days before relapse onset was significantly associated with relapse risk (OR =1.40 [95% confidence interval 1.08-1.81]) in cold season. Consistent results were observed when considering PM 10 as a binary variable, even if not significant. With an appropriate study design and robust ascertainment of neurological events and exposure, the present study highlights the effect of PM 10 on the risk of relapse in MS patients, probably through oxidative stress mechanisms. Copyright © 2017 Elsevier Inc. All rights reserved.

Co-occurring psychiatric symptoms in opioid-dependent women: the prevalence of antenatal and postnatal depression.

PubMed

Holbrook, Amber; Kaltenbach, Karol

2012-11-01

Despite the high prevalence of psychiatric symptoms in substance-dependent women, little evidence is available on postpartum depression in this population. To determine whether demographic variables and prenatal depression predict postpartum depression and select substance abuse treatment outcomes in a sample of pregnant women. A retrospective chart review was conducted on 125 pregnant women enrolled in a comprehensive substance abuse treatment program. Data on demographic variables, prenatal care attendance, urine drug screen (UDS) results, and psychiatric symptoms were abstracted from patient medical and substance abuse treatment charts. The Postpartum Depression Screening Scale (PDSS) was administered 6 weeks post-delivery. Multiple linear regression was conducted to identify predictors of prenatal care attendance and total PDSS scores at 6 weeks postpartum. Multiple logistic regression was used to examine predictors of positive UDS at delivery. Nearly one-third (30.4%) of the sample screened positive for moderate or severe depression at treatment entry. Psychiatric symptoms did not predict either prenatal care compliance or UDS results at delivery. Almost half of the sample (43.7%) exhibited postpartum depression at 6 weeks post-delivery. No demographic variables correlated with incidence of postnatal depression. Only antenatal depression at treatment entry predicted PDSS scores. Prevalence of antenatal psychiatric disorders and postpartum depression was high in this sample of women seeking substance abuse treatment. Results support prior history of depression as a predictor of risk for developing postpartum depression. Routine screening for perinatal and postpartum depression is indicated for women diagnosed with substance abuse disorders.

Missing Oral Health-Related Data in the interRAI-HC - Associations with Selected Variables of General Health and the Effect of Multiple Imputation on the Relationship between Oral and General Health.

PubMed

Krausch-Hofmann, Stefanie; Bogaerts, Kris; Hofmann, Michael; de Almeida Mello, Johanna; Fávaro Moreira, Nádia Cristina; Lesaffre, Emmanuel; Declerck, Dominique; Declercq, Anja; Duyck, Joke

2015-01-01

Missing data within the comprehensive geriatric assessment of the interRAI suite of assessment instruments potentially imply the under-detection of conditions that require care as well as the risk of biased statistical results. Impaired oral health in older individuals has to be registered accurately as it causes pain and discomfort and is related to the general health status. This study was based on interRAI-Home Care (HC) baseline data from 7590 subjects (mean age 81.2 years, SD 6.9) in Belgium. It was investigated if missingness of the oral health-related items was associated with selected variables of general health. It was also determined if multiple imputation of missing data affected the associations between oral and general health. Multivariable logistic regression was used to determine if the prevalence of missingness in the oral health-related variables was associated with activities of daily life (ADLH), cognitive performance (CPS2) and depression (DRS). Associations between oral health and ADLH, CPS2 and DRS were determined, with missing data treated by 1. the complete-case technique and 2. by multiple imputation, and results were compared. The individual oral health-related variables had a similar proportion of missing values, ranging from 16.3% to 17.2%. The prevalence of missing data in all oral health-related variables was significantly associated with symptoms of depression (dental prosthesis use OR 1.66, CI 1.41-1.95; damaged teeth OR 1.74, CI 1.48-2.04; chewing problems OR 1.74, CI 1.47-2.05; dry mouth OR 1.65, CI 1.40-1.94). Missingness in damaged teeth (OR 1.27, CI 1.08-1.48), chewing problems (OR 1.22, CI 1.04-1.44) and dry mouth (OR 1.23, CI 1.05-1.44) occurred more frequently in cognitively impaired subjects. ADLH was not associated with the prevalence of missing data. When comparing the complete-case technique with the multiple imputation approach, nearly identical odds ratios characterized the associations between oral and general health. Cognitively impaired and depressive individuals had a higher risk of missing oral health-related information. Associations between oral health and ADLH, CPS2 and DRS were not influenced by multiple imputation of missing data. Further research should concentrate on the mechanisms that mediate the occurrence of missingness to develop preventative strategies.

Risk factors for lesions of the knee menisci among workers in South Korea's national parks.

PubMed

Shin, Donghee; Youn, Kanwoo; Lee, Eunja; Lee, Myeongjun; Chung, Hweemin; Kim, Deokweon

2016-01-01

This study was designed to investigate the prevalence of the menisci lesions in national park workers and work factors affecting this prevalence. The study subjects were 698 workers who worked in 20 Korean national parks in 2014. An orthopedist visited each national park and performed physical examinations. Knee MRI was performed if the McMurray test or Apley test was positive and there was a complaint of pain in knee area. An orthopedist and a radiologist respectively read these images of the menisci using a grading system based on the MRI signals. To calculate the cumulative intensity of trekking of the workers, the mean trail distance, the difficulty of the trail, the tenure at each national parks, and the number of treks per month for each worker from the start of work until the present were investigated. Chi-square tests was performed to see if there were differences in the menisci lesions grade according to the variables. The variables used in the Chi-square test were evaluated using simple logistic regression analysis to get crude odds ratios, and adjusted odds ratios and 95 % confidence intervals were calculated using multivariate logistic regression analysis after establishing three different models according to the adjusted variables. According to the MRI signal grades of menisci, 29 % were grade 0, 11.3 % were grade 1, 46.0 % were grade 2, and 13.7 % were grade 3. The differences in the MRI signal grades of menisci according to age and the intensity of trekking as calculated by the three different methods were statistically significant. Multiple logistic regression analysis was performed for three models. In model 1, there was no statistically significant factor affecting the menisci lesions. In model 2, among the factors affecting the menisci lesions, the OR of a high cumulative intensity of trekking was 4.08 (95 % CI 1.00-16.61), and in model 3, the OR of a high cumulative intensity of trekking was 5.84 (95 % CI 1.09-31.26). The factor that most affected the menisci lesions among the workers in Korean national park was a high cumulative intensity of trekking.

Association of Fatigue With Sarcopenia and its Elements: A Secondary Analysis of SABE-Bogotá

PubMed Central

Patino-Hernandez, Daniela; David-Pardo, David Gabriel; Borda, Miguel Germán; Pérez-Zepeda, Mario Ulises; Cano-Gutiérrez, Carlos

2017-01-01

Objective: Sarcopenia, fatigue, and depression are associated with higher mortality rates and adverse outcomes in the aging population. Understanding the association among clinical variables, mainly symptoms, is important for screening and appropriately managing these conditions. The aim of this article is to evaluate the association among sarcopenia and its elements with depression and fatigue. Method: We used cross-sectional data from 2012 SABE (Salud, Bienestar y Envejecimiento)-Bogotá study, which included 2,000 participants of ages ≥60 years. Sarcopenia and its elements were taken as the dependent variable, while fatigue and depression were the main independent variables. We tested the association among these through multiple logistic regression models, which were fitted for each dependent variable and adjusted for confounding variables. Results: Our findings showed that gait speed was associated with fatigue (adjusted odds ratio [OR] = 1.41, 95% confidence interval [CI] = [1.05, 1.90], p = .02) as well as abnormal handgrip strength (adjusted OR = 1.40, 95% CI = [1.02, 1.93], p = .04). No other associations were significant. Conclusion: While sarcopenia and fatigue are not associated, two of the sarcopenia-defining variables are associated with fatigue; this suggests that lack of sarcopenia does not exclude undesirable outcomes related to fatigue in aging adults. Also, the lack of association between sarcopenia-defining elements and depression demonstrates that depression and fatigue are different concepts. PMID:28474000

Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

PubMed

Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

2017-05-01

This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Logistic-based patient grouping for multi-disciplinary treatment.

PubMed

Maruşter, Laura; Weijters, Ton; de Vries, Geerhard; van den Bosch, Antal; Daelemans, Walter

2002-01-01

Present-day healthcare witnesses a growing demand for coordination of patient care. Coordination is needed especially in those cases in which hospitals have structured healthcare into specialty-oriented units, while a substantial portion of patient care is not limited to single units. From a logistic point of view, this multi-disciplinary patient care creates a tension between controlling the hospital's units, and the need for a control of the patient flow between units. A possible solution is the creation of new units in which different specialties work together for specific groups of patients. A first step in this solution is to identify the salient patient groups in need of multi-disciplinary care. Grouping techniques seem to offer a solution. However, most grouping approaches in medicine are driven by a search for pathophysiological homogeneity. In this paper, we present an alternative logistic-driven grouping approach. The starting point of our approach is a database with medical cases for 3,603 patients with peripheral arterial vascular (PAV) diseases. For these medical cases, six basic logistic variables (such as the number of visits to different specialist) are selected. Using these logistic variables, clustering techniques are used to group the medical cases in logistically homogeneous groups. In our approach, the quality of the resulting grouping is not measured by statistical significance, but by (i) the usefulness of the grouping for the creation of new multi-disciplinary units; (ii) how well patients can be selected for treatment in the new units. Given a priori knowledge of a patient (e.g. age, diagnosis), machine learning techniques are employed to induce rules that can be used for the selection of the patients eligible for treatment in the new units. In the paper, we describe the results of the above-proposed methodology for patients with PAV diseases. Two groupings and the accompanied classification rule sets are presented. One grouping is based on all the logistic variables, and another grouping is based on two latent factors found by applying factor analysis. On the basis of the experimental results, we can conclude that it is possible to search for medical logistic homogenous groups (i) that can be characterized by rules based on the aggregated logistic variables; (ii) for which we can formulate rules to predict to which cluster new patients belong.

Dietary Inflammatory Index and risk of multiple sclerosis in a case-control study from Iran

PubMed Central

Shivappa, Nitin; Hébert, James R.; Behrooz, Maryam; Rashidkhani, Bahram

2016-01-01

Background Diet and inflammation have been suggested to be important risk factors for multiple sclerosis (MS). Objectives In this study, we examined the ability of the dietary inflammatory index (DII) to predict MS in a case-control study conducted in Iran. Methods This study included 68 MS cases and 140 controls hospitalized for acute non-neoplastic diseases. The DII was computed based on dietary intake assessed by a previously validated food frequency questionnaire. Logistic regression models were used to estimate odds ratios (ORs) adjusted for age, energy, sex, BMI, season of birth, rubella history, history of routine exercise before MS, smoking and history of consumption of cow's mile in the first 2 years of life. Results Subjects with higher DII scores (i.e., with a more pro-inflammatory diet) had a higher risk of MS, with the DII being used as both a continuous variable (ORcontinuous 1.66, 95% confidence interval, (CI), 1.19-2.31; one unit increase corresponding to ≈15% of its range in the current study) and a categorical variable (ORdii>1.43 vs ≤ 1.43 2.68, 95%CI 1.15-6.26). Conclusions These results indicate that a pro-inflammatory diet is associated with increased risk of MS. PMID:27362443

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies

PubMed Central

Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

PubMed

Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.

Anti-citrullinated peptide antibodies are the strongest predictor of clinically relevant radiographic progression in rheumatoid arthritis patients achieving remission or low disease activity: A post hoc analysis of a nationwide cohort in Japan

PubMed Central

Okada, Akitomo; Fukuda, Takaaki; Hidaka, Toshihiko; Ishii, Tomonori; Ueki, Yukitaka; Kodera, Takao; Nakashima, Munetoshi; Takahashi, Yuichi; Honda, Seiyo; Horai, Yoshiro; Watanabe, Ryu; Okuno, Hiroshi; Aramaki, Toshiyuki; Izumiyama, Tomomasa; Takai, Osamu; Miyashita, Taiichiro; Sato, Shuntaro; Kawashiri, Shin-ya; Iwamoto, Naoki; Ichinose, Kunihiro; Tamai, Mami; Origuchi, Tomoki; Nakamura, Hideki; Aoyagi, Kiyoshi; Eguchi, Katsumi; Kawakami, Atsushi

2017-01-01

Objectives To determine prognostic factors of clinically relevant radiographic progression (CRRP) in patients with rheumatoid arthritis (RA) achieving remission or low disease activity (LDA) in clinical practice. Methods Using data from a nationwide, multicenter, prospective study in Japan, we evaluated 198 biological disease-modifying antirheumatic drug (bDMARD)-naïve RA patients who were in remission or had LDA at study entry after being treated with conventional synthetic DMARDs (csDMARDs). CRRP was defined as the yearly progression of modified total Sharp score (mTSS) >3.0 U. We performed a multiple logistic regression analysis to explore the factors to predict CRRP at 1 year. We used receiver operating characteristic (ROC) curve to estimate the performance of relevant variables for predicting CRRP. Results The mean Disease Activity Score in 28 joints-erythrocyte sedimentation rate (DAS28-ESR) was 2.32 ± 0.58 at study entry. During the 1-year observation, remission or LDA persisted in 72% of the patients. CRRP was observed in 7.6% of the patients. The multiple logistic regression analysis revealed that the independent variables to predict the development of CRRP were: anti-citrullinated peptide antibodies (ACPA) positivity at baseline (OR = 15.2, 95%CI 2.64–299), time-integrated DAS28-ESR during the 1 year post-baseline (7.85-unit increase, OR = 1.83, 95%CI 1.03–3.45), and the mTSS at baseline (13-unit increase, OR = 1.22, 95%CI 1.06–1.42). Conclusions ACPA positivity was the strongest independent predictor of CRRP in patients with RA in remission or LDA. Physicians should recognize ACPA as a poor-prognosis factor regarding the radiographic outcome of RA, even among patients showing a clinically favorable response to DMARDs. PMID:28505163

Peak oxygen consumption measured during the stair-climbing test in lung resection candidates.

PubMed

Brunelli, Alessandro; Xiumé, Francesco; Refai, Majed; Salati, Michele; Di Nunzio, Luca; Pompili, Cecilia; Sabbatini, Armando

2010-01-01

The stair-climbing test is commonly used in the preoperative evaluation of lung resection candidates, but it is difficult to standardize and provides little physiologic information on the performance. To verify the association between the altitude and the V(O2peak) measured during the stair-climbing test. 109 consecutive candidates for lung resection performed a symptom-limited stair-climbing test with direct breath-by-breath measurement of V(O2peak) by a portable gas analyzer. Stepwise logistic regression and bootstrap analyses were used to verify the association of several perioperative variables with a V(O2peak) <15 ml/kg/min. Subsequently, multiple regression analysis was also performed to develop an equation to estimate V(O2peak) from stair-climbing parameters and other patient-related variables. 56% of patients climbing <14 m had a V(O2peak) <15 ml/kg/min, whereas 98% of those climbing >22 m had a V(O2peak) >15 ml/kg/min. The altitude reached at stair-climbing test resulted in the only significant predictor of a V(O2peak) <15 ml/kg/min after logistic regression analysis. Multiple regression analysis yielded an equation to estimate V(O2peak) factoring altitude (p < 0.0001), speed of ascent (p = 0.005) and body mass index (p = 0.0008). There was an association between altitude and V(O2peak) measured during the stair-climbing test. Most of the patients climbing more than 22 m are able to generate high values of V(O2peak) and can proceed to surgery without any additional tests. All others need to be referred for a formal cardiopulmonary exercise test. In addition, we were able to generate an equation to estimate V(O2peak), which could assist in streamlining the preoperative workup and could be used across different settings to standardize this test. Copyright (c) 2010 S. Karger AG, Basel.

The Effect of Work Characteristics on Dermatologic Symptoms in Hairdressers

PubMed Central

2014-01-01

Objectives Hairdressers in Korea perform various tasks and are exposed to health risk factors such as chemical substances or prolonged duration of wet work. The objective of this study is to provide descriptive statistics on the demographics and work characteristics of hairdressers in Korea and to identify work-related risk factors for dermatologic symptoms in hairdressers. Methods 1,054 hairdressers were selected and analyzed for this study. Independent variables were exposure to chemical substances, the training status of the hairdressers, and the main tasks required of them, and the dependent variable was the incidence of dermatologic symptoms. The relationships between work characteristics and dermatologic symptoms were evaluated by estimating odds ratios using multiple logistic regression analysis. Results Among the 1,054 study subjects, 212 hairdressers (20.1%) complained of dermatologic symptoms, and the symptoms were more prevalent in younger, unmarried or highly educated hairdressers. The main tasks that comprise the majority of the wet work were strictly determined by training status, since 96.5% of staff hairdressers identified washing as their main task, while only 1.5% and 2.0% of master and designer hairdressers, respectively, identified this as their main task. Multiple logistic regressions was performed to estimate odds ratios. While exposure to hairdressing chemicals showed no significant effect on the odds ratio for the incidence of dermatologic symptoms, higher odds ratios of dermatologic symptoms were shown in staff hairdressers (2.70, 95% CI: 1.32 - 5.51) and in hairdressers who perform washing as their main task (2.03, 95% CI: 1.22 - 3.37), after adjusting for general and work characteristics. Conclusions This study showed that the training status and main tasks of hairdressers are closely related to each other and that the training status and main tasks of hairdressers are related to the incidence of dermatologic symptoms. This suggests that in the future, regulations on working conditions and health management guidelines for hairdressers should be established. PMID:25028609

Large scale landslide susceptibility assessment using the statistical methods of logistic regression and BSA - study case: the sub-basin of the small Niraj (Transylvania Depression, Romania)

NASA Astrophysics Data System (ADS)

Roşca, S.; Bilaşco, Ş.; Petrea, D.; Fodorean, I.; Vescan, I.; Filip, S.; Măguţ, F.-L.

2015-11-01

The existence of a large number of GIS models for the identification of landslide occurrence probability makes difficult the selection of a specific one. The present study focuses on the application of two quantitative models: the logistic and the BSA models. The comparative analysis of the results aims at identifying the most suitable model. The territory corresponding to the Niraj Mic Basin (87 km2) is an area characterised by a wide variety of the landforms with their morphometric, morphographical and geological characteristics as well as by a high complexity of the land use types where active landslides exist. This is the reason why it represents the test area for applying the two models and for the comparison of the results. The large complexity of input variables is illustrated by 16 factors which were represented as 72 dummy variables, analysed on the basis of their importance within the model structures. The testing of the statistical significance corresponding to each variable reduced the number of dummy variables to 12 which were considered significant for the test area within the logistic model, whereas for the BSA model all the variables were employed. The predictability degree of the models was tested through the identification of the area under the ROC curve which indicated a good accuracy (AUROC = 0.86 for the testing area) and predictability of the logistic model (AUROC = 0.63 for the validation area).

Beyond logistic regression: structural equations modelling for binary variables and its application to investigating unobserved confounders.

PubMed

Kupek, Emil

2006-03-15

Structural equation modelling (SEM) has been increasingly used in medical statistics for solving a system of related regression equations. However, a great obstacle for its wider use has been its difficulty in handling categorical variables within the framework of generalised linear models. A large data set with a known structure among two related outcomes and three independent variables was generated to investigate the use of Yule's transformation of odds ratio (OR) into Q-metric by (OR-1)/(OR+1) to approximate Pearson's correlation coefficients between binary variables whose covariance structure can be further analysed by SEM. Percent of correctly classified events and non-events was compared with the classification obtained by logistic regression. The performance of SEM based on Q-metric was also checked on a small (N = 100) random sample of the data generated and on a real data set. SEM successfully recovered the generated model structure. SEM of real data suggested a significant influence of a latent confounding variable which would have not been detectable by standard logistic regression. SEM classification performance was broadly similar to that of the logistic regression. The analysis of binary data can be greatly enhanced by Yule's transformation of odds ratios into estimated correlation matrix that can be further analysed by SEM. The interpretation of results is aided by expressing them as odds ratios which are the most frequently used measure of effect in medical statistics.

Locomotive syndrome is associated not only with physical capacity but also degree of depression.

PubMed

Ikemoto, Tatsunori; Inoue, Masayuki; Nakata, Masatoshi; Miyagawa, Hirofumi; Shimo, Kazuhiro; Wakabayashi, Toshiko; Arai, Young-Chang P; Ushida, Takahiro

2016-05-01

Reports of locomotive syndrome (LS) have recently been increasing. Although physical performance measures for LS have been well investigated to date, studies including psychiatric assessment are still scarce. Hence, the aim of this study was to investigate both physical and mental parameters in relation to presence and severity of LS using a 25-question geriatric locomotive function scale (GLFS-25) questionnaire. 150 elderly people aged over 60 years who were members of our physical-fitness center and displayed well-being were enrolled in this study. Firstly, using the previously determined GLFS-25 cutoff value (=16 points), subjects were divided into two groups accordingly: an LS and non-LS group in order to compare each parameter (age, grip strength, timed-up-and-go test (TUG), one-leg standing with eye open, back muscle and leg muscle strength, degree of depression and cognitive impairment) between the groups using the Mann-Whitney U-test followed by multiple logistic regression analysis. Secondly, a multiple linear regression was conducted to determine which variables showed the strongest correlation with severity of LS. We confirmed 110 people for non-LS (73%) and 40 people for LS using the GLFS-25 cutoff value. Comparative analysis between LS and non-LS revealed significant differences in parameters in age, grip strength, TUG, one-leg standing, back muscle strength and degree of depression (p < 0.006, after Bonferroni correction). Multiple logistic regression revealed that functional decline in grip strength, TUG and one-leg standing and degree of depression were significantly associated with LS. On the other hand, we observed that the significant contributors towards the GLFS-25 score were TUG and degree of depression in multiple linear regression analysis. The results indicate that LS is associated with not only the capacity of physical performance but also the degree of depression although most participants fell under the criteria of LS. Copyright © 2016 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Breast Arterial Calcification Is Associated with Reproductive Factors in Asymptomatic Postmenopausal Women

PubMed Central

Whaley, Dana H.; Sheedy, Patrick F.; Peyser, Patricia A.

2010-01-01

Abstract Objective 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. Methods 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. Results 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. Conclusions 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. PMID:20629578

Logistic regression models of factors influencing the location of bioenergy and biofuels plants

Treesearch

T.M. Young; R.L. Zaretzki; J.H. Perdue; F.M. Guess; X. Liu

2011-01-01

Logistic regression models were developed to identify significant factors that influence the location of existing wood-using bioenergy/biofuels plants and traditional wood-using facilities. Logistic models provided quantitative insight for variables influencing the location of woody biomass-using facilities. Availability of "thinnings to a basal area of 31.7m2/ha...

What Are the Odds of that? A Primer on Understanding Logistic Regression

ERIC Educational Resources Information Center

Huang, Francis L.; Moon, Tonya R.

2013-01-01

The purpose of this Methodological Brief is to present a brief primer on logistic regression, a commonly used technique when modeling dichotomous outcomes. Using data from the National Education Longitudinal Study of 1988 (NELS:88), logistic regression techniques were used to investigate student-level variables in eighth grade (i.e., enrolled in a…

The crux of the method: assumptions in ordinary least squares and logistic regression.

PubMed

Long, Rebecca G

2008-10-01

Logistic regression has increasingly become the tool of choice when analyzing data with a binary dependent variable. While resources relating to the technique are widely available, clear discussions of why logistic regression should be used in place of ordinary least squares regression are difficult to find. The current paper compares and contrasts the assumptions of ordinary least squares with those of logistic regression and explains why logistic regression's looser assumptions make it adept at handling violations of the more important assumptions in ordinary least squares.

[Logistic regression model of noninvasive prediction for portal hypertensive gastropathy in patients with hepatitis B associated cirrhosis].

PubMed

Wang, Qingliang; Li, Xiaojie; Hu, Kunpeng; Zhao, Kun; Yang, Peisheng; Liu, Bo

2015-05-12

To explore the risk factors of portal hypertensive gastropathy (PHG) in patients with hepatitis B associated cirrhosis and establish a Logistic regression model of noninvasive prediction. The clinical data of 234 hospitalized patients with hepatitis B associated cirrhosis from March 2012 to March 2014 were analyzed retrospectively. The dependent variable was the occurrence of PHG while the independent variables were screened by binary Logistic analysis. Multivariate Logistic regression was used for further analysis of significant noninvasive independent variables. Logistic regression model was established and odds ratio was calculated for each factor. The accuracy, sensitivity and specificity of model were evaluated by the curve of receiver operating characteristic (ROC). According to univariate Logistic regression, the risk factors included hepatic dysfunction, albumin (ALB), bilirubin (TB), prothrombin time (PT), platelet (PLT), white blood cell (WBC), portal vein diameter, spleen index, splenic vein diameter, diameter ratio, PLT to spleen volume ratio, esophageal varices (EV) and gastric varices (GV). Multivariate analysis showed that hepatic dysfunction (X1), TB (X2), PLT (X3) and splenic vein diameter (X4) were the major occurring factors for PHG. The established regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4. The accuracy of model for PHG was 79.1% with a sensitivity of 77.2% and a specificity of 80.8%. Hepatic dysfunction, TB, PLT and splenic vein diameter are risk factors for PHG and the noninvasive predicted Logistic regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4.

How Much Is Too Little to Detect Impacts? A Case Study of a Nuclear Power Plant

PubMed Central

Széchy, Maria T. M.; Viana, Mariana S.; Curbelo-Fernandez, Maria P.; Lavrado, Helena P.; Junqueira, Andrea O. R.; Vilanova, Eduardo; Silva, Sérgio H. G.

2012-01-01

Several approaches have been proposed to assess impacts on natural assemblages. Ideally, the potentially impacted site and multiple reference sites are sampled through time, before and after the impact. Often, however, the lack of information regarding the potential overall impact, the lack of knowledge about the environment in many regions worldwide, budgets constraints and the increasing dimensions of human activities compromise the reliability of the impact assessment. We evaluated the impact, if any, and its extent of a nuclear power plant effluent on sessile epibiota assemblages using a suitable and feasible sampling design with no ‘before’ data and budget and logistic constraints. Assemblages were sampled at multiple times and at increasing distances from the point of the discharge of the effluent. There was a clear and localized effect of the power plant effluent (up to 100 m from the point of the discharge). However, depending on the time of the year, the impact reaches up to 600 m. We found a significantly lower richness of taxa in the Effluent site when compared to other sites. Furthermore, at all times, the variability of assemblages near the discharge was also smaller than in other sites. Although the sampling design used here (in particular the number of replicates) did not allow an unambiguously evaluation of the full extent of the impact in relation to its intensity and temporal variability, the multiple temporal and spatial scales used allowed the detection of some differences in the intensity of the impact, depending on the time of sampling. Our findings greatly contribute to increase the knowledge on the effects of multiple stressors caused by the effluent of a power plant and also have important implications for management strategies and conservation ecology, in general. PMID:23110117

How much is too little to detect impacts? A case study of a nuclear power plant.

PubMed

Mayer-Pinto, Mariana; Ignacio, Barbara L; Széchy, Maria T M; Viana, Mariana S; Curbelo-Fernandez, Maria P; Lavrado, Helena P; Junqueira, Andrea O R; Vilanova, Eduardo; Silva, Sérgio H G

2012-01-01

Several approaches have been proposed to assess impacts on natural assemblages. Ideally, the potentially impacted site and multiple reference sites are sampled through time, before and after the impact. Often, however, the lack of information regarding the potential overall impact, the lack of knowledge about the environment in many regions worldwide, budgets constraints and the increasing dimensions of human activities compromise the reliability of the impact assessment. We evaluated the impact, if any, and its extent of a nuclear power plant effluent on sessile epibiota assemblages using a suitable and feasible sampling design with no 'before' data and budget and logistic constraints. Assemblages were sampled at multiple times and at increasing distances from the point of the discharge of the effluent. There was a clear and localized effect of the power plant effluent (up to 100 m from the point of the discharge). However, depending on the time of the year, the impact reaches up to 600 m. We found a significantly lower richness of taxa in the Effluent site when compared to other sites. Furthermore, at all times, the variability of assemblages near the discharge was also smaller than in other sites. Although the sampling design used here (in particular the number of replicates) did not allow an unambiguously evaluation of the full extent of the impact in relation to its intensity and temporal variability, the multiple temporal and spatial scales used allowed the detection of some differences in the intensity of the impact, depending on the time of sampling. Our findings greatly contribute to increase the knowledge on the effects of multiple stressors caused by the effluent of a power plant and also have important implications for management strategies and conservation ecology, in general.

The relationship between children's oral health-related behaviors and their caregiver's social support.

PubMed

Qiu, Rong Min; Tao, Ye; Zhou, Yan; Zhi, Qing Hui; Lin, Huan Cai

2016-09-01

Social support might play a role in helping people adopt healthy behaviors and improve their health. Stronger social support from mothers has been found to be positively related to higher tooth brushing frequency in 1- to 3-year-old children. However, little is known regarding the relationship between the caregiver's social support and the oral health-related behaviors of 5-year-old children in China. This study aimed to investigate this relationship. A cross-sectional study was conducted among 1332 5-year-old children and their caregivers in Guangzhou, southern China. Data were collected using questionnaires that were completed by the caregivers and the children's caries status were examined. The caregivers' social support was measured using the Social Support Rating Scale. The measurements of the children's oral health-related behaviors included the frequencies of sugary snack intake and tooth brushing, utilization of dental services, and patterns of dental visits. Univariate and multiple logistic regression analyses were used to analyze the relationships between the variables. No association was found between the caregiver's social support and the child's oral health-related behaviors in a multiple logistic regression analysis. However, other factors, particularly the oral health-related behaviors of the caregiver, were found to be significantly linked to the child's oral health-related behaviors. The oral health-related behaviors of 5-year-old children in Guangzhou are unrelated to the caregiver's social support but are related to other specific factors, particularly the caregiver's oral health-related behaviors.

[Patients' reaction to pharmacists wearing a mask during their consultations].

PubMed

Tamura, Eri; Kishimoto, Keiko; Fukushima, Noriko

2013-01-01

  This study sought to determine the effect of pharmacists wearing a mask on the consultation intention of patients who do not have a trusting relationship with the pharmacists. We conducted a questionnaire survey of customers at a Tokyo drugstore in August 2012. Subjects answered a questionnaire after watching two medical teaching videos, one in which the pharmacist was wearing a mask and the other in which the pharmacist was not wearing a mask. Data analysis was performed using a paired t-test and multiple logistic regression. The paired t-test revealed a significant difference in 'Maintenance Problem' between the two pharmacist situations. After excluding factors not associated with wearing a mask, multiple logistic regression analysis identified three independent variables with a significant effect on participants not wanting to consult with a pharmacist wearing a mask. Positive factors were 'active-inactive' and 'frequency mask use', a negative factor was 'age'. Our study has shown that pharmacists wearing a mask may be a factor that prevents patients from consulting with pharmacist. Those patients whose intention to consult might be affected by the pharmacists wearing a mask tended to be younger, to have no habit of wearing masks preventively themselves, and to form a negative opinion of such pharmacists. Therefore, it was estimated that pharmacists who wear masks need to provide medical education by asking questions more positively than when they do not wear a mask in order to prevent the patient worrying about oneself.

A framework for evaluating student perceptions of health policy training in medical school.

PubMed

Patel, Mitesh S; Lypson, Monica L; Miller, D Douglas; Davis, Matthew M

2014-10-01

Nearly half of graduating medical students in the United States report that medical school provides inadequate instruction in topics related to health policy. Although most medical schools report some form of policy education, there lacks a standard for teaching core concepts and evaluating student satisfaction. Responses to the Association of American Medical College's Medical School Graduation Questionnaire were obtained for the years 2007-2008 and 2011-2012 and mapped to domains of training in health policy curricula for four domains: systems and principles; value and equity; quality and safety; and politics and law. Chi-square tests were used to test differences among unadjusted temporal trends. Multiple logistic regression models were fit to the outcome variables and adjusted for student characteristics, student preferences, and medical school characteristics. Compared with 2007-2008, students' perceptions of training in 2011-2012 increased on a relative basis by 11.7% for components within systems and principles, 2.8% for quality and safety, and 6.8% for value and equity. Components within politics and law had a composite decline of 4.8%. Multiple logistic regression models found higher odds of reporting satisfaction with training over time for all components within the domains of systems and principles, quality and safety, and value and equity (P < .01), with the exception of medical economics. Medical student perceptions of training in health policy improved over time. Causal factors for these trends require further study. Despite improvement, nearly 40% of graduating medical students still report inadequate instruction in health policy.

Association between red blood cell distribution width (RDW) and carotid artery atherosclerosis (CAS) in patients with primary ischemic stroke.

PubMed

Jia, He; Li, Huimian; Zhang, Yan; Li, Che; Hu, Yingyun; Xia, Chunfang

2015-01-01

The present study aimed to explore the association between RDW and CAS in patients with ischemic stroke, expecting to find a new and significant diagnosis index for clinical practice. This cross-sectional study involves 432 consecutive patients with primary ischemic stroke (within 72 h). All subjects were confirmed by magnetic resonance imaging, and underwent physical examination, laboratory tests and carotid ultrasonography check. Finally, 392 patients were included according to the exclusion criteria. The odds ratios of independent variables were calculated using stepwise multiple logistic regression. Carotid intimal-medial thickness (IMT) and RDW are both significantly different between CAS group and control group. Univariate analyses show that high-sensitive C-reactive protein (Hs-CRP) and RDW (r=0.436) are both in significantly positive association with IMT. Stepwise multiple logistic regression shows that RDW is an independent protective factor of CAS in patients with ischemic stroke. Compared with the lowest quartile, the second to fourth quartiles are 1.13 (95% CI: 1.13-3.05), 2.02 (95% CI: 1.66-4.67), and 3.10 (95% CI: 2.46-7.65), respectively. The present study suggested that RDW level were higher than non-CAS in patients with primary ischemic stroke. Our results facilitated a bridge to connect RDW with ischemic stroke and further confirmed the role of RDW in the progression of the ischemic stroke. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Maximal bite force, facial morphology and sucking habits in young children with functional posterior crossbite.

PubMed

Castelo, Paula Midori; Gavião, Maria Beatriz Duarte; Pereira, Luciano José; Bonjardim, Leonardo Rigoldi

2010-01-01

The maintenance of normal conditions of the masticatory function is determinant for the correct growth and development of its structures. Thus, the aims of this study were to evaluate the influence of sucking habits on the presence of crossbite and its relationship with maximal bite force, facial morphology and body variables in 67 children of both genders (3.5-7 years) with primary or early mixed dentition. The children were divided in four groups: primary-normocclusion (PN, n=19), primary-crossbite (PC, n=19), mixed-normocclusion (MN, n=13), and mixed-crossbite (MC, n=16). Bite force was measured with a pressurized tube, and facial morphology was determined by standardized frontal photographs: AFH (anterior face height) and BFW (bizygomatic facial width). It was observed that MC group showed lower bite force than MN, and AFH/BFW was significantly smaller in PN than PC (t-test). Weight and height were only significantly correlated with bite force in PC group (Pearson's correlation test). In the primary dentition, AFH/BFW and breast-feeding (at least six months) were positive and negatively associated with crossbite, respectively (multiple logistic regression). In the mixed dentition, breast-feeding and bite force showed negative associations with crossbite (univariate regression), while nonnutritive sucking (up to 3 years) associated significantly with crossbite in all groups (multiple logistic regression). In the studied sample, sucking habits played an important role in the etiology of crossbite, which was associated with lower bite force and long-face tendency.

Sarcopenia is associated with an increased risk of advanced colorectal neoplasia.

PubMed

Park, Youn Su; Kim, Ji Won; Kim, Byeong Gwan; Lee, Kook Lae; Lee, Jae Kyung; Kim, Joo Sung; Koh, Seong-Joon

2017-04-01

Although sarcopenia is associated with an increased risk for mortality after the curative resection of colorectal cancer, its influence on the development of advanced colonic neoplasia remains unclear. This study included 1270 subjects aged 40 years or older evaluated with first-time screening colonoscopy at Seoul National University Boramae Health Care Center from January 2010 to February 2015. Skeletal muscle mass was measured with a body composition analyzer (direct segmental multifrequency bioelectrical impedance analysis method). Multiple logistic regression analysis was performed to determine whether sarcopenia is associated with advanced colorectal neoplasia. Of 1270 subjects, 139 (10.9%) were categorized into the sarcopenia group and 1131 (89.1%) into the non-sarcopenia group. In the non-sarcopenia group, 55 subjects (4.9%) had advanced colorectal neoplasia. However, in the sarcopenia group, 19 subjects (13.7%) had advanced colorectal neoplasia, including 1 subject with invasive colorectal cancer (0.7%). In addition, subjects with sarcopenia had a higher prevalence of advanced adenoma (P < 0.001) than those without sarcopenia. According to the multiple logistic regression analysis adjusted for variable confounders, age (odds ratio 1.062, 95% confidence interval 1.032-1.093; P < 0.001), male sex (odds ratio 1.749, 95% confidence interval 1.008-3.036; P = 0.047), and sarcopenia (odds ratio 2.347, 95% confidence interval 1.311-4.202; P = 0.004) were associated with an advanced colorectal neoplasia. Sarcopenia is associated with an increased risk of advanced colorectal neoplasia.

Burnout Syndrome and associated factors among medical students: a cross-sectional study.

PubMed

Costa, Edméa Fontes de Oliva; Santos, Shirley Andrade; Santos, Ana Teresa Rodrigues de Abreu; Melo, Enaldo Vieira de; Andrade, Tarcísio Matos de

2012-01-01

To assess the prevalence and levels of burnout syndrome among medical students at the Universidade Federal de Sergipe-Brazil and to identify associated factors. A cross-sectional study was performed with randomly selected students in 2009. The Maslach Burnout Inventory/Student Survey (MBI-SS) and a structured questionnaire on socio-demographic characteristics, the educational process, and individual aspects were used. Statistical evaluation of multiple variables was performed through backward stepwise logistic regression analysis. The prevalence of burnout was 10.3% (n = 369). The prevalence was higher among those who did not have confidence in their clinical skills (Odds Ratio-OR = 6.47), those who felt uncomfortable with course activities (OR = 5.76), and those who did not see the coursework as a source of pleasure (OR = 4.68). There was a significant prevalence of burnout among the medical students studied. Three variables, in particular, were associated with burnout and were directly related to the medical education process. Preventive and intervention measures must be adopted, and longitudinal studies should be conducted.

Physical performance and its association with anthropometric and body composition variables in the elderly.

PubMed

Silva, Nathalie de Almeida; Pedraza, Dixis Figueroa; de Menezes, Tarciana Nobre

2015-12-01

The aging process leads to biological changes that affect the physical performance and nutritional status of older adults. The objective this study is to determine the association between physical performance and anthropometric and body composition variables in the elderly. This is a cross-sectional study. Were assessed: sex, age, handgrip strength (HGS), flexibility/mobility, balance, body mass index, waist and calf circumference, triceps skinfold thickness, arm fat area and arm muscle circumference. Multiple logistic regression was used (p<0.05). Overall, 420 elderly were evaluated. Malnourished individuals were more likely to show poor HGS. Elderly aged 70-79 years, 80 years or older and those malnourished were more likely to show poor balance. Older women were less likely to show poor flexibility/mobility. We conclude that lowercalf circumferencewas associatedwithworse performance inHGSand balance.The ageincreased the chanceof the elderlypresentinstability.The flexibility/mobilitydoesn't seem tobe influenced bychanges in body composition. Therefore, these resultsmay beimportantguidingspecific actionsto ensurehealthy aging.

Support, Inclusion, and Special Education Teachers' Attitudes toward the Education of Students with Autism Spectrum Disorders

PubMed Central

Rodríguez, Isabel R.; Saldaña, David; Moreno, F. Javier

2012-01-01

This study is aimed at assessing special education teachers' attitudes toward teaching pupils with autism spectrum disorders (ASDs) and at determining the role of variables associated with a positive attitude towards the children and their education. Sixty-nine special education teachers were interviewed. The interview included two multiple-choice Likert-type questionnaires, one about teachers' attitude, and another about teachers' perceived needs in relation to the specific education of the pupil with ASD. The study shows a positive view of teachers' expectations regarding the education of pupils with ASD. A direct logistic regression analysis was performed testing for experience with the child, school relationship with an ASD network and type of school (mainstream or special) as potential predictors. Although all three variables are useful in predicting special education teachers' attitudes, the most relevant was the relationship with an ASD network. Need for information and social support are the relatively highest needs expressed by teachers. PMID:22934171

[Sedentary leisure time and food consumption among Brazilian adolescents: the Brazilian National School-Based Adolescent Health Survey (PeNSE), 2009].

PubMed

Camelo, Lidyane do Valle; Rodrigues, Jôsi Fernandes de Castro; Giatti, Luana; Barreto, Sandhi Maria

2012-11-01

The objective of this paper was to investigate whether sedentary leisure time was associated with increased regular consumption of unhealthy foods, independently of socio-demographic indicators and family context. The analysis included 59,809 students from the Brazilian National School-Based Adolescent Health Survey (PeNSE) in 2009. The response variable was sedentary leisure time, defined as watching more than two hours of TV daily. The target explanatory variables were regular consumption of soft drinks, sweets, cookies, and processed meat. Odds ratios (OR) and 95% confidence limits (95%CI) were obtained by multiple logistic regression. Prevalence of sedentary leisure time was 65%. Regular consumption of unhealthy foods was statistically higher among students reporting sedentary leisure time, before and after adjusting for sex, age, skin color, school administration (public versus private), household assets index, and household composition. The results indicate the need for integrated interventions to promote healthy leisure-time activities and healthy eating habits among young people.

Use of qualitative environmental and phenotypic variables in the context of allele distribution models: detecting signatures of selection in the genome of Lake Victoria cichlids.

PubMed

Joost, Stéphane; Kalbermatten, Michael; Bezault, Etienne; Seehausen, Ole

2012-01-01

When searching for loci possibly under selection in the genome, an alternative to population genetics theoretical models is to establish allele distribution models (ADM) for each locus to directly correlate allelic frequencies and environmental variables such as precipitation, temperature, or sun radiation. Such an approach implementing multiple logistic regression models in parallel was implemented within a computing program named MATSAM: . Recently, this application was improved in order to support qualitative environmental predictors as well as to permit the identification of associations between genomic variation and individual phenotypes, allowing the detection of loci involved in the genetic architecture of polymorphic characters. Here, we present the corresponding methodological developments and compare the results produced by software implementing population genetics theoretical models (DFDIST: and BAYESCAN: ) and ADM (MATSAM: ) in an empirical context to detect signatures of genomic divergence associated with speciation in Lake Victoria cichlid fishes.

Black tobacco, wine and mate in oropharyngeal cancer. A case-control study from Uruguay.

PubMed

De Stefani, E; Correa, P; Oreggia, F; Deneo-Pellegrini, H; Fernandez, G; Zavala, D; Carzoglio, J; Leiva, J; Fontham, E; Rivero, S

1988-01-01

A case-control study of oral and pharyngeal cancer involving interviews with 108 cases and 286 controls was carried out in the University Hospital of Montevideo, Uruguay. The study was restricted to males and cases afflicted with lip, salivary gland and nasopharyngeal cancer were excluded. Point estimates of RR associated with smoking variables, alcohol variables, nutritional items and ingestion of hot infusions of the herb Ilex paraguariensis ('Mate') were obtained by logistic regression analysis. Dark tobacco smokers showed a RR 3.4 times higher than light tobacco users and heavy drinkers of wine displayed an OR of 17.2. Mate exposure showed a significant dose-response, after adjustment for age, tobacco and alcohol intake, with a fivefold increase in risk for heavy consumers. Joint exposure to black tobacco and wine displayed very high risks and no significant interactions were observed. The results suggest that the high rates of oropharyngeal cancer could be explained by the multiplicative effect of black tobacco smoking, wine drinking and mate ingestion.

Trading Sex for Money or Compensation: Prevalence and Associated Characteristics from a Sexually Transmitted Infection (STI) Clinic Sample.

PubMed

Gerassi, Lara B; Jonson-Reid, Melissa; Plax, Katie; Kaushik, Gaurav

2016-01-01

The purpose of this study was to determine the prevalence and individual risk factors of people who trade or sell sex among sexually active individuals seeking HIV and sexually transmitted infection (STI) testing. Using electronic agency records, an analysis of the characteristics of 5,029 youth and adults who voluntarily obtained HIV and STI testing was conducted. Multiple imputation procedures for missing data from 3 variables and logistic regression were conducted. A total of 128 individuals reported having traded sex. Nine variables had statistically significant associations with trading sex. Individuals who identified as White and female had lesser odds of trading sex, whereas individuals who were transgender, were living in a shelter, had been sexually assaulted, had a previous STI, had high-risk sex, or used drugs had greater odds of trading sex. Elevated levels of high-risk behavior in addition to sexual trauma should be considered in intervention research and community health practice. Implications for service providers and researchers are discussed.

Factors associated with HIV/AIDS treatment dropouts in a special care unit in the City of Rio de Janeiro, RJ, Brazil.

PubMed

Schilkowsky, Louise Bastos; Portela, Margareth Crisóstomo; Sá, Marilene de Castilho

2011-06-01

This study aimed to identify factors associated with the health care of patients with HIV/AIDS who drop out. The study was developed in a specialized health care unit of a University hospital in Rio de Janeiro, Brazil, considering a stratified sample of adult patients including all dropout cases (155) and 44.0% of 790 cases under regular follow-up. Bivariate analyses were used to identify associations between health care dropout and demographic, socioeconomic and clinical variables. Logistic and Cox regression models were used to identify the independent effects of the explanatory variables on risk for dropout, in the latter by incorporating information on the outcome over time. Patients were, on average, 35 years old, predominantly males (66.4%) and of a low socioeconomic level (45.0%). In both models, health care dropout was consistently associated with being unemployed or having an unstable job, using illicit drugs and having psychiatric background--positive association; and with age, having AIDS, and having used multiple antiretroviral regimens--negative association. In the logistic regression, dropping out was also positively associated with time between diagnosis and the first outpatient visit, while in the Cox model, the hazard for dropping out was positively associated with being single, and negatively associated with a higher educational level. The results of this work allow for the identification of HIV/AIDS patients more likely to drop out from health care.

The effect of alcohol, tobacco and caffeine consumption and vegetarian diet on gallstone prevalence.

PubMed

Walcher, Thomas; Haenle, Mark Martin; Mason, Richard Andrew; Koenig, Wolfgang; Imhof, Armin; Kratzer, Wolfgang

2010-11-01

To investigate the effects of alcohol, tobacco and caffeine consumption and of vegetarian diet on gallstone prevalence in an urban population sample. A total of 2417 individuals underwent ultrasound examination and completed a standardized questionnaire as part of the EMIL study. Statistical analysis of the data considered the known risk factors of age, female sex, BMI, positive family history and potential confounders, such as alcohol, caffeine and tobacco consumption and vegetarian diet using multiple logistic regression with variable selection. The prevalence of gallstones in the population sample was 8% (171 out of 2147). Findings of the study confirmed the classic risk factors of age, female sex, obesity and positive family history. After the variable selection of potential risk factors in a logistic regression that was adjusted for age, female sex, BMI and positive family history, the factors like tobacco [odds ratio (OR) 1.09, 95% confidence interval (CI): 0.76-1.56, P=0.64] and caffeine consumption (OR: 0.77, 95% CI: 0.42-1.42, P=0.40) as well as vegetarian diet (OR: 1.14, 95% CI: 0.39-3.35, P=0.81) had no effect on gallstone prevalence. A protective effect against development of gallstones was shown for alcohol consumption (OR: 0.67, 95% CI: 0.46-0.99, P=0.04). The factors like tobacco and caffeine consumption as well as vegetarian diet exerted no measurable effect on the prevalence of gallstones. A protective effect was found for alcohol consumption.

Risk Factors for Venous Thromboembolism in Chronic Obstructive Pulmonary Disease

PubMed Central

Kim, Victor; Goel, Nishant; Gangar, Jinal; Zhao, Huaqing; Ciccolella, David E.; Silverman, Edwin K.; Crapo, James D.; Criner, Gerard J.

2014-01-01

Background: COPD patients are at increased risk for venous thromboembolism (VTE). VTE however remains under-diagnosed in this population and the clinical profile of VTE in COPD is unclear. Methods: Global initiative for chronic Obstructive Lung Disease (GOLD) stages II-IV participants in the COPD Genetic Epidemiology (COPDGene) study were divided into 2 groups: VTE+, those who reported a history of VTE by questionnaire, and VTE-, those who did not. We compared variables in these 2 groups with either t-test or chi-squared test for continuous and categorical variables, respectively. We performed a univariate logistic regression for VTE, and then a multivariate logistic regression using the significant predictors of interest in the univariate analysis to ascertain the determinants of VTE. Results: The VTE+ group was older, more likely to be Caucasian, had a higher body mass index (BMI), smoking history, used oxygen, had a lower 6-minute walk distance, worse quality of life scores, and more dyspnea and respiratory exacerbations than the VTE- group. Lung function was not different between groups. A greater percentage of the VTE+ group described multiple medical comorbidities. On multivariate analysis, BMI, 6-minute walk distance, pneumothorax, peripheral vascular disease, and congestive heart failure significantly increased the odds for VTE by history. Conclusions: BMI, exercise capacity, and medical comorbidities were significantly associated with VTE in moderate to severe COPD. Clinicians should suspect VTE in patients who present with dyspnea and should consider possibilities other than infection as causes of COPD exacerbation. PMID:25844397

Perception of Risk for Developing Diabetes Among Foreign-Born Spanish-Speaking US Latinos.

PubMed

Joiner, Kevin L; Sternberg, Rosa Maria; Kennedy, Christine M; Fukuoka, Yoshimi; Chen, Jyu-Lin; Janson, Susan L

2016-08-01

The purpose of the study was to describe perception of risk for developing diabetes among foreign-born Spanish-speaking US Latinos. Participants (N = 146), recruited at food-pantry distribution events and free clinics, were surveyed using the Risk Perception Survey for Developing Diabetes in Spanish. Type 2 diabetes risk factors measured included body mass index, physical activity, and A1C. Sample characteristics were mean (SD) age of 39.5 (9.9) years, 58% with less than a high school graduate-level education, and 65% with a family income less than $15,000/year. Prevalence of risk factors was 81% overweight or obese, 47% less than 150 minutes/week moderate/vigorous-intensity physical activity, and 12% A1C consistent with prediabetes. Of the 135 participants with complete data, 31% perceived a high/moderate risk for developing diabetes. In univariate logistic regression analyses, 9 of 18 potential variables were significant (P < .05) predictors of perception of risk. When these 9 variables were entered into a multiple logistic regression model, 5 were significant predictors of perception of risk: history of gestational diabetes, high school graduate or above, optimistic bias, worry, and perceived personal disease risk. Use of the Spanish-language translation of the Risk Perception Survey for Developing Diabetes revealed factors influencing perception of risk for developing diabetes. Results can be used to promote culturally acceptable type 2 diabetes primary prevention strategies and provide a useful comparison to other populations. © 2016 The Author(s).

PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

EPA Science Inventory

The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

Analyzing Student Learning Outcomes: Usefulness of Logistic and Cox Regression Models. IR Applications, Volume 5

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2005-01-01

Logistic and Cox regression methods are practical tools used to model the relationships between certain student learning outcomes and their relevant explanatory variables. The logistic regression model fits an S-shaped curve into a binary outcome with data points of zero and one. The Cox regression model allows investigators to study the duration…

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

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

Bramer, Lisa M.; Rounds, J.; Burleyson, C. D.

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions were examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and combinations of predictive variables were examined. A penalized logistic regression model which wasmore » fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at various time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. In conclusion, the methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.« less

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

DOE PAGES

Bramer, Lisa M.; Rounds, J.; Burleyson, C. D.; ...

2017-09-22

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions were examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and combinations of predictive variables were examined. A penalized logistic regression model which wasmore » fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at various time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. In conclusion, the methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.« less

Unconditional or Conditional Logistic Regression Model for Age-Matched Case-Control Data?

PubMed

Kuo, Chia-Ling; Duan, Yinghui; Grady, James

2018-01-01

Matching on demographic variables is commonly used in case-control studies to adjust for confounding at the design stage. There is a presumption that matched data need to be analyzed by matched methods. Conditional logistic regression has become a standard for matched case-control data to tackle the sparse data problem. The sparse data problem, however, may not be a concern for loose-matching data when the matching between cases and controls is not unique, and one case can be matched to other controls without substantially changing the association. Data matched on a few demographic variables are clearly loose-matching data, and we hypothesize that unconditional logistic regression is a proper method to perform. To address the hypothesis, we compare unconditional and conditional logistic regression models by precision in estimates and hypothesis testing using simulated matched case-control data. Our results support our hypothesis; however, the unconditional model is not as robust as the conditional model to the matching distortion that the matching process not only makes cases and controls similar for matching variables but also for the exposure status. When the study design involves other complex features or the computational burden is high, matching in loose-matching data can be ignored for negligible loss in testing and estimation if the distributions of matching variables are not extremely different between cases and controls.

Unconditional or Conditional Logistic Regression Model for Age-Matched Case–Control Data?

PubMed Central

Kuo, Chia-Ling; Duan, Yinghui; Grady, James

2018-01-01

Matching on demographic variables is commonly used in case–control studies to adjust for confounding at the design stage. There is a presumption that matched data need to be analyzed by matched methods. Conditional logistic regression has become a standard for matched case–control data to tackle the sparse data problem. The sparse data problem, however, may not be a concern for loose-matching data when the matching between cases and controls is not unique, and one case can be matched to other controls without substantially changing the association. Data matched on a few demographic variables are clearly loose-matching data, and we hypothesize that unconditional logistic regression is a proper method to perform. To address the hypothesis, we compare unconditional and conditional logistic regression models by precision in estimates and hypothesis testing using simulated matched case–control data. Our results support our hypothesis; however, the unconditional model is not as robust as the conditional model to the matching distortion that the matching process not only makes cases and controls similar for matching variables but also for the exposure status. When the study design involves other complex features or the computational burden is high, matching in loose-matching data can be ignored for negligible loss in testing and estimation if the distributions of matching variables are not extremely different between cases and controls. PMID:29552553

Identification of the need for home visiting nurse: development of a new assessment tool

PubMed Central

Taguchi, Atsuko; Nagata, Satoko; Naruse, Takashi; Kuwahara, Yuki; Yamaguchi, Takuhiro; Murashima, Sachiyo

2014-01-01

Objective To develop a Home Visiting Nursing Service Need Assessment Form (HVNS-NAF) to standardize the decision about the need for home visiting nursing service. Methods The sample consisted of older adults who had received coordinated services by care managers. We defined the need for home visiting nursing service by elderly individuals as the decision of the need by a care manager so that the elderly can continue to live independently. Explanatory variables included demographic factors, medical procedure, severity of illness, and caregiver variables. Multiple logistic regression was carried out after univariate analyses to decide the variables to include and the weight of each variable in the HVNS-NAF. We then calculated the sensitivity and specificity of each cutoff value, and defined the score with the highest sensitivity and specificity as the cutoff value. Results Nineteen items were included in the final HVNS-NAF. When the cutoff value was 2 points, the sensitivity was 77.0%, specificity 68.5%, and positive predictive value 56.8%. Conclusions HVNS-NAF is the first validated standard based on characteristics of elderly clients who required home visiting nursing service. Using the HVNS-NAF may result in reducing the unmet need for home visiting nursing service and preventing hospitalization. PMID:24665229

Does emotion and its daily fluctuation correlate with depression? A cross-cultural analysis among six developing countries.

PubMed

Chan, Derwin K C; Zhang, Xin; Fung, Helene H; Hagger, Martin S

2015-03-01

Utilizing a World Health Organization (WHO) multi-national dataset, the present study examined the relationships between emotion, affective variability (i.e., the fluctuation of emotional status), and depression across six developing countries, including China (N=15,050); Ghana (N=5,573); India (N=12,198); Mexico (N=5,448); South Africa (N=4,227); and Russia (N=4,947). Using moderated logistic regression and hierarchical multiple regression, the effects of emotion, affective variability, culture, and their interactions on depression and depressive symptoms were examined when statistically controlling for a number of external factors (i.e., age, gender, marital status, education level, income, smoking, alcohol drinking, physical activity, sedentary behavior, and diet). The results revealed that negative emotion was a statistically significant predictor of depressive symptoms, but the strength of association was smaller in countries with a lower incidence of depression (i.e., China and Ghana). The association between negative affective variability and the risk of depression was higher in India and lower in Ghana. Findings suggested that culture not only was associated with the incidence of depression, but it could also moderate the effects of emotion and affective variability on depression or the experience of depressive symptoms. Copyright © 2014 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.

Poor Health and Experiences of Being Bullied in Adolescents: Self-Perceived Overweight and Frustration with Appearance Matter.

PubMed

Lin, Yi-Ching; Latner, Janet D; Fung, Xavier C C; Lin, Chung-Ying

2018-02-01

To examine the associations between body image (actual and self-perceived weight status; feelings about appearance) and health outcomes (overall health, life satisfaction, and mental health) and between body image and experiences of being bullied. Participants included 8,303 children from 7th to 10th grade in the Health Behavior of School-Aged Children (HBSC) 2009-2010 data set, a large-scale sample in the United States. Several multiple linear regressions (with health outcomes as dependent variables) and multivariate logistic regressions (with being bullied or not as dependent variable) were conducted to investigate the associations between each dependent variable and the following independent variables: relationship with parents, frustration with appearance, and actual and self-perceived weight status. Self-perceived underweight, self-perceived overweight (OW), and frustration with appearance were positively associated with being bullied. Frustration with appearance was a risk factor, while good relationship with parents was a protective factor, especially for psychological health outcomes. Self-perceived OW had a stronger association with the experience of being bullied than actual OW. The relationship between actual OW and being bullied might be attenuated when self-perceived OW is simultaneously considered. Body image may be an important factor in the association between weight status and the experience of being bullied. © 2017 The Obesity Society.

Effect of therapeutic class on counseling in community pharmacies.

PubMed

Vainio, Kirsti K; Airaksinen, Marja S A; Hyykky, Tarja T; Enlund, K Hannes

2002-05-01

To assess the effect and importance of the therapeutic class of a drug as a determinant for verbal counseling by community pharmacists. Direct external observations (n = 1431) of pharmacist-customer interactions at the point of delivery of prescription medicines were conducted in 7 community pharmacies in Finland. Trained observers noted whether the pharmacist provided information on directions for use, mode of action, and adverse effects. To examine factors associated with counseling, a multiple logistic regression analysis was constructed, with the dependent variable being counseling of any of the 3 observed topics. In addition to therapeutic class, other independent variables were the pharmacy; pharmacist's age, gender, and degree; and the customer's age, gender, previous use of medicine, and question asking. Provision of counseling differed significantly according to therapeutic classes. Counseling on any of the 3 observed topics was most likely to be provided for customers with antibiotics (80%) and least likely for customers with gynecologic preparations (18%). Differences between therapeutic classes remained statistically significant when the effects of the other variables were controlled for. Other significant predictors for any verbal counseling were the pharmacy, customer's previous use of the medicine, and question asking. Therapeutic class is an important variable that should be included in further studies and considered when comparing studies on patient counseling in community pharmacies.

Predicting Satisfaction for Unicompartmental Knee Arthroplasty Patients in an Asian Population.

PubMed

Lee, Merrill; Huang, Yilun; Chong, Hwei Chi; Ning, Yilin; Lo, Ngai Nung; Yeo, Seng Jin

2016-08-01

Despite renewed interest in unicompartmental knee arthroplasty (UKA), there is a paucity of published literature with regard to patient satisfaction after UKA within Asian populations. The purpose of this study is to identify characteristics and factors which may contribute to patient dissatisfaction after UKA in a multiracial Asian population. Seven hundred twenty-four UKAs were performed between January 2007 and April 2013. Preoperative and postoperative variables were prospectively captured, such as standardized knee scores, knee range of motion, and patient satisfaction scores. These variables were then analyzed with a multiple logistic regression model to determine statistically significant factors contributing to patients' satisfaction. Minimum duration of follow-up was 2 years, with an overall patient satisfaction rate of 92.2%. There was improvement in mean knee range of motion and across various standardized knee scores. Preoperative variables associated with patient dissatisfaction included a poorer preoperative Mental Component Summary, better preoperative knee extension, and better preoperative Oxford Knee Scores. Significant postoperative variables included better Oxford Knee Score at 6 months and Mental Component Summary at 2 years. Despite the impressive patient satisfaction rate of UKA in this Asian population, these findings suggest that there is a targeted group of patients with select preoperative factors who would benefit from preoperative counseling. Copyright © 2016 Elsevier Inc. All rights reserved.

Combinations of Multiple Neuroimaging Markers using Logistic Regression for Auxiliary Diagnosis of Alzheimer Disease and Mild Cognitive Impairment.

PubMed

Mao, Nini; Liu, Yunting; Chen, Kewei; Yao, Li; Wu, Xia

2018-06-05

Multiple neuroimaging modalities have been developed providing various aspects of information on the human brain. Used together and properly, these complementary multimodal neuroimaging data integrate multisource information which can facilitate a diagnosis and improve the diagnostic accuracy. In this study, 3 types of brain imaging data (sMRI, FDG-PET, and florbetapir-PET) were fused in the hope to improve diagnostic accuracy, and multivariate methods (logistic regression) were applied to these trimodal neuroimaging indices. Then, the receiver-operating characteristic (ROC) method was used to analyze the outcomes of the logistic classifier, with either each index, multiples from each modality, or all indices from all 3 modalities, to investigate their differential abilities to identify the disease. With increasing numbers of indices within each modality and across modalities, the accuracy of identifying Alzheimer disease (AD) increases to varying degrees. For example, the area under the ROC curve is above 0.98 when all the indices from the 3 imaging data types are combined. Using a combination of different indices, the results confirmed the initial hypothesis that different biomarkers were potentially complementary, and thus the conjoint analysis of multiple information from multiple sources would improve the capability to identify diseases such as AD and mild cognitive impairment. © 2018 S. Karger AG, Basel.

Regression: The Apple Does Not Fall Far From the Tree.

PubMed

Vetter, Thomas R; Schober, Patrick

2018-05-15

Researchers and clinicians are frequently interested in either: (1) assessing whether there is a relationship or association between 2 or more variables and quantifying this association; or (2) determining whether 1 or more variables can predict another variable. The strength of such an association is mainly described by the correlation. However, regression analysis and regression models can be used not only to identify whether there is a significant relationship or association between variables but also to generate estimations of such a predictive relationship between variables. This basic statistical tutorial discusses the fundamental concepts and techniques related to the most common types of regression analysis and modeling, including simple linear regression, multiple regression, logistic regression, ordinal regression, and Poisson regression, as well as the common yet often underrecognized phenomenon of regression toward the mean. The various types of regression analysis are powerful statistical techniques, which when appropriately applied, can allow for the valid interpretation of complex, multifactorial data. Regression analysis and models can assess whether there is a relationship or association between 2 or more observed variables and estimate the strength of this association, as well as determine whether 1 or more variables can predict another variable. Regression is thus being applied more commonly in anesthesia, perioperative, critical care, and pain research. However, it is crucial to note that regression can identify plausible risk factors; it does not prove causation (a definitive cause and effect relationship). The results of a regression analysis instead identify independent (predictor) variable(s) associated with the dependent (outcome) variable. As with other statistical methods, applying regression requires that certain assumptions be met, which can be tested with specific diagnostics.

Comparing Building and Neighborhood-Scale Variability of CO₂ and O₃ to Inform Deployment Considerations for Low-Cost Sensor System Use.

PubMed

Collier-Oxandale, Ashley; Coffey, Evan; Thorson, Jacob; Johnston, Jill; Hannigan, Michael

2018-04-26

The increased use of low-cost air quality sensor systems, particularly by communities, calls for the further development of best-practices to ensure these systems collect usable data. One area identified as requiring more attention is that of deployment logistics, that is, how to select deployment sites and how to strategically place sensors at these sites. Given that sensors are often placed at homes and businesses, ideal placement is not always possible. Considerations such as convenience, access, aesthetics, and safety are also important. To explore this issue, we placed multiple sensor systems at an existing field site allowing us to examine both neighborhood-level and building-level variability during a concurrent period for CO₂ (a primary pollutant) and O₃ (a secondary pollutant). In line with previous studies, we found that local and transported emissions as well as thermal differences in sensor systems drive variability, particularly for high-time resolution data. While this level of variability is unlikely to affect data on larger averaging scales, this variability could impact analysis if the user is interested in high-time resolution or examining local sources. However, with thoughtful placement and thorough documentation, high-time resolution data at the neighborhood level has the potential to provide us with entirely new information on local air quality trends and emissions.

Survey on Tuberculosis Patients in Rural Areas in China: Tracing the Role of Stigma in Psychological Distress.

PubMed

Xu, Minlan; Markström, Urban; Lyu, Juncheng; Xu, Lingzhong

2017-10-04

Depressed patients had risks of non-adherence to medication, which brought a big challenge for the control of tuberculosis (TB). The stigma associated with TB may be the reason for distress. This study aimed to assess the psychological distress among TB patients living in rural areas in China and to further explore the relation of experienced stigma to distress. This study was a cross-sectional study with multi-stage randomized sampling for recruiting TB patients. Data was collected by the use of interviewer-led questionnaires. A total of 342 eligible and accessible TB patients being treated at home were included in the survey. Psychological distress was measured using the Kessler Psychological Distress Scale (K10). Experienced stigma was measured using a developed nine-item stigma questionnaire. Univariate analysis and multiple logistic regression were used to analyze the variables related to distress, respectively. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to present the strength of the associations. Finally, the prediction of logistic model was assessed in form of the Receiver Operating Characteristic (ROC) curve and the area under the ROC curve (AUC). According to the referred cut-off point from K10, this study revealed that 65.2% (223/342) of the participants were categorized as having psychological distress. Both the stigma questionnaire and the K10 were proven to be reliable and valid in measurement. Further analysis found that experienced stigma and illness severity were significant variables to psychological distress in the model of logistic regression. The model was assessed well in predicting distress by use of experienced stigma and illness severity in form of ROC and AUC. Rural TB patients had a high prevalence of psychological distress. Experience of stigma played a significant role in psychological distress. To move the barrier of stigma from the surroundings could be a good strategy in reducing distress for the patients and TB controlling for public health management.

Protecting complex infrastructures against multiple strategic attackers

NASA Astrophysics Data System (ADS)

Hausken, Kjell

2011-01-01

Infrastructures are analysed subject to defence by a strategic defender and attack by multiple strategic attackers. A framework is developed where each agent determines how much to invest in defending versus attacking each of multiple targets. A target can have economic, human and symbolic values, which generally vary across agents. Investment expenditure functions for each agent can be linear in the investment effort, concave, convex, logistic, can increase incrementally, or can be subject to budget constraints. Contest success functions (e.g., ratio and difference forms) determine the probability of a successful attack on each target, dependent on the relative investments of the defender and attackers on each target, and on characteristics of the contest. Targets can be in parallel, in series, interlinked, interdependent or independent. The defender minimises the expected damage plus the defence expenditures. Each attacker maximises the expected damage minus the attack expenditures. The number of free choice variables equals the number of agents times the number of targets, or lower if there are budget constraints. Each agent is interested in how his investments vary across the targets, and the impact on his utilities. Alternative optimisation programmes are discussed, together with repeated games, dynamic games and incomplete information. An example is provided for illustration.

Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey

NASA Astrophysics Data System (ADS)

Duman, T. Y.; Can, T.; Gokceoglu, C.; Nefeslioglu, H. A.; Sonmez, H.

2006-11-01

As a result of industrialization, throughout the world, cities have been growing rapidly for the last century. One typical example of these growing cities is Istanbul, the population of which is over 10 million. Due to rapid urbanization, new areas suitable for settlement and engineering structures are necessary. The Cekmece area located west of the Istanbul metropolitan area is studied, because the landslide activity is extensive in this area. The purpose of this study is to develop a model that can be used to characterize landslide susceptibility in map form using logistic regression analysis of an extensive landslide database. A database of landslide activity was constructed using both aerial-photography and field studies. About 19.2% of the selected study area is covered by deep-seated landslides. The landslides that occur in the area are primarily located in sandstones with interbedded permeable and impermeable layers such as claystone, siltstone and mudstone. About 31.95% of the total landslide area is located at this unit. To apply logistic regression analyses, a data matrix including 37 variables was constructed. The variables used in the forwards stepwise analyses are different measures of slope, aspect, elevation, stream power index (SPI), plan curvature, profile curvature, geology, geomorphology and relative permeability of lithological units. A total of 25 variables were identified as exerting strong influence on landslide occurrence, and included by the logistic regression equation. Wald statistics values indicate that lithology, SPI and slope are more important than the other parameters in the equation. Beta coefficients of the 25 variables included the logistic regression equation provide a model for landslide susceptibility in the Cekmece area. This model is used to generate a landslide susceptibility map that correctly classified 83.8% of the landslide-prone areas.

Expeditionary Logistics: How the Marine Corps Supports Its Expeditionary Operations

DTIC Science & Technology

2015-06-01

little additional information of value with regard to the U.S. Marine Corps and expeditionary logistics methodology. Since the expeditionary methodology...size and scope, necessitating differing levels of material support. Additionally , the same variables define the level of Combat Service Support that is...lie outside of doctrine and few manuals have been written discussing how the Marine Corps performs expeditionary logistics. Additionally , few sources

Factors associated with cigarette smoking among public school adolescents.

PubMed

Viana, Tatiana Barreto Pereira; Camargo, Climene Laura de; Gomes, Nadirlene Pereira; Felzemburgh, Ridalva Dias Martins; Mota, Rosana Santos; Lima, Carla Cristina Oliveira de Jesus

2018-01-01

Objective Estimating the prevalence of cigarette smoking and its association with sociodemographic variables, sexual initiation and experience with domestic violence among adolescents from public schools in Guanambi, Bahia, Brazil. Method A crosssectional study carried out with adolescents. Data were collected through interviews guided by a structured instrument, and analyzed according to descriptive and inferential statistics with multiple logistic regression. Results A total of 370 adolescents participated in the study. The prevalence of cigarette smoking was 17.6% and a statistically significant association was observed between the variables: age over 15 years (PR = 5.63 and 95% CI: 1.33 - 23.85), males (PR = 2.53 and 95% CI: 1.47 - 4.37), no reported religion (PR = 1.93 and 95% CI: 0.99 - 3.75), working (PR = 2.17 and 95% CI: 1.25 - 3.74), onset of sexual activity (PR = 10.64 and CI= 95%: 5.31 - 21.33) and experience of domestic violence (PR = 3.61 and 95% CI: 2.07 - 3.28). Conclusion The prevalence of cigarette smoking and the associated variables point to the need for intervention strategies among more vulnerable groups of adolescents, encompassing family involvement and assistance from teachers and health professionals, in particular nurses working in Primary Care.

Mentorship and job satisfaction among Navy family physicians.

PubMed

Saperstein, Adam K; Viera, Anthony J; Firnhaber, Gina C

2012-08-01

Among civilian academic physicians, having a mentor is associated with greater job satisfaction. Whether this is true for military physicians is unknown. We sought to examine whether having a mentor is associated with positive job satisfaction among Navy family physicians. A web-based survey was sent to all Navy family physicians in the Specialty leader's database in May 2008. Our main outcome variable was "positive job satisfaction," and our main exposure variable was being in a mentor relationship. Chi-square was used to test for difference in frequencies in categorical variables and logistic regression was used to adjust for covariates. The response rate was 60.2% (186/309). Among respondents, 73.7% reported positive job satisfaction. Factors associated with positive job satisfaction included having a mentor, being >9 years postresidency, spending <50% of time in patient care, higher rank, male gender, and being active in research. After adjustment for these factors, having a mentor remained significantly associated with positive job satisfaction (odds ratio 2.86, 95% confidence interval 1.22-6.71). Having a mentor is associated with positive job satisfaction among Navy family physicians, even after adjusting for multiple other factors. An implication is that a mentorship program may be a strategy for improving job satisfaction.

Population-Based Questionnaire Survey on Health Effects of Aircraft Noise on Residents Living around U.S. Airfields in the RYUKYUS—PART i: AN Analysis of 12 Scale Scores

NASA Astrophysics Data System (ADS)

MIYAKITA, T.; MATSUI, T.; ITO, A.; TOKUYAMA, T.; HIRAMATSU, K.; OSADA, Y.; YAMAMOTO, T.

2002-02-01

A questionnaire survey was made of health effects of aircraft noise on residents living around Kadena and Futenma airfields using the Todai Health Index. Aircraft noise exposure expressed by Ldnranged from under 55 to over 70 in the surveyed area. The number of valid answers was 7095, including 848 among the control group. Twelve scale scores were converted to dichotomous variables based on scale scores of the 90 percentile value or the 10 percentile value in the control group. Multiple logistic regression analysis was done taking 12 scale scores converted into the dependent variable andLdn , age (six levels), sex, occupation (four categories) and the interaction of age and sex as the independent variables. Significant dose-response relationships were found in the scale scores for vague complaints, respiratory, digestive, mental instability, depression and nervousness. The results suggest that the residents living around Kadena and Futenma airfields may suffer both physical and mental effects as a result of exposure to military aircraft noise and that such responses increase with the level of noise exposure (Ldn).

Effects on employees of controlling working hours and working schedules.

PubMed

Kubo, T; Takahashi, M; Togo, F; Liu, X; Shimazu, A; Tanaka, K; Takaya, M

2013-03-01

High levels of control over working time and low variability in working hours have been associated with improved health-related outcomes. The potential mechanisms for this association remain unclear. To examine how work-time control and variability of working times are associated with fatigue recovery, sleep quality, work-life balance, and 'near misses' at work. Manufacturing sector employees completed a questionnaire that assessed work-time control, work-time variability, fatigue recovery, sleep quality, work-life balance and the frequency of near misses in the past 6 months. Mixed model analysis of covariance and multiple logistic regression analysis tested the main effects of work-time control and variability and their interaction, while adjusting for age, sex, work schedules, and overtime work in the past month. Subscales of work-time control were also investigated (control over daily working hours and over days off). One thousand three hundred and seventy-two completed questionnaires were returned, a response rate of 69%. A significantly higher quality of sleep and better work-life balance were found in the 'high control with low variability' reference group than in the other groups. Significantly better recovery of fatigue was also observed in the group having control over days off with low variability. While near misses were more frequent in the group with high control over daily working hours coupled with high variability compared with the reference group this was not significant. High work-time control and low variability were associated with favourable outcomes of health and work-life balance. This combined effect was not observed for the safety outcome addressed here.

Multivariate logistic regression for predicting total culturable virus presence at the intake of a potable-water treatment plant: novel application of the atypical coliform/total coliform ratio.

PubMed

Black, L E; Brion, G M; Freitas, S J

2007-06-01

Predicting the presence of enteric viruses in surface waters is a complex modeling problem. Multiple water quality parameters that indicate the presence of human fecal material, the load of fecal material, and the amount of time fecal material has been in the environment are needed. This paper presents the results of a multiyear study of raw-water quality at the inlet of a potable-water plant that related 17 physical, chemical, and biological indices to the presence of enteric viruses as indicated by cytopathic changes in cell cultures. It was found that several simple, multivariate logistic regression models that could reliably identify observations of the presence or absence of total culturable virus could be fitted. The best models developed combined a fecal age indicator (the atypical coliform [AC]/total coliform [TC] ratio), the detectable presence of a human-associated sterol (epicoprostanol) to indicate the fecal source, and one of several fecal load indicators (the levels of Giardia species cysts, coliform bacteria, and coprostanol). The best fit to the data was found when the AC/TC ratio, the presence of epicoprostanol, and the density of fecal coliform bacteria were input into a simple, multivariate logistic regression equation, resulting in 84.5% and 78.6% accuracies for the identification of the presence and absence of total culturable virus, respectively. The AC/TC ratio was the most influential input variable in all of the models generated, but producing the best prediction required additional input related to the fecal source and the fecal load. The potential for replacing microbial indicators of fecal load with levels of coprostanol was proposed and evaluated by multivariate logistic regression modeling for the presence and absence of virus.

Acute otitis media and sociomedical risk factors among unselected children in Greenland.

PubMed

Homøe, P; Christensen, R B; Bretlau, P

1999-06-15

To describe the sociomedical risk factors associated with episodes of acute otitis media (AOM), recurrent AOM (rAOM), and chronic otitis media (COM) in Greenlandic children and especially to point out children at high risk of rAOM (defined as > 5 AOM episodes since birth) and COM which are prevalent among Inuit children all over the Arctic. The study design was cross-sectional and included 740 unselected children, 3, 4, 5, and 8-years-old, living in two major Greenlandic towns, Nuuk and Sisimiut. All children were otologically examined and the parents answered a questionnaire containing sociomedical variables including ethnicity, family history of OM, housing, insulation, crowding, daycare, passive cigarette smoking, breast feeding, type of diet, allergy, and chronic diseases. Historical data were cross-checked in medical records which also formed the basis for the drop-out analyses. Statistical analyses included frequency tests, calculation of odds ratio (OR), and multiple logistic regression. The attendance rate was 86%. Former episode of AOM was reported by 2/3 of the children, rAOM by 20%, and COM by 9%. The following variables were found significantly more often in children with AOM by simple frequency testing: Parental (OR = 1.83), sibling (OR = 1.62), and parental plus sibling (OR = 2.56) history of OM, crowding (OR = 5.55), long period of exclusive breast feeding ( > 4 months) (OR = 2.47), and recent acute disease (P = 0.034). The following variables were found significantly more often in children with rAOM or COM by simple frequency testing: Parental history of OM (OR = 1.60; OR = 2.11, respectively) and no recall of breast feeding (P = 0.005; P = 0.003, respectively). Also, COM was found significantly more often in children with two Greenlandic parents (OR = 3.07). A multiple logistic regression test denoted only parental history of OM (OR = 1.82) and long period of exclusive breast feeding (OR = 1.14) as significant predictors of AOM. Many of the risk factors usually associated with AOM could not be confirmed as risk factors in this survey. Parental history of OM and long period of exclusive breast feeding were the strongest factors associated with AOM in Greenlandic children and ethnicity was associated with COM. However, the study confirms that AOM is a multifactorial disease determined by a number of genetic and environmental factors.

A comparison of rule-based and machine learning approaches for classifying patient portal messages.

PubMed

Cronin, Robert M; Fabbri, Daniel; Denny, Joshua C; Rosenbloom, S Trent; Jackson, Gretchen Purcell

2017-09-01

Secure messaging through patient portals is an increasingly popular way that consumers interact with healthcare providers. The increasing burden of secure messaging can affect clinic staffing and workflows. Manual management of portal messages is costly and time consuming. Automated classification of portal messages could potentially expedite message triage and delivery of care. We developed automated patient portal message classifiers with rule-based and machine learning techniques using bag of words and natural language processing (NLP) approaches. To evaluate classifier performance, we used a gold standard of 3253 portal messages manually categorized using a taxonomy of communication types (i.e., main categories of informational, medical, logistical, social, and other communications, and subcategories including prescriptions, appointments, problems, tests, follow-up, contact information, and acknowledgement). We evaluated our classifiers' accuracies in identifying individual communication types within portal messages with area under the receiver-operator curve (AUC). Portal messages often contain more than one type of communication. To predict all communication types within single messages, we used the Jaccard Index. We extracted the variables of importance for the random forest classifiers. The best performing approaches to classification for the major communication types were: logistic regression for medical communications (AUC: 0.899); basic (rule-based) for informational communications (AUC: 0.842); and random forests for social communications and logistical communications (AUCs: 0.875 and 0.925, respectively). The best performing classification approach of classifiers for individual communication subtypes was random forests for Logistical-Contact Information (AUC: 0.963). The Jaccard Indices by approach were: basic classifier, Jaccard Index: 0.674; Naïve Bayes, Jaccard Index: 0.799; random forests, Jaccard Index: 0.859; and logistic regression, Jaccard Index: 0.861. For medical communications, the most predictive variables were NLP concepts (e.g., Temporal_Concept, which maps to 'morning', 'evening' and Idea_or_Concept which maps to 'appointment' and 'refill'). For logistical communications, the most predictive variables contained similar numbers of NLP variables and words (e.g., Telephone mapping to 'phone', 'insurance'). For social and informational communications, the most predictive variables were words (e.g., social: 'thanks', 'much', informational: 'question', 'mean'). This study applies automated classification methods to the content of patient portal messages and evaluates the application of NLP techniques on consumer communications in patient portal messages. We demonstrated that random forest and logistic regression approaches accurately classified the content of portal messages, although the best approach to classification varied by communication type. Words were the most predictive variables for classification of most communication types, although NLP variables were most predictive for medical communication types. As adoption of patient portals increases, automated techniques could assist in understanding and managing growing volumes of messages. Further work is needed to improve classification performance to potentially support message triage and answering. Copyright © 2017 Elsevier B.V. All rights reserved.

Predictors for Employment Status in People With Multiple Sclerosis: A 10-Year Longitudinal Observational Study.

PubMed

Forslin, Mia; Fink, Katharina; Hammar, Ulf; von Koch, Lena; Johansson, Sverker

2018-01-31

To identify predictors for employment status after 10 years in a cohort of people with multiple sclerosis (MS), with the aim to increase knowledge concerning factors present at an early stage that are important for working life and work-life balance. A 10-year longitudinal observational cohort study. University hospital. A consecutive sample of people with MS (N=154) of working age were included at baseline, of which a total of 116 people participated in the 10-year follow-up; 27 people declined participation and 11 were deceased. Not applicable. Baseline data on personal factors and functioning were used as independent variables. Employment status 10 years after baseline, categorized as full-time work, part-time work, and no work, was used as the dependent variable. A generalized ordinal logistic regression was used to analyze the predictive value of the independent variables. Predictors for full- or part-time work after 10 years were young age (P=.002), low perceived physical impact of MS (P=.02), fatigue (P=.03), full-time work (P=.001), and high frequency of social/lifestyle activities (P=.001) at baseline. Low perceived physical impact of MS (P=.02) at baseline also predicted full-time work after 10 years. This study underlines the complexity of working life for people with MS, and indicates that it may be valuable to give more attention to the balance between working and private life, both in clinical practice and future research, to achieve a sustainable working life over time. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Asthma exacerbation and proximity of residence to major roads: a population-based matched case-control study among the pediatric Medicaid population in Detroit, Michigan

PubMed Central

2011-01-01

Background The relationship between asthma and traffic-related pollutants has received considerable attention. The use of individual-level exposure measures, such as residence location or proximity to emission sources, may avoid ecological biases. Method This study focused on the pediatric Medicaid population in Detroit, MI, a high-risk population for asthma-related events. A population-based matched case-control analysis was used to investigate associations between acute asthma outcomes and proximity of residence to major roads, including freeways. Asthma cases were identified as all children who made at least one asthma claim, including inpatient and emergency department visits, during the three-year study period, 2004-06. Individually matched controls were randomly selected from the rest of the Medicaid population on the basis of non-respiratory related illness. We used conditional logistic regression with distance as both categorical and continuous variables, and examined non-linear relationships with distance using polynomial splines. The conditional logistic regression models were then extended by considering multiple asthma states (based on the frequency of acute asthma outcomes) using polychotomous conditional logistic regression. Results Asthma events were associated with proximity to primary roads with an odds ratio of 0.97 (95% CI: 0.94, 0.99) for a 1 km increase in distance using conditional logistic regression, implying that asthma events are less likely as the distance between the residence and a primary road increases. Similar relationships and effect sizes were found using polychotomous conditional logistic regression. Another plausible exposure metric, a reduced form response surface model that represents atmospheric dispersion of pollutants from roads, was not associated under that exposure model. Conclusions There is moderately strong evidence of elevated risk of asthma close to major roads based on the results obtained in this population-based matched case-control study. PMID:21513554

Nutritional variables and work-related accidents: a case-control study.

PubMed

de Medeiros, M A T; Zangirolani, Lia Thieme Oikawa; Cordeiro, Ricardo Carlos; da Costa, Proença Rossana Pacheco; Diez-Garcia, Rosa Wanda

2014-01-01

Nutritional aspects are important for the prevention of diseases and disorders, and few studies have focused on the relationship between risk of work injury and nutritional variables. This study aimed to verify whether nutritional variables constitute risk factors for work-related accidents. 1,422 industrial workers (600 cases plus 822 controls). A case-control study was carried out in an industrial city in south-east Brazil. A multiple logistic regression model was adjusted using work-related accidents as the response variable and nutritional variables as predictors. The associations were assessed by Odds Ratio (OR), with a p-value < 0.05. 47.29% of the workers were overweight or obese. Protective factors for work-related accidents were (a) attending formal education for an above average number of years (OR=0.91, p< 0.0001) and (b) eating a traditional dinner (OR=0.67, p=0.0087). Risks factors were (a) hard physical effort in the workplace (OR=1.37, p< 0.0001), (b) having lunch in the workplace (OR=1.57, p<0.0001) and (c) receiving government benefits in the form of food stamps (OR=1.39, p=0.0350) or food baskets (OR=1.30, p=0.0414). Our findings suggest an association between nutritional variables and work-related accidents. This indicates the need, during the formulation of policies for these kinds of government benefits, to include nutrition aspects in order to minimize work-related accidents risks.

Integrated Logistics Support Analysis of the International Space Station Alpha, Background and Summary of Mathematical Modeling and Failure Density Distributions Pertaining to Maintenance Time Dependent Parameters

NASA Technical Reports Server (NTRS)

Sepehry-Fard, F.; Coulthard, Maurice H.

1995-01-01

The process of predicting the values of maintenance time dependent variable parameters such as mean time between failures (MTBF) over time must be one that will not in turn introduce uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. A minor deviation in the values of the maintenance time dependent variable parameters such as MTBF over time will have a significant impact on the logistics resources demands, International Space Station availability and maintenance support costs. There are two types of parameters in the logistics and maintenance world: a. Fixed; b. Variable Fixed parameters, such as cost per man hour, are relatively easy to predict and forecast. These parameters normally follow a linear path and they do not change randomly. However, the variable parameters subject to the study in this report such as MTBF do not follow a linear path and they normally fall within the distribution curves which are discussed in this publication. The very challenging task then becomes the utilization of statistical techniques to accurately forecast the future non-linear time dependent variable arisings and events with a high confidence level. This, in turn, shall translate in tremendous cost savings and improved availability all around.

Association of glycaemic variability evaluated by continuous glucose monitoring with diabetic peripheral neuropathy in type 2 diabetic patients.

PubMed

Hu, Yu-Ming; Zhao, Li-Hua; Zhang, Xiu-Lin; Cai, Hong-Li; Huang, Hai-Yan; Xu, Feng; Chen, Tong; Wang, Xue-Qin; Guo, Ai-Song; Li, Jian-An; Su, Jian-Bin

2018-05-01

Diabetic peripheral neuropathy (DPN), a common microvascular complication of diabetes, is linked to glycaemic derangements. Glycaemic variability, as a pattern of glycaemic derangements, is a key risk factor for diabetic complications. We investigated the association of glycaemic variability with DPN in a large-scale sample of type 2 diabetic patients. In this cross-sectional study, we enrolled 982 type 2 diabetic patients who were screened for DPN and monitored by a continuous glucose monitoring (CGM) system between February 2011 and January 2017. Multiple glycaemic variability parameters, including the mean amplitude of glycaemic excursions (MAGE), mean of daily differences (MODD), standard deviation of glucose (SD), and 24-h mean glucose (24-h MG), were calculated from glucose profiles obtained from CGM. Other possible risks for DPN were also examined. Of the recruited type 2 diabetic patients, 20.1% (n = 197) presented with DPN, and these patients also had a higher MAGE, MODD, SD, and 24-h MG than patients without DPN (p < 0.001). Using univariate and multiple logistic regression analyses, MAGE and conventional risks including diabetic duration, HOMA-IR, and hemoglobin A1c (HbA1c) were found to be independent contributors to DPN, and the corresponding odds ratios (95% confidence interval) were 4.57 (3.48-6.01), 1.10 (1.03-1.17), 1.24 (1.09-1.41), and 1.33 (1.15-1.53), respectively. Receiver operating characteristic analysis indicated that the optimal MAGE cutoff value for predicting DPN was 4.60 mmol/L; the corresponding sensitivity was 64.47%, and the specificity was 75.54%. In addition to conventional risks including diabetic duration, HOMA-IR and HbA1c, increased glycaemic variability assessed by MAGE is a significant independent contributor to DPN in type 2 diabetic patients.

A Solution to Separation and Multicollinearity in Multiple Logistic Regression

PubMed Central

Shen, Jianzhao; Gao, Sujuan

2010-01-01

In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27–38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth’s penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study. PMID:20376286

A Solution to Separation and Multicollinearity in Multiple Logistic Regression.

PubMed

Shen, Jianzhao; Gao, Sujuan

2008-10-01

In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27-38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth's penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study.

A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test

NASA Technical Reports Server (NTRS)

Messer, Bradley P.

2004-01-01

Propulsion ground test facilities face the daily challenges of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Due to budgetary and schedule constraints, NASA and industry customers are pushing to test more components, for less money, in a shorter period of time. As these new rocket engine component test programs are undertaken, the lack of technology maturity in the test articles, combined with pushing the test facilities capabilities to their limits, tends to lead to an increase in facility breakdowns and unsuccessful tests. Over the last five years Stennis Space Center's propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and broken numerous test facility and test article parts. While various initiatives have been implemented to provide better propulsion test techniques and improve the quality, reliability, and maintainability of goods and parts used in the propulsion test facilities, unexpected failures during testing still occur quite regularly due to the harsh environment in which the propulsion test facilities operate. Previous attempts at modeling the lifecycle of a propulsion component test project have met with little success. Each of the attempts suffered form incomplete or inconsistent data on which to base the models. By focusing on the actual test phase of the tests project rather than the formulation, design or construction phases of the test project, the quality and quantity of available data increases dramatically. A logistic regression model has been developed form the data collected over the last five years, allowing the probability of successfully completing a rocket propulsion component test to be calculated. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),..,X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure. Logistic regression has primarily been used in the fields of epidemiology and biomedical research, but lends itself to many other applications. As indicated the use of logistic regression is not new, however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from the models provide project managers with insight and confidence into the affectivity of rocket engine component ground test projects. The initial success in modeling rocket propulsion ground test projects clears the way for more complex models to be developed in this area.

Flexibility evaluation of multiechelon supply chains.

PubMed

Almeida, João Flávio de Freitas; Conceição, Samuel Vieira; Pinto, Luiz Ricardo; de Camargo, Ricardo Saraiva; Júnior, Gilberto de Miranda

2018-01-01

Multiechelon supply chains are complex logistics systems that require flexibility and coordination at a tactical level to cope with environmental uncertainties in an efficient and effective manner. To cope with these challenges, mathematical programming models are developed to evaluate supply chain flexibility. However, under uncertainty, supply chain models become complex and the scope of flexibility analysis is generally reduced. This paper presents a unified approach that can evaluate the flexibility of a four-echelon supply chain via a robust stochastic programming model. The model simultaneously considers the plans of multiple business divisions such as marketing, logistics, manufacturing, and procurement, whose goals are often conflicting. A numerical example with deterministic parameters is presented to introduce the analysis, and then, the model stochastic parameters are considered to evaluate flexibility. The results of the analysis on supply, manufacturing, and distribution flexibility are presented. Tradeoff analysis of demand variability and service levels is also carried out. The proposed approach facilitates the adoption of different management styles, thus improving supply chain resilience. The model can be extended to contexts pertaining to supply chain disruptions; for example, the model can be used to explore operation strategies when subtle events disrupt supply, manufacturing, or distribution.

Independent risk factors of morbidity in penetrating colon injuries.

PubMed

Girgin, Sadullah; Gedik, Ercan; Uysal, Ersin; Taçyildiz, Ibrahim Halil

2009-05-01

The present study explored the factors effective on colon-related morbidity in patients with penetrating injury of the colon. The medical records of 196 patients were reviewed for variables including age, gender, factor of trauma, time between injury and operation, shock, duration of operation, Penetrating Abdominal Trauma Index (PATI), Injury Severity Score (ISS), site of colon injury, Colon Injury Score, fecal contamination, number of associated intra- and extraabdominal organ injuries, units of transfused blood within the first 24 hours, and type of surgery. In order to determine the independent risk factors, multivariate logistic regression analysis was performed. Gunshot wounds, interval between injury and operation > or =6 hours, shock, duration of the operation > or =6 hours, PATI > or =25, ISS > or =20, Colon Injury Score > or = grade 3, major fecal contamination, number of associated intraabdominal organ injuries >2, number of associated extraabdominal organ injuries >2, multiple blood transfusions, and diversion were significantly associated with morbidity. Multivariate logistic regression analysis showed diversion and transfusion of > or =4 units in the first 24 hours as independent risk factors affecting colon-related morbidity. Diversion and transfusion of > or =4 units in the first 24 hours were determined to be independent risk factors for colon-related morbidity.

Generic emergence of power law distributions and Lévy-Stable intermittent fluctuations in discrete logistic systems

NASA Astrophysics Data System (ADS)

Biham, Ofer; Malcai, Ofer; Levy, Moshe; Solomon, Sorin

1998-08-01

The dynamics of generic stochastic Lotka-Volterra (discrete logistic) systems of the form wi(t+1)=λ(t)wi(t)+aw¯(t)-bwi(t)w¯(t) is studied by computer simulations. The variables wi, i=1,...,N, are the individual system components and w¯(t)=(1/N)∑iwi(t) is their average. The parameters a and b are constants, while λ(t) is randomly chosen at each time step from a given distribution. Models of this type describe the temporal evolution of a large variety of systems such as stock markets and city populations. These systems are characterized by a large number of interacting objects and the dynamics is dominated by multiplicative processes. The instantaneous probability distribution P(w,t) of the system components wi turns out to fulfill a Pareto power law P(w,t)~w-1-α. The time evolution of w¯(t) presents intermittent fluctuations parametrized by a Lévy-stable distribution with the same index α, showing an intricate relation between the distribution of the wi's at a given time and the temporal fluctuations of their average.

Flexibility evaluation of multiechelon supply chains

PubMed Central

Conceição, Samuel Vieira; Pinto, Luiz Ricardo; de Camargo, Ricardo Saraiva; Júnior, Gilberto de Miranda

2018-01-01

Multiechelon supply chains are complex logistics systems that require flexibility and coordination at a tactical level to cope with environmental uncertainties in an efficient and effective manner. To cope with these challenges, mathematical programming models are developed to evaluate supply chain flexibility. However, under uncertainty, supply chain models become complex and the scope of flexibility analysis is generally reduced. This paper presents a unified approach that can evaluate the flexibility of a four-echelon supply chain via a robust stochastic programming model. The model simultaneously considers the plans of multiple business divisions such as marketing, logistics, manufacturing, and procurement, whose goals are often conflicting. A numerical example with deterministic parameters is presented to introduce the analysis, and then, the model stochastic parameters are considered to evaluate flexibility. The results of the analysis on supply, manufacturing, and distribution flexibility are presented. Tradeoff analysis of demand variability and service levels is also carried out. The proposed approach facilitates the adoption of different management styles, thus improving supply chain resilience. The model can be extended to contexts pertaining to supply chain disruptions; for example, the model can be used to explore operation strategies when subtle events disrupt supply, manufacturing, or distribution. PMID:29584755

Barriers to administering intravenous tissue plasminogen activator (tPA) for acute ischemic stroke in the emergency department: A cross-sectional survey of stroke centers.

PubMed

Hargis, Mitch; Shah, Jharna N; Mazabob, Janine; Rao, Chethan Venkatasubba; Suarez, Jose I; Bershad, Eric M

2015-08-01

The logistics involved in administration of IV tPA for acute ischemic stroke patients are complex, and may contribute to variability in door-to-needle times between different hospitals. We sought to identify practice patterns in stroke centers related to IV tPA use. We hypothesized that there would be significant variability in logistics related to ancillary staff (i.e. nursing, pharmacists) processes in the emergency room setting. A 21 question survey was distributed to attendees of the AHA/ASA Southwest Affiliate Stroke Coordinators Conference to evaluate potential barriers and delays with regards to thrombolysis for acute strokes patients in the Emergency Department setting. Answers were anonymous and aggregated to examine trends in responses. Responses were obtained from 37 of 67 (55%) stroke centers, which were located mainly in the Southwest United States. Logistical processes differed between facilities. Nursing and pharmacy carried stroke pagers in only 19% of the centers, and pharmacy responded to stroke alerts only one-third of centers. Insertion of Foley catheters and nasogastric tubes prior to tPA was routine in some of the sites. Other barriers to IV tPA administration included physician reluctance and inadequate communication between health care providers. Practices regarding logistics for giving IV tPA may be variable amongst different stroke centers. Given this potential variability, prospective evaluation to confirm these preliminary findings is warranted. Copyright © 2015 Elsevier B.V. All rights reserved.

Generalized logistic map and its application in chaos based cryptography

NASA Astrophysics Data System (ADS)

Lawnik, M.

2017-12-01

The logistic map is commonly used in, for example, chaos based cryptography. However, its properties do not render a safe construction of encryption algorithms. Thus, the scope of the paper is a proposal of generalization of the logistic map by means of a wellrecognized family of chaotic maps. In the next step, an analysis of Lyapunov exponent and the distribution of the iterative variable are studied. The obtained results confirm that the analyzed model can safely and effectively replace a classic logistic map for applications involving chaotic cryptography.

Multiple regression analysis of anthropometric measurements influencing the cephalic index of male Japanese university students.

PubMed

Hossain, Md Golam; Saw, Aik; Alam, Rashidul; Ohtsuki, Fumio; Kamarul, Tunku

2013-09-01

Cephalic index (CI), the ratio of head breadth to head length, is widely used to categorise human populations. The aim of this study was to access the impact of anthropometric measurements on the CI of male Japanese university students. This study included 1,215 male university students from Tokyo and Kyoto, selected using convenient sampling. Multiple regression analysis was used to determine the effect of anthropometric measurements on CI. The variance inflation factor (VIF) showed no evidence of a multicollinearity problem among independent variables. The coefficients of the regression line demonstrated a significant positive relationship between CI and minimum frontal breadth (p < 0.01), bizygomatic breadth (p < 0.01) and head height (p < 0.05), and a negative relationship between CI and morphological facial height (p < 0.01) and head circumference (p < 0.01). Moreover, the coefficient and odds ratio of logistic regression analysis showed a greater likelihood for minimum frontal breadth (p < 0.01) and bizygomatic breadth (p < 0.01) to predict round-headedness, and morphological facial height (p < 0.05) and head circumference (p < 0.01) to predict long-headedness. Stepwise regression analysis revealed bizygomatic breadth, head circumference, minimum frontal breadth, head height and morphological facial height to be the best predictor craniofacial measurements with respect to CI. The results suggest that most of the variables considered in this study appear to influence the CI of adult male Japanese students.

Age-related risk factors with nonfatal traffic accidents in urban areas in Maringá, Paraná, Brazil.

PubMed

de Melo, Willian Augusto; Alarcão, Ana Carolina Jacinto; de Oliveira, Analice Paula Rocha; Pelloso, Sandra Marisa; Carvalho, Maria Dalva de Barros

2017-02-17

The present study aimed to analyze the factors associated with the occurrence of nonfatal traffic accidents regarding age. A retrospective, transversal, and analytical study was carried out in the municipality of Maringá, Paraná, Brazil, based on data from Boletins de Ocorrência de Acidente de Trânsito ("Police Occurrence Bulletins"; BOATs). Following probability sampling, the sociodemographic aspects, logistics, environmental conditions, and time of occurrence of 418 cases of accidents were analyzed. The age of the victims was considered to be the dependent variable. The data were analyzed using descriptive statistics and bivariate, multivariate, and variance analysis, considering a confidence interval of 95% and a significance level of 5% (P <.05). Results revealed that young people (15-29 years) were twice as likely to be hospitalized due to severe injuries. Young motorcyclists had a 2.5 times greater chance of suffering accidents (P <.001); the use of other vehicles such as cars, bicycles, buses, and trucks represented a protective factor for this group (P <.05). Multiple logistic regression revealed that the main predictors for the occurrence of accidents were being single, having over 8 years of education, having had a driver's license for less than 3 years, roads with low luminosity, and driving at night. Demographic, environmental, and logistical factors were associated with morbidity due to traffic accidents among young people. These results challenge society and policy makers to create more effective strategies to minimize this serious public health problem.

Age of child, more than HPV type, is associated with clinical course in recurrent respiratory papillomatosis.

PubMed

Buchinsky, Farrel J; Donfack, Joseph; Derkay, Craig S; Choi, Sukgi S; Conley, Stephen F; Myer, Charles M; McClay, John E; Campisi, Paolo; Wiatrak, Brian J; Sobol, Steven E; Schweinfurth, John M; Tsuji, Domingos H; Hu, Fen Z; Rockette, Howard E; Ehrlich, Garth D; Post, J Christopher

2008-05-28

RRP is a devastating disease in which papillomas in the airway cause hoarseness and breathing difficulty. The disease is caused by human papillomavirus (HPV) 6 or 11 and is very variable. Patients undergo multiple surgeries to maintain a patent airway and in order to communicate vocally. Several small studies have been published in which most have noted that HPV 11 is associated with a more aggressive course. Papilloma biopsies were taken from patients undergoing surgical treatment of RRP and were subjected to HPV typing. 118 patients with juvenile-onset RRP with at least 1 year of clinical data and infected with a single HPV type were analyzed. HPV 11 was encountered in 40% of the patients. By our definition, most of the patients in the sample (81%) had run an aggressive course. The odds of a patient with HPV 11 running an aggressive course were 3.9 times higher than that of patients with HPV 6 (Fisher's exact p = 0.017). However, clinical course was more closely associated with age of the patient (at diagnosis and at the time of the current surgery) than with HPV type. Patients with HPV 11 were diagnosed at a younger age (2.4y) than were those with HPV 6 (3.4y) (p = 0.014). Both by multiple linear regression and by multiple logistic regression HPV type was only weakly associated with metrics of disease course when simultaneously accounting for age. CONCLUSIONS/SIGNIFICANCE ABSTRACT: The course of RRP is variable and a quarter of the variability can be accounted for by the age of the patient. HPV 11 is more closely associated with a younger age at diagnosis than it is associated with an aggressive clinical course. These data suggest that there are factors other than HPV type and age of the patient that determine disease course.

Susceptibility assessment of earthquake-triggered landslides in El Salvador using logistic regression

NASA Astrophysics Data System (ADS)

García-Rodríguez, M. J.; Malpica, J. A.; Benito, B.; Díaz, M.

2008-03-01

This work has evaluated the probability of earthquake-triggered landslide occurrence in the whole of El Salvador, with a Geographic Information System (GIS) and a logistic regression model. Slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness are the predictor variables used to determine the dependent variable of occurrence or non-occurrence of landslides within an individual grid cell. The results illustrate the importance of terrain roughness and soil type as key factors within the model — using only these two variables the analysis returned a significance level of 89.4%. The results obtained from the model within the GIS were then used to produce a map of relative landslide susceptibility.

The reliable solution and computation time of variable parameters logistic model

NASA Astrophysics Data System (ADS)

Wang, Pengfei; Pan, Xinnong

2018-05-01

The study investigates the reliable computation time (RCT, termed as T c) by applying a double-precision computation of a variable parameters logistic map (VPLM). Firstly, by using the proposed method, we obtain the reliable solutions for the logistic map. Secondly, we construct 10,000 samples of reliable experiments from a time-dependent non-stationary parameters VPLM and then calculate the mean T c. The results indicate that, for each different initial value, the T cs of the VPLM are generally different. However, the mean T c trends to a constant value when the sample number is large enough. The maximum, minimum, and probable distribution functions of T c are also obtained, which can help us to identify the robustness of applying a nonlinear time series theory to forecasting by using the VPLM output. In addition, the T c of the fixed parameter experiments of the logistic map is obtained, and the results suggest that this T c matches the theoretical formula-predicted value.

Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

PubMed

Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

2016-01-01

Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

Can aircraft noise less than or equal 115 to dBA adversely affect reproductive outcome in USAF women?

NASA Astrophysics Data System (ADS)

Brubaker, P. A.

1985-06-01

It has been suggested, mainly through animal studies, that exposure to high noise levels may be associated with lower birth weight, reduced gestational length and other adverse reproductive outcomes. Few studies have been done on humans to show this association. The Air Force employs pregnant women in areas where there is a high potential for exposure to high noise levels. This study proposes a method to determine if there is an association between high frequency noise levels or = 115 dBA and adverse reproductive outcomes through a review of records and self-administered questionnaires in a case-comparison design. Prevelance rates will be calculated and a multiple logistic regression analysis computed for the independent variables that can affect reproduction.

Smoking, alcohol consumption and betal-quid chewing among young adult Myanmar laborers in Thailand.

PubMed

Htin, Kyaw; Howteerakull, Nopporn; Suwannapong, Nawarat; TipayamongkholgulI, Mathuros

2014-07-01

Health-risk behaviors among young adults are a serious public health problem. This cross sectional study aimed to estimate the prevalence of single and concurrent multiple health-risk behaviors: smoking tobacco, consuming alcohol, and chewing betel quid among young adult Myanmar laborers in Mae Sot District, Tak Province, Thailand. Three hundred Myanmar laborers, aged 18-24 years, were interviewed using a structured questionnaire. About 33.6% reported no risk behaviors, 24.7% had one, and 41.7% had two or three risk behaviors. Multinomial logistic regression analysis showed six variables were significantly associated with health-risk behaviors: male gender, high/moderate custom/traditional influences, friends who smoked/consumed alcohol/chewed betel quid, and exposure to betel-quid chewing by other family members.

Patterns of Movement in Foster Care: An Optimal Matching Analysis

PubMed Central

Havlicek, Judy

2011-01-01

Placement instability remains a vexing problem for child welfare agencies across the country. This study uses child welfare administrative data to retrospectively follow the entire placement histories (birth to age 17.5) of 474 foster youth who reached the age of majority in the state of Illinois and to search for patterns in their movement through the child welfare system. Patterns are identified through optimal matching and hierarchical cluster analyses. Multiple logistic regression is used to analyze administrative and survey data in order to examine covariates related to patterns. Five distinct patterns of movement are differentiated: Late Movers, Settled with Kin, Community Care, Institutionalized, and Early Entry. These patterns suggest high but variable rates of movement. Implications for child welfare policy and service provision are discussed. PMID:20873020

Country logistics performance and disaster impact.

PubMed

Vaillancourt, Alain; Haavisto, Ira

2016-04-01

The aim of this paper is to deepen the understanding of the relationship between country logistics performance and disaster impact. The relationship is analysed through correlation analysis and regression models for 117 countries for the years 2007 to 2012 with disaster impact variables from the International Disaster Database (EM-DAT) and logistics performance indicators from the World Bank. The results show a significant relationship between country logistics performance and disaster impact overall and for five out of six specific logistic performance indicators. These specific indicators were further used to explore the relationship between country logistic performance and disaster impact for three specific disaster types (epidemic, flood and storm). The findings enhance the understanding of the role of logistics in a humanitarian context with empirical evidence of the importance of country logistics performance in disaster response operations. © 2016 The Author(s). Disasters © Overseas Development Institute, 2016.

Associations between overweight, peer problems, and mental health in 12-13-year-old Norwegian children.

PubMed

Hestetun, Ingebjørg; Svendsen, Martin Veel; Oellingrath, Inger Margaret

2015-03-01

Overweight and mental health problems represent two major challenges related to child and adolescent health. More knowledge of a possible relationship between the two problems and the influence of peer problems on the mental health of overweight children is needed. It has previously been hypothesized that peer problems may be an underlying factor in the association between overweight and mental health problems. The purpose of the present study was to investigate the associations between overweight, peer problems, and indications of mental health problems in a sample of 12-13-year-old Norwegian schoolchildren. Children aged 12-13 years were recruited from the seventh grade of primary schools in Telemark County, Norway. Parents gave information about mental health and peer problems by completing the extended version of the Strength and Difficulties Questionnaire (SDQ). Height and weight were objectively measured. Complete data were obtained for 744 children. Fisher's exact probability test and multiple logistic regressions were used. Most children had normal good mental health. Multiple logistic regression analysis showed that overweight children were more likely to have indications of psychiatric disorders (adjusted OR: 1.8, CI: 1.0-3.2) and peer problems (adjusted OR: 2.6, CI: 1.6-4.2) than normal-weight children, when adjusted for relevant background variables. When adjusted for peer problems, the association between overweight and indications of any psychiatric disorder was no longer significant. The results support the hypothesis that peer problems may be an important underlying factor for mental health problems in overweight children.

Elevated visfatin/pre-B-cell colony-enhancing factor plasma concentration in ischemic stroke.

PubMed

Lu, Li-Fen; Yang, Sheng-Shan; Wang, Chao-Ping; Hung, Wei-Chin; Yu, Teng-Hung; Chiu, Cheng-An; Chung, Fu-Mei; Shin, Shyi-Jang; Lee, Yau-Jiunn

2009-01-01

Visfatin/pre-B-cell colony-enhancing factor is a cytokine that is expressed as a protein in several tissues (e.g., liver, skeletal muscle, immune cells), including adipose tissue, and is reported to stimulate inflammatory cytokine expressions and promote vascular smooth cell maturation. Visfatin may act as a proinflammatory cytokine and be involved in the process of atherosclerosis. In this study, we investigated whether plasma visfatin levels were altered in patients with ischemic stroke. Plasma visfatin concentrations were measured through enzyme immunoassays in patients with ischemic stroke and in control subjects without stroke. The mean plasma concentration of visfatin in the 120 patients with ischemic stroke was significantly higher than that of the 120 control subjects without stroke (51.5 +/- 48.4 v 23.0 +/- 23.9 ng/mL, P < .001). Multiple logistic regression analysis confirmed plasma visfatin to be an independent factor associated with ischemic stroke. Increasing concentrations of visfatin were independently and significantly associated with a higher risk of ischemic stroke when concentrations were analyzed as both a quartile and a continuous variable. The multiple logistic regression analysis-adjusted odds ratios and 95% confidence intervals for ischemic stroke in the second, third, and fourth quartiles were 2.3 (0.7-7.7), 6.9 (2.2-23.3), and 20.1 (4.9-97.7), respectively. Plasma visfatin concentration was positively associated with high-sensitivity C-reactive protein levels and negatively associated with low-density lipoprotein cholesterol. Our results indicate that higher visfatin levels are associated with ischemic stroke in the Chinese population.

Evaluating construct validity of the second version of the Copenhagen Psychosocial Questionnaire through analysis of differential item functioning and differential item effect.

PubMed

Bjorner, Jakob Bue; Pejtersen, Jan Hyld

2010-02-01

To evaluate the construct validity of the Copenhagen Psychosocial Questionnaire II (COPSOQ II) by means of tests for differential item functioning (DIF) and differential item effect (DIE). We used a Danish general population postal survey (n = 4,732 with 3,517 wage earners) with a one-year register based follow up for long-term sickness absence. DIF was evaluated against age, gender, education, social class, public/private sector employment, and job type using ordinal logistic regression. DIE was evaluated against job satisfaction and self-rated health (using ordinal logistic regression), against depressive symptoms, burnout, and stress (using multiple linear regression), and against long-term sick leave (using a proportional hazards model). We used a cross-validation approach to counter the risk of significant results due to multiple testing. Out of 1,052 tests, we found 599 significant instances of DIF/DIE, 69 of which showed both practical and statistical significance across two independent samples. Most DIF occurred for job type (in 20 cases), while we found little DIF for age, gender, education, social class and sector. DIE seemed to pertain to particular items, which showed DIE in the same direction for several outcome variables. The results allowed a preliminary identification of items that have a positive impact on construct validity and items that have negative impact on construct validity. These results can be used to develop better shortform measures and to improve the conceptual framework, items and scales of the COPSOQ II. We conclude that tests of DIF and DIE are useful for evaluating construct validity.

Potential serum biomarkers from a metabolomics study of autism

PubMed Central

Wang, Han; Liang, Shuang; Wang, Maoqing; Gao, Jingquan; Sun, Caihong; Wang, Jia; Xia, Wei; Wu, Shiying; Sumner, Susan J.; Zhang, Fengyu; Sun, Changhao; Wu, Lijie

2016-01-01

Background Early detection and diagnosis are very important for autism. Current diagnosis of autism relies mainly on some observational questionnaires and interview tools that may involve a great variability. We performed a metabolomics analysis of serum to identify potential biomarkers for the early diagnosis and clinical evaluation of autism. Methods We analyzed a discovery cohort of patients with autism and participants without autism in the Chinese Han population using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS/MS) to detect metabolic changes in serum associated with autism. The potential metabolite candidates for biomarkers were individually validated in an additional independent cohort of cases and controls. We built a multiple logistic regression model to evaluate the validated biomarkers. Results We included 73 patients and 63 controls in the discovery cohort and 100 cases and 100 controls in the validation cohort. Metabolomic analysis of serum in the discovery stage identified 17 metabolites, 11 of which were validated in an independent cohort. A multiple logistic regression model built on the 11 validated metabolites fit well in both cohorts. The model consistently showed that autism was associated with 2 particular metabolites: sphingosine 1-phosphate and docosahexaenoic acid. Limitations While autism is diagnosed predominantly in boys, we were unable to perform the analysis by sex owing to difficulty recruiting enough female patients. Other limitations include the need to perform test–retest assessment within the same individual and the relatively small sample size. Conclusion Two metabolites have potential as biomarkers for the clinical diagnosis and evaluation of autism. PMID:26395811

Association of Sociodemographic Factors, Smoking-Related Beliefs, and Smoking Restrictions With Intention to Quit Smoking in Korean Adults: Findings From the ITC Korea Survey

PubMed Central

Myung, Seung-Kwon; Seo, Hong Gwan; Cheong, Yoo-Seock; Park, Sohee; Lee, Wonkyong B; Fong, Geoffrey T

2012-01-01

Background Few studies have reported the factors associated with intention to quit smoking among Korean adult smokers. This study aimed to examine sociodemographic characteristics, smoking-related beliefs, and smoking-restriction variables associated with intention to quit smoking among Korean adult smokers. Methods We used data from the International Tobacco Control Korea Survey, which was conducted from November through December 2005 by using random-digit dialing and computer-assisted telephone interviewing of male and female smokers aged 19 years or older in 16 metropolitan areas and provinces of Korea. We performed univariate analysis and multiple logistic regression analysis to identify predictors of intention to quit. Results A total of 995 respondents were included in the final analysis. Of those, 74.9% (n = 745) intended to quit smoking. In univariate analyses, smokers with an intention to quit were younger, smoked fewer cigarettes per day, had a higher annual income, were more educated, were more likely to have a religious affiliation, drank less alcohol per week, were less likely to have self-exempting beliefs, and were more likely to have self-efficacy beliefs regarding quitting, to believe that smoking had damaged their health, and to report that smoking was never allowed anywhere in their home. In multiple logistic regression analysis, higher education level, having a religious affiliation, and a higher self-efficacy regarding quitting were significantly associated with intention to quit. Conclusions Sociodemographic factors, smoking-related beliefs, and smoking restrictions at home were associated with intention to quit smoking among Korean adults. PMID:22186157

Association of sociodemographic factors, smoking-related beliefs, and smoking restrictions with intention to quit smoking in Korean adults: findings from the ITC Korea Survey.

PubMed

Myung, Seung-Kwon; Seo, Hong Gwan; Cheong, Yoo-Seock; Park, Sohee; Lee, Wonkyong B; Fong, Geoffrey T

2012-01-01

Few studies have reported the factors associated with intention to quit smoking among Korean adult smokers. This study aimed to examine sociodemographic characteristics, smoking-related beliefs, and smoking-restriction variables associated with intention to quit smoking among Korean adult smokers. We used data from the International Tobacco Control Korea Survey, which was conducted from November through December 2005 by using random-digit dialing and computer-assisted telephone interviewing of male and female smokers aged 19 years or older in 16 metropolitan areas and provinces of Korea. We performed univariate analysis and multiple logistic regression analysis to identify predictors of intention to quit. A total of 995 respondents were included in the final analysis. Of those, 74.9% (n = 745) intended to quit smoking. In univariate analyses, smokers with an intention to quit were younger, smoked fewer cigarettes per day, had a higher annual income, were more educated, were more likely to have a religious affiliation, drank less alcohol per week, were less likely to have self-exempting beliefs, and were more likely to have self-efficacy beliefs regarding quitting, to believe that smoking had damaged their health, and to report that smoking was never allowed anywhere in their home. In multiple logistic regression analysis, higher education level, having a religious affiliation, and a higher self-efficacy regarding quitting were significantly associated with intention to quit. Sociodemographic factors, smoking-related beliefs, and smoking restrictions at home were associated with intention to quit smoking among Korean adults.

Attitude and practice of physical activity and social problem-solving ability among university students.

PubMed

Sone, Toshimasa; Kawachi, Yousuke; Abe, Chihiro; Otomo, Yuki; Sung, Yul-Wan; Ogawa, Seiji

2017-04-04

Effective social problem-solving abilities can contribute to decreased risk of poor mental health. In addition, physical activity has a favorable effect on mental health. These previous studies suggest that physical activity and social problem-solving ability can interact by helping to sustain mental health. The present study aimed to determine the association between attitude and practice of physical activity and social problem-solving ability among university students. Information on physical activity and social problem-solving was collected using a self-administered questionnaire. We analyzed data from 185 students who participated in the questionnaire surveys and psychological tests. Social problem-solving as measured by the Social Problem-Solving Inventory-Revised (SPSI-R) (median score 10.85) was the dependent variable. Multiple logistic regression analysis was employed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for higher SPSI-R according to physical activity categories. The multiple logistic regression analysis indicated that the ORs (95% CI) in reference to participants who said they never considered exercising were 2.08 (0.69-6.93), 1.62 (0.55-5.26), 2.78 (0.86-9.77), and 6.23 (1.81-23.97) for participants who did not exercise but intended to start, tried to exercise but did not, exercised but not regularly, and exercised regularly, respectively. This finding suggested that positive linear association between physical activity and social problem-solving ability (p value for linear trend < 0.01). The present findings suggest that regular physical activity or intention to start physical activity may be an effective strategy to improve social problem-solving ability.

Maximal bite force, facial morphology and sucking habits in young children with functional posterior crossbite

PubMed Central

CASTELO, Paula Midori; GAVIÃO, Maria Beatriz Duarte; PEREIRA, Luciano José; BONJARDIM, Leonardo Rigoldi

2010-01-01

Objective The maintenance of normal conditions of the masticatory function is determinant for the correct growth and development of its structures. Thus, the aims of this study were to evaluate the influence of sucking habits on the presence of crossbite and its relationship with maximal bite force, facial morphology and body variables in 67 children of both genders (3.5-7 years) with primary or early mixed dentition. Material and methods The children were divided in four groups: primary-normocclusion (PN, n=19), primary-crossbite (PC, n=19), mixed-normocclusion (MN, n=13), and mixed-crossbite (MC, n=16). Bite force was measured with a pressurized tube, and facial morphology was determined by standardized frontal photographs: AFH (anterior face height) and BFW (bizygomatic facial width). Results It was observed that MC group showed lower bite force than MN, and AFH/ BFW was significantly smaller in PN than PC (t-test). Weight and height were only significantly correlated with bite force in PC group (Pearson’s correlation test). In the primary dentition, AFH/BFW and breast-feeding (at least six months) were positive and negatively associated with crossbite, respectively (multiple logistic regression). In the mixed dentition, breastfeeding and bite force showed negative associations with crossbite (univariate regression), while nonnutritive sucking (up to 3 years) associated significantly with crossbite in all groups (multiple logistic regression). Conclusions In the studied sample, sucking habits played an important role in the etiology of crossbite, which was associated with lower bite force and long-face tendency. PMID:20485925

High stress, lack of sleep, low school performance, and suicide attempts are associated with high energy drink intake in adolescents.

PubMed

Kim, So Young; Sim, Songyong; Choi, Hyo Geun

2017-01-01

Although an association between energy drinks and suicide has been suggested, few prior studies have considered the role of emotional factors including stress, sleep, and school performance in adolescents. This study aimed to evaluate the association of energy drinks with suicide, independent of possible confounders including stress, sleep, and school performance. In total, 121,106 adolescents with 13-18 years olds from the 2014 and 2015 Korea Youth Risk Behavior Web-based Survey were surveyed for age, sex, region of residence, economic level, paternal and maternal education level, sleep time, stress level, school performance, frequency of energy drink intake, and suicide attempts. Subjective stress levels were classified into severe, moderate, mild, a little, and no stress. Sleep time was divided into 6 groups: < 6 h; 6 ≤ h < 7; 7 ≤ h < 8; 8 ≤ h < 9; and ≥ 9 h. School performance was classified into 5 levels: A (highest), B (middle, high), C (middle), D (middle, low), and E (lowest). Frequency of energy drink consumption was divided into 3 groups: ≥ 3, 1-2, and 0 times a week. The associations of sleep time, stress level, and school performance with suicide attempts and the frequency of energy drink intake were analyzed using multiple and ordinal logistic regression analysis, respectively, with complex sampling. The relationship between frequency of energy drink intake and suicide attempts was analyzed using multiple logistic regression analysis with complex sampling. Higher stress levels, lack of sleep, and low school performance were significantly associated with suicide attempts (each P < 0.001). These variables of high stress level, abnormal sleep time, and low school performance were also proportionally related with higher energy drink intake (P < 0.001). Frequent energy drink intake was significantly associated with suicide attempts in multiple logistic regression analyses (AOR for frequency of energy intake ≥ 3 times a week = 3.03, 95% CI = 2.64-3.49, P < 0.001). Severe stress, inadequate sleep, and low school performance were related with more energy drink intake and suicide attempts in Korean adolescents. Frequent energy drink intake was positively related with suicide attempts, even after adjusting for stress, sleep time, and school performance.

High stress, lack of sleep, low school performance, and suicide attempts are associated with high energy drink intake in adolescents

PubMed Central

Kim, So Young; Sim, Songyong

2017-01-01

Objective Although an association between energy drinks and suicide has been suggested, few prior studies have considered the role of emotional factors including stress, sleep, and school performance in adolescents. This study aimed to evaluate the association of energy drinks with suicide, independent of possible confounders including stress, sleep, and school performance. Methods In total, 121,106 adolescents with 13–18 years olds from the 2014 and 2015 Korea Youth Risk Behavior Web-based Survey were surveyed for age, sex, region of residence, economic level, paternal and maternal education level, sleep time, stress level, school performance, frequency of energy drink intake, and suicide attempts. Subjective stress levels were classified into severe, moderate, mild, a little, and no stress. Sleep time was divided into 6 groups: < 6 h; 6 ≤ h < 7; 7 ≤ h < 8; 8 ≤ h < 9; and ≥ 9 h. School performance was classified into 5 levels: A (highest), B (middle, high), C (middle), D (middle, low), and E (lowest). Frequency of energy drink consumption was divided into 3 groups: ≥ 3, 1–2, and 0 times a week. The associations of sleep time, stress level, and school performance with suicide attempts and the frequency of energy drink intake were analyzed using multiple and ordinal logistic regression analysis, respectively, with complex sampling. The relationship between frequency of energy drink intake and suicide attempts was analyzed using multiple logistic regression analysis with complex sampling. Results Higher stress levels, lack of sleep, and low school performance were significantly associated with suicide attempts (each P < 0.001). These variables of high stress level, abnormal sleep time, and low school performance were also proportionally related with higher energy drink intake (P < 0.001). Frequent energy drink intake was significantly associated with suicide attempts in multiple logistic regression analyses (AOR for frequency of energy intake ≥ 3 times a week = 3.03, 95% CI = 2.64–3.49, P < 0.001). Conclusion Severe stress, inadequate sleep, and low school performance were related with more energy drink intake and suicide attempts in Korean adolescents. Frequent energy drink intake was positively related with suicide attempts, even after adjusting for stress, sleep time, and school performance. PMID:29135989

“Big data” and Gram-negative Resistance: A Multiple Logistic Regression Model Using EMR Data to Predict Carbapenem Resistance in Patients with Klebsiella pneumoniae Bloodstream Infection

PubMed Central

Sullivan, Timothy; Aberg, Judith

2017-01-01

Abstract Background The timely identification of carbapenem resistance is essential in the management of patients with Klebsiella pneumoniae bloodstream infection (BSI). An algorithm using electronic medical record (EMR) data to quickly predict resistance could potentially help guide therapy until more definitive resistance testing results are available. Methods All cases of K. pneumoniae BSI at Mount Sinai Hospital from September 2012 through September 2016 were identified. Cases of persistent BSI or recurrent BSI within 2 weeks were included only once. Patients with recurrent BSI after more than 2 weeks of negative blood cultures were considered distinct cases and included more than once. Carbapenem resistance was defined as an imipenem minimum inhibitory concentration of ≥2 μg/ml. Extensive EMR data for each patient were compiled into a relational database using SQLite. Possible risk factors for carbapenem resistance were queried from the database and analyzed via univariate methods. Significant factors were then entered into a multiple logistic regression model in a forward stepwise approach using SPSS. Results A total of 613 cases of K. pneumoniae BSI were identified in 540 unique patients. The overall incidence of imipenem resistance was 10% (61 cases). Significant markers of resistance included in the final model were (1) prior colonization with imipenem-resistant Klebsiella pneumoniae; (2) hospital unit (defined as high-risk unit, low-risk unit, and emergency department); (3) total inpatient days in the previous 5 years; (4) total days of oral or parenteral antibiotics in the past 2 years; and (5) age >60 years old (Figure 1). The model generated a receiver operating characteristic curve with an area under the curve of 0.75 (Figure 2). At a cut point of 0.083, the model correctly predicted 72% of imipenem-resistant cases while incorrectly labeling 32% of susceptible cases as resistant (Sn = 72%, Sp = 63%, Figure 3). Conclusion A multiple logistic regression model using EMR data can generate immediate, clinically useful predictions of carbapenem resistance in patients with K. pneumoniae BSI. Larger data sets are needed to improve and validate these findings. Figure 1. Algorithm variables Figure 2. Receiver operating characteristic curve Figure 3. Classification table Disclosures All authors: No reported disclosures.

Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations.

PubMed

Hayes, Andrew F; Matthes, Jörg

2009-08-01

Researchers often hypothesize moderated effects, in which the effect of an independent variable on an outcome variable depends on the value of a moderator variable. Such an effect reveals itself statistically as an interaction between the independent and moderator variables in a model of the outcome variable. When an interaction is found, it is important to probe the interaction, for theories and hypotheses often predict not just interaction but a specific pattern of effects of the focal independent variable as a function of the moderator. This article describes the familiar pick-a-point approach and the much less familiar Johnson-Neyman technique for probing interactions in linear models and introduces macros for SPSS and SAS to simplify the computations and facilitate the probing of interactions in ordinary least squares and logistic regression. A script version of the SPSS macro is also available for users who prefer a point-and-click user interface rather than command syntax.

Proposed Nomogram Predicting the Individual Risk of Malignancy in the Patients With Branch Duct Type Intraductal Papillary Mucinous Neoplasms of the Pancreas.

PubMed

Jang, Jin-Young; Park, Taesung; Lee, Selyeong; Kim, Yongkang; Lee, Seung Yeoun; Kim, Sun-Whe; Kim, Song-Cheol; Song, Ki-Byung; Yamamoto, Masakazu; Hatori, Takashi; Hirono, Seiko; Satoi, Sohei; Fujii, Tsutomu; Hirano, Satoshi; Hashimoto, Yasushi; Shimizu, Yashuhiro; Choi, Dong Wook; Choi, Seong Ho; Heo, Jin Seok; Motoi, Fuyuhiko; Matsumoto, Ippei; Lee, Woo Jung; Kang, Chang Moo; Han, Ho-Seong; Yoon, Yoo-Seok; Sho, Masayuki; Nagano, Hiroaki; Honda, Goro; Kim, Sang Geol; Yu, Hee Chul; Chung, Jun Chul; Nagakawa, Yuichi; Seo, Hyung Il; Yamaue, Hiroki

2017-12-01

This study evaluated individual risks of malignancy and proposed a nomogram for predicting malignancy of branch duct type intraductal papillary mucinous neoplasms (BD-IPMNs) using the large database for IPMN. Although consensus guidelines list several malignancy predicting factors in patients with BD-IPMN, those variables have different predictability and individual quantitative prediction of malignancy risk is limited. Clinicopathological factors predictive of malignancy were retrospectively analyzed in 2525 patients with biopsy proven BD-IPMN at 22 tertiary hospitals in Korea and Japan. The patients with main duct dilatation >10 mm and inaccurate information were excluded. The study cohort consisted of 2258 patients. Malignant IPMNs were defined as those with high grade dysplasia and associated invasive carcinoma. Of 2258 patients, 986 (43.7%) had low, 443 (19.6%) had intermediate, 398 (17.6%) had high grade dysplasia, and 431 (19.1%) had invasive carcinoma. To construct and validate the nomogram, patients were randomly allocated into training and validation sets, with fixed ratios of benign and malignant lesions. Multiple logistic regression analysis resulted in five variables (cyst size, duct dilatation, mural nodule, serum CA19-9, and CEA) being selected to construct the nomogram. In the validation set, this nomogram showed excellent discrimination power through a 1000 times bootstrapped calibration test. A nomogram predicting malignancy in patients with BD-IPMN was constructed using a logistic regression model. This nomogram may be useful in identifying patients at risk of malignancy and for selecting optimal treatment methods. The nomogram is freely available at http://statgen.snu.ac.kr/software/nomogramIPMN.

Interactive effect of genetic susceptibility with height, body mass index, and hormone replacement therapy on the risk of breast cancer.

PubMed

Harlid, Sophia; Butt, Salma; Ivarsson, Malin I L; Eyfjörd, Jorunn Erla; Lenner, Per; Manjer, Jonas; Dillner, Joakim; Carlson, Joyce

2012-06-22

Breast cancer today has many established risk factors, both genetic and environmental, but these risk factors by themselves explain only part of the total cancer incidence. We have investigated potential interactions between certain known genetic and phenotypic risk factors, specifically nine single nucleotide polymorphisms (SNPs) and height, body mass index (BMI) and hormone replacement therapy (HRT). We analyzed samples from three different study populations: two prospectively followed Swedish cohorts and one Icelandic case-control study. Totally 2884 invasive breast cancer cases and 4508 controls were analysed in the study. Genotypes were determined using Mass spectrometry-Maldi-TOF and phenotypic variables were derived from measurements and/or questionnaires. Odds Ratios and 95% confidence intervals were calculated using unconditional logistic regression with the inclusion of an interaction term in the logistic regression model. One SNP (rs851987 in ESR1) tended to interact with height, with an increasingly protective effect of the major allele in taller women (p = 0.007) and rs13281615 (on 8q24) tended to confer risk only in non users of HRT (p-for interaction = 0.03). There were no significant interactions after correction for multiple testing. We conclude that much larger sample sets would be necessary to demonstrate interactions between low-risk genetic polymorphisms and the phenotypic variables height, BMI and HRT on the risk for breast cancer. However the present hypothesis-generating study has identified tendencies that would be of interest to evaluate for gene-environment interactions in independent materials.

Perception of Risk for Developing Diabetes among Foreign-Born Spanish-Speaking U.S. Latinos

PubMed Central

Joiner, Kevin L.; Sternberg, Rosa Maria; Kennedy, Christine M.; Fukuoka, Yoshimi; Chen, Jyu-Lin; Janson, Susan L.

2017-01-01

Purpose The purpose of this study was to describe perception of risk for developing diabetes among foreign-born Spanish-speaking U.S. Latinos. Methods Participants (N=146), recruited at food-pantry distribution events and free clinics, were surveyed using the Risk Perception Survey for Developing Diabetes in Spanish. Type 2 diabetes risk factors measured included: Body Mass Index, physical activity, and Hemoglobin A1C. Results Sample characteristics were mean age 39.5 (±9.9) years old, 58% with less than a high school graduate level education, and 65% with a family income less than $15,000/year. Prevalence of risk factors was 81% overweight or obese, 47% < 150 minutes/week moderate/vigorous intensity physical activity, and 12% A1C consistent with prediabetes. Of the 135 participants with complete data, 31% perceived high/moderate risk for developing diabetes. In univariate logistic regression analyses, 9 of 18 potential variables were significant (p<0.05) predictors of perception of risk. When these 9 variables were entered into a multiple logistic regression model, 5 were significant predictors of perception of risk: history of gestational diabetes, ≥ high school graduate, optimistic bias, worry, and perceived personal disease risk. Conclusions This is the first study using the Risk Perception Survey for Developing Diabetes in Spanish in this population and reveals factors that influence perception of risk for developing diabetes. The results can be used to promote culturally acceptable type 2 diabetes primary prevention strategies and provide a useful comparison to other populations. PMID:27150605

Impact of Rehabilitation on Outcomes in Patients With Ischemic Stroke: A Nationwide Retrospective Cohort Study in Japan.

PubMed

Yagi, Maiko; Yasunaga, Hideo; Matsui, Hiroki; Morita, Kojiro; Fushimi, Kiyohide; Fujimoto, Masashi; Koyama, Teruyuki; Fujitani, Junko

2017-03-01

We aimed to examine the concurrent effects of timing and intensity of rehabilitation on improving activities of daily living (ADL) among patients with ischemic stroke. Using the Japanese Diagnosis Procedure Combination inpatient database, we retrospectively analyzed consecutive patients with ischemic stroke at admission who received rehabilitation (n=100 719) from April 2012 to March 2014. Early rehabilitation was defined as that starting within 3 days after admission. The average rehabilitation intensity per day was calculated as the total units of rehabilitation during hospitalization divided by the length of hospital stay. A multivariable logistic regression analysis with multiple imputation and an instrumental variable analysis were performed to examine the association of early and intensive rehabilitation with the proportion of improved ADL score. The proportion of improved ADL score was higher in the early and intensive rehabilitation group. The multivariable logistic regression analysis showed that significant improvements in ADL were observed for early rehabilitation (odds ratio: 1.08; 95% confidence interval: 1.04-1.13; P <0.01) and intensive rehabilitation of >5.0 U/d (odds ratio: 1.87; 95% confidence interval: 1.69-2.07; P <0.01). The instrumental variable analysis showed that an increased proportion of improved ADL was associated with early rehabilitation (risk difference: 2.8%; 95% confidence interval: 2.0-3.4%; P <0.001) and intensive rehabilitation (risk difference: 5.6%; 95% confidence interval: 4.6-6.6%; P <0.001). The present results suggested that early and intensive rehabilitation improved ADL during hospitalization in patients with ischemic stroke. © 2017 American Heart Association, Inc.

Understanding the Personality and Behavioral Mechanisms Defining Hypersexuality in Men Who Have Sex with Men

PubMed Central

Miner, Michael H.; Romine, Rebecca Swinburne; Raymond, Nancy; Janssen, Erick; MacDonald, Angus; Coleman, Eli

2016-01-01

Objective The purpose of this study was to investigate personality factors and behavioral mechanisms that are relevant to hypersexuality in men who have sex with men. Method A sample of 242 men who have sex with men were recruited from various sites in a moderate size mid-western city. Participants were assigned to hypersexuality or control group using a SCID-type interview. Self-report inventories were administered that measured the broad band personality constructs of positive emotionality, negative emotionality and constraint, and more narrow constructs related to sexual behavioral control, behavioral activation, behavioral inhibition, sexual excitation, sexual inhibition, impulsivity, ADHD, and sexual behavior. Hierarchical logistic regression was used to determine the relationship between these personality and behavioral variables and group membership. Results A hierarchical logistic regression, controlling for age, revealed a significant positive relationship between hypersexuality and negative emotionality and a negative relationship with constraint. None of the behavioral mechanism variables entered this equation. However, a hierarchical multiple regression predicting sexual behavioral control indicated that lack of such control was positively related to sexual excitation and sexual inhibition due to the threat of performance failure and negatively related to sexual inhibition due to the threat of performance consequences and general behavioral inhibition Conclusions Hypersexuality was found to be related to two broad personality factors that are characterized by emotional reactivity, risk-taking, and impulsivity. The associated lack of sexual behavior control is influenced by both sexual excitatory and inhibitory mechanisms, but not general behavioral activation and inhibitory mechanisms. PMID:27486137

Biomass bale stack and field outlet locations assessment for efficient infield logistics

USDA-ARS?s Scientific Manuscript database

Harvested hay or biomass are traditionally baled for better handling and they are transported to the outlet for final utilization. For better management of bale logistics, producers often aggregate bales into stacks so that bale-hauling equipment can haul multiple bales for improved efficiency. Obje...

77 FR 39662 - Hazardous Materials; Reverse Logistics (RRR)

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-05

... used batteries from multiple shippers for the purposes of recycling. The petition also notes that, when... recycling falls within the realm of ``reverse logistics.'' Currently Sec. 173.159(e)(4) prevents a battery... comment on how the retail industry should handle the recycling or disposal of these batteries for use in...

The Attitudes of First Year Senior Secondary School Students toward Their Science Classes in the Sudan

NASA Astrophysics Data System (ADS)

Lado, Longun Moses

This study examined the influence of a set of relevant independent variables on students' decision to major in math or science disciplines, on the one hand, or arts or humanities disciplines, on the other. The independent variables of interest in the study were students' attitudes toward science, their gender, their socioeconomic status, their age, and the strength and direction of parents' and peers' influences on their academic decisions. The study answered five research questions that concerned students' intention in math or science, the association between students' attitudes and their choice to major in math or science, the extent to which parents' and peers' perspectives influence students' choice of major, and the influence of a combination of relevant variables on students' choice of major. The scholarly context for the study was literature relating to students' attitudes toward science and math, their likelihood of taking courses or majoring in science or math and various conditions influencing their attitudes and actions with respect to enrollment in science or math disciplines. This literature suggested that students' experiences, their gender, parents' and peers' influence, their socio-economic status, teachers' treatment of them, school curricula, school culture, and other variables may influence students' attitudes toward science and math and their decision regarding the study of these subjects. The study used a questionnaire comprised of 28 items to elicit information from students. Based upon cluster sampling of secondary schools, the researcher surveyed 1000 students from 10 secondary schools and received 987 responses. The researcher used SPSS to analyze students' responses. Descriptive statistics, logistic regression, and multiple regression analyses to provide findings that address the study's research questions. The following are the major findings from the study: (1) The instrument used to measure students' attitudes toward science and mathematics was not highly reliable, perhaps contributing to an attenuation of the relationship between attitude toward science and mathematics and choice of a science or mathematics major (rather than an arts or humanities major). (2) Far more students than the researcher had anticipated provided responses indicating that they planned to major in a science or mathematics discipline rather than an arts or humanities discipline. (3) Students' attitudes towards math and science were more favorable than the researcher anticipated based on findings from previous related studies. This result suggests the possibility of social desirability bias in students' responses. (4) Three significant predicator variables contributed to a significant logistic regression equation in which choice of science or mathematics major was the dependent variable: gender (negative association), attitude toward science and math (positive association), and peer influence 1 (positive association). Gender was the strongest predictor. (5) Five significant predictor variables contributed to a significant multiple linear regression equation in which attitude toward science and mathematics was the dependent variable: peer influence 1 (positive association), parent influence 1 (positive association), parent influence 2 (positive association), books in home (positive association), and peer influence 2 (positive association). The results reveal that among the targeted variables (gender, attitude, peer influence 1, peer influence 2, parent influence 1, parent influence 2, books in home, and age) only gender, peer influence 1, and attitude were significant predictors of students' major in math or science.

Clinical and multiple gene expression variables in survival analysis of breast cancer: Analysis with the hypertabastic survival model

PubMed Central

2012-01-01

Background We explore the benefits of applying a new proportional hazard model to analyze survival of breast cancer patients. As a parametric model, the hypertabastic survival model offers a closer fit to experimental data than Cox regression, and furthermore provides explicit survival and hazard functions which can be used as additional tools in the survival analysis. In addition, one of our main concerns is utilization of multiple gene expression variables. Our analysis treats the important issue of interaction of different gene signatures in the survival analysis. Methods The hypertabastic proportional hazards model was applied in survival analysis of breast cancer patients. This model was compared, using statistical measures of goodness of fit, with models based on the semi-parametric Cox proportional hazards model and the parametric log-logistic and Weibull models. The explicit functions for hazard and survival were then used to analyze the dynamic behavior of hazard and survival functions. Results The hypertabastic model provided the best fit among all the models considered. Use of multiple gene expression variables also provided a considerable improvement in the goodness of fit of the model, as compared to use of only one. By utilizing the explicit survival and hazard functions provided by the model, we were able to determine the magnitude of the maximum rate of increase in hazard, and the maximum rate of decrease in survival, as well as the times when these occurred. We explore the influence of each gene expression variable on these extrema. Furthermore, in the cases of continuous gene expression variables, represented by a measure of correlation, we were able to investigate the dynamics with respect to changes in gene expression. Conclusions We observed that use of three different gene signatures in the model provided a greater combined effect and allowed us to assess the relative importance of each in determination of outcome in this data set. These results point to the potential to combine gene signatures to a greater effect in cases where each gene signature represents some distinct aspect of the cancer biology. Furthermore we conclude that the hypertabastic survival models can be an effective survival analysis tool for breast cancer patients. PMID:23241496

Dental health services utilization and associated factors in children 6 to 12 years old in a low-income country.

PubMed

Medina-Solis, Carlo Eduardo; Maupomé, Gerardo; del Socorro, Herrera Miriam; Pérez-Núñez, Ricardo; Avila-Burgos, Leticia; Lamadrid-Figueroa, Hector

2008-01-01

To determine the factors associated with the dental health services utilization among children ages 6 to 12 in León, Nicaragua. A cross-sectional study was carried out in 1,400 schoolchildren. Using a questionnaire, we determined information related to utilization and independent variables in the previous year. Oral health needs were established by means of a dental examination. To identify the independent variables associated with dental health services utilization, two types of multivariate regression models were used, according to the measurement scale of the outcome variable: a) frequency of utilization as (0) none, (1) one, and (2) two or more, analyzed with the ordered logistic regression and b) the type of service utilized as (0) none, (1) preventive services, (2) curative services, and (3) both services, analyzed with the multinomial logistic regression. The proportion of children who received at least one dental service in the 12 months prior to the study was 27.7 percent. The variables associated with utilization in the two models were older age, female sex, more frequent toothbrushing, positive attitude of the mother toward the child's oral health, higher socioeconomic level, and higher oral health needs. Various predisposing, enabling, and oral health needs variables were associated with higher dental health services utilization. As in prior reports elsewhere, these results from Nicaragua confirmed that utilization inequalities exist between socioeconomic groups. The multinomial logistic regression model evidenced the association of different variables depending on the type of service used.

Cluster Analysis of Campylobacter jejuni Genotypes Isolated from Small and Medium-Sized Mammalian Wildlife and Bovine Livestock from Ontario Farms.

PubMed

Viswanathan, M; Pearl, D L; Taboada, E N; Parmley, E J; Mutschall, S K; Jardine, C M

2017-05-01

Using data collected from a cross-sectional study of 25 farms (eight beef, eight swine and nine dairy) in 2010, we assessed clustering of molecular subtypes of C. jejuni based on a Campylobacter-specific 40 gene comparative genomic fingerprinting assay (CGF40) subtypes, using unweighted pair-group method with arithmetic mean (UPGMA) analysis, and multiple correspondence analysis. Exact logistic regression was used to determine which genes differentiate wildlife and livestock subtypes in our study population. A total of 33 bovine livestock (17 beef and 16 dairy), 26 wildlife (20 raccoon (Procyon lotor), five skunk (Mephitis mephitis) and one mouse (Peromyscus spp.) C. jejuni isolates were subtyped using CGF40. Dendrogram analysis, based on UPGMA, showed distinct branches separating bovine livestock and mammalian wildlife isolates. Furthermore, two-dimensional multiple correspondence analysis was highly concordant with dendrogram analysis showing clear differentiation between livestock and wildlife CGF40 subtypes. Based on multilevel logistic regression models with a random intercept for farm of origin, we found that isolates in general, and raccoons more specifically, were significantly more likely to be part of the wildlife branch. Exact logistic regression conducted gene by gene revealed 15 genes that were predictive of whether an isolate was of wildlife or bovine livestock isolate origin. Both multiple correspondence analysis and exact logistic regression revealed that in most cases, the presence of a particular gene (13 of 15) was associated with an isolate being of livestock rather than wildlife origin. In conclusion, the evidence gained from dendrogram analysis, multiple correspondence analysis and exact logistic regression indicates that mammalian wildlife carry CGF40 subtypes of C. jejuni distinct from those carried by bovine livestock. Future studies focused on source attribution of C. jejuni in human infections will help determine whether wildlife transmit Campylobacter jejuni directly to humans. © 2016 Blackwell Verlag GmbH.

Action control and situational risks in the prevention of HIV and STIs: individual, dyadic, and social influences on consistent condom use in a university population.

PubMed

Svenson, Gary R; Ostergren, Per-Olof; Merlo, Juan; Råstam, Lennart

2002-12-01

The aim of this study was to gain an understanding of consistent condom use. We took the perspective that condom use involves the ability to handle situational risks influenced at multiple levels, including the individual, dyadic, and social. The hypothesis was that action control, as measured by self-regulation, implementation intentions, and self-efficacy, was the primary determinant. The study was conducted at part of a community-based intervention at a major university (36,000 students). Data was collected using a validated questionnaire mailed to a random sample of students (n = 493, response rate = 71.5%). Statistical analysis included logistic regression models that successively included background, individual, dyadic, and social variables. In the final model, consistent condom use was higher among students with strong implementation intentions, high self-regulation and positive peer norms. The results contribute new knowledge on action control in predicting sexual risk behaviors and lends support to the conceptualization and analysis of HIV/sexually transmitted infection prevention at multiple levels of influence.

Peer and Teacher Effects on the Early Onset of Sexual Intercourse

PubMed Central

Brendgen, Mara; Wanner, Brigitte; Vitaro, Frank

2007-01-01

Objectives. We examined the links between peer rejection and verbal abuse by a teacher during childhood with the early onset of sexual intercourse and the mediating role of delinquent behavior and low self-esteem in this context. Methods. We assessed 312 students (159 girls) in northwestern Quebec annually from kindergarten through seventh grade. Peer identifications were used to assess peer rejection and verbal abuse by teachers from kindergarten through fourth grade. In seventh grade, self-reports were used to assess delinquent behavior, self-esteem, and having sexual intercourse. Multiple sources were used to assess control variables. Results. Multiple imputation-based linear and logistic regressions showed that peer rejection was indirectly associated with a higher risk of early intercourse by its link with lower self-esteem, but only for girls. Verbal abuse by teachers during childhood was directly associated with a higher risk of early sexual intercourse and indirectly by its link with delinquent behavior. Conclusions. The results underline the importance of both peers and teachers in healthy sexual development among youths, especially for girls, and emphasize the need for targeted health and sexual education programs. PMID:17901435

24-hour aortic blood pressure variability showed a stronger association with carotid damage than 24-hour brachial blood pressure variability: The SAFAR study.

PubMed

Yu, Shikai; Chi, Chen; Protogerou, Athanase D; Safar, Michel E; Blacher, Jacques; Argyris, Antonis A; Nasothimiou, Efthimia G; Sfikakis, Petros P; Papaioannou, Theodore G; Xu, Henry; Zhang, Yi; Xu, Yawei

2018-03-01

We aim to compare 24-hour aortic blood pressure variability (BPV) with brachial BPV in relation to carotid damage as estimated by carotid intima-media thickness (CIMT) and cross-sectional area (CCSA). Four hundred and forty five individuals received brachial and aortic 24-hour ambulatory BP monitoring with a validated device (Mobil-O-Graph). Systolic BPV was estimated by average real variability (ARV) and time-weighted standard deviation (wSD). In multiple logistic regression analysis, CIMT > 900 μm was significantly and independently associated with aortic ARV (OR = 1.38; 95% CI: 1.04-1.84), aortic wSD (OR = 1.65; 95% CI: 1.19-2.29) and brachial ARV (OR = 1.53; 95% CI: 1.07-2.18), but not with brachial wSD. CCSA > 90th percentile was significantly and independently associated with aortic ARV (OR = 1.50; 95% CI: 1.07-2.10) and wSD (OR = 1.70; 95% CI: 1.12-2.56), but not with brachial BPVs. In receiver operator characteristics curve analysis, aortic wSD identified CCSA > 90th percentile better than brachial wSD (AUC: 0.73 vs 0.68, P < .01). In conclusion, aortic 24-hour systolic BPV showed a slightly stronger association with carotid damage than brachial BPV. ©2018 Wiley Periodicals, Inc.

[Probabilistic models of mortality for patients hospitalized in conventional units].

PubMed

Rué, M; Roqué, M; Solà, J; Macià, M

2001-09-29

We have developed a tool to measure disease severity of patients hospitalized in conventional units in order to evaluate and compare the effectiveness and quality of health care in our setting. A total of 2,274 adult patients admitted consecutively to inpatient units from the Medicine, Surgery and Orthopaedic Surgery, and Trauma Departments of the Corporació Sanitària Parc Taulí of Sabadell, Spain, between November 1, 1997 and September 30, 1998 were included. The following variables were collected: demographic data, previous health state, substance abuse, comorbidity prior to admission, characteristics of the admission, clinical parameters within the first 24 hours of admission, laboratory results and data from the Basic Minimum Data Set of hospital discharges. Multiple logistic regression analysis was used to develop mortality probability models during the hospital stay. The mortality probability model at admission (MPMHOS-0) contained 7 variables associated with mortality during hospital stay: age, urgent admission, chronic cardiac insufficiency, chronic respiratory insufficiency, chronic liver disease, neoplasm, and dementia syndrome. The mortality probability model at 24-48 hours from admission (MPMHOS-24) contained 9 variables: those included in the MPMHOS-0 plus two statistically significant laboratory variables: hemoglobin and creatinine. Severity measures, in particular those presented in this study, can be helpful for the interpretation of hospital mortality rates and can guide mortality or quality committees at the time of investigating health care-related problems.

The Dropout Learning Algorithm

PubMed Central

Baldi, Pierre; Sadowski, Peter

2014-01-01

Dropout is a recently introduced algorithm for training neural network by randomly dropping units during training to prevent their co-adaptation. A mathematical analysis of some of the static and dynamic properties of dropout is provided using Bernoulli gating variables, general enough to accommodate dropout on units or connections, and with variable rates. The framework allows a complete analysis of the ensemble averaging properties of dropout in linear networks, which is useful to understand the non-linear case. The ensemble averaging properties of dropout in non-linear logistic networks result from three fundamental equations: (1) the approximation of the expectations of logistic functions by normalized geometric means, for which bounds and estimates are derived; (2) the algebraic equality between normalized geometric means of logistic functions with the logistic of the means, which mathematically characterizes logistic functions; and (3) the linearity of the means with respect to sums, as well as products of independent variables. The results are also extended to other classes of transfer functions, including rectified linear functions. Approximation errors tend to cancel each other and do not accumulate. Dropout can also be connected to stochastic neurons and used to predict firing rates, and to backpropagation by viewing the backward propagation as ensemble averaging in a dropout linear network. Moreover, the convergence properties of dropout can be understood in terms of stochastic gradient descent. Finally, for the regularization properties of dropout, the expectation of the dropout gradient is the gradient of the corresponding approximation ensemble, regularized by an adaptive weight decay term with a propensity for self-consistent variance minimization and sparse representations. PMID:24771879

[Factors associated with activities of daily living (ADL) in independently living elderly persons in a community: a baseline examination of a large scale cohort study, Fujiwara-kyo study].

PubMed

Komatsu, Masayo; Nezu, Satoko; Tomioka, Kimiko; Hazaki, Kan; Harano, Akihiro; Morikawa, Masayuki; Takagi, Masahiro; Yamada, Masahiro; Matsumoto, Yoshitaka; Iwamoto, Junko; Ishizuka, Rika; Saeki, Keigo; Okamoto, Nozomi; Kurumatani, Norio

2013-01-01

To investigate factors associated with activities of daily living in independently living elderly persons in a community. The potential subjects were 4,472 individuals aged 65 years and older who voluntarily participated in a large cohort study, the Fujiwara-kyo study. We used self-administered questionnaires consisting of an activities of daily living (ADL) questionnaire with the Physical Fitness Test established by the Ministry of Education, Culture, Sports, Science and Technology (12 ADL items) to determine the index of higher-level physical independence, demographics, Geriatric Depression Scale, and so on. Mini-mental state examination, measurement of physical fitness, and blood tests were also carried out. A lower ADL level was defined as having a total score of the 12 ADL items (range, 12-36 points) that was below the first quartile of a total score for all the subjects. Factors associated with a low ADL level were examined by multiple logistic regression. A total of 4,198 remained as subjects for analysis. The male, female and 5-year-old groups showed significant differences in the median score of 12 ADL items between any two groups. The highest odds ratio among factors associated with lower ADL level by multiple logistic regression with mutually adjusted independent variables was 4.49 (95%CI: 2.82-7.17) in the groups of "very sharp pain" or "strong pain" during the last month. Low physical ability, self-awareness of limb weakness, a BMI of over 25, low physical activity, cerebrovascular disorder, depression, low cognitive function, unable "to see normally", unable "to hear someone", "muscle, bone and joint pain" were independently associated with lower ADL level. Multiple factors are associated with lower ADL level assessed on the basis of the 12 ADL items.

Association between Triglyceride to HDL-C Ratio (TG/HDL-C) and Insulin Resistance in Chinese Patients with Newly Diagnosed Type 2 Diabetes Mellitus.

PubMed

Ren, Xingxing; Chen, Zeng Ai; Zheng, Shuang; Han, Tingting; Li, Yangxue; Liu, Wei; Hu, Yaomin

2016-01-01

To explore the association between the triglyceride to HDL-C ratio (TG/HDL-C) and insulin resistance in Chinese patients with newly diagnosed type 2 diabetes mellitus. Patients with newly diagnosed type 2 diabetes mellitus (272 men and 288 women) were enrolled and divided into three groups according to TG/HDL-C tertiles. Insulin resistance was defined by homeostatic model assessment of insulin resistance (HOMA-IR). Demographic information and clinical characteristics were obtained. Spearman's correlation was used to estimate the association between TG/HDL-C and other variables. Multiple logistic regression analyses were adopted to obtain probabilities of insulin resistance. A receiver operating characteristic analysis was conducted to evaluate the ability of TG/HDL-C to discriminate insulin resistance. TG/HDL-C was associated with insulin resistance in Chinese patients with newly diagnosed T2DM (Spearman's correlation coefficient = 0.21, P < 0.01). Patients in the higher tertiles of TG/HDL-C had significantly higher HOMA-IR values than patients in the lower tertiles [T1: 2.68(1.74-3.70); T2: 2.96(2.29-4.56); T3: 3.09(2.30-4.99)]. Multiple logistic regression analysis showed that TG/HDL-C was significantly associated with HOMA-IR, and patients in the higher TG/HDL-C tertile had a higher OR than those in the lower TG/HDL-C tertile, after adjusting for multiple covariates including indices for central obesity [T1: 1; T2: 4.02(1.86-8.71); T3: 4.30(1.99-9.29)]. Following stratification of waist circumference into quartiles, the effect of TG/HDL-C on insulin resistance remained significant irrespective of waist circumference. TG/HDL-C was associated with insulin resistance independent of waist circumference. Whether it could be a surrogate marker for insulin resistance in Chinese patients with newly diagnosed type 2 diabetes mellitus still needs to be confirmed by more researches.

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

Boutilier, Justin J., E-mail: j.boutilier@mail.utoronto.ca; Lee, Taewoo; Craig, Tim

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and appliedmore » three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR weight prediction methodologies perform comparably to the LR model and can produce clinical quality treatment plans by simultaneously predicting multiple weights that capture trade-offs associated with sparing multiple OARs.« less

Burnout Syndrome and associated factors among medical students: a cross-sectional study

PubMed Central

de Oliva Costa, Edméa Fontes; Santos, Shirley Andrade; de Abreu Santos, Ana Teresa Rodrigues; de Melo, Enaldo Vieira; de Andrade, Tarcísio Matos

2012-01-01

OBJECTIVES: To assess the prevalence and levels of burnout syndrome among medical students at the Universidade Federal de Sergipe-Brazil and to identify associated factors. METHODS: A cross-sectional study was performed with randomly selected students in 2009. The Maslach Burnout Inventory/Student Survey (MBI-SS) and a structured questionnaire on socio-demographic characteristics, the educational process, and individual aspects were used. Statistical evaluation of multiple variables was performed through backward stepwise logistic regression analysis. RESULTS: The prevalence of burnout was 10.3% (n = 369). The prevalence was higher among those who did not have confidence in their clinical skills (Odds Ratio–OR = 6.47), those who felt uncomfortable with course activities (OR = 5.76), and those who did not see the coursework as a source of pleasure (OR = 4.68). CONCLUSION: There was a significant prevalence of burnout among the medical students studied. Three variables, in particular, were associated with burnout and were directly related to the medical education process. Preventive and intervention measures must be adopted, and longitudinal studies should be conducted. PMID:22760894

Familial aggregation of focal seizure semiology in the Epilepsy Phenome/Genome Project.

PubMed

Tobochnik, Steven; Fahlstrom, Robyn; Shain, Catherine; Winawer, Melodie R

2017-07-04

To improve phenotype definition in genetic studies of epilepsy, we assessed the familial aggregation of focal seizure types and of specific seizure symptoms within the focal epilepsies in families from the Epilepsy Phenome/Genome Project. We studied 302 individuals with nonacquired focal epilepsy from 149 families. Familial aggregation was assessed by logistic regression analysis of relatives' traits (dependent variable) by probands' traits (independent variable), estimating the odds ratio for each symptom in a relative given presence vs absence of the symptom in the proband. In families containing multiple individuals with nonacquired focal epilepsy, we found significant evidence for familial aggregation of ictal motor, autonomic, psychic, and aphasic symptoms. Within these categories, ictal whole body posturing, diaphoresis, dyspnea, fear/anxiety, and déjà vu/jamais vu showed significant familial aggregation. Focal seizure type aggregated as well, including complex partial, simple partial, and secondarily generalized tonic-clonic seizures. Our results provide insight into genotype-phenotype correlation in the nonacquired focal epilepsies and a framework for identifying subgroups of patients likely to share susceptibility genes. © 2017 American Academy of Neurology.

Assessing digital literacy in web-based physical activity surveillance: the WIN study.

PubMed

Mathew, Merly; Morrow, James R; Frierson, Georita M; Bain, Tyson M

2011-01-01

PURPOSE. Investigate relations between demographic characteristics and submission method, Internet or paper, when physical activity behaviors are reported. DESIGN. Observational. SETTING . Metropolitan. SUBJECTS. Adult women (N  =  918) observed weekly for 2 years (total number of weekly reports, 44,963). MEASURES. Independent variables included age, race, education, income, employment status, and Internet skills. Dependent variables were method of submission (Internet or paper) and adherence. ANALYSIS . Logistic regression to analyze weekly odds of submitting data online and meeting study adherence criteria. Model 1 investigated method of submission, model 2 analyzed meeting study's Internet adherence, and model 3 analyzed meeting total adherence regardless of submission method. RESULTS. Whites, those with good Internet skills, and those reporting higher incomes were more likely to log online. Those who were white, older, and reported good Internet skills were more likely to be at least 75% adherent online. Older women were more likely to be adherent regardless of method. Employed women were less likely to log online or be adherent. CONCLUSION . Providing participants with multiple submission methods may reduce potential bias and provide more generalizable results relevant for future Internet-based research.

Relationship between long working hours and depression in two working populations: a structural equation model approach.

PubMed

Amagasa, Takashi; Nakayama, Takeo

2012-07-01

To test the hypothesis that relationship reported between long working hours and depression was inconsistent in previous studies because job demand was treated as a confounder. Structural equation modeling was used to construct five models, using work-related factors and depressive mood scale obtained from 218 clerical workers, to test for goodness of fit and was externally validated with data obtained from 1160 sales workers. Multiple logistic regression analysis was also performed. The model that showed that long working hours increased depression risk when job demand was regarded as an intermediate variable was the best fitted model (goodness-of-fit index/root-mean-square error of approximation: 0.981 to 0.996/0.042 to 0.044). The odds ratio for depression risk with work that was high demand and 60 hours or more per week was estimated at 2 to 4 versus work that was low demand and less than 60 hours per week. Long working hours increased depression risk, with job demand being an intermediate variable.

Women's Retirement Expectations: How Stable Are They?

PubMed Central

Hardy, Melissa A.

2009-01-01

Objective Using the National Longitudinal Survey of Mature Women, we examine between- and within-person differences in expected retirement age as a key element of the retirement planning process. The expectation typologies of 1,626 women born between 1923 and 1937 were classified jointly on the basis of specificity and consistency. Methods Latent class analysis was used to determine retirement expectation patterns over a 7-year span. Multinomial logistic regression analyses were employed to estimate the effects of demographic and status characteristics on the likelihood of reporting 4 distinct longitudinal patterns of retirement expectations. Results Substantial heterogeneity in reports of expected retirement age between and within individuals over the 7-year span was found. Demographic and status characteristics, specifically age, race, marital status, job tenure, and recent job change, sorted respondents into different retirement expectation patterns. Conclusions The frequent within-person fluctuations and substantial between-person heterogeneity in retirement expectations indicate uncertainty and variability in both expectations and process of expectation formation. Variability in respondents' reports suggests that studying retirement expectations at multiple time points better captures the dynamics of preretirement planning. PMID:19176483

Multinomial Logistic Regression Predicted Probability Map To Visualize The Influence Of Socio-Economic Factors On Breast Cancer Occurrence in Southern Karnataka

NASA Astrophysics Data System (ADS)

Madhu, B.; Ashok, N. C.; Balasubramanian, S.

2014-11-01

Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.

Return-to-work of sick-listed workers without an employment contract--what works?

PubMed

Vermeulen, Sylvia J; Tamminga, Sietske J; Schellart, Antonius Jm; Ybema, Jan Fekke; Anema, Johannes R

2009-07-14

In the past decade flexible labour market arrangements have emerged as a significant change in the European Union labour market. Studies suggest that these new types of labour arrangements may be linked to ill health, an increased risk for work disability, and inadequate vocational rehabilitation. Therefore, the objectives of this study were: 1. to examine demographic characteristics of workers without an employment contract sick-listed for at least 13 weeks, 2. to describe the content and frequency of occupational health care (OHC) interventions for these sick-listed workers, and 3. to examine OHC interventions as possible determinants for return-to-work (RTW) of these workers. A cohort of 1077 sick-listed workers without an employment contract were included at baseline, i.e. 13 weeks after reporting sick. Demographic variables were available at baseline. Measurement of cross-sectional data took place 4-6 months after inclusion. Primary outcome measures were: frequency of OHC interventions and RTW-rates. Measured confounding variables were: gender, age, type of worker (temporary agency worker, unemployed worker, or remaining worker without employment contract), level of education, reason for absenteeism (diagnosis), and perceived health. The association between OHC interventions and RTW was analysed with a logistic multiple regression analysis. At 7-9 months after the first day of reporting sick only 19% of the workers had (partially or completely) returned to work, and most workers perceived their health as fairly poor or poor. The most frequently reported (49%) intervention was 'the OHC professional discussed RTW'. However, the intervention 'OHC professional made and discussed a RTW action plan' was reported by only 19% of the respondents. The logistic multiple regression analysis showed a significant positive association between RTW and the interventions: 'OHC professional discussed RTW'; and 'OHC professional made and discussed a RTW action plan'. The intervention 'OHC professional referred sick-listed worker to a vocational rehabilitation agency' was significantly associated with no RTW. This is the first time that characteristics of a large cohort of sick-listed workers without an employment contract were examined. An experimental or prospective study is needed to explore the causal nature of the associations found between OHC interventions and RTW.

Estimation of a Nonlinear Intervention Phase Trajectory for Multiple-Baseline Design Data

ERIC Educational Resources Information Center

Hembry, Ian; Bunuan, Rommel; Beretvas, S. Natasha; Ferron, John M.; Van den Noortgate, Wim

2015-01-01

A multilevel logistic model for estimating a nonlinear trajectory in a multiple-baseline design is introduced. The model is applied to data from a real multiple-baseline design study to demonstrate interpretation of relevant parameters. A simple change-in-levels (?"Levels") model and a model involving a quadratic function…

Clustering performance comparison using K-means and expectation maximization algorithms.

PubMed

Jung, Yong Gyu; Kang, Min Soo; Heo, Jun

2014-11-14

Clustering is an important means of data mining based on separating data categories by similar features. Unlike the classification algorithm, clustering belongs to the unsupervised type of algorithms. Two representatives of the clustering algorithms are the K -means and the expectation maximization (EM) algorithm. Linear regression analysis was extended to the category-type dependent variable, while logistic regression was achieved using a linear combination of independent variables. To predict the possibility of occurrence of an event, a statistical approach is used. However, the classification of all data by means of logistic regression analysis cannot guarantee the accuracy of the results. In this paper, the logistic regression analysis is applied to EM clusters and the K -means clustering method for quality assessment of red wine, and a method is proposed for ensuring the accuracy of the classification results.

Nowcasting of Low-Visibility Procedure States with Ordered Logistic Regression at Vienna International Airport

NASA Astrophysics Data System (ADS)

Kneringer, Philipp; Dietz, Sebastian; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Low-visibility conditions have a large impact on aviation safety and economic efficiency of airports and airlines. To support decision makers, we develop a statistical probabilistic nowcasting tool for the occurrence of capacity-reducing operations related to low visibility. The probabilities of four different low visibility classes are predicted with an ordered logistic regression model based on time series of meteorological point measurements. Potential predictor variables for the statistical models are visibility, humidity, temperature and wind measurements at several measurement sites. A stepwise variable selection method indicates that visibility and humidity measurements are the most important model inputs. The forecasts are tested with a 30 minute forecast interval up to two hours, which is a sufficient time span for tactical planning at Vienna Airport. The ordered logistic regression models outperform persistence and are competitive with human forecasters.

Landslide Hazard Mapping in Rwanda Using Logistic Regression

NASA Astrophysics Data System (ADS)

Piller, A.; Anderson, E.; Ballard, H.

2015-12-01

Landslides in the United States cause more than $1 billion in damages and 50 deaths per year (USGS 2014). Globally, figures are much more grave, yet monitoring, mapping and forecasting of these hazards are less than adequate. Seventy-five percent of the population of Rwanda earns a living from farming, mostly subsistence. Loss of farmland, housing, or life, to landslides is a very real hazard. Landslides in Rwanda have an impact at the economic, social, and environmental level. In a developing nation that faces challenges in tracking, cataloging, and predicting the numerous landslides that occur each year, satellite imagery and spatial analysis allow for remote study. We have focused on the development of a landslide inventory and a statistical methodology for assessing landslide hazards. Using logistic regression on approximately 30 test variables (i.e. slope, soil type, land cover, etc.) and a sample of over 200 landslides, we determine which variables are statistically most relevant to landslide occurrence in Rwanda. A preliminary predictive hazard map for Rwanda has been produced, using the variables selected from the logistic regression analysis.

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

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

Bramer, L. M.; Rounds, J.; Burleyson, C. D.

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions is examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and datasets were examined. A penalized logistic regression model fit at the operation-zone levelmore » was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at different time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. The methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.« less

Predictive capacity of sperm quality parameters and sperm subpopulations on field fertility after artificial insemination in sheep.

PubMed

Santolaria, P; Vicente-Fiel, S; Palacín, I; Fantova, E; Blasco, M E; Silvestre, M A; Yániz, J L

2015-12-01

This study was designed to evaluate the relevance of several sperm quality parameters and sperm population structure on the reproductive performance after cervical artificial insemination (AI) in sheep. One hundred and thirty-nine ejaculates from 56 adult rams were collected using an artificial vagina, processed for sperm quality assessment and used to perform 1319 AI. Analyses of sperm motility by computer-assisted sperm analysis (CASA), sperm nuclear morphometry by computer-assisted sperm morphometry analysis (CASMA), membrane integrity by acridine orange-propidium iodide combination and sperm DNA fragmentation using the sperm chromatin dispersion test (SCD) were performed. Clustering procedures using the sperm kinematic and morphometric data resulted in the classification of spermatozoa into three kinematic and three morphometric sperm subpopulations. Logistic regression procedures were used, including fertility at AI as the dependent variable (measured by lambing, 0 or 1) and farm, year, month of AI, female parity, female lambing-treatment interval, ram, AI technician and sperm quality parameters (including sperm subpopulations) as independent factors. Sperm quality variables remaining in the logistic regression model were viability and VCL. Fertility increased for each one-unit increase in viability (by a factor of 1.01) and in VCL (by a factor of 1.02). Multiple linear regression analyses were also performed to analyze the factors possibly influencing ejaculate fertility (N=139). The analysis yielded a significant (P<0.05) relationship between sperm viability and ejaculate fertility. The discriminant ability of the different semen variables to predict field fertility was analyzed using receiver operating characteristic (ROC) curve analysis. Sperm viability and VCL showed significant, albeit limited, predictive capacity on field fertility (0.57 and 0.54 Area Under Curve, respectively). The distribution of spermatozoa in the different subpopulations was not related to fertility. Copyright © 2015 Elsevier B.V. All rights reserved.

Area-level poverty and preterm birth risk: A population-based multilevel analysis

PubMed Central

DeFranco, Emily A; Lian, Min; Muglia, Louis A; Schootman, Mario

2008-01-01

Background Preterm birth is a complex disease with etiologic influences from a variety of social, environmental, hormonal, genetic, and other factors. The purpose of this study was to utilize a large population-based birth registry to estimate the independent effect of county-level poverty on preterm birth risk. To accomplish this, we used a multilevel logistic regression approach to account for multiple co-existent individual-level variables and county-level poverty rate. Methods Population-based study utilizing Missouri's birth certificate database (1989–1997). We conducted a multilevel logistic regression analysis to estimate the effect of county-level poverty on PTB risk. Of 634,994 births nested within 115 counties in Missouri, two levels were considered. Individual-level variables included demographics factors, prenatal care, health-related behavioral risk factors, and medical risk factors. The area-level variable included the percentage of the population within each county living below the poverty line (US census data, 1990). Counties were divided into quartiles of poverty; the first quartile (lowest rate of poverty) was the reference group. Results PTB < 35 weeks occurred in 24,490 pregnancies (3.9%). The rate of PTB < 35 weeks was 2.8% in counties within the lowest quartile of poverty and increased through the 4th quartile (4.9%), p < 0.0001. High county-level poverty was significantly associated with PTB risk. PTB risk (< 35 weeks) was increased for women who resided in counties within the highest quartile of poverty, adjusted odds ratio (adjOR) 1.18 (95% CI 1.03, 1.35), with a similar effect at earlier gestational ages (< 32 weeks), adjOR 1.27 (95% CI 1.06, 1.52). Conclusion Women residing in socioeconomically deprived areas are at increased risk of preterm birth, above other underlying risk factors. Although the risk increase is modest, it affects a large number of pregnancies. PMID:18793437

Area-level poverty and preterm birth risk: a population-based multilevel analysis.

PubMed

DeFranco, Emily A; Lian, Min; Muglia, Louis A; Schootman, Mario

2008-09-15

Preterm birth is a complex disease with etiologic influences from a variety of social, environmental, hormonal, genetic, and other factors. The purpose of this study was to utilize a large population-based birth registry to estimate the independent effect of county-level poverty on preterm birth risk. To accomplish this, we used a multilevel logistic regression approach to account for multiple co-existent individual-level variables and county-level poverty rate. Population-based study utilizing Missouri's birth certificate database (1989-1997). We conducted a multilevel logistic regression analysis to estimate the effect of county-level poverty on PTB risk. Of 634,994 births nested within 115 counties in Missouri, two levels were considered. Individual-level variables included demographics factors, prenatal care, health-related behavioral risk factors, and medical risk factors. The area-level variable included the percentage of the population within each county living below the poverty line (US census data, 1990). Counties were divided into quartiles of poverty; the first quartile (lowest rate of poverty) was the reference group. PTB < 35 weeks occurred in 24,490 pregnancies (3.9%). The rate of PTB < 35 weeks was 2.8% in counties within the lowest quartile of poverty and increased through the 4th quartile (4.9%), p < 0.0001. High county-level poverty was significantly associated with PTB risk. PTB risk (< 35 weeks) was increased for women who resided in counties within the highest quartile of poverty, adjusted odds ratio (adj OR) 1.18 (95% CI 1.03, 1.35), with a similar effect at earlier gestational ages (< 32 weeks), adj OR 1.27 (95% CI 1.06, 1.52). Women residing in socioeconomically deprived areas are at increased risk of preterm birth, above other underlying risk factors. Although the risk increase is modest, it affects a large number of pregnancies.

Environmental arsenic exposure and risk of diabetes type 2 in Ron Phibun subdistrict, Nakhon Si Thammarat Province, Thailand: unmatched and matched case–control studies

PubMed Central

Sripaoraya, Kwanyuen; Siriwong, Wattasit; Pavittranon, Sumol; Chapman, Robert S

2017-01-01

Background There are inconsistent findings on associations between low-to-moderate level of arsenic in water and diabetes risk from previous epidemiological reports. In Ron Phibun subdistrict, Nakhon Si Thammarat Province, Thailand, a low level of arsenic exposure among population was observed and increased diabetes mellitus (DM) rate was identified. Objectives We aimed to investigate the association between determinants (including low-level water arsenic exposure) of DM type 2 risk among residents of three villages of Ron Phibun subdistrict, Nakhon Si Thammarat Province. Materials and methods Secondary data from two previous community based-studies, conducted in 2000 and 2008, were utilized. Data on independent variables relating to arsenic exposure and sociodemographic characteristics were taken from questionnaires and worksheets for health-risk screening. Water samples collected during household visit were sent for analysis of arsenic level at certified laboratories. Diabetes cases (N=185) were those who had been diagnosed with DM type 2. Two groups of controls, one unmatched to cases (n=200) and one pair matched on age and gender (n=200), were selected for analysis as unmatched and matched case–control studies, respectively. A multiple imputation technique was used to impute missing values of independent variables. Multivariable logistic regression models, with independent variables for arsenic exposure and sociodemographic characteristics, were constructed. The unmatched and matched data sets were analyzed using unconditional and conditional logistic analyses, respectively. Results Older age, body mass index (BMI), having a history of illness in siblings and parents, and drinking were associated with increased DM type 2 risk. We found no convincing association between DM type 2 risk and water arsenic concentration in either study. Conclusion We did not observe meaningful association between diabetes risk and the low-to-moderate arsenic levels observed in this study. Further research is needed to confirm this finding in the study area and elsewhere in Thailand. PMID:28442938

Do Working Hours and Type of Work Affect Obesity in South Korean Female Workers? Analysis of the Korean Community Health Survey.

PubMed

Yoon, Chang-Gyo; Kang, Mo-Yeol; Bae, Kyu-Jung; Yoon, Jin-Ha

2016-02-01

The prevalence of obesity and the female labor participation rate have been rapidly increasing in South Korea. To examine the relationship between these factors, we investigated the association between timing and type of work and obesity in the Korean female working population. Data collected by the 2008 Community Health Survey (CHS) were analyzed using a complex, stratified, multistage, probability cluster sampling method. Descriptive analysis of relevant variables was performed using the chi-square test, and work-related variables by work type were identified using multivariate logistic regression. The relationship between long working hours, night/shift work, and body-mass index in female workers and explanatory, stratifying, and dependent variables and covariates was analyzed using multiple logistic regression models. A total of 42,234 CHS participants were eligible for study inclusion. Among both manual and nonmanual workers, working less than 40 (adjusted odds ratio [aOR] 1.18, 95% confidence interval [CI] 1.07-1.31 and aOR 1.29; 95% CI 1.09-0.52, respectively) or more than 60 (aOR 1.18, 95% CI 1.06-1.30 and aOR 1.28, 95% CI 1.04-1.57, respectively) hours per week was significantly associated with obesity after controlling for covariates. However, working type (day or night/shift) was significantly associated with obesity only in nonmanual workers (aOR 1.20, 95% CI 1.01-1.42). When we controlled working type in the model, manual workers who work more than 60 hours show higher likelihood of being obese (OR 1.10, 95% CI 1.02-1.18). Working fewer (<40) or more than (>60) hours per week is significantly associated with obesity in the Korean female working population, regardless of the type of work. The type of work (day vs. night/shift work) was significantly associated with obesity only in only nonmanual workers.

Logistics Modeling for Lunar Exploration Systems

NASA Technical Reports Server (NTRS)

Andraschko, Mark R.; Merrill, R. Gabe; Earle, Kevin D.

2008-01-01

The extensive logistics required to support extended crewed operations in space make effective modeling of logistics requirements and deployment critical to predicting the behavior of human lunar exploration systems. This paper discusses the software that has been developed as part of the Campaign Manifest Analysis Tool in support of strategic analysis activities under the Constellation Architecture Team - Lunar. The described logistics module enables definition of logistics requirements across multiple surface locations and allows for the transfer of logistics between those locations. A key feature of the module is the loading algorithm that is used to efficiently load logistics by type into carriers and then onto landers. Attention is given to the capabilities and limitations of this loading algorithm, particularly with regard to surface transfers. These capabilities are described within the context of the object-oriented software implementation, with details provided on the applicability of using this approach to model other human exploration scenarios. Some challenges of incorporating probabilistics into this type of logistics analysis model are discussed at a high level.

[Association between hours of television watched, physical activity, sleep and excess weight among young adults].

PubMed

Martínez-Moyá, María; Navarrete-Muñoz, Eva M; García de la Hera, Manuela; Giménez-Monzo, Daniel; González-Palacios, Sandra; Valera-Gran, Desirée; Sempere-Orts, María; Vioque, Jesús

2014-01-01

To explore the association between excess weight or body mass index (BMI) and the time spent watching television, self-reported physical activity and sleep duration in a young adult population. We analyzed cross-sectional baseline data of 1,135 participants (17-35 years old) from the project Dieta, salud y antropometría en población universitaria (Diet, Health and Anthrompmetric Variables in Univeristy Students). Information about time spent watching television, sleep duration, self-reported physical activity and self-reported height and weight was provided by a baseline questionnaire. BMI was calculated as kg/m(2) and excess of weight was defined as ≥25. We used multiple logistic regression to explore the association between excess weight (no/yes) and independent variables, and multiple linear regression for BMI. The prevalence of excess weight was 13.7% (11.2% were overweight and 2.5% were obese). A significant positive association was found between excess weight and a greater amount of time spent watching television. Participants who reported watching television >2h a day had a higher risk of excess weight than those who watched television ≤1h a day (OR=2.13; 95%CI: 1.37-3.36; p-trend: 0.002). A lower level of physical activity was associated with an increased risk of excess weight, although the association was statistically significant only in multiple linear regression (p=0.037). No association was observed with sleep duration. A greater number of hours spent watching television and lower physical activity were significantly associated with a higher BMI in young adults. Both factors are potentially modifiable with preventive strategies. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

Pregnancy interruption after second trimester diagnosis of fetal structural anomalies: the New Jersey Fetal Abnormalities Registry.

PubMed

Rauch, Eden R; Smulian, John C; DePrince, Kristin; Ananth, Cande V; Marcella, Stephen W

2005-10-01

The purpose of this study was to identify factors that predict a decision to interrupt a pregnancy in which there are fetal anomalies in the second trimester. The New Jersey Fetal Abnormalities Registry prospectively recruits and collects information on pregnancies (> or = 15 weeks of gestation) from New Jersey residents in whom a fetal structural anomaly has been suspected by maternal-fetal medicine specialists. Enrolled pregnancies that have major fetal structural abnormalities identified from 15 to 23 weeks of gestation were included. Outcomes were classified as either elective interruption or a natural pregnancy course, which might include a spontaneous fetal death or live birth. Predictors of elective interruption of pregnancy were examined with univariable and multivariable logistic regression analyses. Of the 97 cases, 33% of the women (n = 32) interrupted the pregnancy. Significant variables in the regression model that were associated with a decision to interrupt a pregnancy were earlier identification of fetal anomalies (19.0 +/- 2 weeks of gestation vs 20.5 +/- 2 weeks of gestation; P = .003), the presence of multiple anomalies (78% [25/32] vs 52% [33/63]; P = .01], and a presumption of lethality (56% [18/32] vs 14% [9/65]; P = .0001). These variables corresponded to an odds ratio for pregnancy interruption of 4.2 (95% CI, 1.0, 17.0) for multiple anomalies, 0.8 (95% CI, 0.7, 1.0) for each week of advancing gestational age, and 36.1 (95% CI, 2.9, 450.7) for presumed lethal abnormalities. Early diagnosis, the identification of multiple abnormalities, and an assessment of likely lethality of fetal anomalies are important factors for the optimization of parental autonomy in deciding pregnancy management.

Demands, skill discretion, decision authority and social climate at work as determinants of major depression in a 3-year follow-up study.

PubMed

Fandiño-Losada, Andrés; Forsell, Yvonne; Lundberg, Ingvar

2013-07-01

The psychosocial work environment may be a determinant of the development and course of depressive disorders, but the literature shows inconsistent findings. Thus, the aim of this study is to determine longitudinal effects of the job demands-control-support model (JDCSM) variables on the occurrence of major depression among working men and women from the general population. The sample comprised 4,710 working women and men living in Stockholm, who answered the same questionnaire twice, 3 years apart, who were not depressed during the first wave and had the same job in both waves. The questionnaire included JDCSM variables (demands, skill discretion, decision authority and social climate) and other co-variables (income, education, occupational group, social support, help and small children at home, living with an adult and depressive symptoms at time 1; and negative life events at time 2). Multiple logistic regressions were run to calculate odds ratios of having major depression at time 2, after adjustment for other JDCSM variables and co-variables. Among women, inadequate work social climate was the only significant risk indicator for major depression. Surprisingly, among men, high job demands and low skill discretion appeared as protective factors against major depression. The results showed a strong relationship between inadequate social climate and major depression among women, while there were no certain effects for the remaining exposure variables. Among men, few cases of major depression hampered well-founded conclusions regarding our findings of low job demands and high skill discretion as related to major depression.

Determinants of financial performance of home-visit nursing agencies in Japan.

PubMed

Fukui, Sakiko; Yoshiuchi, Kazuhiro; Fujita, Junko; Ikezaki, Sumie

2014-01-09

Japan has the highest aging population in the world and promotion of home health services is an urgent policy issue. As home-visit nursing plays a major role in home health services, the Japanese government began promotion of this activity in 1994. However, the scale of home-visit nursing agencies has remained small (the average numbers of nursing staff and other staff were 4.2 and 1.7, respectively, in 2011) and financial performance (profitability) is a concern in such small agencies. Additionally, the factors related to profitability in home-visit nursing agencies in Japan have not been examined multilaterally and in detail. Therefore, the purpose of the study was to examine the determinants of financial performance of home-visit nursing agencies. We performed a nationwide survey of 2,912 randomly selected home-visit nursing agencies in Japan. Multinomial logistic regression was used to clarify the determinants of profitability of the agency (profitable, stable or unprofitable) based on variables related to management of the agency (operating structure, management by a nurse manager, employment, patient utilization, quality control, regional cooperation, and financial condition). Among the selected home-visit nursing agencies, responses suitable for analysis were obtained from 1,340 (effective response rate, 46.0%). Multinomial logistic regression analysis showed that both profitability and unprofitability were related to multiple variables in management of the agency when compared to agencies with stable financial performance. These variables included the number of nursing staff/rehabilitation staff/patients, being owned by a hospital, the number of cooperative hospitals, home-death rate among terminal patients, controlling staff objectives by nurse managers, and income going to compensation. The results suggest that many variables in management of a home-visit nursing agency, including the operating structure of the agency, regional cooperation, staff employment, patient utilization, and quality control of care, have an influence in both profitable and unprofitable agencies. These findings indicate the importance of consideration of management issues in achieving stable financial performance in home-visit nursing agencies in Japan. The findings may also be useful in other countries with growing aging populations.

Determinants of financial performance of home-visit nursing agencies in Japan

PubMed Central

2014-01-01

Background Japan has the highest aging population in the world and promotion of home health services is an urgent policy issue. As home-visit nursing plays a major role in home health services, the Japanese government began promotion of this activity in 1994. However, the scale of home-visit nursing agencies has remained small (the average numbers of nursing staff and other staff were 4.2 and 1.7, respectively, in 2011) and financial performance (profitability) is a concern in such small agencies. Additionally, the factors related to profitability in home-visit nursing agencies in Japan have not been examined multilaterally and in detail. Therefore, the purpose of the study was to examine the determinants of financial performance of home-visit nursing agencies. Methods We performed a nationwide survey of 2,912 randomly selected home-visit nursing agencies in Japan. Multinomial logistic regression was used to clarify the determinants of profitability of the agency (profitable, stable or unprofitable) based on variables related to management of the agency (operating structure, management by a nurse manager, employment, patient utilization, quality control, regional cooperation, and financial condition). Results Among the selected home-visit nursing agencies, responses suitable for analysis were obtained from 1,340 (effective response rate, 46.0%). Multinomial logistic regression analysis showed that both profitability and unprofitability were related to multiple variables in management of the agency when compared to agencies with stable financial performance. These variables included the number of nursing staff/rehabilitation staff/patients, being owned by a hospital, the number of cooperative hospitals, home-death rate among terminal patients, controlling staff objectives by nurse managers, and income going to compensation. Conclusions The results suggest that many variables in management of a home-visit nursing agency, including the operating structure of the agency, regional cooperation, staff employment, patient utilization, and quality control of care, have an influence in both profitable and unprofitable agencies. These findings indicate the importance of consideration of management issues in achieving stable financial performance in home-visit nursing agencies in Japan. The findings may also be useful in other countries with growing aging populations. PMID:24400964

Epidemiologic research using probabilistic outcome definitions.

PubMed

Cai, Bing; Hennessy, Sean; Lo Re, Vincent; Small, Dylan S

2015-01-01

Epidemiologic studies using electronic healthcare data often define the presence or absence of binary clinical outcomes by using algorithms with imperfect specificity, sensitivity, and positive predictive value. This results in misclassification and bias in study results. We describe and evaluate a new method called probabilistic outcome definition (POD) that uses logistic regression to estimate the probability of a clinical outcome using multiple potential algorithms and then uses multiple imputation to make valid inferences about the risk ratio or other epidemiologic parameters of interest. We conducted a simulation to evaluate the performance of the POD method with two variables that can predict the true outcome and compared the POD method with the conventional method. The simulation results showed that when the true risk ratio is equal to 1.0 (null), the conventional method based on a binary outcome provides unbiased estimates. However, when the risk ratio is not equal to 1.0, the traditional method, either using one predictive variable or both predictive variables to define the outcome, is biased when the positive predictive value is <100%, and the bias is very severe when the sensitivity or positive predictive value is poor (less than 0.75 in our simulation). In contrast, the POD method provides unbiased estimates of the risk ratio both when this measure of effect is equal to 1.0 and not equal to 1.0. Even when the sensitivity and positive predictive value are low, the POD method continues to provide unbiased estimates of the risk ratio. The POD method provides an improved way to define outcomes in database research. This method has a major advantage over the conventional method in that it provided unbiased estimates of risk ratios and it is easy to use. Copyright © 2014 John Wiley & Sons, Ltd.

Measuring behaviours for escaping from house fires: use of latent variable models to summarise multiple behaviours.

PubMed

Ploubidis, G B; Edwards, P; Kendrick, D

2015-12-15

This paper reports the development and testing of a construct measuring parental fire safety behaviours for planning escape from a house fire. Latent variable modelling of data on parental-reported fire safety behaviours and plans for escaping from a house fire and multivariable logistic regression to quantify the association between groups defined by the latent variable modelling and parental-report of having a plan for escaping from a house fire. Data comes from 1112 participants in a cluster randomised controlled trial set in children's centres in 4 study centres in the UK. A two class model provided the best fit to the data, combining responses to five fire safety planning behaviours. The first group ('more behaviours for escaping from a house fire') comprised 86% of participants who were most likely to have a torch, be aware of how their smoke alarm sounds, to have external door and window keys accessible, and exits clear. The second group ('fewer behaviours for escaping from a house fire') comprised 14% of participants who were less likely to report these five behaviours. After adjusting for potential confounders, participants allocated to the 'more behaviours for escaping from a house fire group were 2.5 times more likely to report having an escape plan (OR 2.48; 95% CI 1.59-3.86) than those in the "fewer behaviours for escaping from a house fire" group. Multiple fire safety behaviour questions can be combined into a single binary summary measure of fire safety behaviours for escaping from a house fire. Our findings will be useful to future studies wishing to use a single measure of fire safety planning behaviour as measures of outcome or exposure. NCT 01452191. Date of registration 13/10/2011.

The relationship of bone and blood lead to hypertension: Further analyses of the normative aging study data

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

Hu, H.; Kim, Rokho; Korrick, S.

1996-12-31

In an earlier report based on participants in the Veterans Administration Normative Aging Study, we found a significant association between the risk of hypertension and lead levels in tibia. To examine the possible confounding effects of education and occupation, we considered in this study five levels of education and three levels of occupation as independent variables in the statistical model. Of 1,171 active subjects seen between August 1991 and December 1994, 563 provided complete data for this analysis. In the initial logistic regression model, acre and body mass index, family history of hypertension, and dietary sodium intake, but neither cumulativemore » smoking nor alcohol ingestion, conferred increased odds ratios for being hypertensive that were statistically significant. When the lead biomarkers were added separately to this initial logistic model, tibia lead and patella lead levels were associated with significantly elevated odds ratios for hypertension. In the final backward elimination logistic regression model that included categorical variables for education and occupation, the only variables retained were body mass index, family history of hypertension, and tibia lead level. We conclude that education and occupation variables were not confounding the association between the lead biomarkers and hypertension that we reported previously. 27 refs., 3 tabs.« less

Registered dietitian's personal beliefs and characteristics predict their teaching or intention to teach fresh vegetable food safety.

PubMed

Casagrande, Gina; LeJeune, Jeffery; Belury, Martha A; Medeiros, Lydia C

2011-04-01

The Theory of Planned Behavior was used to determine if dietitians personal characteristics and beliefs about fresh vegetable food safety predict whether they currently teach, intend to teach, or neither currently teach nor intend to teach food safety information to their clients. Dietitians who participated in direct client education responded to this web-based survey (n=327). The survey evaluated three independent belief variables: Subjective Norm, Attitudes, and Perceived Behavioral Control. Spearman rho correlations were completed to determine variables that correlated best with current teaching behavior. Multinomial logistical regression was conducted to determine if the belief variables significantly predicted dietitians teaching behavior. Binary logistic regression was used to determine which independent variable was the better predictor of whether dietitians currently taught. Controlling for age, income, education, and gender, the multinomial logistical regression was significant. Perceived behavioral control was the best predictor of whether a dietitian currently taught fresh vegetable food safety. Factors affecting whether dietitians currently taught were confidence in fresh vegetable food safety knowledge, being socially influenced, and a positive attitude toward the teaching behavior. These results validate the importance of teaching food safety effectively and may be used to create more informed food safety curriculum for dietitians. Copyright © 2011 Elsevier Ltd. All rights reserved.

Plasma D-dimer levels and ischaemic lesions in multiple vascular regions can predict occult cancer in patients with cryptogenic stroke.

PubMed

Gon, Y; Sakaguchi, M; Takasugi, J; Kawano, T; Kanki, H; Watanabe, A; Oyama, N; Terasaki, Y; Sasaki, T; Mochizuki, H

2017-03-01

Cancer patients with cryptogenic stroke often have high plasma D-dimer levels and lesions in multiple vascular regions. Hence, if patients with cryptogenic stroke display such characteristics, occult cancer could be predicted. This study aimed to investigate the clinical characteristics of cryptogenic stroke as the first manifestation of occult cancer and to determine whether plasma D-dimer levels and lesions in multiple vascular regions can predict occult cancer in patients with cryptogenic stroke. Between January 2006 and October 2015, data on 1225 patients with acute ischaemic stroke were extracted from the stroke database of Osaka University Hospital. Among them, 184 patients were classified as having cryptogenic stroke, and 120 patients without a diagnosis of cancer at stroke onset were identified. Clinical variables were analyzed between cryptogenic stroke patients with and without occult cancer. Among 120 cryptogenic stroke patients without a diagnosis of cancer, 12 patients had occult cancer. The body mass index, hemoglobin levels and albumin levels were lower; plasma D-dimer and high-sensitivity C-reactive protein levels were higher; and lesions in multiple vascular regions were more common in patients with than in those without occult cancer. Multiple logistic regression analysis revealed that plasma D-dimer levels (odds ratio, 3.48; 95% confidence interval, 1.68-8.33; P = 0.002) and lesions in multiple vascular regions (odds ratio, 7.40; 95% confidence interval, 1.70-39.45; P = 0.01) independently predicted occult cancer. High plasma D-dimer levels and lesions in multiple vascular regions can be used to predict occult cancer in patients with cryptogenic stroke. © 2016 EAN.

Analysis of threats to research validity introduced by audio recording clinic visits: Selection bias, Hawthorne effect, both, or neither?

PubMed Central

Henry, Stephen G.; Jerant, Anthony; Iosif, Ana-Maria; Feldman, Mitchell D.; Cipri, Camille; Kravitz, Richard L.

2015-01-01

Objective To identify factors associated with participant consent to record visits; to estimate effects of recording on patient-clinician interactions Methods Secondary analysis of data from a randomized trial studying communication about depression; participants were asked for optional consent to audio record study visits. Multiple logistic regression was used to model likelihood of patient and clinician consent. Multivariable regression and propensity score analyses were used to estimate effects of audio recording on 6 dependent variables: discussion of depressive symptoms, preventive health, and depression diagnosis; depression treatment recommendations; visit length; visit difficulty. Results Of 867 visits involving 135 primary care clinicians, 39% were recorded. For clinicians, only working in academic settings (P=0.003) and having worked longer at their current practice (P=0.02) were associated with increased likelihood of consent. For patients, white race (P=0.002) and diabetes (P=0.03) were associated with increased likelihood of consent. Neither multivariable regression nor propensity score analyses revealed any significant effects of recording on the variables examined. Conclusion Few clinician or patient characteristics were significantly associated with consent. Audio recording had no significant effect on any dependent variables. Practice Implications Benefits of recording clinic visits likely outweigh the risks of bias in this setting. PMID:25837372

Socio-demographic predictors of sleep complaints in indigenous Siberians with a mixed economy.

PubMed

Wilson, Hannah J; Klimova, Tatiana M; Knuston, Kristen L; Fedorova, Valentina I; Fedorov, Afanasy; Yegorovna, Baltakhinova M; Leonard, William R

2015-08-01

Socio-demographic indicators closely relate to sleep in industrialized populations. However we know very little about how such factors impact sleep in populations undergoing industrialization. Within populations transitioning to the global economy, the preliminary evidence has found an inconsistent relationship between socio-demographics and sleep complaints across countries and social strata. Surveys were conducted on a sample of rural Sakha (Yakut) adults (n = 168) during the autumn of 2103 to assess variation in socio-demographics and sleep complaints, including trouble sleeping and daytime sleepiness. Socio-demographic variables included age, gender, socioeconomic measures, and markers of traditional/market-based lifestyle. We tested whether the socio-demographic variables predicted sleep complaints using bivariate analyses and multiple logistic regressions. Trouble sleeping was reported by 18.5% of the participants and excessive daytime sleepiness (EDS) by 17.3%. Trouble sleeping was significantly predicted by older age, female gender, and mixing traditional and market-based lifestyles. EDS was not significantly predicted by any socio-demographic variable. These findings support the few large-scale studies that found inconsistent relationships between measures of socioeconomic status and sleep complaints in transitioning populations. Employing a mix of traditional and market-based lifestyles may leave Sakha in a space of vulnerability, leading to trouble sleeping. © 2015 Wiley Periodicals, Inc.

Wheezing conditions in early childhood: prevalence and risk factors in the city of São Paulo, Brazil.

PubMed Central

Benício, Maria Helena D.; Ferreira, Marcelo U.; Cardoso, Maria Regina A.; Konno, Sílvia C.; Monteiro, Carlos A.

2004-01-01

OBJECTIVE: To investigate the prevalence and risk factors for wheezing disorders in early childhood in São Paulo, Brazil, the largest metropolitan area of South America. METHODS: A population-based cross-sectional survey of 1132 children aged 6-59 months was carried out between 1995 and 1996 to obtain information on recent wheezing and on independent variables such as demographic, socioeconomic, environmental, maternal and nutritional variables and immunization status. Intestinal parasitic infections were diagnosed using standard techniques. Multiple unconditional logistic regression was used to describe associations between outcome and independent variables. FINDINGS: The prevalence of recent wheezing (one or more reported episodes in the past 12 months) was 12.5%; 93% of children with wheezing were also reported to have a medical diagnosis of asthma. Recent wheezing was associated with low per capita income, poor quality of housing, day-care attendance, low birth weight and infection with intestinal helminths. CONCLUSION: Wheezing in early childhood in São Paulo, although more common than in most developing countries, remains less prevalent than in urban areas of industrialized countries. Low income and conditions associated with poverty (poor housing, low birth weight and parasitic infections) are some of the main risk factors for wheezing disorders among young children in this city. PMID:15508196

HRCT findings of collagen vascular disease-related interstitial pneumonia (CVD-IP): a comparative study among individual underlying diseases.

PubMed

Tanaka, N; Kunihiro, Y; Kubo, M; Kawano, R; Oishi, K; Ueda, K; Gondo, T

2018-05-29

To identify characteristic high-resolution computed tomography (CT) findings for individual collagen vascular disease (CVD)-related interstitial pneumonias (IPs). The HRCT findings of 187 patients with CVD, including 55 patients with rheumatoid arthritis (RA), 50 with systemic sclerosis (SSc), 46 with polymyositis/dermatomyositis (PM/DM), 15 with mixed connective tissue disease, 11 with primary Sjögren's syndrome, and 10 with systemic lupus erythematosus, were evaluated. Lung parenchymal abnormalities were compared among CVDs using χ 2 test, Kruskal-Wallis test, and multiple logistic regression analysis. A CT-pathology correlation was performed in 23 patients. In RA-IP, honeycombing was identified as the significant indicator based on multiple logistic regression analyses. Traction bronchiectasis (81.8%) was further identified as the most frequent finding based on χ 2 test. In SSc IP, lymph node enlargement and oesophageal dilatation were identified as the indicators based on multiple logistic regression analyses, and ground-glass opacity (GGO) was the most extensive based on Kruskal-Wallis test, which reflects the higher frequency of the pathological nonspecific interstitial pneumonia (NSIP) pattern present in the CT-pathology correlation. In PM/DM IP, airspace consolidation and the absence of honeycombing were identified as the indicators based on multiple logistic regression analyses, and predominance of consolidation over GGO (32.6%) and predominant subpleural distribution of GGO/consolidation (41.3%) were further identified as the most frequent findings based on χ 2 test, which reflects the higher frequency of the pathological NSIP and/or the organising pneumonia patterns present in the CT-pathology correlation. Several characteristic high-resolution CT findings with utility for estimating underlying CVD were identified. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Comparison of Two Approaches for Handling Missing Covariates in Logistic Regression

ERIC Educational Resources Information Center

Peng, Chao-Ying Joanne; Zhu, Jin

2008-01-01

For the past 25 years, methodological advances have been made in missing data treatment. Most published work has focused on missing data in dependent variables under various conditions. The present study seeks to fill the void by comparing two approaches for handling missing data in categorical covariates in logistic regression: the…

Predictors of Placement Stability at the State Level: The Use of Logistic Regression to Inform Practice

ERIC Educational Resources Information Center

Courtney, Jon R.; Prophet, Retta

2011-01-01

Placement instability is often associated with a number of negative outcomes for children. To gain state level contextual knowledge of factors associated with placement stability/instability, logistic regression was applied to selected variables from the New Mexico Adoption and Foster Care Administrative Reporting System dataset. Predictors…

Logistics Reduction and Repurposing Beyond Low Earth Orbit

NASA Technical Reports Server (NTRS)

Ewert, Michael K.; Broyan, James L., Jr.

2012-01-01

All human space missions, regardless of destination, require significant logistical mass and volume that is strongly proportional to mission duration. Anything that can be done to reduce initial mass and volume of supplies or reuse items that have been launched will be very valuable. Often, the logistical items require disposal and represent a trash burden. Logistics contributions to total mission architecture mass can be minimized by considering potential reuse using systems engineering analysis. In NASA's Advanced Exploration Systems "Logistics Reduction and Repurposing Project," various tasks will reduce the intrinsic mass of logistical packaging, enable reuse and repurposing of logistical packaging and carriers for other habitation, life support, crew health, and propulsion functions, and reduce or eliminate the nuisance aspects of trash at the same time. Repurposing reduces the trash burden and eliminates the need for hardware whose function can be provided by use of spent logistical items. However, these reuse functions need to be identified and built into future logical systems to enable them to effectively have a secondary function. These technologies and innovations will help future logistics systems to support multiple exploration missions much more efficiently.

The intermediate endpoint effect in logistic and probit regression

PubMed Central

MacKinnon, DP; Lockwood, CM; Brown, CH; Wang, W; Hoffman, JM

2010-01-01

Background An intermediate endpoint is hypothesized to be in the middle of the causal sequence relating an independent variable to a dependent variable. The intermediate variable is also called a surrogate or mediating variable and the corresponding effect is called the mediated, surrogate endpoint, or intermediate endpoint effect. Clinical studies are often designed to change an intermediate or surrogate endpoint and through this intermediate change influence the ultimate endpoint. In many intermediate endpoint clinical studies the dependent variable is binary, and logistic or probit regression is used. Purpose The purpose of this study is to describe a limitation of a widely used approach to assessing intermediate endpoint effects and to propose an alternative method, based on products of coefficients, that yields more accurate results. Methods The intermediate endpoint model for a binary outcome is described for a true binary outcome and for a dichotomization of a latent continuous outcome. Plots of true values and a simulation study are used to evaluate the different methods. Results Distorted estimates of the intermediate endpoint effect and incorrect conclusions can result from the application of widely used methods to assess the intermediate endpoint effect. The same problem occurs for the proportion of an effect explained by an intermediate endpoint, which has been suggested as a useful measure for identifying intermediate endpoints. A solution to this problem is given based on the relationship between latent variable modeling and logistic or probit regression. Limitations More complicated intermediate variable models are not addressed in the study, although the methods described in the article can be extended to these more complicated models. Conclusions Researchers are encouraged to use an intermediate endpoint method based on the product of regression coefficients. A common method based on difference in coefficient methods can lead to distorted conclusions regarding the intermediate effect. PMID:17942466

Sparse modeling of spatial environmental variables associated with asthma

PubMed Central

Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.

2014-01-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437

Sparse modeling of spatial environmental variables associated with asthma.

PubMed

Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

2015-02-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

Association between different measurements of blood pressure variability by ABP monitoring and ankle-brachial index.

PubMed

Wittke, Estefânia; Fuchs, Sandra C; Fuchs, Flávio D; Moreira, Leila B; Ferlin, Elton; Cichelero, Fábio T; Moreira, Carolina M; Neyeloff, Jeruza; Moreira, Marina B; Gus, Miguel

2010-11-05

Blood pressure (BP) variability has been associated with cardiovascular outcomes, but there is no consensus about the more effective method to measure it by ambulatory blood pressure monitoring (ABPM). We evaluated the association between three different methods to estimate BP variability by ABPM and the ankle brachial index (ABI). In a cross-sectional study of patients with hypertension, BP variability was estimated by the time rate index (the first derivative of SBP over time), standard deviation (SD) of 24-hour SBP; and coefficient of variability of 24-hour SBP. ABI was measured with a doppler probe. The sample included 425 patients with a mean age of 57 ± 12 years, being 69.2% women, 26.1% current smokers and 22.1% diabetics. Abnormal ABI (≤ 0.90 or ≥ 1.40) was present in 58 patients. The time rate index was 0.516 ± 0.146 mmHg/min in patients with abnormal ABI versus 0.476 ± 0.124 mmHg/min in patients with normal ABI (P = 0.007). In a logistic regression model the time rate index was associated with ABI, regardless of age (OR = 6.9, 95% CI = 1.1- 42.1; P = 0.04). In a multiple linear regression model, adjusting for age, SBP and diabetes, the time rate index was strongly associated with ABI (P < 0.01). None of the other indexes of BP variability were associated with ABI in univariate and multivariate analyses. Time rate index is a sensible method to measure BP variability by ABPM. Its performance for risk stratification of patients with hypertension should be explored in longitudinal studies.

Measures of work-family conflict predict sickness absence from work.

PubMed

Clays, Els; Kittel, France; Godin, Isabelle; Bacquer, Dirk De; Backer, Guy De

2009-08-01

To examine the relation between work-family conflict and sickness absence. The BELSTRESS III study comprised 2983 middle-aged workers. Strain-based work-home interference (WHI) and home-work interference (HWI) were assessed by means of self-administered questionnaires. Prospective data of registered sickness absence during 12-months follow-up were collected. Multiple logistic regression analysis was conducted. HWI was positively and significantly related to high sickness absence duration (at least 10 sick leave days) and high sickness absence frequency (at least 3 sick leave episodes) in men and women, also after adjustments were made for sociodemographic variables, health indicators, and environmental psychosocial factors. In multivariate analysis, no association between WHI and sickness absence was found. HWI was positively and significantly related to high sickness absence duration and frequency during 12-months follow-up in male and female workers.

Habitat features and predictive habitat modeling for the Colorado chipmunk in southern New Mexico

USGS Publications Warehouse

Rivieccio, M.; Thompson, B.C.; Gould, W.R.; Boykin, K.G.

2003-01-01

Two subspecies of Colorado chipmunk (state threatened and federal species of concern) occur in southern New Mexico: Tamias quadrivittatus australis in the Organ Mountains and T. q. oscuraensis in the Oscura Mountains. We developed a GIS model of potentially suitable habitat based on vegetation and elevation features, evaluated site classifications of the GIS model, and determined vegetation and terrain features associated with chipmunk occurrence. We compared GIS model classifications with actual vegetation and elevation features measured at 37 sites. At 60 sites we measured 18 habitat variables regarding slope, aspect, tree species, shrub species, and ground cover. We used logistic regression to analyze habitat variables associated with chipmunk presence/absence. All (100%) 37 sample sites (28 predicted suitable, 9 predicted unsuitable) were classified correctly by the GIS model regarding elevation and vegetation. For 28 sites predicted suitable by the GIS model, 18 sites (64%) appeared visually suitable based on habitat variables selected from logistic regression analyses, of which 10 sites (36%) were specifically predicted as suitable habitat via logistic regression. We detected chipmunks at 70% of sites deemed suitable via the logistic regression models. Shrub cover, tree density, plant proximity, presence of logs, and presence of rock outcrop were retained in the logistic model for the Oscura Mountains; litter, shrub cover, and grass cover were retained in the logistic model for the Organ Mountains. Evaluation of predictive models illustrates the need for multi-stage analyses to best judge performance. Microhabitat analyses indicate prospective needs for different management strategies between the subspecies. Sensitivities of each population of the Colorado chipmunk to natural and prescribed fire suggest that partial burnings of areas inhabited by Colorado chipmunks in southern New Mexico may be beneficial. These partial burnings may later help avoid a fire that could substantially reduce habitat of chipmunks over a mountain range.

[Correlation between long time systolic blood pressure variability and short time systolic blood pressure in aged population].

PubMed

An, Shasha; Zheng, Xiaoming; Li, Zhifang; Wang, Yang; Wu, Yuntao; Zhang, Wenyan; Zhao, Haiyan; Wu, Aiping; Wang, Ruixia; Tao, Jie; Gao, Xinying; Wu, Shouling

2015-11-01

To investigate the correlation between long time systolic blood pressure variability(SBPV)and short time SBPV in aged population. A total of 752 subjects aged ≥60 years of Kailuan Group who took part in 2006-2007, 2008-2009, 2010-2011 and 2012-2013 health examination were included by cluster sampling method.Long time SBPV was calculated by standard deviation of mean systolic blood pressure measured in 2006-2007, 2008-2009, 2010-2011 and 2012-2013, standard deviation represents short time systolic blood pressure which is derived from 24 hour ambulatory blood pressure monitoring. The observation population was divided into three groups according to the third tertiles of the time systolic blood pressure variability: the first point(<9.09 mmHg (1 mmHg=0.133 kPa)), second point (≥9.09 mmHg, and <14.29 mmHg), and third point (≥14.29 mmHg). Multivariate logistic regression analysis was used to analyze the correlation between long time systolic blood pressure variability and short time systolic blood pressure. (1) The participants' age were (67.0±5.7) years old (284 women). (2) The 24 hours and daytime SSD were (14.7±4.0) mmHg, (14.7±3.5) mmHg, (15.7±4.4) mmHg (P=0.010) and (14.1±4.4) mmHg, (14.2±3.5) mmHg and (15.4±4.6) mmHg (P<0.001) according to the tertiles of long time systolic blood pressure variability, respectively, nighttime SSD were (12.0±4.4) mmHg, (11.8±4.8) mmHg and (11.9±4.9) mmHg (P=0.900). (3) Multiple logistic regression analysis showed that the tertiles of long time SSD was the risk factor for increasing daytime SSD>14.00 mmHg (OR=1.51, 95%CI: 1.03-2.23, P=0.037), but not a risk factor for increasing 24 hours SSD>14.41 mmHg (OR=1.10, 95%CI: 0.75-1.61, P=0.639) and nighttime SSD>11.11 mmHg (OR=0.98, 95%CI: 0.67-1.42, P=0.899). Increased long time SBPV is a risk factor for increasing daytime SBPV.

Logistics Reduction and Repurposing Beyond Low Earth Orbit

NASA Technical Reports Server (NTRS)

Broyan, James Lee, Jr.; Ewert, Michael K.

2011-01-01

All human space missions, regardless of destination, require significant logistical mass and volume that is strongly proportional to mission duration. Anything that can be done to reduce initial mass and volume of supplies or reuse items that have been launched will be very valuable. Often, the logistical items require disposal and represent a trash burden. Utilizing systems engineering to analyze logistics from cradle-to-grave and then to potential reuse, can minimize logistics contributions to total mission architecture mass. In NASA's Advanced Exploration Systems Logistics Reduction and Repurposing Project , various tasks will reduce the intrinsic mass of logistical packaging, enable reuse and repurposing of logistical packaging and carriers for other habitation, life support, crew health, and propulsion functions, and reduce or eliminate the nuisances aspects of trash at the same time. Repurposing reduces the trash burden and eliminates the need for hardware whose function can be provided by use of spent logistic items. However, these reuse functions need to be identified and built into future logical systems to enable them to effectively have a secondary function. These technologies and innovations will help future logistic systems to support multiple exploration missions much more efficiently.

Association of low back pain with muscle stiffness and muscle mass of the lumbar back muscles, and sagittal spinal alignment in young and middle-aged medical workers.

PubMed

Masaki, Mitsuhiro; Aoyama, Tomoki; Murakami, Takashi; Yanase, Ko; Ji, Xiang; Tateuchi, Hiroshige; Ichihashi, Noriaki

2017-11-01

Muscle stiffness of the lumbar back muscles in low back pain (LBP) patients has not been clearly elucidated because quantitative assessment of the stiffness of individual muscles was conventionally difficult. This study aimed to examine the association of LBP with muscle stiffness assessed using ultrasonic shear wave elastography (SWE) and muscle mass of the lumbar back muscle, and spinal alignment in young and middle-aged medical workers. The study comprised 23 asymptomatic medical workers [control (CTR) group] and 9 medical workers with LBP (LBP group). Muscle stiffness and mass of the lumbar back muscles (lumbar erector spinae, multifidus, and quadratus lumborum) in the prone position were measured using ultrasonic SWE. Sagittal spinal alignment in the standing and prone positions was measured using a Spinal Mouse. The association with LBP was investigated by multiple logistic regression analysis with a forward selection method. The analysis was conducted using the shear elastic modulus and muscle thickness of the lumbar back muscles, and spinal alignment, age, body height, body weight, and sex as independent variables. Multiple logistic regression analysis showed that muscle stiffness of the lumbar multifidus muscle and body height were significant and independent determinants of LBP, but that muscle mass and spinal alignment were not. Muscle stiffness of the lumbar multifidus muscle in the LBP group was significantly higher than that in the CTR group. The results of this study suggest that LBP is associated with muscle stiffness of the lumbar multifidus muscle in young and middle-aged medical workers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prevalence and of smoking and associated factors among Malaysian University students.

PubMed

Al-Naggar, Redhwan Ahmed; Al-Dubai, Sami Abdo Radman; Al-Naggar, Thekra Hamoud; Chen, Robert; Al-Jashamy, Karim

2011-01-01

The objectives were to determine the prevalence and associated factors for smoking among university students in Malaysia. A cross-sectional study was conducted among 199 students in the period from December of academic year 2009 until April of academic year 2010 in Management and Science University (MSU), Shah Alam, Selangor, Malaysia. The questionnaire was distributed randomly to all faculties of MSU by choosing one of every 3 lecture rooms, as well as the library and cafeterias of the campus randomly by choosing one from every 3 tables. Questions concerned socio-demographic variables, knowledge, attitudes and practice toward smoking. Participant's consent was obtained and ethical approval was provided by the ethics committee of the University. Data entry and analysis were performed using descriptive statistics, chi square test, Student t- test and logistic multiple regression with the SPSS version 13.0, statistical significance being concluded at p < 0.05. About one third of students were smokers (29%). The most important reason of smoking was stress (20%) followed by 'influenced by friends' (16 %). Prevalence of smoking was significantly higher among male and those in advanced semesters (p = >0.001, p = 0.047). Smokers had low level of knowledge (p < 0.05), had wrong beliefs on smoking (p < 0.05), and negative attitude toward tobacco control policies compared to non smokers (p < 0.05). On multiple logistic regression, significant predictors of smoking in the model were gender (p = 0.025), age (p = 0.037), semester of study (p = 0.025) and attitude toward smoking (p < 0.001). This study found that 29% of university students were smokers. Males and students in advanced semesters were more likely to smoke. The results provide baseline data to develop an anti-smoking program to limit smoking in the university by implementing policies against smoking.

Predictors of long length of stay in infants hospitalized with urinary tract infection.

PubMed

McMullen, Janet A; Mahant, Sanjay; DeGroot, Julie M; Stephens, Derek; Parkin, Patricia C

2014-09-01

Urinary tract infection (UTI) is the most common serious bacterial infection in infants. To use resources optimally, factors contributing to costs through length of stay (LOS) must be identified. This study sought to identify clinical and health system factors associated with long LOS in infants with UTI. Using a case-control design, we included infants <6 months old hospitalized with UTI. Cases had LOS ≥96 hours; controls had LOS <96 hours. Clinical and health system variables were extracted from medical records. Cases and controls were compared by using comparative statistics and multiple logistic regression analysis. Cases (n = 71) and controls (n = 71) did not differ by gender; cases were more likely to be younger (4.2 vs 7.1 weeks, P = .04), born preterm (13% vs 3%, P = .03), have known genitourinary disease (17% vs 4%, P = .01), an ultrasound (85% vs 68%, P = .02) or voiding cystourethrogram (VCUG) (61% vs 34%, P = .001) ordered, longer wait for VCUG (53 vs 27 hours, P = .002), consult requested (54% vs 10%, P < .001), and longer duration of intravenous (IV) antibiotics (125 vs 62 hours, P < .001). Multiple logistic regression demonstrated that cases were more likely to be premature (odds ratio [OR] 7.6), have known genitourinary disease (OR 7.3), and have VCUG ordered in the hospital (OR 4.5). Infants who are older, are born full term, have no genitourinary disease, receive shorter courses of IV antibiotics, and do not have a VCUG ordered have shorter stays and may be eligible for a short-stay unit. Earlier transition to oral antibiotics and delayed ordering of a VCUG may decrease LOS. Copyright © 2014 by the American Academy of Pediatrics.

Coronary calcium in systemic lupus erythematosus is associated with traditional cardiovascular risk factors, but not with disease activity.

PubMed

Kiani, Adnan N; Magder, Laurence; Petri, Michelle

2008-07-01

Cardiovascular disease is a major cause of morbidity and mortality in systemic lupus erythematosus (SLE). The frequency of both subclinical and clinically evident atherosclerosis is greatly increased over healthy controls. We assessed cardiovascular risk factors present in patients with SLE at the baseline visit in a statin intervention trial and their correlation with coronary calcium. Coronary calcium was measured by helical computed tomography (continuous volumetric data acquisition in a single breath-hold) in 200 patients with SLE enrolled in the Lupus Atherosclerosis Prevention Study. Patients had a mean age of 44.3 +/- 11.4 years and were 92% women, 61% Caucasian, 34% African American, 2% Asian, and 2% Hispanic. Coronary calcium was found in 43%. In univariate analysis, coronary calcification was associated with age (p = 0.0001), hypertension (p = 0.0008), body mass index (BMI; p = 0.03), erythrocyte sedimentation rate (ESR; p = 0.03), anti-dsDNA (p = 0.067), and lipoprotein(a) (p = 0.03). Homocysteine (p = 0.050), high-sensitivity C-reactive protein (hsCRP; p = 0.053), and LDL (p = 0.048) had a stronger association when considered as quantitative predictors. In a multiple logistic regression model, only age (p 100. Based on a multiple logistic regression model, only age (p = 0.0017) and diabetes mellitus (p = 0.019) remained significant independent predictors of coronary calcium > 100. Inflammation, measured as ESR or hsCRP, is associated with coronary calcium only in univariate analyses. Age, BMI, and diabetes mellitus are more important associates of coronary calcium in SLE than inflammatory markers and SLE clinical activity.

Gender differences in hypertension control among older korean adults: Korean social life, health, and aging project.

PubMed

Chu, Sang Hui; Baek, Ji Won; Kim, Eun Sook; Stefani, Katherine M; Lee, Won Joon; Park, Yeong-Ran; Youm, Yoosik; Kim, Hyeon Chang

2015-01-01

Controlling blood pressure is a key step in reducing cardiovascular mortality in older adults. Gender differences in patients' attitudes after disease diagnosis and their management of the disease have been identified. However, it is unclear whether gender differences exist in hypertension management among older adults. We hypothesized that gender differences would exist among factors associated with hypertension diagnosis and control among community-dwelling, older adults. This cross-sectional study analyzed data from 653 Koreans aged ≥60 years who participated in the Korean Social Life, Health, and Aging Project. Multiple logistic regression was used to compare several variables between undiagnosed and diagnosed hypertension, and between uncontrolled and controlled hypertension. Diabetes was more prevalent in men and women who had uncontrolled hypertension than those with controlled hypertension or undiagnosed hypertension. High body mass index was significantly associated with uncontrolled hypertension only in men. Multiple logistic regression analysis indicated that in women, awareness of one's blood pressure level (odds ratio [OR], 2.86; p=0.003) and the number of blood pressure checkups over the previous year (OR, 1.06; p=0.011) might influence the likelihood of being diagnosed with hypertension. More highly educated women were more likely to have controlled hypertension than non-educated women (OR, 5.23; p=0.013). This study suggests that gender differences exist among factors associated with hypertension diagnosis and control in the study population of community-dwelling, older adults. Education-based health promotion strategies for hypertension control might be more effective in elderly women than in elderly men. Gender-specific approaches may be required to effectively control hypertension among older adults.

Relationship Between Visceral Infarction and Ischemic Stroke Subtype.

PubMed

Finn, Caitlin; Hung, Peter; Patel, Praneil; Gupta, Ajay; Kamel, Hooman

2018-03-01

Most cryptogenic strokes are thought to have an embolic source. We sought to determine whether cryptogenic strokes are associated with visceral infarcts, which are usually embolic. Among patients prospectively enrolled in CAESAR (Cornell Acute Stroke Academic Registry), we selected those with a contrast-enhanced abdominal computed tomographic scan within 1 year of admission. Our exposure variable was adjudicated stroke subtype per the Trial of ORG 10172 in Acute Stroke Treatment classification. Our outcome was renal or splenic infarction as assessed by a single radiologist blinded to stroke subtype. We used Fisher exact test and multiple logistic regression to compare the prevalence of visceral infarcts among cardioembolic strokes, strokes of undetermined etiology, and noncardioembolic strokes (large- or small-vessel strokes). Among 227 patients with ischemic stroke and a contrast-enhanced abdominal computed tomographic scan, 59 had a visceral infarct (35 renal and 27 splenic). The prevalence of visceral infarction was significantly different among cardioembolic strokes (34.2%; 95% confidence interval [CI], 23.7%-44.6%), strokes of undetermined etiology (23.9%; 95% CI, 15.0%-32.8%), and strokes from large-artery atherosclerosis or small-vessel occlusion (12.5%; 95% CI, 1.8%-23.2%; P =0.03). In multiple logistic regression models adjusted for demographics and vascular comorbidities, we found significant associations with visceral infarction for both cardioembolic stroke (odds ratio, 3.5; 95% CI, 1.2-9.9) and stroke of undetermined source (odds ratio, 3.3; 95% CI, 1.1-10.5) as compared with noncardioembolic stroke. The prevalence of visceral infarction differed significantly across ischemic stroke subtypes. Cardioembolic and cryptogenic strokes were associated with a higher prevalence of visceral infarcts than noncardioembolic strokes. © 2018 American Heart Association, Inc.

High Prevalence of Post-Traumatic Stress Symptoms in Relation to Social Factors in Affected Population One Year after the Fukushima Nuclear Disaster.

PubMed

Tsujiuchi, Takuya; Yamaguchi, Maya; Masuda, Kazutaka; Tsuchida, Marisa; Inomata, Tadashi; Kumano, Hiroaki; Kikuchi, Yasushi; Augusterfer, Eugene F; Mollica, Richard F

2016-01-01

This study investigated post-traumatic stress symptoms in relation to the population affected by the Fukushima Nuclear Disaster, one year after the disaster. Additionally, we investigated social factors, such as forced displacement, which we hypothesize contributed to the high prevalence of post-traumatic stress. Finally, we report of written narratives that were collected from the impacted population. Using the Impact of Event Scale-Revised (IES-R), questionnaires were sent to 2,011 households of those displaced from Fukushima prefecture living temporarily in Saitama prefecture. Of the 490 replies; 350 met the criteria for inclusion in the study. Multiple logistic regression analysis was performed to examine several characteristics and variables of social factors as predictors of probable post-traumatic stress disorder, PTSD. The mean score of IES-R was 36.15±21.55, with 59.4% having scores of 30 or higher, thus indicating a probable PTSD. No significant differences in percentages of high-risk subjects were found among sex, age, evacuation area, housing damages, tsunami affected, family split-up, and acquaintance support. By the result of multiple logistic regression analysis, the significant predictors of probable PTSD were chronic physical diseases (OR = 1.97), chronic mental diseases (OR = 6.25), worries about livelihood (OR = 2.27), lost jobs (OR = 1.71), lost social ties (OR = 2.27), and concerns about compensation (OR = 3.74). Although there are limitations in assuming a diagnosis of PTSD based on self-report IES-R, our findings indicate that there was a high-risk of PTSD strongly related to the nuclear disaster and its consequent evacuation and displacement. Therefore, recovery efforts must focus not only on medical and psychological treatment alone, but also on social and economic issues related to the displacement, as well.

Principal component analysis of early alcohol, drug and tobacco use with major depressive disorder in US adults.

PubMed

Wang, Kesheng; Liu, Ying; Ouedraogo, Youssoufou; Wang, Nianyang; Xie, Xin; Xu, Chun; Luo, Xingguang

2018-05-01

Early alcohol, tobacco and drug use prior to 18 years old are comorbid and correlated. This study included 6239 adults with major depressive disorder (MDD) in the past year and 72,010 controls from the combined data of 2013 and 2014 National Survey on Drug Use and Health (NSDUH). To deal with multicollinearity existing among 17 variables related to early alcohol, tobacco and drug use prior to 18 years old, we used principal component analysis (PCA) to infer PC scores and then use weighted multiple logistic regression analyses to estimate the associations of potential factors and PC scores with MDD. The odds ratios (ORs) with 95% confidence intervals (CIs) were estimated. The overall prevalence of MDD was 6.7%. The first four PCs could explain 57% of the total variance. Weighted multiple logistic regression showed that PC 1 (a measure of psychotherapeutic drugs and illicit drugs other than marijuana use), PC 2 (a measure of cocaine and hallucinogens), PC 3 (a measure of early alcohol, cigarettes, and marijuana use), and PC 4 (a measure of cigar, smokeless tobacco use and illicit drugs use) revealed significant associations with MDD (OR = 1.12, 95% CI = 1.08-1.16, OR = 1.08, 95% CI = 1.04-1.12, OR = 1.13, 95% CI = 1.07-1.18, and OR = 1.15, 95% CI = 1.09-1.21, respectively). In conclusion, PCA can be used to reduce the indicators in complex survey data. Early alcohol, tobacco and drug use prior to 18 years old were found to be associated with increased odds of adult MDD. Copyright © 2018 Elsevier Ltd. All rights reserved.

Social support and amphetamine-type stimulant use among female sex workers in China.

PubMed

Zhao, Qun; Mao, Yuchen; Li, Xiaoming; Zhou, Yuejiao; Shen, Zhiyong

2017-10-01

Existing research has suggested a positive role of social support in reducing drug use among female sex workers (FSWs). However, there is limited research on the role of social support in amphetamine-type stimulant (ATS) use among FSWs in China. This study explored the present situation of ATS use among FSWs in Guangxi, China and examined the associations of different types of social support from different sources with ATS use. A sample of 1022 FSWs was recruited from 56 commercial sex venues in Guangxi Autonomous Region in China. Bivariate comparison was used to compare demographic characteristics and source of emotional or tangible social support across frequency of ATS use among FSWs. The relationship between social support and ATS use was examined using multiple ordinal logistic regression models controlling for the potential confounding effects of demographic variables. The multiple ordinal logistic regression indicated that FSWs who were from younger age groups (aOR = 10.88 for age group <20; aOR = 2.80 for age group 20-23), and from all higher-income venues (aOR = 1.96 for venue level 1; aOR = 2.28 for venue level 2; aOR = 1.81 for venue level 3) tended to use ATS more frequently. They also tended to use ATS more frequently when they depended on their boyfriends (aOR = 1.08) for emotional support or on their co-workers for tangible support (aOR = 1.17). Different types of social support from different sources can be either positively or negatively associated with ATS use among FSWs, therefore, the future intervention efforts should differentiate and target different types and different sources of social support in response to the living and work conditions of FSWs.

Symptom clusters and treatment time delay in Korean patients with ST-elevation myocardial infarction on admission.

PubMed

Kim, Hee-Sook; Eun, Sang Jun; Hwang, Jin Yong; Lee, Kun-Sei; Cho, Sung-Il

2018-05-01

Most patients with acute myocardial infarction (AMI) experience more than one symptom at onset. Although symptoms are an important early indicator, patients and physicians may have difficulty interpreting symptoms and detecting AMI at an early stage. This study aimed to identify symptom clusters among Korean patients with ST-elevation myocardial infarction (STEMI), to examine the relationship between symptom clusters and patient-related variables, and to investigate the influence of symptom clusters on treatment time delay (decision time [DT], onset-to-balloon time [OTB]). This was a prospective multicenter study with a descriptive design that used face-to-face interviews. A total of 342 patients with STEMI were included in this study. To identify symptom clusters, two-step cluster analysis was performed using SPSS software. Multinomial logistic regression to explore factors related to each cluster and multiple logistic regression to determine the effect of symptom clusters on treatment time delay were conducted. Three symptom clusters were identified: cluster 1 (classic MI; characterized by chest pain); cluster 2 (stress symptoms; sweating and chest pain); and cluster 3 (multiple symptoms; dizziness, sweating, chest pain, weakness, and dyspnea). Compared with patients in clusters 2 and 3, those in cluster 1 were more likely to have diabetes or prior MI. Patients in clusters 2 and 3, who predominantly showed other symptoms in addition to chest pain, had a significantly shorter DT and OTB than those in cluster 1. In conclusion, to decrease treatment time delay, it seems important that patients and clinicians recognize symptom clusters, rather than relying on chest pain alone. Further research is necessary to translate our findings into clinical practice and to improve patient education and public education campaigns.

Logistic Regression Likelihood Ratio Test Analysis for Detecting Signals of Adverse Events in Post-market Safety Surveillance.

PubMed

Nam, Kijoeng; Henderson, Nicholas C; Rohan, Patricia; Woo, Emily Jane; Russek-Cohen, Estelle

2017-01-01

The Vaccine Adverse Event Reporting System (VAERS) and other product surveillance systems compile reports of product-associated adverse events (AEs), and these reports may include a wide range of information including age, gender, and concomitant vaccines. Controlling for possible confounding variables such as these is an important task when utilizing surveillance systems to monitor post-market product safety. A common method for handling possible confounders is to compare observed product-AE combinations with adjusted baseline frequencies where the adjustments are made by stratifying on observable characteristics. Though approaches such as these have proven to be useful, in this article we propose a more flexible logistic regression approach which allows for covariates of all types rather than relying solely on stratification. Indeed, a main advantage of our approach is that the general regression framework provides flexibility to incorporate additional information such as demographic factors and concomitant vaccines. As part of our covariate-adjusted method, we outline a procedure for signal detection that accounts for multiple comparisons and controls the overall Type 1 error rate. To demonstrate the effectiveness of our approach, we illustrate our method with an example involving febrile convulsion, and we further evaluate its performance in a series of simulation studies.

Handling nonresponse in surveys: analytic corrections compared with converting nonresponders.

PubMed

Jenkins, Paul; Earle-Richardson, Giulia; Burdick, Patrick; May, John

2008-02-01

A large health survey was combined with a simulation study to contrast the reduction in bias achieved by double sampling versus two weighting methods based on propensity scores. The survey used a census of one New York county and double sampling in six others. Propensity scores were modeled as a logistic function of demographic variables and were used in conjunction with a random uniform variate to simulate response in the census. These data were used to estimate the prevalence of chronic disease in a population whose parameters were defined as values from the census. Significant (p < 0.0001) predictors in the logistic function included multiple (vs. single) occupancy (odds ratio (OR) = 1.3), bank card ownership (OR = 2.1), gender (OR = 1.5), home ownership (OR = 1.3), head of household's age (OR = 1.4), and income >$18,000 (OR = 0.8). The model likelihood ratio chi-square was significant (p < 0.0001), with the area under the receiver operating characteristic curve = 0.59. Double-sampling estimates were marginally closer to population values than those from either weighting method. However, the variance was also greater (p < 0.01). The reduction in bias for point estimation from double sampling may be more than offset by the increased variance associated with this method.

Variation in the prevalence of chronic bronchitis among smokers: a cross-sectional study.

PubMed

Mahesh, P A; Jayaraj, B S; Chaya, S K; Lokesh, K S; McKay, A J; Prabhakar, A K; Pape, U J

2014-07-01

Given the wide variations in prevalence of chronic obstructive pulmonary disease observed between populations with similar levels of exposure to tobacco smoke, we aimed to investigate the possibility of variations in prevalence of chronic bronchitis (CB) between two geographically distinct smoking populations in rural Karnataka, India. The Burden of Obstructive Lung Disease (BOLD) questionnaire was administered to all men aged >30 years in a cross-sectional survey. The χ(2) and Fisher's exact tests were used to compare CB prevalence in the two populations. Logistic regression was used to analyse the impact of multiple variables on the occurrence of CB. Two samples of 2322 and 2182 subjects were included in the study. In non-smokers, CB prevalence did not differ between the populations. However, it was significantly different between smoking populations (44.79% vs. 2.13%, P < 0.0001). Logistic regression indicated that, in addition to smoking, region, age, occupational dust exposure and type of house were associated with higher likelihood of CB. An interaction between smoking and area of residence was found (P < 0.001) and appeared to explain the effect of region (without interaction). A significant difference in CB prevalence was observed between male populations from two areas of Karnataka state, including when stratified by smoking status. No significant difference was observed between non-smokers.

Household food security status in the Northeast of Iran: a cross-sectional study.

PubMed

Gholami, Ali; Foroozanfar, Zohre

2015-01-01

An important issue the world faces today is ensuring that households living in different countries have access to enough food to maintain a healthy life. Food insecurity is prevalent in both developed and developing countries. The objective of this study was to assess the household food security status and related factors among different rural districts of Neyshabur (A city in northeast of Iran). Of 5000 selected rural households 4647 were studied in this cross-sectional study. A validated short questionnaire (with six questions) was used to measure food security. Chi-square test and logistic regression were used for data analysis through SPSS software. In total, 2747 households (59.1%) were identified as food secure. The highest prevalence of food security was observed in Central district (62.3%) and the lowest was in Miyanjolgeh district (52.9%). Backward multiple logistic regression revealed that car ownership, presence of chronic disease in household and household income (per month) were significantly associated with food security in all of surveyed districts (p< 0.05). According to results of this study, lower than 60% of Neyshabur rural households were food secure and economic variables were the most important factors. Therefore, a special attention should be paid to this health problem in these regions.

Coffee agroforestry for sustainability of Upper Sekampung Watershed management

NASA Astrophysics Data System (ADS)

Fitriani; Arifin, Bustanul; Zakaria, Wan Abbas; Hanung Ismono, R.

2018-03-01

The main objective of watershed management is to ensure the optimal hydrological and natural resource use for ecological, social and economic importance. One important adaptive management step in dealing with the risk of damage to forest ecosystems is the practice of agroforestry coffee. This study aimed to (1) assess the farmer's response to ecological service responsibility and (2) analyze the Sekampung watersheds management by providing environmental services. The research location was Air Naningan sub-district, Tanggamus, Lampung Province, Indonesia. The research was conducted from July until November 2016. Stratification random sampling based on the pattern of ownership of land rights is used to determine the respondents. Data were analyzed using descriptive statistics and logistic regression analysis. Based on the analysis, it was concluded that coffee farmers' participation in the practice of coffee agroforestry in the form of 38% shade plants and multiple cropping (62%). The logistic regression analysis indicated that the variables of experience and status of land ownership, and incentive-size plans were able to explain variations in the willingness of coffee growers to follow the scheme of providing environmental services. The existence of farmer with partnership and CBFM scheme on different land tenure on upper Sekampung has a strategic position to minimize the deforestation and recovery watersheds destruction.

Profiling healthy eaters. Determining factors that predict healthy eating practices among Dutch adults.

PubMed

Swan, Emily; Bouwman, Laura; Hiddink, Gerrit Jan; Aarts, Noelle; Koelen, Maria

2015-06-01

Research has identified multiple factors that predict unhealthy eating practices. However what remains poorly understood are factors that promote healthy eating practices. This study aimed to determine a set of factors that represent a profile of healthy eaters. This research applied Antonovsky's salutogenic framework for health development to examine a set of factors that predict healthy eating in a cross-sectional study of Dutch adults. Data were analyzed from participants (n = 703) who completed the study's survey in January 2013. Logistic regression analysis was performed to test the association of survey factors on the outcome variable high dietary score. In the multivariate logistic regression model, five factors contributed significantly (p < .05) to the predictive ability of the overall model: being female; living with a partner; a strong sense of coherence (construct from the salutogenic framework), flexible restraint of eating, and self-efficacy for healthy eating. Findings complement what is already known of the factors that relate to poor eating practices. This can provide nutrition promotion with a more comprehensive picture of the factors that both support and hinder healthy eating practices. Future research should explore these factors to better understand their origins and mechanisms in relation to healthy eating practices. Copyright © 2015 Elsevier Ltd. All rights reserved.

Striatal dopamine transporter binding for predicting the development of delayed neuropsychological sequelae in suicide attempters by carbon monoxide poisoning: A SPECT study.

PubMed

Yang, Kai-Chun; Ku, Hsiao-Lun; Wu, Chia-Liang; Wang, Shyh-Jen; Yang, Chen-Chang; Deng, Jou-Fang; Lee, Ming-Been; Chou, Yuan-Hwa

2011-12-30

Carbon monoxide poisoning (COP) after charcoal burning results in delayed neuropsychological sequelae (DNS), which show clinical resemblance to Parkinson's disease, without adequate predictors at present. This study examined the role of dopamine transporter (DAT) binding for the prediction of DNS. Twenty-seven suicide attempters with COP were recruited. Seven of them developed DNS, while the remainder did not. The striatal DAT binding was measured by single photon emission computed tomography with (99m)Tc-TRODAT. The specific uptake ratio was derived based on a ratio equilibrium model. Using a logistic regression model, multiple clinical variables were examined as potential predictors for DNS. COP patients with DNS had a lower binding on left striatal DAT binding than patients without DNS. Logistic regression analysis showed that a combination of initial loss of consciousness and lower left striatal DAT binding predicted the development of DNS. Our data indicate that the left striatal DAT binding could help to predict the development of DNS. This finding not only demonstrates the feasibility of brain imaging techniques for predicting the development of DNS but will also help clinicians to improve the quality of care for COP patients. 2011 Elsevier Ireland Ltd. All rights reserved.

Systemic disease manifestations associated with epilepsy in tuberous sclerosis complex.

PubMed

Jeong, Anna; Wong, Michael

2016-09-01

Epilepsy is one of the most disabling symptoms of tuberous sclerosis complex (TSC) and is a leading cause of morbidity and mortality in affected individuals. The relationship between systemic disease manifestations and the presence of epilepsy has not been thoroughly investigated. This study utilizes a multicenter TSC Natural History Database including 1,816 individuals to test the hypothesis that systemic disease manifestations of TSC are associated with epilepsy. Univariate analysis was used to identify patient characteristics (e.g., age, gender, race, and TSC mutation status) associated with the presence of epilepsy. Individual logistic regression models were built to examine the association between epilepsy and each candidate systemic or neurologic disease variable, controlling for the patient characteristics found to be significant on univariate analysis. Finally, a multivariable logistic regression model was constructed, using the variables found to be significant on the individual analyses as well as the patient characteristics that were significant on univariate analysis. Nearly 88% of our cohort had a history of epilepsy. After adjusting for age, gender, and TSC mutation status, multiple systemic disease manifestations including cardiac rhabdomyomas (odds ratio [OR] 2.3, 95% confidence interval [CI] 1.3-3.9, p = 0.002), retinal hamartomas (OR 2.1, CI 1.0-4.3, p = 0.04), renal cysts (OR 2.1, CI 1.3-3.4, p = 0.002), renal angiomyolipomas (OR 3.0, CI 1.8-5.1, p < 0.001), shagreen patches (OR 1.7, CI 1.0-2.7, p = 0.04), and facial angiofibromas (OR 1.7, CI 1.1-2.9, p = 0.03) were associated with a higher likelihood of epilepsy. In the multivariable logistic regression model, cardiac rhabdomyomas (OR 1.9, CI 1.0-3.5, p = 0.04) remained significantly associated with the presence of epilepsy. The identification of systemic disease manifestations such as cardiac rhabdomyomas that confer a higher risk of epilepsy development in TSC could contribute to disease prognostication and assist in the identification of individuals who may receive maximal benefit from potentially novel, targeted, preventative therapies. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Multivariate analysis on unilateral cleft lip and palate treatment outcome by EUROCRAN index: A retrospective study.

PubMed

Yew, Ching Ching; Alam, Mohammad Khursheed; Rahman, Shaifulizan Abdul

2016-10-01

This study is to evaluate the dental arch relationship and palatal morphology of unilateral cleft lip and palate patients by using EUROCRAN index, and to assess the factors that affect them using multivariate statistical analysis. A total of one hundred and seven patients from age five to twelve years old with non-syndromic unilateral cleft lip and palate were included in the study. These patients have received cheiloplasty and one stage palatoplasty surgery but yet to receive alveolar bone grafting procedure. Five assessors trained in the use of the EUROCRAN index underwent calibration exercise and ranked the dental arch relationships and palatal morphology of the patients' study models. For intra-rater agreement, the examiners scored the models twice, with two weeks interval in between sessions. Variable factors of the patients were collected and they included gender, site, type and, family history of unilateral cleft lip and palate; absence of lateral incisor on cleft side, cheiloplasty and palatoplasty technique used. Associations between various factors and dental arch relationships were assessed using logistic regression analysis. Dental arch relationship among unilateral cleft lip and palate in local population had relatively worse scoring than other parts of the world. Crude logistics regression analysis did not demonstrate any significant associations among the various socio-demographic factors, cheiloplasty and palatoplasty techniques used with the dental arch relationship outcome. This study has limitations that might have affected the results, example: having multiple operators performing the surgeries and the inability to access the influence of underlying genetic predisposed cranio-facial variability. These may have substantial influence on the treatment outcome. The factors that can affect unilateral cleft lip and palate treatment outcome is multifactorial in nature and remained controversial in general. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Factors associated with the implementation of programs for drug abuse prevention in schools

PubMed Central

Pereira, Ana Paula Dias; Paes, Ângela Tavares; Sanchez, Zila M

2016-01-01

ABSTRACT OBJECTIVE To analyze if characteristics of managers, schools, and curriculum are associated with the implementation of programs for drug abuse prevention in elementary and high schools. METHODS Cross-sectional study, with random sample of 263 school managers. Data were collected between 2012 and 2013 by a program that sends forms via internet. A closed self-filling questionnaire was applied online. Statistical analysis included Chi-square tests and logistic regression models. The outcome variable was the presence of program for drug abuse prevention inserted in the daily life and educational program of the school. The explanatory variables were divided into: demographic data of the manager; characteristics of the school and of the curriculum; health education; and drug use in the school. RESULTS We found that 42.5% (95%CI 36.1–49.1) of the evaluated schools had programs for drug abuse prevention. With the multiple logistic regression model, we observed that the more time the manager has worked with education, the chance of the school having a program increased at about 4.0%. Experimenting with innovative teaching techniques also increased at about six times the chance of the school developing a program for drug abuse prevention. The difficulties in the implementation of the programs were more present in state and municipal schools, when compared with private schools, due to, for instance: lack of teaching materials, lack of money, and competing demands for teaching other subjects. CONCLUSIONS The implementation of programs for drug abuse prevention in the city of Sao Paulo is associated with the experience of the manager in education and with the teaching strategies of the school. PMID:27509010

Prevalence and risk factors of childbirth-related post-traumatic stress symptoms.

PubMed

Modarres, Maryam; Afrasiabi, Sedigheh; Rahnama, Parvin; Montazeri, Ali

2012-09-03

There is evidence that traumatic birth experiences are associated with psychological impairments. This study aimed to estimate the prevalence of childbirth-related post-traumatic stress symptoms and its obstetric and perinatal risk factors among a sample of Iranian women. This was a cross-sectional study carried out in Bushehr, Iran during a 3-months period from July to September 2009. Data were collected from all women attending eleven healthcare centers for postnatal care 6 to 8 weeks after childbirth. Those who had a traumatic delivery were identified and entered into the study. In order to assess childbirth-related post-traumatic stress, the Post-traumatic Symptom Scale-Interview (PSS-I) was administered. Data on demographic, obstetric and perinatal characteristics also were collected. Multivariate logistic regression was performed to examine the association between childbirth-related post-traumatic stress and demographic and obstetric and perinatal variables. In all, 400 women were initially evaluated. Of these, 218 women (54.5%) had a traumatic delivery and overall, 80 women (20%) were found to be suffering from post-partum post-traumatic stress disorder (PTSD). Multiple logistic regression analysis revealed that post-partum PTSD was associated with educational level, gestational age at delivery, number of prenatal care visits, pregnancy complications, pregnancy intervals, labor duration, and mode of delivery. The findings indicated that the prevalence of traumatic birth experiences and post-partum PTSD were relatively high among Iranian women. The findings also indicated that obstetric and perinatal variables were independently the most significant contributing factors to women's post-partum PTSD. It seems that a better perinatal care and supportive childbirth might help to reduce the burden of post-partum PTSD among this population.

Characterizing job satisfaction and intent to leave among nationally registered emergency medical technicians: an analysis of the 2005 LEADS survey.

PubMed

Patterson, P Daniel; Moore, Charity G; Sanddal, Nels D; Wingrove, Gary; LaCroix, Brian

2009-01-01

The primary purpose of this study was to characterize job satisfaction with opportunities for advancement, job satisfaction with pay and benefits, and intent to leave the EMS profession among Nationally Registered EMT-Basics and EMT-Paramedics. A secondary data analysis was performed on the National Registry of EMTs Longitudinal Emergency Medical Technician Attributes and Demographic Study Project (LEADS) 2005 core survey. We used chi-square and multiple logistic regression analyses to test for differences in job satisfaction with opportunities for advancement, job satisfaction with pay and benefits, and intent to leave the EMS profession across years of experience and work location. Among 11 measures of job satisfaction, NREMT-Basics and NREMT-Paramedics were least satisfied with opportunities for advancement and pay and benefits (67.8 and 55.2%, respectively). Nearly 6% of respondents reported intentions of leaving the profession within 12 months. In univariate analyses, job satisfaction with advancement opportunities varied across years of experience and work location. Job satisfaction with pay and benefits varied across years of experience and work location. The proportion reporting intentions of leaving the profession did not vary across the two independent variables of interest. In multivariable logistic regression, statistical differences observed in univariate analyses were attenuated to non-significance across all outcome models. Income, personal health, level of EMS certification, and type of EMS work were significant in several outcome models. EMS workforce research is at its infancy, thus our study adds to a limited but growing body of knowledge. In future and replicated research, one will need to consider different person and organizational variables in predicting different measures of job satisfaction among EMS personnel.

Health assessment questionnaire score is the best predictor of 5-year quality of life in early rheumatoid arthritis.

PubMed

Cohen, Jean-David; Dougados, Maxime; Goupille, Philippe; Cantagrel, Alain; Meyer, Olivier; Sibilia, Jean; Daurès, Jean-Pierre; Combe, Bernard

2006-10-01

To evaluate and determine prognostic factors of 5-year quality of life in patients with early rheumatoid arthritis (RA). A cohort of 191 patients with RA and disease duration < 1 year was prospectively followed over 5 years. The outcome measure was quality of life as assessed by the Arthritis Impact Measurement Scales 2 (AIMS2). Univariate analysis, then stepwise multiple logistic regression, was used to find independent baseline prognostic variables. After accounting for death, loss of followup, and missing data, 158 patients (82.72%) were included in the analysis. The mean AIMS2 physical, symptom, psychological, social interaction, and work scores after 5 years were 1.6 (range 0-6.88), 4.0 (0-10), 3.48 (0-9.22), 4.06 (0-8.69), and 1.87 (0-8.13), respectively. The AIMS2 physical component was significantly correlated with Health Assessment Questionnaire (HAQ) score at 5 years. Logistic regression analysis revealed that the baseline values able to predict the 5-year physical, psychological, symptom, social interaction, and work status were, respectively: HAQ score and erythrocyte sedimentation rate (ESR), body mass index (BMI), HAQ; erosion score and sex, HAQ; ESR and anti-perinuclear antibody; matrix metalloproteinase-3 (MMP3) level, joint space narrowing, and tender joint scores; HAQ score and age. The multidimensional structure of the AIMS2 allowed us to assess the 5-year health-related quality of life in early RA. Using this instrument as an outcome variable, prognostic factors were selected and varied widely depending on the evaluated domain. The baseline HAQ score was the best predictive factor of 4 of the 5 domains of the AIMS2.

Direct and indirect associations between the family physical activity environment and sports participation among 10-12 year-old European children: testing the EnRG framework in the ENERGY project.

PubMed

Timperio, Anna F; van Stralen, Maartje M; Brug, Johannes; Bere, Elling; Chinapaw, Mai J M; De Bourdeaudhuij, Ilse; Jan, Nataša; Maes, Lea; Manios, Yannis; Moreno, Luis A; Salmon, Jo; Te Velde, Saskia J

2013-02-03

Sport participation makes an important contribution to children's overall physical activity. Understanding influences on sports participation is important and the family environment is considered key, however few studies have explored the mechanisms by which the family environment influences children's sport participation. The purpose of this study was to examine whether attitude, perceived behavioural control, health belief and enjoyment mediate associations between the family environment and 10-12 year-old children's sports participation. Children aged 10-12 years ( = 7,234) and one of their parents (n = 6,002) were recruited from 175 schools in seven European countries in 2010. Children self-reported their weekly duration of sports participation, physical activity equipment items at home and the four potential mediator variables. Parents responded to items on financial, logistic and emotional support, reinforcement, modelling and co-participation in physical activity. Cross-sectional single and multiple mediation analyses were performed for 4952 children with complete data using multi-level regression analyses. Availability of equipment (OR = 1.16), financial (OR = 1.53), logistic (OR = 1.47) and emotional (OR = 1.51) support, and parental modelling (OR = 1.07) were positively associated with participation in ≥  30 mins/wk of sport. Attitude, beliefs, perceived behavioural control and enjoyment mediated and explained between 21-34% of these associations. Perceived behavioural control contributed the most to the mediated effect for each aspect of the family environment. Both direct (unmediated) and indirect (mediated) associations were found between most family environment variables and children's sports participation. Thus, family-based physical activity interventions that focus on enhancing the family environment to support children's sport participation are warranted.

One size does not fit all: an examination of low birthweight disparities among a diverse set of racial/ethnic groups.

PubMed

Johnelle Sparks, P

2009-11-01

To examine disparities in low birthweight using a diverse set of racial/ethnic categories and a nationally representative sample. This research explored the degree to which sociodemographic characteristics, health care access, maternal health status, and health behaviors influence birthweight disparities among seven racial/ethnic groups. Binary logistic regression models were estimated using a nationally representative sample of singleton, normal for gestational age births from 2001 using the ECLS-B, which has an approximate sample size of 7,800 infants. The multiple variable models examine disparities in low birthweight (LBW) for seven racial/ethnic groups, including non-Hispanic white, non-Hispanic black, U.S.-born Mexican-origin Hispanic, foreign-born Mexican-origin Hispanic, other Hispanic, Native American, and Asian mothers. Race-stratified logistic regression models were also examined. In the full sample models, only non-Hispanic black mothers have a LBW disadvantage compared to non-Hispanic white mothers. Maternal WIC usage was protective against LBW in the full models. No prenatal care and adequate plus prenatal care increase the odds of LBW. In the race-stratified models, prenatal care adequacy and high maternal health risks are the only variables that influence LBW for all racial/ethnic groups. The race-stratified models highlight the different mechanism important across the racial/ethnic groups in determining LBW. Differences in the distribution of maternal sociodemographic, health care access, health status, and behavior characteristics by race/ethnicity demonstrate that a single empirical framework may distort associations with LBW for certain racial and ethnic groups. More attention must be given to the specific mechanisms linking maternal risk factors to poor birth outcomes for specific racial/ethnic groups.

Ramsay-Curve Item Response Theory for the Three-Parameter Logistic Item Response Model

ERIC Educational Resources Information Center

Woods, Carol M.

2008-01-01

In Ramsay-curve item response theory (RC-IRT), the latent variable distribution is estimated simultaneously with the item parameters of a unidimensional item response model using marginal maximum likelihood estimation. This study evaluates RC-IRT for the three-parameter logistic (3PL) model with comparisons to the normal model and to the empirical…

Logistic regression applied to natural hazards: rare event logistic regression with replications

NASA Astrophysics Data System (ADS)

Guns, M.; Vanacker, V.

2012-06-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

Large unbalanced credit scoring using Lasso-logistic regression ensemble.

PubMed

Wang, Hong; Xu, Qingsong; Zhou, Lifeng

2015-01-01

Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data.

Development of a statistical model for the determination of the probability of riverbank erosion in a Meditteranean river basin

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil; Kourgialas, Nektarios; Karatzas, George; Giannakis, Georgios; Lilli, Maria; Nikolaidis, Nikolaos

2014-05-01

Riverbank erosion affects the river morphology and the local habitat and results in riparian land loss, damage to property and infrastructures, ultimately weakening flood defences. An important issue concerning riverbank erosion is the identification of the areas vulnerable to erosion, as it allows for predicting changes and assists with stream management and restoration. One way to predict the vulnerable to erosion areas is to determine the erosion probability by identifying the underlying relations between riverbank erosion and the geomorphological and/or hydrological variables that prevent or stimulate erosion. A statistical model for evaluating the probability of erosion based on a series of independent local variables and by using logistic regression is developed in this work. The main variables affecting erosion are vegetation index (stability), the presence or absence of meanders, bank material (classification), stream power, bank height, river bank slope, riverbed slope, cross section width and water velocities (Luppi et al. 2009). In statistics, logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable, e.g. binary response, based on one or more predictor variables (continuous or categorical). The probabilities of the possible outcomes are modelled as a function of independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. 1 = "presence of erosion" and 0 = "no erosion") for any value of the independent variables. The regression coefficients are estimated by using maximum likelihood estimation. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested (Atkinson et al. 2003). The developed statistical model is applied to the Koiliaris River Basin in the island of Crete, Greece. The aim is to determine the probability of erosion along the Koiliaris' riverbanks considering a series of independent geomorphological and/or hydrological variables. Data for the river bank slope and for the river cross section width are available at ten locations along the river. The riverbank has indications of erosion at six of the ten locations while four has remained stable. Based on a recent work, measurements for the two independent variables and data regarding bank stability are available at eight different locations along the river. These locations were used as validation points for the proposed statistical model. The results show a very close agreement between the observed erosion indications and the statistical model as the probability of erosion was accurately predicted at seven out of the eight locations. The next step is to apply the model at more locations along the riverbanks. In November 2013, stakes were inserted at selected locations in order to be able to identify the presence or absence of erosion after the winter period. In April 2014 the presence or absence of erosion will be identified and the model results will be compared to the field data. Our intent is to extend the model by increasing the number of independent variables in order to indentify the key factors favouring erosion along the Koiliaris River. We aim at developing an easy to use statistical tool that will provide a quantified measure of the erosion probability along the riverbanks, which could consequently be used to prevent erosion and flooding events. Atkinson, P. M., German, S. E., Sear, D. A. and Clark, M. J. 2003. Exploring the relations between riverbank erosion and geomorphological controls using geographically weighted logistic regression. Geographical Analysis, 35 (1), 58-82. Luppi, L., Rinaldi, M., Teruggi, L. B., Darby, S. E. and Nardi, L. 2009. Monitoring and numerical modelling of riverbank erosion processes: A case study along the Cecina River (central Italy). Earth Surface Processes and Landforms, 34 (4), 530-546. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

The comparison of landslide ratio-based and general logistic regression landslide susceptibility models in the Chishan watershed after 2009 Typhoon Morakot

NASA Astrophysics Data System (ADS)

WU, Chunhung

2015-04-01

The research built the original logistic regression landslide susceptibility model (abbreviated as or-LRLSM) and landslide ratio-based ogistic regression landslide susceptibility model (abbreviated as lr-LRLSM), compared the performance and explained the error source of two models. The research assumes that the performance of the logistic regression model can be better if the distribution of landslide ratio and weighted value of each variable is similar. Landslide ratio is the ratio of landslide area to total area in the specific area and an useful index to evaluate the seriousness of landslide disaster in Taiwan. The research adopted the landside inventory induced by 2009 Typhoon Morakot in the Chishan watershed, which was the most serious disaster event in the last decade, in Taiwan. The research adopted the 20 m grid as the basic unit in building the LRLSM, and six variables, including elevation, slope, aspect, geological formation, accumulated rainfall, and bank erosion, were included in the two models. The six variables were divided as continuous variables, including elevation, slope, and accumulated rainfall, and categorical variables, including aspect, geological formation and bank erosion in building the or-LRLSM, while all variables, which were classified based on landslide ratio, were categorical variables in building the lr-LRLSM. Because the count of whole basic unit in the Chishan watershed was too much to calculate by using commercial software, the research took random sampling instead of the whole basic units. The research adopted equal proportions of landslide unit and not landslide unit in logistic regression analysis. The research took 10 times random sampling and selected the group with the best Cox & Snell R2 value and Nagelkerker R2 value as the database for the following analysis. Based on the best result from 10 random sampling groups, the or-LRLSM (lr-LRLSM) is significant at the 1% level with Cox & Snell R2 = 0.190 (0.196) and Nagelkerke R2 = 0.253 (0.260). The unit with the landslide susceptibility value > 0.5 (≦ 0.5) will be classified as a predicted landslide unit (not landslide unit). The AUC, i.e. the area under the relative operating characteristic curve, of or-LRLSM in the Chishan watershed is 0.72, while that of lr-LRLSM is 0.77. Furthermore, the average correct ratio of lr-LRLSM (73.3%) is better than that of or-LRLSM (68.3%). The research analyzed in detail the error sources from the two models. In continuous variables, using the landslide ratio-based classification in building the lr-LRLSM can let the distribution of weighted value more similar to distribution of landslide ratio in the range of continuous variable than that in building the or-LRLSM. In categorical variables, the meaning of using the landslide ratio-based classification in building the lr-LRLSM is to gather the parameters with approximate landslide ratio together. The mean correct ratio in continuous variables (categorical variables) by using the lr-LRLSM is better than that in or-LRLSM by 0.6 ~ 2.6% (1.7% ~ 6.0%). Building the landslide susceptibility model by using landslide ratio-based classification is practical and of better performance than that by using the original logistic regression.

Computerized Classification Testing under the One-Parameter Logistic Response Model with Ability-Based Guessing

ERIC Educational Resources Information Center

Wang, Wen-Chung; Huang, Sheng-Yun

2011-01-01

The one-parameter logistic model with ability-based guessing (1PL-AG) has been recently developed to account for effect of ability on guessing behavior in multiple-choice items. In this study, the authors developed algorithms for computerized classification testing under the 1PL-AG and conducted a series of simulations to evaluate their…

A Generalized Logistic Regression Procedure to Detect Differential Item Functioning among Multiple Groups

ERIC Educational Resources Information Center

Magis, David; Raiche, Gilles; Beland, Sebastien; Gerard, Paul

2011-01-01

We present an extension of the logistic regression procedure to identify dichotomous differential item functioning (DIF) in the presence of more than two groups of respondents. Starting from the usual framework of a single focal group, we propose a general approach to estimate the item response functions in each group and to test for the presence…

Laboratory-Based Biomarkers and Liver Metastases in Metastatic Castration-Resistant Prostate Cancer.

PubMed

Cotogno, Patrick M; Ranasinghe, Lahiru K; Ledet, Elisa M; Lewis, Brian E; Sartor, Oliver

2018-04-26

Metastatic castrate-resistant prostate cancer (mCRPC) patients with liver metastases have a poor prognosis. No large studies have investigated the clinical and biochemical parameters associated with liver metastases in this population. Patient data made available via Project Data Sphere were collected from 1,281 men with mCRPC who were enrolled on to three phase III clinical trials for the treatment of their disease. Multiple logistic regression was performed on eight clinical and biochemical baseline variables to test their association with the presence of liver metastases on baseline radiographic imaging. Variables of interest included prior docetaxel exposure, Eastern Cooperative Oncology Group performance status, albumin, alkaline phosphatase, alanine transaminase, aspartate transaminase (AST), hemoglobin (HGB), lactate dehydrogenase (LDH), prostate-specific antigen, and total bilirubin. Final models were compared when treating the variables as either continuous or categorized. Multiple variable analysis demonstrated that an increasing serum AST or LDH or a decreasing HGB was associated with an increased probability of having documented radiographic liver metastases ( p  < .0001). The area under the curve for the continuous model was 0.6842 and 0.6890 for the categorical one, with the latter model containing a dichotomized AST and LDH based on the upper limit of normal and tertile ranges of HGB based on the distribution of the outcome. Our analysis demonstrated a significant association between the presence of liver metastases and laboratory levels of AST, LDH, and HGB. These have implications for patient management. More research is needed to validate these biomarkers and prospectively determine their application in the clinical setting. The purpose of this study was to evaluate biochemical and clinical biomarkers associated with the presence of liver metastases in men diagnosed with metastatic castrate-resistant prostate cancer. The results indicate that quantitative assessments of aspartate transaminase, lactate dehydrogenase, and hemoglobin are significantly associated with an increased probability of having documented radiographic liver metastases. Analysis of these simple variables can alert clinicians to those at high risk for prostate cancer that has spread to the liver, a finding of clear importance for clinical management. © AlphaMed Press 2018.

[Changes in the characteristics and incidence of multiple-injury accidents in the Navarre community over a 10-year period].

PubMed

Gradin Purroy, Carlos; Belzunegui Otano, Tomás; Bermejo Fraile, Begoña; Teijeira, Rafael; Fortún Moral, Mariano; Reyero Díez, Diego

2015-06-01

To compare morbidity and mortality rates, the epidemiologic profile, and survival of patients with multiple injuries attended by the emergency services in the Navarre autonomous community in Spain in the periods of 2002-2003 and 2010-2012. Observational analysis of 2 cohorts of accident patients with Injury Severity Scores of 15 points or more. Logistic regression was used to identify variables related to mortality. A total of 651 patients were attended in the first period; 626 were attended in the second. The annual multiple-injury incidence rate decreased from 58.1 per 100 000 population in the first period to 33.5 per 100 000 population in the second; mortality decreased from 30.3 to 15.3 per 100 000 population. The mean (SD) age was 45 (22) years in the first cohort and 52 (23) years in the second. The gender distribution (75% male) did not change. The percentage injured in traffic accidents decreased from 44% to 24%; the percentage of elderly patients hurt in falls increased from 9% to 26%. The problem of the number of young people injured in accidents in our community has been brought under control, but the proportion of older patients injured in falls has risen. This change may slow the effort to improve mortality rates in patients with multiple injuries and it obliges us to introduce measures to prevent falls in the elderly.

Application of classification tree and logistic regression for the management and health intervention plans in a community-based study.

PubMed

Teng, Ju-Hsi; Lin, Kuan-Chia; Ho, Bin-Shenq

2007-10-01

A community-based aboriginal study was conducted and analysed to explore the application of classification tree and logistic regression. A total of 1066 aboriginal residents in Yilan County were screened during 2003-2004. The independent variables include demographic characteristics, physical examinations, geographic location, health behaviours, dietary habits and family hereditary diseases history. Risk factors of cardiovascular diseases were selected as the dependent variables in further analysis. The completion rate for heath interview is 88.9%. The classification tree results find that if body mass index is higher than 25.72 kg m(-2) and the age is above 51 years, the predicted probability for number of cardiovascular risk factors > or =3 is 73.6% and the population is 322. If body mass index is higher than 26.35 kg m(-2) and geographical latitude of the village is lower than 24 degrees 22.8', the predicted probability for number of cardiovascular risk factors > or =4 is 60.8% and the population is 74. As the logistic regression results indicate that body mass index, drinking habit and menopause are the top three significant independent variables. The classification tree model specifically shows the discrimination paths and interactions between the risk groups. The logistic regression model presents and analyses the statistical independent factors of cardiovascular risks. Applying both models to specific situations will provide a different angle for the design and management of future health intervention plans after community-based study.

[A clinical study on the relationship of autonomic nervous function and arteriosclerosis in patients with essential hypertension].

PubMed

Zhao, G; Li, S H; Tan, X

2016-03-01

To investigate the relationship between autonomic nervous function and arteriosclerosis in patients with essential hypertension. From January 2011 to December 2013, a total of 269 patients with essential hypertension hospitalized in Chang'an Branch of First People's Hospital of Liangshan were divided into normal PWV group (PWV<9 m/s, n=178) and high PWV group (PWV≥9 m/s, n=91) via the results of carotid-femoral pulse wave velocity (PWV). Synchronic 24 hours ambulatory blood pressure monitoring and dynamic electrocardiogram were performed for all participants to simultaneously monitor the heart rate variability (HRV) and blood pressure variability (BPV) in these patients. Pearson single factor analysis and multivariate logistic regression analysis were performed to define the relationship between PWV and HRV, BPV respectively. The level of nHR/dHR (index of heart rate variability), 24 hour'sSSD, dSSD, nSSD (indexes of blood pressure variability) increased significantly (all P<0.05), while the level of SDANN (index of heart rate variability) decreased significantly (P<0.05) in high PWV group compared with normal PWV group. Multiple linear regression analysis showed that PWV was positively correlated with 24 hour'sSSD, 24 hour'sPP, LF, LF/HF and night/day heart rate ratio (all P<0.05). HRV (LF, LF/HF, nHR/dHR) and BPV (24 hours'SSD, dSSD, nSSD) are positively correlated to arteriosclerosis in patients with essential hypertension. Our results show that sympathetic activation and vascular injury are closely related in patients with essential hypertension.

Plaque echodensity and textural features are associated with histologic carotid plaque instability.

PubMed

Doonan, Robert J; Gorgui, Jessica; Veinot, Jean P; Lai, Chi; Kyriacou, Efthyvoulos; Corriveau, Marc M; Steinmetz, Oren K; Daskalopoulou, Stella S

2016-09-01

Carotid plaque echodensity and texture features predict cerebrovascular symptomatology. Our purpose was to determine the association of echodensity and textural features obtained from a digital image analysis (DIA) program with histologic features of plaque instability as well as to identify the specific morphologic characteristics of unstable plaques. Patients scheduled to undergo carotid endarterectomy were recruited and underwent carotid ultrasound imaging. DIA was performed to extract echodensity and textural features using Plaque Texture Analysis software (LifeQ Medical Ltd, Nicosia, Cyprus). Carotid plaque surgical specimens were obtained and analyzed histologically. Principal component analysis (PCA) was performed to reduce imaging variables. Logistic regression models were used to determine if PCA variables and individual imaging variables predicted histologic features of plaque instability. Image analysis data from 160 patients were analyzed. Individual imaging features of plaque echolucency and homogeneity were associated with a more unstable plaque phenotype on histology. These results were independent of age, sex, and degree of carotid stenosis. PCA reduced 39 individual imaging variables to five PCA variables. PCA1 and PCA2 were significantly associated with overall plaque instability on histology (both P = .02), whereas PCA3 did not achieve statistical significance (P = .07). DIA features of carotid plaques are associated with histologic plaque instability as assessed by multiple histologic features. Importantly, unstable plaques on histology appear more echolucent and homogeneous on ultrasound imaging. These results are independent of stenosis, suggesting that image analysis may have a role in refining the selection of patients who undergo carotid endarterectomy. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Prediction of thoracic injury severity in frontal impacts by selected anatomical morphomic variables through model-averaged logistic regression approach.

PubMed

Zhang, Peng; Parenteau, Chantal; Wang, Lu; Holcombe, Sven; Kohoyda-Inglis, Carla; Sullivan, June; Wang, Stewart

2013-11-01

This study resulted in a model-averaging methodology that predicts crash injury risk using vehicle, demographic, and morphomic variables and assesses the importance of individual predictors. The effectiveness of this methodology was illustrated through analysis of occupant chest injuries in frontal vehicle crashes. The crash data were obtained from the International Center for Automotive Medicine (ICAM) database for calendar year 1996 to 2012. The morphomic data are quantitative measurements of variations in human body 3-dimensional anatomy. Morphomics are obtained from imaging records. In this study, morphomics were obtained from chest, abdomen, and spine CT using novel patented algorithms. A NASS-trained crash investigator with over thirty years of experience collected the in-depth crash data. There were 226 cases available with occupants involved in frontal crashes and morphomic measurements. Only cases with complete recorded data were retained for statistical analysis. Logistic regression models were fitted using all possible configurations of vehicle, demographic, and morphomic variables. Different models were ranked by the Akaike Information Criteria (AIC). An averaged logistic regression model approach was used due to the limited sample size relative to the number of variables. This approach is helpful when addressing variable selection, building prediction models, and assessing the importance of individual variables. The final predictive results were developed using this approach, based on the top 100 models in the AIC ranking. Model-averaging minimized model uncertainty, decreased the overall prediction variance, and provided an approach to evaluating the importance of individual variables. There were 17 variables investigated: four vehicle, four demographic, and nine morphomic. More than 130,000 logistic models were investigated in total. The models were characterized into four scenarios to assess individual variable contribution to injury risk. Scenario 1 used vehicle variables; Scenario 2, vehicle and demographic variables; Scenario 3, vehicle and morphomic variables; and Scenario 4 used all variables. AIC was used to rank the models and to address over-fitting. In each scenario, the results based on the top three models and the averages of the top 100 models were presented. The AIC and the area under the receiver operating characteristic curve (AUC) were reported in each model. The models were re-fitted after removing each variable one at a time. The increases of AIC and the decreases of AUC were then assessed to measure the contribution and importance of the individual variables in each model. The importance of the individual variables was also determined by their weighted frequencies of appearance in the top 100 selected models. Overall, the AUC was 0.58 in Scenario 1, 0.78 in Scenario 2, 0.76 in Scenario 3 and 0.82 in Scenario 4. The results showed that morphomic variables are as accurate at predicting injury risk as demographic variables. The results of this study emphasize the importance of including morphomic variables when assessing injury risk. The results also highlight the need for morphomic data in the development of human mathematical models when assessing restraint performance in frontal crashes, since morphomic variables are more "tangible" measurements compared to demographic variables such as age and gender. Copyright © 2013 Elsevier Ltd. All rights reserved.

Weight reduction is not a major reason for improvement in rheumatoid arthritis from lacto-vegetarian, vegan or Mediterranean diets

PubMed Central

Sköldstam, Lars; Brudin, Lars; Hagfors, Linda; Johansson, Gunnar

2005-01-01

Objectives Several investigators have reported that clinical improvements of patients with rheumatoid arthritis (RA), from participating in therapeutic diet intervention studies, have been accompanied by loss of body weight. This has raised the question whether weight reduction per se can improve RA. In order to test this hypothesis, three previously conducted diet intervention studies, comprising 95 patients with RA, were pooled. Together with Age, Gender, and Disease Duration, change during the test period in body weight, characterised dichotomously as reduction or no reduction (dichoΔBody Weight), as well as Diet (dichotomously as ordinary diet or test diet), were the independent variables. Dependent variables were the difference (Δ) from baseline to conclusion of the study in five different disease outcome measures. ΔESR and ΔPain Score were both characterised numerically and dichotomously (improvement or no improvement). ΔAcute Phase Response, ΔPhysical Function, and ΔTender Joint Count were characterised dichotomously only. Multiple logistic regression was used to analyse associations between the independent and the disease outcome variables. Results Statistically significant correlations were found between Diet and three disease outcome variables i.e. ΔAcute-Phase Response, ΔPain Score, and ΔPhysical Function. Δ Body Weight was univariately only correlated to ΔAcute-Phase Response but not significant when diet was taken into account. Conclusion Body weight reduction did not significantly contribute to the improvement in rheumatoid arthritis when eating lacto-vegetarian, vegan or Mediterranean diets. PMID:15871736

Implications of Supermarket Access, Neighborhood Walkability, and Poverty Rates for Diabetes Risk in an Employee Population

PubMed Central

Herrick, Cynthia J.; Yount, Byron W.; Eyler, Amy A.

2016-01-01

Objective Diabetes is a growing public health problem, and the environment in which people live and work may affect diabetes risk. The goal of this study was to examine the association between multiple aspects of environment and diabetes risk in an employee population. Design This was a retrospective cross-sectional analysis. Home environment variables were derived using employee zip code. Descriptive statistics were run on all individual and zip code level variables, stratified by diabetes risk and worksite. A multivariable logistic regression analysis was then conducted to determine the strongest associations with diabetes risk. Setting Data was collected from employee health fairs in a Midwestern health system 2009–2012. Subjects The dataset contains 25,227 unique individuals across four years of data. From this group, using an individual’s first entry into the database, 15,522 individuals had complete data for analysis. Results The prevalence of high diabetes risk in this population was 2.3%. There was significant variability in individual and zip code level variables across worksites. From the multivariable analysis, living in a zip code with higher percent poverty and higher walk score was positively associated with high diabetes risk, while living in a zip code with higher supermarket density was associated with a reduction in high diabetes risk. Conclusions Our study underscores the important relationship between poverty, home neighborhood environment, and diabetes risk, even in a relatively healthy employed population, and suggests a role for the employer in promoting health. PMID:26638995

Implications of supermarket access, neighbourhood walkability and poverty rates for diabetes risk in an employee population.

PubMed

Herrick, Cynthia J; Yount, Byron W; Eyler, Amy A

2016-08-01

Diabetes is a growing public health problem, and the environment in which people live and work may affect diabetes risk. The goal of the present study was to examine the association between multiple aspects of environment and diabetes risk in an employee population. This was a retrospective cross-sectional analysis. Home environment variables were derived using employees' zip code. Descriptive statistics were run on all individual- and zip-code-level variables, stratified by diabetes risk and worksite. A multivariable logistic regression analysis was then conducted to determine the strongest associations with diabetes risk. Data were collected from employee health fairs in a Midwestern health system, 2009-2012. The data set contains 25 227 unique individuals across four years of data. From this group, using an individual's first entry into the database, 15 522 individuals had complete data for analysis. The prevalence of high diabetes risk in this population was 2·3 %. There was significant variability in individual- and zip-code-level variables across worksites. From the multivariable analysis, living in a zip code with higher percentage of poverty and higher walk score was positively associated with high diabetes risk, while living in a zip code with higher supermarket density was associated with a reduction in high diabetes risk. Our study underscores the important relationship between poverty, home neighbourhood environment and diabetes risk, even in a relatively healthy employed population, and suggests a role for the employer in promoting health.

Spontaneous prematurity in fetuses with congenital diaphragmatic hernia: a retrospective cohort study about prenatal predictive factors.

PubMed

Barbosa, Bruna Maria Lopes; Rodrigues, Agatha S; Carvalho, Mario Henrique Burlacchini; Bittar, Roberto Eduardo; Francisco, Rossana Pulcineli Vieira; Bernardes, Lisandra Stein

2018-01-12

To evaluate possible predictive factors of spontaneous prematurity in fetuses with congenital diaphragmatic hernia (CDH). A retrospective cohort study was performed. Inclusion criteria were presence of CDH; absence of fetoscopy; absence of karyotype abnormality; maximum of one major malformation associated with diaphragmatic hernia; ultrasound monitoring at the Obstetrics Clinic of Clinicas Hospital at the University of São Paulo School of Medicine, from January 2001 to October 2014. The data were obtained through the electronic records and ultrasound system of our fetal medicine service. The following variables were analyzed: maternal age, primiparity, associated maternal diseases, smoking, previous spontaneous preterm birth, fetal malformation associated with hernia, polyhydramnios, fetal growth restriction, presence of intrathoracic liver, invasive procedures performed, side of hernia and observed-to- expected lung to head ratio (o/e LHR). On individual analysis, variables were assessed using the Chi-square test and the Mann-Whitney test. A multiple logistic regression model was applied to select variables independently influencing the prediction of preterm delivery. A ROC curve was constructed with the significant variable, identifying the values with best sensitivity and specificity to be suggested for use in clinical practice. Eighty fetuses were evaluated, of which, 21 (26.25%) were premature. O/e LHR was the only factor associated with prematurity (p = 0.020). The ROC curve showed 93% sensitivity with 48.4% specificity for the cutoff of 40%. O/e LHR was the only predictor of prematurity in this sample.

Vocational outcome following spinal cord injury.

PubMed

Conroy, L; McKenna, K

1999-09-01

Non-experimental (ex post facto) survey research design involving the use of a fixed alternative format questionnaire. To investigate variables influencing vocational outcome, to identify barriers to gaining and sustaining employment and to identify the effects of variables on the type of work engaged in following spinal cord injury. The two sets of independent variables considered were, individual and injury-related factors (age at onset of injury, time since injury, extent/level of injury, highest educational qualification achieved pre-injury, and pre-injury occupation) and circumstantial factors (means of transport, access difficulties, perceived workplace discrimination, financial disincentives to work and perceived level of skill). The Princess Alexandra Hospital Spinal Injuries Unit, Queensland, Australia. Data on the variables and the vocational outcomes of having ever worked or studied post-injury, current employment status and post-injury occupation were obtained from survey responses. Demographical and medical data were gathered from medical records. Forward stepwise logistic regression revealed that having ever worked or studied post-injury was associated with all individual and injury-related factors except pre-injury occupation, and two circumstantial factors, namely means of transport and access difficulties. Current employment was associated with all circumstantial factors as well as age at injury and pre-injury occupation. Standard multiple regression analyses revealed that post-injury occupation was correlated with all individual and injury-related factors as well as means of transport and perceived workplace discrimination. Tailored rehabilitation programs for individuals with characteristics associated with less successful vocational outcomes may facilitate their employment status after injury.

Chronic back pain and associated work and non-work variables among farmworkers from Starr County, Texas.

PubMed

Shipp, Eva M; Cooper, Sharon P; del Junco, Deborah J; Delclos, George L; Burau, Keith D; Tortolero, Susan; Whitworth, Ryan E

2009-01-01

This study estimated the prevalence of chronic back pain among migrant farmworker family members and identified associated work and non-work variables. Migrant farmworkers (n = 390 from 267 families) from Starr County, Texas were interviewed in their home once a year for 2 years. The original survey included items measuring demographics, smoking, sleep, farm work, and chronic back pain. For this cross-sectional analysis, multi-level logistic regression was used to identify associated work and other variables associated with chronic back pain while accounting for intraclass correlations due to repeated measures and multiple family members. The prevalence of chronic back pain during the last migration season ranged from 9.5% among the youngest children to 33.3% among mothers. Variables significantly associated with chronic back pain were age (odds ratio [OR], 1.03, per year increase), depressive symptoms while migrating (OR, 8.72), fewer than 8 hours of sleep at home in Starr County (OR, 2.26), fairly bad/very bad quality of sleep while migrating (OR, 3.25), sorting crops at work (OR, 0.18), and working tree crops (OR, 11.72). The role of work exposures, depressive symptoms, and sleep in chronic back pain among farmworkers warrants further examination. Refinements in outcome and exposure assessments are also needed given the lack of a standardized case definition and the variety of tasks and crops involved in farm work in the United States.

Relevance of multiple spatial scales in habitat models: A case study with amphibians and grasshoppers

NASA Astrophysics Data System (ADS)

Altmoos, Michael; Henle, Klaus

2010-11-01

Habitat models for animal species are important tools in conservation planning. We assessed the need to consider several scales in a case study for three amphibian and two grasshopper species in the post-mining landscapes near Leipzig (Germany). The two species groups were selected because habitat analyses for grasshoppers are usually conducted on one scale only whereas amphibians are thought to depend on more than one spatial scale. First, we analysed how the preference to single habitat variables changed across nested scales. Most environmental variables were only significant for a habitat model on one or two scales, with the smallest scale being particularly important. On larger scales, other variables became significant, which cannot be recognized on lower scales. Similar preferences across scales occurred in only 13 out of 79 cases and in 3 out of 79 cases the preference and avoidance for the same variable were even reversed among scales. Second, we developed habitat models by using a logistic regression on every scale and for all combinations of scales and analysed how the quality of habitat models changed with the scales considered. To achieve a sufficient accuracy of the habitat models with a minimum number of variables, at least two scales were required for all species except for Bufo viridis, for which a single scale, the microscale, was sufficient. Only for the European tree frog ( Hyla arborea), at least three scales were required. The results indicate that the quality of habitat models increases with the number of surveyed variables and with the number of scales, but costs increase too. Searching for simplifications in multi-scaled habitat models, we suggest that 2 or 3 scales should be a suitable trade-off, when attempting to define a suitable microscale.

The Effect of Neighborhood Context on the Relationship Between Substance Misuse and Weapons Aggression in Urban Adolescents Seeking ED Care

PubMed Central

Goldstick, Jason Elliott; Lipton, Robert I.; Carter, Patrick; Stoddard, Sarah A.; Newton, Manya F.; Reischl, Thomas; Walton, Maureen; Zimmerman, Marc A.; Cunningham, Rebecca M.

2015-01-01

Background Frameworks for studying the ecology of human behavior suggest that multiple levels of the environment influence behavior and that these levels interact. Applied to studies of weapons aggression, this suggests proximal risk factor (e.g., substance use) effects may differ across neighborhoods. Objectives To estimate how the association between weapons aggression and substance use varies as a function of several community-level variables. Methods Individual-level measures (demographics, behavioral measures) were obtained from a survey of youth aged 14–24 years old seeking care at a Level-1 ED in Flint, Michigan. Community-level variables were obtained from public sources. Logistic generalized additive models were used to test whether community-level variables (crime rates, alcohol outlets, demographics) modify the link between individual-level substance use variables and the primary outcome measure: self-reported past 6-month weapon (firearm/knife) related aggression. Results The effect of marijuana misuse on weapons aggression varied significantly as a function of five community-level variables: racial composition, vacant housing rates, female headed household rates, density of package alcohol outlets, and nearby drug crime rates. The effect of high-risk alcohol use did not depend on any of the eight community variables tested. Conclusions The relationship between marijuana misuse and weapons aggression differed across neighborhoods with generally less association in more disadvantaged neighborhoods, while high-risk alcohol use showed a consistently high association with weapons aggression that did not vary across neighborhoods. The results aid in understanding the contributions of alcohol and marijuana use to the etiology of weapon-related aggression among urban youth, but further study in the general population is required. PMID:25607807

The Effect of Neighborhood Context on the Relationship Between Substance Misuse and Weapons Aggression in Urban Adolescents Seeking ED Care.

PubMed

Goldstick, Jason Elliott; Lipton, Robert I; Carter, Patrick; Stoddard, Sarah A; Newton, Manya F; Reischl, Thomas; Walton, Maureen; Zimmerman, Marc A; Cunningham, Rebecca M

2015-04-01

Frameworks for studying the ecology of human behavior suggest that multiple levels of the environment influence behavior and that these levels interact. Applied to studies of weapons aggression, this suggests proximal risk factor (e.g., substance use) effects may differ across neighborhoods. To estimate how the association between weapons aggression and substance use varies as a function of several community-level variables. Individual-level measures (demographics, behavioral measures) were obtained from a survey of youth aged 14-24 years old seeking care at a Level-1 ED in Flint, Michigan. Community-level variables were obtained from public sources. Logistic generalized additive models were used to test whether community-level variables (crime rates, alcohol outlets, demographics) modify the link between individual-level substance use variables and the primary outcome measure: self-reported past 6-month weapon (firearm/knife) related aggression. The effect of marijuana misuse on weapons aggression varied significantly as a function of five community-level variables: racial composition, vacant housing rates, female headed household rates, density of package alcohol outlets, and nearby drug crime rates. The effect of high-risk alcohol use did not depend on any of the eight community variables tested. The relationship between marijuana misuse and weapons aggression differed across neighborhoods with generally less association in more disadvantaged neighborhoods, while high-risk alcohol use showed a consistently high association with weapons aggression that did not vary across neighborhoods. The results aid in understanding the contributions of alcohol and marijuana use to the etiology of weapon-related aggression among urban youth, but further study in the general population is required.

Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression

NASA Astrophysics Data System (ADS)

Khikmah, L.; Wijayanto, H.; Syafitri, U. D.

2017-04-01

The problem often encounters in logistic regression modeling are multicollinearity problems. Data that have multicollinearity between explanatory variables with the result in the estimation of parameters to be bias. Besides, the multicollinearity will result in error in the classification. In general, to overcome multicollinearity in regression used stepwise regression. They are also another method to overcome multicollinearity which involves all variable for prediction. That is Principal Component Analysis (PCA). However, classical PCA in only for numeric data. Its data are categorical, one method to solve the problems is Categorical Principal Component Analysis (CATPCA). Data were used in this research were a part of data Demographic and Population Survey Indonesia (IDHS) 2012. This research focuses on the characteristic of women of using the contraceptive methods. Classification results evaluated using Area Under Curve (AUC) values. The higher the AUC value, the better. Based on AUC values, the classification of the contraceptive method using stepwise method (58.66%) is better than the logistic regression model (57.39%) and CATPCA (57.39%). Evaluation of the results of logistic regression using sensitivity, shows the opposite where CATPCA method (99.79%) is better than logistic regression method (92.43%) and stepwise (92.05%). Therefore in this study focuses on major class classification (using a contraceptive method), then the selected model is CATPCA because it can raise the level of the major class model accuracy.

No rationale for 1 variable per 10 events criterion for binary logistic regression analysis.

PubMed

van Smeden, Maarten; de Groot, Joris A H; Moons, Karel G M; Collins, Gary S; Altman, Douglas G; Eijkemans, Marinus J C; Reitsma, Johannes B

2016-11-24

Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth's correction, are compared. The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect ('separation'). We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth's correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

Logistic regression accuracy across different spatial and temporal scales for a wide-ranging species, the marbled murrelet

Treesearch

Carolyn B. Meyer; Sherri L. Miller; C. John Ralph

2004-01-01

The scale at which habitat variables are measured affects the accuracy of resource selection functions in predicting animal use of sites. We used logistic regression models for a wide-ranging species, the marbled murrelet, (Brachyramphus marmoratus) in a large region in California to address how much changing the spatial or temporal scale of...

Asymptotic Properties of Induced Maximum Likelihood Estimates of Nonlinear Models for Item Response Variables: The Finite-Generic-Item-Pool Case.

ERIC Educational Resources Information Center

Jones, Douglas H.

The progress of modern mental test theory depends very much on the techniques of maximum likelihood estimation, and many popular applications make use of likelihoods induced by logistic item response models. While, in reality, item responses are nonreplicate within a single examinee and the logistic models are only ideal, practitioners make…

New geospatial approaches for efficiently mapping forest biomass logistics at high resolution over large areas

Treesearch

John Hogland; Nathaniel Anderson; Woodam Chung

2018-01-01

Adequate biomass feedstock supply is an important factor in evaluating the financial feasibility of alternative site locations for bioenergy facilities and for maintaining profitability once a facility is built. We used newly developed spatial analysis and logistics software to model the variables influencing feedstock supply and to estimate and map two components of...

Estimation of Logistic Regression Models in Small Samples. A Simulation Study Using a Weakly Informative Default Prior Distribution

ERIC Educational Resources Information Center

Gordovil-Merino, Amalia; Guardia-Olmos, Joan; Pero-Cebollero, Maribel

2012-01-01

In this paper, we used simulations to compare the performance of classical and Bayesian estimations in logistic regression models using small samples. In the performed simulations, conditions were varied, including the type of relationship between independent and dependent variable values (i.e., unrelated and related values), the type of variable…

Large Unbalanced Credit Scoring Using Lasso-Logistic Regression Ensemble

PubMed Central

Wang, Hong; Xu, Qingsong; Zhou, Lifeng

2015-01-01

Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data. PMID:25706988

Analysis Test of Understanding of Vectors with the Three-Parameter Logistic Model of Item Response Theory and Item Response Curves Technique

ERIC Educational Resources Information Center

Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

2016-01-01

This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming…

A bi-national comparative study of health behaviors of Koreans in South Korea and Korean Americans in California.

PubMed

Ryu, So Yeon; Crespi, Catherine M; Maxwell, Annette E

2013-12-01

Few studies have compared health behaviors of Koreans in their home country and Korean Americans. Using 2009 data from the Community Health Survey (South Korea) and the California Health Interview Survey (USA), we compared native Koreans and Korean Americans, grouped by level of acculturation, on prevalence of specific health behaviors and self-rated health, and conducted multiple logistic regression comparing the odds of these behaviors among the groups adjusted for demographic variables. While Korean Americans exhibit healthier behaviors than Koreans in some areas (e.g., reduced smoking and binge drinking in men, increased utilization of flu vaccinations), we also identified problem behaviors (e.g., increased body weight in Korean American men, uptake of alcohol drinking and smoking among Korean American women). Findings support the critical need for health promotion programs addressing these health behaviors to prevent future health problems among Korean Americans.

Predictors of hopelessness among clinically depressed youth.

PubMed

Becker-Weidman, Emily G; Reinecke, Mark A; Jacobs, Rachel H; Martinovich, Zoran; Silva, Susan G; March, John S

2009-05-01

Factors that distinguish depressed individuals who become hopeless from those who do not are poorly understood. In this study, predictors of hopelessness were examined in a sample of 439 clinically depressed adolescents participating in the Treatment for Adolescents with Depression Study (TADS). The total score of the Beck Hopelessness Scale (BHS) was used to assess hopelessness at baseline. Multiple regression and logistic regression analyses were conducted to evaluate the extent to which variables were associated with hopelessness and determine which cluster of measures best predicted clinically significantly hopelessness. Hopelessness was associated with greater depression severity, poor social problem-solving, cognitive distortions, and family conflict. View of self, view of the world, internal attributional style, need for social approval, positive problem-solving orientation, and family problems consistently emerged as the best predictors of hopelessness in depressed youth. Cognitive and familial factors predict those depressed youth who have high levels of hopelessness.

Childhood maltreatment and threats with weapons.

PubMed

Casiano, Hygiea; Mota, Natalie; Afifi, Tracie O; Enns, Murray W; Sareen, Jitender

2009-11-01

The relationship between childhood maltreatment and future threats with weapons is unknown. We examined data from the nationally representative National Comorbidity Survey Replication (n = 5692) and conducted multiple logistic regression analyses to determine the association between childhood maltreatment and lifetime behavior of threatening others with a gun or other weapon. After adjusting for sociodemographic variables, physical abuse, sexual abuse, and witnessing domestic violence were significantly associated with threats made with a gun (adjusted odds ratios [AOR] ranging between 3.38 and 4.07) and other weapons (AOR ranging between 2.16 and 2.83). The greater the number of types of maltreatment experienced, the stronger the association with lifetime threats made to others with guns and any weapons. Over 94% of respondents who experienced maltreatment and made threats reported that the maltreatment occurred prior to threatening others with weapons. Prevention efforts that reduce exposure to maltreatment may reduce violent behavior in later life.

Association of Job Stressors With Panic Attack and Panic Disorder in a Working Population in Japan: A Cross-Sectional Study.

PubMed

Asai, Yumi; Imamura, Kotaro; Kawakami, Norito

2017-06-01

This study aimed to investigate associations of job stressors with panic attack (PA) and panic disorder (PD) among Japanese workers. A cross-sectional online questionnaire survey was conducted of 2060 workers. Job strain, effort/reward imbalance, and workplace social support were measured by the job content questionnaire and effort/reward imbalance questionnaire. These variables were classified into tertiles. PA/PD were measured by self-report based on the mini international neuropsychiatric interview (MINI). Multiple logistic regression was conducted, adjusting for demographic, lifestyle, and health-related covariates. Data from 1965 participants were analyzed. Adjusted odds ratio (OR) of PA/PD was significantly greater for the group with high effort/reward imbalance compared with the group with low effort/reward imbalance (ORs, 2.64 and 2.94, respectively, both P < 0.05). This study found effort/reward imbalance was associated with having PA/PD among Japanese workers.

Association between Sleep Duration and Perceived Stress: Salaried Worker in Circumstances of High Workload.

PubMed

Choi, Dong-Woo; Chun, Sung-Youn; Lee, Sang Ah; Han, Kyu-Tae; Park, Eun-Cheol

2018-04-19

The aim of this study was to find the association between sleep duration and perceived stress in salaried workers according to occupational categories and which lifestyle factors affected those correlations in South Korea. This study used data from the 2015 Community Health Survey (CHS). The self-reported sleep duration was used as the dependent variable in this study. We explored sleep duration and stress awareness among salaried workers, as well as household income and educational level with multiple logistic regression analysis. Salaried workers who slept for five or less hours had a higher odds ratio for high-stress awareness (OR: 1.86, 95% CI: 1.74⁻1.98). Stress awareness is associated with short sleep duration; specialized workers, office workers, those with above mid-high household income and graduate, university, or college level workers especially need to sleep adequately to manage stress.

Recent Suicide Attempts Across Multiple Social Identities Among Gay and Bisexual Men: An Intersectionality Analysis.

PubMed

Ferlatte, Olivier; Salway, Travis; Hankivsky, Olena; Trussler, Terry; Oliffe, John L; Marchand, Rick

2017-09-08

This study draws from intersectionality to describe variations in recent suicide attempts (RSA) among gay and bisexual men (GBM) across sociodemographics. Using survey data, logistic regression modeling explored RSA in two analytical stages: (1) the individual effects of each sociodemographic were measured; (2) two-way interaction terms between sociodemographics were tested and added to the models created in stage A. In stage A, only education and income achieved significance. In stage B, the study found that (a) education and income interacted significantly such that the odds of RSA increased for those with a lower income and a lower education; (b) sexual orientation and partnership status interacted, resulting in decreased odds among bisexual men in heterosexual partnerships; and (c) income and education interacted with geography; the effects of these variables were significant only among urban men. These findings suggest that GBM are at unequal risk of RSA according to intersecting sociodemographics.

Association between Sleep Duration and Perceived Stress: Salaried Worker in Circumstances of High Workload

PubMed Central

Choi, Dong-Woo; Chun, Sung-Youn; Lee, Sang Ah; Han, Kyu-Tae

2018-01-01

The aim of this study was to find the association between sleep duration and perceived stress in salaried workers according to occupational categories and which lifestyle factors affected those correlations in South Korea. This study used data from the 2015 Community Health Survey (CHS). The self-reported sleep duration was used as the dependent variable in this study. We explored sleep duration and stress awareness among salaried workers, as well as household income and educational level with multiple logistic regression analysis. Salaried workers who slept for five or less hours had a higher odds ratio for high-stress awareness (OR: 1.86, 95% CI: 1.74–1.98). Stress awareness is associated with short sleep duration; specialized workers, office workers, those with above mid-high household income and graduate, university, or college level workers especially need to sleep adequately to manage stress. PMID:29671770

Health-Related Quality of Life Among US Workers: Variability Across Occupation Groups.

PubMed

Shockey, Taylor M; Zack, Matthew; Sussell, Aaron

2017-08-01

To examine the health-related quality of life among workers in 22 standard occupation groups using data from the 2013-2014 US Behavioral Risk Factor Surveillance System. We examined the health-related quality of life measures of self-rated health, frequent physical distress, frequent mental distress, frequent activity limitation, and frequent overall unhealthy days by occupation group for 155 839 currently employed adults among 17 states. We performed multiple logistic regression analyses that accounted for the Behavioral Risk Factor Surveillance System's complex survey design to obtain prevalence estimates adjusted for potential confounders. Among all occupation groups, the arts, design, entertainment, sports, and media occupation group reported the highest adjusted prevalence of frequent physical distress, frequent mental distress, frequent activity limitation, and frequent overall unhealthy days. The personal care and service occupation group had the highest adjusted prevalence for fair or poor self-rated health. Workers' jobs affect their health-related quality of life.

Self perceptions as predictors for return to work 2 years after rehabilitation in orthopedic trauma inpatients.

PubMed

Iakova, Maria; Ballabeni, Pierluigi; Erhart, Peter; Seichert, Nikola; Luthi, François; Dériaz, Olivier

2012-12-01

This study aimed to identify self-perception variables which may predict return to work (RTW) in orthopedic trauma patients 2 years after rehabilitation. A prospective cohort investigated 1,207 orthopedic trauma inpatients, hospitalised in rehabilitation, clinics at admission, discharge, and 2 years after discharge. Information on potential predictors was obtained from self administered questionnaires. Multiple logistic regression models were applied. In the final model, a higher likelihood of RTW was predicted by: better general health and lower pain at admission; health and pain improvements during hospitalisation; lower impact of event (IES-R) avoidance behaviour score; higher IES-R hyperarousal score, higher SF-36 mental score and low perceived severity of the injury. RTW is not only predicted by perceived health, pain and severity of the accident at the beginning of a rehabilitation program, but also by the changes in pain and health perceptions observed during hospitalisation.

[Psychomotor development in offspring of mothers with post partum depression].

PubMed

Podestá L, Loreto; Alarcón, Ana María; Muñoz, Sergio; Legüe C, Marcela; Bustos, Luis; Barría P, Mauricio

2013-04-01

Postpartum depression (PPD) has adverse effects on psychomotor development of the offspring. To evaluate the relationship between PPD and psychomotor development in children aged 18 months, consulting in primary care. Cross-sectional study with 360 infants and their mothers. Children had their psychomotor evaluation at l8 months and mothers completed the Edinburgh Postnatal Depression Scale at 4 and 12 weeks postpartum. The prevalence of both PPD and psychomotor alteration was estimated. The association between PPD and psychomotor alteration, including confounding variables, was estimated through logistic multiple regression analysis. The prevalence of PPD and psychomotor alteration was 29 and 16%, respectively Mothers with PPD had twice the probability of having an offspring with psychomotor alteration (Odds ratio = 2.0, confidence intervals = 1.07-3.68). This probability was significantly higher among single mothers or those with an unstable partner. PPD has a detrimental impact on psychomotor development of children.

Sexual violence, weight perception, and eating disorder indicators in college females.

PubMed

Groff Stephens, Sara; Wilke, Dina J

2016-01-01

To examine the relationships between sexual violence experiences, inaccurate body weight perceptions, and the presence of eating disorder (ED) indicators in a sample of female US college students. Participants were 6,090 college females 25 years of age and younger. A secondary analysis of National College Health Assessment data gathered annually at one institution from 2004 to 2013 was utilized. A model predicting ED indicators was tested using logistic regression analyses with multiple categorical variables representing severity of sexual violence, accuracy of body weight perception, and an interaction between the two. Sexual violence and inaccurate body weight perception significantly predicted ED indicators; sexual violence was the strongest predictor of purging behavior, whereas inaccurate body weight perception was best predicted by underweight status. Findings provide support to the relationship between purging behavior and severity of sexual violence and also to the link between inaccurate body weight perception and being underweight.

Glucagon gene polymorphism modifies the effects of smoking and physical activity on risk of type 2 diabetes mellitus in Han Chinese.

PubMed

Li, Linlin; Gao, Kaiping; Zhao, Jingzhi; Feng, Tianping; Yin, Lei; Wang, Jinjin; Wang, Chongjian; Li, Chunyang; Wang, Yan; Wang, Qian; Zhai, Yujia; You, Haifei; Ren, Yongcheng; Wang, Bingyuan; Hu, Dongsheng

2014-01-25

Few genome-wide association studies have considered interactions between multiple genetic variants and environmental factors associated with disease. The interaction was examined between a glucagon gene (GCG) polymorphism and smoking, alcohol consumption and physical activity and the association with risk of type 2 diabetes mellitus (T2DM) in a case-control study of Chinese Han subjects. The rs12104705 polymorphism of GCG and interactions with environmental variables were analyzed for 9619 participants by binary multiple logistic regression. Smoking with the C-C haplotype of rs12104705 was associated with increased risk of T2DM (OR=1.174, 95% CI=1.013-1.361). Moderate and high physical activity with the C-C genotype was associated with decreased risk of T2DM as compared with low physical activity with the genotype (OR=0.251, 95% CI=0.206-0.306 and OR=0.190, 95% CI=0.164-0.220). However, the interaction of drinking and genotype was not associated with risk of T2DM. Genetic polymorphism in rs12104705 of GCG may interact with smoking and physical activity to modify the risk of T2DM. © 2013.

Neutropenia is independently associated with sub-therapeutic serum concentration of vancomycin.

PubMed

Choi, Min Hyuk; Choe, Yeon Hwa; Lee, Sang-Guk; Jeong, Seok Hoon; Kim, Jeong-Ho

2017-02-01

We aimed to identify the impact of the presence of neutropenia on serum vancomycin concentration (SVC). A retrospective study was conducted from January 2005 to December 2015. The study population was comprised of adult patients who were performed serum concentration of vancomycin. Patients with renal failure or using non-conventional dosages of vancomycin were excluded. A total of 1307 adult patients were included in this study, of whom 163 (12.4%) were neutropenic. Patients with neutropenia presented significantly lower SVCs than non-neutropenic patients (P<0.0001). Multiple linear regressions showed significant association between neutropenia and trough SVC (beta coefficients, -2.351; P=0.004). Multiple logistic regression analysis also revealed a significant association between sub-therapeutic vancomycin concentrations (trough SVC values<10mg/l) and neutropenia (odds ratio, 1.75, P=0.029) CONCLUSIONS: The presence of neutropenia is significantly associated with low SVC, even after adjusting for other variables. Therefore, neutropenic patients had a higher risk of sub-therapeutic SVC compared with non-neutropenic patients. We recommended that vancomycin therapy should be monitored with TDM-guided optimization of dosage and intervals, especially in neutropenic patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Scale-invariance underlying the logistic equation and its social applications

NASA Astrophysics Data System (ADS)

Hernando, A.; Plastino, A.

2013-01-01

On the basis of dynamical principles we i) advance a derivation of the Logistic Equation (LE), widely employed (among multiple applications) in the simulation of population growth, and ii) demonstrate that scale-invariance and a mean-value constraint are sufficient and necessary conditions for obtaining it. We also generalize the LE to multi-component systems and show that the above dynamical mechanisms underlie a large number of scale-free processes. Examples are presented regarding city-populations, diffusion in complex networks, and popularity of technological products, all of them obeying the multi-component logistic equation in an either stochastic or deterministic way.

Disparities in chronic conditions and health status by type of disability

PubMed Central

Horner-Johnson, Willi; Dobbertin, Konrad; Lee, Jae Chul; Andresen, Elena M.

2013-01-01

Background Prior research has established health disparities between people with and without disabilities. However, disparities within the disability population, such as those related to type of disability, have been much less studied. Objective To examine differences in chronic conditions and health status between subgroups of people with different types of disability. Methods We analyzed Medical Expenditure Panel Survey annual data files from 2002-2008. Logistic regression analyses considered disparity from three perspectives: 1) basic differences, unadjusted for other factors; 2) controlling for key demographic and health covariates; and 3) controlling for a larger set of demographic variables and socioeconomic status as well as health and access to healthcare. Results Individuals with vision, physical, cognitive, or multiple disability types fared worse than people with hearing impairment on most health outcomes. This was most consistently true for people with multiple disabilities. Even when all covariates were accounted for, people with multiple types of disability were significantly more likely (p < 0.05) than those with hearing impairment (reference group) to report every poor health outcome with the exception of BMI ≥ 25 and lung disease. Conclusions While many of the differences between disability types were reduced when controlling for other factors, some differences remained significant. This argues for a more individualized approach to understanding and preventing chronic conditions and poor health in specific disability groups. PMID:24060250

Musculoskeletal pain and re-employment among unemployed job seekers: a three-year follow-up study.

PubMed

Nwaru, Chioma A; Nygård, Clas-Håkan; Virtanen, Pekka

2016-07-08

Poor health is a potential risk factor for not finding employment among unemployed individuals. We investigated the associations between localized and multiple-site musculoskeletal pain and re-employment in a three-year follow-up of unemployed job seekers. Unemployed people (n = 539) from six localities in southern Finland who participated in various active labour market policy measures at baseline in 2002/2003 were recruited into a three-year health service intervention trial. A questionnaire was used to collect data on musculoskeletal health and background characteristics at baseline and on employment status at the end of the follow-up. We conducted a complete case (n = 284) and multiple imputation analyses using logistic regression to investigate the association between baseline musculoskeletal pain and re-employment after three years. Participants with severe pain in the lower back were less likely to become re-employed. This was independent of potential confounding variables. Pain in the hands/upper extremities, neck/shoulders, lower extremities, as well as multiple site were not determinants of re-employment. Our findings lend some support to the hypothesis that poor health can potentially cause health selection into employment. There is the need to disentangle health problems in order to clearly appreciate their putative impact on employment. This will allow for more targeted interventions for the unemployed.

Effects of field variables on infield biomass bales aggregation strategies

USDA-ARS?s Scientific Manuscript database

Infield aggregation of bales, an essential logistics operation of clearing the field for subsequent cropping, is influenced by several field variables, such as field shape, area, randomness on bale layout, biomass yield per unit area, bale row spacing, number of bales handled simultaneously, collect...

Foraminifera Models to Interrogate Ostensible Proxy-Model Discrepancies During Late Pliocene

NASA Astrophysics Data System (ADS)

Jacobs, P.; Dowsett, H. J.; de Mutsert, K.

2017-12-01

Planktic foraminifera faunal assemblages have been used in the reconstruction of past oceanic states (e.g. the Last Glacial Maximum, the mid-Piacenzian Warm Period). However these reconstruction efforts have typically relied on inverse modeling using transfer functions or the modern analog technique, which by design seek to translate foraminifera into one or two target oceanic variables, primarily sea surface temperature (SST). These reconstructed SST data have then been used to test the performance of climate models, and discrepancies have been attributed to shortcomings in climate model processes and/or boundary conditions. More recently forward proxy models or proxy system models have been used to leverage the multivariate nature of proxy relationships to their environment, and to "bring models into proxy space". Here we construct ecological models of key planktic foraminifera taxa, calibrated and validated with World Ocean Atlas (WO13) oceanographic data. Multiple modeling methods (e.g. multilayer perceptron neural networks, Mahalanobis distance, logistic regression, and maximum entropy) are investigated to ensure robust results. The resulting models are then driven by a Late Pliocene climate model simulation with biogeochemical as well as temperature variables. Similarities and differences with previous model-proxy comparisons (e.g. PlioMIP) are discussed.

Sulfide Generated by Sulfate Reduction is a Primary Controller of the Occurrence of Wild Rice (Zizania palustris) in Shallow Aquatic Ecosystems

NASA Astrophysics Data System (ADS)

Myrbo, A.; Swain, E. B.; Engstrom, D. R.; Coleman Wasik, J.; Brenner, J.; Dykhuizen Shore, M.; Peters, E. B.; Blaha, G.

2017-11-01

Field observations suggest that surface water sulfate concentrations control the distribution of wild rice, an aquatic grass (Zizania palustris). However, hydroponic studies show that sulfate is not toxic to wild rice at even unrealistically high concentrations. To determine how sulfate might directly or indirectly affect wild rice, potential wild rice habitat was characterized for 64 chemical and physical variables in over 100 sites spanning a relatively steep climatic and geological gradient in Minnesota. Habitat suitability was assessed by comparing the occurrence of wild rice with the field variables, through binary logistic regression. This analysis demonstrated that sulfide in sediment pore water, generated by the microbial reduction of sulfate that diffuses or advects into the sediment, is the primary control of wild rice occurrence. Water temperature and water transparency independently control the suitability of habitat for wild rice. In addition to generating phytotoxic sulfide, sulfate reduction also supports anaerobic decomposition of organic matter, releasing nutrients that can compound the harm of direct sulfide toxicity. These results are important because they show that increases in sulfate loading to surface water can have multiple negative consequences for ecosystems, even though sulfate itself is relatively benign.

Maternal infection rates after cesarean delivery by Pfannenstiel or Joel-Cohen incision: a multicenter surveillance study.

PubMed

Dumas, Anne Marie; Girard, Raphaële; Ayzac, Louis; Caillat-Vallet, Emmanuelle; Tissot-Guerraz, Françoise; Vincent-Bouletreau, Agnès; Berland, Michel

2009-12-01

Our purpose was to evaluate maternal nosocomial infection rates according to the incision technique used for caesarean delivery, in a routine surveillance study. This was a prospective study of 5123 cesarean deliveries (43.2% Joel-Cohen, 56.8% Pfannenstiel incisions) in 35 maternity units (Mater Sud Est network). Data on routine surveillance variables, operative duration, and three additional variables (manual removal of the placenta, uterine exteriorization, and/or cleaning of the parieto-colic gutter) were collected. Multiple logistic regression analysis was used to identify independent risk factors for infection. The overall nosocomial infection and endometritis rates were higher for the Joel-Cohen than Pfannenstiel incision (4.5% vs. 3.3%, 0.8% vs. 0.3%, respectively). The higher rate of nosocomial infections with the Joel-Cohen incision was due to a greater proportion of patients presenting risk factors (i.e., emergency delivery, primary cesarean, blood loss > or =800 mL, no manual removal of the placenta and no uterine exteriorization). However, the Joel-Cohen technique was an independent risk factor for endometritis. The Joel-Cohen technique is faster than the Pfannenstiel technique but is associated with a higher incidence of endometritis.

Individual factors associated to malocclusion in adolescents.

PubMed

Rebouças, Adriana Gama; Zanin, Luciane; Ambrosano, Gláucia Maria Bovi; Flório, Flávia Martão

2017-11-01

The study aimed to identify the severity of malocclusions and associated factors among Brazilian adolescents. Data from 5,445 adolescents participating in the Brazilian Oral Health Survey (SBBrasil 2010) were evaluated, of which 4,276 were included in the study based on the inclusion criteria. The dependent variable was severe and very severe malocclusion, according to the Dental Aesthetic Index (DAI > 30). The independent variables were place of residence, macro-region, self-reported ethnicity, income, gender, schooling, access to dental care, untreated caries and front and back teeth loss due to caries. A hierarchical multiple logistical regression analysis was performed, considering the complex cluster sampling plan. Prevalence of severe/very severe malocclusions was 17.5%. After adjustments, black/brown ethnicity group (OR = 1.59, 95% CI: 1.09-2.34), lower household income (OR = 0.67, 95% CI: 0.55-0-82), front (OR = 2.32, 95% CI: 1.14-4.76) and back teeth (OR = 1.45, 95% CI: 1.14-1.84) loss due to caries were associated with the outcome. Therefore, we conclude that black/brown ethnicity, lower household income and greater number of front and back teeth loss due to caries increased the odds for severe/very severe malocclusion.

One-Year Prospective Study on Passion and Gambling Problems in Poker Players.

PubMed

Morvannou, Adèle; Dufour, Magali; Brunelle, Natacha; Berbiche, Djamal; Roy, Élise

2018-06-01

The concept of passion is relevant to understanding gambling behaviours and gambling problems. Longitudinal studies are useful to better understand the absence and development of gambling problems; however, only one study has specifically considered poker players. Using a longitudinal design, this study aims to determine the influence, 1 year later, of two forms of passion-harmonious and obsessive-on gambling problems in poker players. A total of 116 poker players was recruited from across Quebec, Canada. The outcome variable of interest was participants' category on the Canadian Pathological Gambling Index, and the predictive variable was the Gambling Passion Scale. Multiple logistic regression analyses were conducted to identify independent risk factors of at-risk poker players 1 year later. Obsessive passion at baseline doubled the risk of gambling problems 1 year later (p < 0.01); for harmonious passion, there was no association. Number of gambling activities, drug problems, and impulsivity were also associated with at-risk gambling. This study highlights the links between obsessive passion and at-risk behaviours among poker players. It is therefore important to prevent the development of obsessive passion among poker players.

Effect of playing tactics on goal scoring in Norwegian professional soccer.

PubMed

Tenga, Albin; Holme, Ingar; Ronglan, Lars Tore; Bahr, Roald

2010-02-01

Methods that include an assessment of opponent interactions are thought to provide a more valid analysis of team match performance. The purpose of this study was to examine the effect of playing tactics on goal scoring by assessing opponent interactions in Norwegian elite soccer. The sample included 203 team possessions leading to goals (cases) and 1688 random team possessions (control group) from 163 of 182 (90%) matches played in the men's professional league during the 2004 season. Multidimensional qualitative data using ten ordered categorical variables were obtained to characterize each team possession. The proportion of goals scored during counterattacks (52%) was higher than during elaborate attacks (48%), while for the control group the proportion using elaborate attacks (59%) was higher than when using counterattacks (41%) (P = 0.002). Multiple logistic regression analyses showed that, for the main variable "team possession type", counterattacks were more effective than elaborate attacks when playing against an imbalanced defence (OR = 1.64; 95% confidence interval: 1.03 to 2.61; P = 0.038). Assessment of opponent interactions is critical to evaluate the effectiveness of offensive playing tactics on the probability of scoring goals, and improves the validity of team match-performance analysis in soccer.

Zinc and homocysteine levels in polycystic ovarian syndrome patients with insulin resistance.

PubMed

Guler, Ismail; Himmetoglu, Ozdemir; Turp, Ahmet; Erdem, Ahmet; Erdem, Mehmet; Onan, M Anıl; Taskiran, Cagatay; Taslipinar, Mine Yavuz; Guner, Haldun

2014-06-01

In this study, our objective was to evaluating the value of serum zinc levels as an etiologic and prognostic marker in patients with polycystic ovarian syndrome. We conducted a prospective study, including 53 women with polycystic ovarian syndrome and 33 healthy controls. We compared serum zinc levels, as well as clinical and metabolic features, of the cases. We also compared serum zinc levels between patients with polycystic ovarian syndrome with insulin resistance. Mean zinc levels were found to be significantly lower in patients with polycystic ovarian syndrome than healthy controls. Multiple logistic regression analysis of significant metabolic variables between polycystic ovarian syndrome and control groups (serum zinc level, body mass index, the ratio of triglyceride/high-density lipoprotein cholesterol, and homocysteine) revealed that zinc level was the most significant variable to predict polycystic ovarian syndrome. Mean serum zinc levels tended to be lower in patients with polycystic ovarian syndrome with impaired glucose tolerance than patients with normal glucose tolerance, but the difference was not statistically significant. In conclusion, zinc deficiency may play a role in the pathogenesis of polycystic ovarian syndrome and may be related with its long-term metabolic complications.

System design and improvement of an emergency department using Simulation-Based Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Goienetxea Uriarte, A.; Ruiz Zúñiga, E.; Urenda Moris, M.; Ng, A. H. C.

2015-05-01

Discrete Event Simulation (DES) is nowadays widely used to support decision makers in system analysis and improvement. However, the use of simulation for improving stochastic logistic processes is not common among healthcare providers. The process of improving healthcare systems involves the necessity to deal with trade-off optimal solutions that take into consideration a multiple number of variables and objectives. Complementing DES with Multi-Objective Optimization (SMO) creates a superior base for finding these solutions and in consequence, facilitates the decision-making process. This paper presents how SMO has been applied for system improvement analysis in a Swedish Emergency Department (ED). A significant number of input variables, constraints and objectives were considered when defining the optimization problem. As a result of the project, the decision makers were provided with a range of optimal solutions which reduces considerably the length of stay and waiting times for the ED patients. SMO has proved to be an appropriate technique to support healthcare system design and improvement processes. A key factor for the success of this project has been the involvement and engagement of the stakeholders during the whole process.

An iterated local search algorithm for the team orienteering problem with variable profits

NASA Astrophysics Data System (ADS)

Gunawan, Aldy; Ng, Kien Ming; Kendall, Graham; Lai, Junhan

2018-07-01

The orienteering problem (OP) is a routing problem that has numerous applications in various domains such as logistics and tourism. The objective is to determine a subset of vertices to visit for a vehicle so that the total collected score is maximized and a given time budget is not exceeded. The extensive application of the OP has led to many different variants, including the team orienteering problem (TOP) and the team orienteering problem with time windows. The TOP extends the OP by considering multiple vehicles. In this article, the team orienteering problem with variable profits (TOPVP) is studied. The main characteristic of the TOPVP is that the amount of score collected from a visited vertex depends on the duration of stay on that vertex. A mathematical programming model for the TOPVP is first presented and an algorithm based on iterated local search (ILS) that is able to solve modified benchmark instances is then proposed. It is concluded that ILS produces solutions which are comparable to those obtained by the commercial solver CPLEX for smaller instances. For the larger instances, ILS obtains good-quality solutions that have significantly better objective value than those found by CPLEX under reasonable computational times.

[Clinical factors associated with invasive pulmonary aspergillosis in patients with chronic pneumopathies and respiratory isolation of Aspergillus spp].

PubMed

Castón, Juan José; Linares, María José; Rivero, Antonio; Casal, Manuel; Torre-Cisneros, Julián

2012-12-15

To determine clinical variables to distinguish invasive pulmonary aspergillosis (IPA) from colonization in patients with chronic pneumopathies with positive culture of Aspergillus spp. in respiratory samples. Retrospective cohort study including patients with respiratory isolations of Aspergillus spp. during a period of 10 years. IPA was evaluated according to the Bulpa criteria. Clinical variables were collected and a multiple logistic regression analysis was carried out. Eighty-three patients with isolation of Aspergillus spp. from respiratory samples were included; 68.7% (n=57) of the patients had chronic obstructive pulmonary disease, 18% (n=15) pulmonary fibrosis and 13.3% (n=11) bronchial asthma. Twenty-two patients (26.6%) had IPA. The use of fluconazole (OR 4.49; CI 95% 1.5-13.4; P=.007), severe respiratory failure (OR 4.64; CI 95% 1.46-14.72; P=.009) and hospitalization time (OR 1.05; CI 95% 1.01-1.1; P=.006) were associated with IPA. Prior use of fluconazole, severe respiratory failure and hospitalization time are associated with IPA in patients with chronic pneumopathies with respiratory isolation of Aspergillus spp. Copyright © 2012 Elsevier España, S.L. All rights reserved.

Specificity and detail in autobiographical memory: Same or different constructs?

PubMed

Kyung, Yoonhee; Yanes-Lukin, Paula; Roberts, John E

2016-01-01

Research on autobiographical memory has focused on whether memories are coded as specific (i.e., describe a single event that happened at a particular time and place). Although some theory and research suggests that the amount of detail in autobiographical memories reflects a similar underlying construct as memory specificity, past research has not investigated whether these variables converge. Therefore, the present study compared the proportion of specific memories and the amount of detail embedded in memory responses to cue words. Results demonstrated that memory detail and proportion of specific memories were not correlated with each other and showed different patterns of association with other conceptually relevant variables. When responses to neutral cue words were examined in multiple linear and logistic regression analyses, the proportion of specific memories uniquely predicted less depressive symptoms, low emotional avoidance, lower emotion reactivity, better executive control and lower rumination, whereas the amount of memory detail uniquely predicted the presence of depression diagnosis, as well as greater depressive symptoms, subjective stress, emotion reactivity and rumination. Findings suggest that the ability to retrieve specific memories and the tendency to retrieve detailed personal memories reflect different constructs that have different implications in the development of emotional distress.

Gender and racial differences for suicide attempters and ideators in a high-risk community corrections population.

PubMed

McCullumsmith, Cheryl B; Clark, C Brendan; Perkins, Adam; Fife, Jessaka; Cropsey, Karen L

2013-01-01

Community corrections populations are a high-risk group who carry multiple suicide risk factors. To identify factors correlated with historical suicide attempts and ideation among African-American men, African-American women, White men, and White women in a community corrections population. Self-report data from 18,753 enrollees in community corrections were analyzed. Multinomial logistic regression analyses were conducted to determine associations between historical suicidal ideation and attempts among the four demographic groups. Participants with historical suicide attempts tended to be younger, White, female, be taking psychotropic medication, have a history of physical or sexual abuse, and meet criteria for dependence on alcohol, amphetamines, cocaine, opioids, or sedatives. Five variables were commonly associated with suicide attempts for all four race/gender groups: younger age, being on disability or retirement, taking psychotropic medication, history of sexual or physical abuse, and cocaine dependence. Other demographic variables had race or gender specificities as risk factors for suicide attempts. Participants had high rates of historical suicide attempts with unique correlates differentiating attempters from ideators among different racial and gender groups. Cocaine dependence was universal predictor of suicide attempts, while other substance dependencies show specific racial and gender profiles associated with suicide attempts.

Correlates of children and parents being physically active together.

PubMed

Lee, Sarah M; Nihiser, Allison; Strouse, Darcy; Das, Barnali; Michael, Shannon; Huhman, Marian

2010-11-01

Co-physical activity (between parents and children), as an outcome variable, and its correlates have not been examined previously. The purpose of this study was to investigate correlates of co-physical activity among a nationally representative sample of 9- to 13-year-old children and their parents. Data were from the 2004 Youth Media Campaign Longitudinal Survey, a national survey of 5177 child-parent dyads. Parents of 9- to 13-year-old children were asked to report co-physical activity. Parents and children responded to a series of sociodemographic, behavioral, and psychosocial measures. Co-physical activity was treated as a dichotomous variable (ie, some or none). Logistic regression was used to assess associations of correlates directly and possible interactions between correlates. More than three-quarters of parents reported co-physical activity at least 1 day in the prior week. Age, race/ethnicity, sports team participation, eating meals together, parental confidence to influence the child's organized activity, and the child's perception of parental support were significantly associated with co-physical activity. The majority of respondents reported participating in co-physical activity, and multiple sociodemographic, behavioral, and psychosocial correlates were significantly associated with co-physical activity. This study provides insight for physical activity interventions that might involve parents.

Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

NASA Astrophysics Data System (ADS)

Ma, Chuang; Bao, Zhong-Kui; Zhang, Hai-Feng

2017-10-01

So far, many network-structure-based link prediction methods have been proposed. However, these methods only highlight one or two structural features of networks, and then use the methods to predict missing links in different networks. The performances of these existing methods are not always satisfied in all cases since each network has its unique underlying structural features. In this paper, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same network, their inner structural features are utterly different. Therefore, more structural features should be considered. However, owing to the remarkably different structural features, the contributions of different features are hard to be given in advance. Inspired by these facts, an adaptive fusion model regarding link prediction is proposed to incorporate multiple structural features. In the model, a logistic function combing multiple structural features is defined, then the weight of each feature in the logistic function is adaptively determined by exploiting the known structure information. Last, we use the "learnt" logistic function to predict the connection probabilities of missing links. According to our experimental results, we find that the performance of our adaptive fusion model is better than many similarity indices.

Prevalence of difficult venous access and associated risk factors in highly complex hospitalised patients.

PubMed

Armenteros-Yeguas, Victoria; Gárate-Echenique, Lucía; Tomás-López, Maria Aranzazu; Cristóbal-Domínguez, Estíbaliz; Moreno-de Gusmão, Breno; Miranda-Serrano, Erika; Moraza-Dulanto, Maria Inmaculada

2017-12-01

To estimate the prevalence of difficult venous access in complex patients with multimorbidity and to identify associated risk factors. In highly complex patients, factors like ageing, the need for frequent use of irritant medication and multiple venous catheterisations to complete treatment could contribute to exhaustion of venous access. A cross-sectional study was conducted. 'Highly complex' patients (n = 135) were recruited from March 2013-November 2013. The main study variable was the prevalence of difficult venous access, assessed using one of the following criteria: (1) a history of difficulties obtaining venous access based on more than two attempts to insert an intravenous line and (2) no visible or palpable veins. Other factors potentially associated with the risk of difficult access were also measured (age, gender and chronic illnesses). Univariate analysis was performed for each potential risk factor. Factors with p < 0·2 were then included in multivariable logistic regression analysis. Odds ratios were also calculated. The prevalence of difficult venous access was 59·3%. The univariate logistic regression analysis indicated that gender, a history of vascular access complications and osteoarticular disease were significantly associated with difficult venous access. The multivariable logistic regression showed that only gender was an independent risk factor and the odds ratios was 2·85. The prevalence of difficult venous access is high in this population. Gender (female) is the only independent risk factor associated with this. Previous history of several attempts at catheter insertion is an important criterion in the assessment of difficult venous access. The prevalence of difficult venous access in complex patients is 59·3%. Significant risk factors include being female and a history of complications related to vascular access. © 2017 John Wiley & Sons Ltd.

Lithium and neuroleptics in combination: is there enhancement of neurotoxicity leading to permanent sequelae?

PubMed

Goldman, S A

1996-10-01

Neurotoxicity in relation to concomitant administration of lithium and neuroleptic drugs, particularly haloperidol, has been an ongoing issue. This study examined whether use of lithium with neuroleptic drugs enhances neurotoxicity leading to permanent sequelae. The Spontaneous Reporting System database of the United States Food and Drug Administration and extant literature were reviewed for spectrum cases of lithium/neuroleptic neurotoxicity. Groups taking lithium alone (Li), lithium/haloperidol (LiHal) and lithium/ nonhaloperidol neuroleptics (LiNeuro), each paired for recovery and sequelae, were established for 237 cases. Statistical analyses included pairwise comparisons of lithium levels using the Wilcoxon Rank Sum procedure and logistic regression to analyze the relationship between independent variables and development of sequelae. The Li and Li-Neuro groups showed significant statistical differences in median lithium levels between recovery and sequelae pairs, whereas the LiHal pair did not differ significantly. Lithium level was associated with sequelae development overall and within the Li and LiNeuro groups; no such association was evident in the LiHal group. On multivariable logistic regression analysis, lithium level and taking lithium/haloperidol were significant factors in the development of sequelae, with multiple possibly confounding factors (e.g., age, sex) not statistically significant. Multivariable logistic regression analyses with neuroleptic dose as five discrete dose ranges or actual dose did not show an association between development of sequelae and dose. Database limitations notwithstanding, the lack of apparent impact of serum lithium level on the development of sequelae in patients treated with haloperidol contrasts notably with results in the Li and LiNeuro groups. These findings may suggest a possible effect of pharmacodynamic factors in lithium/neuroleptic combination therapy.

Nailfold capillaroscopy for prediction of novel future severe organ involvement in systemic sclerosis.

PubMed

Smith, Vanessa; Riccieri, Valeria; Pizzorni, Carmen; Decuman, Saskia; Deschepper, Ellen; Bonroy, Carolien; Sulli, Alberto; Piette, Yves; De Keyser, Filip; Cutolo, Maurizio

2013-12-01

Assessment of associations of nailfold videocapillaroscopy (NVC) scleroderma (systemic sclerosis; SSc) ("early," "active," and "late") with novel future severe clinical involvement in 2 independent cohorts. Sixty-six consecutive Belgian and 82 Italian patients with SSc underwent NVC at baseline. Images were blindly assessed and classified into normal, early, active, or late NVC pattern. Clinical evaluation was performed for 9 organ systems (general, peripheral vascular, skin, joint, muscle, gastrointestinal tract, lung, heart, and kidney) according to the Medsger disease severity scale (DSS) at baseline and in the future (18-24 months of followup). Severe clinical involvement was defined as category 2 to 4 per organ of the DSS. Logistic regression analysis (continuous NVC predictor variable) was performed. The OR to develop novel future severe organ involvement was stronger according to more severe NVC patterns and similar in both cohorts. In simple logistic regression analysis the OR in the Belgian/Italian cohort was 2.16 (95% CI 1.19-4.47, p = 0.010)/2.33 (95% CI 1.36-4.22, p = 0.002) for the early NVC SSc pattern, 4.68/5.42 for the active pattern, and 10.14/12.63 for the late pattern versus the normal pattern. In multiple logistic regression analysis, adjusting for disease duration, subset, and vasoactive medication, the OR was 2.99 (95% CI 1.31-8.82, p = 0.007)/1.88 (95% CI 1.00-3.71, p = 0.050) for the early NVC SSc pattern, 8.93/3.54 for the active pattern, and 26.69/6.66 for the late pattern versus the normal pattern. Capillaroscopy may be predictive of novel future severe organ involvement in SSc, as attested by 2 independent cohorts.

[Obesity in Brazilian women: association with parity and socioeconomic status].

PubMed

Ferreira, Regicely Aline Brandão; Benicio, Maria Helena D'Aquino

2015-05-01

To determine the influence of reproductive history on the prevalence of obesity in Brazilian women and the possible modifying effect of socioeconomic variables on the association between parity and excess weight. A retrospective analysis of complex sample data collected as part of the 2006 Brazilian National Survey on Demography and Health, which included a group representative of women of childbearing age in Brazil was conducted. The study included 11 961 women aged 20 to 49 years. The association between the study factor (parity) and the outcome of interest (obesity) was tested using logistic regression analysis. The adjusted effect of parity on obesity was assessed in a multiple regression model containing control variables: age, family purchasing power, as defined by the Brazilian Association of Research Enterprises (ABEP), schooling, and health care. Significance level was set at below 0.05. The prevalence of obesity in the study population was 18.6%. The effect of parity on obesity was significant (P for trend < 0.001). Unadjusted analysis showed a positive association of obesity with parity and age. Family purchase power had a significant odds ratio for obesity only in the unadjusted analysis. In the adjusted model, this variable did not explain obesity. The present findings suggest that parity has an influence on obesity in Brazilian women of childbearing age, with higher prevalence in women vs. without children.

Dose response explorer: an integrated open-source tool for exploring and modelling radiotherapy dose volume outcome relationships

NASA Astrophysics Data System (ADS)

El Naqa, I.; Suneja, G.; Lindsay, P. E.; Hope, A. J.; Alaly, J. R.; Vicic, M.; Bradley, J. D.; Apte, A.; Deasy, J. O.

2006-11-01

Radiotherapy treatment outcome models are a complicated function of treatment, clinical and biological factors. Our objective is to provide clinicians and scientists with an accurate, flexible and user-friendly software tool to explore radiotherapy outcomes data and build statistical tumour control or normal tissue complications models. The software tool, called the dose response explorer system (DREES), is based on Matlab, and uses a named-field structure array data type. DREES/Matlab in combination with another open-source tool (CERR) provides an environment for analysing treatment outcomes. DREES provides many radiotherapy outcome modelling features, including (1) fitting of analytical normal tissue complication probability (NTCP) and tumour control probability (TCP) models, (2) combined modelling of multiple dose-volume variables (e.g., mean dose, max dose, etc) and clinical factors (age, gender, stage, etc) using multi-term regression modelling, (3) manual or automated selection of logistic or actuarial model variables using bootstrap statistical resampling, (4) estimation of uncertainty in model parameters, (5) performance assessment of univariate and multivariate analyses using Spearman's rank correlation and chi-square statistics, boxplots, nomograms, Kaplan-Meier survival plots, and receiver operating characteristics curves, and (6) graphical capabilities to visualize NTCP or TCP prediction versus selected variable models using various plots. DREES provides clinical researchers with a tool customized for radiotherapy outcome modelling. DREES is freely distributed. We expect to continue developing DREES based on user feedback.

Predictors of unsafe sexual behavior among people living with human immunodeficiency virus/AIDS attending antiretroviral therapy center in Western India.

PubMed

Mehta, Kedar G; Baxi, Rajendra; Chavda, Parag; Patel, Sangita; Mazumdar, Vihang

2016-01-01

As more and more people with human immunodeficiency virus (HIV) live longer and healthier lives because of antiretroviral therapy (ART), an increasing number of sexual transmissions of HIV may arise from these people living with HIV/AIDS (PLWHA). Hence, this study is conducted to assess the predictors of unsafe sexual behavior among PLWHA on ART in Western India. The current cross-sectional study was carried out among 175 PLWHAs attending ART center of a Tertiary Care Hospital in Western India. Unsafe sex was defined as inconsistent and/or incorrect condom use. A total of 39 variables from four domains viz., sociodemographic, relationship-related, medical and psycho-social factors were studied for their relationship to unsafe sexual behavior. The variables found to be significantly associated with unsafe sex practices in bivariate analysis were explored by multivariate analysis using multiple logistic regression in SPSS 17.0 version. Fifty-eight percentage of PLWHAs were practicing unsafe sex. 15 out of total 39 variables showed significant association in bivariate analysis. Finally, 11 of them showed significant association in multivariate analysis. Young age group, illiteracy, lack of counseling, misbeliefs about condom use, nondisclosure to spouse and lack of partner communication were the major factors found to be independently associated with unsafe sex in multivariate analysis. Appropriate interventions like need-based counseling are required to address risk factors associated with unsafe sex.

Social networks and self-rated health in two French-speaking Canadian community dwelling populations over 65.

PubMed

Zunzunegui, M V; Koné, A; Johri, M; Béland, F; Wolfson, C; Bergman, H

2004-05-01

The objective was to evaluate the associations between older persons' health status and their social integration and social networks (family, children, friends and community), in two French-speaking, Canadian community dwelling populations aged 65 years and over, using the conceptual framework proposed by Berkman and Thomas. Data were taken from two 1995 surveys conducted in the city of Moncton (n = 1518) and the Montreal neighbourhood of Hochelaga-Maisonneuve (n = 1500). Social engagement (a cumulative index of social activities), networks consisting of friends, family and children and social support were measured using validated scales. Multiple logistic regressions based on structured inclusion of potentially mediating variables were fitted to estimate the associations between health status and social networks. Self-rated health was better for those with a high level of social integration and a strong network of friends in both locations. In addition, in Hochelaga-Maisonneuve family and children networks were positively associated with good health, though the effect of friend networks was attenuated in the presence of disability, good social support from children was associated with good health. Age, sex and education were included as antecedent variables; smoking, alcohol consumption, exercise, locus of control and depressive symptoms were considered intermediary variables between social networks and health. In conclusion, social networks, integration and support demonstrated unique positive associations with health. The nature of these associations may vary between populations and cultures.

Association between alcohol advertising and beer drinking among adolescents.

PubMed

Faria, Roberta; Vendrame, Alan; Silva, Rebeca; Pinsky, Ilana

2011-06-01

To analyze the association between alcohol advertising and beer drinking among adolescents. A total of 1,115 students enrolled in the 7th and 8th grades of three public schools in São Bernardo do Campo, Southeastern Brazil, were interviewed in 2006. The independent variables were as follows: attention paid to alcohol advertisements, belief in the veracity of advertisements, affective response to advertisements and previous tobacco use, among others. The dependent variable was beer drinking in the last 30 days. Univariate and multiple logistic regression analyses were made. Age, importance given to religion and the presence of a bathroom in the home were used as control. Beer drinking in the last 30 days was associated with tobacco use (OR = 4.551), having a favorite alcoholic beverage brand (OR = 5.150), poor parental supervision (OR = 2.139), considering parties one goes to as similar to those seen in commercials (OR = 1.712), paying more attention to advertisements (OR = 1.563) and believing that advertisements tell the truth (OR = 2.122). This association remained, even in the presence of other variables associated with beer drinking. Alcohol advertisements are positively associated with recent beer drinking, because they remind adolescents of their own reality or make them believe in their veracity. Alcohol advertisement restrictions can be one way to prevent alcohol use and abuse by adolescents.

Too little sleep and an unhealthy diet could increase the risk of sustaining a new injury in adolescent elite athletes.

PubMed

von Rosen, P; Frohm, A; Kottorp, A; Fridén, C; Heijne, A

2017-11-01

Little is known about health variables and if these variables could increase the risk of injuries among adolescent elite athletes. The primary aim was to present overall data on self-perceived stress, nutrition intake, self-esteem, and sleep, as well as gender and age differences, on two occasions among adolescent elite athletes. A secondary aim was to study these health variables as potential risk factors on injury incidence. A questionnaire was e-mailed to 340 adolescent elite athletes on two occasions during a single school year: autumn semester and spring semester. The results show that during autumn semester, the recommended intake of fruits, vegetables, and fish was not met for 20%, 39%, and 43% of the adolescent elite athletes, respectively. The recommended amount of sleep during weekdays was not obtained by 19%. Multiple logistic regression showed that athletes sleeping more than 8 h of sleep during weekdays reduced the odds of injury with 61% (OR, 0.39; 95% CI, 0.16-0.99) and athletes reaching the recommended nutrition intake reduced the odds with 64% (OR, 0.36; 95% CI, 0.14-0.91). Our findings suggest that nutrition intake and sleep volume are of importance in understanding injury incidence. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Challenges of Measuring Glycemic Variability

PubMed Central

Rodbard, David

2012-01-01

This commentary reviews several of the challenges encountered when attempting to quantify glycemic variability and correlate it with risk of diabetes complications. These challenges include (1) immaturity of the field, including problems of data accuracy, precision, reliability, cost, and availability; (2) larger relative error in the estimates of glycemic variability than in the estimates of the mean glucose; (3) high correlation between glycemic variability and mean glucose level; (4) multiplicity of measures; (5) correlation of the multiple measures; (6) duplication or reinvention of methods; (7) confusion of measures of glycemic variability with measures of quality of glycemic control; (8) the problem of multiple comparisons when assessing relationships among multiple measures of variability and multiple clinical end points; and (9) differing needs for routine clinical practice and clinical research applications. PMID:22768904

Regularization Paths for Conditional Logistic Regression: The clogitL1 Package.

PubMed

Reid, Stephen; Tibshirani, Rob

2014-07-01

We apply the cyclic coordinate descent algorithm of Friedman, Hastie, and Tibshirani (2010) to the fitting of a conditional logistic regression model with lasso [Formula: see text] and elastic net penalties. The sequential strong rules of Tibshirani, Bien, Hastie, Friedman, Taylor, Simon, and Tibshirani (2012) are also used in the algorithm and it is shown that these offer a considerable speed up over the standard coordinate descent algorithm with warm starts. Once implemented, the algorithm is used in simulation studies to compare the variable selection and prediction performance of the conditional logistic regression model against that of its unconditional (standard) counterpart. We find that the conditional model performs admirably on datasets drawn from a suitable conditional distribution, outperforming its unconditional counterpart at variable selection. The conditional model is also fit to a small real world dataset, demonstrating how we obtain regularization paths for the parameters of the model and how we apply cross validation for this method where natural unconditional prediction rules are hard to come by.

Regularization Paths for Conditional Logistic Regression: The clogitL1 Package

PubMed Central

Reid, Stephen; Tibshirani, Rob

2014-01-01

We apply the cyclic coordinate descent algorithm of Friedman, Hastie, and Tibshirani (2010) to the fitting of a conditional logistic regression model with lasso (ℓ1) and elastic net penalties. The sequential strong rules of Tibshirani, Bien, Hastie, Friedman, Taylor, Simon, and Tibshirani (2012) are also used in the algorithm and it is shown that these offer a considerable speed up over the standard coordinate descent algorithm with warm starts. Once implemented, the algorithm is used in simulation studies to compare the variable selection and prediction performance of the conditional logistic regression model against that of its unconditional (standard) counterpart. We find that the conditional model performs admirably on datasets drawn from a suitable conditional distribution, outperforming its unconditional counterpart at variable selection. The conditional model is also fit to a small real world dataset, demonstrating how we obtain regularization paths for the parameters of the model and how we apply cross validation for this method where natural unconditional prediction rules are hard to come by. PMID:26257587

Ordinal logistic regression analysis on the nutritional status of children in KarangKitri village

NASA Astrophysics Data System (ADS)

Ohyver, Margaretha; Yongharto, Kimmy Octavian

2015-09-01

Ordinal logistic regression is a statistical technique that can be used to describe the relationship between ordinal response variable with one or more independent variables. This method has been used in various fields including in the health field. In this research, ordinal logistic regression is used to describe the relationship between nutritional status of children with age, gender, height, and family status. Nutritional status of children in this research is divided into over nutrition, well nutrition, less nutrition, and malnutrition. The purpose for this research is to describe the characteristics of children in the KarangKitri Village and to determine the factors that influence the nutritional status of children in the KarangKitri village. There are three things that obtained from this research. First, there are still children who are not categorized as well nutritional status. Second, there are children who come from sufficient economic level which include in not normal status. Third, the factors that affect the nutritional level of children are age, family status, and height.

Analysis of an Environmental Exposure Health Questionnaire in a Metropolitan Minority Population Utilizing Logistic Regression and Support Vector Machines

PubMed Central

Chen, Chau-Kuang; Bruce, Michelle; Tyler, Lauren; Brown, Claudine; Garrett, Angelica; Goggins, Susan; Lewis-Polite, Brandy; Weriwoh, Mirabel L; Juarez, Paul D.; Hood, Darryl B.; Skelton, Tyler

2014-01-01

The goal of this study was to analyze a 54-item instrument for assessment of perception of exposure to environmental contaminants within the context of the built environment, or exposome. This exposome was defined in five domains to include 1) home and hobby, 2) school, 3) community, 4) occupation, and 5) exposure history. Interviews were conducted with child-bearing-age minority women at Metro Nashville General Hospital at Meharry Medical College. Data were analyzed utilizing DTReg software for Support Vector Machine (SVM) modeling followed by an SPSS package for a logistic regression model. The target (outcome) variable of interest was respondent's residence by ZIP code. The results demonstrate that the rank order of important variables with respect to SVM modeling versus traditional logistic regression models is almost identical. This is the first study documenting that SVM analysis has discriminate power for determination of higher-ordered spatial relationships on an environmental exposure history questionnaire. PMID:23395953

Analysis of an environmental exposure health questionnaire in a metropolitan minority population utilizing logistic regression and Support Vector Machines.

PubMed

Chen, Chau-Kuang; Bruce, Michelle; Tyler, Lauren; Brown, Claudine; Garrett, Angelica; Goggins, Susan; Lewis-Polite, Brandy; Weriwoh, Mirabel L; Juarez, Paul D; Hood, Darryl B; Skelton, Tyler

2013-02-01

The goal of this study was to analyze a 54-item instrument for assessment of perception of exposure to environmental contaminants within the context of the built environment, or exposome. This exposome was defined in five domains to include 1) home and hobby, 2) school, 3) community, 4) occupation, and 5) exposure history. Interviews were conducted with child-bearing-age minority women at Metro Nashville General Hospital at Meharry Medical College. Data were analyzed utilizing DTReg software for Support Vector Machine (SVM) modeling followed by an SPSS package for a logistic regression model. The target (outcome) variable of interest was respondent's residence by ZIP code. The results demonstrate that the rank order of important variables with respect to SVM modeling versus traditional logistic regression models is almost identical. This is the first study documenting that SVM analysis has discriminate power for determination of higher-ordered spatial relationships on an environmental exposure history questionnaire.

Relaxing the rule of ten events per variable in logistic and Cox regression.

PubMed

Vittinghoff, Eric; McCulloch, Charles E

2007-03-15

The rule of thumb that logistic and Cox models should be used with a minimum of 10 outcome events per predictor variable (EPV), based on two simulation studies, may be too conservative. The authors conducted a large simulation study of other influences on confidence interval coverage, type I error, relative bias, and other model performance measures. They found a range of circumstances in which coverage and bias were within acceptable levels despite less than 10 EPV, as well as other factors that were as influential as or more influential than EPV. They conclude that this rule can be relaxed, in particular for sensitivity analyses undertaken to demonstrate adequate control of confounding.

Detecting Anomalies in Process Control Networks

NASA Astrophysics Data System (ADS)

Rrushi, Julian; Kang, Kyoung-Don

This paper presents the estimation-inspection algorithm, a statistical algorithm for anomaly detection in process control networks. The algorithm determines if the payload of a network packet that is about to be processed by a control system is normal or abnormal based on the effect that the packet will have on a variable stored in control system memory. The estimation part of the algorithm uses logistic regression integrated with maximum likelihood estimation in an inductive machine learning process to estimate a series of statistical parameters; these parameters are used in conjunction with logistic regression formulas to form a probability mass function for each variable stored in control system memory. The inspection part of the algorithm uses the probability mass functions to estimate the normalcy probability of a specific value that a network packet writes to a variable. Experimental results demonstrate that the algorithm is very effective at detecting anomalies in process control networks.

Binary logistic regression modelling: Measuring the probability of relapse cases among drug addict

NASA Astrophysics Data System (ADS)

Ismail, Mohd Tahir; Alias, Siti Nor Shadila

2014-07-01

For many years Malaysia faced the drug addiction issues. The most serious case is relapse phenomenon among treated drug addict (drug addict who have under gone the rehabilitation programme at Narcotic Addiction Rehabilitation Centre, PUSPEN). Thus, the main objective of this study is to find the most significant factor that contributes to relapse to happen. The binary logistic regression analysis was employed to model the relationship between independent variables (predictors) and dependent variable. The dependent variable is the status of the drug addict either relapse, (Yes coded as 1) or not, (No coded as 0). Meanwhile the predictors involved are age, age at first taking drug, family history, education level, family crisis, community support and self motivation. The total of the sample is 200 which the data are provided by AADK (National Antidrug Agency). The finding of the study revealed that age and self motivation are statistically significant towards the relapse cases..

Maximum likelihood estimation for predicting the probability of obtaining variable shortleaf pine regeneration densities

Treesearch

Thomas B. Lynch; Jean Nkouka; Michael M. Huebschmann; James M. Guldin

2003-01-01

A logistic equation is the basis for a model that predicts the probability of obtaining regeneration at specified densities. The density of regeneration (trees/ha) for which an estimate of probability is desired can be specified by means of independent variables in the model. When estimating parameters, the dependent variable is set to 1 if the regeneration density (...

Space Operations Center orbit altitude selection strategy

NASA Technical Reports Server (NTRS)

Indrikis, J.; Myers, H. L.

1982-01-01

The strategy for the operational altitude selection has to respond to the Space Operation Center's (SOC) maintenance requirements and the logistics demands of the missions to be supported by the SOC. Three orbit strategies are developed: two are constant altitude, and one variable altitude. In order to minimize the effect of atmospheric uncertainty the dynamic altitude method is recommended. In this approach the SOC will operate at the optimum altitude for the prevailing atmospheric conditions and logistics model, provided that mission safety constraints are not violated. Over a typical solar activity cycle this method produces significant savings in the overall logistics cost.

Selenium in irrigated agricultural areas of the western United States

USGS Publications Warehouse

Nolan, B.T.; Clark, M.L.

1997-01-01

A logistic regression model was developed to predict the likelihood that Se exceeds the USEPA chronic criterion for aquatic life (5 ??g/L) in irrigated agricultural areas of the western USA. Preliminary analysis of explanatory variables used in the model indicated that surface-water Se concentration increased with increasing dissolved solids (DS) concentration and with the presence of Upper Cretaceous, mainly marine sediment. The presence or absence of Cretaceous sediment was the major variable affecting Se concentration in surface-water samples from the National Irrigation Water Quality Program. Median Se concentration was 14 ??g/L in samples from areas underlain by Cretaceous sediments and < 1 ??g/L in samples from areas underlain by non-Cretaceous sediments. Wilcoxon rank sum tests indicated that elevated Se concentrations in samples from areas with Cretaceous sediments, irrigated areas, and from closed lakes and ponds were statistically significant. Spearman correlations indicated that Se was positively correlated with a binary geology variable (0.64) and DS (0.45). Logistic regression models indicated that the concentration of Se in surface water was almost certain to exceed the Environmental Protection Agency aquatic-life chronic criterion of 5 ??g/L when DS was greater than 3000 mg/L in areas with Cretaceous sediments. The 'best' logistic regression model correctly predicted Se exceedances and nonexceedances 84.4% of the time, and model sensitivity was 80.7%. A regional map of Cretaceous sediment showed the location of potential problem areas. The map and logistic regression model are tools that can be used to determine the potential for Se contamination of irrigated agricultural areas in the western USA.

School-Related Factors Affecting High School Seniors' Methamphetamine Use

ERIC Educational Resources Information Center

Stanley, Jarrod M.; Lo, Celia C.

2009-01-01

Data from the 2005 Monitoring the Future survey were used to examine relationships between school-related factors and high school seniors' lifetime methamphetamine use. The study applied logistic regression techniques to evaluate effects of social bonding variables and social learning variables on likelihood of lifetime methamphetamine use. The…

Assessment of Risk Factors of Intrauterine Adhesions in Patients With Induced Abortion and the Curative Effect of Hysteroscopic Surgery.

PubMed

Mo, Xiaoliang; Qin, Guirong; Zhou, Zhoulin; Jiang, Xiaoli

2017-10-03

To explore the risk factors for intrauterine adhesions in patients with artificial abortion and clinical efficacy of hysteroscopic dissection. 1500 patients undergoing artificial abortion between January 2014 and June 2015 were enrolled into this study. The patients were divided into two groups with or without intrauterine adhesions. Univariate and Multiple logistic regression were conducted to assess the effects of multiple factors on the development of intrauterine adhesions following induced abortion. The incidence rate for intrauterine adhesions following induced abortion is 17.0%. Univariate showed that preoperative inflammation, multiple pregnancies and suction evacuation time are the influence risk factors of intrauterine adhesions. Multiple logistic regression demonstrates that multiple pregnancies, high intrauterine negative pressure, and long suction evacuation time are independent risk factors for the development of intrauterine adhesions following induced abortion. Additionally, intrauterine adhesions were observed in 105 mild, 80 moderate, and 70 severe cases. The cure rates for these three categories of intrauterine adhesions by hysteroscopic surgery were 100.0%, 93.8%, and 85.7%, respectively. Multiple pregnancies, high negative pressure suction evacuation and long suction evacuation time are independent risk factors for the development of intrauterine adhesions following induced abortions. Hysteroscopic surgery substantially improves the clinical outcomes of intrauterine adhesions.

Multiple balance tests improve the assessment of postural stability in subjects with Parkinson's disease

PubMed Central

Jacobs, J V; Horak, F B; Tran, V K; Nutt, J G

2006-01-01

Objectives Clinicians often base the implementation of therapies on the presence of postural instability in subjects with Parkinson's disease (PD). These decisions are frequently based on the pull test from the Unified Parkinson's Disease Rating Scale (UPDRS). We sought to determine whether combining the pull test, the one‐leg stance test, the functional reach test, and UPDRS items 27–29 (arise from chair, posture, and gait) predicts balance confidence and falling better than any test alone. Methods The study included 67 subjects with PD. Subjects performed the one‐leg stance test, the functional reach test, and the UPDRS motor exam. Subjects also responded to the Activities‐specific Balance Confidence (ABC) scale and reported how many times they fell during the previous year. Regression models determined the combination of tests that optimally predicted mean ABC scores or categorised fall frequency. Results When all tests were included in a stepwise linear regression, only gait (UPDRS item 29), the pull test (UPDRS item 30), and the one‐leg stance test, in combination, represented significant predictor variables for mean ABC scores (r2 = 0.51). A multinomial logistic regression model including the one‐leg stance test and gait represented the model with the fewest significant predictor variables that correctly identified the most subjects as fallers or non‐fallers (85% of subjects were correctly identified). Conclusions Multiple balance tests (including the one‐leg stance test, and the gait and pull test items of the UPDRS) that assess different types of postural stress provide an optimal assessment of postural stability in subjects with PD. PMID:16484639

Spatial interpolation schemes of daily precipitation for hydrologic modeling

USGS Publications Warehouse

Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

2012-01-01

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

Prevalence of Pterygia in Hawaii: Examining Cumulative Surfing Hours as a Risk Factor.

PubMed

Lin, Alexander D; Miles, Ku'ulei; Brinks, Mitchel V

2016-08-01

To examine the association between surfing and pterygium prevalence in Hawaii. A convenience sampling was performed at four beaches on the island of Oahu, Hawaii. A total of 169 individuals were interviewed and underwent penlight examination to assess grade and extent of pterygium. Of 169 participants aged 18-80 years, 88 non-surfers, 41 occasional surfers, 15 recreational surfers and 25 surfing enthusiasts were identified based on their lifetime surfing hours. Overall, 19 participants were found to have pterygia (28 pterygia total) including two non-surfers (2.3%), five occasional surfers (12.2%), three recreational surfers (20.0%), and nine enthusiast surfers (36.0%). Variables associated with pterygium prevalence were lifetime surfing hours (p < 0.0001), outdoor occupation (p = 0.04), Hawaiian residence (p = 0.009), and Hawaiian/Pacific Islander ethnicity (p = 0.002). Multiple logistic regression with the outcome of pterygium was performed, along with multiple linear regression for the continuous outcomes of corneal extent, chord length, and apex-visual axis gap, with lifetime surfing hours as the primary explanatory variable. After adjustment for confounders, a significant linear relationship was observed between chord length and lifetime surfing hours (p = 0.01). Surfing was associated with an increased pterygium prevalence and trend towards an association with increased pterygium severity. Increased risk of exposure to wind, particle irritation, and ultraviolet (UV) radiation while surfing may contribute to pterygium development. Implications for public health include promoting UV protective eyewear during surfing, in addition to raising awareness about the association of pterygia and the sport of surfing.

Are the frail destined to fail? Frailty index as predictor of surgical morbidity and mortality in the elderly.

PubMed

Farhat, Joseph S; Velanovich, Vic; Falvo, Anthony J; Horst, H Mathilda; Swartz, Andrew; Patton, Joe H; Rubinfeld, Ilan S

2012-06-01

America's aging population has led to an increase in the number of elderly patients necessitating emergency general surgery. Previous studies have demonstrated that increased frailty is a predictor of outcomes in medicine and surgical patients. We hypothesized that use of a modification of the Canadian Study of Health and Aging Frailty Index would be a predictor of morbidity and mortality in patients older than 60 years undergoing emergency general surgery. Data were obtained from the National Surgical Quality Improvement Program Participant Use Files database in compliance with the National Surgical Quality Improvement Program Data Use Agreement. We selected all emergency cases in patients older than 60 years performed by general surgeons from 2005 to 2009. The effect of increasing frailty on multiple outcomes including wound infection, wound occurrence, any infection, any occurrence, and mortality was then evaluated. Total sample size was 35,334 patients. As the modified frailty index increased, associated increases occurred in wound infection, wound occurrence, any infection, any occurrence, and mortality. Logistic regression of multiple variables demonstrated that the frailty index was associated with increased mortality with an odds ratio of 11.70 (p < 0.001). Frailty index is an important predictive variable in emergency general surgery patients older than 60 years. The modified frailty index can be used to evaluate risk of both morbidity and mortality in these patients. Frailty index will be a valuable preoperative risk assessment tool for the acute care surgeon. Prognostic study, level II. Copyright © 2012 by Lippincott Williams & Wilkins

Use of multiple-locus variable-number tandem repeat analysis to evaluate Escherichia coli O157 subtype distribution and transmission dynamics following natural exposure on a closed beef feedlot facility.

PubMed

Williams, Michele L; Pearl, David L; Bishop, Katherine E; Lejeune, Jeffrey T

2013-10-01

To better understand the epizootiology of Escherichia coli O157:H7 among cattle, all E. coli O157 isolates recovered on a research feedlot during a single feeding period were characterized by multiple-locus variable-number tandem repeat analysis (MLVA). Three distinct MLVA subtypes (A, B, C), accounting for 24%, 15%, and 64% of total isolates, respectively, were identified. Subtypes A and B were isolated at the initiation of sampling, but their prevalence waned and subtype C, first isolated on the third sampling date, became the predominant subtype on the feedlot. Supershedding events, however, occurred with equal frequency for all three MLVA-types. Using a multilevel logistic regression model, we investigated whether the odds of shedding subtype C relative to subtypes A or B were associated with time, diet, or the presence of a penmate shedding high numbers of subtype C. Only time and exposure to an animal shedding MLVA-type C at 10³ colony-forming units or greater in the pen at the time of sampling were significantly associated with increased shedding of subtype C. High-level shedding of those E. coli O157 subtypes better suited for survival in the environment and/or in the host appear to play a significant role in the development of predominant E. coli O157 subtypes. Supershedding events alone are neither required nor sufficient to drive the epidemiology of specific E. coli O157 subtypes. Additional factors are necessary to direct successful on-farm transmission of E. coli O157.

Combining biological and psychosocial baseline variables did not improve prediction of outcome of a very-low-energy diet in a clinic referral population.

PubMed

Sumithran, P; Purcell, K; Kuyruk, S; Proietto, J; Prendergast, L A

2018-02-01

Consistent, strong predictors of obesity treatment outcomes have not been identified. It has been suggested that broadening the range of predictor variables examined may be valuable. We explored methods to predict outcomes of a very-low-energy diet (VLED)-based programme in a clinically comparable setting, using a wide array of pre-intervention biological and psychosocial participant data. A total of 61 women and 39 men (mean ± standard deviation [SD] body mass index: 39.8 ± 7.3 kg/m 2 ) underwent an 8-week VLED and 12-month follow-up. At baseline, participants underwent a blood test and assessment of psychological, social and behavioural factors previously associated with treatment outcomes. Logistic regression, linear discriminant analysis, decision trees and random forests were used to model outcomes from baseline variables. Of the 100 participants, 88 completed the VLED and 42 attended the Week 60 visit. Overall prediction rates for weight loss of ≥10% at weeks 8 and 60, and attrition at Week 60, using combined data were between 77.8 and 87.6% for logistic regression, and lower for other methods. When logistic regression analyses included only baseline demographic and anthropometric variables, prediction rates were 76.2-86.1%. In this population, considering a wide range of biological and psychosocial data did not improve outcome prediction compared to simply-obtained baseline characteristics. © 2017 World Obesity Federation.

An investigation on fatality of drivers in vehicle-fixed object accidents on expressways in China: Using multinomial logistic regression model.

PubMed

Peng, Yong; Peng, Shuangling; Wang, Xinghua; Tan, Shiyang

2018-06-01

This study aims to identify the effects of characteristics of vehicle, roadway, driver, and environment on fatality of drivers in vehicle-fixed object accidents on expressways in Changsha-Zhuzhou-Xiangtan district of Hunan province in China by developing multinomial logistic regression models. For this purpose, 121 vehicle-fixed object accidents from 2011-2017 are included in the modeling process. First, descriptive statistical analysis is made to understand the main characteristics of the vehicle-fixed object crashes. Then, 19 explanatory variables are selected, and correlation analysis of each two variables is conducted to choose the variables to be concluded. Finally, five multinomial logistic regression models including different independent variables are compared, and the model with best fitting and prediction capability is chosen as the final model. The results showed that the turning direction in avoiding fixed objects raised the possibility that drivers would die. About 64% of drivers died in the accident were found being ejected out of the car, of which 50% did not use a seatbelt before the fatal accidents. Drivers are likely to die when they encounter bad weather on the expressway. Drivers with less than 10 years of driving experience are more likely to die in these accidents. Fatigue or distracted driving is also a significant factor in fatality of drivers. Findings from this research provide an insight into reducing fatality of drivers in vehicle-fixed object accidents.

Serum magnesium but not calcium was associated with hemorrhagic transformation in stroke overall and stroke subtypes: a case-control study in China.

PubMed

Tan, Ge; Yuan, Ruozhen; Wei, ChenChen; Xu, Mangmang; Liu, Ming

2018-05-26

Association between serum calcium and magnesium versus hemorrhagic transformation (HT) remains to be identified. A total of 1212 non-thrombolysis patients with serum calcium and magnesium collected within 24 h from stroke onset were enrolled. Backward stepwise multivariate logistic regression analysis was conducted to investigate association between calcium and magnesium versus HT. Calcium and magnesium were entered into logistic regression analysis in two models, separately: model 1, as continuous variable (per 1-mmol/L increase), and model 2, as four-categorized variable (being collapsed into quartiles). HT occurred in 140 patients (11.6%). Serum calcium was slightly lower in patients with HT than in patient without HT (P = 0.273). But serum magnesium was significantly lower in patients with HT than in patients without HT (P = 0.007). In logistic regression analysis, calcium displayed no association with HT. Magnesium, as either continuous or four-categorized variable, was independently and inversely associated with HT in stroke overall and stroke of large-artery atherosclerosis (LAA). The results demonstrated that serum calcium had no association with HT in patients without thrombolysis after acute ischemic stroke. Serum magnesium in low level was independently associated with increasing HT in stroke overall and particularly in stroke of LAA.

Item Response Theory Modeling of the Philadelphia Naming Test.

PubMed

Fergadiotis, Gerasimos; Kellough, Stacey; Hula, William D

2015-06-01

In this study, we investigated the fit of the Philadelphia Naming Test (PNT; Roach, Schwartz, Martin, Grewal, & Brecher, 1996) to an item-response-theory measurement model, estimated the precision of the resulting scores and item parameters, and provided a theoretical rationale for the interpretation of PNT overall scores by relating explanatory variables to item difficulty. This article describes the statistical model underlying the computer adaptive PNT presented in a companion article (Hula, Kellough, & Fergadiotis, 2015). Using archival data, we evaluated the fit of the PNT to 1- and 2-parameter logistic models and examined the precision of the resulting parameter estimates. We regressed the item difficulty estimates on three predictor variables: word length, age of acquisition, and contextual diversity. The 2-parameter logistic model demonstrated marginally better fit, but the fit of the 1-parameter logistic model was adequate. Precision was excellent for both person ability and item difficulty estimates. Word length, age of acquisition, and contextual diversity all independently contributed to variance in item difficulty. Item-response-theory methods can be productively used to analyze and quantify anomia severity in aphasia. Regression of item difficulty on lexical variables supported the validity of the PNT and interpretation of anomia severity scores in the context of current word-finding models.

Application of a Multidimensional Nested Logit Model to Multiple-Choice Test Items

ERIC Educational Resources Information Center

Bolt, Daniel M.; Wollack, James A.; Suh, Youngsuk

2012-01-01

Nested logit models have been presented as an alternative to multinomial logistic models for multiple-choice test items (Suh and Bolt in "Psychometrika" 75:454-473, 2010) and possess a mathematical structure that naturally lends itself to evaluating the incremental information provided by attending to distractor selection in scoring. One potential…

Primary Factors Related to Multiple Placements for Children in Out-of-Home Care

ERIC Educational Resources Information Center

Eggertsen, Lars

2008-01-01

Using an ecological framework, this study identified which factors related to out-of-home placements significantly influenced multiple placements for children in Utah during 2000, 2001, and 2002. Multinomial logistic regression statistical procedures and a geographical information system (GIS) were used to analyze the data. The final model…

The Effectiveness of Using a Multiple Gating Approach to Discriminate among ADHD Subtypes

ERIC Educational Resources Information Center

Simonsen, Brandi M.; Bullis, Michael D.

2007-01-01

This study explored the ability of Systematically Progressive Assessment (SPA), a multiple gating approach for assessing students with attention-deficit/hyperactivity disorder (ADHD), to discriminate between subtypes of ADHD. A total of 48 students with ADHD (ages 6-11) were evaluated with three "gates" of assessment. Logistic regression analysis…

The impact of multi-morbidity on disability among older adults in South Africa: do hypertension and socio-demographic characteristics matter?

PubMed

Waterhouse, Philippa; van der Wielen, Nele; Banda, Pamela Chirwa; Channon, Andrew Amos

2017-04-08

Alongside the global population ageing phenomenon, there has been a rise in the number of individuals who suffer from multiple chronic conditions. Taking the case of South Africa, this study aims, first, to investigate the association between multi-morbidity and disability among older adults; and second, to examine whether hypertension (both diagnosed and undiagnosed) mediates this relationship. Lastly, we consider whether the impact of the multi-morbidity on disability varies by socio-demographic characteristics. Data were drawn from Wave 1 (2007-08) of the South African Study on Global Ageing and Adult Health. Disability was measured using the 12-item World Health Organisation Disability Assessment Schedule (WHODAS) 2.0. Scores were transformed into a binary variable whereby those over the 90 th percentile were classified as having a severe disability. The measure of multi-morbidity was based on a simple count of self-reported diagnosis of selected chronic conditions. Self-reports of diagnosed hypertension, in addition to blood pressure measurements at the time of interview, were used to create a three category hypertension variable: no hypertension (diagnosed or measured), diagnosed hypertension, hypertension not diagnosed but hypertensive measured blood pressure. Interactions between the number of chronic diseases with sex, ethnicity and wealth were tested. Logistic regression was used to analyze the relationships. 25.4% of the final sample had one and 13.2% two or more chronic diseases. Nearly half of the respondents had a hypertensive blood pressure when measured during the interview, but had not been previously diagnosed. A further third self-reported they had been told by a health professional they had hypertension. The logistic regression showed in comparison to those with no chronic conditions, those with one or two or more had significantly higher odds of severe disability. Hypertension was insignificant and did not change the direction or size of the effect of the multi-morbidity measure substantially. The interactions between number of chronic conditions with wealth were significant at the 5% level. The diagnosis of multiple chronic conditions, can be used to identify those most at risk of severe disability. Limited resources should be prioritized for such individuals in terms of preventative, rehabilitative and palliative care.

Return-to-work of sick-listed workers without an employment contract – what works?

PubMed Central

Vermeulen, Sylvia J; Tamminga, Sietske J; Schellart, Antonius JM; Ybema, Jan Fekke; Anema, Johannes R

2009-01-01

Background In the past decade flexible labour market arrangements have emerged as a significant change in the European Union labour market. Studies suggest that these new types of labour arrangements may be linked to ill health, an increased risk for work disability, and inadequate vocational rehabilitation. Therefore, the objectives of this study were: 1. to examine demographic characteristics of workers without an employment contract sick-listed for at least 13 weeks, 2. to describe the content and frequency of occupational health care (OHC) interventions for these sick-listed workers, and 3. to examine OHC interventions as possible determinants for return-to-work (RTW) of these workers. Methods A cohort of 1077 sick-listed workers without an employment contract were included at baseline, i.e. 13 weeks after reporting sick. Demographic variables were available at baseline. Measurement of cross-sectional data took place 4–6 months after inclusion. Primary outcome measures were: frequency of OHC interventions and RTW-rates. Measured confounding variables were: gender, age, type of worker (temporary agency worker, unemployed worker, or remaining worker without employment contract), level of education, reason for absenteeism (diagnosis), and perceived health. The association between OHC interventions and RTW was analysed with a logistic multiple regression analysis. Results At 7–9 months after the first day of reporting sick only 19% of the workers had (partially or completely) returned to work, and most workers perceived their health as fairly poor or poor. The most frequently reported (49%) intervention was 'the OHC professional discussed RTW'. However, the intervention 'OHC professional made and discussed a RTW action plan' was reported by only 19% of the respondents. The logistic multiple regression analysis showed a significant positive association between RTW and the interventions: 'OHC professional discussed RTW'; and 'OHC professional made and discussed a RTW action plan'. The intervention 'OHC professional referred sick-listed worker to a vocational rehabilitation agency' was significantly associated with no RTW. Conclusion This is the first time that characteristics of a large cohort of sick-listed workers without an employment contract were examined. An experimental or prospective study is needed to explore the causal nature of the associations found between OHC interventions and RTW. PMID:19602219

Risk factors of fatal occupational accidents in Iran.

PubMed

Asady, Hadi; Yaseri, Mehdi; Hosseini, Mostafa; Zarif-Yeganeh, Morvarid; Yousefifard, Mahmoud; Haghshenas, Mahin; Hajizadeh-Moghadam, Parisa

2018-01-01

Occupational accidents are of most important consequences of globalization in developing countries. Therefore, investigating the causes of occupational accidents for improving the job situation and making operational policy is necessary. So the aim of this study was to investigate factors affecting the fatal occupational accidents and also calculate the years of life lost for dead workers. This cross-sectional study was conducted on data related to the 6052 injured workers that was registered in the 2013 registry system of the Ministry of Health and Medical Education of Iran. Variables including sex, education, age, job tenure, injury cause, referred location of injured workers, occupation, shift work, season, accident day, damaged part of the body were chosen as independent variables. The Chi-squared and Fisher exact tests were used for univariate analysis and then exact multiple logistic regression was carried out to identify independent risk factors of fatal occupational accidents. Finally, for dead workers, years of life lost, according to the injury causes was calculated. Among the 6052 accidents reported, 33 deaths were recorded. Chi-square and Fisher exact tests showed that factors including: current job tenure ( p  = 0.01), damaged parts of the body ( p  < 0.001) and injury cause ( p  < 0.001) are associated with the fatal accidents. Also exact multiple logistic regression analysis showed a significant association between electric shocks as a cause of injury (OR = 7.04; 95% CI: 1.01-43.74; p  = 0.02) and current job tenure more than 1 year (OR = 0.21; 95% CI: 0.05-0.70; p  = 0.005) with the fatal accidents. The total amount of years of life lost based on causes of injuries was estimated 1289.12 years. In Iran, fatal accident odds in workers with job tenure more than 1 year was less in comparing to the workers with job tenure less and equal to 1 year. Also odd of death for electrical shock was more than other causes of injuries. So it seems that employing of workers who have more than one-year work experience in a specific job and using of appropriate safeguards will be useful for the reducing of fatal occupational accidents.

Artificialized land characteristics and sediment connectivity explain muddy flood hazard in Wallonia

NASA Astrophysics Data System (ADS)

de Walque, Baptiste; Bielders, Charles; Degré, Aurore; Maugnard, Alexandre

2017-04-01

Muddy flood occurrence is an off-site erosion problem of growing interest in Europe and in particular in the loess belt and Condroz regions of Wallonia (Belgium). In order to assess the probability of occurrence of muddy floods in specific places, a muddy flood hazard prediction model has been built. It was used to test 11 different explanatory variables in simple and multiple logistic regressions approaches. A database of 442 muddy flood-affected sites and an equal number of homologous non flooded sites was used. For each site, relief, land use, sediment production and sediment connectivity of the contributing area were extracted. To assess the prediction quality of the model, we proceeded to a validation using 48 new pairs of homologous sites. Based on Akaïke Information Criterion (AIC), we determined that the best muddy flood hazard assessment model requires a total of 6 explanatory variable as inputs: the spatial aggregation of the artificialized land, the sediment connectivity, the artificialized land proximity to the outlet, the proportion of artificialized land, the mean slope and the Gravelius index of compactness of the contributive area. The artificialized land properties listed above showed to improve substantially the model quality (p-values from 10e-10 to 10e-4). All of the 3 properties showed negative correlation with the muddy flood hazard. These results highlight the importance of considering the artificialized land characteristics in the sediment transport assessment models. Indeed, artificialized land such as roads may dramatically deviate flows and influence the connectivity in the landscape. Besides the artificialized land properties, the sediment connectivity showed significant explanatory power (p-value of 10e-11). A positive correlation between the sediment connectivity and the muddy flood hazard was found, ranging from 0.3 to 0.45 depending on the sediment connectivity index. Several studies already have highlighted the importance of this parameter in the sediment transport characterization in the landscape. Using the best muddy flood probability of occurrence threshold value of 0.49, the validation of the best multiple logistic regression resulted in a prediction quality of 75.6% (original dataset) and 81.2% (secondary dataset). The developed statistical model could be used as a reliable tool to target muddy floods mitigation measures in sites resulting with the highest muddy floods hazard.

A generation at risk: a cross-sectional study on HIV/AIDS knowledge, exposure to mass media, and stigmatizing behaviors among young women aged 15-24 years in Ghana.

PubMed

Asamoah, Charity Konadu; Asamoah, Benedict Oppong; Agardh, Anette

2017-01-01

HIV/AIDS stigmatizing behaviors are a huge barrier to early detection and treatment of individuals with the AIDS virus. HIV/AIDS stigma and related consequences are debilitating, especially for vulnerable populations. This study sought to assess whether young women's HIV/AIDS knowledge levels and exposure to mass media (television and radio) have an influence on their stigmatizing behaviors and role as agents of stigma towards individuals living with HIV and AIDS. The data used for this study originated from the Ghana Multiple Indicator Cluster Survey 2011. Binary and multiple (stepwise) logistic regression analyses were used to examine the associations between HIV/AIDS knowledge, frequency of exposure to mass media, and HIV/AIDS stigmatizing behaviors among young women aged 15-24 years in Ghana. Of the 3573 young women, 80% of 15-19-year-olds and 76% of 20-24-year-olds had at least one stigmatizing behavior towards persons living with HIV/AIDS (PLHA). Young women with increased knowledge regarding HIV/AIDS and frequent exposure to mass media (television and radio) had lesser tendency to stigmatize or act as agents of stigma towards PLHA (proportion with at least one stigmatizing behavior per subgroup - HIV/AIDS knowledge: those with highest knowledge score 579 [70.1%], those with lowest knowledge score 28 [90.3%]; mass media: those with daily exposure 562 [73.4%], those not exposed at all 249 [89.2%]). There was a graded negative 'exposure-response' association between the ranked variables: HIV/AIDS knowledge, mass media, and HIV/AIDS stigmatizing behaviors. The significant inverse association between HIV/AIDS knowledge, frequency of exposure to mass media, and HIV/AIDS stigmatizing behaviors persisted even after adjusting for all other covariates in the multiple logistic regression models. It is extremely important to increase HIV/AIDS-related knowledge and reduce stigma among young women in Ghana through targeted HIV/AIDS factual knowledge transfer. The use of mass media for communication of issues regarding HIV/AIDS, its mode of transmission, and associated stigma should be emphasized among women in Ghana.

Physical fitness of 9 year olds in England: related factors.

PubMed

Kikuchi, S; Rona, R J; Chinn, S

1995-04-01

To examine the influence of social factors, passive smoking, and other parental health related factors, as well as anthropometric and other measurements on children's cardiorespiratory fitness. This was a cross sectional study. The analysis was based on 22 health areas in England. The subjects were 299 boys and 282 girls aged 8 to 9 years. Parents did not give positive consent for 15% of the eligible sample. A further 25% of the eligible sample did not participate because the cycle-ergometer broke down, study time was insufficient, or they were excluded from the analysis because they were from ethnic minority groups or had missing data on one continuous variable. Cardiorespiratory fitness was determined using the cycle-ergometer test. It was measured in terms of PWC85%-that is, power output per body weight (watt/kg) assessed at 85% of maximum heart rate. The association between children's fitness and biological and social factors was analysed in two stages. Firstly, multiple logistic analysis was used to examine the factors associated with the children's ability to complete the test for at least four minutes. Secondly, multiple linear regression analysis was used to examine the independent association of the factors with PWC85%. In the logistic analysis, shorter children, children with higher blood pressure, and boys with a larger sibship size had poorer fitness. In the multiple regression analysis, only height (p < 0.001) was positively associated, and the sum of skinfold thicknesses at four sites (p = 0.001) was negatively associated with fitness in both sexes. In girls, a positive association was found with pre-exercise peak expiratory flow rate (p < 0.05), and there were negative associations with systolic blood pressure (p < 0.05) and family history of heart attack (p < 0.05). In boys an association was found with skinfold distribution and fitness (p < 0.05), so that children with relatively less body fat were fitter. Social and health behaviour factors such as father's social class, father's employment status, or parents' smoking habits were unrelated to child's fitness. Height and obesity are strongly associated, and systolic blood pressure to a small extent, with children's fitness, but social factors are unrelated.

Association between Triglyceride to HDL-C Ratio (TG/HDL-C) and Insulin Resistance in Chinese Patients with Newly Diagnosed Type 2 Diabetes Mellitus

PubMed Central

Ren, Xingxing; Chen, Zeng.ai; Zheng, Shuang; Han, Tingting; Li, Yangxue; Liu, Wei; Hu, Yaomin

2016-01-01

Objectives To explore the association between the triglyceride to HDL-C ratio (TG/HDL-C) and insulin resistance in Chinese patients with newly diagnosed type 2 diabetes mellitus. Methods Patients with newly diagnosed type 2 diabetes mellitus (272 men and 288 women) were enrolled and divided into three groups according to TG/HDL-C tertiles. Insulin resistance was defined by homeostatic model assessment of insulin resistance (HOMA-IR). Demographic information and clinical characteristics were obtained. Spearman’s correlation was used to estimate the association between TG/HDL-C and other variables. Multiple logistic regression analyses were adopted to obtain probabilities of insulin resistance. A receiver operating characteristic analysis was conducted to evaluate the ability of TG/HDL-C to discriminate insulin resistance. Results TG/HDL-C was associated with insulin resistance in Chinese patients with newly diagnosed T2DM (Spearman’s correlation coefficient = 0.21, P < 0.01). Patients in the higher tertiles of TG/HDL-C had significantly higher HOMA-IR values than patients in the lower tertiles [T1: 2.68(1.74–3.70); T2: 2.96(2.29–4.56); T3: 3.09(2.30–4.99)]. Multiple logistic regression analysis showed that TG/HDL-C was significantly associated with HOMA-IR, and patients in the higher TG/HDL-C tertile had a higher OR than those in the lower TG/HDL-C tertile, after adjusting for multiple covariates including indices for central obesity [T1: 1; T2: 4.02(1.86–8.71); T3: 4.30(1.99–9.29)]. Following stratification of waist circumference into quartiles, the effect of TG/HDL-C on insulin resistance remained significant irrespective of waist circumference. Conclusions TG/HDL-C was associated with insulin resistance independent of waist circumference. Whether it could be a surrogate marker for insulin resistance in Chinese patients with newly diagnosed type 2 diabetes mellitus still needs to be confirmed by more researches. PMID:27115999

Two models for evaluating landslide hazards

USGS Publications Warehouse

Davis, J.C.; Chung, C.-J.; Ohlmacher, G.C.

2006-01-01

Two alternative procedures for estimating landslide hazards were evaluated using data on topographic digital elevation models (DEMs) and bedrock lithologies in an area adjacent to the Missouri River in Atchison County, Kansas, USA. The two procedures are based on the likelihood ratio model but utilize different assumptions. The empirical likelihood ratio model is based on non-parametric empirical univariate frequency distribution functions under an assumption of conditional independence while the multivariate logistic discriminant model assumes that likelihood ratios can be expressed in terms of logistic functions. The relative hazards of occurrence of landslides were estimated by an empirical likelihood ratio model and by multivariate logistic discriminant analysis. Predictor variables consisted of grids containing topographic elevations, slope angles, and slope aspects calculated from a 30-m DEM. An integer grid of coded bedrock lithologies taken from digitized geologic maps was also used as a predictor variable. Both statistical models yield relative estimates in the form of the proportion of total map area predicted to already contain or to be the site of future landslides. The stabilities of estimates were checked by cross-validation of results from random subsamples, using each of the two procedures. Cell-by-cell comparisons of hazard maps made by the two models show that the two sets of estimates are virtually identical. This suggests that the empirical likelihood ratio and the logistic discriminant analysis models are robust with respect to the conditional independent assumption and the logistic function assumption, respectively, and that either model can be used successfully to evaluate landslide hazards. ?? 2006.

Should "Multiple Imputations" Be Treated as "Multiple Indicators"?

ERIC Educational Resources Information Center

Mislevy, Robert J.

1993-01-01

Multiple imputations for latent variables are constructed so that analyses treating them as true variables have the correct expectations for population characteristics. Analyzing multiple imputations in accordance with their construction yields correct estimates of population characteristics, whereas analyzing them as multiple indicators generally…

Impact of different approaches of primary care mental health on the prevalence of mental disorders.

PubMed

Moscovici, Leonardo; de Azevedo-Marques, Joao Mazzoncini; Bolsoni, Lívia Maria; Rodrigues-Junior, Antonio Luiz; Zuardi, Antonio Waldo

2018-05-01

AimTo compare the impact of three different approaches to primary care mental health on the prevalence of mental disorders. Millions of people suffer from mental disorders. As entry point into the health service, primary healthcare plays an important role in providing mental health prevention and treatment. Random sample of households in three different areas of the city of Ribeirão Preto (state of São Paulo, Brazil) were selected, and 20 trained medical students conducted interviews using a mental health screening instrument, the Mini-Screening of Mental Disorders, and a socio-demographic datasheet. Primary care mental health was provided in each area through a specific approach. The influence of the area of residence and the socio-demographic variables on the prevalence of mental disorder was explored and analyzed by univariate binary logistic regression and then by a multiple logistic regression model.FindingsA total of 1545 subjects were interviewed. Comparison between the three areas showed a significantly higher number of people with mental disorders in the area covered by the primary care team that did not have physicians with specific primary care mental health training, even when this association was adjusted for the influence of age, education, and socio-economic status.Our results suggest that residing in areas with family physicians with mental health training is associated with a lower prevalence of mental disorders.

[Biodiversity and depressive symptoms in Mexican adults: Exploration of beneficial environmental effects].

PubMed

Duarte-Tagles, Héctor; Salinas-Rodríguez, Aarón; Idrovo, Álvaro J; Búrquez, Alberto; Corral-Verdugo, Víctor

2015-08-01

Depression is a highly prevalent illness among adults, and it is the second most frequently reported mental disorder in urban settings in México. Exposure to natural environments and its components may improve the mental health of the population. To evaluate the association between biodiversity indicators and the prevalence of depressive symptoms among the adult population (20 to 65 years of age) in México. Information from the Encuesta Nacional de Salud y Nutrición 2006 (ENSANUT 2006) and the Compendio de Estadísticas Ambientales 2008 was analyzed. A biodiversity index was constructed based on the species richness and ecoregions in each state. A multilevel logistic regression model was built with random intercepts and a multiple logistic regression was generated with clustering by state. The factors associated with depressive symptoms were being female, self-perceived as indigenous, lower education level, not living with a partner, lack of steady paid work, having a chronic illness and drinking alcohol. The biodiversity index was found to be inversely associated with the prevalence of depressive symptoms when defined as a continuous variable, and the results from the regression were grouped by state (OR=0.71; 95% CI = 0.59-0.87). Although the design was cross-sectional, this study adds to the evidence of the potential benefits to mental health from contact with nature and its components.

Metabolic outcomes of workers according to the International Standard Classification of Occupations in Korea.

PubMed

Lee, Wanhyung; Yeom, Hyungseon; Yoon, Jin-Ha; Won, Jong-Uk; Jung, Pil Kyun; Lee, June-Hee; Seok, Hongdeok; Roh, Jaehoon

2016-08-01

Occupation influences the risk for developing chronic metabolic diseases. We compared the prevalence of MetS by International Standard Classification of Occupations using the nationally representative data in Korea (KNHANES). We enrolled 16,763 workers (9,175 males; 7,588 females) who had measurements for the National Cholesterol Education Program criteria III and other variables. OR and 95%CIs for MetS and its components were estimated according to occupation using the multiple logistic regression models. The occupational groups with the highest age-standardized prevalence of MetS were lower skilled white-collar men (31.1 ± 2.4%) and green-collar women (24.2 ± 2.9%). Compared with the unskilled male blue-collar group, which had the lowest prevalence of MetS, the OR (95%CIs) of MetS in men were 1.77 (1.45-2.15) in higher skilled white-collar, 1.82 (1.47-2.26) in lower-skilled white-collar, 1.63 (1.32-2.01) in pink-collar and 1.37 (1.13-1.66) in skilled blue-collar workers in final logistic regression model. MetS and its components vary by occupational category and gender in ways that may guide health interventions. Am. J. Ind. Med. 59:685-694, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

[Characteristics of elderly leaders volunteering to participate in a fall prevention programme].

PubMed

Shimanuki, Hideki; Ueki, Shouzoh; Ito, Tunehisa; Honda, Haruhiko; Takato, Jinro; Kasai, Toshiyuki; Sakamoto, Yuzuru; Niino, Naoakira; Haga, Hiroshi

2005-09-01

This study was conducted to assess characteristics of elderly leaders volunteering to participate in a fall prevention programme. We surveyed 1,503 individuals (75 elderly leaders volunteering to participate in a fall prevention programme and 1,428 non-leader elderly) among the elderly population living in a rural community, Miyagi Prefecture. Subjects were aged 70-84 years. The questionnaire covered socio-demographic factors, as well as physical, psychology and social variables. To analyze the characteristics of the elderly leaders volunteering to participate in this programme, the relationships of socio-demographic, physical, psychology and social factors to whether the elderly were leaders in the programme were analyzed using logistic regression. As a result of multiple logistic regression analysis, the characteristics of elderly leaders volunteering to participate in the fall prevention programme were as follows; 1) being male (OR = 0.25, 95%CI 0.14-0.44); 2) young age (OR=0.43, 95%CI 0.25-0.73); 3) having a high intellectual activity (OR = 2.72, 95%CI 1.65-4.48); 4) being well satisfied with their health (OR = 1.45, 95%CI 1.02-2.07), and 5) having a high IKIGAI (OR = 1.06, 95%CI 1.01-1.13). Only elderly individuals capable of high-level intellectual activities can fill the roles of elderly volunteer group leaders discussed in this study.

IL-8 predicts pediatric oncology patients with febrile neutropenia at low risk for bacteremia.

PubMed

Cost, Carrye R; Stegner, Martha M; Leonard, David; Leavey, Patrick

2013-04-01

Despite a low bacteremia rate, pediatric oncology patients are frequently admitted for febrile neutropenia. A pediatric risk prediction model with high sensitivity to identify patients at low risk for bacteremia is not available. We performed a single-institution prospective cohort study of pediatric oncology patients with febrile neutropenia to create a risk prediction model using clinical factors, respiratory viral infection, and cytokine expression. Pediatric oncology patients with febrile neutropenia were enrolled between March 30, 2010 and April 1, 2011 and managed per institutional protocol. Blood samples for C-reactive protein and cytokine expression and nasopharyngeal swabs for respiratory viral testing were obtained. Medical records were reviewed for clinical data. Statistical analysis utilized mixed multiple logistic regression modeling. During the 12-month period, 195 febrile neutropenia episodes were enrolled. There were 24 (12%) episodes of bacteremia. Univariate analysis revealed several factors predictive for bacteremia, and interleukin (IL)-8 was the most predictive variable in the multivariate stepwise logistic regression. Low serum IL-8 predicted patients at low risk for bacteremia with a sensitivity of 0.9 and negative predictive value of 0.98. IL-8 is a highly sensitive predictor for patients at low risk for bacteremia. IL-8 should be utilized in a multi-institution prospective trial to assign risk stratification to pediatric patients admitted with febrile neutropenia.

Family Medicine or Primary Care Residency Selection: Effects of Family Medicine Interest Groups, MD/MPH Dual Degrees, and Rural Medical Education.

PubMed

Wei McIntosh, Elizabeth; Morley, Christopher P

2016-05-01

If medical schools are to produce primary care physicians (family medicine, pediatrics, or general internal medicine), they must provide educational experiences that enable medical students to maintain existing or form new interests in such careers. This study examined three mechanisms for doing so, at one medical school: participation as an officer in a family medicine interest group (FMIG), completion of a dual medical/public health (MD/MPH) degree program, and participation in a rural medical education (RMED) clinical track. Specialty Match data for students who graduated from the study institution between 2006 and 2015 were included as dependent variables in bivariate analysis (c2) and logistic regression models, examining FMIG, MD/MPH, and RMED participation as independent predictors of specialty choice (family medicine yes/no, or any primary care (PC) yes/no), controlling for student demographic data. In bivariate c2 analyses, FMIG officership did not significantly predict matching with family medicine or any PC; RMED and MD/MPH education were significant predictors of both family medicine and PC. Binary logistic regression analyses replicated the bivariate findings, controlling for student demographics. Dual MD/MPH and rural medical education had stronger effects in producing primary care physicians than participation in a FMIG as an officer, at one institution. Further study at multiple institutions is warranted.