Multilevel joint competing risk models

NASA Astrophysics Data System (ADS)

Karunarathna, G. H. S.; Sooriyarachchi, M. R.

2017-09-01

Joint modeling approaches are often encountered for different outcomes of competing risk time to event and count in many biomedical and epidemiology studies in the presence of cluster effect. Hospital length of stay (LOS) has been the widely used outcome measure in hospital utilization due to the benchmark measurement for measuring multiple terminations such as discharge, transferred, dead and patients who have not completed the event of interest at the follow up period (censored) during hospitalizations. Competing risk models provide a method of addressing such multiple destinations since classical time to event models yield biased results when there are multiple events. In this study, the concept of joint modeling has been applied to the dengue epidemiology in Sri Lanka, 2006-2008 to assess the relationship between different outcomes of LOS and platelet count of dengue patients with the district cluster effect. Two key approaches have been applied to build up the joint scenario. In the first approach, modeling each competing risk separately using the binary logistic model, treating all other events as censored under the multilevel discrete time to event model, while the platelet counts are assumed to follow a lognormal regression model. The second approach is based on the endogeneity effect in the multilevel competing risks and count model. Model parameters were estimated using maximum likelihood based on the Laplace approximation. Moreover, the study reveals that joint modeling approach yield more precise results compared to fitting two separate univariate models, in terms of AIC (Akaike Information Criterion).

Linking stressors and ecological responses

USGS Publications Warehouse

Gentile, J.H.; Solomon, K.R.; Butcher, J.B.; Harrass, M.; Landis, W.G.; Power, M.; Rattner, B.A.; Warren-Hicks, W.J.; Wenger, R.; Foran, Jeffery A.; Ferenc, Susan A.

1999-01-01

To characterize risk, it is necessary to quantify the linkages and interactions between chemical, physical and biological stressors and endpoints in the conceptual framework for ecological risk assessment (ERA). This can present challenges in a multiple stressor analysis, and it will not always be possible to develop a quantitative stressor-response profile. This review commences with a conceptual representation of the problem of developing a linkage analysis for multiple stressors and responses. The remainder of the review surveys a variety of mathematical and statistical methods (e.g., ranking methods, matrix models, multivariate dose-response for mixtures, indices, visualization, simulation modeling and decision-oriented methods) for accomplishing the linkage analysis for multiple stressors. Describing the relationships between multiple stressors and ecological effects are critical components of 'effects assessment' in the ecological risk assessment framework.

Integrated presentation of ecological risk from multiple stressors

NASA Astrophysics Data System (ADS)

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-10-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Integrated presentation of ecological risk from multiple stressors.

PubMed

Goussen, Benoit; Price, Oliver R; Rendal, Cecilie; Ashauer, Roman

2016-10-26

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

[Survival analysis with competing risks: estimating failure probability].

PubMed

Llorca, Javier; Delgado-Rodríguez, Miguel

2004-01-01

To show the impact of competing risks of death on survival analysis. We provide an example of survival time without chronic rejection after heart transplantation, where death before rejection acts as a competing risk. Using a computer simulation, we compare the Kaplan-Meier estimator and the multiple decrement model. The Kaplan-Meier method overestimated the probability of rejection. Next, we illustrate the use of the multiple decrement model to analyze secondary end points (in our example: death after rejection). Finally, we discuss Kaplan-Meier assumptions and why they fail in the presence of competing risks. Survival analysis should be adjusted for competing risks of death to avoid overestimation of the risk of rejection produced with the Kaplan-Meier method.

Dynamic Modeling of Systemic Risk in Financial Networks

NASA Astrophysics Data System (ADS)

Avakian, Adam

Modern financial networks are complicated structures that can contain multiple types of nodes and connections between those nodes. Banks, governments and even individual people weave into an intricate network of debt, risk correlations and many other forms of interconnectedness. We explore multiple types of financial network models with a focus on understanding the dynamics and causes of cascading failures in such systems. In particular, we apply real-world data from multiple sources to these models to better understand real-world financial networks. We use the results of the Federal Reserve "Banking Organization Systemic Risk Report" (FR Y-15), which surveys the largest US banks on their level of interconnectedness, to find relationships between various measures of network connectivity and systemic risk in the US financial sector. This network model is then stress-tested under a number of scenarios to determine systemic risks inherent in the various network structures. We also use detailed historical balance sheet data from the Venezuelan banking system to build a bipartite network model and find relationships between the changing network structure over time and the response of the system to various shocks. We find that the relationship between interconnectedness and systemic risk is highly dependent on the system and model but that it is always a significant one. These models are useful tools that add value to regulators in creating new measurements of systemic risk in financial networks. These models could be used as macroprudential tools for monitoring the health of the entire banking system as a whole rather than only of individual banks.

Multiple-Strain Approach and Probabilistic Modeling of Consumer Habits in Quantitative Microbial Risk Assessment: A Quantitative Assessment of Exposure to Staphylococcal Enterotoxin A in Raw Milk.

PubMed

Crotta, Matteo; Rizzi, Rita; Varisco, Giorgio; Daminelli, Paolo; Cunico, Elena Cosciani; Luini, Mario; Graber, Hans Ulrich; Paterlini, Franco; Guitian, Javier

2016-03-01

Quantitative microbial risk assessment (QMRA) models are extensively applied to inform management of a broad range of food safety risks. Inevitably, QMRA modeling involves an element of simplification of the biological process of interest. Two features that are frequently simplified or disregarded are the pathogenicity of multiple strains of a single pathogen and consumer behavior at the household level. In this study, we developed a QMRA model with a multiple-strain approach and a consumer phase module (CPM) based on uncertainty distributions fitted from field data. We modeled exposure to staphylococcal enterotoxin A in raw milk in Lombardy; a specific enterotoxin production module was thus included. The model is adaptable and could be used to assess the risk related to other pathogens in raw milk as well as other staphylococcal enterotoxins. The multiplestrain approach, implemented as a multinomial process, allowed the inclusion of variability and uncertainty with regard to pathogenicity at the bacterial level. Data from 301 questionnaires submitted to raw milk consumers were used to obtain uncertainty distributions for the CPM. The distributions were modeled to be easily updatable with further data or evidence. The sources of uncertainty due to the multiple-strain approach and the CPM were identified, and their impact on the output was assessed by comparing specific scenarios to the baseline. When the distributions reflecting the uncertainty in consumer behavior were fixed to the 95th percentile, the risk of exposure increased up to 160 times. This reflects the importance of taking into consideration the diversity of consumers' habits at the household level and the impact that the lack of knowledge about variables in the CPM can have on the final QMRA estimates. The multiple-strain approach lends itself to use in other food matrices besides raw milk and allows the model to better capture the complexity of the real world and to be capable of geographical specificity.

Development of good modelling practice for phsiologically based pharmacokinetic models for use in risk assessment: The first steps

EPA Science Inventory

The increasing use of tissue dosimetry estimated using pharmacokinetic models in chemical risk assessments in multiple countries necessitates the need to develop internationally recognized good modelling practices. These practices would facilitate sharing of models and model eva...

Modeling month-season of birth as a risk factor in mouse models of chronic disease: from multiple sclerosis to autoimmune encephalomyelitis.

PubMed

Reynolds, Jacob D; Case, Laure K; Krementsov, Dimitry N; Raza, Abbas; Bartiss, Rose; Teuscher, Cory

2017-06-01

Month-season of birth (M-SOB) is a risk factor in multiple chronic diseases, including multiple sclerosis (MS), where the lowest and greatest risk of developing MS coincide with the lowest and highest birth rates, respectively. To determine whether M-SOB effects in such chronic diseases as MS can be experimentally modeled, we examined the effect of M-SOB on susceptibility of C57BL/6J mice to experimental autoimmune encephalomyelitis (EAE). As in MS, mice that were born during the M-SOB with the lowest birth rate were less susceptible to EAE than mice born during the M-SOB with the highest birth rate. We also show that the M-SOB effect on EAE susceptibility is associated with differential production of multiple cytokines/chemokines by neuroantigen-specific T cells that are known to play a role in EAE pathogenesis. Taken together, these results support the existence of an M-SOB effect that may reflect seasonally dependent developmental differences in adaptive immune responses to self-antigens independent of external stimuli, including exposure to sunlight and vitamin D. Moreover, our documentation of an M-SOB effect on EAE susceptibility in mice allows for modeling and detailed analysis of mechanisms that underlie the M-SOB effect in not only MS but in numerous other diseases in which M-SOB impacts susceptibility.-Reynolds, J. D., Case, L. K., Krementsov, D. N., Raza, A., Bartiss, R., Teuscher, C. Modeling month-season of birth as a risk factor in mouse models of chronic disease: from multiple sclerosis to autoimmune encephalomyelitis. © FASEB.

Modeling Success: Using Preenrollment Data to Identify Academically At-Risk Students

ERIC Educational Resources Information Center

Gansemer-Topf, Ann M.; Compton, Jonathan; Wohlgemuth, Darin; Forbes, Greg; Ralston, Ekaterina

2015-01-01

Improving student success and degree completion is one of the core principles of strategic enrollment management. To address this principle, institutional data were used to develop a statistical model to identify academically at-risk students. The model employs multiple linear regression techniques to predict students at risk of earning below a…

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Risk Prediction Score for HIV Infection: Development and Internal Validation with Cross-Sectional Data from Men Who Have Sex with Men in China.

PubMed

Yin, Lu; Zhao, Yuejuan; Peratikos, Meridith Blevins; Song, Liang; Zhang, Xiangjun; Xin, Ruolei; Sun, Zheya; Xu, Yunan; Zhang, Li; Hu, Yifei; Hao, Chun; Ruan, Yuhua; Shao, Yiming; Vermund, Sten H; Qian, Han-Zhu

2018-05-21

Receptive anal intercourse, multiple partners, condomless sex, sexually transmitted infections (STIs), and drug/alcohol addiction are familiar factors that correlate with increased human immunodeficiency virus (HIV) risk among men who have sex with men (MSM). To improve estimation to HIV acquisition, we created a composite score using questions from routine survey of 3588 MSM in Beijing, China. The HIV prevalence was 13.4%. A risk scoring tool using penalized maximum likelihood multivariable logistic regression modeling was developed, deploying backward step-down variable selection to obtain a reduced-form model. The full penalized model included 19 sexual predictors, while the reduced-form model had 12 predictors. Both models calibrated well; bootstrap-corrected c-indices were 0.70 (full model) and 0.71 (reduced-form model). Non-Beijing residence, short-term living in Beijing, illegal drug use, multiple male sexual partners, receptive anal sex, inconsistent condom use, alcohol consumption before sex, and syphilis infection were the strongest predictors of HIV infection. Discriminating higher-risk MSM for targeted HIV prevention programming using a validated risk score could improve the efficiency of resource deployment for educational and risk reduction programs. A valid risk score can also identify higher risk persons into prevention and vaccine clinical trials, which would improve trial cost-efficiency.

Integrated presentation of ecological risk from multiple stressors

PubMed Central

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-01-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic. PMID:27782171

Modeling the Potential Effects of New Tobacco Products and Policies. A Dynamic Population Model for Multiple Product Use and Harm

DOE PAGES

Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.; ...

2015-03-27

Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use formore » the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health outcomes such as morbidity and disability.« less

Modeling the Potential Effects of New Tobacco Products and Policies: A Dynamic Population Model for Multiple Product Use and Harm

PubMed Central

Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.; Brodsky, Nancy S.; Brown, Theresa J.; Choiniere, Conrad J.; Coleman, Blair N.; Paredes, Antonio; Apelberg, Benjamin J.

2015-01-01

Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health outcomes such as morbidity and disability. PMID:25815840

Modeling the potential effects of new tobacco products and policies: a dynamic population model for multiple product use and harm.

PubMed

Vugrin, Eric D; Rostron, Brian L; Verzi, Stephen J; Brodsky, Nancy S; Brown, Theresa J; Choiniere, Conrad J; Coleman, Blair N; Paredes, Antonio; Apelberg, Benjamin J

2015-01-01

Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health outcomes such as morbidity and disability.

Modeling the Potential Effects of New Tobacco Products and Policies. A Dynamic Population Model for Multiple Product Use and Harm

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

Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.

Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use formore » the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health outcomes such as morbidity and disability.« less

Society of Thoracic Surgeons 2008 cardiac risk models predict in-hospital mortality of heart valve surgery in a Chinese population: a multicenter study.

PubMed

Wang, Lv; Lu, Fang-Lin; Wang, Chong; Tan, Meng-Wei; Xu, Zhi-yun

2014-12-01

The Society of Thoracic Surgeons 2008 cardiac surgery risk models have been developed for heart valve surgery with and without coronary artery bypass grafting. The aim of our study was to evaluate the performance of Society of Thoracic Surgeons 2008 cardiac risk models in Chinese patients undergoing single valve surgery and the predicted mortality rates of those undergoing multiple valve surgery derived from the Society of Thoracic Surgeons 2008 risk models. A total of 12,170 patients underwent heart valve surgery from January 2008 to December 2011. Combined congenital heart surgery and aortal surgery cases were excluded. A relatively small number of valve surgery combinations were excluded. The final research population included the following isolated heart valve surgery types: aortic valve replacement, mitral valve replacement, and mitral valve repair. The following combined valve surgery types were included: mitral valve replacement plus tricuspid valve repair, mitral valve replacement plus aortic valve replacement, and mitral valve replacement plus aortic valve replacement and tricuspid valve repair. Evaluation was performed by using the Hosmer-Lemeshow test and C-statistics. Data from 9846 patients were analyzed. The Society of Thoracic Surgeons 2008 cardiac risk models showed reasonable discrimination and poor calibration (C-statistic, 0.712; P = .00006 in Hosmer-Lemeshow test). Society of Thoracic Surgeons 2008 models had better discrimination (C-statistic, 0.734) and calibration (P = .5805) in patients undergoing isolated valve surgery than in patients undergoing multiple valve surgery (C-statistic, 0.694; P = .00002 in Hosmer-Lemeshow test). Estimates derived from the Society of Thoracic Surgeons 2008 models exceeded the mortality rates of multiple valve surgery (observed/expected ratios of 1.44 for multiple valve surgery and 1.17 for single valve surgery). The Society of Thoracic Surgeons 2008 cardiac surgery risk models performed well when predicting the mortality for Chinese patients undergoing valve surgery. The Society of Thoracic Surgeons 2008 models were suitable for single valve surgery in a Chinese population; estimates of mortality for multiple valve surgery derived from the Society of Thoracic Surgeons 2008 models were less accurate. Copyright © 2014 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Multiple imputation for estimating the risk of developing dementia and its impact on survival.

PubMed

Yu, Binbing; Saczynski, Jane S; Launer, Lenore

2010-10-01

Dementia, Alzheimer's disease in particular, is one of the major causes of disability and decreased quality of life among the elderly and a leading obstacle to successful aging. Given the profound impact on public health, much research has focused on the age-specific risk of developing dementia and the impact on survival. Early work has discussed various methods of estimating age-specific incidence of dementia, among which the illness-death model is popular for modeling disease progression. In this article we use multiple imputation to fit multi-state models for survival data with interval censoring and left truncation. This approach allows semi-Markov models in which survival after dementia depends on onset age. Such models can be used to estimate the cumulative risk of developing dementia in the presence of the competing risk of dementia-free death. Simulations are carried out to examine the performance of the proposed method. Data from the Honolulu Asia Aging Study are analyzed to estimate the age-specific and cumulative risks of dementia and to examine the effect of major risk factors on dementia onset and death.

Site-wide seismic risk model for Savannah River Site nuclear facilities

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

Eide, S.A.; Shay, R.S.; Durant, W.S.

1993-09-01

The 200,000 acre Savannah River Site (SRS) has nearly 30 nuclear facilities spread throughout the site. The safety of each facility has been established in facility-specific safety analysis reports (SARs). Each SAR contains an analysis of risk from seismic events to both on-site workers and the off-site population. Both radiological and chemical releases are considered, and air and water pathways are modeled. Risks to the general public are generally characterized by evaluating exposure to the maximally exposed individual located at the SRS boundary and to the off-site population located within 50 miles. Although the SARs are appropriate methods for studyingmore » individual facility risks, there is a class of accident initiators that can simultaneously affect several of all of the facilities, Examples include seismic events, strong winds or tornados, floods, and loss of off-site electrical power. Overall risk to the off-site population from such initiators is not covered by the individual SARs. In such cases multiple facility radionuclide or chemical releases could occur, and off-site exposure would be greater than that indicated in a single facility SAR. As a step towards an overall site-wide risk model that adequately addresses multiple facility releases, a site-wide seismic model for determining off-site risk has been developed for nuclear facilities at the SRS. Risk from seismic events up to the design basis earthquake (DBE) of 0.2 g (frequency of 2.0E-4/yr) is covered by the model. Present plans include expanding the scope of the model to include other types of initiators that can simultaneously affect multiple facilities.« less

Modeling Environment for Total Risk-4M

EPA Science Inventory

MENTOR-4M uses an integrated, mechanistically consistent, source-to-dose modeling framework to quantify simultaneous exposures and doses of individuals and populations to multiple contaminants. It is an implementation of the MENTOR system for exposures to Multiple contaminants fr...

A Case Study Application of the Aggregate Exposure Pathway (AEP) and Adverse Outcome Pathway (AOP) Frameworks to Facilitate the Integration of Human Health and Ecological End Points for Cumulative Risk Assessment (CRA)

EPA Science Inventory

Cumulative risk assessment (CRA) methods promote the use of a conceptual site model (CSM) to apportion exposures and integrate risk from multiple stressors. While CSMs may encompass multiple species, evaluating end points across taxa can be challenging due to data availability an...

Low Dose Radiation Cancer Risks: Epidemiological and Toxicological Models

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

David G. Hoel, PhD

2012-04-19

The basic purpose of this one year research grant was to extend the two stage clonal expansion model (TSCE) of carcinogenesis to exposures other than the usual single acute exposure. The two-stage clonal expansion model of carcinogenesis incorporates the biological process of carcinogenesis, which involves two mutations and the clonal proliferation of the intermediate cells, in a stochastic, mathematical way. The current TSCE model serves a general purpose of acute exposure models but requires numerical computation of both the survival and hazard functions. The primary objective of this research project was to develop the analytical expressions for the survival functionmore » and the hazard function of the occurrence of the first cancer cell for acute, continuous and multiple exposure cases within the framework of the piece-wise constant parameter two-stage clonal expansion model of carcinogenesis. For acute exposure and multiple exposures of acute series, it is either only allowed to have the first mutation rate vary with the dose, or to have all the parameters be dose dependent; for multiple exposures of continuous exposures, all the parameters are allowed to vary with the dose. With these analytical functions, it becomes easy to evaluate the risks of cancer and allows one to deal with the various exposure patterns in cancer risk assessment. A second objective was to apply the TSCE model with varing continuous exposures from the cancer studies of inhaled plutonium in beagle dogs. Using step functions to estimate the retention functions of the pulmonary exposure of plutonium the multiple exposure versions of the TSCE model was to be used to estimate the beagle dog lung cancer risks. The mathematical equations of the multiple exposure versions of the TSCE model were developed. A draft manuscript which is attached provides the results of this mathematical work. The application work using the beagle dog data from plutonium exposure has not been completed due to the fact that the research project did not continue beyond its first year.« less

Determination of osteoporosis risk factors using a multiple logistic regression model in postmenopausal Turkish women.

PubMed

Akkus, Zeki; Camdeviren, Handan; Celik, Fatma; Gur, Ali; Nas, Kemal

2005-09-01

To determine the risk factors of osteoporosis using a multiple binary logistic regression method and to assess the risk variables for osteoporosis, which is a major and growing health problem in many countries. We presented a case-control study, consisting of 126 postmenopausal healthy women as control group and 225 postmenopausal osteoporotic women as the case group. The study was carried out in the Department of Physical Medicine and Rehabilitation, Dicle University, Diyarbakir, Turkey between 1999-2002. The data from the 351 participants were collected using a standard questionnaire that contains 43 variables. A multiple logistic regression model was then used to evaluate the data and to find the best regression model. We classified 80.1% (281/351) of the participants using the regression model. Furthermore, the specificity value of the model was 67% (84/126) of the control group while the sensitivity value was 88% (197/225) of the case group. We found the distribution of residual values standardized for final model to be exponential using the Kolmogorow-Smirnow test (p=0.193). The receiver operating characteristic curve was found successful to predict patients with risk for osteoporosis. This study suggests that low levels of dietary calcium intake, physical activity, education, and longer duration of menopause are independent predictors of the risk of low bone density in our population. Adequate dietary calcium intake in combination with maintaining a daily physical activity, increasing educational level, decreasing birth rate, and duration of breast-feeding may contribute to healthy bones and play a role in practical prevention of osteoporosis in Southeast Anatolia. In addition, the findings of the present study indicate that the use of multivariate statistical method as a multiple logistic regression in osteoporosis, which maybe influenced by many variables, is better than univariate statistical evaluation.

A method for mapping fire hazard and risk across multiple scales and its application in fire management

Treesearch

Robert E. Keane; Stacy A. Drury; Eva C. Karau; Paul F. Hessburg; Keith M. Reynolds

2010-01-01

This paper presents modeling methods for mapping fire hazard and fire risk using a research model called FIREHARM (FIRE Hazard and Risk Model) that computes common measures of fire behavior, fire danger, and fire effects to spatially portray fire hazard over space. FIREHARM can compute a measure of risk associated with the distribution of these measures over time using...

Overview of the Special Issue: A Multi-Model Framework to Achieve Consistent Evaluation of Climate Change Impacts in the United States

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

Waldhoff, Stephanie T.; Martinich, Jeremy; Sarofim, Marcus

2015-07-01

The Climate Change Impacts and Risk Analysis (CIRA) modeling exercise is a unique contribution to the scientific literature on climate change impacts, economic damages, and risk analysis that brings together multiple, national-scale models of impacts and damages in an integrated and consistent fashion to estimate climate change impacts, damages, and the benefits of greenhouse gas (GHG) mitigation actions in the United States. The CIRA project uses three consistent socioeconomic, emissions, and climate scenarios across all models to estimate the benefits of GHG mitigation policies: a Business As Usual (BAU) and two policy scenarios with radiative forcing (RF) stabilization targets ofmore » 4.5 W/m2 and 3.7 W/m2 in 2100. CIRA was also designed to specifically examine the sensitivity of results to uncertainties around climate sensitivity and differences in model structure. The goals of CIRA project are to 1) build a multi-model framework to produce estimates of multiple risks and impacts in the U.S., 2) determine to what degree risks and damages across sectors may be lowered from a BAU to policy scenarios, 3) evaluate key sources of uncertainty along the causal chain, and 4) provide information for multiple audiences and clearly communicate the risks and damages of climate change and the potential benefits of mitigation. This paper describes the motivations, goals, and design of the CIRA modeling exercise and introduces the subsequent papers in this special issue.« less

A Model for Generating Multi-hazard Scenarios

NASA Astrophysics Data System (ADS)

Lo Jacomo, A.; Han, D.; Champneys, A.

2017-12-01

Communities in mountain areas are often subject to risk from multiple hazards, such as earthquakes, landslides, and floods. Each hazard has its own different rate of onset, duration, and return period. Multiple hazards tend to complicate the combined risk due to their interactions. Prioritising interventions for minimising risk in this context is challenging. We developed a probabilistic multi-hazard model to help inform decision making in multi-hazard areas. The model is applied to a case study region in the Sichuan province in China, using information from satellite imagery and in-situ data. The model is not intended as a predictive model, but rather as a tool which takes stakeholder input and can be used to explore plausible hazard scenarios over time. By using a Monte Carlo framework and varrying uncertain parameters for each of the hazards, the model can be used to explore the effect of different mitigation interventions aimed at reducing the disaster risk within an uncertain hazard context.

A comparison of imputation techniques for handling missing predictor values in a risk model with a binary outcome.

PubMed

Ambler, Gareth; Omar, Rumana Z; Royston, Patrick

2007-06-01

Risk models that aim to predict the future course and outcome of disease processes are increasingly used in health research, and it is important that they are accurate and reliable. Most of these risk models are fitted using routinely collected data in hospitals or general practices. Clinical outcomes such as short-term mortality will be near-complete, but many of the predictors may have missing values. A common approach to dealing with this is to perform a complete-case analysis. However, this may lead to overfitted models and biased estimates if entire patient subgroups are excluded. The aim of this paper is to investigate a number of methods for imputing missing data to evaluate their effect on risk model estimation and the reliability of the predictions. Multiple imputation methods, including hotdecking and multiple imputation by chained equations (MICE), were investigated along with several single imputation methods. A large national cardiac surgery database was used to create simulated yet realistic datasets. The results suggest that complete case analysis may produce unreliable risk predictions and should be avoided. Conditional mean imputation performed well in our scenario, but may not be appropriate if using variable selection methods. MICE was amongst the best performing multiple imputation methods with regards to the quality of the predictions. Additionally, it produced the least biased estimates, with good coverage, and hence is recommended for use in practice.

An integrative formal model of motivation and decision making: The MGPM*.

PubMed

Ballard, Timothy; Yeo, Gillian; Loft, Shayne; Vancouver, Jeffrey B; Neal, Andrew

2016-09-01

We develop and test an integrative formal model of motivation and decision making. The model, referred to as the extended multiple-goal pursuit model (MGPM*), is an integration of the multiple-goal pursuit model (Vancouver, Weinhardt, & Schmidt, 2010) and decision field theory (Busemeyer & Townsend, 1993). Simulations of the model generated predictions regarding the effects of goal type (approach vs. avoidance), risk, and time sensitivity on prioritization. We tested these predictions in an experiment in which participants pursued different combinations of approach and avoidance goals under different levels of risk. The empirical results were consistent with the predictions of the MGPM*. Specifically, participants pursuing 1 approach and 1 avoidance goal shifted priority from the approach to the avoidance goal over time. Among participants pursuing 2 approach goals, those with low time sensitivity prioritized the goal with the larger discrepancy, whereas those with high time sensitivity prioritized the goal with the smaller discrepancy. Participants pursuing 2 avoidance goals generally prioritized the goal with the smaller discrepancy. Finally, all of these effects became weaker as the level of risk increased. We used quantitative model comparison to show that the MGPM* explained the data better than the original multiple-goal pursuit model, and that the major extensions from the original model were justified. The MGPM* represents a step forward in the development of a general theory of decision making during multiple-goal pursuit. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A Framework for Linking Population Model Development with Ecological Risk Assessment Objectives.

EPA Science Inventory

The value of models that link organism‐level impacts to the responses of a population in ecological risk assessments (ERAs) has been demonstrated extensively over the past few decades. There is little debate about the utility of these models to translate multiple organism&#...

Care delivery for Filipino Americans using the Neuman systems model.

PubMed

Angosta, Alona D; Ceria-Ulep, Clementina D; Tse, Alice M

2014-04-01

Filipino Americans are at risk of coronary heart disease due to the presence of multiple cardiometabolic factors. Selecting a framework that addresses the factors leading to coronary heart disease is vital when providing care for this population. The Neuman systems model is a comprehensive and wholistic framework that offers an innovative method of viewing clients, their families, and the healthcare system across multiple dimensions. Using the Neuman systems model, advanced practice nurses can develop and implement interventions that will help reduce the potential cardiovascular problems of clients with multiple risk factors. The authors in this article provides insight into the cardiovascular health of Filipino Americans and has implications for nurses and other healthcare providers working with various Southeast Asian groups in the United States.

Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms.

PubMed

Barzegar, Rahim; Moghaddam, Asghar Asghari; Deo, Ravinesh; Fijani, Elham; Tziritis, Evangelos

2018-04-15

Constructing accurate and reliable groundwater risk maps provide scientifically prudent and strategic measures for the protection and management of groundwater. The objectives of this paper are to design and validate machine learning based-risk maps using ensemble-based modelling with an integrative approach. We employ the extreme learning machines (ELM), multivariate regression splines (MARS), M5 Tree and support vector regression (SVR) applied in multiple aquifer systems (e.g. unconfined, semi-confined and confined) in the Marand plain, North West Iran, to encapsulate the merits of individual learning algorithms in a final committee-based ANN model. The DRASTIC Vulnerability Index (VI) ranged from 56.7 to 128.1, categorized with no risk, low and moderate vulnerability thresholds. The correlation coefficient (r) and Willmott's Index (d) between NO 3 concentrations and VI were 0.64 and 0.314, respectively. To introduce improvements in the original DRASTIC method, the vulnerability indices were adjusted by NO 3 concentrations, termed as the groundwater contamination risk (GCR). Seven DRASTIC parameters utilized as the model inputs and GCR values utilized as the outputs of individual machine learning models were served in the fully optimized committee-based ANN-predictive model. The correlation indicators demonstrated that the ELM and SVR models outperformed the MARS and M5 Tree models, by virtue of a larger d and r value. Subsequently, the r and d metrics for the ANN-committee based multi-model in the testing phase were 0.8889 and 0.7913, respectively; revealing the superiority of the integrated (or ensemble) machine learning models when compared with the original DRASTIC approach. The newly designed multi-model ensemble-based approach can be considered as a pragmatic step for mapping groundwater contamination risks of multiple aquifer systems with multi-model techniques, yielding the high accuracy of the ANN committee-based model. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling Joint Exposures and Health Outcomes for Cumulative Risk Assessment: The Case of Radon and Smoking

PubMed Central

Chahine, Teresa; Schultz, Bradley D.; Zartarian, Valerie G.; Xue, Jianping; Subramanian, SV; Levy, Jonathan I.

2011-01-01

Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case example, given its large attributable risk, effect modification due to smoking, and significant variability in radon concentrations and smoking patterns. In spite of this fact, no study to date has estimated geographic and sociodemographic patterns of both radon and smoking in a manner that would allow for inclusion of radon in community-based cumulative risk assessment. In this study, we apply multi-level regression models to explain variability in radon based on housing characteristics and geological variables, and construct a regression model predicting housing characteristics using U.S. Census data. Multi-level regression models of smoking based on predictors common to the housing model allow us to link the exposures. We estimate county-average lifetime lung cancer risks from radon ranging from 0.15 to 1.8 in 100, with high-risk clusters in areas and for subpopulations with high predicted radon and smoking rates. Our findings demonstrate the viability of screening-level assessment to characterize patterns of lung cancer risk from radon, with an approach that can be generalized to multiple chemical and non-chemical stressors. PMID:22016710

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

PubMed

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

2015-05-01

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

Modified social ecological model: a tool to guide the assessment of the risks and risk contexts of HIV epidemics.

PubMed

Baral, Stefan; Logie, Carmen H; Grosso, Ashley; Wirtz, Andrea L; Beyrer, Chris

2013-05-17

Social and structural factors are now well accepted as determinants of HIV vulnerabilities. These factors are representative of social, economic, organizational and political inequities. Associated with an improved understanding of multiple levels of HIV risk has been the recognition of the need to implement multi-level HIV prevention strategies. Prevention sciences research and programming aiming to decrease HIV incidence requires epidemiologic studies to collect data on multiple levels of risk to inform combination HIV prevention packages. Proximal individual-level risks, such as sharing injection devices and unprotected penile-vaginal or penile-anal sex, are necessary in mediating HIV acquisition and transmission. However, higher order social and structural-level risks can facilitate or reduce HIV transmission on population levels. Data characterizing these risks is often far more actionable than characterizing individual-level risks. We propose a modified social ecological model (MSEM) to help visualize multi-level domains of HIV infection risks and guide the development of epidemiologic HIV studies. Such a model may inform research in epidemiology and prevention sciences, particularly for key populations including men who have sex with men (MSM), people who inject drugs (PID), and sex workers. The MSEM builds on existing frameworks by examining multi-level risk contexts for HIV infection and situating individual HIV infection risks within wider network, community, and public policy contexts as well as epidemic stage. The utility of the MSEM is demonstrated with case studies of HIV risk among PID and MSM. The MSEM is a flexible model for guiding epidemiologic studies among key populations at risk for HIV in diverse sociocultural contexts. Successful HIV prevention strategies for key populations require effective integration of evidence-based biomedical, behavioral, and structural interventions. While the focus of epidemiologic studies has traditionally been on describing individual-level risk factors, the future necessitates comprehensive epidemiologic data characterizing multiple levels of HIV risk.

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.

A modeling framework for exposing risks in complex systems.

PubMed

Sharit, J

2000-08-01

This article introduces and develops a modeling framework for exposing risks in the form of human errors and adverse consequences in high-risk systems. The modeling framework is based on two components: a two-dimensional theory of accidents in systems developed by Perrow in 1984, and the concept of multiple system perspectives. The theory of accidents differentiates systems on the basis of two sets of attributes. One set characterizes the degree to which systems are interactively complex; the other emphasizes the extent to which systems are tightly coupled. The concept of multiple perspectives provides alternative descriptions of the entire system that serve to enhance insight into system processes. The usefulness of these two model components derives from a modeling framework that cross-links them, enabling a variety of work contexts to be exposed and understood that would otherwise be very difficult or impossible to identify. The model components and the modeling framework are illustrated in the case of a large and comprehensive trauma care system. In addition to its general utility in the area of risk analysis, this methodology may be valuable in applications of current methods of human and system reliability analysis in complex and continually evolving high-risk systems.

A Framework for Linking Population Model Development with Ecological Risk Assessment Objectives

EPA Science Inventory

The value of models that link organism-level impacts to the responses of a population in ecological risk assessments (ERA) has been demonstrated extensively over the past few decades. There is little debate about the utility of these models to translate multiple organism-level en...

ASSESSING POPULATION EXPOSURES TO MULTIPLE AIR POLLUTANTS USING A MECHANISTIC SOURCE-TO-DOSE MODELING FRAMEWORK

EPA Science Inventory

The Modeling Environment for Total Risks studies (MENTOR) system, combined with an extension of the SHEDS (Stochastic Human Exposure and Dose Simulation) methodology, provide a mechanistically consistent framework for conducting source-to-dose exposure assessments of multiple pol...

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

PubMed

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

2016-07-01

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

An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on multiple ecosystem services

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

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

ERIC Educational Resources Information Center

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

2012-01-01

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

Care Delivery for Filipino Americans Using the Neuman Systems Model

PubMed Central

Angosta, Alona D.; Ceria-Ulep, Clementina D.; Tse, Alice M.

2016-01-01

Filipino Americans are at risk of coronary heart disease due to the presence of multiple cardiometabolic factors. Selecting a framework that addresses the factors leading to coronary heart disease is vital when providing care for this population. The Neuman systems model is a comprehensive and wholistic framework that offers an innovative method of viewing clients, their families, and the healthcare system across multiple dimensions. Using the Neuman systems model, advanced practice nurses can develop and implement interventions that will help reduce the potential cardiovascular problems of clients with multiple risk factors. The authors in this article provides insight into the cardiovascular health of Filipino Americans and has implications for nurses and other healthcare providers working with various Southeast Asian groups in the United States. PMID:24740949

Assessment of BTEX-induced health risk under multiple uncertainties at a petroleum-contaminated site: An integrated fuzzy stochastic approach

NASA Astrophysics Data System (ADS)

Zhang, Xiaodong; Huang, Guo H.

2011-12-01

Groundwater pollution has gathered more and more attention in the past decades. Conducting an assessment of groundwater contamination risk is desired to provide sound bases for supporting risk-based management decisions. Therefore, the objective of this study is to develop an integrated fuzzy stochastic approach to evaluate risks of BTEX-contaminated groundwater under multiple uncertainties. It consists of an integrated interval fuzzy subsurface modeling system (IIFMS) and an integrated fuzzy second-order stochastic risk assessment (IFSOSRA) model. The IIFMS is developed based on factorial design, interval analysis, and fuzzy sets approach to predict contaminant concentrations under hybrid uncertainties. Two input parameters (longitudinal dispersivity and porosity) are considered to be uncertain with known fuzzy membership functions, and intrinsic permeability is considered to be an interval number with unknown distribution information. A factorial design is conducted to evaluate interactive effects of the three uncertain factors on the modeling outputs through the developed IIFMS. The IFSOSRA model can systematically quantify variability and uncertainty, as well as their hybrids, presented as fuzzy, stochastic and second-order stochastic parameters in health risk assessment. The developed approach haw been applied to the management of a real-world petroleum-contaminated site within a western Canada context. The results indicate that multiple uncertainties, under a combination of information with various data-quality levels, can be effectively addressed to provide supports in identifying proper remedial efforts. A unique contribution of this research is the development of an integrated fuzzy stochastic approach for handling various forms of uncertainties associated with simulation and risk assessment efforts.

Invited OSU class lecture: An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on multiple ecosystem services

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on multiple ecosystem services - 4/27/10

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

Risk-taking behavior in the presence of nonconvex asset dynamics.

PubMed

Lybbert, Travis J; Barrett, Christopher B

2011-01-01

The growing literature on poverty traps emphasizes the links between multiple equilibria and risk avoidance. However, multiple equilibria may also foster risk-taking behavior by some poor people. We illustrate this idea with a simple analytical model in which people with different wealth and ability endowments make investment and risky activity choices in the presence of known nonconvex asset dynamics. This model underscores a crucial distinction between familiar static concepts of risk aversion and forward-looking dynamic risk responses to nonconvex asset dynamics. Even when unobservable preferences exhibit decreasing absolute risk aversion, observed behavior may suggest that risk aversion actually increases with wealth near perceived dynamic asset thresholds. Although high ability individuals are not immune from poverty traps, they can leverage their capital endowments more effectively than lower ability types and are therefore less likely to take seemingly excessive risks. In general, linkages between behavioral responses and wealth dynamics often seem to run in both directions. Both theoretical and empirical poverty trap research could benefit from making this two-way linkage more explicit.

Ecosystem Risk Assessment Using the Comprehensive Assessment of Risk to Ecosystems (CARE) Tool

NASA Astrophysics Data System (ADS)

Battista, W.; Fujita, R.; Karr, K.

2016-12-01

Effective Ecosystem Based Management requires a localized understanding of the health and functioning of a given system as well as of the various factors that may threaten the ongoing ability of the system to support the provision of valued services. Several risk assessment models are available that can provide a scientific basis for understanding these factors and for guiding management action, but these models focus mainly on single species and evaluate only the impacts of fishing in detail. We have developed a new ecosystem risk assessment model - the Comprehensive Assessment of Risk to Ecosystems (CARE) - that allows analysts to consider the cumulative impact of multiple threats, interactions among multiple threats that may result in synergistic or antagonistic impacts, and the impacts of a suite of threats on whole-ecosystem productivity and functioning, as well as on specific ecosystem services. The CARE model was designed to be completed in as little as two hours, and uses local and expert knowledge where data are lacking. The CARE tool can be used to evaluate risks facing a single site; to compare multiple sites for the suitability or necessity of different management options; or to evaluate the effects of a proposed management action aimed at reducing one or more risks. This analysis can help users identify which threats are the most important at a given site, and therefore where limited management resources should be targeted. CARE can be applied to virtually any system, and can be modified as knowledge is gained or to better match different site characteristics. CARE builds on previous ecosystem risk assessment tools to provide a comprehensive assessment of fishing and non-fishing threats that can be used to inform environmental management decisions across a broad range of systems.

Ecosystem Risk Assessment Using the Comprehensive Assessment of Risk to Ecosystems (CARE) Tool

NASA Astrophysics Data System (ADS)

Battista, W.; Fujita, R.; Karr, K.

2016-02-01

Effective Ecosystem Based Management requires a localized understanding of the health and functioning of a given system as well as of the various factors that may threaten the ongoing ability of the system to support the provision of valued services. Several risk assessment models are available that can provide a scientific basis for understanding these factors and for guiding management action, but these models focus mainly on single species and evaluate only the impacts of fishing in detail. We have developed a new ecosystem risk assessment model - the Comprehensive Assessment of Risk to Ecosystems (CARE) - that allows analysts to consider the cumulative impact of multiple threats, interactions among multiple threats that may result in synergistic or antagonistic impacts, and the impacts of a suite of threats on whole-ecosystem productivity and functioning, as well as on specific ecosystem services. The CARE model was designed to be completed in as little as two hours, and uses local and expert knowledge where data are lacking. The CARE tool can be used to evaluate risks facing a single site; to compare multiple sites for the suitability or necessity of different management options; or to evaluate the effects of a proposed management action aimed at reducing one or more risks. This analysis can help users identify which threats are the most important at a given site, and therefore where limited management resources should be targeted. CARE can be applied to virtually any system, and can be modified as knowledge is gained or to better match different site characteristics. CARE builds on previous ecosystem risk assessment tools to provide a comprehensive assessment of fishing and non-fishing threats that can be used to inform environmental management decisions across a broad range of systems.

Multiple attribute decision making model and application to food safety risk evaluation.

PubMed

Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

2017-01-01

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

INCORPORATING NONCHEMICAL STRESSORS INTO CUMMULATIVE RISK ASSESSMENTS

EPA Science Inventory

The risk assessment paradigm has begun to shift from assessing single chemicals using "reasonable worst case" assumptions for individuals to considering multiple chemicals and community-based models. Inherent in community-based risk assessment is examination of all stressors a...

Multiple roles and all-cause mortality: the Japan Collaborative Cohort Study.

PubMed

Tamakoshi, Akiko; Ikeda, Ai; Fujino, Yoshihisa; Tamakoshi, Koji; Iso, Hisoyasu

2013-02-01

Two contrasting perspectives on the effects of multiple roles; the 'role overload hypothesis' and the 'role enhancement model', have been proposed to predict variations in health. The aim of this study was to evaluate the impact of multiple roles on all-cause mortality in Japan where gender roles are currently changing. A total of 76,758 individuals from the Japan Collaborative Cohort Study were followed for an average of 15.7 years. Hazard ratios (HRs) with 95% confidence intervals were calculated from proportional hazard models to estimate the risk of all-cause mortality according to multiple roles (spouse, parent and worker, and combinations of these roles). After adjusting for potential confounding factors, the risks of all-cause mortality were elevated among men and women without a role. The number of roles was also associated with all-cause mortality risk, showing the highest risk values among those with no roles compared with those with triple roles (HR: 1.66 in men and 1.78 in women). The impact of the lack of a role was generally greater in men than in women and also in the middle-aged than in the elderly. A beneficial effect of multiple roles was suggested among Japanese. The fewer roles they had, the higher all-cause mortality risks were observed. The risk values of those with fewer roles were generally higher in men than in women and also in the middle-aged than in the elderly, partially explained by greater role overload in middle-aged women than other groups in Japan.

Personalized long-term prediction of cognitive function: Using sequential assessments to improve model performance.

PubMed

Chi, Chih-Lin; Zeng, Wenjun; Oh, Wonsuk; Borson, Soo; Lenskaia, Tatiana; Shen, Xinpeng; Tonellato, Peter J

2017-12-01

Prediction of onset and progression of cognitive decline and dementia is important both for understanding the underlying disease processes and for planning health care for populations at risk. Predictors identified in research studies are typically accessed at one point in time. In this manuscript, we argue that an accurate model for predicting cognitive status over relatively long periods requires inclusion of time-varying components that are sequentially assessed at multiple time points (e.g., in multiple follow-up visits). We developed a pilot model to test the feasibility of using either estimated or observed risk factors to predict cognitive status. We developed two models, the first using a sequential estimation of risk factors originally obtained from 8 years prior, then improved by optimization. This model can predict how cognition will change over relatively long time periods. The second model uses observed rather than estimated time-varying risk factors and, as expected, results in better prediction. This model can predict when newly observed data are acquired in a follow-up visit. Performances of both models that are evaluated in10-fold cross-validation and various patient subgroups show supporting evidence for these pilot models. Each model consists of multiple base prediction units (BPUs), which were trained using the same set of data. The difference in usage and function between the two models is the source of input data: either estimated or observed data. In the next step of model refinement, we plan to integrate the two types of data together to flexibly predict dementia status and changes over time, when some time-varying predictors are measured only once and others are measured repeatedly. Computationally, both data provide upper and lower bounds for predictive performance. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

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

2014-03-01

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

Using multiple lines of evidence to assess the risk of ecosystem collapse

PubMed Central

Regan, Tracey J.; Dinh, Minh Ngoc; Ferrari, Renata; Keith, David A.; Lester, Rebecca; Mouillot, David; Murray, Nicholas J.; Nguyen, Hoang Anh; Nicholson, Emily

2017-01-01

Effective ecosystem risk assessment relies on a conceptual understanding of ecosystem dynamics and the synthesis of multiple lines of evidence. Risk assessment protocols and ecosystem models integrate limited observational data with threat scenarios, making them valuable tools for monitoring ecosystem status and diagnosing key mechanisms of decline to be addressed by management. We applied the IUCN Red List of Ecosystems criteria to quantify the risk of collapse of the Meso-American Reef, a unique ecosystem containing the second longest barrier reef in the world. We collated a wide array of empirical data (field and remotely sensed), and used a stochastic ecosystem model to backcast past ecosystem dynamics, as well as forecast future ecosystem dynamics under 11 scenarios of threat. The ecosystem is at high risk from mass bleaching in the coming decades, with compounding effects of ocean acidification, hurricanes, pollution and fishing. The overall status of the ecosystem is Critically Endangered (plausibly Vulnerable to Critically Endangered), with notable differences among Red List criteria and data types in detecting the most severe symptoms of risk. Our case study provides a template for assessing risks to coral reefs and for further application of ecosystem models in risk assessment. PMID:28931744

Using multiple lines of evidence to assess the risk of ecosystem collapse.

PubMed

Bland, Lucie M; Regan, Tracey J; Dinh, Minh Ngoc; Ferrari, Renata; Keith, David A; Lester, Rebecca; Mouillot, David; Murray, Nicholas J; Nguyen, Hoang Anh; Nicholson, Emily

2017-09-27

Effective ecosystem risk assessment relies on a conceptual understanding of ecosystem dynamics and the synthesis of multiple lines of evidence. Risk assessment protocols and ecosystem models integrate limited observational data with threat scenarios, making them valuable tools for monitoring ecosystem status and diagnosing key mechanisms of decline to be addressed by management. We applied the IUCN Red List of Ecosystems criteria to quantify the risk of collapse of the Meso-American Reef, a unique ecosystem containing the second longest barrier reef in the world. We collated a wide array of empirical data (field and remotely sensed), and used a stochastic ecosystem model to backcast past ecosystem dynamics, as well as forecast future ecosystem dynamics under 11 scenarios of threat. The ecosystem is at high risk from mass bleaching in the coming decades, with compounding effects of ocean acidification, hurricanes, pollution and fishing. The overall status of the ecosystem is Critically Endangered (plausibly Vulnerable to Critically Endangered), with notable differences among Red List criteria and data types in detecting the most severe symptoms of risk. Our case study provides a template for assessing risks to coral reefs and for further application of ecosystem models in risk assessment. © 2017 The Authors.

Markov chains and semi-Markov models in time-to-event analysis.

PubMed

Abner, Erin L; Charnigo, Richard J; Kryscio, Richard J

2013-10-25

A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields.

Markov chains and semi-Markov models in time-to-event analysis

PubMed Central

Abner, Erin L.; Charnigo, Richard J.; Kryscio, Richard J.

2014-01-01

A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields. PMID:24818062

Combined impact of lead, cadmium, polychlorinated biphenyls and non-chemical risk factors on blood pressure in NHANES

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

Peters, Junenette L., E-mail: petersj@bu.edu; Patricia Fabian, M., E-mail: pfabian@bu.edu; Levy, Jonathan I., E-mail: jonlevy@bu.edu

High blood pressure is associated with exposure to multiple chemical and non-chemical risk factors, but epidemiological analyses to date have not assessed the combined effects of both chemical and non-chemical stressors on human populations in the context of cumulative risk assessment. We developed a novel modeling approach to evaluate the combined impact of lead, cadmium, polychlorinated biphenyls (PCBs), and multiple non-chemical risk factors on four blood pressure measures using data for adults aged ≥20 years from the National Health and Nutrition Examination Survey (1999–2008). We developed predictive models for chemical and other stressors. Structural equation models were applied to accountmore » for complex associations among predictors of stressors as well as blood pressure. Models showed that blood lead, serum PCBs, and established non-chemical stressors were significantly associated with blood pressure. Lead was the chemical stressor most predictive of diastolic blood pressure and mean arterial pressure, while PCBs had a greater influence on systolic blood pressure and pulse pressure, and blood cadmium was not a significant predictor of blood pressure. The simultaneously fit exposure models explained 34%, 43% and 52% of the variance for lead, cadmium and PCBs, respectively. The structural equation models were developed using predictors available from public data streams (e.g., U.S. Census), which would allow the models to be applied to any U.S. population exposed to these multiple stressors in order to identify high risk subpopulations, direct intervention strategies, and inform public policy. - Highlights: • We evaluated joint impact of chemical and non-chemical stressors on blood pressure. • We built predictive models for lead, cadmium and polychlorinated biphenyls (PCBs). • Our approach allows joint evaluation of predictors from population-specific data. • Lead, PCBs and established non-chemical stressors were related to blood pressure. • Framework allows cumulative risk assessment in specific geographic settings.« less

The quandaries and promise of risk management: a scientist's perspective on integration of science and management.

Treesearch

B.G. Marcot

2007-01-01

This paper briefly lists constraints and problems of traditional approaches to natural resource risk analysis and risk management. Such problems include disparate definitions of risk, multiple and conflicting objectives and decisions, conflicting interpretations of uncertainty, and failure of articulating decision criteria, risk attitudes, modeling assumptions, and...

Anthropometric characteristics and risk of multiple myeloma.

PubMed

Blair, Cindy K; Cerhan, James R; Folsom, Aaron R; Ross, Julie A

2005-09-01

Few studies have examined obesity and risk for multiple myeloma, and the results are inconsistent. Laboratory evidence suggests mechanisms through which obesity could influence carcinogenesis of this hematopoietic malignancy. We examined the association between anthropometric characteristics and incident multiple myeloma in a prospective, population-based sample of 37,083 postmenopausal women. In 1986, the women completed a mailed questionnaire that included self-report of height and weight, and friend measurement of waist and hip circumferences. During 16 years of follow up, 95 cases of multiple myeloma were identified through linkage to the Iowa Cancer Registry. In an age-adjusted model, women in the highest category of several anthropometric measurements compared with the lowest category were at increased risk of developing multiple myeloma. For body mass index (kg/m), the rate ratio (95% confidence interval) was 1.5 (0.92-2.6); for weight, 1.9 (1.1-3.4); for waist circumference, 2.0 (1.1-3.5); and for hip circumference, 1.8 (1.0-3.0). Greater adiposity may increase the risk of multiple myeloma.

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

PubMed Central

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

2017-01-01

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

Quantitative risk assessment system (QRAS)

NASA Technical Reports Server (NTRS)

Tan, Zhibin (Inventor); Mosleh, Ali (Inventor); Weinstock, Robert M (Inventor); Smidts, Carol S (Inventor); Chang, Yung-Hsien (Inventor); Groen, Francisco J (Inventor); Swaminathan, Sankaran (Inventor)

2001-01-01

A quantitative risk assessment system (QRAS) builds a risk model of a system for which risk of failure is being assessed, then analyzes the risk of the system corresponding to the risk model. The QRAS performs sensitivity analysis of the risk model by altering fundamental components and quantifications built into the risk model, then re-analyzes the risk of the system using the modifications. More particularly, the risk model is built by building a hierarchy, creating a mission timeline, quantifying failure modes, and building/editing event sequence diagrams. Multiplicities, dependencies, and redundancies of the system are included in the risk model. For analysis runs, a fixed baseline is first constructed and stored. This baseline contains the lowest level scenarios, preserved in event tree structure. The analysis runs, at any level of the hierarchy and below, access this baseline for risk quantitative computation as well as ranking of particular risks. A standalone Tool Box capability exists, allowing the user to store application programs within QRAS.

Plasma Free Amino Acid Profiles Predict Four-Year Risk of Developing Diabetes, Metabolic Syndrome, Dyslipidemia, and Hypertension in Japanese Population

PubMed Central

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

2015-01-01

Plasma free amino acid (PFAA) profile is highlighted in its association with visceral obesity and hyperinsulinemia, and future diabetes. Indeed PFAA profiling potentially can evaluate individuals’ future risks of developing lifestyle-related diseases, in addition to diabetes. However, few studies have been performed especially in Asian populations, about the optimal combination of PFAAs for evaluating health risks. We quantified PFAA levels in 3,701 Japanese subjects, and determined visceral fat area (VFA) and two-hour post-challenge insulin (Ins120 min) values in 865 and 1,160 subjects, respectively. Then, models between PFAA levels and the VFA or Ins120 min values were constructed by multiple linear regression analysis with variable selection. Finally, a cohort study of 2,984 subjects to examine capabilities of the obtained models for predicting four-year risk of developing new-onset lifestyle-related diseases was conducted. The correlation coefficients of the obtained PFAA models against VFA or Ins120 min were higher than single PFAA level. Our models work well for future risk prediction. Even after adjusting for commonly accepted multiple risk factors, these models can predict future development of diabetes, metabolic syndrome, and dyslipidemia. PFAA profiles confer independent and differing contributions to increasing the lifestyle-related disease risks in addition to the currently known factors in a general Japanese population. PMID:26156880

Prediction of HIV Sexual Risk Behaviors among Disadvantaged African American Adults using a Syndemic Conceptual Framework

PubMed Central

Nehl, Eric J.; Klein, Hugh; Sterk, Claire E.; Elifson, Kirk W.

2015-01-01

The focus of this paper is on HIV sexual risk taking among a community-based sample of disadvantaged African American adults. The objective is to examine multiple factors associated with sexual HIV risk behaviors within a syndemic conceptual framework. Face-to-face, computer-assisted, structured interviews were conducted with 1,535 individuals in Atlanta, Georgia. Bivariate analyses indicated a high level of relationships among the HIV sexual risks and other factors. Results from multivariate models indicated that gender, sexual orientation, relationship status, self-esteem, condom use self-efficacy, sex while the respondent was high, and sex while the partner was high were significant predictors of condomless sex. Additionally, a multivariate additive model of risk behaviors indicated that the number of health risks significantly increased the risk of condomless sex. This intersection of HIV sexual risk behaviors and their associations with various other behavioral, socio-demographics, and psychological functioning factors helps explain HIV risk-taking among this sample of African American adults and highlights the need for research and practice that accounts for multiple health behaviors and problems. PMID:26188618

Occupational exposure to methylene chloride and risk of cancer: a meta-analysis.

PubMed

Liu, Tao; Xu, Qin-er; Zhang, Chuan-hui; Zhang, Peng

2013-12-01

We searched MEDLINE and EMBASE for epidemiologic studies on occupational exposure to methylene chloride and risk of cancer. Estimates of study-specific odds ratios (ORs) were calculated using inverse-variance-weighted fixed-effects models and random-effects models. Statistical tests for heterogeneity were applied. We summarized data from five cohort studies and 13 case-control studies. The pooled OR for multiple myeloma was (OR 2.04; 95 % CI 1.31-3.17) in relation to occupational exposure to methylene chloride but not for non-Hodgkin's lymphoma, leukemia, breast, bronchus, trachea and lung, brain and other CNS, biliary passages and liver, prostate, pancreas, and rectum. Furthermore, we focused on specific outcomes for non-Hodgkin's lymphoma and multiple myeloma because of exposure misclassification. The pooling OR for non-Hodgkin's lymphoma and multiple myeloma was 1.42 (95 % CI 1.10-1.83) with moderate degree of heterogeneity among the studies (I (2) = 26.9 %, p = 0.205). We found an excess risk of multiple myeloma. The non-Hodgkin's lymphoma and leukemia that have shown weak effects should be investigated further.

A spatially explicit model for estimating risks of pesticide exposure on bird populations

EPA Science Inventory

Product Description (FY17 Key Product): Current ecological risk assessment for pesticides under FIFRA relies on risk quotients (RQs), which suffer from significant methodological shortcomings. For example, RQs do not integrate adverse effects arising from multiple demographic pr...

Accidental Water Pollution Risk Analysis of Mine Tailings Ponds in Guanting Reservoir Watershed, Zhangjiakou City, China.

PubMed

Liu, Renzhi; Liu, Jing; Zhang, Zhijiao; Borthwick, Alistair; Zhang, Ke

2015-12-02

Over the past half century, a surprising number of major pollution incidents occurred due to tailings dam failures. Most previous studies of such incidents comprised forensic analyses of environmental impacts after a tailings dam failure, with few considering the combined pollution risk before incidents occur at a watershed-scale. We therefore propose Watershed-scale Tailings-pond Pollution Risk Analysis (WTPRA), designed for multiple mine tailings ponds, stemming from previous watershed-scale accidental pollution risk assessments. Transferred and combined risk is embedded using risk rankings of multiple routes of the "source-pathway-target" in the WTPRA. The previous approach is modified using multi-criteria analysis, dam failure models, and instantaneous water quality models, which are modified for application to multiple tailings ponds. The study area covers the basin of Gutanting Reservoir (the largest backup drinking water source for Beijing) in Zhangjiakou City, where many mine tailings ponds are located. The resultant map shows that risk is higher downstream of Gutanting Reservoir and in its two tributary basins (i.e., Qingshui River and Longyang River). Conversely, risk is lower in the midstream and upstream reaches. The analysis also indicates that the most hazardous mine tailings ponds are located in Chongli and Xuanhua, and that Guanting Reservoir is the most vulnerable receptor. Sensitivity and uncertainty analyses are performed to validate the robustness of the WTPRA method.

Accidental Water Pollution Risk Analysis of Mine Tailings Ponds in Guanting Reservoir Watershed, Zhangjiakou City, China

PubMed Central

Liu, Renzhi; Liu, Jing; Zhang, Zhijiao; Borthwick, Alistair; Zhang, Ke

2015-01-01

Over the past half century, a surprising number of major pollution incidents occurred due to tailings dam failures. Most previous studies of such incidents comprised forensic analyses of environmental impacts after a tailings dam failure, with few considering the combined pollution risk before incidents occur at a watershed-scale. We therefore propose Watershed-scale Tailings-pond Pollution Risk Analysis (WTPRA), designed for multiple mine tailings ponds, stemming from previous watershed-scale accidental pollution risk assessments. Transferred and combined risk is embedded using risk rankings of multiple routes of the “source-pathway-target” in the WTPRA. The previous approach is modified using multi-criteria analysis, dam failure models, and instantaneous water quality models, which are modified for application to multiple tailings ponds. The study area covers the basin of Gutanting Reservoir (the largest backup drinking water source for Beijing) in Zhangjiakou City, where many mine tailings ponds are located. The resultant map shows that risk is higher downstream of Gutanting Reservoir and in its two tributary basins (i.e., Qingshui River and Longyang River). Conversely, risk is lower in the midstream and upstream reaches. The analysis also indicates that the most hazardous mine tailings ponds are located in Chongli and Xuanhua, and that Guanting Reservoir is the most vulnerable receptor. Sensitivity and uncertainty analyses are performed to validate the robustness of the WTPRA method. PMID:26633450

Morphological characteristics associated with rupture risk of multiple intracranial aneurysms.

PubMed

Wang, Guang-Xian; Liu, Lan-Lan; Wen, Li; Cao, Yun-Xing; Pei, Yu-Chun; Zhang, Dong

2017-10-01

To identify the morphological parameters that are related to intracranial aneurysms (IAs) rupture using a case-control model. A total of 107 patients with multiple IAs and aneurysmal subarachnoid hemorrhage between August 2011 and February 2017 were enrolled in this study. Characteristics of IAs location, shape, neck width, perpendicular height, depth, maximum size, flow angle, parent vessel diameter (PVD), aspect ratio (AR) and size ratio (SR) were evaluated using CT angiography. Multiple logistic regression analysis was used to identify the independent risk factors associated with IAs rupture. Receiver operating characteristic curve analysis was performed on the final model, and the optimal thresholds were obtained. IAs located in the internal carotid artery (ICA) was associated with a negative risk of rupture, whereas AR, SR1 (height/PVD) and SR2 (depth/PVD) were associated with increased risk of rupture. When SR was calculated differently, the odds ratio values of these factors were also different. The receiver operating characteristic curve showed that AR, SR1 and SR2 had cut-off values of 1.01, 1.48 and 1.40, respectively. SR3 (maximum size/PVD) was not associated with IAs rupture. IAs located in the ICA are associated with a negative risk of rupture, while high AR (>1.01), SR1 (>1.48) or SR2 (>1.40) are risk factors for multiple IAs rupture. Copyright © 2017 Hainan Medical University. Production and hosting by Elsevier B.V. All rights reserved.

Climate change and health modeling: horses for courses.

PubMed

Ebi, Kristie L; Rocklöv, Joacim

2014-01-01

Mathematical and statistical models are needed to understand the extent to which weather, climate variability, and climate change are affecting current and may affect future health burdens in the context of other risk factors and a range of possible development pathways, and the temporal and spatial patterns of any changes. Such understanding is needed to guide the design and the implementation of adaptation and mitigation measures. Because each model projection captures only a narrow range of possible futures, and because models serve different purposes, multiple models are needed for each health outcome ('horses for courses'). Multiple modeling results can be used to bracket the ranges of when, where, and with what intensity negative health consequences could arise. This commentary explores some climate change and health modeling issues, particularly modeling exposure-response relationships, developing early warning systems, projecting health risks over coming decades, and modeling to inform decision-making. Research needs are also suggested.

Probabilistic risk models for multiple disturbances: an example of forest insects and wildfires

Treesearch

Haiganoush K. Preisler; Alan A. Ager; Jane L. Hayes

2010-01-01

Building probabilistic risk models for highly random forest disturbances like wildfire and forest insect outbreaks is a challenging. Modeling the interactions among natural disturbances is even more difficult. In the case of wildfire and forest insects, we looked at the probability of a large fire given an insect outbreak and also the incidence of insect outbreaks...

Modeling Joint Exposures and Health Outcomes for Cumulative Risk Assessment: the Case of Radon and Smoking

EPA Science Inventory

Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case exam...

Departures From Optimality When Pursuing Multiple Approach or Avoidance Goals

PubMed Central

2016-01-01

This article examines how people depart from optimality during multiple-goal pursuit. The authors operationalized optimality using dynamic programming, which is a mathematical model used to calculate expected value in multistage decisions. Drawing on prospect theory, they predicted that people are risk-averse when pursuing approach goals and are therefore more likely to prioritize the goal in the best position than the dynamic programming model suggests is optimal. The authors predicted that people are risk-seeking when pursuing avoidance goals and are therefore more likely to prioritize the goal in the worst position than is optimal. These predictions were supported by results from an experimental paradigm in which participants made a series of prioritization decisions while pursuing either 2 approach or 2 avoidance goals. This research demonstrates the usefulness of using decision-making theories and normative models to understand multiple-goal pursuit. PMID:26963081

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

PubMed

Ostaszewski, Krzysztof; Zimmerman, Marc A

2006-12-01

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

Multiple environmental contexts and preterm birth risks

EPA Science Inventory

Human health is affected by simultaneous exposure to numerous stressors and amenities, but research often focuses on single exposure models. To address this, a United States county-level Multiple Environmental Domain Index (MEDI) was constructed with data representing five envir...

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

PubMed

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

2014-12-23

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

Aggression at Age 5 as a Function of Prenatal Exposure to Cocaine, Gender, and Environmental Risk

PubMed Central

Bendersky, Margaret; Bennett, David; Lewis, Michael

2006-01-01

Objective To examine childhood aggression at age 5 in a multiple risk model that includes cocaine exposure, environmental risk, and gender as predictors. Methods Aggression was assessed in 206 children by using multiple methods including teacher report, parent report, child’s response to hypothetical provocations, and child’s observed behavior. Also examined was a composite score that reflected high aggression across contexts. Results Multiple regression analyses indicated that a significant amount of variance in each of the aggression measures and the composite was explained by the predictors. The variables that were independently related differed depending on the outcome. Cocaine exposure, gender, and environmental risk were all related to the composite aggression score. Conclusions Cocaine exposure, being male, and a high-risk environment were all predictive of aggressive behavior at 5 years. It is this group of exposed boys at high environmental risk that is most likely to show continued aggression over time. PMID:15827351

A retrospective likelihood approach for efficient integration of multiple omics factors in case-control association studies.

PubMed

Balliu, Brunilda; Tsonaka, Roula; Boehringer, Stefan; Houwing-Duistermaat, Jeanine

2015-03-01

Integrative omics, the joint analysis of outcome and multiple types of omics data, such as genomics, epigenomics, and transcriptomics data, constitute a promising approach for powerful and biologically relevant association studies. These studies often employ a case-control design, and often include nonomics covariates, such as age and gender, that may modify the underlying omics risk factors. An open question is how to best integrate multiple omics and nonomics information to maximize statistical power in case-control studies that ascertain individuals based on the phenotype. Recent work on integrative omics have used prospective approaches, modeling case-control status conditional on omics, and nonomics risk factors. Compared to univariate approaches, jointly analyzing multiple risk factors with a prospective approach increases power in nonascertained cohorts. However, these prospective approaches often lose power in case-control studies. In this article, we propose a novel statistical method for integrating multiple omics and nonomics factors in case-control association studies. Our method is based on a retrospective likelihood function that models the joint distribution of omics and nonomics factors conditional on case-control status. The new method provides accurate control of Type I error rate and has increased efficiency over prospective approaches in both simulated and real data. © 2015 Wiley Periodicals, Inc.

Individual and social determinants of multiple chronic disease behavioral risk factors among youth.

PubMed

Alamian, Arsham; Paradis, Gilles

2012-03-22

Behavioral risk factors are known to co-occur among youth, and to increase risks of chronic diseases morbidity and mortality later in life. However, little is known about determinants of multiple chronic disease behavioral risk factors, particularly among youth. Previous studies have been cross-sectional and carried out without a sound theoretical framework. Using longitudinal data (n = 1135) from Cycle 4 (2000-2001), Cycle 5 (2002-2003) and Cycle 6 (2004-2005) of the National Longitudinal Survey of Children and Youth, a nationally representative sample of Canadian children who are followed biennially, the present study examines the influence of a set of conceptually-related individual/social distal variables (variables situated at an intermediate distance from behaviors), and individual/social ultimate variables (variables situated at an utmost distance from behaviors) on the rate of occurrence of multiple behavioral risk factors (physical inactivity, sedentary behavior, tobacco smoking, alcohol drinking, and high body mass index) in a sample of children aged 10-11 years at baseline. Multiple behavioral risk factors were assessed using a multiple risk factor score. All statistical analyses were performed using SAS, version 9.1, and SUDAAN, version 9.01. Multivariate longitudinal Poisson models showed that social distal variables including parental/peer smoking and peer drinking (Log-likelihood ratio (LLR) = 187.86, degrees of freedom (DF) = 8, p < .001), as well as individual distal variables including low self-esteem (LLR = 76.94, DF = 4, p < .001) increased the rate of occurrence of multiple behavioral risk factors. Individual ultimate variables including age, sex, and anxiety (LLR = 9.34, DF = 3, p < .05), as well as social ultimate variables including family socioeconomic status, and family structure (LLR = 10.93, DF = 5, p = .05) contributed minimally to the rate of co-occurrence of behavioral risk factors. The results suggest targeting individual/social distal variables in prevention programs of multiple chronic disease behavioral risk factors among youth.

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.

Evaluation of machine learning algorithms for improved risk assessment for Down's syndrome.

PubMed

Koivu, Aki; Korpimäki, Teemu; Kivelä, Petri; Pahikkala, Tapio; Sairanen, Mikko

2018-05-04

Prenatal screening generates a great amount of data that is used for predicting risk of various disorders. Prenatal risk assessment is based on multiple clinical variables and overall performance is defined by how well the risk algorithm is optimized for the population in question. This article evaluates machine learning algorithms to improve performance of first trimester screening of Down syndrome. Machine learning algorithms pose an adaptive alternative to develop better risk assessment models using the existing clinical variables. Two real-world data sets were used to experiment with multiple classification algorithms. Implemented models were tested with a third, real-world, data set and performance was compared to a predicate method, a commercial risk assessment software. Best performing deep neural network model gave an area under the curve of 0.96 and detection rate of 78% with 1% false positive rate with the test data. Support vector machine model gave area under the curve of 0.95 and detection rate of 61% with 1% false positive rate with the same test data. When compared with the predicate method, the best support vector machine model was slightly inferior, but an optimized deep neural network model was able to give higher detection rates with same false positive rate or similar detection rate but with markedly lower false positive rate. This finding could further improve the first trimester screening for Down syndrome, by using existing clinical variables and a large training data derived from a specific population. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development of in Vivo Biomarkers for Progressive Tau Pathology after Traumatic Brain Injury

DTIC Science & Technology

2015-02-01

13. SUPPLEMENTARY NOTES 14. ABSTRACT Athletes in contact sports who have sustained multiple concussive traumatic brain injuries are at high risk for...multiple concussive traumatic brain injuries 15-17 may also be at risk for this condition. Currently, there are no methods to identify progressive tau...after traumatic brain injury. Progress to date: To date, none of the attempts to model progressive tau pathology after repetitive concussive TBI in

A new multiple regression model to identify multi-family houses with a high prevalence of sick building symptoms "SBS", within the healthy sustainable house study in Stockholm (3H).

PubMed

Engvall, Karin; Hult, M; Corner, R; Lampa, E; Norbäck, D; Emenius, G

2010-01-01

The aim was to develop a new model to identify residential buildings with higher frequencies of "SBS" than expected, "risk buildings". In 2005, 481 multi-family buildings with 10,506 dwellings in Stockholm were studied by a new stratified random sampling. A standardised self-administered questionnaire was used to assess "SBS", atopy and personal factors. The response rate was 73%. Statistical analysis was performed by multiple logistic regressions. Dwellers owning their building reported less "SBS" than those renting. There was a strong relationship between socio-economic factors and ownership. The regression model, ended up with high explanatory values for age, gender, atopy and ownership. Applying our model, 9% of all residential buildings in Stockholm were classified as "risk buildings" with the highest proportion in houses built 1961-1975 (26%) and lowest in houses built 1985-1990 (4%). To identify "risk buildings", it is necessary to adjust for ownership and population characteristics.

A Nationwide Epidemiologic Modeling Study of LD: Risk, Protection, and Unintended Impact

ERIC Educational Resources Information Center

McDermott, Paul A.; Goldberg, Michelle M.; Watkins, Marley W.; Stanley, Jeanne L.; Glutting, Joseph J.

2006-01-01

Through multiple logistic regression modeling, this article explores the relative importance of risk and protective factors associated with learning disabilities (LD). A representative national sample of 6- to 17-year-old students (N = 1,268) was drawn by random stratification and classified by the presence versus absence of LD in reading,…

Rift Valley fever risk map model and seroprevalence in selected wild ungulates and camels from Kenya

USDA-ARS?s Scientific Manuscript database

Since the first isolation of Rift Valley fever virus (RVFV) in the 1930s, there have been multiple epizootics and epidemics in animals and humans in sub-Saharan Africa. Prospective climate-based models have recently been developed that flag areas at risk of RVFV transmission in endemic regions based...

Risk assessment and adaptive runoff utilization in water resource system considering the complex relationship among water supply, electricity generation and environment

NASA Astrophysics Data System (ADS)

Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.

2017-12-01

Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.

Geographic risk modeling of childhood cancer relative to county-level crops, hazardous air pollutants and population density characteristics in Texas.

PubMed

Thompson, James A; Carozza, Susan E; Zhu, Li

2008-09-25

Childhood cancer has been linked to a variety of environmental factors, including agricultural activities, industrial pollutants and population mixing, but etiologic studies have often been inconclusive or inconsistent when considering specific cancer types. More specific exposure assessments are needed. It would be helpful to optimize future studies to incorporate knowledge of high-risk locations or geographic risk patterns. The objective of this study was to evaluate potential geographic risk patterns in Texas accounting for the possibility that multiple cancers may have similar geographic risks patterns. A spatio-temporal risk modeling approach was used, whereby 19 childhood cancer types were modeled as potentially correlated within county-years. The standard morbidity ratios were modeled as functions of intensive crop production, intensive release of hazardous air pollutants, population density, and rapid population growth. There was supportive evidence for elevated risks for germ cell tumors and "other" gliomas in areas of intense cropping and for hepatic tumors in areas of intense release of hazardous air pollutants. The risk for Hodgkin lymphoma appeared to be reduced in areas of rapidly growing population. Elevated spatial risks included four cancer histotypes, "other" leukemias, Central Nervous System (CNS) embryonal tumors, CNS other gliomas and hepatic tumors with greater than 95% likelihood of elevated risks in at least one county. The Bayesian implementation of the Multivariate Conditional Autoregressive model provided a flexible approach to the spatial modeling of multiple childhood cancer histotypes. The current study identified geographic factors supporting more focused studies of germ cell tumors and "other" gliomas in areas of intense cropping, hepatic cancer near Hazardous Air Pollutant (HAP) release facilities and specific locations with increased risks for CNS embryonal tumors and for "other" leukemias. Further study should be performed to evaluate potentially lower risk for Hodgkin lymphoma and malignant bone tumors in counties with rapidly growing population.

Coffee and Green Tea Consumption and Subsequent Risk of Malignant Lymphoma and Multiple Myeloma in Japan: The Japan Public Health Center-based Prospective Study.

PubMed

Ugai, Tomotaka; Matsuo, Keitaro; Sawada, Norie; Iwasaki, Motoki; Yamaji, Taiki; Shimazu, Taichi; Sasazuki, Shizuka; Inoue, Manami; Kanda, Yoshinobu; Tsugane, Shoichiro

2017-08-01

Background: The aim of this study was to investigate the association of coffee and green tea consumption and the risk of malignant lymphoma and multiple myeloma in a large-scale population-based cohort study in Japan. Methods: In this analysis, a total of 95,807 Japanese subjects (45,937 men and 49,870 women; ages 40-69 years at baseline) of the Japan Public Health Center-based Prospective Study who completed a questionnaire about their coffee and green tea consumption were followed up until December 31, 2012, for an average of 18 years. HRs and 95% confidence intervals were estimated using a Cox regression model adjusted for potential confounders as a measure of association between the risk of malignant lymphoma and multiple myeloma associated with coffee and green tea consumption at baseline. Results: During the follow-up period, a total of 411 malignant lymphoma cases and 138 multiple myeloma cases were identified. Overall, our findings showed no significant association between coffee or green tea consumption and the risk of malignant lymphoma or multiple myeloma for both sexes. Conclusions: In this study, we observed no significant association between coffee or green tea consumption and the risk of malignant lymphoma or multiple myeloma. Impact: Our results do not support an association between coffee or green tea consumption and the risk of malignant lymphoma or multiple myeloma. Cancer Epidemiol Biomarkers Prev; 26(8); 1352-6. ©2017 AACR . ©2017 American Association for Cancer Research.

Comparative analysis of Multiple risks in the Western part of Georgia

NASA Astrophysics Data System (ADS)

Tsereteli, N.; Chelidze, T.; Varazanashvili, O.; Amiranashvili, A.

2009-04-01

Georgia is prone to catastrophes. In the last two decades, there have occurred the following natural disasters: (a) Avalanches in Svaneti and Khevsureti, (b) landslides in the mountainous Achara, floods, (c) hurricane and drought in West and East Georgia, (d) Racha earthquake of 1991 and (e) the Tbilisi Earthquake of 2002. These phenomena are very special both from ecological and from social-economical points of view. By the disaster risk index obtained by the UNDP, Georgia is similar to countries with medium and high level risk. Therefore, natural disasters in Georgia are considered as a negative factor in the development process of the country. This implies the necessity of more active actions by all possible means to reduce the risk of natural disasters at each level and maintain the sustainable economic development of the country, including good education at the universities and schools for real understanding of natural hazards. The main goal of the work here is the assessment of 12 widespread natural disasters and multiple risks for political districts in West Georgia. These natural disasters include earthquakes, landslides, avalanches, floods, mudflows, droughts, hurricanes, lightning, hail, glaze, freezes, mists. The research was based on the following steps: (a) Creation of electronic detailed databases of natural disasters that occurred in Georgia. These databases consist of the parameters of such hazardous phenomena class that caused natural disasters. (b) Quantitative investigation of energetic and spatial-time regularities of 12 natural disasters for the territory of Georgia. Estimation of people and environment (technosphere) vulnerability. (c) Elaboration of mathematical models and algorithms of disasters multiple risks taking into account the concrete conditions: (i) Sharing and generalization of gathered experience in the world. This allows more proper and wide comparison of the multiple risks of Caucasus countries; (ii) Taking into account the general formula of risk = hazard x damage, transfer from analyze of separate risk to its complex one; (iii) Taking into account the reality of Georgia and complex scheme of revealed risk in separate district of the country during the construction of multiple risk models. Investigation of each step reveals problem according to essential parts in the multiple risks assessments, such as communication between scientists, engineers, civil protection and other agencies. A big gap in such kind of relationship leads to lack of important information, such as economic loss according to each hazard. Low level in education according in natural hazards cause bad management and sometimes increase economic and mortality loss.

Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model

NASA Astrophysics Data System (ADS)

Hanley, J.; Stevens-Goodnight, S.; Kulkarni, S.; Bustamante, D.; Fytilis, N.; Goff, P.; Monroy, C.; Morrissey, L. A.; Orantes, L.; Stevens, L.; Dorn, P.; Lucero, D.; Rios, J.; Rizzo, D. M.

2012-12-01

The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that the system's structure generates its behavior; and STELLA®'s graphical interface allows researchers at multiple educational levels to observe patterns and trends as the system changes over time. Graduate students and postdoctoral researchers will utilize these initial models to more efficiently communicate and transfer knowledge across disciplines prior to generating more novel and complex disease risk models. The hope is that these models will improve causal viewpoints, understanding of the system patterns, and how to best mitigate disease risk across multiple spatial scales. Yasar O, Landau RH (2003) Elements of computational science and engineering education. Siam Review 45(4): 787-805.

Population-based absolute risk estimation with survey data

PubMed Central

Kovalchik, Stephanie A.; Pfeiffer, Ruth M.

2013-01-01

Absolute risk is the probability that a cause-specific event occurs in a given time interval in the presence of competing events. We present methods to estimate population-based absolute risk from a complex survey cohort that can accommodate multiple exposure-specific competing risks. The hazard function for each event type consists of an individualized relative risk multiplied by a baseline hazard function, which is modeled nonparametrically or parametrically with a piecewise exponential model. An influence method is used to derive a Taylor-linearized variance estimate for the absolute risk estimates. We introduce novel measures of the cause-specific influences that can guide modeling choices for the competing event components of the model. To illustrate our methodology, we build and validate cause-specific absolute risk models for cardiovascular and cancer deaths using data from the National Health and Nutrition Examination Survey. Our applications demonstrate the usefulness of survey-based risk prediction models for predicting health outcomes and quantifying the potential impact of disease prevention programs at the population level. PMID:23686614

"An integrative formal model of motivation and decision making: The MGPM*": Correction to Ballard et al. (2016).

PubMed

2017-02-01

Reports an error in "An integrative formal model of motivation and decision making: The MGPM*" by Timothy Ballard, Gillian Yeo, Shayne Loft, Jeffrey B. Vancouver and Andrew Neal ( Journal of Applied Psychology , 2016[Sep], Vol 101[9], 1240-1265). Equation A3 contained an error. This correct equation is provided in the erratum. (The following abstract of the original article appeared in record 2016-28692-001.) We develop and test an integrative formal model of motivation and decision making. The model, referred to as the extended multiple-goal pursuit model (MGPM*), is an integration of the multiple-goal pursuit model (Vancouver, Weinhardt, & Schmidt, 2010) and decision field theory (Busemeyer & Townsend, 1993). Simulations of the model generated predictions regarding the effects of goal type (approach vs. avoidance), risk, and time sensitivity on prioritization. We tested these predictions in an experiment in which participants pursued different combinations of approach and avoidance goals under different levels of risk. The empirical results were consistent with the predictions of the MGPM*. Specifically, participants pursuing 1 approach and 1 avoidance goal shifted priority from the approach to the avoidance goal over time. Among participants pursuing 2 approach goals, those with low time sensitivity prioritized the goal with the larger discrepancy, whereas those with high time sensitivity prioritized the goal with the smaller discrepancy. Participants pursuing 2 avoidance goals generally prioritized the goal with the smaller discrepancy. Finally, all of these effects became weaker as the level of risk increased. We used quantitative model comparison to show that the MGPM* explained the data better than the original multiple-goal pursuit model, and that the major extensions from the original model were justified. The MGPM* represents a step forward in the development of a general theory of decision making during multiple-goal pursuit. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Proceedings of the 2006 Toxicology and Risk Assessment Conference: Applying Mode of Action in Risk Assessment

DTIC Science & Technology

2006-07-01

physiologically-based pharmacokinetic modeling of interactions and multiple route exposure assessment; and integrating relative potency factors with response...defaults, while at the other end is the use of extensive chemical-specific data in physiologically based pharmacokinetic (PBPK) modeling or even...for internal dosimetry as well as an in depth prospective on the use and limitations of physiologically based pharmacokinetic (PBPK) models in

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.

Conceptual models for cumulative risk assessment.

PubMed

Linder, Stephen H; Sexton, Ken

2011-12-01

In the absence of scientific consensus on an appropriate theoretical framework, cumulative risk assessment and related research have relied on speculative conceptual models. We argue for the importance of theoretical backing for such models and discuss 3 relevant theoretical frameworks, each supporting a distinctive "family" of models. Social determinant models postulate that unequal health outcomes are caused by structural inequalities; health disparity models envision social and contextual factors acting through individual behaviors and biological mechanisms; and multiple stressor models incorporate environmental agents, emphasizing the intermediary role of these and other stressors. The conclusion is that more careful reliance on established frameworks will lead directly to improvements in characterizing cumulative risk burdens and accounting for disproportionate adverse health effects.

Conceptual Models for Cumulative Risk Assessment

PubMed Central

Sexton, Ken

2011-01-01

In the absence of scientific consensus on an appropriate theoretical framework, cumulative risk assessment and related research have relied on speculative conceptual models. We argue for the importance of theoretical backing for such models and discuss 3 relevant theoretical frameworks, each supporting a distinctive “family” of models. Social determinant models postulate that unequal health outcomes are caused by structural inequalities; health disparity models envision social and contextual factors acting through individual behaviors and biological mechanisms; and multiple stressor models incorporate environmental agents, emphasizing the intermediary role of these and other stressors. The conclusion is that more careful reliance on established frameworks will lead directly to improvements in characterizing cumulative risk burdens and accounting for disproportionate adverse health effects. PMID:22021317

A review of vulnerability and risks for schizophrenia: Beyond the two hit hypothesis

PubMed Central

Davis, Justin; Eyre, Harris; Jacka, Felice N; Dodd, Seetal; Dean, Olivia; McEwen, Sarah; Debnath, Monojit; McGrath, John; Maes, Michael; Amminger, Paul; McGorry, Patrick D; Pantelis, Christos; Berk, Michael

2016-01-01

Schizophrenia risk has often been conceptualized using a model which requires two hits in order to generate the clinical phenotype—the first as an early priming in a genetically predisposed individual and the second a likely environmental insult. The aim of this paper was to review the literature and reformulate this binary risk-vulnerability model. We sourced the data for this narrative review from the electronic database PUBMED. Our search terms were not limited by language or date of publication. The development of schizophrenia may be driven by genetic vulnerability interacting with multiple vulnerability factors including lowered prenatal vitamin D exposure, viral infections, smoking intelligence quotient, social cognition cannabis use, social defeat, nutrition and childhood trauma. It is likely that these genetic risks, environmental risks and vulnerability factors are cumulative and interactive with each other and with critical periods of neurodevelopmental vulnerability. The development of schizophrenia is likely to be more complex and nuanced than the binary two hit model originally proposed nearly thirty years ago. Risk appears influenced by a more complex process involving genetic risk interfacing with multiple potentially interacting hits and vulnerability factors occurring at key periods of neurodevelopmental activity, which culminate in the expression of disease state. These risks are common across a number of neuropsychiatric and medical disorders, which might inform common preventive and intervention strategies across non-communicable disorders. PMID:27073049

Two approaches to incorporate clinical data uncertainty into multiple criteria decision analysis for benefit-risk assessment of medicinal products.

PubMed

Wen, Shihua; Zhang, Lanju; Yang, Bo

2014-07-01

The Problem formulation, Objectives, Alternatives, Consequences, Trade-offs, Uncertainties, Risk attitude, and Linked decisions (PrOACT-URL) framework and multiple criteria decision analysis (MCDA) have been recommended by the European Medicines Agency for structured benefit-risk assessment of medicinal products undergoing regulatory review. The objective of this article was to provide solutions to incorporate the uncertainty from clinical data into the MCDA model when evaluating the overall benefit-risk profiles among different treatment options. Two statistical approaches, the δ-method approach and the Monte-Carlo approach, were proposed to construct the confidence interval of the overall benefit-risk score from the MCDA model as well as other probabilistic measures for comparing the benefit-risk profiles between treatment options. Both approaches can incorporate the correlation structure between clinical parameters (criteria) in the MCDA model and are straightforward to implement. The two proposed approaches were applied to a case study to evaluate the benefit-risk profile of an add-on therapy for rheumatoid arthritis (drug X) relative to placebo. It demonstrated a straightforward way to quantify the impact of the uncertainty from clinical data to the benefit-risk assessment and enabled statistical inference on evaluating the overall benefit-risk profiles among different treatment options. The δ-method approach provides a closed form to quantify the variability of the overall benefit-risk score in the MCDA model, whereas the Monte-Carlo approach is more computationally intensive but can yield its true sampling distribution for statistical inference. The obtained confidence intervals and other probabilistic measures from the two approaches enhance the benefit-risk decision making of medicinal products. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

DEVELOPING THE NEXT GENERATION OF WATERSHED RISK ASSESSMENT AND MANAGEMENT MODELS: WHERE DO WE GO FROM HERE?

EPA Science Inventory

Wise management decisions to protect ecological resources require an understanding of how the resource is affcted by multiple stressors at multiple scales and how it responds to the change(s) effected by the management action.

HUMAN EXPOSURE MODELING FOR CUMULATIVE RISK

EPA Science Inventory

US EPA's Office of Research and Development (ORD) has identified cumulative risk assessment as a priority research area. This is because humans and other organisms are exposed to a multitude of chemicals, physical agents, and other stressors through multiple pathways, routes, an...

Multiplicative Effects of Social and Psychological Risk Factors on College Students' Suicidal Behaviors.

PubMed

Assari, Shervin

2018-05-17

Less is known about the multiplicative effects of social and psychological risk and protective factors of suicidality on college campuses. The current study aimed to investigate the multiplicative effects of social (identifying oneself as gay/lesbian, financial difficulty, violence victimization, and religiosity) and psychological (anxiety, depression, problem alcohol use, drug use) and risk/protective factors on suicidal behaviors among college students in the United States. Using a cross-sectional design, the Healthy Mind Study (HMS; 2016⁻2017), is a national online survey of college students in the United States. Social (identifying oneself as gay/lesbian, violence victimization, financial difficulty, and religiosity) and psychological (anxiety, depression, problem alcohol use, and drug use) risk/protective factors were assessed among 27,961 individuals. Three aspects of suicidality, including ideation, plan, and attempt, were also assessed. Logistic regression models were used for data analysis. Financial difficulty, violence victimization, identifying oneself as gay/lesbian, anxiety, depression, and drug use increased, while religiosity reduced the odds of suicidal behaviors. Multiplicative effects were found between the following social and psychological risk factors: (1) financial difficulty and anxiety; (2) financial difficulty and depression; (3) depression and drug use; (4) problem alcohol use and drug use; and (5) depression and problem alcohol use. There is a considerable overlap in the social and psychological processes, such as financial stress, mood disorders, and substance use problems, on risk of suicide in college students. As social and psychological risk factors do not operate independently, comprehensive suicidal risk evaluations that simultaneously address multiple social and psychological risk factors may be superior to programs that only address a single risk factor.

Multi-hazard risk analysis related to hurricanes

NASA Astrophysics Data System (ADS)

Lin, Ning

Hurricanes present major hazards to the United States. Associated with extreme winds, heavy rainfall, and storm surge, landfalling hurricanes often cause enormous structural damage to coastal regions. Hurricane damage risk assessment provides the basis for loss mitigation and related policy-making. Current hurricane risk models, however, often oversimplify the complex processes of hurricane damage. This dissertation aims to improve existing hurricane risk assessment methodology by coherently modeling the spatial-temporal processes of storm landfall, hazards, and damage. Numerical modeling technologies are used to investigate the multiplicity of hazards associated with landfalling hurricanes. The application and effectiveness of current weather forecasting technologies to predict hurricane hazards is investigated. In particular, the Weather Research and Forecasting model (WRF), with Geophysical Fluid Dynamics Laboratory (GFDL)'s hurricane initialization scheme, is applied to the simulation of the wind and rainfall environment during hurricane landfall. The WRF model is further coupled with the Advanced Circulation (AD-CIRC) model to simulate storm surge in coastal regions. A case study examines the multiple hazards associated with Hurricane Isabel (2003). Also, a risk assessment methodology is developed to estimate the probability distribution of hurricane storm surge heights along the coast, particularly for data-scarce regions, such as New York City. This methodology makes use of relatively simple models, specifically a statistical/deterministic hurricane model and the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model, to simulate large numbers of synthetic surge events, and conducts statistical analysis. The estimation of hurricane landfall probability and hazards are combined with structural vulnerability models to estimate hurricane damage risk. Wind-induced damage mechanisms are extensively studied. An innovative windborne debris risk model is developed based on the theory of Poisson random measure, substantiated by a large amount of empirical data. An advanced vulnerability assessment methodology is then developed, by integrating this debris risk model and a component-based pressure damage model, to predict storm-specific or annual damage to coastal residential neighborhoods. The uniqueness of this vulnerability model lies in its detailed description of the interaction between wind pressure and windborne debris effects over periods of strong winds, which is a major mechanism leading to structural failures during hurricanes.

Father Involvement and Young, Rural African American Men's Engagement in Substance Misuse and Multiple Sexual Partnerships.

PubMed

Barton, Allen W; Kogan, Steven M; Cho, Junhan; Brown, Geoffrey L

2015-12-01

This study was designed to examine the associations of biological father and social father involvement during childhood with African American young men's development and engagement in risk behaviors. With a sample of 505 young men living in the rural South of the United States, a dual mediation model was tested in which retrospective reports of involvement from biological fathers and social fathers were linked to young men's substance misuse and multiple sexual partnerships through men's relational schemas and future expectations. Results from structural equation modeling indicated that levels of involvement from biological fathers and social fathers predicted young men's relational schemas; only biological fathers' involvement predicted future expectations. In turn, future expectations predicted levels of substance misuse, and negative relational schemas predicted multiple sexual partnerships. Biological fathers' involvement evinced significant indirect associations with young men's substance misuse and multiple sexual partnerships through both schemas and expectations; social fathers' involvement exhibited an indirect association with multiple sexual partnerships through relational schemas. Findings highlight the unique influences of biological fathers and social fathers on multiple domains of African American young men's psychosocial development that subsequently render young men more or less likely to engage in risk behaviors.

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.

Diagnosis-Based Risk Adjustment for Medicare Capitation Payments

PubMed Central

Ellis, Randall P.; Pope, Gregory C.; Iezzoni, Lisa I.; Ayanian, John Z.; Bates, David W.; Burstin, Helen; Ash, Arlene S.

1996-01-01

Using 1991-92 data for a 5-percent Medicare sample, we develop, estimate, and evaluate risk-adjustment models that utilize diagnostic information from both inpatient and ambulatory claims to adjust payments for aged and disabled Medicare enrollees. Hierarchical coexisting conditions (HCC) models achieve greater explanatory power than diagnostic cost group (DCG) models by taking account of multiple coexisting medical conditions. Prospective models predict average costs of individuals with chronic conditions nearly as well as concurrent models. All models predict medical costs far more accurately than the current health maintenance organization (HMO) payment formula. PMID:10172666

Modelling the impact of correlations between condom use and sexual contact pattern on the dynamics of sexually transmitted infections.

PubMed

Yamamoto, Nao; Ejima, Keisuke; Nishiura, Hiroshi

2018-05-31

It is believed that sexually active people, i.e. people having multiple or concurrent sexual partners, are at a high risk of sexually transmitted infections (STI), but they are likely to be more aware of the risk and may exhibit greater fraction of the use of condom. The purpose of the present study is to examine the correlation between condom use and sexual contact pattern and clarify its impact on the transmission dynamics of STIs using a mathematical model. The definition of sexual contact pattern can be broad, but we focus on two specific aspects: (i) type of partnership (i.e. steady or casual partnership) and (ii) existence of concurrency (i.e. with single or multiple partners). Systematic review and meta-analysis of published studies are performed, analysing literature that epidemiologically examined the relationship between condom use and sexual contact pattern. Subsequently, we employ an epidemiological model and compute the reproduction number that accounts for with and without concurrency so that the corresponding coverage of condom use and its correlation with existence of concurrency can be explicitly investigated using the mathematical model. Combining the model with parameters estimated from the meta-analysis along with other assumed parameters, the impact of varying the proportion of population with multiple partners on the reproduction number is examined. Based on systematic review, we show that a greater number of people used condoms during sexual contact with casual partners than with steady partners. Furthermore, people with multiple partners use condoms more frequently than people with a single partner alone. Our mathematical model revealed a positive relationship between the effective reproduction number and the proportion of people with multiple partners. Nevertheless, the association was reversed to be negative by employing a slightly greater value of the relative risk of condom use for people with multiple partners than that empirically estimated. Depending on the correlation between condom use and the existence of concurrency, association between the proportion of people with multiple partners and the reproduction number can be reversed, suggesting the sexually active population is not necessary a primary target population to encourage condom use (i.e., sexually less active individuals could equivalently be a target in some cases).

An Updated Meta-Analysis of Risk of Multiple Sclerosis following Infectious Mononucleosis

PubMed Central

Handel, Adam E.; Williamson, Alexander J.; Disanto, Giulio; Handunnetthi, Lahiru; Giovannoni, Gavin; Ramagopalan, Sreeram V.

2010-01-01

Background Multiple sclerosis (MS) appears to develop in genetically susceptible individuals as a result of environmental exposures. Epstein-Barr virus (EBV) infection is an almost universal finding among individuals with MS. Symptomatic EBV infection as manifested by infectious mononucleosis (IM) has been shown in a previous meta-analysis to be associated with the risk of MS, however a number of much larger studies have since been published. Methods/Principal Findings We performed a Medline search to identify articles published since the original meta-analysis investigating MS risk following IM. A total of 18 articles were included in this study, including 19390 MS patients and 16007 controls. We calculated the relative risk of MS following IM using a generic inverse variance with random effects model. This showed that the risk of MS was strongly associated with IM (relative risk (RR) 2.17; 95% confidence interval 1.97–2.39; p<10−54). Discussion Our results establish firmly that a history of infectious mononucleosis significantly increases the risk of multiple sclerosis. Future work should focus on the mechanism of this association and interaction with other risk factors. PMID:20824132

Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations

NASA Astrophysics Data System (ADS)

Gan, Luping; Li, Yan-Feng; Zhu, Shun-Peng; Yang, Yuan-Jian; Huang, Hong-Zhong

2014-06-01

Failure mode, effects and criticality analysis (FMECA) and Fault tree analysis (FTA) are powerful tools to evaluate reliability of systems. Although single failure mode issue can be efficiently addressed by traditional FMECA, multiple failure modes and component correlations in complex systems cannot be effectively evaluated. In addition, correlated variables and parameters are often assumed to be precisely known in quantitative analysis. In fact, due to the lack of information, epistemic uncertainty commonly exists in engineering design. To solve these problems, the advantages of FMECA, FTA, fuzzy theory, and Copula theory are integrated into a unified hybrid method called fuzzy probability weighted geometric mean (FPWGM) risk priority number (RPN) method. The epistemic uncertainty of risk variables and parameters are characterized by fuzzy number to obtain fuzzy weighted geometric mean (FWGM) RPN for single failure mode. Multiple failure modes are connected using minimum cut sets (MCS), and Boolean logic is used to combine fuzzy risk priority number (FRPN) of each MCS. Moreover, Copula theory is applied to analyze the correlation of multiple failure modes in order to derive the failure probabilities of each MCS. Compared to the case where dependency among multiple failure modes is not considered, the Copula modeling approach eliminates the error of reliability analysis. Furthermore, for purpose of quantitative analysis, probabilities importance weight from failure probabilities are assigned to FWGM RPN to reassess the risk priority, which generalize the definition of probability weight and FRPN, resulting in a more accurate estimation than that of the traditional models. Finally, a basic fatigue analysis case drawn from turbine and compressor blades in aeroengine is used to demonstrate the effectiveness and robustness of the presented method. The result provides some important insights on fatigue reliability analysis and risk priority assessment of structural system under failure correlations.

Lung Cancer Risk from Occupational and Environmental Radon and Role of Smoking in Two Czech Nested Case-Control Studies

PubMed Central

Tomasek, Ladislav

2013-01-01

The aim of the present study was to evaluate the risk of lung cancer from combined exposure to radon and smoking. Methodologically, it is based on case-control studies nested within two Czech cohort studies of nearly 11,000 miners followed-up for mortality in 1952–2010 and nearly 12,000 inhabitants exposed to high levels of radon in homes, with mortality follow-up in 1960–2010. In addition to recorded radon exposure, these studies use information on smoking collected from the subjects or their relatives. A total of 1,029 and 370 cases with smoking information have been observed in the occupational and environmental (residential) studies, respectively. Three or four control subjects have been individually matched to cases according to sex, year of birth, and age. The combined effect from radon and smoking is analyzed in terms of geometric mixture models of which the additive and multiplicative models are special cases. The resulting models are relatively close to the additive interaction (mixing parameter 0.2 and 0.3 in the occupational and residential studies, respectively). The impact of the resulting model in the residential radon study is illustrated by estimates of lifetime risk in hypothetical populations of smokers and non-smokers. In comparison to the multiplicative risk model, the lifetime risk from the best geometric mixture model is considerably higher, particularly in the non-smoking population. PMID:23470882

Analysis of underlying and multiple-cause mortality data: the life table methods.

PubMed

Moussa, M A

1987-02-01

The stochastic compartment model concepts are employed to analyse and construct complete and abbreviated total mortality life tables, multiple-decrement life tables for a disease, under the underlying and pattern-of-failure definitions of mortality risk, cause-elimination life tables, cause-elimination effects on saved population through the gain in life expectancy as a consequence of eliminating the mortality risk, cause-delay life tables designed to translate the clinically observed increase in survival time as the population gain in life expectancy that would occur if a treatment protocol was made available to the general population and life tables for disease dependency in multiple-cause data.

The psychological factor 'self-blame' predicts overuse injury among top-level Swedish track and field athletes: a 12-month cohort study.

PubMed

Timpka, Toomas; Jacobsson, Jenny; Dahlström, Örjan; Kowalski, Jan; Bargoria, Victor; Ekberg, Joakim; Nilsson, Sverker; Renström, Per

2015-11-01

Athletes' psychological characteristics are important for understanding sports injury mechanisms. We examined the relevance of psychological factors in an integrated model of overuse injury risk in athletics/track and field. Swedish track and field athletes (n=278) entering a 12-month injury surveillance in March 2009 were also invited to complete a psychological survey. Simple Cox proportional hazards models were compiled for single explanatory variables. We also tested multiple models for 3 explanatory variable groupings: an epidemiological model without psychological variables, a psychological model excluding epidemiological variables and an integrated (combined) model. The integrated multiple model included the maladaptive coping behaviour self-blame (p=0.007; HR 1.32; 95% CI 1.08 to 1.61), and an interaction between athlete category and injury history (p<0.001). Youth female (p=0.034; HR 0.51; 95% CI 0.27 to 0.95) and youth male (p=0.047; HR 0.49; 95% CI 0.24 to 0.99) athletes with no severe injury the previous year were at half the risk of sustaining a new injury compared with the reference group. A training load index entered the epidemiological multiple model, but not the integrated model. The coping behaviour self-blame replaced training load in an integrated explanatory model of overuse injury risk in athletes. What seemed to be more strongly related to the likelihood of overuse injury was not the athletics load per se, but, rather, the load applied in situations when the athlete's body was in need of rest. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

STakeholder-Objective Risk Model (STORM): Determining the aggregated risk of multiple contaminant hazards in groundwater well catchments

NASA Astrophysics Data System (ADS)

Enzenhoefer, R.; Binning, P. J.; Nowak, W.

2015-09-01

Risk is often defined as the product of probability, vulnerability and value. Drinking water supply from groundwater abstraction is often at risk due to multiple hazardous land use activities in the well catchment. Each hazard might or might not introduce contaminants into the subsurface at any point in time, which then affects the pumped quality upon transport through the aquifer. In such situations, estimating the overall risk is not trivial, and three key questions emerge: (1) How to aggregate the impacts from different contaminants and spill locations to an overall, cumulative impact on the value at risk? (2) How to properly account for the stochastic nature of spill events when converting the aggregated impact to a risk estimate? (3) How will the overall risk and subsequent decision making depend on stakeholder objectives, where stakeholder objectives refer to the values at risk, risk attitudes and risk metrics that can vary between stakeholders. In this study, we provide a STakeholder-Objective Risk Model (STORM) for assessing the total aggregated risk. Or concept is a quantitative, probabilistic and modular framework for simulation-based risk estimation. It rests on the source-pathway-receptor concept, mass-discharge-based aggregation of stochastically occuring spill events, accounts for uncertainties in the involved flow and transport models through Monte Carlo simulation, and can address different stakeholder objectives. We illustrate the application of STORM in a numerical test case inspired by a German drinking water catchment. As one may expect, the results depend strongly on the chosen stakeholder objectives, but they are equally sensitive to different approaches for risk aggregation across different hazards, contaminant types, and over time.

Capacity planning for electronic waste management facilities under uncertainty: multi-objective multi-time-step model development.

PubMed

Poonam Khanijo Ahluwalia; Nema, Arvind K

2011-07-01

Selection of optimum locations for locating new facilities and decision regarding capacities at the proposed facilities is a major concern for municipal authorities/managers. The decision as to whether a single facility is preferred over multiple facilities of smaller capacities would vary with varying priorities to cost and associated risks such as environmental or health risk or risk perceived by the society. Currently management of waste streams such as that of computer waste is being done using rudimentary practices and is flourishing as an unorganized sector, mainly as backyard workshops in many cities of developing nations such as India. Uncertainty in the quantification of computer waste generation is another major concern due to the informal setup of present computer waste management scenario. Hence, there is a need to simultaneously address uncertainty in waste generation quantities while analyzing the tradeoffs between cost and associated risks. The present study aimed to address the above-mentioned issues in a multi-time-step, multi-objective decision-support model, which can address multiple objectives of cost, environmental risk, socially perceived risk and health risk, while selecting the optimum configuration of existing and proposed facilities (location and capacities).

Research on efficiency evaluation model of integrated energy system based on hybrid multi-attribute decision-making.

PubMed

Li, Yan

2017-05-25

The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.

Assessing interactions between HLA-DRB1*15 and infectious mononucleosis on the risk of multiple sclerosis.

PubMed

Disanto, Giulio; Hall, Carolina; Lucas, Robyn; Ponsonby, Anne-Louise; Berlanga-Taylor, Antonio J; Giovannoni, Gavin; Ramagopalan, Sreeram V

2013-09-01

Gene-environment interactions may shed light on the mechanisms underlying multiple sclerosis (MS). We pooled data from two case-control studies on incident demyelination and used different methods to assess interaction between HLA-DRB1*15 (DRB1-15) and history of infectious mononucleosis (IM). Individuals exposed to both factors were at substantially increased risk of disease (OR=7.32, 95% CI=4.92-10.90). In logistic regression models, DRB1-15 and IM status were independent predictors of disease while their interaction term was not (DRB1-15*IM: OR=1.35, 95% CI=0.79-2.23). However, interaction on an additive scale was evident (Synergy index=2.09, 95% CI=1.59-2.59; excess risk due to interaction=3.30, 95%CI=0.47-6.12; attributable proportion due to interaction=45%, 95% CI=22-68%). This suggests, if the additive model is appropriate, the DRB1-15 and IM may be involved in the same causal process leading to MS and highlights the benefit of reporting gene-environment interactions on both a multiplicative and additive scale.

Adjusted variable plots for Cox's proportional hazards regression model.

PubMed

Hall, C B; Zeger, S L; Bandeen-Roche, K J

1996-01-01

Adjusted variable plots are useful in linear regression for outlier detection and for qualitative evaluation of the fit of a model. In this paper, we extend adjusted variable plots to Cox's proportional hazards model for possibly censored survival data. We propose three different plots: a risk level adjusted variable (RLAV) plot in which each observation in each risk set appears, a subject level adjusted variable (SLAV) plot in which each subject is represented by one point, and an event level adjusted variable (ELAV) plot in which the entire risk set at each failure event is represented by a single point. The latter two plots are derived from the RLAV by combining multiple points. In each point, the regression coefficient and standard error from a Cox proportional hazards regression is obtained by a simple linear regression through the origin fit to the coordinates of the pictured points. The plots are illustrated with a reanalysis of a dataset of 65 patients with multiple myeloma.

Does Alcohol Use among Sexually Active College Students Moderate HIV Risk Behavior?

ERIC Educational Resources Information Center

Lewis, John E.; Malow, Robert M.; Norman, Lisa

2008-01-01

College students frequently use alcohol and are very sexually active, but do the two behaviors result in greater HIV risk? We employed the AIDS Risk Reduction Model to assess condom use during vaginal intercourse for sexually active college students using and not using alcohol proximal to sex. Students reported multiple lifetime sex partners and…

Using multiple decrement models to estimate risk and morbidity from specific AIDS illnesses. Multicenter AIDS Cohort Study (MACS).

PubMed

Hoover, D R; Peng, Y; Saah, A J; Detels, R R; Day, R S; Phair, J P

A simple non-parametric approach is developed to simultaneously estimate net incidence and morbidity time from specific AIDS illnesses in populations at high risk for death from these illnesses and other causes. The disease-death process has four-stages that can be recast as two sandwiching three-state multiple decrement processes. Non-parametric estimation of net incidence and morbidity time with error bounds are achieved from these sandwiching models through modification of methods from Aalen and Greenwood, and bootstrapping. An application to immunosuppressed HIV-1 infected homosexual men reveals that cytomegalovirus disease, Kaposi's sarcoma and Pneumocystis pneumonia are likely to occur and cause significant morbidity time.

Variable- and Person-Centered Approaches to Examining Temperament Vulnerability and Resilience to the Effects of Contextual Risk

PubMed Central

Moran, Lyndsey; Lengua, Liliana J.; Zalewski, Maureen; Ruberry, Erika; Klien, Melanie; Thompson, Stephanie; Kiff, Cara

2016-01-01

Using both variable- and person-centered approaches, this study examined the role of temperament in relation to children's vulnerable or resilient responses to cumulative risk. Observed reactivity and regulation dimensions of temperament were tested as mediating and moderating the relation between family cumulative risk and teacher-reported adjustment problems in a sample of 259 preschool-age children. Further, latent profile analyses were used to examine whether profiles of temperament, accounting for multiple characteristics simultaneously, provided additional information about the role of temperament in children's responses to risk. Results support a diathesis-stress model in which high frustration, low fear, and low delay ability confer particular vulnerability for children in high-risk contexts. Benefits of multiple approaches are highlighted. PMID:28408769

The incidence of leukemia, lymphoma, and multiple myeloma among atomic bomb survivors: 1950 – 2001

PubMed Central

Hsu, Wan-Ling; Preston, Dale L.; Soda, Midori; Sugiyama, Hiromi; Funamoto, Sachiyo; Kodama, Kazunori; Kimura, Akiro; Kamada, Nanao; Dohy, Hiroo; Tomonaga, Masao; Iwanaga, Masako; Miyazaki, Yasushi; Cullings, Harry M.; Suyama, Akihiko; Ozasa, Kotaro; Shore, Roy E.; Mabuchi, Kiyohiko

2013-01-01

A marked increase in leukemia risks was the first and most striking late effect of radiation exposure seen among the Hiroshima and Nagasaki atomic bomb survivors. This paper presents analyses of radiation effects on leukemia, lymphoma, and multiple myeloma incidence in the Life Span Study cohort of atomic bomb survivors updated 14 years since the last comprehensive report on these malignancies. These analyses make use of tumor- and leukemia-registry-based incidence data on 113,011 cohort members with 3.6 million person-years of follow-up from late 1950 through the end of 2001. In addition to a detailed analysis of the excess risk for all leukemias other than chronic lymphocytic leukemia or adult T-cell leukemia (neither of which appear to be radiation-related), we present results for the major hematopoietic malignancy types: acute lymphoblastic leukemia, chronic lymphocytic leukemia, acute myeloid leukemia, chronic myeloid leukemia, adult T-cell leukemia, Hodgkin and non-Hodgkin lymphoma, and multiple myeloma. Poisson regression methods were used to characterize the shape of the radiation dose response relationship and, to the extent the data allowed, to investigate variation in the excess risks with sex, attained age, exposure age, and time since exposure. In contrast to the previous report that focused on describing excess absolute rates, we considered both excess absolute rate (EAR) and excess relative risk (ERR) models and found that ERR models can often provide equivalent and sometimes more parsimonious descriptions of the excess risk than EAR models. The leukemia results indicated that there was a non-linear dose response for leukemias other than chronic lymphocytic leukemia or adult T-cell leukemia, which varied markedly with time and age at exposure, with much of the evidence for this non-linearity arising from the acute myeloid leukemia risks. Although the leukemia excess risks generally declined with attained age or time since exposure, there was evidence that the radiation-associated excess leukemia risks, especially for acute myeloid leukemia, had persisted throughout the follow-up period out to – 55 years after the bombings. As in earlier analyses, there was a weak suggestion of a radiation dose response for non-Hodgkin lymphoma among men with no indication of such an effect among women. There was no evidence of radiation-associated excess risks for either Hodgkin lymphoma or multiple myeloma. PMID:23398354

Application of Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling in Cumulative Risk Assessment for N-Methyl Carbamate Insecticides

EPA Science Inventory

Human exposure to xenobiotics may occur through multiple pathways and routes of entry punctuated by exposure intervals throughout a work or leisure day. Exposure to a single environmental chemical along multiple pathways and routes (aggregate exposure) may have an influence on an...

Integrating Human Factors into Space Vehicle Processing for Risk Management

NASA Technical Reports Server (NTRS)

Woodbury, Sarah; Richards, Kimberly J.

2008-01-01

This presentation will discuss the multiple projects performed in United Space Alliance's Human Engineering Modeling and Performance (HEMAP) Lab, improvements that resulted from analysis, and the future applications of the HEMAP Lab for risk assessment by evaluating human/machine interaction and ergonomic designs.

Privacy Protection on Multiple Sensitive Attributes

NASA Astrophysics Data System (ADS)

Li, Zhen; Ye, Xiaojun

In recent years, a privacy model called k-anonymity has gained popularity in the microdata releasing. As the microdata may contain multiple sensitive attributes about an individual, the protection of multiple sensitive attributes has become an important problem. Different from the existing models of single sensitive attribute, extra associations among multiple sensitive attributes should be invested. Two kinds of disclosure scenarios may happen because of logical associations. The Q&S Diversity is checked to prevent the foregoing disclosure risks, with an α Requirement definition used to ensure the diversity requirement. At last, a two-step greedy generalization algorithm is used to carry out the multiple sensitive attributes processing which deal with quasi-identifiers and sensitive attributes respectively. We reduce the overall distortion by the measure of Masking SA.

A Bayesian model averaging approach for estimating the relative risk of mortality associated with heat waves in 105 U.S. cities.

PubMed

Bobb, Jennifer F; Dominici, Francesca; Peng, Roger D

2011-12-01

Estimating the risks heat waves pose to human health is a critical part of assessing the future impact of climate change. In this article, we propose a flexible class of time series models to estimate the relative risk of mortality associated with heat waves and conduct Bayesian model averaging (BMA) to account for the multiplicity of potential models. Applying these methods to data from 105 U.S. cities for the period 1987-2005, we identify those cities having a high posterior probability of increased mortality risk during heat waves, examine the heterogeneity of the posterior distributions of mortality risk across cities, assess sensitivity of the results to the selection of prior distributions, and compare our BMA results to a model selection approach. Our results show that no single model best predicts risk across the majority of cities, and that for some cities heat-wave risk estimation is sensitive to model choice. Although model averaging leads to posterior distributions with increased variance as compared to statistical inference conditional on a model obtained through model selection, we find that the posterior mean of heat wave mortality risk is robust to accounting for model uncertainty over a broad class of models. © 2011, The International Biometric Society.

Reducing economic risk in areally anisotropic formations with multiple-lateral horizontal wells

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

Smith, J.; Economides, M.J.; Frick, T.P.

1995-12-31

Well orientation is critical to horizontal well performance in areally anisotropic reservoirs. A horizontal well, drilled normal to the direction of maximum permeability, will have higher productivity than one drilled in any other arbitrary direction. Currently, horizontal permeability magnitudes and even indications of direction are rarely measured in the field. Based on well performance modeling and economic evaluation, this study attempts to determine the relative attractiveness of horizontal wells with multiple-laterals. The work exposes the economic risk in ignoring horizontal permeability magnitudes and directions and demonstrates the importance of adequate reservoir testing. A new rationalization for multiple-lateral horizontal wells ismore » the reduction of the economic risk associated with poor reservoir characterization in areally anisotropic formations while increasing the incremental net present value (NPV) over single-horizontal wells.« less

Development and validation of risk profiles of West African rural communities facing multiple natural hazards

PubMed Central

Renaud, Fabrice G.; Kloos, Julia; Walz, Yvonne; Rhyner, Jakob

2017-01-01

West Africa has been described as a hotspot of climate change. The reliance on rain-fed agriculture by over 65% of the population means that vulnerability to climatic hazards such as droughts, rainstorms and floods will continue. Yet, the vulnerability and risk levels faced by different rural social-ecological systems (SES) affected by multiple hazards are poorly understood. To fill this gap, this study quantifies risk and vulnerability of rural communities to drought and floods. Risk is assessed using an indicator-based approach. A stepwise methodology is followed that combines participatory approaches with statistical, remote sensing and Geographic Information System techniques to develop community level vulnerability indices in three watersheds (Dano, Burkina Faso; Dassari, Benin; Vea, Ghana). The results show varying levels of risk profiles across the three watersheds. Statistically significant high levels of mean risk in the Dano area of Burkina Faso are found whilst communities in the Dassari area of Benin show low mean risk. The high risk in the Dano area results from, among other factors, underlying high exposure to droughts and rainstorms, longer dry season duration, low caloric intake per capita, and poor local institutions. The study introduces the concept of community impact score (CIS) to validate the indicator-based risk and vulnerability modelling. The CIS measures the cumulative impact of the occurrence of multiple hazards over five years. 65.3% of the variance in observed impact of hazards/CIS was explained by the risk models and communities with high simulated disaster risk generally follow areas with high observed disaster impacts. Results from this study will help disaster managers to better understand disaster risk and develop appropriate, inclusive and well integrated mitigation and adaptation plans at the local level. It fulfills the increasing need to balance global/regional assessments with community level assessments where major decisions against risk are actually taken and implemented. PMID:28248969

On cancer risk estimation of urban air pollution.

PubMed Central

Törnqvist, M; Ehrenberg, L

1994-01-01

The usefulness of data from various sources for a cancer risk estimation of urban air pollution is discussed. Considering the irreversibility of initiations, a multiplicative model is preferred for solid tumors. As has been concluded for exposure to ionizing radiation, the multiplicative model, in comparison with the additive model, predicts a relatively larger number of cases at high ages, with enhanced underestimation of risks by short follow-up times in disease-epidemiological studies. For related reasons, the extrapolation of risk from animal tests on the basis of daily absorbed dose per kilogram body weight or per square meter surface area without considering differences in life span may lead to an underestimation, and agreements with epidemiologically determined values may be fortuitous. Considering these possibilities, the most likely lifetime risks of cancer death at the average exposure levels in Sweden were estimated for certain pollution fractions or indicator compounds in urban air. The risks amount to approximately 50 deaths per 100,000 for inhaled particulate organic material (POM), with a contribution from ingested POM about three times larger, and alkenes, and butadiene cause 20 deaths, respectively, per 100,000 individuals. Also, benzene and formaldehyde are expected to be associated with considerable risk increments. Comparative potency methods were applied for POM and alkenes. Due to incompleteness of the list of compounds considered and the uncertainties of the above estimates, the total risk calculation from urban air has not been attempted here. PMID:7821292

Features predictive of brain arteriovenous malformation hemorrhage: extrapolation to a physiologic model.

PubMed

Sahlein, Daniel H; Mora, Paloma; Becske, Tibor; Huang, Paul; Jafar, Jafar J; Connolly, E Sander; Nelson, Peter K

2014-07-01

Although there is generally thought to be a 2% to 4% per annum rupture risk for brain arteriovenous malformations (bAVMs), there is no way to estimate risk for an individual patient. In this retrospective study, patients were eligible who had nidiform bAVMs and underwent detailed pretreatment diagnostic cerebral angiography at our medical center from 1996 to 2006. All patients had superselective microcatheter angiography, and films were reviewed for the purpose of this project. Patient demographics, clinical presentation, and angioarchitectural characteristics were analyzed. A univariate analysis was performed, and angioarchitectural features with potential physiological significance that showed at least a trend toward significance were added to a multivariate logistic regression model. One hundred twenty-two bAVMs met criteria for study entry. bAVMs with single venous drainage anatomy were more likely to present with hemorrhage. In addition, patients with multiple draining veins and a venous stenosis reverted to a risk similar to those with 1 draining vein, whereas those with multiple draining veins and without stenosis had diminished association with hemorrhage presentation. Those bAVMs with associated aneurysms were more likely to present with hemorrhage. These findings were robust in both univariate and multivariate models. The results of this article lead to the first physiological, internally consistent model of individual bAVM hemorrhage risk, where 1 draining vein, venous stenosis, and associated aneurysms increase risk. © 2014 American Heart Association, Inc.

Meta-analysis of the association of MTHFR polymorphisms with multiple myeloma risk

PubMed Central

Ma, Li-Min; Ruan, Lin-Hai; Yang, Hai-Ping

2015-01-01

The association of methylenetetrahydrofolate reductase (MTHFR) polymorphisms with multiple myeloma (MM) risk has been explored, but the results remain controversial. Thus, a meta-analysis was performed to provide a comprehensively estimate. The case-control studies about MTHFR C677T and A1298C polymorphisms with MM risk were collected by searching PubMed, Elsevier, China National Knowledge Infrastructure and Wanfang Databases. Odds ratios (ORs) with 95% confidence intervals (CIs) were applied to assess the strength of association. Overall, no significant association was found between MTHFR A1298C polymorphism and MM risk under all four genetic models (AC vs. AA, OR = 0.99, 95%CI = 0.82-1.20; CC vs. AA, OR = 1.14, 95%CI = 0.77-1.68; recessive model, OR = 1.10, 95%CI = 0.76-1.59; dominant model, OR = 1.01, 95%CI = 0.84-1.22). The risk was also not significantly altered for C677T polymorphism and MM in overall comparisons (CT vs. CC, OR = 1.04, 95%CI = 0.93-1.17; TT vs. CC, OR = 1.16, 95%CI = 0.98-1.37; recessive model, OR = 1.13, 95%CI = 0.98-1.32; dominant model, OR = 1.07, 95%CI = 0.96-1.20). In subgroup analyses by ethnicity, no significant association was observed in both Caucasians and Asians. This meta-analysis suggested that MTHFR polymorphisms were not associated with MM risk. PMID:26022785

Multiple Novel Prostate Cancer Predisposition Loci Confirmed by an International Study: The PRACTICAL Consortium

PubMed Central

Kote-Jarai, Zsofia; Easton, Douglas F.; Stanford, Janet L.; Ostrander, Elaine A.; Schleutker, Johanna; Ingles, Sue A.; Schaid, Daniel; Thibodeau, Stephen; Dörk, Thilo; Neal, David; Cox, Angela; Maier, Christiane; Vogel, Walter; Guy, Michelle; Muir, Kenneth; Lophatananon, Artitaya; Kedda, Mary-Anne; Spurdle, Amanda; Steginga, Suzanne; John, Esther M.; Giles, Graham; Hopper, John; Chappuis, Pierre O.; Hutter, Pierre; Foulkes, William D.; Hamel, Nancy; Salinas, Claudia A.; Koopmeiners, Joseph S.; Karyadi, Danielle M.; Johanneson, Bo; Wahlfors, Tiina; Tammela, Teuvo L.; Stern, Mariana C.; Corral, Roman; McDonnell, Shannon K.; Schürmann, Peter; Meyer, Andreas; Kuefer, Rainer; Leongamornlert, Daniel A.; Tymrakiewicz, Malgorzata; Liu, Jo-fen; O'Mara, Tracy; Gardiner, R.A. (Frank); Aitken, Joanne; Joshi, Amit D.; Severi, Gianluca; English, Dallas R.; Southey, Melissa; Edwards, Stephen M.; Amin Al Olama, Ali; Eeles, Rosalind A.

2009-01-01

A recent genome-wide association study found that genetic variants on chromosomes 3, 6, 7, 10, 11, 19 and X were associated with prostate cancer risk. We evaluated the most significant single-nucleotide polymorphisms (SNP) in these loci using a worldwide consortium of 13 groups (PRACTICAL). Blood DNA from 7,370 prostate cancer cases and 5,742 male controls was analyzed by genotyping assays. Odds ratios (OR) associated with each genotype were estimated using unconditional logistic regression. Six of the seven SNPs showed clear evidence of association with prostate cancer (P = 0.0007-P = 10−17). For each of these six SNPs, the estimated per-allele OR was similar to those previously reported and ranged from 1.12 to 1.29. One SNP on 3p12 (rs2660753) showed a weaker association than previously reported [per-allele OR, 1.08 (95% confidence interval, 1.00-1.16; P = 0.06) versus 1.18 (95% confidence interval, 1.06-1.31)]. The combined risks associated with each pair of SNPs were consistent with a multiplicative risk model. Under this model, and in combination with previously reported SNPs on 8q and 17q, these loci explain 16% of the familial risk of the disease, and men in the top 10% of the risk distribution have a 2.1-fold increased risk relative to general population rates. This study provides strong confirmation of these susceptibility loci in multiple populations and shows that they make an important contribution to prostate cancer risk prediction. PMID:18708398

Bayesian dose-response analysis for epidemiological studies with complex uncertainty in dose estimation.

PubMed

Kwon, Deukwoo; Hoffman, F Owen; Moroz, Brian E; Simon, Steven L

2016-02-10

Most conventional risk analysis methods rely on a single best estimate of exposure per person, which does not allow for adjustment for exposure-related uncertainty. Here, we propose a Bayesian model averaging method to properly quantify the relationship between radiation dose and disease outcomes by accounting for shared and unshared uncertainty in estimated dose. Our Bayesian risk analysis method utilizes multiple realizations of sets (vectors) of doses generated by a two-dimensional Monte Carlo simulation method that properly separates shared and unshared errors in dose estimation. The exposure model used in this work is taken from a study of the risk of thyroid nodules among a cohort of 2376 subjects who were exposed to fallout from nuclear testing in Kazakhstan. We assessed the performance of our method through an extensive series of simulations and comparisons against conventional regression risk analysis methods. When the estimated doses contain relatively small amounts of uncertainty, the Bayesian method using multiple a priori plausible draws of dose vectors gave similar results to the conventional regression-based methods of dose-response analysis. However, when large and complex mixtures of shared and unshared uncertainties are present, the Bayesian method using multiple dose vectors had significantly lower relative bias than conventional regression-based risk analysis methods and better coverage, that is, a markedly increased capability to include the true risk coefficient within the 95% credible interval of the Bayesian-based risk estimate. An evaluation of the dose-response using our method is presented for an epidemiological study of thyroid disease following radiation exposure. Copyright © 2015 John Wiley & Sons, Ltd.

Making assessments while taking repeated risks: a pattern of multiple response pathways.

PubMed

Pleskac, Timothy J; Wershbale, Avishai

2014-02-01

Beyond simply a decision process, repeated risky decisions also require a number of cognitive processes including learning, search and exploration, and attention. In this article, we examine how multiple response pathways develop over repeated risky decisions. Using the Balloon Analogue Risk Task (BART) as a case study, we show that 2 different response pathways emerge over the course of the task. The assessment pathway is a slower, more controlled pathway where participants deliberate over taking a risk. The 2nd pathway is a faster, more automatic process where no deliberation occurs. Results imply the slower assessment pathway is taken as choice conflict increases and that the faster automatic response is a learned response. Based on these results, we modify an existing formal cognitive model of decision making during the BART to account for these dual response pathways. The slower more deliberative response process is modeled with a sequential sampling process where evidence is accumulated to a threshold, while the other response is given automatically. We show that adolescents with conduct disorder and substance use disorder symptoms not only evaluate risks differently during the BART but also differ in the rate at which they develop the more automatic response. More broadly, our results suggest cognitive models of judgment decision making need to transition from treating observed decisions as the result of a single response pathway to the result of multiple response pathways that change and develop over time.

Cognitive Phenotype of Velocardiofacial Syndrome: A Review

ERIC Educational Resources Information Center

Furniss, Frederick; Biswas, Asit B.; Gumber, Rohit; Singh, Niraj

2011-01-01

The behavioural phenotype of velocardiofacial syndrome (VCFS), one of the most common human multiple anomaly syndromes, includes developmental disabilities, frequently including intellectual disability (ID) and high risk of diagnosis of psychotic disorders including schizophrenia. VCFS may offer a model of the relationship between ID and risk of…

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

PubMed Central

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

2016-01-01

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

Is This Kid a Likely Experimenter or a Likely Persister? An Analysis of Individual-Level and Family-Level Risk Factors Predicting Multiple Offending Among a Group of Adjudicated Youth.

PubMed

Buker, Hasan; Erbay, Ayhan

2018-02-01

To implement effective diversion programs and determine for a well-suited intervention strategy, ascertaining who, among the adjudicated youth, is more likely to involve in multiple offending, rather than desisting after an initial delinquent behavior, is of great significance. The overall objective of this study, therefore, is to contribute to the existing knowledge on assessing the risks for multiple offending during juvenile adjudication processes. In this regard, this study examined the predicting powers of several individual-level and family-level risk factors on multiple offending during adolescence, based on a data set derived from court-ordered social examination reports (SERs) on 400 adjudicated youth in Turkey. Two binomial regression models were implemented to test the predictor values of various risk factors from these two domains. Results indicated the following as significant predictors of multiple offending among the subjects: younger age of onset in delinquency, dropping out of school, having delinquent/drug abusing (risky) friends, being not able to share problems with the family, increased number of siblings, and having a domestically migrated family. Conclusively, these findings were compared with the existing literature, and the policy implications and recommendations for future research were discussed.

Air Pollution Exposure Modeling for Health Studies

EPA Science Inventory

Dr. Michael Breen is leading the development of air pollution exposure models, integrated with novel personal sensor technologies, to improve exposure and risk assessments for individuals in health studies. He is co-investigator for multiple health studies assessing the exposure ...

Relationship between FEV1 and Cardiovascular Risk Factors in General Population without Airflow Limitation.

PubMed

Lee, Jeong Hyeon; Kang, Yun-Seong; Jeong, Yun-Jeong; Yoon, Young-Soon; Kwack, Won Gun; Oh, Jin Young

2016-01-01

Purpose. We aimed to determine the value of lung function measurement for predicting cardiovascular (CV) disease by evaluating the association between FEV1 (%) and CV risk factors in general population. Materials and Methods. This was a cross-sectional, retrospective study of subjects above 18 years of age who underwent health examinations. The relationship between FEV1 (%) and presence of carotid plaque and thickened carotid IMT (≥0.8 mm) was analyzed by multiple logistic regression, and the relationship between FEV1 (%) and PWV (%), and serum uric acid was analyzed by multiple linear regression. Various factors were adjusted by using Model 1 and Model 2. Results. 1,003 subjects were enrolled in this study and 96.7% ( n = 970) of the subjects were men. In both models, the odds ratio of the presence of carotid plaque and thickened carotid IMT had no consistent trend and statistical significance. In the analysis of the PWV (%) and uric acid, there was no significant relationship with FEV1 (%) in both models. Conclusion. FEV1 had no significant relationship with CV risk factors. The result suggests that FEV1 may have no association with CV risk factors or may be insensitive to detecting the association in general population without airflow limitation.

Investigating the effect of child maltreatment on early adolescent peer-on-peer sexual aggression: testing a multiple mediator model in a non-incarcerated sample of Danish adolescents.

PubMed

Bramsen, Rikke Holm; Lasgaard, Mathias; Koss, Mary P; Elklit, Ask; Banner, Jytte

2014-01-01

The aim of the present study was to investigate the relationship between child maltreatment and severe early adolescent peer-on-peer sexual aggression, using a multiple mediator model. The study comprised 330 male Grade 9 students with a mean age of 14.9 years (SD=0.5). Estimates from the mediation model indicated significant indirect effects of child physical abuse on sexual aggression via peer influence and insecure-hostile masculinity. No significant total effect of child sexual abuse and child neglect on sexual aggression was found. Findings of the present study identify risk factors that are potentially changeable and therefore of value in informing the design of prevention programs aiming at early adolescent peer-on-peer sexual aggression in at-risk youth.

Comparing biomarkers as principal surrogate endpoints.

PubMed

Huang, Ying; Gilbert, Peter B

2011-12-01

Recently a new definition of surrogate endpoint, the "principal surrogate," was proposed based on causal associations between treatment effects on the biomarker and on the clinical endpoint. Despite its appealing interpretation, limited research has been conducted to evaluate principal surrogates, and existing methods focus on risk models that consider a single biomarker. How to compare principal surrogate value of biomarkers or general risk models that consider multiple biomarkers remains an open research question. We propose to characterize a marker or risk model's principal surrogate value based on the distribution of risk difference between interventions. In addition, we propose a novel summary measure (the standardized total gain) that can be used to compare markers and to assess the incremental value of a new marker. We develop a semiparametric estimated-likelihood method to estimate the joint surrogate value of multiple biomarkers. This method accommodates two-phase sampling of biomarkers and is more widely applicable than existing nonparametric methods by incorporating continuous baseline covariates to predict the biomarker(s), and is more robust than existing parametric methods by leaving the error distribution of markers unspecified. The methodology is illustrated using a simulated example set and a real data set in the context of HIV vaccine trials. © 2011, The International Biometric Society.

AN OPTIMAL MAINTENANCE MANAGEMENT MODEL FOR AIRPORT CONCRETE PAVEMENT

NASA Astrophysics Data System (ADS)

Shimomura, Taizo; Fujimori, Yuji; Kaito, Kiyoyuki; Obama, Kengo; Kobayashi, Kiyoshi

In this paper, an optimal management model is formulated for the performance-based rehabilitation/maintenance contract for airport concrete pavement, whereby two types of life cycle cost risks, i.e., ground consolidation risk and concrete depreciation risk, are explicitly considered. The non-homogenous Markov chain model is formulated to represent the deterioration processes of concrete pavement which are conditional upon the ground consolidation processes. The optimal non-homogenous Markov decision model with multiple types of risk is presented to design the optimal rehabilitation/maintenance plans. And the methodology to revise the optimal rehabilitation/maintenance plans based upon the monitoring data by the Bayesian up-to-dating rules. The validity of the methodology presented in this paper is examined based upon the case studies carried out for the H airport.

Revealing the underlying drivers of disaster risk: a global analysis

NASA Astrophysics Data System (ADS)

Peduzzi, Pascal

2017-04-01

Disasters events are perfect examples of compound events. Disaster risk lies at the intersection of several independent components such as hazard, exposure and vulnerability. Understanding the weight of each component requires extensive standardisation. Here, I show how footprints of past disastrous events were generated using GIS modelling techniques and used for extracting population and economic exposures based on distribution models. Using past event losses, it was possible to identify and quantify a wide range of socio-politico-economic drivers associated with human vulnerability. The analysis was applied to about nine thousand individual past disastrous events covering earthquakes, floods and tropical cyclones. Using a multiple regression analysis on these individual events it was possible to quantify each risk component and assess how vulnerability is influenced by various hazard intensities. The results show that hazard intensity, exposure, poverty, governance as well as other underlying factors (e.g. remoteness) can explain the magnitude of past disasters. Analysis was also performed to highlight the role of future trends in population and climate change and how this may impacts exposure to tropical cyclones in the future. GIS models combined with statistical multiple regression analysis provided a powerful methodology to identify, quantify and model disaster risk taking into account its various components. The same methodology can be applied to various types of risk at local to global scale. This method was applied and developed for the Global Risk Analysis of the Global Assessment Report on Disaster Risk Reduction (GAR). It was first applied on mortality risk in GAR 2009 and GAR 2011. New models ranging from global assets exposure and global flood hazard models were also recently developed to improve the resolution of the risk analysis and applied through CAPRA software to provide probabilistic economic risk assessments such as Average Annual Losses (AAL) and Probable Maximum Losses (PML) in GAR 2013 and GAR 2015. In parallel similar methodologies were developed to highlitght the role of ecosystems for Climate Change Adaptation (CCA) and Disaster Risk Reduction (DRR). New developments may include slow hazards (such as e.g. soil degradation and droughts), natech hazards (by intersecting with georeferenced critical infrastructures) The various global hazard, exposure and risk models can be visualized and download through the PREVIEW Global Risk Data Platform.

Multiplicity in public health supply systems: a learning agenda.

PubMed

Bornbusch, Alan; Bates, James

2013-08-01

Supply chain integration-merging products for health programs into a single supply chain-tends to be the dominant model in health sector reform. However, multiplicity in a supply system may be justified as a risk management strategy that can better ensure product availability, advance specific health program objectives, and increase efficiency.

Goal Oriented and Risk Taking Behavior: The Roles of Multiple Systems for Caucasian and Arab-American Adolescents

ERIC Educational Resources Information Center

Tynan, Joshua J.; Somers, Cheryl L.; Gleason, Jamie H.; Markman, Barry S.; Yoon, Jina

2015-01-01

With Bronfenbrenner's (1977) ecological theory and other multifactor models (e.g. Pianta, 1999; Prinstein, Boergers, & Spirito, 2001) underlying this study design, the purpose was to examine, simultaneously, key variables in multiple life contexts (microsystem, mesosystem, exosystem levels) for their individual and combined roles in predicting…

Living Near Major Traffic Roads and Risk of Deep Vein Thrombosis

PubMed Central

Baccarelli, Andrea; Martinelli, Ida; Pegoraro, Valeria; Melly, Steven; Grillo, Paolo; Zanobetti, Antonella; Hou, Lifang; Bertazzi, Pier Alberto; Mannucci, Pier Mannuccio; Schwartz, Joel

2010-01-01

Background Particulate air pollution has been consistently linked to increased risk of arterial cardiovascular disease. Few data on air pollution exposure and risk of venous thrombosis are available. We investigated whether living near major traffic roads increases the risk of deep vein thrombosis (DVT), using distance from roads as a proxy for traffic exposure. Methods and Results Between 1995-2005, we examined 663 patients with DVT of the lower limbs and 859 age-matched controls from cities with population>15,000 inhabitants in Lombardia Region, Italy. We assessed distance from residential addresses to the nearest major traffic road using geographic information system methodology. The risk of DVT was estimated from logistic regression models adjusting for multiple clinical and environmental covariates. The risk of DVT was increased (Odds Ratio [OR]=1.33; 95% CI 1.03-1.71; p=0.03 in age-adjusted models; OR=1.47; 95%CI 1.10-1.96; p=0.008 in models adjusted for multiple covariates) for subjects living near a major traffic road (3 meters, 10th centile of the distance distribution) compared to those living farther away (reference distance of 245 meters, 90th centile). The increase in DVT risk was approximately linear over the observed distance range (from 718 to 0 meters), and was not modified after adjusting for background levels of particulate matter (OR=1.47; 95%CI 1.11-1.96; p=0.008 for 10th vs. 90th distance centile in models adjusting for area levels of particulate matter <10 μm in aerodynamic diameter [PM10] in the year before diagnosis). Conclusions Living near major traffic roads is associated with increased risk of DVT. PMID:19506111

Analysis of perceived risk among construction workers: a cross-cultural study and reflection on the Hofstede model.

PubMed

Martinez-Fiestas, Myriam; Rodríguez-Garzón, Ignacio; Delgado-Padial, Antonio; Lucas-Ruiz, Valeriano

2017-09-01

This article presents a cross-cultural study on perceived risk in the construction industry. Worker samples from three different countries were studied: Spain, Peru and Nicaragua. The main goal was to explain how construction workers perceive their occupational hazard and to analyze how this is related to their national culture. The model used to measure perceived risk was the psychometric paradigm. The results show three very similar profiles, indicating that risk perception is independent of nationality. A cultural analysis was conducted using the Hofstede model. The results of this analysis and the relation to perceived risk showed that risk perception in construction is independent of national culture. Finally, a multiple lineal regression analysis was conducted to determine what qualitative attributes could predict the global quantitative size of risk perception. All of the findings have important implications regarding the management of safety in the workplace.

Finding Groups Using Model-Based Cluster Analysis: Heterogeneous Emotional Self-Regulatory Processes and Heavy Alcohol Use Risk

ERIC Educational Resources Information Center

Mun, Eun Young; von Eye, Alexander; Bates, Marsha E.; Vaschillo, Evgeny G.

2008-01-01

Model-based cluster analysis is a new clustering procedure to investigate population heterogeneity utilizing finite mixture multivariate normal densities. It is an inferentially based, statistically principled procedure that allows comparison of nonnested models using the Bayesian information criterion to compare multiple models and identify the…

Religious Influences on the Risk of Marital Dissolution

ERIC Educational Resources Information Center

Vaaler, Margaret L.; Ellison, Christopher G.; Powers, Daniel A.

2009-01-01

This study examined multiple dimensions of religious involvement and the risk of divorce among a nationwide sample of 2,979 first-time married couples. Multivariate proportional hazards modeling was used to analyze two waves of the National Survey of Families and Households. Results indicated that although each partner's religious attendance bore…

Human and bovine viruses and bacteria at three Great Lakes beaches: Environmental variable associations and health risk

USGS Publications Warehouse

Corsi, Steven R.; Borchardt, Mark A.; Carvin, Rebecca B.; Burch, Tucker R; Spencer, Susan K.; Lutz, Michelle A.; McDermott, Colleen M.; Busse, Kimberly M.; Kleinheinz, Gregory; Feng, Xiaoping; Zhu, Jun

2016-01-01

Waterborne pathogens were measured at three beaches in Lake Michigan, environmental factors for predicting pathogen concentrations were identified, and the risk of swimmer infection and illness was estimated. Waterborne pathogens were detected in 96% of samples collected at three Lake Michigan beaches in summer, 2010. Samples were quantified for 22 pathogens in four microbial categories (human viruses, bovine viruses, protozoa, and pathogenic bacteria). All beaches had detections of human and bovine viruses and pathogenic bacteria indicating influence of multiple contamination sources at these beaches. Occurrence ranged from 40 to 87% for human viruses, 65–87% for pathogenic bacteria, and 13–35% for bovine viruses. Enterovirus, adenovirus A, Salmonella spp., Campylobacter jejuni, bovine polyomavirus, and bovine rotavirus A were present most frequently. Variables selected in multiple regression models used to explore environmental factors that influence pathogens included wave direction, cloud cover, currents, and water temperature. Quantitative Microbial Risk Assessment was done for C. jejuni, Salmonella spp., and enteroviruses to estimate risk of infection and illness. Median infection risks for one-time swimming events were approximately 3 × 10–5, 7 × 10–9, and 3 × 10–7 for C. jejuni, Salmonella spp., and enteroviruses, respectively. Results highlight the importance of investigating multiple pathogens within multiple categories to avoid underestimating the prevalence and risk of waterborne pathogens.

Risk transfer modeling among hierarchically associated stakeholders in development of space systems

NASA Astrophysics Data System (ADS)

Henkle, Thomas Grove, III

Research develops an empirically derived cardinal model that prescribes handling and transfer of risks between organizations with hierarchical relationships. Descriptions of mission risk events, risk attitudes, and conditions for risk transfer are determined for client and underwriting entities associated with acquisition, production, and deployment of space systems. The hypothesis anticipates that large client organizations should be able to assume larger dollar-value risks of a program in comparison to smaller organizations even though many current risk transfer arrangements via space insurance violate this hypothesis. A literature survey covers conventional and current risk assessment methods, current techniques used in the satellite industry for complex system development, cardinal risk modeling, and relevant aspects of utility theory. Data gathered from open literature on demonstrated launch vehicle and satellite in-orbit reliability, annual space insurance premiums and losses, and ground fatalities and range damage associated with satellite launch activities are presented. Empirically derived models are developed for risk attitudes of space system clients and third-party underwriters associated with satellite system development and deployment. Two application topics for risk transfer are examined: the client-underwriter relationship on assumption or transfer of risks associated with first-year mission success, and statutory risk transfer agreements between space insurance underwriters and the US government to promote growth in both commercial client and underwriting industries. Results indicate that client entities with wealth of at least an order of magnitude above satellite project costs should retain risks to first-year mission success despite present trends. Furthermore, large client entities such as the US government should never pursue risk transfer via insurance under previously demonstrated probabilities of mission success; potential savings may reasonably exceed multiple tens of $millions per space project. Additional results indicate that current US government statutory arrangements on risk sharing with underwriting entities appears reasonable with respect to stated objectives. This research combines aspects of multiple disciplines to include risk management, decision theory, utility theory, and systems architecting. It also demonstrates development of a more general theory on prescribing risk transfer criteria between distinct, but hierarchically associated entities involved in complex system development with applicability to a variety of technical domains.

Prediction of Coronary Artery Disease Risk Based on Multiple Longitudinal Biomarkers

PubMed Central

Yang, Lili; Yu, Menggang; Gao, Sujuan

2016-01-01

In the last decade, few topics in the area of cardiovascular disease (CVD) research have received as much attention as risk prediction. One of the well documented risk factors for CVD is high blood pressure (BP). Traditional CVD risk prediction models consider BP levels measured at a single time and such models form the basis for current clinical guidelines for CVD prevention. However, in clinical practice, BP levels are often observed and recorded in a longitudinal fashion. Information on BP trajectories can be powerful predictors for CVD events. We consider joint modeling of time to coronary artery disease and individual longitudinal measures of systolic and diastolic BPs in a primary care cohort with up to 20 years of follow-up. We applied novel prediction metrics to assess the predictive performance of joint models. Predictive performances of proposed joint models and other models were assessed via simulations and illustrated using the primary care cohort. PMID:26439685

Risk of multiple myeloma following medication use and medical conditions: a case-control study in Connecticut women.

PubMed

Landgren, Ola; Zhang, Yawei; Zahm, Sheila Hoar; Inskip, Peter; Zheng, Tongzhang; Baris, Dalsu

2006-12-01

Certain commonly used drugs and medical conditions characterized by chronic immune dysfunction and/or antigen stimulation have been suggested to affect important pathways in multiple myeloma tumor cell growth and survival. We conducted a population-based case-control study to investigate the role of medical history in the etiology of multiple myeloma among Connecticut women. A total of 179 incident multiple myeloma cases (21-84 years, diagnosed 1996-2002) and 691 population-based controls was included in this study. Information on medical conditions, medications, and medical radiation was obtained by in-person interviews. We calculated odds ratios (OR) as measures of relative risks using logistic regression models. A reduced multiple myeloma risk was found among women who had used antilipid statin therapy [OR, 0.4; 95% confidence interval (95% CI), 0.2-0.8] or estrogen replacement therapy (OR, 0.6; 95% CI, 0.4-0.99) or who had a medical history of allergy (OR, 0.4; 95% CI, 0.3-0.7), scarlet fever (OR, 0.5; 95% CI, 0.2-0.9), or bursitis (OR, 0.4; 95% CI, 0.2-0.7). An increased risk of multiple myeloma was found among women who used prednisone (OR, 5.1; 95% CI, 1.8-14.4), insulin (OR, 3.1; 95% CI, 1.1-9.0), or gout medication (OR, 6.7; 95% CI, 1.2-38.0). If our results are confirmed, mechanistic studies examining how prior use of insulin, prednisone, and, perhaps, gout medication might promote increased occurrence of multiple myeloma and how antilipid statins, estrogen replacement therapy, and certain medical conditions might protect against multiple myeloma may provide insights to the as yet unknown etiology of multiple myeloma.

The Prevalence of High-Risk HPV Types and Factors Determining Infection in Female Colombian Adolescents

PubMed Central

Del Río-Ospina, Luisa; Soto-De León, Sara Cecilia; Camargo, Milena; Sánchez, Ricardo; Mancilla, Cindy Lizeth; Patarroyo, Manuel Elkin

2016-01-01

This study reports six HR-HPV types’ infection prevalence discriminated by species and multiple infection in unvaccinated Colombian female adolescents, as well as some factors modulating the risk of infection. HPV DNA for six high-risk viral types was identified in cervical samples taken from 2,134 12–19 year-old females using conventional generic and type-specific PCR. Binomial logistical regression analysis was used for modelling HR-HPV infection and multiple infection risk. The interaction between variables in a stepwise model was also included in such analysis. Viral DNA was detected in 48.97% of the females; 28.52% of them had multiple infections, HPV-16 being the most frequently occurring type (37.44%). Cytological abnormality prevalence was 15.61%. Being over 16 years-old (1.66: 1.01–2.71 95%CI), white ethnicity (4.40: 1.16–16.73 95%CI), having had 3 or more sexual partners (1.77: 1.11–2.81 95%CI) and prior sexually-transmitted infections (STI) (1.65: 1.17–2.32 95%CI) were associated with a greater risk of HPV infection. Having given birth was related to a higher risk of infection by A7 species and antecedent of abortion to less risk of coinfection. Where the females in this study came from also influenced the risk of infection by A7 species as female adolescents from the Andean region had a lower risk of infection (0.42: 0.18–0.99 95%CI). The presence of factors related to risky sexual behaviour in the study population indicated that public health services should pay special attention to female adolescents to modify the risk of infection by high-risk HPV types and decrease their impact on this age group. PMID:27846258

A diversity index for model space selection in the estimation of benchmark and infectious doses via model averaging.

PubMed

Kim, Steven B; Kodell, Ralph L; Moon, Hojin

2014-03-01

In chemical and microbial risk assessments, risk assessors fit dose-response models to high-dose data and extrapolate downward to risk levels in the range of 1-10%. Although multiple dose-response models may be able to fit the data adequately in the experimental range, the estimated effective dose (ED) corresponding to an extremely small risk can be substantially different from model to model. In this respect, model averaging (MA) provides more robustness than a single dose-response model in the point and interval estimation of an ED. In MA, accounting for both data uncertainty and model uncertainty is crucial, but addressing model uncertainty is not achieved simply by increasing the number of models in a model space. A plausible set of models for MA can be characterized by goodness of fit and diversity surrounding the truth. We propose a diversity index (DI) to balance between these two characteristics in model space selection. It addresses a collective property of a model space rather than individual performance of each model. Tuning parameters in the DI control the size of the model space for MA. © 2013 Society for Risk Analysis.

Clustering of health behaviours in adult survivors of childhood cancer and the general population.

PubMed

Rebholz, C E; Rueegg, C S; Michel, G; Ammann, R A; von der Weid, N X; Kuehni, C E; Spycher, B D

2012-07-10

Little is known about engagement in multiple health behaviours in childhood cancer survivors. Using latent class analysis, we identified health behaviour patterns in 835 adult survivors of childhood cancer (age 20-35 years) and 1670 age- and sex-matched controls from the general population. Behaviour groups were determined from replies to questions on smoking, drinking, cannabis use, sporting activities, diet, sun protection and skin examination. The model identified four health behaviour patterns: 'risk-avoidance', with a generally healthy behaviour; 'moderate drinking', with higher levels of sporting activities, but moderate alcohol-consumption; 'risk-taking', engaging in several risk behaviours; and 'smoking', smoking but not drinking. Similar proportions of survivors and controls fell into the 'risk-avoiding' (42% vs 44%) and the 'risk-taking' cluster (14% vs 12%), but more survivors were in the 'moderate drinking' (39% vs 28%) and fewer in the 'smoking' cluster (5% vs 16%). Determinants of health behaviour clusters were gender, migration background, income and therapy. A comparable proportion of childhood cancer survivors as in the general population engage in multiple health-compromising behaviours. Because of increased vulnerability of survivors, multiple risk behaviours should be addressed in targeted health interventions.

A model for assessing the risk of human trafficking on a local level

NASA Astrophysics Data System (ADS)

Colegrove, Amanda

Human trafficking is a human rights violation that is difficult to quantify. Models for estimating the number of victims of trafficking presented by previous researchers depend on inconsistent, poor quality data. As an intermediate step to help current efforts by nonprofits to combat human trafficking, this project presents a model that is not dependent on quantitative data specific to human trafficking, but rather profiles the risk of human trafficking at the local level through causative factors. Businesses, indicated by the literature, were weighted based on the presence of characteristics that increase the likelihood of trafficking in persons. The mean risk was calculated by census tract to reveal the multiplicity of risk levels in both rural and urban settings. Results indicate that labor trafficking may be a more diffuse problem in Missouri than sex trafficking. Additionally, spatial patterns of risk remained largely the same regardless of adjustments made to the model.

Innovative neuro-fuzzy system of smart transport infrastructure for road traffic safety

NASA Astrophysics Data System (ADS)

Beinarovica, Anna; Gorobetz, Mikhail; Levchenkov, Anatoly

2017-09-01

The proposed study describes applying of neural network and fuzzy logic in transport control for safety improvement by evaluation of accidents’ risk by intelligent infrastructure devices. Risk evaluation is made by following multiple-criteria: danger, changeability and influence of changes for risk increasing. Neuro-fuzzy algorithms are described and proposed for task solution. The novelty of the proposed system is proved by deep analysis of known studies in the field. The structure of neuro-fuzzy system for risk evaluation and mathematical model is described in the paper. The simulation model of the intelligent devices for transport infrastructure is proposed to simulate different situations, assess the risks and propose the possible actions for infrastructure or vehicles to minimize the risk of possible accidents.

Assessing Women's Preferences and Preference Modeling for Breast Reconstruction Decision-Making.

PubMed

Sun, Clement S; Cantor, Scott B; Reece, Gregory P; Crosby, Melissa A; Fingeret, Michelle C; Markey, Mia K

2014-03-01

Women considering breast reconstruction must make challenging trade-offs amongst issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction. In this study, we used multiattribute utility theory to combine multiple objectives to yield a summary value using nine different preference models. We elicited the preferences of 36 women, aged 32 or older with no history of breast cancer, for the patient-reported outcome measures of breast satisfaction, psychosocial well-being, chest well-being, abdominal well-being, and sexual wellbeing as measured by the BREAST-Q in addition to time lost to reconstruction and out-of-pocket cost. Participants ranked hypothetical breast reconstruction outcomes. We examined each multiattribute utility preference model and assessed how often each model agreed with participants' rankings. The median amount of time required to assess preferences was 34 minutes. Agreement among the nine preference models with the participants ranged from 75.9% to 78.9%. None of the preference models performed significantly worse than the best performing risk averse multiplicative model. We hypothesize an average theoretical agreement of 94.6% for this model if participant error is included. There was a statistically significant positive correlation with more unequal distribution of weight given to the seven attributes. We recommend the risk averse multiplicative model for modeling the preferences of patients considering different forms of breast reconstruction because it agreed most often with the participants in this study.

Innovative model uses a new brand of specialist to target the high-risk chronically ill.

PubMed

2002-06-01

Some patients simply can't be taken care of in your typical 15-minute office visit. That's why a Houston-based organization developed a new model--and a new specialist--to deal with the growing number of patients affected by multiple diagnoses and other factors putting them at high risk for hospital utilization. With early success, the approach has now attracted the attention of Medicare and other insurers.

Revisiting the Table 2 fallacy: A motivating example examining preeclampsia and preterm birth.

PubMed

Bandoli, Gretchen; Palmsten, Kristin; Chambers, Christina D; Jelliffe-Pawlowski, Laura L; Baer, Rebecca J; Thompson, Caroline A

2018-05-21

A "Table Fallacy," as coined by Westreich and Greenland, reports multiple adjusted effect estimates from a single model. This practice, which remains common in published literature, can be problematic when different types of effect estimates are presented together in a single table. The purpose of this paper is to quantitatively illustrate this potential for misinterpretation with an example estimating the effects of preeclampsia on preterm birth. We analysed a retrospective population-based cohort of 2 963 888 singleton births in California between 2007 and 2012. We performed a modified Poisson regression to calculate the total effect of preeclampsia on the risk of PTB, adjusting for previous preterm birth. pregnancy alcohol abuse, maternal education, and maternal socio-demographic factors (Model 1). In subsequent models, we report the total effects of previous preterm birth, alcohol abuse, and education on the risk of PTB, comparing and contrasting the controlled direct effects, total effects, and confounded effect estimates, resulting from Model 1. The effect estimate for previous preterm birth (a controlled direct effect in Model 1) increased 10% when estimated as a total effect. The risk ratio for alcohol abuse, biased due to an uncontrolled confounder in Model 1, was reduced by 23% when adjusted for drug abuse. The risk ratio for maternal education, solely a predictor of the outcome, was essentially unchanged. Reporting multiple effect estimates from a single model may lead to misinterpretation and lack of reproducibility. This example highlights the need for careful consideration of the types of effects estimated in statistical models. © 2018 John Wiley & Sons Ltd.

Occupation, exposure to chemicals, sensitizing agents, and risk of multiple myeloma in Sweden.

PubMed

Lope, Virginia; Pérez-Gómez, Beatriz; Aragonés, Nuria; López-Abente, Gonzalo; Gustavsson, Per; Plato, Nils; Zock, Jan-Paul; Pollán, Marina

2008-11-01

This study sought to identify occupations with high incidence of multiple myeloma and to investigate possible excess risk associated with occupational exposure to chemicals and sensitizing agents in Sweden. A historical cohort of 2,992,166 workers was followed up (1971--1989) through record linkage with the National Cancer and Death Registries. For each job category, age and period standardized incidence ratios and age and period adjusted relative risks of multiple myeloma were calculated using Poisson models. Exposure to chemicals and to sensitizing agents was also assessed using two job-exposure matrices. Men and women were analyzed separately. During follow-up, 3,127 and 1,282 myelomas were diagnosed in men and women, respectively. In men, excess risk was detected among working proprietors, agricultural, horticultural and forestry enterprisers, bakers and pastry cooks, dental technicians, stone cutters/carvers, and prison/reformatory officials. In women, this excess was observed among attendants in psychiatric care, metal workers, bakers and pastry cooks, and paper/paperboard product workers. Workers, particularly bakers and pastry cooks, exposed to high molecular weight sensitizing agents registered an excess risk of over 40% across the sexes. Occasional, although intense, exposure to pesticides was also associated with risk of myeloma in our cohort. Our study supports a possible etiologic role for farming and use of pesticides in myeloma risk. The high incidence found in both female and male bakers and pastry cooks has not been described previously. Further research is required to assess the influence of high molecular weight sensitizing agents on risk of multiple myeloma.

Multiple-Tumor Analysis with MS_Combo Model (Use with BMDS Wizard)

EPA Pesticide Factsheets

Exercises and procedures on setting up and using the MS_Combo Wizard. The MS_Combo model provides BMD and BMDL estimates for the risk of getting one or more tumors for any combination of tumors observed in a single bioassay.

COST VS. QUALITY IN DEMOGRAPHIC MODELLING: WHEN IS A VITAL RATE GOOD ENOUGH?

EPA Science Inventory

This presentation will focus on the assessment of quality for demographic parameters to be used in population-level risk assessment. Current population models can handle genetic, demographic, and environmental stochasticity, density dependence, and multiple stressors. However, cu...

Evaluation of a model of violence risk assessment among forensic psychiatric patients.

PubMed

Douglas, Kevin S; Ogloff, James R P; Hart, Stephen D

2003-10-01

This study tested the interrater reliability and criterion-related validity of structured violence risk judgments made by using one application of the structured professional judgment model of violence risk assessment, the HCR-20 violence risk assessment scheme, which assesses 20 key risk factors in three domains: historical, clinical, and risk management. The HCR-20 was completed for a sample of 100 forensic psychiatric patients who had been found not guilty by reason of a mental disorder and were subsequently released to the community. Violence in the community was determined from multiple file-based sources. Interrater reliability of structured final risk judgments of low, moderate, or high violence risk made on the basis of the structured professional judgment model was acceptable (weighted kappa=.61). Structured final risk judgments were significantly predictive of postrelease community violence, yielding moderate to large effect sizes. Event history analyses showed that final risk judgments made with the structured professional judgment model added incremental validity to the HCR-20 used in an actuarial (numerical) sense. The findings support the structured professional judgment model of risk assessment as well as the HCR-20 specifically and suggest that clinical judgment, if made within a structured context, can contribute in meaningful ways to the assessment of violence risk.

A Contemporary Prostate Biopsy Risk Calculator Based on Multiple Heterogeneous Cohorts.

PubMed

Ankerst, Donna P; Straubinger, Johanna; Selig, Katharina; Guerrios, Lourdes; De Hoedt, Amanda; Hernandez, Javier; Liss, Michael A; Leach, Robin J; Freedland, Stephen J; Kattan, Michael W; Nam, Robert; Haese, Alexander; Montorsi, Francesco; Boorjian, Stephen A; Cooperberg, Matthew R; Poyet, Cedric; Vertosick, Emily; Vickers, Andrew J

2018-05-16

Prostate cancer prediction tools provide quantitative guidance for doctor-patient decision-making regarding biopsy. The widely used online Prostate Cancer Prevention Trial Risk Calculator (PCPTRC) utilized data from the 1990s based on six-core biopsies and outdated grading systems. We prospectively gathered data from men undergoing prostate biopsy in multiple diverse North American and European institutions participating in the Prostate Biopsy Collaborative Group (PBCG) in order to build a state-of-the-art risk prediction tool. We obtained data from 15 611 men undergoing 16 369 prostate biopsies during 2006-2017 at eight North American institutions for model-building and three European institutions for validation. We used multinomial logistic regression to estimate the risks of high-grade prostate cancer (Gleason score ≥7) on biopsy based on clinical characteristics, including age, prostate-specific antigen, digital rectal exam, African ancestry, first-degree family history, and prior negative biopsy. We compared the PBCG model to the PCPTRC using internal cross-validation and external validation on the European cohorts. Cross-validation on the North American cohorts (5992 biopsies) yielded the PBCG model area under the receiver operating characteristic curve (AUC) as 75.5% (95% confidence interval: 74.2-76.8), a small improvement over the AUC of 72.3% (70.9-73.7) for the PCPTRC (p<0.0001). However, calibration and clinical net benefit were far superior for the PBCG model. Using a risk threshold of 10%, clinical use of the PBCG model would lead to the equivalent of 25 fewer biopsies per 1000 patients without missing any high-grade cancers. Results were similar on external validation on 10 377 European biopsies. The PBCG model should be used in place of the PCPTRC for prediction of prostate biopsy outcome. A contemporary risk tool for outcomes on prostate biopsy based on the routine clinical risk factors is now available for informed decision-making. Copyright © 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Project START: Using a Multiple Intelligences Model in Identifying and Promoting Talent in High-Risk Students. Research Monograph 95136.

ERIC Educational Resources Information Center

Callahan, Carolyn M.; Tomlinson, Carol A.; Moon, Tonya R.; Tomchin, Ellen M.; Plucker, Jonathan A.

This monograph describes Project START (Support To Affirm Rising Talent), a three-year collaborative research effort to develop and apply gifted identification procedures based on Howard Gardner's (1983) theory of multiple intelligences. Specifically, the study attempted to: (1) develop identification procedures; (2) identify high-potential…

Multiple Ways of Knowing: Fostering Resiliency through Providing Opportunities for Participating in Learning

ERIC Educational Resources Information Center

Shepard, Jerri Simms

2004-01-01

The model of multiple intelligences developed by Howard Gardner is proposed as a framework for developing strengths, which will provide protective factors against risk and contribute to resilient outcomes. Educators are continually challenged to find successful ways to meet the needs of their students. One means is to support students by…

Multiple-scale prediction of forest loss risk across Borneo

Treesearch

Samuel A. Cushman; Ewan A. Macdonald; Erin L. Landguth; Yadvinder Malhi; David W. Macdonald

2017-01-01

Context: The forests of Borneo have among the highest biodiversity and also the highest forest loss rates on the planet. Objectives: Our objectives were to: (1) compare multiple modelling approaches, (2) evaluate the utility of landscape composition and configuration as predictors, (3) assess the influence of the ratio of forest loss and persistence points in the...

Data Model for Multi Hazard Risk Assessment Spatial Support Decision System

NASA Astrophysics Data System (ADS)

Andrejchenko, Vera; Bakker, Wim; van Westen, Cees

2014-05-01

The goal of the CHANGES Spatial Decision Support System is to support end-users in making decisions related to risk reduction measures for areas at risk from multiple hydro-meteorological hazards. The crucial parts in the design of the system are the user requirements, the data model, the data storage and management, and the relationships between the objects in the system. The implementation of the data model is carried out entirely with an open source database management system with a spatial extension. The web application is implemented using open source geospatial technologies with PostGIS as the database, Python for scripting, and Geoserver and javascript libraries for visualization and the client-side user-interface. The model can handle information from different study areas (currently, study areas from France, Romania, Italia and Poland are considered). Furthermore, the data model handles information about administrative units, projects accessible by different types of users, user-defined hazard types (floods, snow avalanches, debris flows, etc.), hazard intensity maps of different return periods, spatial probability maps, elements at risk maps (buildings, land parcels, linear features etc.), economic and population vulnerability information dependent on the hazard type and the type of the element at risk, in the form of vulnerability curves. The system has an inbuilt database of vulnerability curves, but users can also add their own ones. Included in the model is the management of a combination of different scenarios (e.g. related to climate change, land use change or population change) and alternatives (possible risk-reduction measures), as well as data-structures for saving the calculated economic or population loss or exposure per element at risk, aggregation of the loss and exposure using the administrative unit maps, and finally, producing the risk maps. The risk data can be used for cost-benefit analysis (CBA) and multi-criteria evaluation (SMCE). The data model includes data-structures for CBA and SMCE. The model is at the stage where risk and cost-benefit calculations can be stored but the remaining part is currently under development. Multi-criteria information, user management and the relation of these with the rest of the model is our next step. Having a carefully designed data model plays a crucial role in the development of the whole system for rapid development, keeping the data consistent, and in the end, support the end-user in making good decisions in risk-reduction measures related to multiple natural hazards. This work is part of the EU FP7 Marie Curie ITN "CHANGES"project (www.changes-itn.edu)

A Strategy for a Parametric Flood Insurance Using Proxies

NASA Astrophysics Data System (ADS)

Haraguchi, M.; Lall, U.

2017-12-01

Traditionally, the design of flood control infrastructure and flood plain zoning require the estimation of return periods, which have been calculated by river hydraulic models with rainfall-runoff models. However, this multi-step modeling process leads to significant uncertainty to assess inundation. In addition, land use change and changing climate alter the potential losses, as well as make the modeling results obsolete. For these reasons, there is a strong need to create parametric indexes for the financial risk transfer for large flood events, to enable rapid response and recovery. Hence, this study examines the possibility of developing a parametric flood index at the national or regional level in Asia, which can be quickly mobilized after catastrophic floods. Specifically, we compare a single trigger based on rainfall index with multiple triggers using rainfall and streamflow indices by conducting case studies in Bangladesh and Thailand. The proposed methodology is 1) selecting suitable indices of rainfall and streamflow (if available), 2) identifying trigger levels for specified return periods for losses using stepwise and logistic regressions, 3) measuring the performance of indices, and 4) deriving return periods of selected windows and trigger levels. Based on the methodology, actual trigger levels were identified for Bangladesh and Thailand. Models based on multiple triggers reduced basis risks, an inherent problem in an index insurance. The proposed parametric flood index can be applied to countries with similar geographic and meteorological characteristics, and serve as a promising method for ex-ante risk financing for developing countries. This work is intended to be a preliminary work supporting future work on pricing risk transfer mechanisms in ex-ante risk finance.

Investigating Uncertainty and Sensitivity in Integrated, Multimedia Environmental Models: Tools for FRAMES-3MRA

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

Babendreier, Justin E.; Castleton, Karl J.

2005-08-01

Elucidating uncertainty and sensitivity structures in environmental models can be a difficult task, even for low-order, single-medium constructs driven by a unique set of site-specific data. Quantitative assessment of integrated, multimedia models that simulate hundreds of sites, spanning multiple geographical and ecological regions, will ultimately require a comparative approach using several techniques, coupled with sufficient computational power. The Framework for Risk Analysis in Multimedia Environmental Systems - Multimedia, Multipathway, and Multireceptor Risk Assessment (FRAMES-3MRA) is an important software model being developed by the United States Environmental Protection Agency for use in risk assessment of hazardous waste management facilities. The 3MRAmore » modeling system includes a set of 17 science modules that collectively simulate release, fate and transport, exposure, and risk associated with hazardous contaminants disposed of in land-based waste management units (WMU) .« less

Genetic risk factors for ovarian cancer and their role for endometriosis risk.

PubMed

Burghaus, Stefanie; Fasching, Peter A; Häberle, Lothar; Rübner, Matthias; Büchner, Kathrin; Blum, Simon; Engel, Anne; Ekici, Arif B; Hartmann, Arndt; Hein, Alexander; Beckmann, Matthias W; Renner, Stefan P

2017-04-01

Several genetic variants have been validated as risk factors for ovarian cancer. Endometriosis has also been described as a risk factor for ovarian cancer. Identifying genetic risk factors that are common to the two diseases might help improve our understanding of the molecular pathogenesis potentially linking the two conditions. In a hospital-based case-control analysis, 12 single nucleotide polymorphisms (SNPs), validated by the Ovarian Cancer Association Consortium (OCAC) and the Collaborative Oncological Gene-environment Study (COGS) project, were genotyped using TaqMan® OpenArray™ analysis. The cases consisted of patients with endometriosis, and the controls were healthy individuals without endometriosis. A total of 385 cases and 484 controls were analyzed. Odds ratios and P values were obtained using simple logistic regression models, as well as from multiple logistic regression models with adjustment for clinical predictors. rs11651755 in HNF1B was found to be associated with endometriosis in this case-control study. The OR was 0.66 (95% CI, 0.51 to 0.84) and the P value after correction for multiple testing was 0.01. None of the other genotypes was associated with a risk for endometriosis. As rs11651755 in HNF1B modified both the ovarian cancer risk and also the risk for endometriosis, HNF1B may be causally involved in the pathogenetic pathway leading from endometriosis to ovarian cancer. Copyright © 2017 Elsevier Inc. All rights reserved.

Tempo-spatial downscaling of multiple GCMs projections for soil erosion risk analysis at El Reno, Oklahoma, USA

USDA-ARS?s Scientific Manuscript database

Proper spatial and temporal treatments of climate change scenarios projected by General Circulation Models (GCMs) are critical to accurate assessment of climatic impacts on natural resources and ecosystems. For accurate prediction of soil erosion risk at a particular farm or field under climate cha...

Monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM): novel biological insights and development of early treatment strategies

PubMed Central

Kristinsson, Sigurdur Y.

2011-01-01

Monoclonal gammopathy of unknown significance (MGUS) and smoldering multiple myeloma (SMM) are asymptomatic plasma cell dyscrasias, with a propensity to progress to symptomatic MM. In recent years there have been improvements in risk stratification models (involving molecular markers) of both disorders, which have led to better understanding of the biology and probability of progression of MGUS and SMM. In the context of numerous molecular events and heterogeneous risk of progression, developing individualized risk profiles for patients with MGUS and SMM represents an ongoing challenge that has to be addressed by prospective clinical monitoring and extensive correlative science. In this review we discuss the current standard of care of patients with MGUS and SMM, the use of risk models, including flow cytometry and free-light chain analyses, for predicting risk of progression. Emerging evidence from molecular studies on MGUS and SMM, involving cytogenetics, gene-expression profiling, and microRNA as well as molecular imaging is described. Finally, future directions for improving individualized management of MGUS and SMM patients, as well as the potential for developing early treatment strategies designed to delay and prevent development of MM are discussed. PMID:21441462

Monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM): novel biological insights and development of early treatment strategies.

PubMed

Korde, Neha; Kristinsson, Sigurdur Y; Landgren, Ola

2011-05-26

Monoclonal gammopathy of unknown significance (MGUS) and smoldering multiple myeloma (SMM) are asymptomatic plasma cell dyscrasias, with a propensity to progress to symptomatic MM. In recent years there have been improvements in risk stratification models (involving molecular markers) of both disorders, which have led to better understanding of the biology and probability of progression of MGUS and SMM. In the context of numerous molecular events and heterogeneous risk of progression, developing individualized risk profiles for patients with MGUS and SMM represents an ongoing challenge that has to be addressed by prospective clinical monitoring and extensive correlative science. In this review we discuss the current standard of care of patients with MGUS and SMM, the use of risk models, including flow cytometry and free-light chain analyses, for predicting risk of progression. Emerging evidence from molecular studies on MGUS and SMM, involving cytogenetics, gene-expression profiling, and microRNA as well as molecular imaging is described. Finally, future directions for improving individualized management of MGUS and SMM patients, as well as the potential for developing early treatment strategies designed to delay and prevent development of MM are discussed.

The Role of C-Peptide as Marker of Cardiometabolic Risk in Women With Polycystic Ovary Syndrome: A Controlled Study

PubMed Central

de Medeiros, Sebastiao Freitas; Angelo, Laura Camila Antunes; de Medeiros, Matheus Antonio Souto; Banhara, Camila Regis; Barbosa, Bruna Barcelo; Yamamoto, Marcia Marly Winck

2018-01-01

Background The aim of this study was to examine the role of C-peptide as a biological marker of cardiometabolic risk in polycystic ovary syndrome (PCOS). Methods This case-control study enrolled 385 PCOS patients and 240 normal cycling women. Anthropometric and clinical variables were taken at first visit. Fasting C-peptide, glucose, lipids, and hormone measurements were performed. Simple and multiple correlations between C-peptide and other variables associated with dysmetabolism and cardiovascular disease were examined. Results C-peptide was well correlated with several anthropometric, metabolic, and endocrine parameters. In PCOS patients, stepwise multiple regression including C-peptide as the criterion variable and other predictors of cardiovascular disease risk provided a significant model in which the fasting C-peptide/glucose ratio, glucose, body weight, and free estrogen index (FEI) were retained (adjusted R2 = 0.988, F = 7.161, P = 0.008). Conclusion C-peptide levels alone or combined with C-peptide/glucose ratio, glucose, body weight, and FEI provided a significant model to identify PCOS patients with higher risk of future cardiometabolic diseases. PMID:29416587

Risk modelling study for carotid endarterectomy.

PubMed

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

2001-12-01

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

Separating spatial search and efficiency rates as components of predation risk

PubMed Central

DeCesare, Nicholas J.

2012-01-01

Predation risk is an important driver of ecosystems, and local spatial variation in risk can have population-level consequences by affecting multiple components of the predation process. I use resource selection and proportional hazard time-to-event modelling to assess the spatial drivers of two key components of risk—the search rate (i.e. aggregative response) and predation efficiency rate (i.e. functional response)—imposed by wolves (Canis lupus) in a multi-prey system. In my study area, both components of risk increased according to topographic variation, but anthropogenic features affected only the search rate. Predicted models of the cumulative hazard, or risk of a kill, underlying wolf search paths validated well with broad-scale variation in kill rates, suggesting that spatial hazard models provide a means of scaling up from local heterogeneity in predation risk to population-level dynamics in predator–prey systems. Additionally, I estimated an integrated model of relative spatial predation risk as the product of the search and efficiency rates, combining the distinct contributions of spatial heterogeneity to each component of risk. PMID:22977145

Model Checking of a Diabetes-Cancer Model

NASA Astrophysics Data System (ADS)

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

2011-06-01

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

Source preference and ambiguity aversion: models and evidence from behavioral and neuroimaging experiments.

PubMed

Chew, Soo Hong; Li, King King; Chark, Robin; Zhong, Songfa

2008-01-01

This experimental economics study using brain imaging techniques investigates the risk-ambiguity distinction in relation to the source preference hypothesis (Fox & Tversky, 1995) in which identically distributed risks arising from different sources of uncertainty may engender distinct preferences for the same decision maker, contrary to classical economic thinking. The use of brain imaging enables sharper testing of the implications of different models of decision-making including Chew and Sagi's (2008) axiomatization of source preference. Using fMRI, brain activations were observed when subjects make 48 sequential binary choices among even-chance lotteries based on whether the trailing digits of a number of stock prices at market closing would be odd or even. Subsequently, subjects rate familiarity of the stock symbols. When contrasting brain activation from more familiar sources with those from less familiar ones, regions appearing to be more active include the putamen, medial frontal cortex, and superior temporal gyrus. ROI analysis showed that the activation patterns in the familiar-unfamiliar and unfamiliar-familiar contrasts are similar to those in the risk-ambiguity and ambiguity-risk contrasts reported by Hsu et al. (2005). This supports the conjecture that the risk-ambiguity distinction can be subsumed by the source preference hypothesis. Our odd-even design has the advantage of inducing the same "unambiguous" probability of half for each subject in each binary comparison. Our finding supports the implications of the Chew-Sagi model and rejects models based on global probabilistic sophistication, including rank-dependent models derived from non-additive probabilities, e.g., Choquet expected utility and cumulative prospect theory, as well as those based on multiple priors, e.g., alpha-maxmin. The finding in Hsu et al. (2005) that orbitofrontal cortex lesion patients display neither ambiguity aversion nor risk aversion offers further support to the Chew-Sagi model. Our finding also supports the Levy et al. (2007) contention of a single valuation system encompassing risk and ambiguity aversion. This is the first neuroimaging study of the source preference hypothesis using a design which can discriminate among decision models ranging from risk-based ones to those relying on multiple priors.

Stress in multiple sclerosis: review of new developments and future directions.

PubMed

Lovera, Jesus; Reza, Tara

2013-11-01

In the experimental autoimmune encephalitis model of multiple sclerosis, the effects of stress on disease severity depend on multiple factors, including the animal's genetics and the type of stressor. The studies in humans relating stress to the risk of developing multiple sclerosis have found discordant results. The studies looking at the association of stress with relapses show a fairly consistent association, where higher stress is associated with a higher risk of relapse. Higher stress levels also appear to increase the risk of development of gadolinium-enhancing lesions. A recent randomized trial shows that reducing stress using stress management therapy (SMT), a cognitive-behavioral therapy approach, results in a statistically significant reduction in new magnetic resonance imaging lesions. The magnitude of this effect is large and comparable to the effects of existent disease-modifying therapies, but no data exist yet proving that SMT reduces relapses or clinical progression; the effect of SMT appears to be short-lived. Additional work is needed to improve the duration of this effect and make this therapy more widely accessible.

Strength and cardiometabolic risk in young adults: The mediator role of aerobic fitness and waist circumference.

PubMed

Díez-Fernández, A; Martínez-Vizcaíno, V; Torres-Costoso, A; Cañete García-Prieto, J; Franquelo-Morales, P; Sánchez-López, M

2018-07-01

The aim of this study was to analyze the mediation role of cardiorespiratory fitness and waist circumference in the association between muscular strength and cardiometabolic risk. A cross-sectional study involved first-year college students (n = 370) from a Spanish public university was performed. We measured weight, height, waist circumference, blood pressure, biochemical variables, maximum handgrip strength assessment, and cardiorespiratory fitness. We calculated handgrip dynamometry/weight and a previously validated cardiometabolic risk index. Analysis of covariance models was conducted to test differences in cardiometabolic risk values across muscular strength, cardiorespiratory fitness, and waist circumference categories, controlling for confounders. Hayes' PROCESS macro was used for the multiple mediation analysis. The relationship between muscular strength and cardiometabolic risk did not remain significant (c' = 1.76 [1.4]; P > .05) in a multiple serial bootstrapped mediation model including cardiorespiratory fitness and waist circumference as mediators when controlling for age and sex. According to the indirect effect, the significant paths in the model mediating this relationship between muscular strength and cardiometabolic risk index were as follows: muscular strength → waist circumference → cardiometabolic risk index (-4.899; 95% CI: -6.690; -3.450) and muscular strength → cardiorespiratory fitness → waist circumference → cardiometabolic risk index (-0.720; 95% CI: -1.316; -0.360). Both cardiorespiratory fitness and waist circumference mediate the association between muscular strength and cardiometabolic risk in young adults. Thus, our results place cardiorespiratory fitness and waist circumference as the main targets of physical activity programmes aimed at preventing cardiometabolic diseases. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Statistical Physics of Vaccine Design

NASA Astrophysics Data System (ADS)

Deem, Michael

2009-03-01

I will define a new parameter to quantify the antigenic distance between two H3N2 influenza strains. I will use this parameter to measure antigenic distance between circulating H3N2 strains and the closest vaccine component of the influenza vaccine. For the data between 1971 and 2004, the measure of antigenic distance correlates better with efficacy in humans of the H3N2 influenza A annual vaccine than do current state of the art measures of antigenic distance such as phylogenetic sequence analysis or ferret antisera inhibition assays. I suggest that this measure of antigenic distance can be used to guide the design of the annual flu vaccine. I will describe combining this measure of antigenic distance with a multiple-strain avian influenza transmission model to study the threat of simultaneous introduction of multiple avian influenza strains. For H3N2 influenza, the model is validated against observed viral fixation rates and epidemic progression rates from the World Health Organization FluNet - Global Influenza Surveillance Network. I find that a multiple-component avian influenza vaccine is helpful to control a simultaneous multiple introduction of bird-flu strains. I introduce Population at Risk (PaR) to quantify the risk of a flu pandemic, and calculate by this metric the improvement that a multiple vaccine offers.

A robust prognostic signature for hormone-positive node-negative breast cancer.

PubMed

Griffith, Obi L; Pepin, François; Enache, Oana M; Heiser, Laura M; Collisson, Eric A; Spellman, Paul T; Gray, Joe W

2013-01-01

Systemic chemotherapy in the adjuvant setting can cure breast cancer in some patients that would otherwise recur with incurable, metastatic disease. However, since only a fraction of patients would have recurrence after surgery alone, the challenge is to stratify high-risk patients (who stand to benefit from systemic chemotherapy) from low-risk patients (who can safely be spared treatment related toxicities and costs). We focus here on risk stratification in node-negative, ER-positive, HER2-negative breast cancer. We use a large database of publicly available microarray datasets to build a random forests classifier and develop a robust multi-gene mRNA transcription-based predictor of relapse free survival at 10 years, which we call the Random Forests Relapse Score (RFRS). Performance was assessed by internal cross-validation, multiple independent data sets, and comparison to existing algorithms using receiver-operating characteristic and Kaplan-Meier survival analysis. Internal redundancy of features was determined using k-means clustering to define optimal signatures with smaller numbers of primary genes, each with multiple alternates. Internal OOB cross-validation for the initial (full-gene-set) model on training data reported an ROC AUC of 0.704, which was comparable to or better than those reported previously or obtained by applying existing methods to our dataset. Three risk groups with probability cutoffs for low, intermediate, and high-risk were defined. Survival analysis determined a highly significant difference in relapse rate between these risk groups. Validation of the models against independent test datasets showed highly similar results. Smaller 17-gene and 8-gene optimized models were also developed with minimal reduction in performance. Furthermore, the signature was shown to be almost equally effective on both hormone-treated and untreated patients. RFRS allows flexibility in both the number and identity of genes utilized from thousands to as few as 17 or eight genes, each with multiple alternatives. The RFRS reports a probability score strongly correlated with risk of relapse. This score could therefore be used to assign systemic chemotherapy specifically to those high-risk patients most likely to benefit from further treatment.

A robust prognostic signature for hormone-positive node-negative breast cancer

PubMed Central

2013-01-01

Background Systemic chemotherapy in the adjuvant setting can cure breast cancer in some patients that would otherwise recur with incurable, metastatic disease. However, since only a fraction of patients would have recurrence after surgery alone, the challenge is to stratify high-risk patients (who stand to benefit from systemic chemotherapy) from low-risk patients (who can safely be spared treatment related toxicities and costs). Methods We focus here on risk stratification in node-negative, ER-positive, HER2-negative breast cancer. We use a large database of publicly available microarray datasets to build a random forests classifier and develop a robust multi-gene mRNA transcription-based predictor of relapse free survival at 10 years, which we call the Random Forests Relapse Score (RFRS). Performance was assessed by internal cross-validation, multiple independent data sets, and comparison to existing algorithms using receiver-operating characteristic and Kaplan-Meier survival analysis. Internal redundancy of features was determined using k-means clustering to define optimal signatures with smaller numbers of primary genes, each with multiple alternates. Results Internal OOB cross-validation for the initial (full-gene-set) model on training data reported an ROC AUC of 0.704, which was comparable to or better than those reported previously or obtained by applying existing methods to our dataset. Three risk groups with probability cutoffs for low, intermediate, and high-risk were defined. Survival analysis determined a highly significant difference in relapse rate between these risk groups. Validation of the models against independent test datasets showed highly similar results. Smaller 17-gene and 8-gene optimized models were also developed with minimal reduction in performance. Furthermore, the signature was shown to be almost equally effective on both hormone-treated and untreated patients. Conclusions RFRS allows flexibility in both the number and identity of genes utilized from thousands to as few as 17 or eight genes, each with multiple alternatives. The RFRS reports a probability score strongly correlated with risk of relapse. This score could therefore be used to assign systemic chemotherapy specifically to those high-risk patients most likely to benefit from further treatment. PMID:24112773

Risk factors of suicide mortality among multiple attempters: A national registry study in Taiwan.

PubMed

Chen, I-Ming; Liao, Shih-Cheng; Lee, Ming-Been; Wu, Chia-Yi; Lin, Po-Hsien; Chen, Wei J

2016-05-01

Little is known about the risk factors of suicide mortality among multiple attempters. This study aims to investigate the predictors of suicidal mortality in a prospective cohort of attempters in Taiwan, focusing on the time interval and suicide method change between the last two nonfatal attempts. The representative data retrieved from the National Suicide Surveillance System (NSSS) was linked with National Mortality Database to identify the causes of death in multiple attempters during 2006-2008. Cox-proportional hazard models were applied to calculate the hazard ratios for the predictors of suicide. Among the 55,560 attempters, 6485 (11.7%) had survived attempts ranging from one to 11 times; 861 (1.5%) eventually died by suicide. Multiple attempters were characterized by female (OR = 1.56, p < 0.0001), nonrecipient of national aftercare service (OR = 1.62, p < 0.0001), and current contact with mental health services (OR = 3.17, p < 0.0001). Most multiple attempters who survived from hanging (68.1%) and gas poisoning (61.9%) chose the same method in the following fatal episode. Predictors of suicidal death were identified as male, older age (≥ 45 years), shorter interval and not maintaining methods of low lethality in the last two nonfatal attempts. Receipt of nationwide aftercare was associated with lower risk of suicide but the effect was insignificant. The time interval of the last two nonfatal attempts and alteration in the lethality of suicide method were significant factors for completed suicide. Risk assessment involving these two factors may be necessary for multiple attempters in different clinical settings. Effective strategies for suicide prevention emphasizing this high risk population should be developed in the future. Copyright © 2015. Published by Elsevier B.V.

Development of a GCR Event-based Risk Model

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Ponomarev, Artem L.; Plante, Ianik; Carra, Claudio; Kim, Myung-Hee

2009-01-01

A goal at NASA is to develop event-based systems biology models of space radiation risks that will replace the current dose-based empirical models. Complex and varied biochemical signaling processes transmit the initial DNA and oxidative damage from space radiation into cellular and tissue responses. Mis-repaired damage or aberrant signals can lead to genomic instability, persistent oxidative stress or inflammation, which are causative of cancer and CNS risks. Protective signaling through adaptive responses or cell repopulation is also possible. We are developing a computational simulation approach to galactic cosmic ray (GCR) effects that is based on biological events rather than average quantities such as dose, fluence, or dose equivalent. The goal of the GCR Event-based Risk Model (GERMcode) is to provide a simulation tool to describe and integrate physical and biological events into stochastic models of space radiation risks. We used the quantum multiple scattering model of heavy ion fragmentation (QMSFRG) and well known energy loss processes to develop a stochastic Monte-Carlo based model of GCR transport in spacecraft shielding and tissue. We validated the accuracy of the model by comparing to physical data from the NASA Space Radiation Laboratory (NSRL). Our simulation approach allows us to time-tag each GCR proton or heavy ion interaction in tissue including correlated secondary ions often of high multiplicity. Conventional space radiation risk assessment employs average quantities, and assumes linearity and additivity of responses over the complete range of GCR charge and energies. To investigate possible deviations from these assumptions, we studied several biological response pathway models of varying induction and relaxation times including the ATM, TGF -Smad, and WNT signaling pathways. We then considered small volumes of interacting cells and the time-dependent biophysical events that the GCR would produce within these tissue volumes to estimate how GCR event rates mapped to biological signaling induction and relaxation times. We considered several hypotheses related to signaling and cancer risk, and then performed simulations for conditions where aberrant or adaptive signaling would occur on long-duration space mission. Our results do not support the conventional assumptions of dose, linearity and additivity. A discussion on how event-based systems biology models, which focus on biological signaling as the mechanism to propagate damage or adaptation, can be further developed for cancer and CNS space radiation risk projections is given.

Designing a multiple dependent state sampling plan based on the coefficient of variation.

PubMed

Yan, Aijun; Liu, Sanyang; Dong, Xiaojuan

2016-01-01

A multiple dependent state (MDS) sampling plan is developed based on the coefficient of variation of the quality characteristic which follows a normal distribution with unknown mean and variance. The optimal plan parameters of the proposed plan are solved by a nonlinear optimization model, which satisfies the given producer's risk and consumer's risk at the same time and minimizes the sample size required for inspection. The advantages of the proposed MDS sampling plan over the existing single sampling plan are discussed. Finally an example is given to illustrate the proposed plan.

The motivation, skills, and decision-making model of "drug abuse" prevention.

PubMed

Sussman, Steve; Earleywine, Mitchell; Wills, Thomas; Cody, Christine; Biglan, Tony; Dent, Clyde W; Newcomb, Michael D

2004-01-01

This article summarizes the theoretical basis for targeted prevention programs as they apply to different high-risk groups. We explain the advantages and disadvantages of different definitions of risk and discuss strategies for preventing drug use related problems in high-risk youth. Productive prevention programs for many at-risk groups share similar components, including those that address motivation, skills, and decision making. We present key aspects of these three components and link them to theories in clinical psychology, social psychology, sociology, and chemical dependence treatment. Among a total of 29 promising targeted prevention programs, we describe examples of empirically evaluated, intensive interventions that have made a positive impact on the attitudes and behavior of multiple problem youth. Incorporating the perspectives of multiple disciplines appears essential for progress in drug abuse and other problem behavior prevention.

Genotype-Based Association Mapping of Complex Diseases: Gene-Environment Interactions with Multiple Genetic Markers and Measurement Error in Environmental Exposures

PubMed Central

Lobach, Irvna; Fan, Ruzone; Carroll, Raymond T.

2011-01-01

With the advent of dense single nucleotide polymorphism genotyping, population-based association studies have become the major tools for identifying human disease genes and for fine gene mapping of complex traits. We develop a genotype-based approach for association analysis of case-control studies of gene-environment interactions in the case when environmental factors are measured with error and genotype data are available on multiple genetic markers. To directly use the observed genotype data, we propose two genotype-based models: genotype effect and additive effect models. Our approach offers several advantages. First, the proposed risk functions can directly incorporate the observed genotype data while modeling the linkage disequihbrium information in the regression coefficients, thus eliminating the need to infer haplotype phase. Compared with the haplotype-based approach, an estimating procedure based on the proposed methods can be much simpler and significantly faster. In addition, there is no potential risk due to haplotype phase estimation. Further, by fitting the proposed models, it is possible to analyze the risk alleles/variants of complex diseases, including their dominant or additive effects. To model measurement error, we adopt the pseudo-likelihood method by Lobach et al. [2008]. Performance of the proposed method is examined using simulation experiments. An application of our method is illustrated using a population-based case-control study of association between calcium intake with the risk of colorectal adenoma development. PMID:21031455

Analysis of longitudinal multivariate outcome data from couples cohort studies: application to HPV transmission dynamics

PubMed Central

Kong, Xiangrong; Wang, Mei-Cheng; Gray, Ronald

2014-01-01

We consider a specific situation of correlated data where multiple outcomes are repeatedly measured on each member of a couple. Such multivariate longitudinal data from couples may exhibit multi-faceted correlations which can be further complicated if there are polygamous partnerships. An example is data from cohort studies on human papillomavirus (HPV) transmission dynamics in heterosexual couples. HPV is a common sexually transmitted disease with 14 known oncogenic types causing anogenital cancers. The binary outcomes on the multiple types measured in couples over time may introduce inter-type, intra-couple, and temporal correlations. Simple analysis using generalized estimating equations or random effects models lacks interpretability and cannot fully utilize the available information. We developed a hybrid modeling strategy using Markov transition models together with pairwise composite likelihood for analyzing such data. The method can be used to identify risk factors associated with HPV transmission and persistence, estimate difference in risks between male-to-female and female-to-male HPV transmission, compare type-specific transmission risks within couples, and characterize the inter-type and intra-couple associations. Applying the method to HPV couple data collected in a Ugandan male circumcision (MC) trial, we assessed the effect of MC and the role of gender on risks of HPV transmission and persistence. PMID:26195849

Partner violence, power, and gender differences in South African adolescents' HIV/sexually transmitted infections risk behaviors.

PubMed

Teitelman, Anne M; Jemmott, John B; Bellamy, Scarlett L; Icard, Larry D; O'Leary, Ann; Heeren, G Anita; Ngwane, Zolani; Ratcliffe, Sarah J

2016-07-01

Low relationship power and victimization by intimate partner violence (IPV) have been linked to HIV risks among adult and adolescent women. This article examines associations of IPV and relationship power with sexual-risk behaviors and whether the associations differ by gender among South African adolescents. Sexual-risk behaviors (multiple partners in past 3 months; condom use at last sex), IPV, and relationship power were collected from 786 sexually experienced adolescents (mean age = 16.9) in Eastern Cape Province, South Africa, during the 54-month follow-up of a HIV/sexually transmitted infection (STI) risk-reduction intervention trial. The data were analyzed with logistic regression models. Adolescent boys were less likely to report condom use at last sex (p = .001) and more likely to report multiple partners (p < .001). A Gender × IPV interaction (p = .002) revealed that as IPV victimization increased, self-reported condom use at last sex decreased among girls, but increased among boys. A Gender × Relationship Power interaction (p = .004) indicated that as relationship power increased, self-reported condom use at last sex increased among girls, but decreased among boys. A Gender × IPV interaction (p = .004) indicated that as IPV victimization increased, self-reports of having multiple partners increased among boys, but not among girls. As relationship power increased, self-reports of having multiple partners decreased irrespective of gender. HIV risk-reduction interventions and policies should address gender differences in sexual-risk consequences of IPV and relationship power among adolescents and promote gender equity. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Reviewing Bayesian Networks potentials for climate change impacts assessment and management: A multi-risk perspective.

PubMed

Sperotto, Anna; Molina, José-Luis; Torresan, Silvia; Critto, Andrea; Marcomini, Antonio

2017-11-01

The evaluation and management of climate change impacts on natural and human systems required the adoption of a multi-risk perspective in which the effect of multiple stressors, processes and interconnections are simultaneously modelled. Despite Bayesian Networks (BNs) are popular integrated modelling tools to deal with uncertain and complex domains, their application in the context of climate change still represent a limited explored field. The paper, drawing on the review of existing applications in the field of environmental management, discusses the potential and limitation of applying BNs to improve current climate change risk assessment procedures. Main potentials include the advantage to consider multiple stressors and endpoints in the same framework, their flexibility in dealing and communicate with the uncertainty of climate projections and the opportunity to perform scenario analysis. Some limitations (i.e. representation of temporal and spatial dynamics, quantitative validation), however, should be overcome to boost BNs use in climate change impacts assessment and management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Risk management of a fund for natural disasters

NASA Astrophysics Data System (ADS)

Flores, C.

2003-04-01

Mexico is a country which has to deal with several natural disaster risks: earthquakes, droughts, volcanic eruptions, floods, slides, wild fires, extreme temperatures, etc. In order to reduce the country's vulnerability to the impact of these natural disasters and to support rapid recovery when they occur, the government established in 1996 Mexico's Fund for Natural Disasters (FONDEN). Since its creation, its resources have been insufficient to meet all government obligations. The aim of this project is the development of a dynamic strategy to optimise the management of a fund for natural disasters starting from the example of FONDEN. The problem of budgetary planning is being considered for the modelling. We control the level of the fund's cash (R_t)0<= t0 at t=0 and then we try to pull at every moment the process to this objective. Multifractal models in geophysics are physically based stochastic models. A multiplicative cascade model fitted to a data set can be used for generation of synthetic sequences that resemble the original data in terms of its scaling properties. Since recent years, uncertainty concepts based on multifractal fields are being applied to the development of techniques to calculate marginal and conditional probabilities of an extreme rainfall event in a determined zone. As initial point to the development of the model, a multifractal model for extreme rainfall events will be used as part of the input for the stochastic control model. A theme for further research is linking more warning systems to the model. Keywords: risk management, stochastic control, multifractal measures, multiplicative cascades, heavy rainfall events.

The effects of sleep quality, physical activity, and environmental quality on the risk of falls in dementia.

PubMed

Eshkoor, Sima Ataollahi; Hamid, Tengku Aizan; Nudin, Siti Sa'adiah Hassan; Mun, Chan Yoke

2013-06-01

This study aimed to identify the effects of sleep quality, physical activity, environmental quality, age, ethnicity, sex differences, marital status, and educational level on the risk of falls in the elderly individuals with dementia. Data were derived from a group of 1210 Malaysian elderly individuals who were noninstitutionalized and demented. The multiple logistic regression model was applied to estimate the risk of falls in respondents. Approximately the prevalence of falls was 17% among the individuals. The results of multiple logistic regression analysis revealed that age (odds ratio [OR] = 1.03), ethnicity (OR = 1.76), sleep quality (OR = 1.46), and environmental quality (OR = 0.62) significantly affected the risk of falls in individuals (P < .05). Furthermore, sex differences, marital status, educational level, and physical activity were not significant predictors of falls in samples (P > .05). It was found that age, ethnic non-Malay, and sleep disruption increased the risk of falls in respondents, but high environmental quality reduced the risk of falls.

APPLICATION OF A MULTIROUTE HUMAN PBPK MODEL FOR BROMODICHLOROMETHANE (BDCM)

EPA Science Inventory

Due to its presence in water as a volatile disinfection byproduct, BDCM poses a risk for exposure via multiple routes. Mechanistic data suggest target tissue metabolism could be important for some types of BDCM-induced toxicity. Utilizing our refined PBPK model for BDCM, the impa...

An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on forest ecosystem services

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

[DIFFERENT APPROACHES FOR CHEMICAL RISK ASSESSMENT IN LABORATORIES].

PubMed

Caporossi, Lidia; Papaleo, Bruno; Capanna, Silvia; Calicchia, Sara; Marcellini, Laura; De Rosa, Mariangela; Castellano, Paola

2015-01-01

The aim of this study was to compare the different approaches used for chemical risk assessment, in relation to the perception of riskfor operators, in some research laboratories of a hospital in Rome. All information regarding the chemicals used for the application of three algorithmic models for chemical risk assessment ("Movarisch", "Inforisk", "Archimede") were collected. An environmental and biological monitoring and a study on the combined exposure to multiple chemicals using the World Health Organization proposed steps were carried out. A questionnaire was prepared for the identification of risk perception. An estimation of chemical risk with algorithms was compared with data from monitoring: findings showed that estimated risk was higher than those identified with airborne or urine concentrations, always under their limit values. The study of multiple exposure showed a possible cumulative risk, in some cases, but the conditions of use (volume and time) often bring to a reduced one. The perception of risk attributed to the monitored hazardous substances showed a correct perception in all laboratories and for all workers, with regard to the substances manipulated.

Clustering of health behaviours in adult survivors of childhood cancer and the general population

PubMed Central

Rebholz, C E; Rueegg, C S; Michel, G; Ammann, R A; von der Weid, N X; Kuehni, C E; Spycher, B D

2012-01-01

Background: Little is known about engagement in multiple health behaviours in childhood cancer survivors. Methods: Using latent class analysis, we identified health behaviour patterns in 835 adult survivors of childhood cancer (age 20–35 years) and 1670 age- and sex-matched controls from the general population. Behaviour groups were determined from replies to questions on smoking, drinking, cannabis use, sporting activities, diet, sun protection and skin examination. Results: The model identified four health behaviour patterns: ‘risk-avoidance', with a generally healthy behaviour; ‘moderate drinking', with higher levels of sporting activities, but moderate alcohol-consumption; ‘risk-taking', engaging in several risk behaviours; and ‘smoking', smoking but not drinking. Similar proportions of survivors and controls fell into the ‘risk-avoiding' (42% vs 44%) and the ‘risk-taking' cluster (14% vs 12%), but more survivors were in the ‘moderate drinking' (39% vs 28%) and fewer in the ‘smoking' cluster (5% vs 16%). Determinants of health behaviour clusters were gender, migration background, income and therapy. Conclusion: A comparable proportion of childhood cancer survivors as in the general population engage in multiple health-compromising behaviours. Because of increased vulnerability of survivors, multiple risk behaviours should be addressed in targeted health interventions. PMID:22722311

Socioeconomic status and esophageal squamous cell carcinoma risk in Kashmir, India.

PubMed

Dar, Nazir A; Shah, Idrees A; Bhat, Gulzar A; Makhdoomi, Muzamil A; Iqbal, Beenish; Rafiq, Rumaisa; Nisar, Iqra; Bhat, Arshid B; Nabi, Sumaiya; Masood, Akbar; Shah, Sajad A; Lone, Mohd M; Zargar, Showkat A; Islami, Farhad; Boffetta, Paolo

2013-09-01

Studies have persistently associated esophageal squamous cell carcinoma (ESCC) risk with low socioeconomic status (SES), but this association is unexplored in Kashmir, an area with a high incidence of ESCC in the northernmost part of India. We carried out a case-control study to assess the association of multiple indicators of SES and ESCC risk in the Kashmir valley. A total number of 703 histologically confirmed ESCC cases and 1664 controls matched to the cases for age, sex, and district of residence were recruited from October 2008 to January 2012. Conditional logistic regression models were used to calculate unadjusted and adjusted odds ratios and 95% confidence intervals. Composite wealth scores were constructed based on the ownership of several appliances using multiple correspondence analyses. Higher education, living in a kiln brick or concrete house, use of liquefied petroleum gas and electricity for cooking, and higher wealth scores all showed an inverse association with ESCC risk. Compared to farmers, individuals who had government jobs or worked in the business sector were at lower risk of ESCC, but this association disappeared in fully adjusted models. Occupational strenuous physical activity was strongly associated with ESCC risk. In summary, we found a strong relationship of low SES and ESCC in Kashmir. The findings need to be studied further to understand the mechanisms through which such SES parameters increase ESCC risk. © 2013 Japanese Cancer Association.

Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making

PubMed Central

Sun, Clement S.; Cantor, Scott B.; Reece, Gregory P.; Crosby, Melissa A.; Fingeret, Michelle C.

2014-01-01

Background: Women considering breast reconstruction must make challenging trade-offs among issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction. Methods: In this study, we used multiattribute utility theory to combine multiple objectives to yield a summary value using 9 different preference models. We elicited the preferences of 36 women, aged 32 or older with no history of breast cancer, for the patient-reported outcome measures of breast satisfaction, psychosocial well-being, chest well-being, abdominal well-being, and sexual well-being as measured by the BREAST-Q in addition to time lost to reconstruction and out-of-pocket cost. Participants ranked hypothetical breast reconstruction outcomes. We examined each multiattribute utility preference model and assessed how often each model agreed with participants’ rankings. Results: The median amount of time required to assess preferences was 34 minutes. Agreement among the 9 preference models with the participants ranged from 75.9% to 78.9%. None of the preference models performed significantly worse than the best-performing risk-averse multiplicative model. We hypothesize an average theoretical agreement of 94.6% for this model if participant error is included. There was a statistically significant positive correlation with more unequal distribution of weight given to the 7 attributes. Conclusions: We recommend the risk-averse multiplicative model for modeling the preferences of patients considering different forms of breast reconstruction because it agreed most often with the participants in this study. PMID:25105083

Links between Risk and Attachment Security: Models of Influence

ERIC Educational Resources Information Center

Raikes, H. Abigail; Thompson, Ross A.

2005-01-01

The relation between maternal behavior and child attachment security is weaker among low SES samples, but it is unclear how stressors/risks associated with low SES alter the dynamics of attachment relationships. Results of this study of 63 low income mothers and their 24-36-month-old children indicated that the influence of multiple economic risks…

Discovering a Gold Mine of Strategies for At-Risk Students through Systematic Staff Development.

ERIC Educational Resources Information Center

Bernal, Jesse R.; Villarreal, Diana

This paper discusses an effective model of systematic staff development focusing on prevention and intervention strategies used with at-risk students. The following are key elements: (1) matching of the purposes of training to the goals of the school districts; (2) multiple and integrated activities; (3) participants' thorough orientation to the…

CFH Variants Affect Structural and Functional Brain Changes and Genetic Risk of Alzheimer's Disease.

PubMed

Zhang, Deng-Feng; Li, Jin; Wu, Huan; Cui, Yue; Bi, Rui; Zhou, He-Jiang; Wang, Hui-Zhen; Zhang, Chen; Wang, Dong; Kong, Qing-Peng; Li, Tao; Fang, Yiru; Jiang, Tianzi; Yao, Yong-Gang

2016-03-01

The immune response is highly active in Alzheimer's disease (AD). Identification of genetic risk contributed by immune genes to AD may provide essential insight for the prognosis, diagnosis, and treatment of this neurodegenerative disease. In this study, we performed a genetic screening for AD-related top immune genes identified in Europeans in a Chinese cohort, followed by a multiple-stage study focusing on Complement Factor H (CFH) gene. Effects of the risk SNPs on AD-related neuroimaging endophenotypes were evaluated through magnetic resonance imaging scan, and the effects on AD cerebrospinal fluid biomarkers (CSF) and CFH expression changes were measured in aged and AD brain tissues and AD cellular models. Our results showed that the AD-associated top immune genes reported in Europeans (CR1, CD33, CLU, and TREML2) have weak effects in Chinese, whereas CFH showed strong effects. In particular, rs1061170 (P(meta)=5.0 × 10(-4)) and rs800292 (P(meta)=1.3 × 10(-5)) showed robust associations with AD, which were confirmed in multiple world-wide sample sets (4317 cases and 16 795 controls). Rs1061170 (P=2.5 × 10(-3)) and rs800292 (P=4.7 × 10(-4)) risk-allele carriers have an increased entorhinal thickness in their young age and a higher atrophy rate as the disease progresses. Rs800292 risk-allele carriers have higher CSF tau and Aβ levels and severe cognitive decline. CFH expression level, which was affected by the risk-alleles, was increased in AD brains and cellular models. These comprehensive analyses suggested that CFH is an important immune factor in AD and affects multiple pathological changes in early life and during disease progress.

Selection of first-line therapy in multiple sclerosis using risk-benefit decision analysis.

PubMed

Bargiela, David; Bianchi, Matthew T; Westover, M Brandon; Chibnik, Lori B; Healy, Brian C; De Jager, Philip L; Xia, Zongqi

2017-02-14

To integrate long-term measures of disease-modifying drug efficacy and risk to guide selection of first-line treatment of multiple sclerosis. We created a Markov decision model to evaluate disability worsening and progressive multifocal leukoencephalopathy (PML) risk in patients receiving natalizumab (NTZ), fingolimod (FGL), or glatiramer acetate (GA) over 30 years. Leveraging publicly available data, we integrated treatment utility, disability worsening, and risk of PML into quality-adjusted life-years (QALYs). We performed sensitivity analyses varying PML risk, mortality and morbidity, and relative risk of disease worsening across clinically relevant ranges. Over the entire reported range of NTZ-associated PML risk, NTZ as first-line therapy is predicted to provide a greater net benefit (15.06 QALYs) than FGL (13.99 QALYs) or GA (12.71 QALYs) treatment over 30 years, after accounting for loss of QALYs due to PML or death (resulting from all causes). NTZ treatment is associated with delayed worsening to an Expanded Disability Status Scale score ≥6.0 vs FGL or GA (22.7, 17.0, and 12.4 years, respectively). Compared to untreated patients, NTZ-treated patients have a greater relative risk of death in the early years of treatment that varies according to PML risk profile. NTZ as a first-line treatment is associated with the highest net benefit across full ranges of PML risk, mortality, and morbidity compared to FGL or GA. Integrated modeling of long-term treatment risks and benefits informs stratified clinical decision-making and can support patient counseling on selection of first-line treatment options. © 2017 American Academy of Neurology.

Empirical assessment of debris flow risk on a regional scale in Yunnan province, southwestern China.

PubMed

Liu, Xilin; Yue, Zhong Qi; Tham, Lesliw George; Lee, Chack Fan

2002-08-01

Adopting the definition suggested by the United Nations, a risk model for regional debris flow assessment is presented. Risk is defined as the product of hazard and vulnerability, both of which are necessary for evaluation. A Multiple-Factor Composite Assessment Model is developed for quantifying regional debris flow hazard by taking into account eight variables that contribute to debris flow magnitude and its frequency of occurrence. Vulnerability is a measure of the potential total losses. On a regional scale, it can be measured by the fixed asset, gross domestic product, land resources, population density, as well as the age, education, and wealth of the inhabitants. A nonlinear power-function assessment model that accounts for these indexes is developed. As a case study, the model is applied to compute the hazard, vulnerability and risk for each prefecture of the Yunnan province in southwestern China.

Obesity during childhood and adolescence increases susceptibility to multiple sclerosis after accounting for established genetic and environmental risk factors.

PubMed

Gianfrancesco, Milena A; Acuna, Brigid; Shen, Ling; Briggs, Farren B S; Quach, Hong; Bellesis, Kalliope H; Bernstein, Allan; Hedstrom, Anna K; Kockum, Ingrid; Alfredsson, Lars; Olsson, Tomas; Schaefer, Catherine; Barcellos, Lisa F

2014-01-01

To investigate the association between obesity and multiple sclerosis (MS) while accounting for established genetic and environmental risk factors. Participants included members of Kaiser Permanente Medical Care Plan, Northern California Region (KPNC) (1235 MS cases and 697 controls). Logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (95% CI). Body mass index (BMI) or body size was the primary predictor of each model. Both incident and prevalent MS cases were studied. In analyses stratified by gender, being overweight at ages 10 and 20 were associated with MS in females (p<0.01). Estimates trended in the same direction for males, but were not significant. BMI in 20s demonstrated a linear relationship with MS (p-trend=9.60×10(-4)), and a twofold risk of MS for females with a BMI≥30kg/m(2) was observed (OR=2.15, 95% CI 1.18, 3.92). Significant associations between BMI in 20s and MS in males were not observed. Multivariate modelling demonstrated that significant associations between BMI or body size with MS in females persisted after adjusting for history of infectious mononucleosis and genetic risk factors, including HLA-DRB1*15:01 and established non-HLA risk alleles. Results show that childhood and adolescence obesity confer increased risk of MS in females beyond established heritable and environmental risk factors. Strong evidence for a dose-effect of BMI in 20s and MS was observed. The magnitude of BMI association with MS is as large as other known MS risk factors. Copyright © 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Obesity during childhood and adolescence increases susceptibility to multiple sclerosis after accounting for established genetic and environmental risk factors

PubMed Central

Gianfrancesco, Milena A.; Acuna, Brigid; Shen, Ling; Briggs, Farren B.S.; Quach, Hong; Bellesis, Kalliope H.; Bernstein, Allan; Hedstrom, Anna K.; Kockum, Ingrid; Alfredsson, Lars; Olsson, Tomas; Schaefer, Catherine; Barcellos, Lisa F.

2014-01-01

Objective To investigate the association between obesity and multiple sclerosis (MS) while accounting for established genetic and environmental risk factors. Methods Participants included members of Kaiser Permanente Medical Care Plan, Northern California Region (KPNC) (1,235 MS cases and 697 controls). Logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (95% CI). Body mass index (BMI) or body size was the primary predictor of each model. Both incident and prevalent MS cases were studied. Results In analyses stratified by gender, being overweight at age 10 and 20 were associated with MS in females (p<0.01). Estimates trended in the same direction for males, but were not significant. BMI in 20’s demonstrated a linear relationship with MS (p-trend=9.60 × 10−4), and a twofold risk of MS for females with a BMI ≥ 30 kg/m2 was observed (OR = 2.15, 95% CI 1.18, 3.92). Significant associations between BMI in 20’s and MS in males were not observed. Multivariate modeling demonstrated that significant associations between BMI or body size with MS in females persisted after adjusting for history of infectious mononucleosis and genetic risk factors, including HLA-DRB1*15:01 and established non-HLA risk alleles. Interpretation Results show that childhood and adolescence obesity confer increased risk of MS in females beyond established heritable and environmental risk factors. Strong evidence for a dose-effect of BMI in 20’s and MS was observed. The magnitude of BMI association with MS is as large as other known MS risk factors. PMID:25263833

Assessing Inter-Sectoral Climate Change Risks: The Role of ISIMIP

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia; Arnell, Nigel W.; Ebi, Kristie L.; Lotze-Campen, Hermann; Raes, Frank; Rapley, Chris; Smith, Mark Stafford; Cramer, Wolfgang; Frieler, Katja; Reyer, Christopher P. O.;

Balancing precision and risk: should multiple detection methods be analyzed separately in N-mixture models?

USGS Publications Warehouse

Graves, Tabitha A.; Royle, J. Andrew; Kendall, Katherine C.; Beier, Paul; Stetz, Jeffrey B.; Macleod, Amy C.

2012-01-01

Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic) and bear rubs (opportunistic). We used hierarchical abundance models (N-mixture models) with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1) lead to the selection of the same variables as important and (2) provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3) yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight), and (4) improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed against those risks. The analysis framework presented here will be useful for other species exhibiting heterogeneity by detection method.

Testing a multiple mediator model of the effect of childhood sexual abuse on adolescent sexual victimization.

PubMed

Bramsen, Rikke H; Lasgaard, Mathias; Koss, Mary P; Shevlin, Mark; Elklit, Ask; Banner, Jytte

2013-01-01

The present study modeled the direct relationship between child sexual abuse (CSA) and adolescent peer-to-peer sexual victimization (APSV) and the mediated effect via variables representing the number of sexual partners, sexual risk behavior, and signaling sexual boundaries. A cross-sectional study on the effect of CSA on APSV was conducted, utilizing a multiple mediator model. Mediated and direct effects in the model were estimated employing Mplus using bootstrapped percentile based confidence intervals to test for significance of mediated effects. The study employed 327 Danish female adolescents with a mean age of 14.9 years (SD = 0.5). The estimates from the mediational model indicated full mediation of the effect of CSA on APSV via number of sexual partners and sexual risk behavior. The current study suggests that the link between CSA and APSV was mediated by sexual behaviors specifically pertaining to situations of social peer interaction, rather than directly on prior experiences of sexual victimization. The present study identifies a modifiable target area for intervention to reduce adolescent sexual revictimization. © 2013 American Orthopsychiatric Association.

The multiple stressor ecological risk assessment for the mercury-contaminated South River and upper Shenandoah River using the Bayesian network-relative risk model.

PubMed

Landis, Wayne G; Ayre, Kimberley K; Johns, Annie F; Summers, Heather M; Stinson, Jonah; Harris, Meagan J; Herring, Carlie E; Markiewicz, April J

2017-01-01

We have conducted a regional scale risk assessment using the Bayesian Network Relative Risk Model (BN-RRM) to calculate the ecological risks to the South River and upper Shenandoah River study area. Four biological endpoints (smallmouth bass, white sucker, Belted Kingfisher, and Carolina Wren) and 4 abiotic endpoints (Fishing River Use, Swimming River Use, Boating River Use, and Water Quality Standards) were included in this risk assessment, based on stakeholder input. Although mercury (Hg) contamination was the original impetus for the site being remediated, other chemical and physical stressors were evaluated. There were 3 primary conclusions from the BN-RRM results. First, risk varies according to location, type and quality of habitat, and exposure to stressors within the landscape. The patterns of risk can be evaluated with reasonable certitude. Second, overall risk to abiotic endpoints was greater than overall risk to biotic endpoints. By including both biotic and abiotic endpoints, we are able to compare risk to endpoints that represent a wide range of stakeholder values. Third, whereas Hg reduction is the regulatory priority for the South River, Hg is not the only stressor driving risk to the endpoints. Ecological and habitat stressors contribute risk to the endpoints and should be considered when managing this site. This research provides the foundation for evaluating the risks of multiple stressors of the South River to a variety of endpoints. From this foundation, tools for the evaluation of management options and an adaptive management tools have been forged. Integr Environ Assess Manag 2017;13:85-99. © 2016 SETAC. © 2016 SETAC.

Multiple Pathways from Stress to Suicidality and the Protective Effect of Social Support in Hong Kong Adolescents

ERIC Educational Resources Information Center

Cheng, Sheung-Tak; Chan, Alfred C. M.

2007-01-01

Two theoretical models were constructed to illustrate how stressful events, family and friends support, depression, substance use, and death attitude mutually influence to create cumulative risks for suicide. The models were evaluated using structural equation modeling. Results showed that suicidality was strongly predicted by death attitude,…

Low cigarette consumption and risk of coronary heart disease and stroke: meta-analysis of 141 cohort studies in 55 study reports.

PubMed

Hackshaw, Allan; Morris, Joan K; Boniface, Sadie; Tang, Jin-Ling; Milenković, Dušan

2018-01-24

To use the relation between cigarette consumption and cardiovascular disease to quantify the risk of coronary heart disease and stroke for light smoking (one to five cigarettes/day). Systematic review and meta-analysis. Medline 1946 to May 2015, with manual searches of references. Prospective cohort studies with at least 50 events, reporting hazard ratios or relative risks (both hereafter referred to as relative risk) compared with never smokers or age specific incidence in relation to risk of coronary heart disease or stroke. MOOSE guidelines were followed. For each study, the relative risk was estimated for smoking one, five, or 20 cigarettes per day by using regression modelling between risk and cigarette consumption. Relative risks were adjusted for at least age and often additional confounders. The main measure was the excess relative risk for smoking one cigarette per day (RR 1_per_day -1) expressed as a proportion of that for smoking 20 cigarettes per day (RR 20_per_day -1), expected to be about 5% assuming a linear relation between risk and consumption (as seen with lung cancer). The relative risks for one, five, and 20 cigarettes per day were also pooled across all studies in a random effects meta-analysis. Separate analyses were done for each combination of sex and disorder. The meta-analysis included 55 publications containing 141 cohort studies. Among men, the pooled relative risk for coronary heart disease was 1.48 for smoking one cigarette per day and 2.04 for 20 cigarettes per day, using all studies, but 1.74 and 2.27 among studies in which the relative risk had been adjusted for multiple confounders. Among women, the pooled relative risks were 1.57 and 2.84 for one and 20 cigarettes per day (or 2.19 and 3.95 using relative risks adjusted for multiple factors). Men who smoked one cigarette per day had 46% of the excess relative risk for smoking 20 cigarettes per day (53% using relative risks adjusted for multiple factors), and women had 31% of the excess risk (38% using relative risks adjusted for multiple factors). For stroke, the pooled relative risks for men were 1.25 and 1.64 for smoking one or 20 cigarettes per day (1.30 and 1.56 using relative risks adjusted for multiple factors). In women, the pooled relative risks were 1.31 and 2.16 for smoking one or 20 cigarettes per day (1.46 and 2.42 using relative risks adjusted for multiple factors). The excess risk for stroke associated with one cigarette per day (in relation to 20 cigarettes per day) was 41% for men and 34% for women (or 64% and 36% using relative risks adjusted for multiple factors). Relative risks were generally higher among women than men. Smoking only about one cigarette per day carries a risk of developing coronary heart disease and stroke much greater than expected: around half that for people who smoke 20 per day. No safe level of smoking exists for cardiovascular disease. Smokers should aim to quit instead of cutting down to significantly reduce their risk of these two common major disorders. 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.

Low cigarette consumption and risk of coronary heart disease and stroke: meta-analysis of 141 cohort studies in 55 study reports

PubMed Central

Morris, Joan K; Boniface, Sadie; Tang, Jin-Ling; Milenković, Dušan

2018-01-01

Abstract Objective To use the relation between cigarette consumption and cardiovascular disease to quantify the risk of coronary heart disease and stroke for light smoking (one to five cigarettes/day). Design Systematic review and meta-analysis. Data sources Medline 1946 to May 2015, with manual searches of references. Eligibility criteria for selecting studies Prospective cohort studies with at least 50 events, reporting hazard ratios or relative risks (both hereafter referred to as relative risk) compared with never smokers or age specific incidence in relation to risk of coronary heart disease or stroke. Data extraction/synthesis MOOSE guidelines were followed. For each study, the relative risk was estimated for smoking one, five, or 20 cigarettes per day by using regression modelling between risk and cigarette consumption. Relative risks were adjusted for at least age and often additional confounders. The main measure was the excess relative risk for smoking one cigarette per day (RR1_per_day−1) expressed as a proportion of that for smoking 20 cigarettes per day (RR20_per_day−1), expected to be about 5% assuming a linear relation between risk and consumption (as seen with lung cancer). The relative risks for one, five, and 20 cigarettes per day were also pooled across all studies in a random effects meta-analysis. Separate analyses were done for each combination of sex and disorder. Results The meta-analysis included 55 publications containing 141 cohort studies. Among men, the pooled relative risk for coronary heart disease was 1.48 for smoking one cigarette per day and 2.04 for 20 cigarettes per day, using all studies, but 1.74 and 2.27 among studies in which the relative risk had been adjusted for multiple confounders. Among women, the pooled relative risks were 1.57 and 2.84 for one and 20 cigarettes per day (or 2.19 and 3.95 using relative risks adjusted for multiple factors). Men who smoked one cigarette per day had 46% of the excess relative risk for smoking 20 cigarettes per day (53% using relative risks adjusted for multiple factors), and women had 31% of the excess risk (38% using relative risks adjusted for multiple factors). For stroke, the pooled relative risks for men were 1.25 and 1.64 for smoking one or 20 cigarettes per day (1.30 and 1.56 using relative risks adjusted for multiple factors). In women, the pooled relative risks were 1.31 and 2.16 for smoking one or 20 cigarettes per day (1.46 and 2.42 using relative risks adjusted for multiple factors). The excess risk for stroke associated with one cigarette per day (in relation to 20 cigarettes per day) was 41% for men and 34% for women (or 64% and 36% using relative risks adjusted for multiple factors). Relative risks were generally higher among women than men. Conclusions Smoking only about one cigarette per day carries a risk of developing coronary heart disease and stroke much greater than expected: around half that for people who smoke 20 per day. No safe level of smoking exists for cardiovascular disease. Smokers should aim to quit instead of cutting down to significantly reduce their risk of these two common major disorders. PMID:29367388

Modelling self-assessed vulnerability to HIV and its associated factors in a HIV-burdened country.

PubMed

Fagbamigbe, A F; Lawal, A M; Idemudia, E S

2017-12-01

Globally, individuals' self-assessment of vulnerability to HIV infection is important to maintain safer sexual behaviour and reduce risky behaviours. However, determinants of self-perceived risk of HIV infection are not well documented and differ. We assessed the level of self-perceived vulnerability to HIV infection in Nigeria and also identified its risk factors. We explored a recent nationally representative data with self-reported vulnerability ('high', 'low' and 'no risk at all') to HIV infection as the outcome of interest. Data were weighted and association between the outcomes and the risk factors determined. We used simple ordered logit regression to model relationship between the outcome variable and risk factors, and controlled for the significant variables in multiple ordered logistic regression at 5% significance level. About 74% had good knowledge of HIV transmission and 6% had experienced STI recently. The likelihood of assessing oneself as having 'no risk at all' was 50% and for 'high chances' was 1.6%. Self-perceived high risk of HIV was higher among those who recently experienced STI (5.6%) than those who did not (1.7%), and also higher among those who recently engaged in transactional sex and had multiple sexual partners. The odds of good knowledge of HIV transmission on high self-perceived vulnerability to HIV was 19% higher than poor knowledge (OR = 1.19, 95% CI: 1.12-1.27). Also, respondents who recently had multiple sexual partners were 72% (OR = 1.72, 95% CI: 1.60-1.86) more likely to report self as having high risk. Younger respondents aged 14-19 years had higher odds of 41% (OR = 1.41, 95% CI: 1.29-1.55) to perceive self as having high vulnerability to HIV than older respondents. High vulnerability to HIV infection was reported among younger respondents, those with history of STIS and those who engage in multiple sexual relations. Despite high level of risky sexual behaviour and good knowledge of HIV transmission and prevention found in this study, self-perceived vulnerability to HIV generally is low. For the low perception found in this study to translate to low chance of HIV infection, there is need for all stakeholders to embark on risk reduction initiatives through sexual education that would minimise risky sexual practices and ensuring availability and affordability of HIV prevention methods.

Modeling Freedom From Progression for Standard-Risk Medulloblastoma: A Mathematical Tumor Control Model With Multiple Modes of Failure

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

Brodin, N. Patrik, E-mail: nils.patrik.brodin@rh.dk; Niels Bohr Institute, University of Copenhagen, Copenhagen; Vogelius, Ivan R.

2013-10-01

Purpose: As pediatric medulloblastoma (MB) is a relatively rare disease, it is important to extract the maximum information from trials and cohort studies. Here, a framework was developed for modeling tumor control with multiple modes of failure and time-to-progression for standard-risk MB, using published pattern of failure data. Methods and Materials: Outcome data for standard-risk MB published after 1990 with pattern of relapse information were used to fit a tumor control dose-response model addressing failures in both the high-dose boost volume and the elective craniospinal volume. Estimates of 5-year event-free survival from 2 large randomized MB trials were used tomore » model the time-to-progression distribution. Uncertainty in freedom from progression (FFP) was estimated by Monte Carlo sampling over the statistical uncertainty in input data. Results: The estimated 5-year FFP (95% confidence intervals [CI]) for craniospinal doses of 15, 18, 24, and 36 Gy while maintaining 54 Gy to the posterior fossa was 77% (95% CI, 70%-81%), 78% (95% CI, 73%-81%), 79% (95% CI, 76%-82%), and 80% (95% CI, 77%-84%) respectively. The uncertainty in FFP was considerably larger for craniospinal doses below 18 Gy, reflecting the lack of data in the lower dose range. Conclusions: Estimates of tumor control and time-to-progression for standard-risk MB provides a data-driven setting for hypothesis generation or power calculations for prospective trials, taking the uncertainties into account. The presented methods can also be applied to incorporate further risk-stratification for example based on molecular biomarkers, when the necessary data become available.« less

Invited seminar, University of North Texas: An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on forest ecosystem services - ESRP mtg

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...

Misleading prioritizations from modelling range shifts under climate change

Treesearch

Helen R. Sofaer; Catherine S. Jarnevich; Curtis H. Flather

2018-01-01

Conservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated...

DEVELOPMENT AND PEER REVIEW OF TIME-TO-EFFECT MODELS FOR THE ANALYSIS OF NEUROTOXICITY AND OTHER TIME DEPENDENT DATA

EPA Science Inventory

Neurobehavioral studies pose unique challenges for dose-response modeling, including small sample size and relatively large intra-subject variation, repeated measurements over time, multiple endpoints with both continuous and ordinal scales, and time dependence of risk characteri...

Economic Disadvantage in Complex Family Systems: Expansion of Family Stress Models

ERIC Educational Resources Information Center

Barnett, Melissa A.

2008-01-01

Economic disadvantage is associated with multiple risks to early socioemotional development. This article reviews research regarding family stress frameworks to model the pathways from economic disadvantage to negative child outcomes via family processes. Future research in this area should expand definitions of family and household to incorporate…

Behavioral Modeling of Adversaries with Multiple Objectives in Counterterrorism.

PubMed

Mazicioglu, Dogucan; Merrick, Jason R W

2018-05-01

Attacker/defender models have primarily assumed that each decisionmaker optimizes the cost of the damage inflicted and its economic repercussions from their own perspective. Two streams of recent research have sought to extend such models. One stream suggests that it is more realistic to consider attackers with multiple objectives, but this research has not included the adaption of the terrorist with multiple objectives to defender actions. The other stream builds off experimental studies that show that decisionmakers deviate from optimal rational behavior. In this article, we extend attacker/defender models to incorporate multiple objectives that a terrorist might consider in planning an attack. This includes the tradeoffs that a terrorist might consider and their adaption to defender actions. However, we must also consider experimental evidence of deviations from the rationality assumed in the commonly used expected utility model in determining such adaption. Thus, we model the attacker's behavior using multiattribute prospect theory to account for the attacker's multiple objectives and deviations from rationality. We evaluate our approach by considering an attacker with multiple objectives who wishes to smuggle radioactive material into the United States and a defender who has the option to implement a screening process to hinder the attacker. We discuss the problems with implementing such an approach, but argue that research in this area must continue to avoid misrepresenting terrorist behavior in determining optimal defensive actions. © 2017 Society for Risk Analysis.

Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models.

PubMed

Riley, Richard D; Ensor, Joie; Jackson, Dan; Burke, Danielle L

2017-01-01

Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher's information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis).

Fall risk factors analysis based on sample entropy of plantar kinematic signal during stance phase.

PubMed

Shengyun Liang; Huiyu Jia; Zilong Li; Huiqi Li; Xing Gao; Zuchang Ma; Yingnan Ma; Guoru Zhao

2016-08-01

Falls are a multi-causal phenomenon with a complex interaction. The aim of our research is to study the effect of multiple variables for potential risk of falls and construct an elderly fall risk assessment model based on demographics data and gait characteristics. A total of 101 subjects, whom belong to Malianwa Street, aged above 50 years old and participated in questionnaire survey. Participants were classified into three groups (high, medium and low risk group) according to the score of elderly fall risk assessment scale. In addition, the data of ground reaction force (GRF) and ground reaction moment (GRM) was record when they performed walking at comfortable state. The demographic variables, sample entropy of GRF and GRM, and impulse difference of bilateral foot were considered as potential explanatory variables of risk assessment model. Firstly, we investigated whether different groups could present difference in every variable. Statistical differences were found for the following variables: age (p=2.28e-05); impulse difference (p=0.02036); sample entropy of GRF in vertical direction (p=0.0144); sample entropy of GRM in anterior-posterior direction (p=0.0387). Finally, the multiple regression analysis results indicated that age, impulse difference and sample entropy of resultant GRM could identify individuals who had different levels of fall risk. Therefore, those results could potentially be useful in the fall risk assessment and monitor the state of physical function in elderly population.

Trends in Mortality After Primary Cytoreductive Surgery for Ovarian Cancer: A Systematic Review and Metaregression of Randomized Clinical Trials and Observational Studies.

PubMed

Di Donato, Violante; Kontopantelis, Evangelos; Aletti, Giovanni; Casorelli, Assunta; Piacenti, Ilaria; Bogani, Giorgio; Lecce, Francesca; Benedetti Panici, Pierluigi

2017-06-01

Primary cytoreductive surgery (PDS) followed by platinum-based chemotherapy is the cornerstone of treatment and the absence of residual tumor after PDS is universally considered the most important prognostic factor. The aim of the present analysis was to evaluate trend and predictors of 30-day mortality in patients undergoing primary cytoreduction for ovarian cancer. Literature was searched for records reporting 30-day mortality after PDS. All cohorts were rated for quality. Simple and multiple Poisson regression models were used to quantify the association between 30-day mortality and the following: overall or severe complications, proportion of patients with stage IV disease, median age, year of publication, and weighted surgical complexity index. Using the multiple regression model, we calculated the risk of perioperative mortality at different levels for statistically significant covariates of interest. Simple regression identified median age and proportion of patients with stage IV disease as statistically significant predictors of 30-day mortality. When included in the multiple Poisson regression model, both remained statistically significant, with an incidence rate ratio of 1.087 for median age and 1.017 for stage IV disease. Disease stage was a strong predictor, with the risk estimated to increase from 2.8% (95% confidence interval 2.02-3.66) for stage III to 16.1% (95% confidence interval 6.18-25.93) for stage IV, for a cohort with a median age of 65 years. Metaregression demonstrated that increased age and advanced clinical stage were independently associated with an increased risk of mortality, and the combined effects of both factors greatly increased the risk.

Modeling trade-offs between plant fiber and toxins: a framework for quantifying risks perceived by foraging herbivores.

PubMed

Camp, Meghan J; Shipley, Lisa A; Johnson, Timothy R; Forbey, Jennifer Sorensen; Rachlow, Janet L; Crowell, Miranda M

2015-12-01

When selecting habitats, herbivores must weigh multiple risks, such as predation, starvation, toxicity, and thermal stress, forcing them to make fitness trade-offs. Here, we applied the method of paired comparisons (PC) to investigate how herbivores make trade-offs between habitat features that influence selection of food patches. The method of PC measures utility and the inverse of utility, relative risk, and makes trade-offs and indifferences explicit by forcing animals to make choices between two patches with different types of risks. Using a series of paired-choice experiments to titrate the equivalence curve and find the marginal rate of substitution for one risk over the other, we evaluated how toxin-tolerant (pygmy rabbit Brachylagus idahoensis) and fiber-tolerant (mountain cottontail rabbit Sylviagus nuttallii) herbivores differed in their hypothesized perceived risk of fiber and toxins in food. Pygmy rabbits were willing to consume nearly five times more of the toxin 1,8-cineole in their diets to avoid consuming higher levels of fiber than were mountain cottontails. Fiber posed a greater relative risk for pygmy rabbits than cottontails and cineole a greater risk for cottontails than pygmy rabbits. Our flexible modeling approach can be used to (1) quantify how animals evaluate and trade off multiple habitat attributes when the benefits and risks are difficult to quantify, and (2) integrate diverse risks that influence fitness and habitat selection into a single index of habitat value. This index potentially could be applied to landscapes to predict habitat selection across several scales.

Modeling individual movement decisions of brown hare (Lepus europaeus) as a key concept for realistic spatial behavior and exposure: A population model for landscape-level risk assessment.

PubMed

Kleinmann, Joachim U; Wang, Magnus

2017-09-01

Spatial behavior is of crucial importance for the risk assessment of pesticides and for the assessment of effects of agricultural practice or multiple stressors, because it determines field use, exposition, and recovery. Recently, population models have increasingly been used to understand the mechanisms driving risk and recovery or to conduct landscape-level risk assessments. To include spatial behavior appropriately in population models for use in risk assessments, a new method, "probabilistic walk," was developed, which simulates the detailed daily movement of individuals by taking into account food resources, vegetation cover, and the presence of conspecifics. At each movement step, animals decide where to move next based on probabilities being determined from this information. The model was parameterized to simulate populations of brown hares (Lepus europaeus). A detailed validation of the model demonstrated that it can realistically reproduce various natural patterns of brown hare ecology and behavior. Simulated proportions of time animals spent in fields (PT values) were also comparable to field observations. It is shown that these important parameters for the risk assessment may, however, vary in different landscapes. The results demonstrate the value of using population models to reduce uncertainties in risk assessment and to better understand which factors determine risk in a landscape context. Environ Toxicol Chem 2017;36:2299-2307. © 2017 SETAC. © 2017 SETAC.

Global review of open access risk assessment software packages valid for global or continental scale analysis

NASA Astrophysics Data System (ADS)

Daniell, James; Simpson, Alanna; Gunasekara, Rashmin; Baca, Abigail; Schaefer, Andreas; Ishizawa, Oscar; Murnane, Rick; Tijssen, Annegien; Deparday, Vivien; Forni, Marc; Himmelfarb, Anne; Leder, Jan

2015-04-01

Over the past few decades, a plethora of open access software packages for the calculation of earthquake, volcanic, tsunami, storm surge, wind and flood have been produced globally. As part of the World Bank GFDRR Review released at the Understanding Risk 2014 Conference, over 80 such open access risk assessment software packages were examined. Commercial software was not considered in the evaluation. A preliminary analysis was used to determine whether the 80 models were currently supported and if they were open access. This process was used to select a subset of 31 models that include 8 earthquake models, 4 cyclone models, 11 flood models, and 8 storm surge/tsunami models for more detailed analysis. By using multi-criteria analysis (MCDA) and simple descriptions of the software uses, the review allows users to select a few relevant software packages for their own testing and development. The detailed analysis evaluated the models on the basis of over 100 criteria and provides a synopsis of available open access natural hazard risk modelling tools. In addition, volcano software packages have since been added making the compendium of risk software tools in excess of 100. There has been a huge increase in the quality and availability of open access/source software over the past few years. For example, private entities such as Deltares now have an open source policy regarding some flood models (NGHS). In addition, leaders in developing risk models in the public sector, such as Geoscience Australia (EQRM, TCRM, TsuDAT, AnuGA) or CAPRA (ERN-Flood, Hurricane, CRISIS2007 etc.), are launching and/or helping many other initiatives. As we achieve greater interoperability between modelling tools, we will also achieve a future wherein different open source and open access modelling tools will be increasingly connected and adapted towards unified multi-risk model platforms and highly customised solutions. It was seen that many software tools could be improved by enabling user-defined exposure and vulnerability. Without this function, many tools can only be used regionally and not at global or continental scale. It is becoming increasingly easy to use multiple packages for a single region and/or hazard to characterize the uncertainty in the risk, or use as checks for the sensitivities in the analysis. There is a potential for valuable synergy between existing software. A number of open source software packages could be combined to generate a multi-risk model with multiple views of a hazard. This extensive review has simply attempted to provide a platform for dialogue between all open source and open access software packages and to hopefully inspire collaboration between developers, given the great work done by all open access and open source developers.

Trade-space Analysis for Constellations

NASA Astrophysics Data System (ADS)

Le Moigne, J.; Dabney, P.; de Weck, O. L.; Foreman, V.; Grogan, P.; Holland, M. P.; Hughes, S. P.; Nag, S.

2016-12-01

Traditionally, space missions have relied on relatively large and monolithic satellites, but in the past few years, under a changing technological and economic environment, including instrument and spacecraft miniaturization, scalable launchers, secondary launches as well as hosted payloads, there is growing interest in implementing future NASA missions as Distributed Spacecraft Missions (DSM). The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. In this first version of our Trade-space Analysis Tool for Constellations (TAT-C), we are investigating questions such as: "How many spacecraft should be included in the constellation? Which design has the best cost/risk value?" The main goals of TAT-C are to: Handle multiple spacecraft sharing a mission objective, from SmallSats up through flagships, Explore the variables trade space for pre-defined science, cost and risk goals, and pre-defined metrics Optimize cost and performance across multiple instruments and platforms vs. one at a time. This paper describes the overall architecture of TAT-C including: a User Interface (UI) interacting with multiple users - scientists, missions designers or program managers; an Executive Driver gathering requirements from UI, then formulating Trade-space Search Requests for the Trade-space Search Iterator first with inputs from the Knowledge Base, then, in collaboration with the Orbit & Coverage, Reduction & Metrics, and Cost& Risk modules, generating multiple potential architectures and their associated characteristics. TAT-C leverages the use of the Goddard Mission Analysis Tool (GMAT) to compute coverage and ancillary data, streamlining the computations by modeling orbits in a way that balances accuracy and performance. TAT-C current version includes uniform Walker constellations as well as Ad-Hoc constellations, and its cost model represents an aggregate model consisting of Cost Estimating Relationships (CERs) from widely accepted models. The Knowledge Base supports both analysis and exploration, and the current GUI prototype automatically generates graphics representing metrics such as average revisit time or coverage as a function of cost.

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

PubMed

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

2017-08-01

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

Magnitude of income-related disparities in adverse perinatal outcomes.

PubMed

Shankardass, Ketan; O'Campo, Patricia; Dodds, Linda; Fahey, John; Joseph, Ks; Morinis, Julia; Allen, Victoria M

2014-03-04

To assess and compare multiple measurements of socioeconomic position (SEP) in order to determine the relationship with adverse perinatal outcomes across various contexts. A birth registry, the Nova Scotia Atlee Perinatal Database, was confidentially linked to income tax and related information for the year in which delivery occurred. Multiple logistic regression was used to examine odds ratios between multiple indicators of SEP and multiple adverse perinatal outcomes in 117734 singleton births between 1988 and 2003. Models for after tax family income were also adjusted for neighborhood deprivation to gauge the relative magnitude of effects related to SEP at both levels. Effects of SEP were stratified by single- versus multiple-parent family composition, and by urban versus rural location of residence. The risk of small for gestational age and spontaneous preterm birth was higher across all the indicators of lower SEP, while risk for large for gestational age was lower across indicators of lower SEP. Higher risk of postneonatal death was demonstrated for several measures of lower SEP. Higher material deprivation in the neighborhood of residence was associated with increased risk for perinatal death, small for gestational age birth, and iatrogenic and spontaneous preterm birth. Family composition and urbanicity were shown to modify the association between income and some perinatal outcomes. This study highlights the importance of understanding the definitions of SEP and the mechanisms that lead to the association between income and poor perinatal outcomes, and broadening the types of SEP measures used in some cases.

Magnitude of income-related disparities in adverse perinatal outcomes

PubMed Central

2014-01-01

Background To assess and compare multiple measurements of socioeconomic position (SEP) in order to determine the relationship with adverse perinatal outcomes across various contexts. Methods A birth registry, the Nova Scotia Atlee Perinatal Database, was confidentially linked to income tax and related information for the year in which delivery occurred. Multiple logistic regression was used to examine odds ratios between multiple indicators of SEP and multiple adverse perinatal outcomes in 117734 singleton births between 1988 and 2003. Models for after tax family income were also adjusted for neighborhood deprivation to gauge the relative magnitude of effects related to SEP at both levels. Effects of SEP were stratified by single- versus multiple-parent family composition, and by urban versus rural location of residence. Results The risk of small for gestational age and spontaneous preterm birth was higher across all the indicators of lower SEP, while risk for large for gestational age was lower across indicators of lower SEP. Higher risk of postneonatal death was demonstrated for several measures of lower SEP. Higher material deprivation in the neighborhood of residence was associated with increased risk for perinatal death, small for gestational age birth, and iatrogenic and spontaneous preterm birth. Family composition and urbanicity were shown to modify the association between income and some perinatal outcomes. Conclusions This study highlights the importance of understanding the definitions of SEP and the mechanisms that lead to the association between income and poor perinatal outcomes, and broadening the types of SEP measures used in some cases. PMID:24589212

Multiple-time scales analysis of physiological time series under neural control

NASA Technical Reports Server (NTRS)

Peng, C. K.; Hausdorff, J. M.; Havlin, S.; Mietus, J. E.; Stanley, H. E.; Goldberger, A. L.

1998-01-01

We discuss multiple-time scale properties of neurophysiological control mechanisms, using heart rate and gait regulation as model systems. We find that scaling exponents can be used as prognostic indicators. Furthermore, detection of more subtle degradation of scaling properties may provide a novel early warning system in subjects with a variety of pathologies including those at high risk of sudden death.

A diversified portfolio model of adaptability.

PubMed

Chandra, Siddharth; Leong, Frederick T L

2016-12-01

A new model of adaptability, the diversified portfolio model (DPM) of adaptability, is introduced. In the 1950s, Markowitz developed the financial portfolio model by demonstrating that investors could optimize the ratio of risk and return on their portfolios through risk diversification. The DPM integrates attractive features of a variety of models of adaptability, including Linville's self-complexity model, the risk and resilience model, and Bandura's social cognitive theory. The DPM draws on the concept of portfolio diversification, positing that diversified investment in multiple life experiences, life roles, and relationships promotes positive adaptation to life's challenges. The DPM provides a new integrative model of adaptability across the biopsychosocial levels of functioning. More importantly, the DPM addresses a gap in the literature by illuminating the antecedents of adaptive processes studied in a broad array of psychological models. The DPM is described in relation to the biopsychosocial model and propositions are offered regarding its utility in increasing adaptiveness. Recommendations for future research are also offered. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Drug Use in Soldiers: Family and Peer Contextual Associations.

PubMed

Habibi, Mojtaba; Darharaj, Mohammad; Kelly, Adrian B; Shahmiri, Hasan; Malekianjabali, Mona; Kheirolomoom, Seyedeh Leili

2017-08-24

Given the stressful nature of military life, people in the armed forces are vulnerable to substance use. The aim of this study was to explore the relationship between family and peers with drug use among military forces in Iran. Convenience sampling was used to recruit a total of 422 draftees doing military service in army units in Tehran, Iran. Measures of family and peers' risk and protective factors, alcohol use, and other drug use were administered. Findings indicated significant relationships between family (i.e., family models for risk behavior, parent sanctions, and family controls) and peers (i.e., peer modeling for risk behavior, peer controls, support from friends) with drug use. A multiple regression analysis revealed that peer modeling for risk behavior, family models for risk behavior, and parent sanctions were significant predictors of drug use in soldiers. These results were consistent with the influence of family and peer on drug use amongst soldiers. Programs designed to reduce alcohol and other drug use may benefit from tailoring to fit risk and protective files amongst peer and family networks.

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

PubMed

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

2008-09-01

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

Effect of genetic polymorphisms on development of gout.

PubMed

Urano, Wako; Taniguchi, Atsuo; Inoue, Eisuke; Sekita, Chieko; Ichikawa, Naomi; Koseki, Yumi; Kamatani, Naoyuki; Yamanaka, Hisashi

2013-08-01

To validate the association between genetic polymorphisms and gout in Japanese patients, and to investigate the cumulative effects of multiple genetic factors on the development of gout. Subjects were 153 Japanese male patients with gout and 532 male controls. The genotypes of 11 polymorphisms in the 10 genes that have been indicated to be associated with serum uric acid levels or gout were determined. The cumulative effects of the genetic polymorphisms were investigated using a weighted genotype risk score (wGRS) based on the number of risk alleles and the OR for gout. A model to discriminate between patients with gout and controls was constructed by incorporating the wGRS and clinical factors. C statistics method was applied to evaluate the capability of the model to discriminate gout patients from controls. Seven polymorphisms were shown to be associated with gout. The mean wGRS was significantly higher in patients with gout (15.2 ± 2.01) compared to controls (13.4 ± 2.10; p < 0.0001). The C statistic for the model using genetic information alone was 0.72, while the C statistic was 0.81 for the full model that incorporated all genetic and clinical factors. Accumulation of multiple genetic factors is associated with the development of gout. A prediction model for gout that incorporates genetic and clinical factors may be useful for identifying individuals who are at risk of gout.

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

PubMed Central

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

2009-01-01

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

Vascular protection in peripheral artery disease: systematic review and modelling study.

PubMed

Hackam, D G; Sultan, N M; Criqui, M H

2009-07-01

To ascertain the effectiveness of medical therapy for reducing risk in peripheral artery disease (PAD) and to model the potential impact of combining multiple efficacious approaches. 17 electronic databases, reference lists of primary studies, clinical practice guidelines, review articles, trial registries and conference proceedings from cardiology, vascular surgery and atherosclerosis meetings were screened. Eligible studies were randomized trials or meta-analyses of randomized trials of medical therapy for PAD which reported major cardiovascular events (myocardial infarction, stroke and cardiovascular death). Baseline event rates for modelling analyses were derived from published natural history cohorts. Overall, three strategies had persuasive evidence for reducing risk in PAD: antiplatelet agents (pooled RRR 26%, 95% CI 10 to 42), statins (pooled RRR 26%, 95% CI 18 to 33) and angiotensin-converting enzyme inhibitors (individual trial RRR 25%, 95% CI 8 to 39). The estimated cumulative relative risk reduction for all three strategies was 59% (CI 32 to 76). Given a 5-year major cardiovascular event rate of 25%, the corresponding absolute risk reduction and number needed to treat to prevent one event were 15% (CI 8 to 19) and 7 (CI 5 to 12), respectively. Population level analyses suggest that increased uptake of these modalities could prevent more than 200 000 events in patients with PAD each year. The use of multiple efficacious strategies has the potential to substantially reduce the cardiovascular burden of PAD. However, these data should be regarded as hypothetical, since they are based on mathematical modelling rather than factorial randomized trials.

A review of multi-risk methodologies for natural hazards: Consequences and challenges for a climate change impact assessment.

PubMed

Gallina, Valentina; Torresan, Silvia; Critto, Andrea; Sperotto, Anna; Glade, Thomas; Marcomini, Antonio

2016-03-01

This paper presents a review of existing multi-risk assessment concepts and tools applied by organisations and projects providing the basis for the development of a multi-risk methodology in a climate change perspective. Relevant initiatives were developed for the assessment of multiple natural hazards (e.g. floods, storm surges, droughts) affecting the same area in a defined timeframe (e.g. year, season, decade). Major research efforts were focused on the identification and aggregation of multiple hazard types (e.g. independent, correlated, cascading hazards) by means of quantitative and semi-quantitative approaches. Moreover, several methodologies aim to assess the vulnerability of multiple targets to specific natural hazards by means of vulnerability functions and indicators at the regional and local scale. The overall results of the review show that multi-risk approaches do not consider the effects of climate change and mostly rely on the analysis of static vulnerability (i.e. no time-dependent vulnerabilities, no changes among exposed elements). A relevant challenge is therefore to develop comprehensive formal approaches for the assessment of different climate-induced hazards and risks, including dynamic exposure and vulnerability. This requires the selection and aggregation of suitable hazard and vulnerability metrics to make a synthesis of information about multiple climate impacts, the spatial analysis and ranking of risks, including their visualization and communication to end-users. To face these issues, climate impact assessors should develop cross-sectorial collaborations among different expertise (e.g. modellers, natural scientists, economists) integrating information on climate change scenarios with sectorial climate impact assessment, towards the development of a comprehensive multi-risk assessment process. Copyright © 2015 Elsevier Ltd. All rights reserved.

Calibration and validation of toxicokinetic-toxicodynamic models for three neonicotinoids and some aquatic macroinvertebrates.

PubMed

Focks, Andreas; Belgers, Dick; Boerwinkel, Marie-Claire; Buijse, Laura; Roessink, Ivo; Van den Brink, Paul J

2018-05-01

Exposure patterns in ecotoxicological experiments often do not match the exposure profiles for which a risk assessment needs to be performed. This limitation can be overcome by using toxicokinetic-toxicodynamic (TKTD) models for the prediction of effects under time-variable exposure. For the use of TKTD models in the environmental risk assessment of chemicals, it is required to calibrate and validate the model for specific compound-species combinations. In this study, the survival of macroinvertebrates after exposure to the neonicotinoid insecticide was modelled using TKTD models from the General Unified Threshold models of Survival (GUTS) framework. The models were calibrated on existing survival data from acute or chronic tests under static exposure regime. Validation experiments were performed for two sets of species-compound combinations: one set focussed on multiple species sensitivity to a single compound: imidacloprid, and the other set on the effects of multiple compounds for a single species, i.e., the three neonicotinoid compounds imidacloprid, thiacloprid and thiamethoxam, on the survival of the mayfly Cloeon dipterum. The calibrated models were used to predict survival over time, including uncertainty ranges, for the different time-variable exposure profiles used in the validation experiments. From the comparison between observed and predicted survival, it appeared that the accuracy of the model predictions was acceptable for four of five tested species in the multiple species data set. For compounds such as neonicotinoids, which are known to have the potential to show increased toxicity under prolonged exposure, the calibration and validation of TKTD models for survival needs to be performed ideally by considering calibration data from both acute and chronic tests.

Fall Risk Assessment Tools for Elderly Living in the Community: Can We Do Better?

PubMed

Palumbo, Pierpaolo; Palmerini, Luca; Bandinelli, Stefania; Chiari, Lorenzo

2015-01-01

Falls are a common, serious threat to the health and self-confidence of the elderly. Assessment of fall risk is an important aspect of effective fall prevention programs. In order to test whether it is possible to outperform current prognostic tools for falls, we analyzed 1010 variables pertaining to mobility collected from 976 elderly subjects (InCHIANTI study). We trained and validated a data-driven model that issues probabilistic predictions about future falls. We benchmarked the model against other fall risk indicators: history of falls, gait speed, Short Physical Performance Battery (Guralnik et al. 1994), and the literature-based fall risk assessment tool FRAT-up (Cattelani et al. 2015). Parsimony in the number of variables included in a tool is often considered a proxy for ease of administration. We studied how constraints on the number of variables affect predictive accuracy. The proposed model and FRAT-up both attained the same discriminative ability; the area under the Receiver Operating Characteristic (ROC) curve (AUC) for multiple falls was 0.71. They outperformed the other risk scores, which reported AUCs for multiple falls between 0.64 and 0.65. Thus, it appears that both data-driven and literature-based approaches are better at estimating fall risk than commonly used fall risk indicators. The accuracy-parsimony analysis revealed that tools with a small number of predictors (~1-5) were suboptimal. Increasing the number of variables improved the predictive accuracy, reaching a plateau at ~20-30, which we can consider as the best trade-off between accuracy and parsimony. Obtaining the values of these ~20-30 variables does not compromise usability, since they are usually available in comprehensive geriatric assessments.

KIT polymorphisms were associated with the risk for head and neck squamous carcinoma in Chinese population.

PubMed

Hang, Dong; Yuan, Hua; Liu, Li; Wang, Lihua; Miao, Limin; Zhu, Meng; Du, Jiangbo; Dai, Juncheng; Hu, Zhibin; Chen, Ning; Shen, Hongbing; Ma, Hongxia

2017-01-01

KITLG/KIT pathway plays a vital role in multiple types of human cancer including head and neck squamous cell carcinoma (HNSCC). Genetic variations in KITLG and KIT may affect the expression or function of these genes, thereby modifying cancer risk. In this study, we evaluated the association of KITLG and KIT polymorphisms with HNSCC risk among Chinese population. Twenty-two tagging SNPs in KITLG and KIT genes were genotyped in a case-control study with 576 HNSCC patients and 1552 healthy controls. Logistic regression analyses revealed that an upstream SNP rs6554198 [additive model: adjusted odds ratio (OR) = 0.85, 95% confidence interval (CI) = 0.74-0.97, P = 0.019] and two intron SNPs rs2237025 (additive model: adjusted OR = 0.82, 95%CI = 0.70-0.95, P = 0.007), and rs17084687 (additive model: adjusted OR = 0.85, 95%CI = 0.73-0.99, P = 0.042) of KIT were significantly associated with the decreased risk of HNSCC. Combined analysis of the three SNPs showed that subjects carrying the protective alleles had decreased risk of HNSCC in a dose-response manner (P trend  = 0.001). Furthermore, interaction analyses revealed a significant multiplicative interaction between rs17084687 and drinking on HNSCC risk (P = 0.012). Luciferase activity assay indicated that the allele A of potentially functional rs6554198 led to significantly lower transcription activity of KIT compared to the risk allele G. Summarily, our findings suggested that SNPs in KIT gene may play a role in genetic susceptibility to HNSCC, which may improve our understanding of the pathogenic mechanisms of this disease. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Psychosocial risks associated with multiple births resulting from assisted reproduction: a Spanish sample.

PubMed

Roca de Bes, Montserrat; Gutierrez Maldonado, José; Gris Martínez, José M

2009-09-01

To determine the psychosocial risks associated with multiple births (twins or triplets) resulting from assisted reproductive technology (ART). Transverse study. Infertility units of a university hospital and a private hospital. Mothers and fathers of children between 6 months and 4 years conceived by ART (n = 123). The sample was divided into three groups: parents of singletons (n = 77), twins (n = 37), and triplets (n = 9). The questionnaire was self-administered by patients. It was either completed at the hospital or mailed to participants' homes. Scales measured material needs, quality of life, social stigma, depression, stress, and marital satisfaction. Logistic regression models were applied. Significant odds ratios were obtained for the number of children, material needs, social stigma, quality of life, and marital satisfaction. The results were more significant for data provided by mothers than by fathers. The informed consent form handed out at the beginning of ART should include information on the high risk of conceiving twins and triplets and on the possible psychosocial consequences of multiple births. As soon as a multiple pregnancy is confirmed, it would be useful to provide information on support groups and institutions. Psychological advice should also be given to the parents.

Assessing Climate Change Risks Using a Multi-Model Approach

NASA Astrophysics Data System (ADS)

Knorr, W.; Scholze, M.; Prentice, C.

2007-12-01

We quantify the risks of climate-induced changes in key ecosystem processes during the 21st century by forcing a dynamic global vegetation model with multiple scenarios from the IPCC AR4 data archive using 16 climate models and mapping the proportions of model runs showing exceedance of natural variability in wildfire frequency and freshwater supply or shifts in vegetation cover. Our analysis does not assign probabilities to scenarios. Instead, we consider the distribution of outcomes within three sets of model runs grouped according to the amount of global warming they simulate: < 2 degree C (including committed climate change simulations), 2-3 degree C, and >3 degree C. Here, we are contrasting two different methods for calculating the risks: first we use an equal weighting approach giving every model within one of the three sets the same weight, and second, we weight the models according to their ability to model ENSO. The differences are underpinning the need for the development of more robust performance metrics for global climate models.

Long-range Ising model for credit portfolios with heterogeneous credit exposures

NASA Astrophysics Data System (ADS)

Kato, Kensuke

2016-11-01

We propose the finite-size long-range Ising model as a model for heterogeneous credit portfolios held by a financial institution in the view of econophysics. The model expresses the heterogeneity of the default probability and the default correlation by dividing a credit portfolio into multiple sectors characterized by credit rating and industry. The model also expresses the heterogeneity of the credit exposure, which is difficult to evaluate analytically, by applying the replica exchange Monte Carlo method to numerically calculate the loss distribution. To analyze the characteristics of the loss distribution for credit portfolios with heterogeneous credit exposures, we apply this model to various credit portfolios and evaluate credit risk. As a result, we show that the tail of the loss distribution calculated by this model has characteristics that are different from the tail of the loss distribution of the standard models used in credit risk modeling. We also show that there is a possibility of different evaluations of credit risk according to the pattern of heterogeneity.

Health effects models for nuclear power plant accident consequence analysis: Low LET radiation

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

Evans, J.S.

1990-01-01

This report describes dose-response models intended to be used in estimating the radiological health effects of nuclear power plant accidents. Models of early and continuing effects, cancers and thyroid nodules, and genetic effects are provided. Weibull dose-response functions are recommended for evaluating the risks of early and continuing health effects. Three potentially lethal early effects -- the hematopoietic, pulmonary, and gastrointestinal syndromes -- are considered. In addition, models are included for assessing the risks of several nonlethal early and continuing effects -- including prodromal vomiting and diarrhea, hypothyroidism and radiation thyroiditis, skin burns, reproductive effects, and pregnancy losses. Linear andmore » linear-quadratic models are recommended for estimating cancer risks. Parameters are given for analyzing the risks of seven types of cancer in adults -- leukemia, bone, lung, breast, gastrointestinal, thyroid, and other.'' The category, other'' cancers, is intended to reflect the combined risks of multiple myeloma, lymphoma, and cancers of the bladder, kidney, brain, ovary, uterus and cervix. Models of childhood cancers due to in utero exposure are also developed. For most cancers, both incidence and mortality are addressed. The models of cancer risk are derived largely from information summarized in BEIR III -- with some adjustment to reflect more recent studies. 64 refs., 18 figs., 46 tabs.« less

Novel risk score of contrast-induced nephropathy after percutaneous coronary intervention.

PubMed

Ji, Ling; Su, XiaoFeng; Qin, Wei; Mi, XuHua; Liu, Fei; Tang, XiaoHong; Li, Zi; Yang, LiChuan

2015-08-01

Contrast-induced nephropathy (CIN) post-percutaneous coronary intervention (PCI) is a major cause of acute kidney injury. In this study, we established a comprehensive risk score model to assess risk of CIN after PCI procedure, which could be easily used in a clinical environment. A total of 805 PCI patients, divided into analysis cohort (70%) and validation cohort (30%), were enrolled retrospectively in this study. Risk factors for CIN were identified using univariate analysis and multivariate logistic regression in the analysis cohort. Risk score model was developed based on multiple regression coefficients. Sensitivity and specificity of the new risk score system was validated in the validation cohort. Comparisons between the new risk score model and previous reported models were applied. The incidence of post-PCI CIN in the analysis cohort (n = 565) was 12%. Considerably high CIN incidence (50%) was observed in patients with chronic kidney disease (CKD). Age >75, body mass index (BMI) >25, myoglobin level, cardiac function level, hypoalbuminaemia, history of chronic kidney disease (CKD), Intra-aortic balloon pump (IABP) and peripheral vascular disease (PVD) were identified as independent risk factors of post-PCI CIN. A novel risk score model was established using multivariate regression coefficients, which showed highest sensitivity and specificity (0.917, 95%CI 0.877-0.957) compared with previous models. A new post-PCI CIN risk score model was developed based on a retrospective study of 805 patients. Application of this model might be helpful to predict CIN in patients undergoing PCI procedure. © 2015 Asian Pacific Society of Nephrology.

Multiple transitions and HIV risk among orphaned Kenyan schoolgirls.

PubMed

Mojola, Sanyu A

2011-03-01

Why are orphaned girls at particular risk of acquiring HIV infection? Using a transition-to-adulthood framework, this study employs qualitative data from Nyanza Province, Kenya, to explore pathways to HIV risk among orphaned and nonorphaned high-school girls. It shows how simultaneous processes such as leaving their parental home, negotiating financial access, and relationship transitions interact to produce disproportionate risk for orphaned girls. The role of financial provision and parental love in modifying girls' trajectories to risk are also explored. A testable theoretical model is proposed based on the qualitative findings, and policy implications are suggested.

MULTIPLE TRANSITIONS AND HIV RISK AMONG AFRICAN SCHOOL GIRLS

PubMed Central

Mojola, Sanyu A

2012-01-01

Why are orphaned girls at particular risk of contracting HIV? Using a transition to adulthood framework, this paper uses qualitative data from Nyanza province, Kenya to explore pathways to HIV risk among orphaned and non-orphaned high school girls. I show how co-occurring processes such as residential transition out of the parental home, negotiating financial access and relationship transitions interact to produce disproportionate risk for orphan girls. I also explore the role of financial provision and parental love in modifying girls’ trajectories to risk. I propose a testable theoretical model based on the qualitative findings and suggest policy implications. PMID:21500699

Impact of exposure measurement error in air pollution epidemiology: effect of error type in time-series studies.

PubMed

Goldman, Gretchen T; Mulholland, James A; Russell, Armistead G; Strickland, Matthew J; Klein, Mitchel; Waller, Lance A; Tolbert, Paige E

2011-06-22

Two distinctly different types of measurement error are Berkson and classical. Impacts of measurement error in epidemiologic studies of ambient air pollution are expected to depend on error type. We characterize measurement error due to instrument imprecision and spatial variability as multiplicative (i.e. additive on the log scale) and model it over a range of error types to assess impacts on risk ratio estimates both on a per measurement unit basis and on a per interquartile range (IQR) basis in a time-series study in Atlanta. Daily measures of twelve ambient air pollutants were analyzed: NO2, NOx, O3, SO2, CO, PM10 mass, PM2.5 mass, and PM2.5 components sulfate, nitrate, ammonium, elemental carbon and organic carbon. Semivariogram analysis was applied to assess spatial variability. Error due to this spatial variability was added to a reference pollutant time-series on the log scale using Monte Carlo simulations. Each of these time-series was exponentiated and introduced to a Poisson generalized linear model of cardiovascular disease emergency department visits. Measurement error resulted in reduced statistical significance for the risk ratio estimates for all amounts (corresponding to different pollutants) and types of error. When modelled as classical-type error, risk ratios were attenuated, particularly for primary air pollutants, with average attenuation in risk ratios on a per unit of measurement basis ranging from 18% to 92% and on an IQR basis ranging from 18% to 86%. When modelled as Berkson-type error, risk ratios per unit of measurement were biased away from the null hypothesis by 2% to 31%, whereas risk ratios per IQR were attenuated (i.e. biased toward the null) by 5% to 34%. For CO modelled error amount, a range of error types were simulated and effects on risk ratio bias and significance were observed. For multiplicative error, both the amount and type of measurement error impact health effect estimates in air pollution epidemiology. By modelling instrument imprecision and spatial variability as different error types, we estimate direction and magnitude of the effects of error over a range of error types.

Validation of a novel air toxic risk model with air monitoring.

PubMed

Pratt, Gregory C; Dymond, Mary; Ellickson, Kristie; Thé, Jesse

2012-01-01

Three modeling systems were used to estimate human health risks from air pollution: two versions of MNRiskS (for Minnesota Risk Screening), and the USEPA National Air Toxics Assessment (NATA). MNRiskS is a unique cumulative risk modeling system used to assess risks from multiple air toxics, sources, and pathways on a local to a state-wide scale. In addition, ambient outdoor air monitoring data were available for estimation of risks and comparison with the modeled estimates of air concentrations. Highest air concentrations and estimated risks were generally found in the Minneapolis-St. Paul metropolitan area and lowest risks in undeveloped rural areas. Emissions from mobile and area (nonpoint) sources created greater estimated risks than emissions from point sources. Highest cancer risks were via ingestion pathway exposures to dioxins and related compounds. Diesel particles, acrolein, and formaldehyde created the highest estimated inhalation health impacts. Model-estimated air concentrations were generally highest for NATA and lowest for the AERMOD version of MNRiskS. This validation study showed reasonable agreement between available measurements and model predictions, although results varied among pollutants, and predictions were often lower than measurements. The results increased confidence in identifying pollutants, pathways, geographic areas, sources, and receptors of potential concern, and thus provide a basis for informing pollution reduction strategies and focusing efforts on specific pollutants (diesel particles, acrolein, and formaldehyde), geographic areas (urban centers), and source categories (nonpoint sources). The results heighten concerns about risks from food chain exposures to dioxins and PAHs. Risk estimates were sensitive to variations in methodologies for treating emissions, dispersion, deposition, exposure, and toxicity. © 2011 Society for Risk Analysis.

Individual versus systemic risk and the Regulator's Dilemma.

PubMed

Beale, Nicholas; Rand, David G; Battey, Heather; Croxson, Karen; May, Robert M; Nowak, Martin A

2011-08-02

The global financial crisis of 2007-2009 exposed critical weaknesses in the financial system. Many proposals for financial reform address the need for systemic regulation--that is, regulation focused on the soundness of the whole financial system and not just that of individual institutions. In this paper, we study one particular problem faced by a systemic regulator: the tension between the distribution of assets that individual banks would like to hold and the distribution across banks that best supports system stability if greater weight is given to avoiding multiple bank failures. By diversifying its risks, a bank lowers its own probability of failure. However, if many banks diversify their risks in similar ways, then the probability of multiple failures can increase. As more banks fail simultaneously, the economic disruption tends to increase disproportionately. We show that, in model systems, the expected systemic cost of multiple failures can be largely explained by two global parameters of risk exposure and diversity, which can be assessed in terms of the risk exposures of individual actors. This observation hints at the possibility of regulatory intervention to promote systemic stability by incentivizing a more diverse diversification among banks. Such intervention offers the prospect of an additional lever in the armory of regulators, potentially allowing some combination of improved system stability and reduced need for additional capital.

Adaptation of a Counseling Intervention to Address Multiple Cancer Risk Factors Among Overweight/Obese Latino Smokers

PubMed Central

Castro, Yessenia; Fernández, Maria E.; Strong, Larkin L.; Stewart, Diana W.; Krasny, Sarah; Robles, Eden Hernandez; Heredia, Natalia; Spears, Claire A.; Correa-Fernández, Virmarie; Eakin, Elizabeth; Resnicow, Ken; Basen-Engquist, Karen; Wetter, David W.

2015-01-01

More than 60% of cancer-related deaths in the United States are attributable to tobacco use, poor nutrition, and physical inactivity, and these risk factors tend to cluster together. Thus, strategies for cancer risk reduction would benefit from addressing multiple health risk behaviors. We adapted an evidence-based intervention grounded in social cognitive theory and principles of motivational interviewing originally developed for smoking cessation to also address physical activity and fruit/vegetable consumption among Latinos exhibiting multiple health risk behaviors. Literature reviews, focus groups, expert consultation, pretesting, and pilot testing were used to inform adaptation decisions. We identified common mechanisms underlying change in smoking, physical activity, and diet used as treatment targets; identified practical models of patient-centered cross-cultural service provision; and identified that family preferences and support as particularly strong concerns among the priority population. Adaptations made to the original intervention are described. The current study is a practical example of how an intervention can be adapted to maximize relevance and acceptability and also maintain the core elements of the original evidence-based intervention. The intervention has significant potential to influence cancer prevention efforts among Latinos in the United States and is being evaluated in a sample of 400 Latino overweight/obese smokers. PMID:25527143

Application of Deep Learning and Supervised Learning Methods to Recognize Nonlinear Hidden Pattern in Water Stress Levels from Spatiotemporal Datasets across Rural and Urban US Counties

NASA Astrophysics Data System (ADS)

Eisenhart, T.; Josset, L.; Rising, J. A.; Devineni, N.; Lall, U.

2017-12-01

In the wake of recent water crises, the need to understand and predict the risk of water stress in urban and rural areas has grown. This understanding has the potential to improve decision making in public resource management, policy making, risk management and investment decisions. Assuming an underlying relationship between urban and rural water stress and observable features, we apply Deep Learning and Supervised Learning models to uncover hidden nonlinear patterns from spatiotemporal datasets. Results of interest includes prediction accuracy on extreme categories (i.e. urban areas highly prone to water stress) and not solely the average risk for urban or rural area, which adds complexity to the tuning of model parameters. We first label urban water stressed counties using annual water quality violations and compile a comprehensive spatiotemporal dataset that captures the yearly evolution of climatic, demographic and economic factors of more than 3,000 US counties over the 1980-2010 period. As county-level data reporting is not done on a yearly basis, we test multiple imputation methods to get around the issue of missing data. Using Python libraries, TensorFlow and scikit-learn, we apply and compare the ability of, amongst other methods, Recurrent Neural Networks (testing both LSTM and GRU cells), Convolutional Neural Networks and Support Vector Machines to predict urban water stress. We evaluate the performance of those models over multiple time spans and combine methods to diminish the risk of overfitting and increase prediction power on test sets. This methodology seeks to identify hidden nonlinear patterns to assess the predominant data features that influence urban and rural water stress. Results from this application at the national scale will assess the performance of deep learning models to predict water stress risk areas across all US counties and will highlight a predominant Machine Learning method for modeling water stress risk using spatiotemporal data.

Transferability and robustness of real-time freeway crash risk assessment.

PubMed

Shew, Cameron; Pande, Anurag; Nuworsoo, Cornelius

2013-09-01

This study examines the data from single loop detectors on northbound (NB) US-101 in San Jose, California to estimate real-time crash risk assessment models. The classification tree and neural network based crash risk assessment models developed with data from NB US-101 are applied to data from the same freeway, as well as to the data from nearby segments of the SB US-101, NB I-880, and SB I-880 corridors. The performance of crash risk assessment models on these nearby segments is the focus of this research. The model applications show that it is in fact possible to use the same model for multiple freeways, as the underlying relationships between traffic data and crash risk remain similar. The framework provided here may be helpful to authorities for freeway segments with newly installed traffic surveillance apparatuses, since the real-time crash risk assessment models from nearby freeways with existing infrastructure would be able to provide a reasonable estimate of crash risk. The robustness of the model output is also assessed by location, time of day, and day of week. The analysis shows that on some locations the models may require further learning due to higher than expected false positive (e.g., the I-680/I-280 interchange on US-101 NB) or false negative rates. The approach for post-processing the results from the model provides ideas to refine the model prior to or during the implementation. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

A simulation study to determine the attenuation and bias in health risk estimates due to exposure measurement error in bi-pollutant models

EPA Science Inventory

To understand the combined health effects of exposure to ambient air pollutant mixtures, it is becoming more common to include multiple pollutants in epidemiologic models. However, the complex spatial and temporal pattern of ambient pollutant concentrations and related exposures ...

Development and Application of a Human PBPK Model for Bromodichloromethane (BDCM) to Investigate Impacts of Multi-Route Exposure

EPA Science Inventory

Due to its presence in water as a volatile disinfection byproduct, BDCM, which is mutagenic and a rodent carcinogen, poses a risk for exposure via multiple routes. We developed a refined human PBPK model for BDCM (including new chemical-specific human parameters) to evaluate the...

Developmental dyslexia: predicting individual risk

PubMed Central

Thompson, Paul A; Hulme, Charles; Nash, Hannah M; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J

2015-01-01

Background Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. Methods The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6 months (T1) at approximately annual intervals on tasks tapping cognitive, language, and executive-motor skills. The children were recruited to three groups: children at family risk of dyslexia, children with concerns regarding speech, and language development at 3;06 years and controls considered to be typically developing. At 8 years, children were classified as ‘dyslexic’ or not. Logistic regression models were used to predict the individual risk of dyslexia and to investigate how risk factors accumulate to predict poor literacy outcomes. Results Family-risk status was a stronger predictor of dyslexia at 8 years than low language in preschool. Additional predictors in the preschool years include letter knowledge, phonological awareness, rapid automatized naming, and executive skills. At the time of school entry, language skills become significant predictors, and motor skills add a small but significant increase to the prediction probability. We present classification accuracy using different probability cutoffs for logistic regression models and ROC curves to highlight the accumulation of risk factors at the individual level. Conclusions Dyslexia is the outcome of multiple risk factors and children with language difficulties at school entry are at high risk. Family history of dyslexia is a predictor of literacy outcome from the preschool years. However, screening does not reach an acceptable clinical level until close to school entry when letter knowledge, phonological awareness, and RAN, rather than family risk, together provide good sensitivity and specificity as a screening battery. PMID:25832320

Families at risk of poor parenting: a model for service delivery, assessment, and intervention.

PubMed

Ayoub, C; Jacewitz, M M

1982-01-01

The At Risk Parent Child Program is a multidisciplinary network agency designed for the secondary prevention of poor parenting and the extremes of child abuse and neglect. This model system of service delivery emphasizes (1) the coordination of existing community resources to access a target population of families at risk of parenting problems, (2) the provision of multiple special services in a neutral location (ambulatory pediatric clinic), and (3) the importance of intensive individual contact with a clinical professional who serves as primary therapist, social advocate and service coordinator for client families. Identification and assessment of families is best done during prenatal and perinatal periods. Both formal and informal procedures for screening for risk factors are described, and a simple set of at risk criteria for use by hospital nursing staff is provided. Preventive intervention strategies include special medical, psychological, social and developmental services, offered in an inpatient; outpatient, or in-home setting. Matching family needs to modality and setting of treatment is a major program concern. All direct services to at risk families are supplied by professionals employed within existing local agencies (hospital, public health department, state guidance center, and medical school pediatric clinic). Multiple agency involvement allows a broad-based screening capacity which allows thousands of families routine access to program services. The administrative center of the network stands as an independent, community-funded core which coordinates and monitors direct clinical services, and provides local political advocacy for families at risk of parenting problems.

Modeling adverse environmental impacts on the reproductive system.

PubMed

Sussman, N B; Mazumdar, S; Mattison, D R

1999-03-01

When priority topics are being established for the study of women's health, it is generally agreed that one important area on which to focus research is reproduction. For example, increasing attention has been directed to environmental exposures that disrupt the endocrine system and alter reproduction. These concerns also suggest the need to give greater attention to the use of animal toxicologic testing to draw inferences about human reproductive risks. Successful reproduction requires multiple simultaneous and sequential processes in both the male and female, and the effect of toxicity on reproduction-related processes is time dependent. Currently, however, the risk assessment approach does not allow for the use of multiple processes or for considering the reproductive process response as a function of time. We discuss several issues in modeling exposure effects on reproductive function for risk assessment and present an overview of approaches for reproductive risk assessment. Recommendations are provided for an effective animal study design for determining reproductive risk that addresses optimization of the duration of dosing, observation of the effects of exposure on validated biomarkers, analysis of several biomarkers for complete characterization of the exposure on the underlying biologic processes, the need for longitudinally observed exposure effects, and a procedure for estimating human reproductive risk from the animal findings. An approach to characterizing reproductive toxicity to estimate the increased fertility risks in a dibromochloropropane (DBCP)-exposed human population is illustrated, using several reproductive biomarkers simultaneously from a longitudinal rabbit inhalation study of DBCP and an interspecies extrapolation method.

Comparative and Predictive Multimedia Assessments Using Monte Carlo Uncertainty Analyses

NASA Astrophysics Data System (ADS)

Whelan, G.

2002-05-01

Multiple-pathway frameworks (sometimes referred to as multimedia models) provide a platform for combining medium-specific environmental models and databases, such that they can be utilized in a more holistic assessment of contaminant fate and transport in the environment. These frameworks provide a relatively seamless transfer of information from one model to the next and from databases to models. Within these frameworks, multiple models are linked, resulting in models that consume information from upstream models and produce information to be consumed by downstream models. The Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES) is an example, which allows users to link their models to other models and databases. FRAMES is an icon-driven, site-layout platform that is an open-architecture, object-oriented system that interacts with environmental databases; helps the user construct a Conceptual Site Model that is real-world based; allows the user to choose the most appropriate models to solve simulation requirements; solves the standard risk paradigm of release transport and fate; and exposure/risk assessments to people and ecology; and presents graphical packages for analyzing results. FRAMES is specifically designed allow users to link their own models into a system, which contains models developed by others. This paper will present the use of FRAMES to evaluate potential human health exposures using real site data and realistic assumptions from sources, through the vadose and saturated zones, to exposure and risk assessment at three real-world sites, using the Multimedia Environmental Pollutant Assessment System (MEPAS), which is a multimedia model contained within FRAMES. These real-world examples use predictive and comparative approaches coupled with a Monte Carlo analysis. A predictive analysis is where models are calibrated to monitored site data, prior to the assessment, and a comparative analysis is where models are not calibrated but based solely on literature or judgement and is usually used to compare alternatives. In many cases, a combination is employed where the model is calibrated to a portion of the data (e.g., to determine hydrodynamics), then used to compare alternatives. Three subsurface-based multimedia examples are presented, increasing in complexity. The first presents the application of a predictive, deterministic assessment; the second presents a predictive and comparative, Monte Carlo analysis; and the third presents a comparative, multi-dimensional Monte Carlo analysis. Endpoints are typically presented in terms of concentration, hazard, risk, and dose, and because the vadose zone model typically represents a connection between a source and the aquifer, it does not generally represent the final medium in a multimedia risk assessment.

Advantages of new cardiovascular risk-assessment strategies in high-risk patients with hypertension.

PubMed

Ruilope, Luis M; Segura, Julian

2005-10-01

Accurate assessment of cardiovascular disease (CVD) risk in patients with hypertension is important when planning appropriate treatment of modifiable risk factors. The causes of CVD are multifactorial, and hypertension seldom exists as an isolated risk factor. Classic models of risk assessment are more accurate than a simple counting of risk factors, but they are not generalizable to all populations. In addition, the risk associated with hypertension is graded, continuous, and independent of other risk factors, and this is not reflected in classic models of risk assessment. This article is intended to review both classic and newer models of CVD risk assessment. MEDLINE was searched for articles published between 1990 and 2005 that contained the terms cardiovascular disease, hypertension, or risk assessment. Articles describing major clinical trials, new data about cardiovascular risk, or global risk stratification were selected for review. Some patients at high long-term risk for CVD events (eg, patients aged <50 years with multiple risk factors) may go untreated because they do not meet the absolute risk-intervention threshold of 20% risk over 10 years with the classic model. Recognition of the limitations of classic risk-assessment models led to new guidelines, particularly those of the European Society of Hypertension-European Society of Cardiology. These guidelines view hypertension as one of many risk and disease factors that require treatment to decrease risk. These newer guidelines include a more comprehensive range of risk factors and more finely graded blood pressure ranges to stratify patients by degree of risk. Whether they accurately predict CVD risk in most populations is not known. Evidence from the Valsartan Antihypertensive Long-term Use Evaluation (VALUE) study, which stratified patients by several risk and disease factors, highlights the predictive value of some newer CVD risk assessments. Modern risk assessments, which include blood pressure along with a wide array of modifiable risk factors, may be more accurate than classic models for CVD risk prediction.

Alternative research funding to improve clinical outcomes: model of prediction and prevention of sudden cardiac death.

PubMed

Myerburg, Robert J; Ullmann, Steven G

2015-04-01

Although identification and management of cardiovascular risk markers have provided important population risk insights and public health benefits, individual risk prediction remains challenging. Using sudden cardiac death risk as a base case, the complex epidemiology of sudden cardiac death risk and the substantial new funding required to study individual risk are explored. Complex epidemiology derives from the multiple subgroups having different denominators and risk profiles, while funding limitations emerge from saturation of conventional sources of research funding without foreseeable opportunities for increases. A resolution to this problem would have to emerge from new sources of funding targeted to individual risk prediction. In this analysis, we explore the possibility of a research funding strategy that would offer business incentives to the insurance industries, while providing support for unresolved research goals. The model is developed for the case of sudden cardiac death risk, but the concept is applicable to other areas of the medical enterprise. © 2015 American Heart Association, Inc.

[Communication on health and safety risk control in contemporary society: an interdisciplinary approach].

PubMed

Rangel-S, Maria Ligia

2007-01-01

This paper discusses communication as a technology for risk control with health and safety protection and promotion, within the context of a "risk society". As a component of Risk Analysis, risk communication is a technology that appears in risk literature, with well defined objectives, principles and models. These aspects are described and the difficulties are stressed, taking into consideration the multiple rationales related to risks in the culture and the many different aspects of risk regulation and control in the so-called "late modernity". Consideration is also given to the complexity of the communications process, guided by theoretical and methodological discussions in the field. In order to understand the true value of the communications field for risk control with health and safety protection and promotion, this paper also offers an overview of communication theories that support discussions of this matter, proposing a critical approach to models that include the dimensions of power and culture in the context of a capitalist society.

Gender Differences in Factors Related to HIV Risk Behaviors among People Who Inject Drugs in North-East India

PubMed Central

McFall, Allison M.; Solomon, Sunil S.; Srikrishnan, Aylur K.; Vasudevan, Canjeevaram K.; Anand, Santhanam; Celentano, David D.; Mehta, Shruti H.; Kumar, Suresh; Lucas, Gregory M.

2017-01-01

People who inject drugs (PWID) in India are at high risk for HIV, with women being at elevated risk. Using a socio-ecological framework, this study assessed whether factors associated with HIV transmission risk behaviors differed across men and women PWID. Data for this cross-sectional study were collected from 6449 PWID in 7 cities in Northeast India. Men (n = 5653) and women (n = 796) PWID were recruited using respondent-driven sampling (RDS). We assessed sex differences in two recent HIV transmission risk behaviors: multiple sex partners and needle/syringe sharing. We used multi-level logistic regression models, which incorporated sampling weights and random intercepts for city, to assess factors associated with these HIV risks, separately among men and women. The prevalence of HIV was significantly higher among women than men (53% vs 18.4%, p<0.01). Nearly 13% of men and 8% of women (p = .30) had multiple partners. Employment in men and relationship status and stigma in women were significantly associated with multiple partners. Approximately 25% of men and 19% of women engaged in needle sharing (p = .16). Younger age in women and depression symptoms in men were significantly associated with increased risk for sharing needles. We found that sexual and drug related risk behaviors were common among PWID in Northeast India, and there were differences between men and women in the socio-ecologic correlates of these behaviors. Contextually-integrated and gender-specific HIV prevention and intervention efforts are needed that consider factors at individual, interpersonal- and community-levels that uniquely impact HIV risks among PWID. PMID:28099458

Genetic modifiers of CHEK2*1100delC associated breast cancer risk

PubMed Central

Muranen, Taru A.; Greco, Dario; Blomqvist, Carl; Aittomäki, Kristiina; Khan, Sofia; Hogervorst, Frans; Verhoef, Senno; Pharoah, Paul D.P.; Dunning, Alison M.; Shah, Mitul; Luben, Robert; Bojesen, Stig E.; Nordestgaard, Børge G.; Schoemaker, Minouk; Swerdlow, Anthony; García-Closas, Montserrat; Figueroa, Jonine; Dörk, Thilo; Bogdanova, Natalia V.; Hall, Per; Li, Jingmei; Khusnutdinova, Elza; Bermisheva, Marina; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Peto, Julian; dos Santos Silva, Isabel; Couch, Fergus J.; Olson, Janet E.; Hillemans, Peter; Park-Simon, Tjoung-Won; Brauch, Hiltrud; Hamann, Ute; Burwinkel, Barbara; Marme, Frederik; Meindl, Alfons; Schmutzler, Rita K.; Cox, Angela; Cross, Simon S.; Sawyer, Elinor J.; Tomlinson, Ian; Lambrechts, Diether; Moisse, Matthieu; Lindblom, Annika; Margolin, Sara; Hollestelle, Antoinette; Martens, John W.M.; Fasching, Peter A.; Beckmann, Matthias W.; Andrulis, Irene L.; Knight, Julia A.; Anton-Culver, Hoda; Ziogas, Argyrios; Giles, Graham G.; Milne, Roger L.; Brenner, Hermann; Arndt, Volker; Mannermaa, Arto; Kosma, Veli-Matti; Chang-Claude, Jenny; Rudolph, Anja; Devilee, Peter; Seynaeve, Caroline; Hopper, John L.; Southey, Melissa C.; John, Esther M.; Whittemore, Alice S.; Bolla, Manjeet K.; Wang, Qin; Michailidou, Kyriaki; Dennis, Joe; Easton, Douglas F.; Schmidt, Marjanka K.; Nevanlinna, Heli

2016-01-01

Purpose CHEK2*1100delC is a founder variant in European populations conferring a 2–3 fold increased risk of breast cancer (BC). Epidemiologic and family studies have suggested that the risk associated with CHEK2*1100delC is modified by other genetic factors in a multiplicative fashion. We have investigated this empirically using data from the Breast Cancer Association Consortium (BCAC). Methods With genotype data of 39,139 (624 1100delC carriers) BC patients and 40,063 (224) healthy controls from 32 BCAC studies, we analyzed the combined risk effects of CHEK2*1100delC and 77 common variants in terms of a polygenic risk score (PRS) and pairwise interaction. Results The PRS conferred an odds ratio (OR) of 1.59 [95% CI 1.21–2.09] per standard deviation for BC for CHEK2*1100delC carriers and 1.58 [1.55–1.62] for non-carriers. No evidence for deviation from the multiplicative model was found. The OR for the highest quintile of the PRS was 2.03 [0.86–4.78] for CHEK2*1100delC carriers placing them to the high risk category according to UK NICE guidelines. OR for the lowest quintile was 0.52 [0.16–1.74], indicating life-time risk close to population average. Conclusion Our results confirm the multiplicative nature of risk effects conferred by CHEK2*1100delC and the common susceptibility variants. Furthermore, the PRS could identify the carriers at a high life-time risk for clinical actions. PMID:27711073

Genetic modifiers of CHEK2*1100delC-associated breast cancer risk.

PubMed

Muranen, Taru A; Greco, Dario; Blomqvist, Carl; Aittomäki, Kristiina; Khan, Sofia; Hogervorst, Frans; Verhoef, Senno; Pharoah, Paul D P; Dunning, Alison M; Shah, Mitul; Luben, Robert; Bojesen, Stig E; Nordestgaard, Børge G; Schoemaker, Minouk; Swerdlow, Anthony; García-Closas, Montserrat; Figueroa, Jonine; Dörk, Thilo; Bogdanova, Natalia V; Hall, Per; Li, Jingmei; Khusnutdinova, Elza; Bermisheva, Marina; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Investigators, Nbcs; Peto, Julian; Dos Santos Silva, Isabel; Couch, Fergus J; Olson, Janet E; Hillemans, Peter; Park-Simon, Tjoung-Won; Brauch, Hiltrud; Hamann, Ute; Burwinkel, Barbara; Marme, Frederik; Meindl, Alfons; Schmutzler, Rita K; Cox, Angela; Cross, Simon S; Sawyer, Elinor J; Tomlinson, Ian; Lambrechts, Diether; Moisse, Matthieu; Lindblom, Annika; Margolin, Sara; Hollestelle, Antoinette; Martens, John W M; Fasching, Peter A; Beckmann, Matthias W; Andrulis, Irene L; Knight, Julia A; Investigators, kConFab/Aocs; Anton-Culver, Hoda; Ziogas, Argyrios; Giles, Graham G; Milne, Roger L; Brenner, Hermann; Arndt, Volker; Mannermaa, Arto; Kosma, Veli-Matti; Chang-Claude, Jenny; Rudolph, Anja; Devilee, Peter; Seynaeve, Caroline; Hopper, John L; Southey, Melissa C; John, Esther M; Whittemore, Alice S; Bolla, Manjeet K; Wang, Qin; Michailidou, Kyriaki; Dennis, Joe; Easton, Douglas F; Schmidt, Marjanka K; Nevanlinna, Heli

2017-05-01

CHEK2*1100delC is a founder variant in European populations that confers a two- to threefold increased risk of breast cancer (BC). Epidemiologic and family studies have suggested that the risk associated with CHEK2*1100delC is modified by other genetic factors in a multiplicative fashion. We have investigated this empirically using data from the Breast Cancer Association Consortium (BCAC). Using genotype data from 39,139 (624 1100delC carriers) BC patients and 40,063 (224) healthy controls from 32 BCAC studies, we analyzed the combined risk effects of CHEK2*1100delC and 77 common variants in terms of a polygenic risk score (PRS) and pairwise interaction. The PRS conferred odds ratios (OR) of 1.59 (95% CI: 1.21-2.09) per standard deviation for BC for CHEK2*1100delC carriers and 1.58 (1.55-1.62) for noncarriers. No evidence of deviation from the multiplicative model was found. The OR for the highest quintile of the PRS was 2.03 (0.86-4.78) for CHEK2*1100delC carriers, placing them in the high risk category according to UK NICE guidelines. The OR for the lowest quintile was 0.52 (0.16-1.74), indicating a lifetime risk close to the population average. Our results confirm the multiplicative nature of risk effects conferred by CHEK2*1100delC and the common susceptibility variants. Furthermore, the PRS could identify carriers at a high lifetime risk for clinical actions.Genet Med advance online publication 06 October 2016.

Application of the two-stage clonal expansion model in characterizing the joint effect of exposure to two carcinogens

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

Zielinski, J.M.; Krewski, D.

1992-12-31

In this paper, we describe application of the two-stage clonal expansion model to characterize the joint effect of exposure to two carcinogens. This biologically based model of carcinogenesis provides a useful framework for the quantitative description of carcinogenic risks and for defining agents that act as initiators, promoters, and completers. Depending on the mechanism of action, the agent-specific relative risk following exposure to two carcinogens can be additive, multiplicative, or supramultiplicative, with supra-additive relative risk indicating a synergistic effect between the two agents. Maximum-likelihood methods for fitting the two-stage clonal expansion model with intermittent exposure to two carcinogens are describedmore » and illustrated, using data on lung-cancer mortality among Colorado uranium miners exposed to both radon and tobacco smoke.« less

Improving the evidence base for services working with youth at-risk of involvement in the criminal justice system: developing a standardised program approach.

PubMed

Knight, Alice; Maple, Myfanwy; Shakeshaft, Anthony; Shakehsaft, Bernie; Pearce, Tania

2018-04-16

Young people who engage in multiple risk behaviour (high-risk young people) such as substance abuse, antisocial behaviour, low engagement in education and employment, self-harm or suicide ideation are more likely to experience serious harms later in life including homelessness, incarceration, violence and premature death. In addition to personal disadvantage, these harms represent an avoidable social and economic cost to society. Despite these harms, there is insufficient evidence about how to improve outcomes for high-risk young people. A key reason for this is a lack of standardisation in the way in which programs provided by services are defined and evaluated. This paper describes the development of a standardised intervention model for high-risk young people. The model can be used by service providers to achieve greater standardisation across their programs, outcomes and outcome measures. To demonstrate its feasibility, the model is applied to an existing program for high-risk young people. The development and uptake of a standardised intervention model for these programs will help to more rapidly develop a larger and more rigorous evidence-base to improve outcomes for high-risk young people.

Consumption of artificial sweetener– and sugar-containing soda and risk of lymphoma and leukemia in men and women1234

PubMed Central

Schernhammer, Eva S; Bertrand, Kimberly A; Birmann, Brenda M; Sampson, Laura; Willett, Walter C; Feskanich, Diane

2012-01-01

Background: Despite safety reports of the artificial sweetener aspartame, health-related concerns remain. Objective: We prospectively evaluated whether the consumption of aspartame- and sugar-containing soda is associated with risk of hematopoetic cancers. Design: We repeatedly assessed diet in the Nurses’ Health Study (NHS) and Health Professionals Follow-Up Study (HPFS). Over 22 y, we identified 1324 non-Hodgkin lymphomas (NHLs), 285 multiple myelomas, and 339 leukemias. We calculated incidence RRs and 95% CIs by using Cox proportional hazards models. Results: When the 2 cohorts were combined, there was no significant association between soda intake and risks of NHL and multiple myeloma. However, in men, ≥1 daily serving of diet soda increased risks of NHL (RR: 1.31; 95% CI: 1.01, 1.72) and multiple myeloma (RR: 2.02; 95% CI: 1.20, 3.40) in comparison with men who did not consume diet soda. We observed no increased risks of NHL and multiple myeloma in women. We also observed an unexpected elevated risk of NHL (RR: 1.66; 95% CI: 1.10, 2.51) with a higher consumption of regular, sugar-sweetened soda in men but not in women. In contrast, when sexes were analyzed separately with limited power, neither regular nor diet soda increased risk of leukemia but were associated with increased leukemia risk when data for men and women were combined (RR for consumption of ≥1 serving of diet soda/d when the 2 cohorts were pooled: 1.42; 95% CI: 1.00, 2.02). Conclusion: Although our findings preserve the possibility of a detrimental effect of a constituent of diet soda, such as aspartame, on select cancers, the inconsistent sex effects and occurrence of an apparent cancer risk in individuals who consume regular soda do not permit the ruling out of chance as an explanation. PMID:23097267

Consumption of artificial sweetener- and sugar-containing soda and risk of lymphoma and leukemia in men and women.

PubMed

Schernhammer, Eva S; Bertrand, Kimberly A; Birmann, Brenda M; Sampson, Laura; Willett, Walter C; Feskanich, Diane

2012-12-01

Despite safety reports of the artificial sweetener aspartame, health-related concerns remain. We prospectively evaluated whether the consumption of aspartame- and sugar-containing soda is associated with risk of hematopoetic cancers. We repeatedly assessed diet in the Nurses' Health Study (NHS) and Health Professionals Follow-Up Study (HPFS). Over 22 y, we identified 1324 non-Hodgkin lymphomas (NHLs), 285 multiple myelomas, and 339 leukemias. We calculated incidence RRs and 95% CIs by using Cox proportional hazards models. When the 2 cohorts were combined, there was no significant association between soda intake and risks of NHL and multiple myeloma. However, in men, ≥1 daily serving of diet soda increased risks of NHL (RR: 1.31; 95% CI: 1.01, 1.72) and multiple myeloma (RR: 2.02; 95% CI: 1.20, 3.40) in comparison with men who did not consume diet soda. We observed no increased risks of NHL and multiple myeloma in women. We also observed an unexpected elevated risk of NHL (RR: 1.66; 95% CI: 1.10, 2.51) with a higher consumption of regular, sugar-sweetened soda in men but not in women. In contrast, when sexes were analyzed separately with limited power, neither regular nor diet soda increased risk of leukemia but were associated with increased leukemia risk when data for men and women were combined (RR for consumption of ≥1 serving of diet soda/d when the 2 cohorts were pooled: 1.42; 95% CI: 1.00, 2.02). Although our findings preserve the possibility of a detrimental effect of a constituent of diet soda, such as aspartame, on select cancers, the inconsistent sex effects and occurrence of an apparent cancer risk in individuals who consume regular soda do not permit the ruling out of chance as an explanation.

Scenario-based modeling for multiple allocation hub location problem under disruption risk: multiple cuts Benders decomposition approach

NASA Astrophysics Data System (ADS)

Yahyaei, Mohsen; Bashiri, Mahdi

2017-12-01

The hub location problem arises in a variety of domains such as transportation and telecommunication systems. In many real-world situations, hub facilities are subject to disruption. This paper deals with the multiple allocation hub location problem in the presence of facilities failure. To model the problem, a two-stage stochastic formulation is developed. In the proposed model, the number of scenarios grows exponentially with the number of facilities. To alleviate this issue, two approaches are applied simultaneously. The first approach is to apply sample average approximation to approximate the two stochastic problem via sampling. Then, by applying the multiple cuts Benders decomposition approach, computational performance is enhanced. Numerical studies show the effective performance of the SAA in terms of optimality gap for small problem instances with numerous scenarios. Moreover, performance of multi-cut Benders decomposition is assessed through comparison with the classic version and the computational results reveal the superiority of the multi-cut approach regarding the computational time and number of iterations.

Traffic, Air Pollution, Minority and Socio-Economic Status: Addressing Inequities in Exposure and Risk

PubMed Central

Pratt, Gregory C.; Vadali, Monika L.; Kvale, Dorian L.; Ellickson, Kristie M.

2015-01-01

Higher levels of nearby traffic increase exposure to air pollution and adversely affect health outcomes. Populations with lower socio-economic status (SES) are particularly vulnerable to stressors like air pollution. We investigated cumulative exposures and risks from traffic and from MNRiskS-modeled air pollution in multiple source categories across demographic groups. Exposures and risks, especially from on-road sources, were higher than the mean for minorities and low SES populations and lower than the mean for white and high SES populations. Owning multiple vehicles and driving alone were linked to lower household exposures and risks. Those not owning a vehicle and walking or using transit had higher household exposures and risks. These results confirm for our study location that populations on the lower end of the socio-economic spectrum and minorities are disproportionately exposed to traffic and air pollution and at higher risk for adverse health outcomes. A major source of disparities appears to be the transportation infrastructure. Those outside the urban core had lower risks but drove more, while those living nearer the urban core tended to drive less but had higher exposures and risks from on-road sources. We suggest policy considerations for addressing these inequities. PMID:25996888

Modeling life course pathways from adverse childhood experiences to adult mental health.

PubMed

Jones, Tiffany M; Nurius, Paula; Song, Chiho; Fleming, Christopher M

2018-06-01

Although the association between adverse childhood experiences (ACEs) and adult mental health is becoming well established, less is known about the complex and multiple pathways through which ACEs exert their influence. Growing evidence suggests that adversity early in life conveys not only early impacts, but also augments risk of stress-related life course cascades that continue to undermine health. The present study aims to test pathways of stress proliferation and stress embodiment processes linking ACEs to mental health impairment in adulthood. Data are from the 2011 Behavioral Risk Factor Surveillance Survey, a representative sample of Washington State adults ages 18 and over (N = 14,001). Structural equation modeling allowed for testing of direct and indirect effects from ACEs though low income status, experiences of adversity in adulthood, and social support. The model demonstrated that adult low income, social support and adult adversity are in fact conduits through which ACEs exert their influence on mental health impairment in adulthood. Significant indirect pathways through these variables supported hypotheses that the effect of ACEs is carried through these variables. This is among the first models that demonstrates multiple stress-related life course pathways through which early life adversity compromises adult mental health. Discussion elaborates multiple service system opportunities for intervention in early and later life to interrupt direct and indirect pathways of ACE effects. Copyright © 2018 Elsevier Ltd. All rights reserved.

Monte Carlo mixture model of lifetime cancer incidence risk from radiation exposure on shuttle and international space station

NASA Technical Reports Server (NTRS)

Peterson, L. E.; Cucinotta, F. A.; Wilson, J. W. (Principal Investigator)

1999-01-01

Estimating uncertainty in lifetime cancer risk for human exposure to space radiation is a unique challenge. Conventional risk assessment with low-linear-energy-transfer (LET)-based risk from Japanese atomic bomb survivor studies may be inappropriate for relativistic protons and nuclei in space due to track structure effects. This paper develops a Monte Carlo mixture model (MCMM) for transferring additive, National Institutes of Health multiplicative, and multiplicative excess cancer incidence risks based on Japanese atomic bomb survivor data to determine excess incidence risk for various US astronaut exposure profiles. The MCMM serves as an anchor point for future risk projection methods involving biophysical models of DNA damage from space radiation. Lifetime incidence risks of radiation-induced cancer for the MCMM based on low-LET Japanese data for nonleukemia (all cancers except leukemia) were 2.77 (90% confidence limit, 0.75-11.34) for males exposed to 1 Sv at age 45 and 2.20 (90% confidence limit, 0.59-10.12) for males exposed at age 55. For females, mixture model risks for nonleukemia exposed separately to 1 Sv at ages of 45 and 55 were 2.98 (90% confidence limit, 0.90-11.70) and 2.44 (90% confidence limit, 0.70-10.30), respectively. Risks for high-LET 200 MeV protons (LET=0.45 keV/micrometer), 1 MeV alpha-particles (LET=100 keV/micrometer), and 600 MeV iron particles (LET=180 keV/micrometer) were scored on a per particle basis by determining the particle fluence required for an average of one particle per cell nucleus of area 100 micrometer(2). Lifetime risk per proton was 2.68x10(-2)% (90% confidence limit, 0.79x10(-3)%-0. 514x10(-2)%). For alpha-particles, lifetime risk was 14.2% (90% confidence limit, 2.5%-31.2%). Conversely, lifetime risk per iron particle was 23.7% (90% confidence limit, 4.5%-53.0%). Uncertainty in the DDREF for high-LET particles may be less than that for low-LET radiation because typically there is very little dose-rate dependence. Probability density functions for high-LET radiation quality and dose-rate may be preferable to conventional risk assessment approaches. Nuclear reactions and track structure effects in tissue may not be properly estimated by existing data using in vitro models for estimating RBEs. The method used here is being extended to estimate uncertainty in spacecraft shielding effectiveness in various space radiation environments.

Assessing the Effect of Spaceflight on the Propensity for Astronauts to Develop Disc Herniation

NASA Technical Reports Server (NTRS)

Feiveson, A.; Mendez, C.; Somers, J.

2015-01-01

A previous study reported that the instantaneous risk of developing a Herniated Nucleus Pulposus (HNP) was higher in astronauts who had flown at least one mission, as compared with those in the corps who had not yet flown. However, the study only analyzed time to HNP after the first mission (if any) and did not account for the possible effects of multiple missions. While many HNPs occurred well into astronauts' careers or in somecases years after retirement, the higher incidence of HNPs relatively soon after completion of space missions appears to indicate that spaceflight may lead to an increased risk of HNP. In addition, when an HNP occurs after spaceflight, is it related to previous spaceflight exposure? The purpose of this study was to investigate whether multiple missions, sex, age, vehicle landing dynamics, and flight duration affect the risk of developing an HNP usinga competing risks model. The outcome of the study will inform the Human System Risk Board assessment of back pain, inform the risk of injury due to dynamic loads, and update the previous dataset, which contained events up to December 31, 2006.

Exposure to Pre- and Perinatal Risk Factors Partially Explains Mean Differences in Self-Regulation between Races.

PubMed

Barnes, J C; Boutwell, Brian B; Miller, J Mitchell; DeShay, Rashaan A; Beaver, Kevin M; White, Norman

2016-01-01

To examine whether differential exposure to pre- and perinatal risk factors explained differences in levels of self-regulation between children of different races (White, Black, Hispanic, Asian, and Other). Multiple regression models based on data from the Early Childhood Longitudinal Study, Birth Cohort (n ≈ 9,850) were used to analyze the impact of pre- and perinatal risk factors on the development of self-regulation at age 2 years. Racial differences in levels of self-regulation were observed. Racial differences were also observed for 9 of the 12 pre-/perinatal risk factors. Multiple regression analyses revealed that a portion of the racial differences in self-regulation was explained by differential exposure to several of the pre-/perinatal risk factors. Specifically, maternal age at childbirth, gestational timing, and the family's socioeconomic status were significantly related to the child's level of self-regulation. These factors accounted for a statistically significant portion of the racial differences observed in self-regulation. The findings indicate racial differences in self-regulation may be, at least partially, explained by racial differences in exposure to pre- and perinatal risk factors.

Elevated risk of adverse obstetric outcomes in pregnant women with depression.

PubMed

Kim, Deborah R; Sockol, Laura E; Sammel, Mary D; Kelly, Caroline; Moseley, Marian; Epperson, C Neill

2013-12-01

In this study, we evaluated the association between prenatal depression symptoms adverse birth outcomes in African-American women. We conducted a retrospective cohort study of 261 pregnant African-American women who were screened with the Edinburgh Postnatal Depression Scale (EPDS) at their initial prenatal visit. Medical records were reviewed to assess pregnancy and neonatal outcomes, specifically preeclampsia, preterm birth, intrauterine growth retardation, and low birth weight. Using multivariable logistic regression models, an EPDS score ≥10 was associated with increased risk for preeclampsia, preterm birth, and low birth weight. An EPDS score ≥10 was associated with increased risk for intrauterine growth retardation, but after controlling for behavioral risk factors, this association was no longer significant. Patients who screen positive for depression symptoms during pregnancy are at increased risk for multiple adverse birth outcomes. In a positive, patient-rated depression screening at the initial obstetrics visit, depression is associated with increased risk for multiple adverse birth outcomes. Given the retrospective study design and small sample size, these findings should be confirmed in a prospective cohort study.

A Bayesian Approach to Integrated Ecological and Human Health Risk Assessment for the South River, Virginia Mercury-Contaminated Site.

PubMed

Harris, Meagan J; Stinson, Jonah; Landis, Wayne G

2017-07-01

We conducted a regional-scale integrated ecological and human health risk assessment by applying the relative risk model with Bayesian networks (BN-RRM) to a case study of the South River, Virginia mercury-contaminated site. Risk to four ecological services of the South River (human health, water quality, recreation, and the recreational fishery) was evaluated using a multiple stressor-multiple endpoint approach. These four ecological services were selected as endpoints based on stakeholder feedback and prioritized management goals for the river. The BN-RRM approach allowed for the calculation of relative risk to 14 biotic, human health, recreation, and water quality endpoints from chemical and ecological stressors in five risk regions of the South River. Results indicated that water quality and the recreational fishery were the ecological services at highest risk in the South River. Human health risk for users of the South River was low relative to the risk to other endpoints. Risk to recreation in the South River was moderate with little spatial variability among the five risk regions. Sensitivity and uncertainty analysis identified stressors and other parameters that influence risk for each endpoint in each risk region. This research demonstrates a probabilistic approach to integrated ecological and human health risk assessment that considers the effects of chemical and ecological stressors across the landscape. © 2017 Society for Risk Analysis.

Creating Resilient Children and Empowering Families Using a Multifamily Group Process.

ERIC Educational Resources Information Center

Sayger, Thomas V.

1996-01-01

Presents a model for prevention and early intervention using a multifamily group counseling process to increase the resiliency of children and to empower families living with multiple stressors in high-risk environments. (Author)

Analysis of potential factors affecting microbiological cultures in tissue donors during procurement.

PubMed

Lannau, B; Van Geyt, C; Van Maele, G; Beele, H

2015-03-01

During the procurement of musculoskeletal grafts contamination may occur. As this might be detrimental for the acceptor, it is important to know which variables influence this occurrence and to alter procurement protocols accordingly. From 2004 to 2012 we gathered information on 6,428 allografts obtained from 291 donors. Using a multiple regression model we attempted to determine the factors that influence the contamination risk during procurement. We used the following variables: cause of death, type of hospital (i.e. university hospital vs. general hospital), previous blood vessel donation, previous organ donation, donor age, time between death and the start of the procurement, duration of the procurement, number of people attending the procurement and the number of procured grafts. The multiple regression model was only able to explain 5 % of the variability of the used outcome variable. None of the variables examined appear to have an important influence on the contamination risk.

A Practical Approach to Address Uncertainty in Stakeholder Deliberations.

PubMed

Gregory, Robin; Keeney, Ralph L

2017-03-01

This article addresses the difficulties of incorporating uncertainty about consequence estimates as part of stakeholder deliberations involving multiple alternatives. Although every prediction of future consequences necessarily involves uncertainty, a large gap exists between common practices for addressing uncertainty in stakeholder deliberations and the procedures of prescriptive decision-aiding models advanced by risk and decision analysts. We review the treatment of uncertainty at four main phases of the deliberative process: with experts asked to describe possible consequences of competing alternatives, with stakeholders who function both as individuals and as members of coalitions, with the stakeholder committee composed of all stakeholders, and with decisionmakers. We develop and recommend a model that uses certainty equivalents as a theoretically robust and practical approach for helping diverse stakeholders to incorporate uncertainties when evaluating multiple-objective alternatives as part of public policy decisions. © 2017 Society for Risk Analysis.

Risk factors for antepartum fetal death.

PubMed

Oron, T; Sheiner, E; Shoham-Vardi, I; Mazor, M; Katz, M; Hallak, M

2001-09-01

To determine the demographic, maternal, pregnancy-related and fetal risk factors for antepartum fetal death (APFD). From our perinatal database between the years 1990 and 1997, 68,870 singleton birth files were analyzed. Fetuses weighing < 1,000 g at birth and those with structural malformations and/or known chromosomal anomalies were excluded from the study. In order to determine independent factors contributing to APFD, a multiple logistic regression model was constructed. During the study period there were 246 cases of APFD (3.6 per 1,000 births). The following obstetric factors significantly correlated with APFD in a multiple logistic regression model: preterm deliveries: small size for gestational age (SGA), multiparity (> 5 deliveries), oligohydramnios, placental abruption, umbilical cord complications (cord around the neck and true knot of cord), pathologic presentations (nonvertex) and meconium-stained amniotic fluid. APFD was not significantly associated with advanced maternal age. APFD was significantly associated with several risk factors. Placental and umbilical cord pathologies might be the direct cause of death. Grand multiparity, oligohydramnios, meconium-stained amniotic fluid, pathologic presentations and suspected SGA should be carefully evaluated during pregnancy in order to decrease the incidence of APFD.

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.

A Multilevel Model of Child- and Classroom-Level Psychosocial Factors that Support Language and Literacy Resilience of Children in Head Start

ERIC Educational Resources Information Center

Maier, Michelle F.; Vitiello, Virginia E.; Greenfield, Daryl B.

2012-01-01

Early exposure to the multiple risk factors associated with poverty is related to an elevated risk for academic difficulty. Therefore, it is important to promote academic resilience as early as possible and to identify factors that support resilience. Given the positive relation between early language skills and later academic outcomes, examining…

Longitudinal patterns and predictors of multiple health risk behaviors among adolescents: The TRAILS study.

PubMed

de Winter, Andrea F; Visser, Leenke; Verhulst, Frank C; Vollebergh, Wilma A M; Reijneveld, Sijmen A

2016-03-01

Most studies on multiple health risk behaviors among adolescents have cross-sectionally studied a limited number of health behaviors or determinants. To examine the prevalence, longitudinal patterns and predictors of individual and multiple health risk behaviors among adolescents. Eight health risk behaviors (no regular consumption of fruit, vegetables or breakfast, overweight or obesity, physical inactivity, smoking, alcohol use and cannabis use) were assessed in a prospective population study (second and third wave). Participants were assessed in three waves between ages 10 and 17 (2001-2008; n=2230). Multiple linear regression was used to assess the influence of gender, self-control, parental health risk behaviors, parental monitoring and socioeconomic factors on the number of health risk behaviors adjusted for preceding multiple health risk behaviors (analysis: 2013-2014). Rates of >5 health risk behaviors were high: 3.6% at age 13.5 and 10.2% at age 16. Smoking at age 13.5 was frequently associated with health risk behaviors at age 16. No regular consumption of fruit, vegetables and breakfast, overweight or obesity, physical inactivity and smoking predicted the co-occurrence of health risk behaviors at follow-up. Significant predictors of the development of multiple health risk behaviors were adolescents' levels of self-control, socioeconomic status and maternal smoking. Multiple health risk behaviors are common among adolescents. Individual and social factors predict changes in multiple health risk behaviors, showing that prevention targeting multiple risk behaviors is needed. Special attention should be paid to adolescents with low self-control and families with low socioeconomic status or a mother who smokes. Copyright © 2015 Elsevier Inc. All rights reserved.

Exploration Systems Development (ESD) Approach to Enterprise Risk Management

NASA Technical Reports Server (NTRS)

Bauder, Stephen P.

2014-01-01

The National Aeronautics and Space Administration (NASA) Exploration Systems Development (ESD) Division has implemented an innovative approach to Enterprise Risk Management under a unique governance structure and streamlined integration model. ESD's mission is to design and build the capability to extend human existence to deep space. The Enterprise consists of three Programs: Space Launch System (SLS), Orion, and Ground Systems Development and Operations (GSDO). The SLS is a rocket and launch system that will be capable of powering humans, habitats, and support systems to deep space. Orion will be the first spacecraft in history capable of taking humans to multiple destinations within deep space. GSDO is modernizing Kennedy's spaceport to launch spacecraft built and designed by both NASA and private industry. ESD's approach to Enterprise Risk Management is commensurate with affordability and a streamlined management philosophy. ESD Enterprise Risk Management leverages off of the primary mechanisms for integration within the Enterprise. The Enterprise integration approach emphasizes delegation of authority to manage and execute the majority of cross-program activities and products to the individual Programs, while maintaining the overall responsibility for all cross-program activities at the Division. The intent of the ESD Enterprise Risk Management approach is to improve risk communication, to avoid replication and/or contradictory strategies, and to minimize overhead process burden. This is accomplished by the facilitation and integration of risk information within ESD. The ESD Division risks, Orion risks, SLS risks, and GSDO risks are owned and managed by the applicable Program. When the Programs have shared risks with multiple consequences, they are jointly owned and managed. When a risk is associated with the integrated system that involves more than one Program in condition, consequence, or mitigation plan, it is considered an Exploration Systems Integration (ESI) Risk. An ESI risk may require visibility and risk handling by multiple organizations. The Integrated Risk Working Group (IRWG) is a small team of Risk experts that are responsible for collaborating and communicating best practices. In addition, the forum facilitates proper integration of risks across the Enterprise. The IRWG uses a Continuous Risk Management approach for facilitating the identification, analysis, planning, tracking, and controlling of ESI Risks. The ESD Division, Programs, and Integrated Task Teams identify ESI Risks. The IRWG maintains a set of metrics for understanding Enterprise Risk process and the overall Risk Posture. The team is also actively involved in the modeling of risk for Enterprise Performance Management. With the Enterprise being constrained in Schedule and Budget, and with significant technical complexity, the appropriate use of Risk Management techniques is crucial to the success of the Enterprise. The IRWG achieves this through the modified approach, providing a forum for collaboration on risks that cross boundaries between the separate entities.

Utility of existing diabetes risk prediction tools for young black and white adults: Evidence from the Bogalusa Heart Study.

PubMed

Pollock, Benjamin D; Hu, Tian; Chen, Wei; Harville, Emily W; Li, Shengxu; Webber, Larry S; Fonseca, Vivian; Bazzano, Lydia A

2017-01-01

To evaluate several adult diabetes risk calculation tools for predicting the development of incident diabetes and pre-diabetes in a bi-racial, young adult population. Surveys beginning in young adulthood (baseline age ≥18) and continuing across multiple decades for 2122 participants of the Bogalusa Heart Study were used to test the associations of five well-known adult diabetes risk scores with incident diabetes and pre-diabetes using separate Cox models for each risk score. Racial differences were tested within each model. Predictive utility and discrimination were determined for each risk score using the Net Reclassification Index (NRI) and Harrell's c-statistic. All risk scores were strongly associated (p<.0001) with incident diabetes and pre-diabetes. The Wilson model indicated greater risk of diabetes for blacks versus whites with equivalent risk scores (HR=1.59; 95% CI 1.11-2.28; p=.01). C-statistics for the diabetes risk models ranged from 0.79 to 0.83. Non-event NRIs indicated high specificity (non-event NRIs: 76%-88%), but poor sensitivity (event NRIs: -23% to -3%). Five diabetes risk scores established in middle-aged, racially homogenous adult populations are generally applicable to younger adults with good specificity but poor sensitivity. The addition of race to these models did not result in greater predictive capabilities. A more sensitive risk score to predict diabetes in younger adults is needed. Copyright © 2017 Elsevier Inc. All rights reserved.

Caries risk assessment in schoolchildren - a form based on Cariogram® software

PubMed Central

CABRAL, Renata Nunes; HILGERT, Leandro Augusto; FABER, Jorge; LEAL, Soraya Coelho

2014-01-01

Identifying caries risk factors is an important measure which contributes to best understanding of the cariogenic profile of the patient. The Cariogram® software provides this analysis, and protocols simplifying the method were suggested. Objectives The aim of this study was to determine whether a newly developed Caries Risk Assessment (CRA) form based on the Cariogram® software could classify schoolchildren according to their caries risk and to evaluate relationships between caries risk and the variables in the form. Material and Methods 150 schoolchildren aged 5 to 7 years old were included in this survey. Caries prevalence was obtained according to International Caries Detection and Assessment System (ICDAS) II. Information for filling in the form based on Cariogram® was collected clinically and from questionnaires sent to parents. Linear regression and a forward stepwise multiple regression model were applied to correlate the variables included in the form with the caries risk. Results Caries prevalence, in primary dentition, including enamel and dentine carious lesions was 98.6%, and 77.3% when only dentine lesions were considered. Eighty-six percent of the children were classified as at moderate caries risk. The forward stepwise multiple regression model result was significant (R2=0.904; p<0.00001), showing that the most significant factors influencing caries risk were caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources. Conclusion The use of the form based on the Cariogram® software enabled classification of the schoolchildren at low, moderate and high caries risk. Caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources are the variables that were shown to be highly correlated with caries risk. PMID:25466473

DNA repair variants and breast cancer risk.

PubMed

Grundy, Anne; Richardson, Harriet; Schuetz, Johanna M; Burstyn, Igor; Spinelli, John J; Brooks-Wilson, Angela; Aronson, Kristan J

2016-05-01

A functional DNA repair system has been identified as important in the prevention of tumour development. Previous studies have hypothesized that common polymorphisms in DNA repair genes could play a role in breast cancer risk and also identified the potential for interactions between these polymorphisms and established breast cancer risk factors such as physical activity. Associations with breast cancer risk for 99 single nucleotide polymorphisms (SNPs) from genes in ten DNA repair pathways were examined in a case-control study including both Europeans (644 cases, 809 controls) and East Asians (299 cases, 160 controls). Odds ratios in both additive and dominant genetic models were calculated separately for participants of European and East Asian ancestry using multivariate logistic regression. The impact of multiple comparisons was assessed by correcting for the false discovery rate within each DNA repair pathway. Interactions between several breast cancer risk factors and DNA repair SNPs were also evaluated. One SNP (rs3213282) in the gene XRCC1 was associated with an increased risk of breast cancer in the dominant model of inheritance following adjustment for the false discovery rate (P < 0.05), although no associations were observed for other DNA repair SNPs. Interactions of six SNPs in multiple DNA repair pathways with physical activity were evident prior to correction for FDR, following which there was support for only one of the interaction terms (P < 0.05). No consistent associations between variants in DNA repair genes and breast cancer risk or their modification by breast cancer risk factors were observed. © 2016 Wiley Periodicals, Inc.

Novice drivers' risky driving behavior, risk perception, and crash risk: findings from the DRIVE study.

PubMed

Ivers, Rebecca; Senserrick, Teresa; Boufous, Soufiane; Stevenson, Mark; Chen, Huei-Yang; Woodward, Mark; Norton, Robyn

2009-09-01

We explored the risky driving behaviors and risk perceptions of a cohort of young novice drivers and sought to determine their associations with crash risk. Provisional drivers aged 17 to 24 (n = 20 822) completed a detailed questionnaire that included measures of risk perception and behaviors; 2 years following recruitment, survey data were linked to licensing and police-reported crash data. Poisson regression models that adjusted for multiple confounders were created to explore crash risk. High scores on questionnaire items for risky driving were associated with a 50% increased crash risk (adjusted relative risk = 1.51; 95% confidence interval = 1.25, 1.81). High scores for risk perception (poorer perceptions of safety) were also associated with increased crash risk in univariate and multivariate models; however, significance was not sustained after adjustment for risky driving. The overrepresentation of youths in crashes involving casualties is a significant public health issue. Risky driving behavior is strongly linked to crash risk among young drivers and overrides the importance of risk perceptions. Systemwide intervention, including licensing reform, is warranted.

A risk-based decision support framework for selection of appropriate safety measure system for underground coal mines.

PubMed

Samantra, Chitrasen; Datta, Saurav; Mahapatra, Siba Sankar

2017-03-01

In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.

Development of a Risk-Based Comparison Methodology of Carbon Capture Technologies

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

Engel, David W.; Dalton, Angela C.; Dale, Crystal

2014-06-01

Given the varying degrees of maturity among existing carbon capture (CC) technology alternatives, an understanding of the inherent technical and financial risk and uncertainty associated with these competing technologies is requisite to the success of carbon capture as a viable solution to the greenhouse gas emission challenge. The availability of tools and capabilities to conduct rigorous, risk–based technology comparisons is thus highly desirable for directing valuable resources toward the technology option(s) with a high return on investment, superior carbon capture performance, and minimum risk. To address this research need, we introduce a novel risk-based technology comparison method supported by anmore » integrated multi-domain risk model set to estimate risks related to technological maturity, technical performance, and profitability. Through a comparison between solid sorbent and liquid solvent systems, we illustrate the feasibility of estimating risk and quantifying uncertainty in a single domain (modular analytical capability) as well as across multiple risk dimensions (coupled analytical capability) for comparison. This method brings technological maturity and performance to bear on profitability projections, and carries risk and uncertainty modeling across domains via inter-model sharing of parameters, distributions, and input/output. The integration of the models facilitates multidimensional technology comparisons within a common probabilistic risk analysis framework. This approach and model set can equip potential technology adopters with the necessary computational capabilities to make risk-informed decisions about CC technology investment. The method and modeling effort can also be extended to other industries where robust tools and analytical capabilities are currently lacking for evaluating nascent technologies.« less

Predicting the Influence of Situational and Immigration Stress on Latino Day Laborers' Workplace Injuries: An Exploratory Structural Equation Model.

PubMed

Fernández-Esquer, Maria Eugenia; Gallardo, Kathryn R; Diamond, Pamela M

2018-05-16

Latino day laborers are a socially and economically marginalized immigrant population with a high risk of occupational injury. These workers confront multiple social, psychological, and environmental hardships that increase their risk for adverse health outcomes. How these stressors interact and influence work-related injuries in this population remains unclear. We conducted an exploratory study with 327 Latino day laborers who completed a community survey. We developed a structural equation model, using cross-sectional data to explore the relationships among socioeconomic status, situational and immigration stress, depression, work risk exposure, and occupational injury. The model revealed a statistically significant mediated effect from situational stress to injury through work risk exposure as well as a significant mediated effect from immigration stress through depression to injury. These initial findings suggest that situational and immigration-related stress have a detrimental impact on Latino day laborers' mental health and workplace safety and, ultimately, increase their risk of occupational injury.

Development of a statistical oil spill model for risk assessment.

PubMed

Guo, Weijun

2017-11-01

To gain a better understanding of the impacts from potential risk sources, we developed an oil spill model using probabilistic method, which simulates numerous oil spill trajectories under varying environmental conditions. The statistical results were quantified from hypothetical oil spills under multiple scenarios, including area affected probability, mean oil slick thickness, and duration of water surface exposed to floating oil. The three sub-indices together with marine area vulnerability are merged to compute the composite index, characterizing the spatial distribution of risk degree. Integral of the index can be used to identify the overall risk from an emission source. The developed model has been successfully applied in comparison to and selection of an appropriate oil port construction location adjacent to a marine protected area for Phoca largha in China. The results highlight the importance of selection of candidates before project construction, since that risk estimation from two adjacent potential sources may turn out to be significantly different regarding hydrodynamic conditions and eco-environmental sensitivity. Copyright © 2017. Published by Elsevier Ltd.

Unmetabolized Folic Acid, Tetrahydrofolate, and Colorectal Adenoma Risk.

PubMed

Rees, Judy R; Morris, Carolyn B; Peacock, Janet L; Ueland, Per M; Barry, Elizabeth L; McKeown-Eyssen, Gail E; Figueiredo, Jane C; Snover, Dale C; Baron, John A

2017-08-01

In a randomized trial of folic acid supplementation for the prevention of colorectal adenomas, we previously found indications of increased risk during later treatment and follow-up. This could have been due to the unmetabolized folic acid (UFA) or natural reduced and methylated folates (mF) to which it is metabolized. In post hoc analyses, we measured mF (the sum of 5-methyl-tetrahydrofolate and 4-alfa-hydroxy-5-methyl-THF) and UFA concentrations in the serum of 924 participants. Using binomial regression models with a log link, we assessed the associations between plasma mF or UFA and adenoma occurrence. We found no association between plasma mF or UFA and overall adenoma risk. However, during later follow-up, the prespecified, composite endpoint of high-risk findings (advanced or multiple adenomas) was positively associated with plasma mF ( P linear trend = 0.009), with a 58% increased risk for participants in the upper versus lowest quartile. An irregular association was seen with plasma UFA, with suggestions of an inverse trend ( P linear trend =0.049). A modest, significant inverse association was also seen between mF and risk of serrated lesions, with a 39% lower risk for upper versus lower quartile participants ( P linear trend = 0.03). In conclusion, during the later follow-up period in which folic acid supplementation was previously seen to increase the risk of advanced and multiple adenomas, higher serum mF was associated with a higher risk of multiple and/or advanced adenomas, but no clear indication that UFA played a direct role. There were indications that higher mF was associated with reduced risk of serrated polyps. Cancer Prev Res; 10(8); 451-8. ©2017 AACR . ©2017 American Association for Cancer Research.

System Dynamics Modeling for Public Health: Background and Opportunities

PubMed Central

Homer, Jack B.; Hirsch, Gary B.

2006-01-01

The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591

A multiple deficit model of reading disability and attention-deficit/hyperactivity disorder: searching for shared cognitive deficits.

PubMed

McGrath, Lauren M; Pennington, Bruce F; Shanahan, Michelle A; Santerre-Lemmon, Laura E; Barnard, Holly D; Willcutt, Erik G; Defries, John C; Olson, Richard K

2011-05-01

This study tests a multiple cognitive deficit model of reading disability (RD), attention-deficit/hyperactivity disorder (ADHD), and their comorbidity. A structural equation model (SEM) of multiple cognitive risk factors and symptom outcome variables was constructed. The model included phonological awareness as a unique predictor of RD and response inhibition as a unique predictor of ADHD. Processing speed, naming speed, and verbal working memory were modeled as potential shared cognitive deficits. Model fit indices from the SEM indicated satisfactory fit. Closer inspection of the path weights revealed that processing speed was the only cognitive variable with significant unique relationships to RD and ADHD dimensions, particularly inattention. Moreover, the significant correlation between reading and inattention was reduced to non-significance when processing speed was included in the model, suggesting that processing speed primarily accounted for the phenotypic correlation (or comorbidity) between reading and inattention. This study illustrates the power of a multiple deficit approach to complex developmental disorders and psychopathologies, particularly for exploring comorbidities. The theoretical role of processing speed in the developmental pathways of RD and ADHD and directions for future research are discussed. © 2010 The Authors. Journal of Child Psychology and Psychiatry © 2010 Association for Child and Adolescent Mental Health.

RTEL1 and TERT polymorphisms are associated with astrocytoma risk in the Chinese Han population.

PubMed

Jin, Tian-Bo; Zhang, Jia-Yi; Li, Gang; Du, Shu-Li; Geng, Ting-Ting; Gao, Jing; Liu, Qian-Ping; Gao, Guo-Dong; Kang, Long-Li; Chen, Chao; Li, Shan-Qu

2013-12-01

Common variants of multiple genes play a role in glioma onset. However, research related to astrocytoma, the most common primary brain neoplasm, is rare. In this study, we chose 21 tagging SNPs (tSNPs), previously reported to be associated with glioma risk in a Chinese case-control study from Xi'an, China, and identified their contributions to astrocytoma susceptibility. We found an association with astrocytoma susceptibility for two tSNPs (rs6010620 and rs2853676) in two different genes: regulator of telomere elongation helicase 1 (RTEL1) and telomerase reverse transcriptase (TERT), respectively. We confirmed our results using recessive, dominant, and additive models. In the recessive model, we found two tSNPs (rs2297440 and rs6010620) associated with increased astrocytoma risk. In the dominant model, we found that rs2853676 was associated with increased astrocytoma risk. In the additive model, all three tSNPs (rs2297440, rs2853676, and rs6010620) were associated with increased astrocytoma risk. Our results demonstrate, for the first time, the potential roles of RTEL1 and TERT in astrocytoma development.

Patterns of multiple health risk-behaviours in university students and their association with mental health: application of latent class analysis.

PubMed

Kwan, M Y; Arbour-Nicitopoulos, K P; Duku, E; Faulkner, G

2016-08-01

University and college campuses may be the last setting where it is possible to comprehensively address the health of a large proportion of the young adult population. It is important that health promoters understand the collective challenges students are facing, and to better understand the broader lifestyle behavioural patterning evident during this life stage. The purpose of this study was to examine the clustering of modifiable health-risk behaviours and to explore the relationship between these identified clusters and mental health outcomes among a large Canadian university sample. Undergraduate students (n = 837; mean age = 21 years) from the University of Toronto completed the National College Health Assessment survey. The survey consists of approximately 300 items, including assessments of student health status, mental health and health-risk behaviours. Latent class analysis was used to identify patterning based on eight salient health-risk behaviours (marijuana use, other illicit drug use, risky sex, smoking, binge drinking, poor diet, physical inactivity, and insufficient sleep). A three-class model based on student behavioural patterns emerged: "typical," "high-risk" and "moderately healthy." Results also found high-risk students reporting significantly higher levels of stress than typical students (χ2(1671) = 7.26, p < .01). Students with the highest likelihood of engaging in multiple health-risk behaviours reported poorer mental health, particularly as it relates to stress. Although these findings should be interpreted with caution due to the 28% response rate, they do suggest that interventions targeting specific student groups with similar patterning of multiple health-risk behaviours may be needed.

Developing a Conceptually Equivalent Type 2 Diabetes Risk Score for Indian Gujaratis in the UK

PubMed Central

Patel, Naina; Stone, Margaret; Barber, Shaun; Gray, Laura; Davies, Melanie; Khunti, Kamlesh

2016-01-01

Aims. To apply and assess the suitability of a model consisting of commonly used cross-cultural translation methods to achieve a conceptually equivalent Gujarati language version of the Leicester self-assessment type 2 diabetes risk score. Methods. Implementation of the model involved multiple stages, including pretesting of the translated risk score by conducting semistructured interviews with a purposive sample of volunteers. Interviews were conducted on an iterative basis to enable findings to inform translation revisions and to elicit volunteers' ability to self-complete and understand the risk score. Results. The pretest stage was an essential component involving recruitment of a diverse sample of 18 Gujarati volunteers, many of whom gave detailed suggestions for improving the instructions for the calculation of the risk score and BMI table. Volunteers found the standard and level of Gujarati accessible and helpful in understanding the concept of risk, although many of the volunteers struggled to calculate their BMI. Conclusions. This is the first time that a multicomponent translation model has been applied to the translation of a type 2 diabetes risk score into another language. This project provides an invaluable opportunity to share learning about the transferability of this model for translation of self-completed risk scores in other health conditions. PMID:27703985

Protective personality traits: High openness and low neuroticism linked to better memory in multiple sclerosis.

PubMed

Leavitt, Victoria M; Buyukturkoglu, Korhan; Inglese, Matilde; Sumowski, James F

2017-11-01

Memory impairment in multiple sclerosis (MS) is common, although few risk/protective factors are known. To examine relationships of personality to memory/non-memory cognition in MS. 80 patients completed a cognitive battery and a personality scale measuring the "Big 5" traits: openness, neuroticism, agreeableness, extraversion, and conscientiousness. Memory was most related to openness, with higher openness linked to better memory and lower risk for memory impairment, controlling for age, atrophy, education, and intelligence quotient (IQ). Lower neuroticism was also related to better memory, and lower conscientiousness to memory impairment. Non-memory cognition was unrelated to personality. Personality may inform predictive models of memory impairment in MS.

Structural equation modeling in environmental risk assessment.

PubMed

Buncher, C R; Succop, P A; Dietrich, K N

1991-01-01

Environmental epidemiology requires effective models that take individual observations of environmental factors and connect them into meaningful patterns. Single-factor relationships have given way to multivariable analyses; simple additive models have been augmented by multiplicative (logistic) models. Each of these steps has produced greater enlightenment and understanding. Models that allow for factors causing outputs that can affect later outputs with putative causation working at several different time points (e.g., linkage) are not commonly used in the environmental literature. Structural equation models are a class of covariance structure models that have been used extensively in economics/business and social science but are still little used in the realm of biostatistics. Path analysis in genetic studies is one simplified form of this class of models. We have been using these models in a study of the health and development of infants who have been exposed to lead in utero and in the postnatal home environment. These models require as input the directionality of the relationship and then produce fitted models for multiple inputs causing each factor and the opportunity to have outputs serve as input variables into the next phase of the simultaneously fitted model. Some examples of these models from our research are presented to increase familiarity with this class of models. Use of these models can provide insight into the effect of changing an environmental factor when assessing risk. The usual cautions concerning believing a model, believing causation has been proven, and the assumptions that are required for each model are operative.

Quantifying the dynamics of field cancerization in tobacco-related head and neck cancer: a multi-scale modeling approach

PubMed Central

Ryser, Marc D.; Lee, Walter T.; Readyz, Neal E.; Leder, Kevin Z.; Foo, Jasmine

2017-01-01

High rates of local recurrence in tobacco-related head and neck squamous cell carcinoma (HNSCC) are commonly attributed to unresected fields of precancerous tissue. Since they are not easily detectable at the time of surgery without additional biopsies, there is a need for non-invasive methods to predict the extent and dynamics of these fields. Here we developed a spatial stochastic model of tobacco-related HNSCC at the tissue level and calibrated the model using a Bayesian framework and population-level incidence data from the Surveillance, Epidemiology, and End Results (SEER) registry. Probabilistic model analyses were performed to predict the field geometry at time of diagnosis, and model predictions of age-specific recurrence risks were tested against outcome data from SEER. The calibrated models predicted a strong dependence of the local field size on age at diagnosis, with a doubling of the expected field diameter between ages at diagnosis of 50 and 90 years, respectively. Similarly, the probability of harboring multiple, clonally unrelated fields at the time of diagnosis were found to increase substantially with patient age. Based on these findings, we hypothesized a higher recurrence risk in older compared to younger patients when treated by surgery alone; we successfully tested this hypothesis using age-stratified outcome data. Further clinical studies are needed to validate the model predictions in a patient-specific setting. This work highlights the importance of spatial structure in models of epithelial carcinogenesis, and suggests that patient age at diagnosis may be a critical predictor of the size and multiplicity of precancerous lesions. Major Findings Patient age at diagnosis was found to be a critical predictor of the size and multiplicity of precancerous lesions. This finding challenges the current one-size-fits-all approach to surgical excision margins. PMID:27913438

Teaching Subtraction and Multiplication with Regrouping Using the Concrete-Representational-Abstract Sequence and Strategic Instruction Model

ERIC Educational Resources Information Center

Flores, Margaret M.; Hinton, Vanessa; Strozier, Shaunita D.

2014-01-01

Based on Common Core Standards (2010), mathematics interventions should emphasize conceptual understanding of numbers and operations as well as fluency. For students at risk for failure, the concrete-representational-abstract (CRA) sequence and the Strategic Instruction Model (SIM) have been shown effective in teaching computation with an emphasis…

Risk factors and mediating pathways of loneliness and social support in community-dwelling older adults.

PubMed

Schnittger, Rebecca I B; Wherton, Joseph; Prendergast, David; Lawlor, Brian A

2012-01-01

To develop biopsychosocial models of loneliness and social support thereby identifying their key risk factors in an Irish sample of community-dwelling older adults. Additionally, to investigate indirect effects of social support on loneliness through mediating risk factors. A total of 579 participants (400 females; 179 males) were given a battery of biopsychosocial assessments with the primary measures being the De Jong Gierveld Loneliness Scale and the Lubben Social Network Scale along with a broad range of secondary measures. Bivariate correlation analyses identified items to be included in separate psychosocial, cognitive, biological and demographic multiple regression analyses. The resulting model items were then entered into further multiple regression analyses to obtain overall models. Following this, bootstrapping mediation analyses was conducted to examine indirect effects of social support on the subtypes (emotional and social) of loneliness. The overall model for (1) emotional loneliness included depression, neuroticism, perceived stress, living alone and accommodation type, (2) social loneliness included neuroticism, perceived stress, animal naming and number of grandchildren and (3) social support included extraversion, executive functioning (Trail Making Test B-time), history of falls, age and whether the participant drives or not. Social support influenced emotional loneliness predominantly through indirect means, while its effect on social loneliness was more direct. These results characterise the biopsychosocial risk factors of emotional loneliness, social loneliness and social support and identify key pathways by which social support influences emotional and social loneliness. These findings highlight issues with the potential for consideration in the development of targeted interventions.

Development of in Vivo Biomarkers for Progressive Tau Pathology after Traumatic Brain Injury

DTIC Science & Technology

2015-02-01

Athletes in contact sports who have sustained multiple concussive traumatic brain injuries are at high risk for delayed, progressive neurological and...11 or ‘punch drunk’ syndrome 9, 12. US military personnel 13, 14 and others who have sustained multiple concussive traumatic brain injuries 15-17...To date, none of the attempts to model progressive tau pathology after repetitive concussive TBI in mice has been optimal. Ongoing efforts include

Development of in Vivo Biomarkers for Progressive Tau Pathology after Traumatic Brain Injury

DTIC Science & Technology

2016-02-01

14. ABSTRACT Athletes in contact sports who have sustained multiple concussive traumatic brain injuries are at high risk for delayed, progressive...pugilistica 3, 11 or ‘punch drunk’ syndrome 9, 12. US military personnel 13, 14 and others who have sustained multiple concussive traumatic brain...Progress to date: To date, none of the attempts to model progressive tau pathology after repetitive concussive TBI in mice has been optimal. Ongoing

A triangular climate-based decision model to forecast crop anomalies in Kenya

NASA Astrophysics Data System (ADS)

Guimarães Nobre, G.; Davenport, F.; Veldkamp, T.; Jongman, B.; Funk, C. C.; Husak, G. J.; Ward, P.; Aerts, J.

2017-12-01

By the end of 2017, the world is expected to experience unprecedented demands for food assistance where, across 45 countries, some 81 million people will face a food security crisis. Prolonged droughts in Eastern Africa are playing a major role in these crises. To mitigate famine risk and save lives, government bodies and international donor organisations are increasingly building up efforts to resolve conflicts and secure humanitarian relief. Disaster-relief and financing organizations traditionally focus on emergency response, providing aid after an extreme drought event, instead of taking actions in advance based on early warning. One of the reasons for this approach is that the seasonal risk information provided by early warning systems is often considered highly uncertain. Overcoming the reluctance to act based on early warnings greatly relies on understanding the risk of acting in vain, and assessing the cost-effectiveness of early actions. This research develops a triangular climate-based decision model for multiple seasonal time-scales to forecast strong anomalies in crop yield shortages in Kenya using Casual Discovery Algorithms and Fast and Frugal Decision Trees. This Triangular decision model (1) estimates the causality and strength of the relationship between crop yields and hydro climatological predictors (extracted from the Famine Early Warning Systems Network's data archive) during the crop growing season; (2) provides probabilistic forecasts of crop yield shortages in multiple time scales before the harvesting season; and (3) evaluates the cost-effectiveness of different financial mechanisms to respond to early warning indicators of crop yield shortages obtained from the model. Furthermore, we reflect on how such a model complements and advances the current state-of-art FEWS Net system, and examine its potential application to improve the management of agricultural risks in Kenya.

Application of a Pharmacokinetic Model of Metformin Clearance in a Population with Acute Myeloid Leukemia.

PubMed

Ceacareanu, Alice C; Brown, Geoffrey W; Moussa, Hoda A; Wintrob, Zachary A P

2018-01-01

We aimed to estimate the metformin-associated lactic acidosis (MALA) risk by assessing retrospectively the renal clearance variability and applying a pharmacokinetic (PK) model of metformin clearance in a population diagnosed with acute myeloid leukemia (AML) and diabetes mellitus (DM). All adults with preexisting DM and newly diagnosed AML at Roswell Park Cancer Institute were reviewed (January 2003-December 2010, n = 78). Creatinine clearance (CrCl) and total body weight distributions were used in a two-compartment PK model adapted for multiple dosing and modified to account for actual intra- and inter-individual variability. Based on this renal function variability evidence, 1000 PK profiles were simulated for multiple metformin regimens with the resultant PK profiles being assessed for safe CrCl thresholds. Metformin 500 mg up to three times daily was safe for all simulated profiles with CrCl ≥25 mL/min. Furthermore, the estimated overall MALA risk was below 10%, remaining under 5% for 500 mg given once daily. CrCl ≥65.25 mL/min was safe for administration in any of the tested regimens (500 mg or 850 mg up to three times daily or 1000 mg up to twice daily). PK simulation-guided prescribing can maximize metformin's beneficial effects on cancer outcomes while minimizing MALA risk.

Models and mosaics: investigating cross-cultural differences in risk perception and risk preference.

PubMed

Weber, E U; Hsee, C K

1999-12-01

In this article, we describe a multistudy project designed to explain observed cross-national differences in risk taking between respondents from the People's Republic of China and the United States. Using this example, we develop the following recommendations for cross-cultural investigations. First, like all psychological research, cross-cultural studies should be model based. Investigators should commit themselves to a model of the behavior under study that explicitly specifies possible causal constructs or variables hypothesized to influence the behavior, as well as the relationship between those variables, and allows for individual, group, or cultural differences in the value of these variables or in the relationship between them. This moves the focus from a simple demonstration of cross-national differences toward a prediction of the behavior, including its cross-national variation. Ideally, the causal construct hypothesized and shown to differ between cultures should be demonstrated to serve as a moderator or a mediator between culture and observed behavioral differences. Second, investigators should look for converging evidence for hypothesized cultural effects on behavior by looking at multiple dependent variables and using multiple methodological approaches. Thus, the data collection that will allow for the establishment of conclusive causal connections between a cultural variable and some target behavior can be compared with the creation of a mosaic.

Multidimensional Patterns of Sexual Risk Behavior and Psychiatric Disorders in Men with Substance Use Disorders.

PubMed

Villalobos-Gallegos, Luis; Medina-Mora, María Elena; Benjet, Corina; Ruiz-Velasco, Silvia; Magis-Rodriguez, Carlos; Marín-Navarrete, Rodrigo

2018-05-29

Previous evidence links substance use disorders (SUD) to STI/HIV risk and suggests that comorbid psychiatric disorders increase the probability to engage in sexual risk behaviors. This study had two aims: (1) to identify subgroups based on sexual risk behavior using a person-centered approach in a sample of substance users and (2) to measure the association of psychiatric and SUD with subgroup membership. We assessed 402 male adults with SUD, reporting sexual intercourse in the previous 12 months using the HIV-Risk Behavior Scale and the Mini International Neuropsychiatric Interview. Latent class analysis was performed to determine multidimensional patterns of sexual risk behaviors and multinomial logistic regression was utilized to associate classes with disorders. The three-class model showed the best fit, and the classes were labeled: Relationship-Based (31.34% of the sample), Condom-Based (39.55%), and Multiple Risks (29.10%). Controlling for age and marital status, major depressive disorders, antisocial personality disorder, and any psychiatric disorder were associated with the Multiple Risks class. Results stress the importance of developing a personalized assessment and counseling for sexual risk behaviors in individuals with SUD, particularly when they endorse criteria for comorbid psychiatric disorders. Future studies should focus on evaluating differential response to preventive interventions.

Modeling the Diagnostic Criteria for Alcohol Dependence with Genetic Animal Models

PubMed Central

Kendler, Kenneth S.; Hitzemann, Robert J.

2012-01-01

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

Risk factors for epistaxis in jump racing in Great Britain (2001-2009).

PubMed

Reardon, Richard J M; Boden, Lisa A; Mellor, Dominic J; Love, Sandy; Newton, Richard J; Stirk, Anthony J; Parkin, Timothy D

2015-07-01

The aim of this study was to evaluate risk factors associated with developing epistaxis in jump racing in Great Britain (GB). A retrospective analysis of records from horses running in all hurdle and steeplechase races in GB between 2001 and 2009 identified diagnoses of epistaxis whilst still at the racecourse. Data were used from 603 starts resulting in epistaxis (event) and 169,065 starts resulting in no epistaxis (non-event) in hurdle racing, and from 550 event starts and 102,344 non-event starts in steeplechase racing. Two multivariable logistic regression models to evaluate risk factors associated with epistaxis were produced. The potential effect of clustering of data (within horse, horse dam, horse sire, trainer, jockey, course, race and race meet) on the associations between risk factors and epistaxis was examined using mixed-effects models. Multiple factors associated with increased risk of epistaxis were identified. Those identified in both types of jump racing included running on firmer ground; horses with >75% of career starts in flat racing and a previous episode of epistaxis recorded during racing. Risk factors identified only in hurdle racing included racing in the spring and increased age at first race; and those identified only in steeplechase racing included running in a claiming race and more starts in the previous 3-6 months. The risk factors identified provide important information about the risk of developing epistaxis. Multiple avenues for further investigation are highlighted, including unmeasured variables at the level of the racecourse. The results of this study can be used to guide the development of interventions to minimise the risk of epistaxis in jump racing. Copyright © 2015. Published by Elsevier Ltd.

Developing and validating risk prediction models in an individual participant data meta-analysis

PubMed Central

2014-01-01

Background Risk prediction models estimate the risk of developing future outcomes for individuals based on one or more underlying characteristics (predictors). We review how researchers develop and validate risk prediction models within an individual participant data (IPD) meta-analysis, in order to assess the feasibility and conduct of the approach. Methods A qualitative review of the aims, methodology, and reporting in 15 articles that developed a risk prediction model using IPD from multiple studies. Results The IPD approach offers many opportunities but methodological challenges exist, including: unavailability of requested IPD, missing patient data and predictors, and between-study heterogeneity in methods of measurement, outcome definitions and predictor effects. Most articles develop their model using IPD from all available studies and perform only an internal validation (on the same set of data). Ten of the 15 articles did not allow for any study differences in baseline risk (intercepts), potentially limiting their model’s applicability and performance in some populations. Only two articles used external validation (on different data), including a novel method which develops the model on all but one of the IPD studies, tests performance in the excluded study, and repeats by rotating the omitted study. Conclusions An IPD meta-analysis offers unique opportunities for risk prediction research. Researchers can make more of this by allowing separate model intercept terms for each study (population) to improve generalisability, and by using ‘internal-external cross-validation’ to simultaneously develop and validate their model. Methodological challenges can be reduced by prospectively planned collaborations that share IPD for risk prediction. PMID:24397587

Associations of Sexual Victimization, Depression, and Sexual Assertiveness with Unprotected Sex: A Test of the Multifaceted Model of HIV Risk Across Gender

PubMed Central

Morokoff, Patricia J.; Redding, Colleen A.; Harlow, Lisa L.; Cho, Sookhyun; Rossi, Joseph S.; Meier, Kathryn S.; Mayer, Kenneth H.; Koblin, Beryl; Brown-Peterside, Pamela

2014-01-01

This study examined whether the Multifaceted Model of HIV Risk (MMOHR) would predict unprotected sex based on predictors including gender, childhood sexual abuse (CSA), sexual victimization (SV), depression, and sexual assertiveness for condom use. A community-based sample of 473 heterosexually active men and women, aged 18–46 years completed survey measures of model variables. Gender predicted several variables significantly. A separate model for women demonstrated excellent fit, while the model for men demonstrated reasonable fit. Multiple sample model testing supported the use of MMOHR in both men and women, while simultaneously highlighting areas of gender difference. Prevention interventions should focus on sexual assertiveness, especially for CSA and SV survivors, as well as targeting depression, especially among men. PMID:25018617

Mitigating circumstances: A model-based analysis of associations between risk environment and infrequent condom use among Chinese street-based sex workers.

PubMed

Chang, Ruth C; Hail-Jares, Katie; Zheng, Huang; He, Na; Bouey, Jennifer Z H

2018-01-01

Little is known about how freelance street-based sex workers navigate condom use while soliciting. Traditional behavioural model may fail to account for the complex risk environment that most street-based sex workers work within. We examine first the association of self-efficacy and the infrequent condom use, then we investigated the roles of clients and venues frequented on this association. Using a purposive chain-referral sampling method, we surveyed 248 street-based sex workers in Shanghai. The survey focused on sex workers HIV risk factors, sex work patterns, HIV knowledge, and related HIV self-efficacy. Clients types and behaviours, and characteristics of the venues frequented by these commercial sex workers were also collected. We conducted a series of multiple logistic regression models to explore how the association between a sex worker's self-efficacy with infrequent condom use change as client and venue characteristics were added to the models. We find that within the basic model, low self-efficacy was marginally associated with infrequent condom use (54.9% vs. 45.1%, AOR = 1.70, 95% CI = 0.95-3.03). As client- and venue- characteristics were added, the associations between self-efficacy and condom use were strengthened (AOR = 2.10 95% CI = 1.12-3.91 and 2.54 95% CI = 1.24-5.19 respectively). Those who reported middle-tiered income were more likely to report infrequent condom use compared to their peers of high income (AOR = 3.92 95% CI = 1.32-11.70) whereas such difference was not found between low income and high income sex workers. Visiting multiple venues and having migrant workers as clients were also associated with infrequent condom use. Our findings suggest sex worker's self-efficacy matters in their HIV risk behaviours only when environment characteristics were adjusted. Risk environment for street-based sex workers are complex. Programming addressing behavioural changes among female sex workers should adopt holistic, multilevel models with the consideration of risk environments.

A framework for quantifying net benefits of alternative prognostic models.

PubMed

Rapsomaniki, Eleni; White, Ian R; Wood, Angela M; Thompson, Simon G

2012-01-30

New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks. Copyright © 2011 John Wiley & Sons, Ltd.

Mediation of late adolescent health-risk behaviors and gender influences.

PubMed

Christopherson, Toni Michelle; Conner, Bradley T

2012-11-01

This study explored how multiple bioecological constructs operate to explain health-risk behaviors in late adolescence and to test for moderator effects of gender. This was a descriptive, cross-sectional study with a convenience sample of 437 predominately Caucasian late adolescents with an average age of 19 years who lived in Northern California. Parental Attachment, Shyness, Loneliness, Law Abidance, and Youth Risk Behaviors were measured with self-report tools and analyzed using structural equation modeling. Confirmatory factor analysis indicated that the data fit the model well. Analysis of group differences revealed that gender moderated the relationships among the measured variables; thus, data were analyzed in independent gender-based models. Structural modeling demonstrated good model fit for each gender. Shyness and parental attachment each were associated with loneliness. Loneliness was associated with smoking. Loneliness linked the relationship between shyness, parental attachment, and smoking. Parental attachment was associated with law abidance. Law abidance was associated with sexual behaviors for female adolescents only. This study provides valuable insights for public health nurses as it pertains to late adolescent health-risk behaviors. Nurses should use screening tools and techniques to ensure appropriate referrals and interventions to meet the needs of at-risk adolescents. © 2012 Wiley Periodicals, Inc.

Assessing patient risk of central line-associated bacteremia via machine learning.

PubMed

Beeler, Cole; Dbeibo, Lana; Kelley, Kristen; Thatcher, Levi; Webb, Douglas; Bah, Amadou; Monahan, Patrick; Fowler, Nicole R; Nicol, Spencer; Judy-Malcolm, Alisa; Azar, Jose

2018-04-13

Central line-associated bloodstream infections (CLABSIs) contribute to increased morbidity, length of hospital stay, and cost. Despite progress in understanding the risk factors, there remains a need to accurately predict the risk of CLABSIs and, in real time, prevent them from occurring. A predictive model was developed using retrospective data from a large academic healthcare system. Models were developed with machine learning via construction of random forests using validated input variables. Fifteen variables accounted for the most significant effect on CLABSI prediction based on a retrospective study of 70,218 unique patient encounters between January 1, 2013, and May 31, 2016. The area under the receiver operating characteristic curve for the best-performing model was 0.82 in production. This model has multiple applications for resource allocation for CLABSI prevention, including serving as a tool to target patients at highest risk for potentially cost-effective but otherwise time-limited interventions. Machine learning can be used to develop accurate models to predict the risk of CLABSI in real time prior to the development of infection. Copyright © 2018 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types

PubMed Central

Elashoff, Robert M.; Li, Gang; Li, Ning

2009-01-01

Summary In this article we study a joint model for longitudinal measurements and competing risks survival data. Our joint model provides a flexible approach to handle possible nonignorable missing data in the longitudinal measurements due to dropout. It is also an extension of previous joint models with a single failure type, offering a possible way to model informatively censored events as a competing risk. Our model consists of a linear mixed effects submodel for the longitudinal outcome and a proportional cause-specific hazards frailty submodel (Prentice et al., 1978, Biometrics 34, 541-554) for the competing risks survival data, linked together by some latent random effects. We propose to obtain the maximum likelihood estimates of the parameters by an expectation maximization (EM) algorithm and estimate their standard errors using a profile likelihood method. The developed method works well in our simulation studies and is applied to a clinical trial for the scleroderma lung disease. PMID:18162112

Approximate Uncertainty Modeling in Risk Analysis with Vine Copulas

PubMed Central

Bedford, Tim; Daneshkhah, Alireza

2015-01-01

Many applications of risk analysis require us to jointly model multiple uncertain quantities. Bayesian networks and copulas are two common approaches to modeling joint uncertainties with probability distributions. This article focuses on new methodologies for copulas by developing work of Cooke, Bedford, Kurowica, and others on vines as a way of constructing higher dimensional distributions that do not suffer from some of the restrictions of alternatives such as the multivariate Gaussian copula. The article provides a fundamental approximation result, demonstrating that we can approximate any density as closely as we like using vines. It further operationalizes this result by showing how minimum information copulas can be used to provide parametric classes of copulas that have such good levels of approximation. We extend previous approaches using vines by considering nonconstant conditional dependencies, which are particularly relevant in financial risk modeling. We discuss how such models may be quantified, in terms of expert judgment or by fitting data, and illustrate the approach by modeling two financial data sets. PMID:26332240

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

PubMed

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

2012-08-01

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

The prediction of type 1 diabetes by multiple autoantibody levels and their incorporation into an autoantibody risk score in relatives of type 1 diabetic patients.

PubMed

Sosenko, Jay M; Skyler, Jay S; Palmer, Jerry P; Krischer, Jeffrey P; Yu, Liping; Mahon, Jeffrey; Beam, Craig A; Boulware, David C; Rafkin, Lisa; Schatz, Desmond; Eisenbarth, George

2013-09-01

We assessed whether a risk score that incorporates levels of multiple islet autoantibodies could enhance the prediction of type 1 diabetes (T1D). TrialNet Natural History Study participants (n = 784) were tested for three autoantibodies (GADA, IA-2A, and mIAA) at their initial screening. Samples from those positive for at least one autoantibody were subsequently tested for ICA and ZnT8A. An autoantibody risk score (ABRS) was developed from a proportional hazards model that combined autoantibody levels from each autoantibody along with their designations of positivity and negativity. The ABRS was strongly predictive of T1D (hazard ratio [with 95% CI] 2.72 [2.23-3.31], P < 0.001). Receiver operating characteristic curve areas (with 95% CI) for the ABRS revealed good predictability (0.84 [0.78-0.90] at 2 years, 0.81 [0.74-0.89] at 3 years, P < 0.001 for both). The composite of levels from the five autoantibodies was predictive of T1D before and after an adjustment for the positivity or negativity of autoantibodies (P < 0.001). The findings were almost identical when ICA was excluded from the risk score model. The combination of the ABRS and the previously validated Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) predicted T1D more accurately (0.93 [0.88-0.98] at 2 years, 0.91 [0.83-0.99] at 3 years) than either the DPTRS or the ABRS alone (P ≤ 0.01 for all comparisons). These findings show the importance of considering autoantibody levels in assessing the risk of T1D. Moreover, levels of multiple autoantibodies can be incorporated into an ABRS that accurately predicts T1D.

The Prediction of Type 1 Diabetes by Multiple Autoantibody Levels and Their Incorporation Into an Autoantibody Risk Score in Relatives of Type 1 Diabetic Patients

PubMed Central

Sosenko, Jay M.; Skyler, Jay S.; Palmer, Jerry P.; Krischer, Jeffrey P.; Yu, Liping; Mahon, Jeffrey; Beam, Craig A.; Boulware, David C.; Rafkin, Lisa; Schatz, Desmond; Eisenbarth, George

2013-01-01

OBJECTIVE We assessed whether a risk score that incorporates levels of multiple islet autoantibodies could enhance the prediction of type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS TrialNet Natural History Study participants (n = 784) were tested for three autoantibodies (GADA, IA-2A, and mIAA) at their initial screening. Samples from those positive for at least one autoantibody were subsequently tested for ICA and ZnT8A. An autoantibody risk score (ABRS) was developed from a proportional hazards model that combined autoantibody levels from each autoantibody along with their designations of positivity and negativity. RESULTS The ABRS was strongly predictive of T1D (hazard ratio [with 95% CI] 2.72 [2.23–3.31], P < 0.001). Receiver operating characteristic curve areas (with 95% CI) for the ABRS revealed good predictability (0.84 [0.78–0.90] at 2 years, 0.81 [0.74–0.89] at 3 years, P < 0.001 for both). The composite of levels from the five autoantibodies was predictive of T1D before and after an adjustment for the positivity or negativity of autoantibodies (P < 0.001). The findings were almost identical when ICA was excluded from the risk score model. The combination of the ABRS and the previously validated Diabetes Prevention Trial–Type 1 Risk Score (DPTRS) predicted T1D more accurately (0.93 [0.88–0.98] at 2 years, 0.91 [0.83–0.99] at 3 years) than either the DPTRS or the ABRS alone (P ≤ 0.01 for all comparisons). CONCLUSIONS These findings show the importance of considering autoantibody levels in assessing the risk of T1D. Moreover, levels of multiple autoantibodies can be incorporated into an ABRS that accurately predicts T1D. PMID:23818528

Dose-rate effects of ethylene oxide exposure on developmental toxicity.

PubMed

Weller, E; Long, N; Smith, A; Williams, P; Ravi, S; Gill, J; Henessey, R; Skornik, W; Brain, J; Kimmel, C; Kimmel, G; Holmes, L; Ryan, L

1999-08-01

In risk assessment, evaluating a health effect at a duration of exposure that is untested involves assuming that equivalent multiples of concentration (C) and duration (T) of exposure have the same effect. The limitations of this approach (attributed to F. Haber, Zur Geschichte des Gaskrieges [On the history of gas warfare], in Funf Vortrage aus den Jahren 1920-1923 [Five lectures from the years 1920-1923], 1924, Springer, Berlin, pp. 76-92), have been noted in several studies. The study presented in this paper was designed to specifically look at dose-rate (C x T) effects, and it forms an ideal case study to implement statistical models and to examine the statistical issues in risk assessment. Pregnant female C57BL/6J mice were exposed, on gestational day 7, to ethylene oxide (EtO) via inhalation for 1.5, 3, or 6 h at exposures that result in C x T multiples of 2100 or 2700 ppm-h. EtO was selected because of its short half-life, documented developmental toxicity, and relevance to exposures that occur in occupational settings. Concurrent experiments were run with animals exposed to air for similar periods. Statistical analysis using models developed to assess dose-rate effects revealed significant effects with respect to fetal death and resorptions, malformations, crown-to-rump length, and fetal weight. Animals exposed to short, high exposures of EtO on day 7 of gestation were found to have more adverse effects than animals exposed to the same C x T multiple but at longer, lower exposures. The implication for risk assessment is that applying Haber's Law could potentially lead to an underestimation of risk at a shorter duration of exposure and an overestimation of risk at a longer duration of exposure. Further research, toxicological and statistical, are required to understand the mechanism of the dose-rate effects, and how to incorporate the mechanistic information into the risk assessment decision process.

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

PubMed Central

Janmaimool, Piyapong; Watanabe, Tsunemi

2014-01-01

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

Decisional role preferences, risk knowledge and information interests in patients with multiple sclerosis.

PubMed

Heesen, Christoph; Kasper, Jürgen; Segal, Julia; Köpke, Sascha; Mühlhauser, Ingrid

2004-12-01

Shared decision making is increasingly recognized as the ideal model of patient-physician communication especially in chronic diseases with partially effective treatments as multiple sclerosis (MS). To evaluate prerequisite factors for this kind of decision making we studied patients' decisional role preferences in medical decision making, knowledge on risks, information interests and the relations between these factors in MS. After conducting focus groups to generate hypotheses, 219 randomly selected patients from the MS Outpatient Clinic register (n = 1374) of the University Hospital Hamburg received mailed questionnaires on their knowledge of risks in MS, their perception of their own level of knowledge, information interests and role preferences. Most patients (79%) indicated that they preferred an active role in treatment decisions giving the shared decision and the informed choice model the highest priority. MS risk knowledge was low but questionnaire results depended on disease course, disease duration and ongoing immune therapy. Measured knowledge as well as perceived knowledge was only weakly correlated with preferences of active roles. Major information interests were related to symptom alleviation, diagnostic procedures and prognosis. Patients with MS claimed autonomous roles in their health care decisions. The weak correlation between knowledge and preferences for active roles implicates that other factors largely influence role preferences.

Proximity to pollution sources and risk of amphibian limb malformation.

PubMed

Taylor, Brynn; Skelly, David; Demarchis, Livia K; Slade, Martin D; Galusha, Deron; Rabinowitz, Peter M

2005-11-01

The cause of limb deformities in wild amphibian populations remains unclear, even though the apparent increase in prevalence of this condition may have implications for human health. Few studies have simultaneously assessed the effect of multiple exposures on the risk of limb deformities. In a cross-sectional survey of 5,264 hylid and ranid metamorphs in 42 Vermont wetlands, we assessed independent risk factors for nontraumatic limb malformation. The rate of nontraumatic limb malformation varied by location from 0 to 10.2%. Analysis of a subsample did not demonstrate any evidence of infection with the parasite Ribeiroia. We used geographic information system (GIS) land-use/land-cover data to validate field observations of land use in the proximity of study wetlands. In a multiple logistic regression model that included land use as well as developmental stage, genus, and water-quality measures, proximity to agricultural land use was associated with an increased risk of limb malformation (odds ratio = 2.26; 95% confidence interval, 1.42-3.58; p < 0.001). The overall discriminant power of the statistical model was high (C = 0.79). These findings from one of the largest systematic surveys to date provide support for the role of chemical toxicants in the development of amphibian limb malformation and demonstrate the value of an epidemiologic approach to this problem.

Identification of water quality management policy of watershed system with multiple uncertain interactions using a multi-level-factorial risk-inference-based possibilistic-probabilistic programming approach.

PubMed

Liu, Jing; Li, Yongping; Huang, Guohe; Fu, Haiyan; Zhang, Junlong; Cheng, Guanhui

2017-06-01

In this study, a multi-level-factorial risk-inference-based possibilistic-probabilistic programming (MRPP) method is proposed for supporting water quality management under multiple uncertainties. The MRPP method can handle uncertainties expressed as fuzzy-random-boundary intervals, probability distributions, and interval numbers, and analyze the effects of uncertainties as well as their interactions on modeling outputs. It is applied to plan water quality management in the Xiangxihe watershed. Results reveal that a lower probability of satisfying the objective function (θ) as well as a higher probability of violating environmental constraints (q i ) would correspond to a higher system benefit with an increased risk of violating system feasibility. Chemical plants are the major contributors to biological oxygen demand (BOD) and total phosphorus (TP) discharges; total nitrogen (TN) would be mainly discharged by crop farming. It is also discovered that optimistic decision makers should pay more attention to the interactions between chemical plant and water supply, while decision makers who possess a risk-averse attitude would focus on the interactive effect of q i and benefit of water supply. The findings can help enhance the model's applicability and identify a suitable water quality management policy for environmental sustainability according to the practical situations.

Identification and Quantification of Cumulative Factors that ...

EPA Pesticide Factsheets

Evaluating the combined adverse effects of multiple stressors upon human health is an imperative component of cumulative risk assessment (CRA)1. In addition to chemical stressors, other non-chemical factors are also considered. For examples, smoking will elevate the risks of having lung cancer associated with radon exposure2; toluene and noise together will induce higher levels of hearing loss3; children exposed to violence will have higher risks of developing asthma in the presence of air pollution4. Environmental Justice (EJ) indicators, used as a tool to assess and quantify some of these non-chemical factors, include health, economic, and social indicators such as vulnerability and susceptibility5. Vulnerability factors encompass race, ethnicity, behavior, geographic location, etc., while susceptibility factors include life stage, genetic predisposition, pre-existing health condition and others6, although these two categories are not always mutually exclusive. Numerous findings regarding combined effects of EJ indicators and chemical stressors have been identified7-11. However, fewer studies have analyzed the interrelation between multiple stressors that exert combined harmful effects upon individual or population health in the context of exposure assessment within the risk assessment framework12. In this study, we connected EJ indicators to variables in the exposure assessment model, especially the Average Daily Dose (ADD) model13, in order to better underst

Sexual behavior, risk perception, and HIV transmission can respond to HIV antiviral drugs and vaccines through multiple pathways.

PubMed

Tully, Stephen; Cojocaru, Monica; Bauch, Chris T

2015-10-28

There has been growing use of highly active antiretroviral treatment (HAART) for HIV and significant progress in developing prophylactic HIV vaccines. The simplest theories of counterproductive behavioral responses to such interventions tend to focus on single feedback mechanisms: for instance, HAART optimism makes infection less scary and thus promotes risky sexual behavior. Here, we develop an agent based, age-structured model of HIV transmission, risk perception, and partner selection in a core group to explore behavioral responses to interventions. We find that interventions can activate not one, but several feedback mechanisms that could potentially influence decision-making and HIV prevalence. In the model, HAART increases the attractiveness of unprotected sex, but it also increases perceived risk of infection and, on longer timescales, causes demographic impacts that partially counteract HAART optimism. Both HAART and vaccination usually lead to lower rates of unprotected sex on the whole, but intervention effectiveness depends strongly on whether individuals over- or under-estimate intervention coverage. Age-specific effects cause sexual behavior and HIV prevalence to change in opposite ways in old and young age groups. For complex infections like HIV-where interventions influence transmission, demography, sexual behavior and risk perception-we conclude that evaluations of behavioral responses should consider multiple feedback mechanisms.

Modeling Classical Swine Fever Outbreak-Related Outcomes

PubMed Central

Yadav, Shankar; Olynk Widmar, Nicole J.; Weng, Hsin-Yi

2016-01-01

The study was carried out to estimate classical swine fever (CSF) outbreak-related outcomes, such as epidemic duration and number of infected, vaccinated, and depopulated premises, using defined most likely CSF outbreak scenarios. Risk metrics were established using empirical data to select the most likely CSF outbreak scenarios in Indiana. These scenarios were simulated using a stochastic between-premises disease spread model to estimate outbreak-related outcomes. A total of 19 single-site (i.e., with one index premises at the onset of an outbreak) and 15 multiple-site (i.e., with more than one index premises at the onset of an outbreak) outbreak scenarios of CSF were selected using the risk metrics. The number of index premises in the multiple-site outbreak scenarios ranged from 4 to 32. The multiple-site outbreak scenarios were further classified into clustered (N = 6) and non-clustered (N = 9) groups. The estimated median (5th, 95th percentiles) epidemic duration (days) was 224 (24, 343) in the single-site and was 190 (157, 251) and 210 (167, 302) in the clustered and non-clustered multiple-site outbreak scenarios, respectively. The median (5th, 95th percentiles) number of infected premises was 323 (0, 488) in the single-site outbreak scenarios and was 529 (395, 662) and 465 (295, 640) in the clustered and non-clustered multiple-site outbreak scenarios, respectively. Both the number and spatial distributions of the index premises affected the outcome estimates. The results also showed the importance of implementing vaccinations to accommodate depopulation in the CSF outbreak controls. The use of routinely collected surveillance data in the risk metrics and disease spread model allows end users to generate timely outbreak-related information based on the initial outbreak’s characteristics. Swine producers can use this information to make an informed decision on the management of swine operations and continuity of business, so that potential losses could be minimized during a CSF outbreak. Government authorities might use the information to make emergency preparedness plans for CSF outbreak control. PMID:26870741

Neonatal Risk Factors for Treatment-Demanding Retinopathy of Prematurity: A Danish National Study.

PubMed

Slidsborg, Carina; Jensen, Aksel; Forman, Julie Lyng; Rasmussen, Steen; Bangsgaard, Regitze; Fledelius, Hans Callø; Greisen, Gorm; la Cour, Morten

2016-04-01

One goal of the study was to identify "new" statistically independent risk factors for treatment-demanding retinopathy of prematurity (ROP). Another goal was to evaluate whether any new risk factors could explain the increase in the incidence of treatment-demanding ROP over time in Denmark. A retrospective, register-based cohort study. The study included premature infants (n = 6490) born in Denmark from 1997 to 2008. The study sample and the 31 candidate risk factors were identified in 3 national registers. Data were linked through a unique civil registration number. Each of the 31 candidate risk factors were evaluated in univariate analyses, while adjusted for known risk factors (i.e., gestational age [GA] at delivery, small for gestational age [SGA], multiple births, and male sex). Significant outcomes were analyzed thereafter in a backward selection multiple logistic regression model. Treatment-demanding ROP and its associations to candidate risk factors. Mechanical ventilation (odds ratio [OR], 2.84; 95% confidence interval [CI], 1.99-4.08; P < 0.01) and blood transfusion (OR, 1.97; 95% CI, 1.20-3.14; P = 0.01) were the only new statistically independent risk factors, in addition to GA at delivery, SGA, multiple births, and male sex. Modification in these prognostic factors for ROP did not cause an increase in treatment-demanding ROP. In a large study population, blood transfusion and mechanical ventilation were the only new statistically independent risk factors to predict the development of treatment-demanding ROP. Modification in the neonatal treatment with mechanical ventilation or blood transfusion did not cause the observed increase in the incidence of preterm infants with treatment-demanding ROP during a recent birth period (2003-2008). Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Analysis of multiple tank car releases in train accidents.

PubMed

Liu, Xiang; Liu, Chang; Hong, Yili

2017-10-01

There are annually over two million carloads of hazardous materials transported by rail in the United States. The American railroads use large blocks of tank cars to transport petroleum crude oil and other flammable liquids from production to consumption sites. Being different from roadway transport of hazardous materials, a train accident can potentially result in the derailment and release of multiple tank cars, which may result in significant consequences. The prior literature predominantly assumes that the occurrence of multiple tank car releases in a train accident is a series of independent Bernoulli processes, and thus uses the binomial distribution to estimate the total number of tank car releases given the number of tank cars derailing or damaged. This paper shows that the traditional binomial model can incorrectly estimate multiple tank car release probability by magnitudes in certain circumstances, thereby significantly affecting railroad safety and risk analysis. To bridge this knowledge gap, this paper proposes a novel, alternative Correlated Binomial (CB) model that accounts for the possible correlations of multiple tank car releases in the same train. We test three distinct correlation structures in the CB model, and find that they all outperform the conventional binomial model based on empirical tank car accident data. The analysis shows that considering tank car release correlations would result in a significantly improved fit of the empirical data than otherwise. Consequently, it is prudent to consider alternative modeling techniques when analyzing the probability of multiple tank car releases in railroad accidents. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of Species Sensitivity Distributions for Wildlife Using Interspecies Toxicity Correlation Models

EPA Science Inventory

Species sensitivity distributions (SSD) are cumulative distributions of chemical toxicity of multiple species and have had limited application in wildlife risk assessment because of relatively small datasets of wildlife toxicity values. Interspecies correlation estimation (ICE) m...

Project management tool

NASA Technical Reports Server (NTRS)

Maluf, David A. (Inventor); Bell, David G. (Inventor); Gurram, Mohana M. (Inventor); Gawdiak, Yuri O. (Inventor)

2009-01-01

A system for managing a project that includes multiple tasks and a plurality of workers. Input information includes characterizations based upon a human model, a team model and a product model. Periodic reports, such as a monthly report, a task plan report, a budget report and a risk management report, are generated and made available for display or further analysis. An extensible database allows searching for information based upon context and upon content.

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

PubMed

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

2014-01-01

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

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.

Numerical study of impact erosion of multiple solid particle

NASA Astrophysics Data System (ADS)

Zheng, Chao; Liu, Yonghong; Chen, Cheng; Qin, Jie; Ji, Renjie; Cai, Baoping

2017-11-01

Material erosion caused by continuous particle impingement during hydraulic fracturing results in significant economic loss and increased production risks. The erosion process is complex and has not been clearly explained through physical experiments. To address this problem, a multiple particle model in a 3D configuration was proposed to investigate the dynamic erosion process. This approach can significantly reduce experiment costs. The numerical model considered material damping and elastic-plastic material behavior of target material. The effects of impact parameters on erosion characteristics, such as plastic deformation, contact time, and energy loss rate, were investigated. Based on comprehensive studies, the dynamic erosion mechanism and geometry evolution of eroded crater was obtained. These findings can provide a detailed erosion process of target material and insights into the material erosion caused by multiple particle impingement.

Individual versus systemic risk and the Regulator's Dilemma

PubMed Central

Beale, Nicholas; Rand, David G.; Battey, Heather; Croxson, Karen; May, Robert M.; Nowak, Martin A.

2011-01-01

The global financial crisis of 2007–2009 exposed critical weaknesses in the financial system. Many proposals for financial reform address the need for systemic regulation—that is, regulation focused on the soundness of the whole financial system and not just that of individual institutions. In this paper, we study one particular problem faced by a systemic regulator: the tension between the distribution of assets that individual banks would like to hold and the distribution across banks that best supports system stability if greater weight is given to avoiding multiple bank failures. By diversifying its risks, a bank lowers its own probability of failure. However, if many banks diversify their risks in similar ways, then the probability of multiple failures can increase. As more banks fail simultaneously, the economic disruption tends to increase disproportionately. We show that, in model systems, the expected systemic cost of multiple failures can be largely explained by two global parameters of risk exposure and diversity, which can be assessed in terms of the risk exposures of individual actors. This observation hints at the possibility of regulatory intervention to promote systemic stability by incentivizing a more diverse diversification among banks. Such intervention offers the prospect of an additional lever in the armory of regulators, potentially allowing some combination of improved system stability and reduced need for additional capital. PMID:21768387

Managing hospitals in turbulent times: do organizational changes improve hospital survival?

PubMed Central

Lee, S Y; Alexander, J A

1999-01-01

OBJECTIVE: To examine (1) the degree to which organizational changes affected hospital survival; (2) whether core and peripheral organizational changes affected hospital survival differently; and (3) how simultaneous organizational changes affected hospital survival. DATA SOURCES: AHA Hospital Surveys, the Area Resource File, and the AHA Hospital Guides, Part B: Multihospital Systems. STUDY DESIGN: The study employed a longitudinal panel design. We followed changes in all community hospitals in the continental United States from 1981 through 1994. The dependent variable, hospital closure, was examined as a function of multiple changes in a hospital's core and peripheral structures as well as the hospital's organizational and environmental characteristics. Cox regression models were used to test the expectations that core changes increased closure risk while peripheral changes decreased such risk, and that simultaneous core and peripheral changes would lead to higher risk of closure. PRINCIPAL FINDINGS: Results indicated more peripheral than core changes in community hospitals. Overall, findings contradicted our expectations. Change in specialty, a core change, was beneficial for hospitals, because it reduced closure risk. The two most frequent peripheral changes, downsizing and leadership change, were positively associated with closure. Simultaneous organizational changes displayed a similar pattern: multiple core changes reduced closure risk, while multiple peripheral changes increased the risk. These patterns held regardless of the level of uncertainty in hospital environments. CONCLUSIONS: Organizational changes are not all beneficial for hospitals, suggesting that hospital leaders should be both cautious and selective in their efforts to turn their hospitals around. PMID:10536977

Water shortage risk assessment considering large-scale regional transfers: a copula-based uncertainty case study in Lunan, China.

PubMed

Gao, Xueping; Liu, Yinzhu; Sun, Bowen

2018-06-05

The risk of water shortage caused by uncertainties, such as frequent drought, varied precipitation, multiple water resources, and different water demands, brings new challenges to the water transfer projects. Uncertainties exist for transferring water and local surface water; therefore, the relationship between them should be thoroughly studied to prevent water shortage. For more effective water management, an uncertainty-based water shortage risk assessment model (UWSRAM) is developed to study the combined effect of multiple water resources and analyze the shortage degree under uncertainty. The UWSRAM combines copula-based Monte Carlo stochastic simulation and the chance-constrained programming-stochastic multiobjective optimization model, using the Lunan water-receiving area in China as an example. Statistical copula functions are employed to estimate the joint probability of available transferring water and local surface water and sampling from the multivariate probability distribution, which are used as inputs for the optimization model. The approach reveals the distribution of water shortage and is able to emphasize the importance of improving and updating transferring water and local surface water management, and examine their combined influence on water shortage risk assessment. The possible available water and shortages can be calculated applying the UWSRAM, also with the corresponding allocation measures under different water availability levels and violating probabilities. The UWSRAM is valuable for mastering the overall multi-water resource and water shortage degree, adapting to the uncertainty surrounding water resources, establishing effective water resource planning policies for managers and achieving sustainable development.

Health effects models for nuclear power plant accident consequence analysis: Low LET radiation: Part 2, Scientific bases for health effects models

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

Abrahamson, S.; Bender, M.; Book, S.

1989-05-01

This report provides dose-response models intended to be used in estimating the radiological health effects of nuclear power plant accidents. Models of early and continuing effects, cancers and thyroid nodules, and genetic effects are provided. Two-parameter Weibull hazard functions are recommended for estimating the risks of early and continuing health effects. Three potentially lethal early effects -- the hematopoietic, pulmonary and gastrointestinal syndromes -- are considered. Linear and linear-quadratic models are recommended for estimating cancer risks. Parameters are given for analyzing the risks of seven types of cancer in adults -- leukemia, bone, lung, breast, gastrointestinal, thyroid and ''other''. Themore » category, ''other'' cancers, is intended to reflect the combined risks of multiple myeloma, lymphoma, and cancers of the bladder, kidney, brain, ovary, uterus and cervix. Models of childhood cancers due to in utero exposure are also provided. For most cancers, both incidence and mortality are addressed. Linear and linear-quadratic models are also recommended for assessing genetic risks. Five classes of genetic disease -- dominant, x-linked, aneuploidy, unbalanced translocation and multifactorial diseases --are considered. In addition, the impact of radiation-induced genetic damage on the incidence of peri-implantation embryo losses is discussed. The uncertainty in modeling radiological health risks is addressed by providing central, upper, and lower estimates of all model parameters. Data are provided which should enable analysts to consider the timing and severity of each type of health risk. 22 refs., 14 figs., 51 tabs.« less

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

PubMed

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

2012-01-01

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

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

PubMed Central

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

2015-01-01

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

Child Maltreatment Among Singletons and Multiple Births in Japan: A Population-Based Study.

PubMed

Yokoyama, Yoshie; Oda, Terumi; Nagai, Noriyo; Sugimoto, Masako; Mizukami, Kenji

2015-12-01

The occurrence of multiple births has been recognized as a risk factor for child maltreatment. However, few population-based studies have examined the relationship between multiple births and child maltreatment. This study aimed to evaluate the degree of risk of child maltreatment among singletons and multiple births in Japan and to identify factors associated with increased risk. Using population-based data, we analyzed the database of records on child maltreatment and medical checkups for infants aged 1.5 years filed at Nishinomiya City Public Health Center between April 2007 and March 2011. To protect personal information, the data were transferred to anonymized electronic files for analysis. After adjusting by logistic regression for each associated factor and gestation number, multiples themselves were not associated with the risk of child maltreatment. However, compared with singletons, multiples had a significantly higher rate of risk factors for child maltreatment, including low birth weight and neural abnormality. Moreover, compared with mothers of singleton, mothers of twins had a significantly higher rate of poor health, which is a risk factor of child maltreatment. Multiples were not associated with the risk of child maltreatment. However, compared with singletons, multiples and their mothers had a significantly higher rate of risk factors of child maltreatment.

A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning

PubMed Central

2018-01-01

Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic genes, we aimed to develop a novel system-level risk stratification model for lung adenocarcinoma based on gene coexpression network. Using multiple microarray, gene coexpression network analysis was performed to identify survival-related networks. A deep learning based risk stratification model was constructed with representative genes of these networks. The model was validated in two test sets. Survival analysis was performed using the output of the model to evaluate whether it could predict patients' survival independent of clinicopathological variables. Five networks were significantly associated with patients' survival. Considering prognostic significance and representativeness, genes of the two survival-related networks were selected for input of the model. The output of the model was significantly associated with patients' survival in two test sets and training set (p < 0.00001, p < 0.0001 and p = 0.02 for training and test sets 1 and 2, resp.). In multivariate analyses, the model was associated with patients' prognosis independent of other clinicopathological features. Our study presents a new perspective on incorporating gene coexpression networks into the gene expression signature and clinical application of deep learning in genomic data science for prognosis prediction. PMID:29581968

The impact of attachment and depression symptoms on multiple risk behaviors in post-war adolescents in northern Uganda.

PubMed

Okello, J; Nakimuli-Mpungu, E; Klasen, F; Voss, C; Musisi, S; Broekaert, E; Derluyn, I

2015-07-15

We have previously shown that depression symptoms are associated with multiple risk behaviors and that parental attachments are protective against depression symptoms in post-war adolescents. Accumulating literature indicates that low levels of attachment may sensitize individuals to increased multiple risk behaviors when depression symptoms exist. This investigation examined the interactive effects of attachment and depression symptoms on multiple risk behavior. We conducted hierarchical logistic regression analyses to examine the impact of attachment and depression symptoms on multiple risk behavior in our post-war sample of 551 adolescents in Gulu district. Analyses revealed interactive effects for only maternal attachment-by-depression interaction. Interestingly, high levels of maternal attachment exacerbated the relationship between depression symptoms and multiple risk behaviors while low levels of maternal attachment attenuated this relationship. It is possible that this analysis could be biased by a common underlying factor that influences self-reporting and therefore is correlated with each of self-reported attachment security, depressive symptoms, and multiple risk behaviors. These findings suggest that maternal attachment serves as a protective factor at low levels while serving as an additional risk factor at high levels. Findings support and expand current knowledge about the roles that attachment and depression symptoms play in the development of multiple risk behaviors and suggest a more complex etiology for post-war adolescents. Copyright © 2015 Elsevier B.V. All rights reserved.

Volcano warning systems: Chapter 67

USGS Publications Warehouse

Gregg, Chris E.; Houghton, Bruce F.; Ewert, John W.

2015-01-01

Messages conveying volcano alert level such as Watches and Warnings are designed to provide people with risk information before, during, and after eruptions. Information is communicated to people from volcano observatories and emergency management agencies and from informal sources and social and environmental cues. Any individual or agency can be both a message sender and a recipient and multiple messages received from multiple sources is the norm in a volcanic crisis. Significant challenges to developing effective warning systems for volcanic hazards stem from the great diversity in unrest, eruption, and post-eruption processes and the rapidly advancing digital technologies that people use to seek real-time risk information. Challenges also involve the need to invest resources before unrest to help people develop shared mental models of important risk factors. Two populations of people are the target of volcano notifications–ground- and aviation-based populations, and volcano warning systems must address both distinctly different populations.

Integrative assessment of multiple pesticides as risk factors for non-Hodgkin's lymphoma among men

PubMed Central

De Roos, A J; Zahm, S; Cantor, K; Weisenburger, D; Holmes, F; Burmeister, L; Blair, A

2003-01-01

Methods: During the 1980s, the National Cancer Institute conducted three case-control studies of NHL in the midwestern United States. These pooled data were used to examine pesticide exposures in farming as risk factors for NHL in men. The large sample size (n = 3417) allowed analysis of 47 pesticides simultaneously, controlling for potential confounding by other pesticides in the model, and adjusting the estimates based on a prespecified variance to make them more stable. Results: Reported use of several individual pesticides was associated with increased NHL incidence, including organophosphate insecticides coumaphos, diazinon, and fonofos, insecticides chlordane, dieldrin, and copper acetoarsenite, and herbicides atrazine, glyphosate, and sodium chlorate. A subanalysis of these "potentially carcinogenic" pesticides suggested a positive trend of risk with exposure to increasing numbers. Conclusion: Consideration of multiple exposures is important in accurately estimating specific effects and in evaluating realistic exposure scenarios. PMID:12937207

Social environments, risk-taking and injury in farm adolescents

PubMed Central

Pickett, William; Berg, Richard L; Marlenga, Barbara

2017-01-01

Background Farm environments are especially hazardous for young people. While much is known about acute physical causes of traumatic farm injury, little is known about social factors that may underlie their aetiology. Objectives In a nationally representative sample of young Canadians aged 11–15 years, we described and compared farm and non-farm adolescents in terms of the qualities of their social environments, engagement in overt multiple risk-taking as well as how such exposures relate aetiologically to their reported injury experiences. Methods Cross-sectional analysis of survey reports from the 2014 (Cycle 7) Canadian Health Behaviour in School-Aged Children study was conducted. Children (n=2567; 2534 weighted) who reported living or working on farms were matched within schools in a 1:1 ratio with children not living or working on farms. Scales examining quality of social environments and overt risk-taking were compared between the two groups, stratified by gender. We then related the occurrence of any serious injury to these social exposures in direct and interactive models. Results Farm and non-farm children reported social environments that were quite similar, with the exception of overt multiple risk-taking, which was demonstrably higher in farm children of both genders. Engagement in overt risk-taking, but not the other social environmental factors, was strongly and consistently associated with risks for serious injury in farm as well as non-farm children, particularly among males. Conclusions Study findings highlight the strength of associations between overt multiple risk-taking and injury among farm children. This appears to be a normative aspect of adolescent farm culture. PMID:28137978

Estimating the lifetime risk of cancer associated with multiple CT scans.

PubMed

Ivanov, V K; Kashcheev, V V; Chekin, S Yu; Menyaylo, A N; Pryakhin, E A; Tsyb, A F; Mettler, F A

2014-12-01

Multiple CT scans are often done on the same patient resulting in an increased risk of cancer. Prior publications have estimated risks on a population basis and often using an effective dose. Simply adding up the risks from single scans does not correctly account for the survival function. A methodology for estimating personal radiation risks attributed to multiple CT imaging using organ doses is presented in this article. The estimated magnitude of the attributable risk fraction for the possible development of radiation-induced cancer indicates the necessity for strong clinical justification when ordering multiple CT scans.

The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study.

PubMed

Lekman, Magnus; Hössjer, Ola; Andrews, Peter; Källberg, Henrik; Uvehag, Daniel; Charney, Dennis; Manji, Husseini; Rush, John A; McMahon, Francis J; Moore, Jason H; Kockum, Ingrid

2014-01-01

Genetic contributions to major depressive disorder (MDD) are thought to result from multiple genes interacting with each other. Different procedures have been proposed to detect such interactions. Which approach is best for explaining the risk of developing disease is unclear. This study sought to elucidate the genetic interaction landscape in candidate genes for MDD by conducting a SNP-SNP interaction analysis using an exhaustive search through 3,704 SNP-markers in 1,732 cases and 1,783 controls provided from the GAIN MDD study. We used three different methods to detect interactions, two logistic regressions models (multiplicative and additive) and one data mining and machine learning (MDR) approach. Although none of the interaction survived correction for multiple comparisons, the results provide important information for future genetic interaction studies in complex disorders. Among the 0.5% most significant observations, none had been reported previously for risk to MDD. Within this group of interactions, less than 0.03% would have been detectable based on main effect approach or an a priori algorithm. We evaluated correlations among the three different models and conclude that all three algorithms detected the same interactions to a low degree. Although the top interactions had a surprisingly large effect size for MDD (e.g. additive dominant model Puncorrected = 9.10E-9 with attributable proportion (AP) value = 0.58 and multiplicative recessive model with Puncorrected = 6.95E-5 with odds ratio (OR estimated from β3) value = 4.99) the area under the curve (AUC) estimates were low (< 0.54). Moreover, the population attributable fraction (PAF) estimates were also low (< 0.15). We conclude that the top interactions on their own did not explain much of the genetic variance of MDD. The different statistical interaction methods we used in the present study did not identify the same pairs of interacting markers. Genetic interaction studies may uncover previously unsuspected effects that could provide novel insights into MDD risk, but much larger sample sizes are needed before this strategy can be powerfully applied.

Improving measurement of injection drug risk behavior using item response theory.

PubMed

Janulis, Patrick

2014-03-01

Recent research highlights the multiple steps to preparing and injecting drugs and the resultant viral threats faced by drug users. This research suggests that more sensitive measurement of injection drug HIV risk behavior is required. In addition, growing evidence suggests there are gender differences in injection risk behavior. However, the potential for differential item functioning between genders has not been explored. To explore item response theory as an improved measurement modeling technique that provides empirically justified scaling of injection risk behavior and to examine for potential gender-based differential item functioning. Data is used from three studies in the National Institute on Drug Abuse's Criminal Justice Drug Abuse Treatment Studies. A two-parameter item response theory model was used to scale injection risk behavior and logistic regression was used to examine for differential item functioning. Item fit statistics suggest that item response theory can be used to scale injection risk behavior and these models can provide more sensitive estimates of risk behavior. Additionally, gender-based differential item functioning is present in the current data. Improved measurement of injection risk behavior using item response theory should be encouraged as these models provide increased congruence between construct measurement and the complexity of injection-related HIV risk. Suggestions are made to further improve injection risk behavior measurement. Furthermore, results suggest direct comparisons of composite scores between males and females may be misleading and future work should account for differential item functioning before comparing levels of injection risk behavior.

Methodological issues underlying multiple decrement life table analysis.

PubMed

Mode, C J; Avery, R C; Littman, G S; Potter, R G

1977-02-01

In this paper, the actuarial method of multiple decrement life table analysis of censored, longitudinal data is examined. The discussion is organized in terms of the first segment of usage of an intrauterine device. Weaknesses of the actuarial approach are pointed out, and an alternative approach, based on the classical model of competing risks, is proposed. Finally, the actuarial and the alternative method of analyzing censored data are compared, using data from the Taichung Medical Study on Intrauterine Devices.

A framework for quantifying net benefits of alternative prognostic models‡

PubMed Central

Rapsomaniki, Eleni; White, Ian R; Wood, Angela M; Thompson, Simon G

2012-01-01

New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21905066

BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface

PubMed Central

Lee, A J; Cunningham, A P; Kuchenbaecker, K B; Mavaddat, N; Easton, D F; Antoniou, A C

2014-01-01

Background: The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) is a risk prediction model that is used to compute probabilities of carrying mutations in the high-risk breast and ovarian cancer susceptibility genes BRCA1 and BRCA2, and to estimate the future risks of developing breast or ovarian cancer. In this paper, we describe updates to the BOADICEA model that extend its capabilities, make it easier to use in a clinical setting and yield more accurate predictions. Methods: We describe: (1) updates to the statistical model to include cancer incidences from multiple populations; (2) updates to the distributions of tumour pathology characteristics using new data on BRCA1 and BRCA2 mutation carriers and women with breast cancer from the general population; (3) improvements to the computational efficiency of the algorithm so that risk calculations now run substantially faster; and (4) updates to the model's web interface to accommodate these new features and to make it easier to use in a clinical setting. Results: We present results derived using the updated model, and demonstrate that the changes have a significant impact on risk predictions. Conclusion: All updates have been implemented in a new version of the BOADICEA web interface that is now available for general use: http://ccge.medschl.cam.ac.uk/boadicea/. PMID:24346285

Modeling Flow and Pollutant Transport in a Karst Watershed with SWAT

USDA-ARS?s Scientific Manuscript database

Karst hydrology is characterized by multiple springs, sinkholes, and losing streams resulting from acidic water percolating through limestone. These features provide direct connections between surface water and groundwater and increase the risk of groundwater, springs and stream contamination. Anthr...

Evaluating nonindigenous species management in a Bayesian networks derived relative risk framework for Padilla Bay, WA, USA.

PubMed

Herring, Carlie E; Stinson, Jonah; Landis, Wayne G

2015-10-01

Many coastal regions are encountering issues with the spread of nonindigenous species (NIS). In this study, we conducted a regional risk assessment using a Bayesian network relative risk model (BN-RRM) to analyze multiple vectors of NIS introductions to Padilla Bay, Washington, a National Estuarine Research Reserve. We had 3 objectives in this study. The 1st objective was to determine whether the BN-RRM could be used to calculate risk from NIS introductions for Padilla Bay. Our 2nd objective was to determine which regions and endpoints were at greatest risk from NIS introductions. Our 3rd objective was to incorporate a management option into the model and predict endpoint risk if it were to be implemented. Eradication can occur at different stages of NIS invasions, such as the elimination of these species before being introduced to the habitat or removal of the species after settlement. We incorporated the ballast water treatment management scenario into the model, observed the risk to the endpoints, and compared this risk with the initial risk estimates. The model results indicated that the southern portion of the bay was at greatest risk because of NIS. Changes in community composition, Dungeness crab, and eelgrass were the endpoints most at risk from NIS introductions. The currents node, which controls the exposure of NIS to the bay from the surrounding marine environment, was the parameter that had the greatest influence on risk. The ballast water management scenario displayed an approximate 1% reduction in risk in this Padilla Bay case study. The models we developed provide an adaptable template for decision makers interested in managing NIS in other coastal regions and large bodies of water. © 2015 SETAC.

Filling Terrorism Gaps: VEOs, Evaluating Databases, and Applying Risk Terrain Modeling to Terrorism

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

Hagan, Ross F.

2016-08-29

This paper aims to address three issues: the lack of literature differentiating terrorism and violent extremist organizations (VEOs), terrorism incident databases, and the applicability of Risk Terrain Modeling (RTM) to terrorism. Current open source literature and publicly available government sources do not differentiate between terrorism and VEOs; furthermore, they fail to define them. Addressing the lack of a comprehensive comparison of existing terrorism data sources, a matrix comparing a dozen terrorism databases is constructed, providing insight toward the array of data available. RTM, a method for spatial risk analysis at a micro level, has some applicability to terrorism research, particularlymore » for studies looking at risk indicators of terrorism. Leveraging attack data from multiple databases, combined with RTM, offers one avenue for closing existing research gaps in terrorism literature.« less

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

PubMed

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

2016-08-26

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

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.

Forecasting the onset of an allergic risk to poaceae in Nancy and Strasbourg (France) with different methods.

PubMed

Cassagne, E; Caillaud, P D; Besancenot, J P; Thibaudon, M

2007-10-01

Pollen of Poaceae is among the most allergenic pollen in Europe with pollen of birch. It is therefore useful to elaborate models to help pollen allergy sufferers. The objective of this study was to construct forecast models that could predict the first day characterized by a certain level of allergic risk called here the Starting Date of the Allergic Risk (SDAR). Models result from four forecast methods (three summing and one multiple regression analysis) used in the literature. They were applied on Nancy and Strasbourg from 1988 to 2005 and were tested on 2006. Mean Absolute Error and Actual forecast ability test are the parameters used to choose best models, assess and compare their accuracy. It was found, on the whole, that all the models presented a good forecast accuracy which was equivalent. They were all reliable and were used in order to forecast the SDAR in 2006 with contrasting results in forecasting precision.

Multiple environmental chemical exposures to lead, mercury and polychlorinated biphenyls among childbearing-aged women (NHANES 1999-2004): Body burden and risk factors.

PubMed

Thompson, Marcella Remer; Boekelheide, Kim

2013-02-01

Lead, mercury and polychlorinated biphenyls (PCBs) are neurotoxicants with intergenerational health consequences from maternal body burden and gestational exposures. Little is known about multiple chemical exposures among childbearing-aged women. To determine the percentage of women aged 16-49 of diverse races and ethnicities whose body burdens for all three xenobiotics were at or above the median; to identify mixed exposures; and to describe those women disproportionately burdened by two or more of these chemicals based on susceptibility- and exposure-related attributes, socioeconomic factors and race-ethnicity. Secondary data analysis of National Health and Nutrition Examination Survey (1999-2004). The best-fit logistic regression model without interactions contained 12 variables. Four risk factors associated with body burden were notable (P≤0.05). An exponential relationship was demonstrated with increasing age. Any fish consumption in past 30 days more than doubled the odds. Heavy alcohol consumption increased the relative risk. History of breastfeeding reduced this risk. These women were more likely to have two xenobiotics at or above the median than one. More than one-fifth of these childbearing-aged women had three xenobiotic levels at or above the median. These findings are among the first description of US childbearing-aged women's body burden and risk factors for multiple chemical exposures. This study supports increasing age, any fish consumption and heavy alcohol consumption as significant risk factors for body burden. History of breastfeeding lowered the body burden. Limited evidence was found of increased risk among minority women independent of other risk factors. Copyright © 2012 Elsevier Inc. All rights reserved.

Quantification of Treatment Effect Modification on Both an Additive and Multiplicative Scale

PubMed Central

Girerd, Nicolas; Rabilloud, Muriel; Pibarot, Philippe; Mathieu, Patrick; Roy, Pascal

2016-01-01

Background In both observational and randomized studies, associations with overall survival are by and large assessed on a multiplicative scale using the Cox model. However, clinicians and clinical researchers have an ardent interest in assessing absolute benefit associated with treatments. In older patients, some studies have reported lower relative treatment effect, which might translate into similar or even greater absolute treatment effect given their high baseline hazard for clinical events. Methods The effect of treatment and the effect modification of treatment were respectively assessed using a multiplicative and an additive hazard model in an analysis adjusted for propensity score in the context of coronary surgery. Results The multiplicative model yielded a lower relative hazard reduction with bilateral internal thoracic artery grafting in older patients (Hazard ratio for interaction/year = 1.03, 95%CI: 1.00 to 1.06, p = 0.05) whereas the additive model reported a similar absolute hazard reduction with increasing age (Delta for interaction/year = 0.10, 95%CI: -0.27 to 0.46, p = 0.61). The number needed to treat derived from the propensity score-adjusted multiplicative model was remarkably similar at the end of the follow-up in patients aged < = 60 and in patients >70. Conclusions The present example demonstrates that a lower treatment effect in older patients on a relative scale can conversely translate into a similar treatment effect on an additive scale due to large baseline hazard differences. Importantly, absolute risk reduction, either crude or adjusted, can be calculated from multiplicative survival models. We advocate for a wider use of the absolute scale, especially using additive hazard models, to assess treatment effect and treatment effect modification. PMID:27045168

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

PubMed

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

2011-05-20

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

The Ability of American Football Helmets to Manage Linear Acceleration With Repeated High-Energy Impacts.

PubMed

Cournoyer, Janie; Post, Andrew; Rousseau, Philippe; Hoshizaki, Blaine

2016-03-01

Football players can receive up to 1400 head impacts per season, averaging 6.3 impacts per practice and 14.3 impacts per game. A decrease in the capacity of a helmet to manage linear acceleration with multiple impacts could increase the risk of traumatic brain injury. To investigate the ability of football helmets to manage linear acceleration with multiple high-energy impacts. Descriptive laboratory study. Laboratory. We collected linear-acceleration data for 100 impacts at 6 locations on 4 helmets of different models currently used in football. Impacts 11 to 20 were compared with impacts 91 to 100 for each of the 6 locations. Linear acceleration was greater after multiple impacts (91-100) than after the first few impacts (11-20) for the front, front-boss, rear, and top locations. However, these differences are not clinically relevant as they do not affect the risk for head injury. American football helmet performance deteriorated with multiple impacts, but this is unlikely to be a factor in head-injury causation during a game or over a season.

Conditional Creation and Rescue of Nipbl-Deficiency in Mice Reveals Multiple Determinants of Risk for Congenital Heart Defects

PubMed Central

Jacobs, Russell E.; Lopez-Burks, Martha E.; Choi, Hojae; Wikenheiser, Jamie; Hallgrimsson, Benedikt; Jamniczky, Heather A.; Fraser, Scott E.; Lander, Arthur D.; Calof, Anne L.

2016-01-01

Elucidating the causes of congenital heart defects is made difficult by the complex morphogenesis of the mammalian heart, which takes place early in development, involves contributions from multiple germ layers, and is controlled by many genes. Here, we use a conditional/invertible genetic strategy to identify the cell lineage(s) responsible for the development of heart defects in a Nipbl-deficient mouse model of Cornelia de Lange Syndrome, in which global yet subtle transcriptional dysregulation leads to development of atrial septal defects (ASDs) at high frequency. Using an approach that allows for recombinase-mediated creation or rescue of Nipbl deficiency in different lineages, we uncover complex interactions between the cardiac mesoderm, endoderm, and the rest of the embryo, whereby the risk conferred by genetic abnormality in any one lineage is modified, in a surprisingly non-additive way, by the status of others. We argue that these results are best understood in the context of a model in which the risk of heart defects is associated with the adequacy of early progenitor cell populations relative to the sizes of the structures they must eventually form. PMID:27606604

Examining the association of abortion history and current mental health: A reanalysis of the National Comorbidity Survey using a common-risk-factors model.

PubMed

Steinberg, Julia R; Finer, Lawrence B

2011-01-01

Using the US National Comorbidity Survey (NCS), Coleman, Coyle, Shuping, and Rue (2009) published an analysis indicating that compared to women who had never had an abortion, women who had reported an abortion were at an increased risk of several anxiety, mood, and substance use disorders. Here, we show that those results are not replicable. That is, using the same data, sample, and codes as indicated by those authors, it is not possible to replicate the simple bivariate statistics testing the relationship of ever having had an abortion to each mental health disorder when no factors were controlled for in analyses (Table 2 in Coleman et al., 2009). Furthermore, among women with prior pregnancies in the NCS, we investigated whether having zero, one, or multiple abortions (abortion history) was associated with having a mood, anxiety, or substance use disorder at the time of the interview. In doing this, we tested two competing frameworks: the abortion-as-trauma versus the common-risk-factors approach. Our results support the latter framework. In the bivariate context when no other factors were included in models, abortion history was not related to having a mood disorder, but it was related to having an anxiety or substance use disorder. When prior mental health and violence experience were controlled in our models, no significant relation was found between abortion history and anxiety disorders. When these same risk factors and other background factors were controlled, women who had multiple abortions remained at an increased risk of having a substance use disorder compared to women who had no abortions, likely because we were unable to control for other risk factors associated with having an abortion and substance use. Policy, practice, and research should focus on assisting women at greatest risk of having unintended pregnancies and having poor mental health-those with violence in their lives and prior mental health problems. Copyright © 2010 Elsevier Ltd. All rights reserved.

D-dimer levels over time and the risk of recurrent venous thromboembolism: an update of the Vienna prediction model.

PubMed

Eichinger, Sabine; Heinze, Georg; Kyrle, Paul A

2014-01-02

Patients with unprovoked venous thromboembolism (VTE) can be stratified according to their recurrence risk based on their sex, the VTE location, and D-dimer measured 3 weeks after anticoagulation by the Vienna Prediction Model. We aimed to expand the model to also assess the recurrence risk from later points on. Five hundred and fifty-three patients with a first VTE were followed for a median of 68 months. We excluded patients with VTE provoked by a transient risk factor or female hormone intake, with a natural inhibitor deficiency, the lupus anticoagulant, or cancer. The study end point was recurrent VTE, which occurred in 150 patients. D-dimer levels did not substantially increase over time. Subdistribution hazard ratios (95% confidence intervals) dynamically changed from 2.43 (1.57 to 3.77) at 3 weeks to 2.27 (1.48 to 3.48), 1.98 (1.30 to 3.02) , and 1.73 (1.11 to 2.69) at 3, 9, and 15 months in men versus women, from 1.84 (1.00 to 3.43) to 1.68 (0.91 to 3.10), 1.49 (0.79 to 2.81) , and 1.44 (0.76 to 2.72) in patients with proximal deep vein thrombosis or pulmonary embolism compared with calf vein thrombosis, and from 1.30 (1.07 to 1.58) to 1.27 (1.06 to 1.51), 1.20 (1.02 to 1.41), and 1.13 (0.95 to 1.36) per doubling D-dimer. Using a dynamic landmark competing risks regression approach, we generated nomograms and a web-based calculator to calculate risk scores and recurrence rates from multiple times after anticoagulation. Risk of recurrent VTE after discontinuation of anticoagulation can be predicted from multiple random time points by integrating the patient's sex, location of first VTE, and serial D-dimer measurements.

Defining the role of polyamines in colon carcinogenesis using mouse models

PubMed Central

Ignatenko, Natalia A.; Gerner, Eugene W.; Besselsen, David G.

2011-01-01

Genetics and diet are both considered important risk determinants for colorectal cancer, a leading cause of death in the US and worldwide. Genetically engineered mouse (GEM) models have made a significant contribution to the characterization of colorectal cancer risk factors. Reliable, reproducible, and clinically relevant animal models help in the identification of the molecular events associated with disease progression and in the development of effictive treatment strategies. This review is focused on the use of mouse models for studying the role of polyamines in colon carcinogenesis. We describe how the available mouse models of colon cancer such as the multiple intestinal neoplasia (Min) mice and knockout genetic models facilitate understanding of the role of polyamines in colon carcinogenesis and help in the development of a rational strategy for colon cancer chemoprevention. PMID:21712957

Space Shuttle Propulsion Systems Plume Modeling and Simulation for the Lift-Off Computational Fluid Dynamics Model

NASA Technical Reports Server (NTRS)

Strutzenberg, L. L.; Dougherty, N. S.; Liever, P. A.; West, J. S.; Smith, S. D.

2007-01-01

This paper details advances being made in the development of Reynolds-Averaged Navier-Stokes numerical simulation tools, models, and methods for the integrated Space Shuttle Vehicle at launch. The conceptual model and modeling approach described includes the development of multiple computational models to appropriately analyze the potential debris transport for critical debris sources at Lift-Off. The conceptual model described herein involves the integration of propulsion analysis for the nozzle/plume flow with the overall 3D vehicle flowfield at Lift-Off. Debris Transport Analyses are being performed using the Shuttle Lift-Off models to assess the risk to the vehicle from Lift-Off debris and appropriately prioritized mitigation of potential debris sources to continue to reduce vehicle risk. These integrated simulations are being used to evaluate plume-induced debris environments where the multi-plume interactions with the launch facility can potentially accelerate debris particles toward the vehicle.

Allostatic load as a predictor of all-cause and cause-specific mortality in the general population: Evidence from the Scottish Health Survey.

PubMed

Robertson, Tony; Beveridge, Gayle; Bromley, Catherine

2017-01-01

Allostatic load is a multiple biomarker measure of physiological 'wear and tear' that has shown some promise as marker of overall physiological health, but its power as a risk predictor for mortality and morbidity is less well known. This study has used data from the 2003 Scottish Health Survey (SHeS) (nationally representative sample of Scottish population) linked to mortality records to assess how well allostatic load predicts all-cause and cause-specific mortality. From the sample, data from 4,488 men and women were available with mortality status at 5 and 9.5 (rounded to 10) years after sampling in 2003. Cox proportional hazard models estimated the risk of death (all-cause and the five major causes of death in the population) according to allostatic load score. Multiple imputation was used to address missing values in the dataset. Analyses were also adjusted for potential confounders (sex, age and deprivation). There were 258 and 618 deaths over the 5-year and 10-year follow-up period, respectively. In the fully-adjusted model, higher allostatic load (poorer physiological 'health') was not associated with an increased risk of all-cause mortality after 5 years (HR = 1.07, 95% CI 0.94 to 1.22; p = 0.269), but it was after 10 years (HR = 1.08, 95% CI 1.01 to 1.16; p = 0.026). Allostatic load was not associated with specific causes of death over the same follow-up period. In conclusions, greater physiological wear and tear across multiple physiological systems, as measured by allostatic load, is associated with an increased risk of death, but may not be as useful as a predictor for specific causes of death.

Allostatic load as a predictor of all-cause and cause-specific mortality in the general population: Evidence from the Scottish Health Survey

PubMed Central

Beveridge, Gayle; Bromley, Catherine

2017-01-01

Allostatic load is a multiple biomarker measure of physiological ‘wear and tear’ that has shown some promise as marker of overall physiological health, but its power as a risk predictor for mortality and morbidity is less well known. This study has used data from the 2003 Scottish Health Survey (SHeS) (nationally representative sample of Scottish population) linked to mortality records to assess how well allostatic load predicts all-cause and cause-specific mortality. From the sample, data from 4,488 men and women were available with mortality status at 5 and 9.5 (rounded to 10) years after sampling in 2003. Cox proportional hazard models estimated the risk of death (all-cause and the five major causes of death in the population) according to allostatic load score. Multiple imputation was used to address missing values in the dataset. Analyses were also adjusted for potential confounders (sex, age and deprivation). There were 258 and 618 deaths over the 5-year and 10-year follow-up period, respectively. In the fully-adjusted model, higher allostatic load (poorer physiological ‘health’) was not associated with an increased risk of all-cause mortality after 5 years (HR = 1.07, 95% CI 0.94 to 1.22; p = 0.269), but it was after 10 years (HR = 1.08, 95% CI 1.01 to 1.16; p = 0.026). Allostatic load was not associated with specific causes of death over the same follow-up period. In conclusions, greater physiological wear and tear across multiple physiological systems, as measured by allostatic load, is associated with an increased risk of death, but may not be as useful as a predictor for specific causes of death. PMID:28813505

Priority setting for invasive species management: risk assessment of Ponto-Caspian invasive species into Great Britain.

PubMed

Gallardo, Belinda; Aldridge, David C

2013-03-01

Invasive species drive important ecological and economic losses across wide geographies, with some regions supporting especially large numbers of nonnative species and consequently suffering relatively high impacts. For this reason, integrated risk assessments able to screen a suite of multiple invaders over large geographic areas are needed for prioritizing the allocation of limited resources. A total of 16 Ponto-Caspian aquatic species (10 gammarids, one isopod, two mysids, and three fishes) have been short-listed as recent or potential future invaders of British waters, whose introduction and spread is of high concern. In this study, we use multiple modeling techniques to assess their risk of establishment and spread into Great Britain. Climate suitability maps for these 16 species differed depending on the eastern and western distribution of species in continental Europe, which was related to their respective migration corridor: southern (Danube-Rhine rivers), and northern (Don and Volga rivers and Baltic lakes). Species whose suitability was high across large parts of Great Britain included four gammarids (Cheliorophium robustum, Dikerogammarus bispinosus, D. villosus, and Echinogammarus trichiatus) and a mysid (Hemimysis anomala). A climatic "heat map" combining the results of all 16 species together pointed to the southeast of England as the area most vulnerable to multiple invasions, particularly the Thames, Anglian, Severn, and Humber river basin districts. Regression models further suggested that alkalinity concentration > 120 mg/L in southeast England may favor the establishment of Ponto-Caspian invaders. The production of integrated risk maps for future invaders provides a means for the scientifically informed prioritization of resources toward particular species and geographic regions. Such tools have great utility in helping environmental managers focus efforts on the most effective prevention, management, and monitoring programs.

Scientific reporting is suboptimal for aspects that characterize genetic risk prediction studies: a review of published articles based on the Genetic RIsk Prediction Studies statement.

PubMed

Iglesias, Adriana I; Mihaescu, Raluca; Ioannidis, John P A; Khoury, Muin J; Little, Julian; van Duijn, Cornelia M; Janssens, A Cecile J W

2014-05-01

Our main objective was to raise awareness of the areas that need improvements in the reporting of genetic risk prediction articles for future publications, based on the Genetic RIsk Prediction Studies (GRIPS) statement. We evaluated studies that developed or validated a prediction model based on multiple DNA variants, using empirical data, and were published in 2010. A data extraction form based on the 25 items of the GRIPS statement was created and piloted. Forty-two studies met our inclusion criteria. Overall, more than half of the evaluated items (34 of 62) were reported in at least 85% of included articles. Seventy-seven percentage of the articles were identified as genetic risk prediction studies through title assessment, but only 31% used the keywords recommended by GRIPS in the title or abstract. Seventy-four percentage mentioned which allele was the risk variant. Overall, only 10% of the articles reported all essential items needed to perform external validation of the risk model. Completeness of reporting in genetic risk prediction studies is adequate for general elements of study design but is suboptimal for several aspects that characterize genetic risk prediction studies such as description of the model construction. Improvements in the transparency of reporting of these aspects would facilitate the identification, replication, and application of genetic risk prediction models. Copyright © 2014 Elsevier Inc. All rights reserved.

Medical resource inventory model for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport

PubMed Central

Pan, Wei; Guo, Ying; Jin, Lei; Liao, ShuJie

2017-01-01

With the high accident rate of civil aviation, medical resource inventory becomes more important for emergency management at the airport. Meanwhile, medical products usually are time-sensitive and short lifetime. Moreover, we find that the optimal medical resource inventory depends on multiple factors such as different risk preferences, the material shelf life and so on. Thus, it becomes very complex in a real-life environment. According to this situation, we construct medical resource inventory decision model for emergency preparation at the airport. Our model is formulated in such a way as to simultaneously consider uncertain demand, stochastic occurrence time and different risk preferences. For solving this problem, a new programming is developed. Finally, a numerical example is presented to illustrate the proposed method. The results show that it is effective for determining the optimal medical resource inventory for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport. PMID:28931007

Medical resource inventory model for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport.

PubMed

Pan, Wei; Guo, Ying; Jin, Lei; Liao, ShuJie

2017-01-01

With the high accident rate of civil aviation, medical resource inventory becomes more important for emergency management at the airport. Meanwhile, medical products usually are time-sensitive and short lifetime. Moreover, we find that the optimal medical resource inventory depends on multiple factors such as different risk preferences, the material shelf life and so on. Thus, it becomes very complex in a real-life environment. According to this situation, we construct medical resource inventory decision model for emergency preparation at the airport. Our model is formulated in such a way as to simultaneously consider uncertain demand, stochastic occurrence time and different risk preferences. For solving this problem, a new programming is developed. Finally, a numerical example is presented to illustrate the proposed method. The results show that it is effective for determining the optimal medical resource inventory for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport.

A regression tree for identifying combinations of fall risk factors associated to recurrent falling: a cross-sectional elderly population-based study.

PubMed

Kabeshova, A; Annweiler, C; Fantino, B; Philip, T; Gromov, V A; Launay, C P; Beauchet, O

2014-06-01

Regression tree (RT) analyses are particularly adapted to explore the risk of recurrent falling according to various combinations of fall risk factors compared to logistic regression models. The aims of this study were (1) to determine which combinations of fall risk factors were associated with the occurrence of recurrent falls in older community-dwellers, and (2) to compare the efficacy of RT and multiple logistic regression model for the identification of recurrent falls. A total of 1,760 community-dwelling volunteers (mean age ± standard deviation, 71.0 ± 5.1 years; 49.4 % female) were recruited prospectively in this cross-sectional study. Age, gender, polypharmacy, use of psychoactive drugs, fear of falling (FOF), cognitive disorders and sad mood were recorded. In addition, the history of falls within the past year was recorded using a standardized questionnaire. Among 1,760 participants, 19.7 % (n = 346) were recurrent fallers. The RT identified 14 nodes groups and 8 end nodes with FOF as the first major split. Among participants with FOF, those who had sad mood and polypharmacy formed the end node with the greatest OR for recurrent falls (OR = 6.06 with p < 0.001). Among participants without FOF, those who were male and not sad had the lowest OR for recurrent falls (OR = 0.25 with p < 0.001). The RT correctly classified 1,356 from 1,414 non-recurrent fallers (specificity = 95.6 %), and 65 from 346 recurrent fallers (sensitivity = 18.8 %). The overall classification accuracy was 81.0 %. The multiple logistic regression correctly classified 1,372 from 1,414 non-recurrent fallers (specificity = 97.0 %), and 61 from 346 recurrent fallers (sensitivity = 17.6 %). The overall classification accuracy was 81.4 %. Our results show that RT may identify specific combinations of risk factors for recurrent falls, the combination most associated with recurrent falls involving FOF, sad mood and polypharmacy. The FOF emerged as the risk factor strongly associated with recurrent falls. In addition, RT and multiple logistic regression were not sensitive enough to identify the majority of recurrent fallers but appeared efficient in detecting individuals not at risk of recurrent falls.

Developmental dyslexia: predicting individual risk.

PubMed

Thompson, Paul A; Hulme, Charles; Nash, Hannah M; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J

2015-09-01

Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6 months (T1) at approximately annual intervals on tasks tapping cognitive, language, and executive-motor skills. The children were recruited to three groups: children at family risk of dyslexia, children with concerns regarding speech, and language development at 3;06 years and controls considered to be typically developing. At 8 years, children were classified as 'dyslexic' or not. Logistic regression models were used to predict the individual risk of dyslexia and to investigate how risk factors accumulate to predict poor literacy outcomes. Family-risk status was a stronger predictor of dyslexia at 8 years than low language in preschool. Additional predictors in the preschool years include letter knowledge, phonological awareness, rapid automatized naming, and executive skills. At the time of school entry, language skills become significant predictors, and motor skills add a small but significant increase to the prediction probability. We present classification accuracy using different probability cutoffs for logistic regression models and ROC curves to highlight the accumulation of risk factors at the individual level. Dyslexia is the outcome of multiple risk factors and children with language difficulties at school entry are at high risk. Family history of dyslexia is a predictor of literacy outcome from the preschool years. However, screening does not reach an acceptable clinical level until close to school entry when letter knowledge, phonological awareness, and RAN, rather than family risk, together provide good sensitivity and specificity as a screening battery. © 2015 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.

Assessing the risk of ships striking large whales in marine spatial planning.

PubMed

Redfern, J V; McKenna, M F; Moore, T J; Calambokidis, J; Deangelis, M L; Becker, E A; Barlow, J; Forney, K A; Fiedler, P C; Chivers, S J

2013-04-01

Marine spatial planning provides a comprehensive framework for managing multiple uses of the marine environment and has the potential to minimize environmental impacts and reduce conflicts among users. Spatially explicit assessments of the risks to key marine species from human activities are a requirement of marine spatial planning. We assessed the risk of ships striking humpback (Megaptera novaeangliae), blue (Balaenoptera musculus), and fin (Balaenoptera physalus) whales in alternative shipping routes derived from patterns of shipping traffic off Southern California (U.S.A.). Specifically, we developed whale-habitat models and assumed ship-strike risk for the alternative shipping routes was proportional to the number of whales predicted by the models to occur within each route. This definition of risk assumes all ships travel within a single route. We also calculated risk assuming ships travel via multiple routes. We estimated the potential for conflict between shipping and other uses (military training and fishing) due to overlap with the routes. We also estimated the overlap between shipping routes and protected areas. The route with the lowest risk for humpback whales had the highest risk for fin whales and vice versa. Risk to both species may be ameliorated by creating a new route south of the northern Channel Islands and spreading traffic between this new route and the existing route in the Santa Barbara Channel. Creating a longer route may reduce the overlap between shipping and other uses by concentrating shipping traffic. Blue whales are distributed more evenly across our study area than humpback and fin whales; thus, risk could not be ameliorated by concentrating shipping traffic in any of the routes we considered. Reducing ship-strike risk for blue whales may be necessary because our estimate of the potential number of strikes suggests that they are likely to exceed allowable levels of anthropogenic impacts established under U.S. laws. Conservation Biology © 2013 Society for Conservation Biology No claim to original US government works.

Quantifying and modeling long-range cross correlations in multiple time series with applications to world stock indices

NASA Astrophysics Data System (ADS)

Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H. Eugene

2011-04-01

We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes “bad news” for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.

Quantifying and modeling long-range cross correlations in multiple time series with applications to world stock indices.

PubMed

Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H Eugene

2011-04-01

We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes "bad news" for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.

Resilience moderates the risk of depression and anxiety symptoms on suicidal ideation in patients with depression and/or anxiety disorders.

PubMed

Min, Jung-Ah; Lee, Chang-Uk; Chae, Jeong-Ho

2015-01-01

Few studies have investigated the role of protective factors for suicidal ideation, which include resilience and social support among psychiatric patients with depression and/or anxiety disorders who are at increased risk of suicide. Demographic data, history of childhood maltreatment, and levels of depression, anxiety, problematic alcohol use, resilience, perceived social support, and current suicidal ideation were collected from a total of 436 patients diagnosed with depression and/or anxiety disorders. Hierarchical multiple logistic regression analyses were used to identify the independent and interaction effects of potentially influencing factors. Moderate-severe suicidal ideation was reported in 24.5% of our sample. After controlling for relevant covariates, history of emotional neglect and sexual abuse, low resilience, and high depression and anxiety symptoms were sequentially included in the model. In the final model, high depression (adjusted odds ratio (OR)=9.33, confidence interval (CI) 3.99-21.77) and anxiety (adjusted OR=2.62, CI=1.24-5.53) were independently associated with moderate-severe suicidal ideation among risk factors whereas resilience was not. In the multiple logistic regression model that examined interaction effects between risk and protective factors, the interactions between resilience and depression (p<.001) and between resilience and anxiety were significant (p=.021). A higher level of resilience was protective against moderate-severe suicide ideation among those with higher levels of depression or anxiety symptoms. Our results indicate that resilience potentially moderates the risk of depression and anxiety symptoms on suicidal ideation in patients with depression and/or anxiety disorders. Assessment of resilience and intervention focused on resilience enhancement is suggested for suicide prevention. Copyright © 2014 Elsevier Inc. All rights reserved.

Gender-specific differences in high-risk sexual behaviors among methamphetamine users in Myanmar-China border city, Muse, Myanmar: who is at risk?

PubMed

Saw, Yu Mon; Saw, Thu Nandar; Chan, Nyein; Cho, Su Myat; Jimba, Masamine

2018-02-01

Methamphetamine (MA) use is a significant public health concern due to its negative effects on health. However, to date, no epidemiological research has examined high-risk sexual behaviors (inconsistent condom use, having multiple sexual partners and having a history of sexually transmitted infections) among MA users. This topic is particularly important in Myanmar, which is recognized as one of the key MA production countries in the Southeast Asia region. Therefore, this study examined factors associated with high-risk sexual behaviors among MA users in Muse city, Myanmar. A community-based cross-sectional study was conducted from January to March 2013 in Muse city, Northern Shan State, Myanmar. In total, 1183 MA users (772 male; 411 female) were recruited using respondent-driven sampling and a computer assisted self-interviewing method. Generalized estimating equation models were used to examine factors associated with high-risk sexual behaviors. A large proportion of MA users engaged in high-risk sexual behaviors (inconsistent condom use: males, 90.7%, females, 85.2%; multiple sexual partners: males, 94.2%, females, 47.2%; and history of STIs: males, 55.7%, females, 56.0%). Among males, being a multiple stimulants drug user (adjusted odds ratio [AOR] =1.77; 95% confidence interval [CI] =1.30-2.41) and being a client of sex workers (AOR = 1.41; 95% CI = 1.08-1.83) were risk factors for engaging in high-risk sexual behaviors. Among females, being a migrant worker (AOR = 2.70; 95% CI = 1.86-3.93) and being employed (AOR = 1.57; 95% CI = 1.13-2.18) were risk factors for engaging in high-risk sexual behaviors as well. High-risk sexual behaviors were particularly pronounced among both male and female MA users. MA prevention programs that reflect gender considerations should be developed to pay more attention to vulnerable populations such as migrants, clients of sex workers, and less educated female MA users.

Prediction of breast cancer risk based on profiling with common genetic variants.

PubMed

Mavaddat, Nasim; Pharoah, Paul D P; Michailidou, Kyriaki; Tyrer, Jonathan; Brook, Mark N; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Dunning, Alison M; Shah, Mitul; Luben, Robert; Brown, Judith; Bojesen, Stig E; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Czene, Kamila; Darabi, Hatef; Eriksson, Mikael; Peto, Julian; Dos-Santos-Silva, Isabel; Dudbridge, Frank; Johnson, Nichola; Schmidt, Marjanka K; Broeks, Annegien; Verhoef, Senno; Rutgers, Emiel J; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J; Figueroa, Jonine; Chanock, Stephen J; Brinton, Louise; Lissowska, Jolanta; Couch, Fergus J; Olson, Janet E; Vachon, Celine; Pankratz, Vernon S; Lambrechts, Diether; Wildiers, Hans; Van Ongeval, Chantal; van Limbergen, Erik; Kristensen, Vessela; Grenaker Alnæs, Grethe; Nord, Silje; Borresen-Dale, Anne-Lise; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Fasching, Peter A; Haeberle, Lothar; Ekici, Arif B; Beckmann, Matthias W; Burwinkel, Barbara; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Trentham-Dietz, Amy; Newcomb, Polly; Titus, Linda; Egan, Kathleen M; Hunter, David J; Lindstrom, Sara; Tamimi, Rulla M; Kraft, Peter; Rahman, Nazneen; Turnbull, Clare; Renwick, Anthony; Seal, Sheila; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Benitez, Javier; Pilar Zamora, M; Arias Perez, Jose Ignacio; Menéndez, Primitiva; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katarzyna; Bogdanova, Natalia V; Antonenkova, Natalia N; Dörk, Thilo; Anton-Culver, Hoda; Neuhausen, Susan L; Ziogas, Argyrios; Bernstein, Leslie; Devilee, Peter; Tollenaar, Robert A E M; Seynaeve, Caroline; van Asperen, Christi J; Cox, Angela; Cross, Simon S; Reed, Malcolm W R; Khusnutdinova, Elza; Bermisheva, Marina; Prokofyeva, Darya; Takhirova, Zalina; Meindl, Alfons; Schmutzler, Rita K; Sutter, Christian; Yang, Rongxi; Schürmann, Peter; Bremer, Michael; Christiansen, Hans; Park-Simon, Tjoung-Won; Hillemanns, Peter; Guénel, Pascal; Truong, Thérèse; Menegaux, Florence; Sanchez, Marie; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Pensotti, Valeria; Hopper, John L; Tsimiklis, Helen; Apicella, Carmel; Southey, Melissa C; Brauch, Hiltrud; Brüning, Thomas; Ko, Yon-Dschun; Sigurdson, Alice J; Doody, Michele M; Hamann, Ute; Torres, Diana; Ulmer, Hans-Ulrich; Försti, Asta; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Marie Mulligan, Anna; Chenevix-Trench, Georgia; Balleine, Rosemary; Giles, Graham G; Milne, Roger L; McLean, Catriona; Lindblom, Annika; Margolin, Sara; Haiman, Christopher A; Henderson, Brian E; Schumacher, Fredrick; Le Marchand, Loic; Eilber, Ursula; Wang-Gohrke, Shan; Hooning, Maartje J; Hollestelle, Antoinette; van den Ouweland, Ans M W; Koppert, Linetta B; Carpenter, Jane; Clarke, Christine; Scott, Rodney; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Brenner, Hermann; Arndt, Volker; Stegmaier, Christa; Karina Dieffenbach, Aida; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Offit, Kenneth; Vijai, Joseph; Robson, Mark; Rau-Murthy, Rohini; Dwek, Miriam; Swann, Ruth; Annie Perkins, Katherine; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Eccles, Diana M; Tapper, William J; Rafiq, Sajjad; John, Esther M; Whittemore, Alice S; Slager, Susan; Yannoukakos, Drakoulis; Toland, Amanda E; Yao, Song; Zheng, Wei; Halverson, Sandra L; González-Neira, Anna; Pita, Guillermo; Rosario Alonso, M; Álvarez, Nuria; Herrero, Daniel; Tessier, Daniel C; Vincent, Daniel; Bacot, Francois; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Maranian, Mel; Healey, Catherine S; Simard, Jacques; Hall, Per; Easton, Douglas F; Garcia-Closas, Montserrat

2015-05-01

Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report. © The Author 2015. Published by Oxford University Press.

Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants

PubMed Central

Pharoah, Paul D. P.; Michailidou, Kyriaki; Tyrer, Jonathan; Brook, Mark N.; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Dunning, Alison M.; Shah, Mitul; Luben, Robert; Brown, Judith; Bojesen, Stig E.; Nordestgaard, Børge G.; Nielsen, Sune F.; Flyger, Henrik; Czene, Kamila; Darabi, Hatef; Eriksson, Mikael; Peto, Julian; dos-Santos-Silva, Isabel; Dudbridge, Frank; Johnson, Nichola; Schmidt, Marjanka K.; Broeks, Annegien; Verhoef, Senno; Rutgers, Emiel J.; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J.; Figueroa, Jonine; Chanock, Stephen J.; Brinton, Louise; Lissowska, Jolanta; Couch, Fergus J.; Olson, Janet E.; Vachon, Celine; Pankratz, Vernon S.; Lambrechts, Diether; Wildiers, Hans; Van Ongeval, Chantal; van Limbergen, Erik; Kristensen, Vessela; Grenaker Alnæs, Grethe; Nord, Silje; Borresen-Dale, Anne-Lise; Nevanlinna, Heli; Muranen, Taru A.; Aittomäki, Kristiina; Blomqvist, Carl; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Fasching, Peter A.; Haeberle, Lothar; Ekici, Arif B.; Beckmann, Matthias W.; Burwinkel, Barbara; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Trentham-Dietz, Amy; Newcomb, Polly; Titus, Linda; Egan, Kathleen M.; Hunter, David J.; Lindstrom, Sara; Tamimi, Rulla M.; Kraft, Peter; Rahman, Nazneen; Turnbull, Clare; Renwick, Anthony; Seal, Sheila; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Benitez, Javier; Pilar Zamora, M.; Arias Perez, Jose Ignacio; Menéndez, Primitiva; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katarzyna; Bogdanova, Natalia V.; Antonenkova, Natalia N.; Dörk, Thilo; Anton-Culver, Hoda; Neuhausen, Susan L.; Ziogas, Argyrios; Bernstein, Leslie; Devilee, Peter; Tollenaar, Robert A. E. M.; Seynaeve, Caroline; van Asperen, Christi J.; Cox, Angela; Cross, Simon S.; Reed, Malcolm W. R.; Khusnutdinova, Elza; Bermisheva, Marina; Prokofyeva, Darya; Takhirova, Zalina; Meindl, Alfons; Schmutzler, Rita K.; Sutter, Christian; Yang, Rongxi; Schürmann, Peter; Bremer, Michael; Christiansen, Hans; Park-Simon, Tjoung-Won; Hillemanns, Peter; Guénel, Pascal; Truong, Thérèse; Menegaux, Florence; Sanchez, Marie; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Pensotti, Valeria; Hopper, John L.; Tsimiklis, Helen; Apicella, Carmel; Southey, Melissa C.; Brauch, Hiltrud; Brüning, Thomas; Ko, Yon-Dschun; Sigurdson, Alice J.; Doody, Michele M.; Hamann, Ute; Torres, Diana; Ulmer, Hans-Ulrich; Försti, Asta; Sawyer, Elinor J.; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Marie Mulligan, Anna; Chenevix-Trench, Georgia; Balleine, Rosemary; Giles, Graham G.; Milne, Roger L.; McLean, Catriona; Lindblom, Annika; Margolin, Sara; Haiman, Christopher A.; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Eilber, Ursula; Wang-Gohrke, Shan; Hooning, Maartje J.; Hollestelle, Antoinette; van den Ouweland, Ans M. W.; Koppert, Linetta B.; Carpenter, Jane; Clarke, Christine; Scott, Rodney; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Brenner, Hermann; Arndt, Volker; Stegmaier, Christa; Karina Dieffenbach, Aida; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Offit, Kenneth; Vijai, Joseph; Robson, Mark; Rau-Murthy, Rohini; Dwek, Miriam; Swann, Ruth; Annie Perkins, Katherine; Goldberg, Mark S.; Labrèche, France; Dumont, Martine; Eccles, Diana M.; Tapper, William J.; Rafiq, Sajjad; John, Esther M.; Whittemore, Alice S.; Slager, Susan; Yannoukakos, Drakoulis; Toland, Amanda E.; Yao, Song; Zheng, Wei; Halverson, Sandra L.; González-Neira, Anna; Pita, Guillermo; Rosario Alonso, M.; Álvarez, Nuria; Herrero, Daniel; Tessier, Daniel C.; Vincent, Daniel; Bacot, Francois; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Maranian, Mel; Healey, Catherine S.; Simard, Jacques; Hall, Per; Easton, Douglas F.; Garcia-Closas, Montserrat

2015-01-01

Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report. PMID:25855707

Evaluating Pharmacokinetic and Pharmacodynamic Interactions with Computational Models in Cumulative Risk Assessment

EPA Science Inventory

Simultaneous or sequential exposure to multiple chemicals may cause interactions in the pharmacokinetics (PK) and/or pharmacodynamics (PD) of the individual chemicals. Such interactions can cause modification of the internal or target dose/response of one chemical in the mixture ...

Modeling survival: application of the Andersen-Gill model to Yellowstone grizzly bears

USGS Publications Warehouse

Johnson, Christopher J.; Boyce, Mark S.; Schwartz, Charles C.; Haroldson, Mark A.

2004-01-01

 Wildlife ecologists often use the Kaplan-Meier procedure or Cox proportional hazards model to estimate survival rates, distributions, and magnitude of risk factors. The Andersen-Gill formulation (A-G) of the Cox proportional hazards model has seen limited application to mark-resight data but has a number of advantages, including the ability to accommodate left-censored data, time-varying covariates, multiple events, and discontinuous intervals of risks. We introduce the A-G model including structure of data, interpretation of results, and assessment of assumptions. We then apply the model to 22 years of radiotelemetry data for grizzly bears (Ursus arctos) of the Greater Yellowstone Grizzly Bear Recovery Zone in Montana, Idaho, and Wyoming, USA. We used Akaike's Information Criterion (AICc) and multi-model inference to assess a number of potentially useful predictive models relative to explanatory covariates for demography, human disturbance, and habitat. Using the most parsimonious models, we generated risk ratios, hypothetical survival curves, and a map of the spatial distribution of high-risk areas across the recovery zone. Our results were in agreement with past studies of mortality factors for Yellowstone grizzly bears. Holding other covariates constant, mortality was highest for bears that were subjected to repeated management actions and inhabited areas with high road densities outside Yellowstone National Park. Hazard models developed with covariates descriptive of foraging habitats were not the most parsimonious, but they suggested that high-elevation areas offered lower risks of mortality when compared to agricultural areas.

Is Hypovitaminosis D One of the Environmental Risk Factors for Multiple Sclerosis?

ERIC Educational Resources Information Center

Pierrot-Deseilligny, Charles; Souberbielle, Jean-Claude

2010-01-01

The role of hypovitaminosis D as a possible risk factor for multiple sclerosis is reviewed. First, it is emphasized that hypovitaminosis D could be only one of the risk factors for multiple sclerosis and that numerous other environmental and genetic risk factors appear to interact and combine to trigger the disease. Secondly, the classical…

High EDSS can predict risk for upper urinary tract damage in patients with multiple sclerosis.

PubMed

Ineichen, Benjamin V; Schneider, Marc P; Hlavica, Martin; Hagenbuch, Niels; Linnebank, Michael; Kessler, Thomas M

2018-04-01

Neurogenic lower urinary tract dysfunction (NLUTD) is very common in patients with multiple sclerosis (MS), and it might jeopardize renal function and thereby increase mortality. Although there are well-known urodynamic risk factors for upper urinary tract damage, no clinical prediction parameters are available. We aimed to assess clinical parameters potentially predicting urodynamic risk factors for upper urinary tract damage. A consecutive series of 141 patients with MS referred from neurologists for primary neuro-urological work-up including urodynamics were prospectively evaluated. Clinical parameters taken into account were age, sex, duration, and clinical course of MS and Expanded Disability Status Scale (EDSS). Multivariate modeling revealed EDSS as a clinical parameter significantly associated with urodynamic risk factors for upper urinary tract damage (odds ratio = 1.34, 95% confidence interval (CI) = 1.06-1.71, p = 0.02). Using receiver operator characteristic (ROC) curves, an EDSS of 5.0 as cutoff showed a sensitivity of 86%-87% and a specificity of 52% for at least one urodynamic risk factor for upper urinary tract damage. High EDSS is significantly associated with urodynamic risk factors for upper urinary tract damage and allows a risk-dependent stratification in daily neurological clinical practice to identify MS patients requiring further neuro-urological assessment and treatment.

Geographic Differences in Genetic Susceptibility to IgA Nephropathy: GWAS Replication Study and Geospatial Risk Analysis

PubMed Central

Kiryluk, Krzysztof; Li, Yifu; Sanna-Cherchi, Simone; Rohanizadegan, Mersedeh; Suzuki, Hitoshi; Eitner, Frank; Snyder, Holly J.; Choi, Murim; Hou, Ping; Scolari, Francesco; Izzi, Claudia; Gigante, Maddalena; Gesualdo, Loreto; Savoldi, Silvana; Amoroso, Antonio; Cusi, Daniele; Zamboli, Pasquale; Julian, Bruce A.; Novak, Jan; Wyatt, Robert J.; Mucha, Krzysztof; Perola, Markus; Kristiansson, Kati; Viktorin, Alexander; Magnusson, Patrik K.; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Stefansson, Kari; Boland, Anne; Metzger, Marie; Thibaudin, Lise; Wanner, Christoph; Jager, Kitty J.; Goto, Shin; Maixnerova, Dita; Karnib, Hussein H.; Nagy, Judit; Panzer, Ulf; Xie, Jingyuan; Chen, Nan; Tesar, Vladimir; Narita, Ichiei; Berthoux, Francois; Floege, Jürgen; Stengel, Benedicte; Zhang, Hong; Lifton, Richard P.; Gharavi, Ali G.

2012-01-01

IgA nephropathy (IgAN), major cause of kidney failure worldwide, is common in Asians, moderately prevalent in Europeans, and rare in Africans. It is not known if these differences represent variation in genes, environment, or ascertainment. In a recent GWAS, we localized five IgAN susceptibility loci on Chr.6p21 (HLA-DQB1/DRB1, PSMB9/TAP1, and DPA1/DPB2 loci), Chr.1q32 (CFHR3/R1 locus), and Chr.22q12 (HORMAD2 locus). These IgAN loci are associated with risk of other immune-mediated disorders such as type I diabetes, multiple sclerosis, or inflammatory bowel disease. We tested association of these loci in eight new independent cohorts of Asian, European, and African-American ancestry (N = 4,789), followed by meta-analysis with risk-score modeling in 12 cohorts (N = 10,755) and geospatial analysis in 85 world populations. Four susceptibility loci robustly replicated and all five loci were genome-wide significant in the combined cohort (P = 5×10−32–3×10−10), with heterogeneity detected only at the PSMB9/TAP1 locus (I2 = 0.60). Conditional analyses identified two new independent risk alleles within the HLA-DQB1/DRB1 locus, defining multiple risk and protective haplotypes within this interval. We also detected a significant genetic interaction, whereby the odds ratio for the HORMAD2 protective allele was reversed in homozygotes for a CFHR3/R1 deletion (P = 2.5×10−4). A seven–SNP genetic risk score, which explained 4.7% of overall IgAN risk, increased sharply with Eastward and Northward distance from Africa (r = 0.30, P = 3×10−128). This model paralleled the known East–West gradient in disease risk. Moreover, the prediction of a South–North axis was confirmed by registry data showing that the prevalence of IgAN–attributable kidney failure is increased in Northern Europe, similar to multiple sclerosis and type I diabetes. Variation at IgAN susceptibility loci correlates with differences in disease prevalence among world populations. These findings inform genetic, biological, and epidemiological investigations of IgAN and permit cross-comparison with other complex traits that share genetic risk loci and geographic patterns with IgAN. PMID:22737082

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

PubMed

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

2010-08-15

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

Association of Antenatal Corticosteroids with Mortality, Morbidity, and Neurodevelopmental Outcomes in Extremely Preterm Multiple Gestation Infants

PubMed Central

Boghossian, Nansi S.; McDonald, Scott A.; Bell, Edward F.; Carlo, Waldemar A.; Brumbaugh, Jane E.; Stoll, Barbara J.; Laptook, Abbot R.; Shankaran, Seetha; Walsh, Michele C.; Das, Abhik; Higgins, Rosemary D.

2017-01-01

Importance Little is known about the benefits of antenatal corticosteroids on extremely preterm multiples. Objective To examine in extremely preterm multiples if use of antenatal corticosteroids is associated with improvement in major outcomes. Design, Setting, and Participants Infants with gestational age 22–28 weeks born at an NICHD Neonatal Research Network center (1998–2013) were studied. Generalized estimating equation models were used to generate adjusted relative risks (aRR) controlling for important maternal and neonatal variables. Main Outcome Measures In-hospital mortality, the composite outcome of neurodevelopmental impairment at 18–22 months’ corrected age or death before assessment. Results Of 6925 multiple-birth infants, 6094 (88%) were born to women who received antenatal corticosteroids. In-hospital mortality was lower among infants with exposure to antenatal corticosteroids vs no exposure (aRR=0.87, 95% CI 0.78–0.96). Neurodevelopmental impairment or death was not significantly lower among those exposed to antenatal corticosteroids vs no exposure (aRR=0.93, 95% CI 0.84–1.03). Other adverse outcomes that occurred less frequently among infants of women receiving antenatal corticosteroids included severe intraventricular hemorrhage (aRR=0.68, 95% CI 0.58–0.78) and the combined outcomes of necrotizing enterocolitis or death and severe intraventricular hemorrhage or death. Subgroup analyses indicated that exposure to antenatal corticosteroids was associated with a lower risk of mortality and the composite of neurodevelopmental impairment or mortality among non-small for gestational age multiples (aRR=0.82, 95% CI 0.74–0.92 and aRR=0.89, 95% CI 0.80–0.98, respectively) and a higher risk among small for gestational age multiples (aRR=1.40, 95% CI 1.02–1.93 and aRR=1.62, 95% CI 1.22–2.16, respectively). Antenatal corticosteroids were associated with higher neurodevelopmental impairment or mortality among multiple-birth infants of mothers with diabetes (aRR=1.55, 95% CI 1.00–2.38) but not among infants of mothers without diabetes (aRR=0.91, 95% CI 0.83–1.01). Conclusion In extremely preterm multiples, exposure to antenatal corticosteroids compared with no exposure was associated with a lower risk of mortality with no significant differences for the composite of neurodevelopmental impairment or death. Future research should investigate the increased risks of mortality and the composite of neurodevelopmental impairment or death associated with exposure to corticosteroids among small for gestational age multiples. PMID:27088897

Quantifying and Reducing Uncertainty in Correlated Multi-Area Short-Term Load Forecasting

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

Sun, Yannan; Hou, Zhangshuan; Meng, Da

2016-07-17

In this study, we represent and reduce the uncertainties in short-term electric load forecasting by integrating time series analysis tools including ARIMA modeling, sequential Gaussian simulation, and principal component analysis. The approaches are mainly focusing on maintaining the inter-dependency between multiple geographically related areas. These approaches are applied onto cross-correlated load time series as well as their forecast errors. Multiple short-term prediction realizations are then generated from the reduced uncertainty ranges, which are useful for power system risk analyses.

A Critique of Recent Epidemiologic Studies of Cancer Mortality Among Nuclear Workers.

PubMed

Scott, Bobby R

2018-01-01

Current justification by linear no-threshold (LNT) cancer risk model advocates for its use in low-dose radiation risk assessment is now mainly based on results from flawed and unreliable epidemiologic studies that manufacture small risk increases (ie, phantom risks). Four such studies of nuclear workers, essentially carried out by the same group of epidemiologists, are critiqued in this article. Three of the studies that forcibly applied the LNT model (inappropriate null hypothesis) to cancer mortality data and implicated increased mortality risk from any radiation exposure, no matter how small the dose, are demonstrated to manufacture risk increases for doses up to 100 mSv (or 100 mGy). In a study where risk reduction (hormetic effect/adaptive response) was implicated for nuclear workers, it was assumed by the researchers to relate to a "strong healthy worker effect" with no consideration of the possibility that low radiation doses may help prevent cancer mortality (which is consistent with findings from basic radiobiological research). It was found with basic research that while large radiation doses suppress our multiple natural defenses (barriers) against cancer, these barriers are enhanced by low radiation doses, thereby decreasing cancer risk, essentially rendering the LNT model to be inconsistent with the data.

The Role of Dosimetry in High-Quality EMI Risk Assessment

DTIC Science & Technology

2006-09-14

wireless communication usage and exposure to different parts of the body (especially for children and foetuses ), including multiple exposure from...Calculation of induced electric fields in pregnant women and in the foetus is urgently needed. Very little computation has been carried out on...advanced models of the pregnant human and the foetus with appropriate anatomical modelling. It is important to assess possible enhanced induction of

An Applied Framework for Incorporating Multiple Sources of Uncertainty in Fisheries Stock Assessments.

PubMed

Scott, Finlay; Jardim, Ernesto; Millar, Colin P; Cerviño, Santiago

2016-01-01

Estimating fish stock status is very challenging given the many sources and high levels of uncertainty surrounding the biological processes (e.g. natural variability in the demographic rates), model selection (e.g. choosing growth or stock assessment models) and parameter estimation. Incorporating multiple sources of uncertainty in a stock assessment allows advice to better account for the risks associated with proposed management options, promoting decisions that are more robust to such uncertainty. However, a typical assessment only reports the model fit and variance of estimated parameters, thereby underreporting the overall uncertainty. Additionally, although multiple candidate models may be considered, only one is selected as the 'best' result, effectively rejecting the plausible assumptions behind the other models. We present an applied framework to integrate multiple sources of uncertainty in the stock assessment process. The first step is the generation and conditioning of a suite of stock assessment models that contain different assumptions about the stock and the fishery. The second step is the estimation of parameters, including fitting of the stock assessment models. The final step integrates across all of the results to reconcile the multi-model outcome. The framework is flexible enough to be tailored to particular stocks and fisheries and can draw on information from multiple sources to implement a broad variety of assumptions, making it applicable to stocks with varying levels of data availability The Iberian hake stock in International Council for the Exploration of the Sea (ICES) Divisions VIIIc and IXa is used to demonstrate the framework, starting from length-based stock and indices data. Process and model uncertainty are considered through the growth, natural mortality, fishing mortality, survey catchability and stock-recruitment relationship. Estimation uncertainty is included as part of the fitting process. Simple model averaging is used to integrate across the results and produce a single assessment that considers the multiple sources of uncertainty.

Application of a Pharmacokinetic Model of Metformin Clearance in a Population with Acute Myeloid Leukemia

PubMed Central

Ceacareanu, Alice C.; Brown, Geoffrey W.; Moussa, Hoda A.; Wintrob, Zachary A. P.

2018-01-01

Objective: We aimed to estimate the metformin-associated lactic acidosis (MALA) risk by assessing retrospectively the renal clearance variability and applying a pharmacokinetic (PK) model of metformin clearance in a population diagnosed with acute myeloid leukemia (AML) and diabetes mellitus (DM). Methods: All adults with preexisting DM and newly diagnosed AML at Roswell Park Cancer Institute were reviewed (January 2003–December 2010, n = 78). Creatinine clearance (CrCl) and total body weight distributions were used in a two-compartment PK model adapted for multiple dosing and modified to account for actual intra- and inter-individual variability. Based on this renal function variability evidence, 1000 PK profiles were simulated for multiple metformin regimens with the resultant PK profiles being assessed for safe CrCl thresholds. Findings: Metformin 500 mg up to three times daily was safe for all simulated profiles with CrCl ≥25 mL/min. Furthermore, the estimated overall MALA risk was below 10%, remaining under 5% for 500 mg given once daily. CrCl ≥65.25 mL/min was safe for administration in any of the tested regimens (500 mg or 850 mg up to three times daily or 1000 mg up to twice daily). Conclusion: PK simulation-guided prescribing can maximize metformin's beneficial effects on cancer outcomes while minimizing MALA risk. PMID:29755998

Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring.

PubMed

Kallenberg, Michiel; Petersen, Kersten; Nielsen, Mads; Ng, Andrew Y; Pengfei Diao; Igel, Christian; Vachon, Celine M; Holland, Katharina; Winkel, Rikke Rass; Karssemeijer, Nico; Lillholm, Martin

2016-05-01

Mammographic risk scoring has commonly been automated by extracting a set of handcrafted features from mammograms, and relating the responses directly or indirectly to breast cancer risk. We present a method that learns a feature hierarchy from unlabeled data. When the learned features are used as the input to a simple classifier, two different tasks can be addressed: i) breast density segmentation, and ii) scoring of mammographic texture. The proposed model learns features at multiple scales. To control the models capacity a novel sparsity regularizer is introduced that incorporates both lifetime and population sparsity. We evaluated our method on three different clinical datasets. Our state-of-the-art results show that the learned breast density scores have a very strong positive relationship with manual ones, and that the learned texture scores are predictive of breast cancer. The model is easy to apply and generalizes to many other segmentation and scoring problems.

Identifying Children in Middle Childhood Who Are at Risk for Reading Problems.

PubMed

Speece, Deborah L; Ritchey, Kristen D; Silverman, Rebecca; Schatschneider, Christopher; Walker, Caroline Y; Andrusik, Katryna N

2010-06-01

The purpose of this study was to identify and evaluate a universal screening battery for reading that is appropriate for older elementary students in a response to intervention model. Multiple measures of reading and reading correlates were administered to 230 fourth-grade children. Teachers rated children's reading skills, academic competence, and attention. Children were classified as not-at-risk or at-risk readers based on a three-factor model reflecting reading comprehension, word recognition/decoding, and word fluency. Predictors of reading status included group-administered tests of reading comprehension, silent word reading fluency, and teacher ratings of reading problems. Inclusion of individually administered tests and growth estimates did not add substantial variance. The receiver-operator characteristic curve analysis yielded an area under the curve index of 0.90, suggesting this model may both accurately and efficiently screen older elementary students with reading problems.

Bayesian networks improve causal environmental ...

EPA Pesticide Factsheets

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value

A long-term comparative assessment of human health risk to leachate-contaminated groundwater from heavy metal with different liner systems.

PubMed

Mishra, Harshit; Karmakar, Subhankar; Kumar, Rakesh; Kadambala, Praneeth

2018-01-01

The handling and management of municipal solid waste (MSW) are major challenges for solid waste management in developing countries. Open dumping is still the most common waste disposal method in India. However, landfilling also causes various environmental, social, and human health impacts. The generation of heavily polluted leachate is a major concern to public health. Engineered barrier systems (EBSs) are commonly used to restrict potentially harmful wastes by preventing the leachate percolation to groundwater and overflow to surface water bodies. The EBSs are made of natural (e.g., soil, clay) and/or synthetic materials such as polymeric materials (e.g., geomembranes, geosynthetic clay liners) by arranging them in layers. Various studies have estimated the human health risk from leachate-contaminated groundwater. However, no studies have been reported to compare the human health risks, particularly due to the leachate contamination with different liner systems. The present study endeavors to quantify the human health risk to contamination from MSW landfill leachate using multiple simulations for various EBSs. To quantify the variation in health risks to groundwater consumption to the child and adult populations, the Turbhe landfill of Navi Mumbai in India has been selected. The leachate and groundwater samples were collected continuously throughout January-September in 2015 from the landfill site, and heavy metal concentrations were analyzed using an inductively coupled plasma system. The LandSim 2.5 Model, a landfill simulator, was used to simulate the landfill activities for various time slices, and non-carcinogenic human health risk was determined for selected heavy metals. Further, the uncertainties associated with multiple input parameters in the health risk model were quantified under a Monte Carlo simulation framework.

Integrating copper toxicity and climate change to understand extinction risk to two species of pond-breeding anurans.

PubMed

Weir, Scott M; Scott, David E; Salice, Christopher J; Lance, Stacey L

2016-09-01

Chemical contamination is often suggested as an important contributing factor to amphibian population declines, but direct links are rarely reported. Population modeling provides a quantitative method to integrate toxicity data with demographic data to understand the long-term effects of contaminants on population persistence. In this study we use laboratory-derived embryo and larval toxicity data for two anuran species to investigate the potential for toxicity to contribute to population declines. We use the southern toad (Anaxyrus terrestris) and the southern leopard frog (Lithobates sphenocephalus) as model species to investigate copper (Cu) toxicity. We use matrix models to project populations through time and quantify extinction risk (the probability of quasi-extinction in 35 yr). Life-history parameters for toads and frogs were obtained from previously published literature or unpublished data from a long-term (>35 yr) data set. In addition to Cu toxicity, we investigate the role of climate change on amphibian populations by including the probability of early pond drying that results in catastrophic reproductive failure (CRF, i.e., complete mortality of all larval individuals). Our models indicate that CRF is an important parameter for both species as both were unable to persist when CRF probability was >50% for toads or 40% for frogs. Copper toxicity alone did not result in significant effects on extinction risk unless toxicity was very high (>50% reduction in survival parameters). For toads, Cu toxicity and high probability of CRF both resulted in high extinction risk but no synergistic (or greater than additive) effects between the two stressors occurred. For leopard frogs, in the absence of CRF survival was high even under Cu toxicity, but with CRF Cu toxicity increased extinction risk. Our analyses highlight the importance of considering multiple stressors as well as species differences in response to those stressors. Our models were consistently most sensitive to juvenile and adult survival, further suggesting the importance of terrestrial stages to population persistence. Future models will incorporate multiple wetlands with different combinations of stressors to understand if our results for a single wetland result in a population sink within the landscape. © 2016 by the Ecological Society of America.

Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

NASA Astrophysics Data System (ADS)

Fernandes, R.; Braunschweig, F.; Lourenço, F.; Neves, R.

2015-07-01

The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events. A combined methodology to dynamically estimate time and space variable shoreline risk levels from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area - Portuguese Continental shelf - with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time. Shoreline risks can be computed in real-time or from previously obtained data. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns, "hot spots" or developing sensitivity analysis to specific conditions, whereas real time risk levels can be used in the prioritization of individual ships, geographical areas, strategic tug positioning and implementation of dynamic risk-based vessel traffic monitoring.

MS Sunshine Study: Sun Exposure But Not Vitamin D Is Associated with Multiple Sclerosis Risk in Blacks and Hispanics.

PubMed

Langer-Gould, Annette; Lucas, Robyn; Xiang, Anny H; Chen, Lie H; Wu, Jun; Gonzalez, Edlin; Haraszti, Samantha; Smith, Jessica B; Quach, Hong; Barcellos, Lisa F

2018-02-27

Multiple sclerosis (MS) incidence and serum 25-hydroxyvitamin D (25OHD) levels vary by race/ethnicity. We examined the consistency of beneficial effects of 25OHD and/or sun exposure for MS risk across multiple racial/ethnic groups. We recruited incident MS cases and controls (blacks 116 cases/131 controls; Hispanics 183/197; whites 247/267) from the membership of Kaiser Permanente Southern California into the MS Sunshine Study to simultaneously examine sun exposure and 25OHD, accounting for genetic ancestry and other factors. Higher lifetime ultraviolet radiation exposure (a rigorous measure of sun exposure) was associated with a lower risk of MS independent of serum 25OHD levels in blacks (adjusted OR = 0.53, 95% CI = 0.31-0.83; p = 0.007) and whites (OR = 0.68, 95% CI = 0.48-0.94; p = 0.020) with a similar magnitude of effect that did not reach statistical significance in Hispanics (OR = 0.66, 95% CI = 0.42-1.04; p = 0.071). Higher serum 25OHD levels were associated with a lower risk of MS only in whites. No association was found in Hispanics or blacks regardless of how 25OHD was modeled. Lifetime sun exposure appears to reduce the risk of MS regardless of race/ethnicity. In contrast, serum 25OHD levels are not associated with MS risk in blacks or Hispanics. Our findings challenge the biological plausibility of vitamin D deficiency as causal for MS and call into question the targeting of specific serum 25OHD levels to achieve health benefits, particularly in blacks and Hispanics.

Maternal Risk Factors for Fetal Alcohol Spectrum Disorders in a Province in Italy*

PubMed Central

Ceccanti, Mauro; Fiorentino, Daniela; Coriale, Giovanna; Kalberg, Wendy O.; Buckley, David; Hoyme, H. Eugene; Gossage, J. Phillip; Robinson, Luther K.; Manning, Melanie; Romeo, Marina; Hasken, Julie M.; Tabachnick, Barbara; Blankenship, Jason

2016-01-01

Background Maternal risk factors for fetal alcohol spectrum disorders (FASD) in Italy and Mediterranean cultures need clarification, as there are few studies and most are plagued by inaccurate reporting of antenatal alcohol use. Methods Maternal interviews (n=905) were carried out in a population-based study of the prevalence and characteristics of FASD in the Lazio region of Italy which provided data for multivariate case control comparisons and multiple correlation models. Results Case control findings from interviews seven years post-partum indicate that mothers of children with FASD are significantly more likely than randomly-selected controls or community mothers to: be shorter; have higher body mass indexes (BMI); be married to a man with legal problems; report more drinking three months pre-pregnancy; engage in more current drinking and drinking alone; and have alcohol problems in her family. Logistic regression analysis of multiple candidate predictors of a FASD diagnosis indicates that alcohol problems in the child’s family is the most significant risk factor, making a diagnosis within the continuum of FASD 9 times more likely (95% C.I. = 1.6 to 50.7). Sequential multiple regression analysis of the child’s neuropsychological performance also identifies alcohol problems in the child’s family as the only significant maternal risk variable (p<.001) when controlling for other potential risk factors. Conclusions Underreporting of prenatal alcohol use has been demonstrated among Italian and other Mediterranean antenatal samples, and it was suspected in this sample. Nevertheless, several significant maternal risk factors for FASD have been identified. PMID:25456331

Maternal risk factors for fetal alcohol spectrum disorders in a province in Italy.

PubMed

Ceccanti, Mauro; Fiorentino, Daniela; Coriale, Giovanna; Kalberg, Wendy O; Buckley, David; Hoyme, H Eugene; Gossage, J Phillip; Robinson, Luther K; Manning, Melanie; Romeo, Marina; Hasken, Julie M; Tabachnick, Barbara; Blankenship, Jason; May, Philip A

2014-12-01

Maternal risk factors for fetal alcohol spectrum disorders (FASD) in Italy and Mediterranean cultures need clarification, as there are few studies and most are plagued by inaccurate reporting of antenatal alcohol use. Maternal interviews (n = 905) were carried out in a population-based study of the prevalence and characteristics of FASD in the Lazio region of Italy which provided data for multivariate case control comparisons and multiple correlation models. Case control findings from interviews seven years post-partum indicate that mothers of children with FASD are significantly more likely than randomly-selected controls or community mothers to: be shorter; have higher body mass indexes (BMI); be married to a man with legal problems; report more drinking three months pre-pregnancy; engage in more current drinking and drinking alone; and have alcohol problems in her family. Logistic regression analysis of multiple candidate predictors of a FASD diagnosis indicates that alcohol problems in the child's family is the most significant risk factor, making a diagnosis within the continuum of FASD 9 times more likely (95%C.I. = 1.6 to 50.7). Sequential multiple regression analysis of the child's neuropsychological performance also identifies alcohol problems in the child's family as the only significant maternal risk variable (p < .001) when controlling for other potential risk factors. Underreporting of prenatal alcohol use has been demonstrated among Italian and other Mediterranean antenatal samples, and it was suspected in this sample. Nevertheless, several significant maternal risk factors for FASD have been identified. Copyright © 2014. Published by Elsevier Ireland Ltd.

Absence of evidence for increase in risk for autism or attention-deficit hyperactivity disorder following antidepressant exposure during pregnancy: a replication study.

PubMed

Castro, V M; Kong, S W; Clements, C C; Brady, R; Kaimal, A J; Doyle, A E; Robinson, E B; Churchill, S E; Kohane, I S; Perlis, R H

2016-01-05

Multiple studies have examined the risk of prenatal antidepressant exposure and risk for autism spectrum disorder (ASD) or attention-deficit hyperactivity disorder (ADHD), with inconsistent results. Precisely estimating such risk, if any, is of great importance in light of the need to balance such risk with the benefit of depression and anxiety treatment. We developed a method to integrate data from multiple New England health systems, matching offspring and maternal health data in electronic health records to characterize diagnoses and medication exposure. Children with ASD or ADHD were matched 1:3 with children without neurodevelopmental disorders. Association between maternal antidepressant exposure and ASD or ADHD liability was examined using logistic regression, adjusting for potential sociodemographic and psychiatric confounding variables. In new cohorts of 1245 ASD cases and 1701 ADHD cases, along with age-, sex- and socioeconomic status matched controls, neither disorder was significantly associated with prenatal antidepressant exposure in crude or adjusted models (adjusted odds ratio 0.90, 95% confidence interval 0.50-1.54 for ASD; 0.97, 95% confidence interval 0.53-1.69 for ADHD). Pre-pregnancy antidepressant exposure significantly increased risk for both disorders. These results suggest that prior reports of association between prenatal antidepressant exposure and neurodevelopmental disease are likely to represent a false-positive finding, which may arise in part through confounding by indication. They further demonstrate the potential to integrate data across electronic health records studies spanning multiple health systems to enable efficient pharmacovigilance investigation.

Development of a Risk Assessment Tool to Predict Fall-Related Severe Injuries Occurring in a Hospital

PubMed Central

Toyabe, Shin-ichi

2014-01-01

Inpatient falls are the most common adverse events that occur in a hospital, and about 3 to 10% of falls result in serious injuries such as bone fractures and intracranial haemorrhages. We previously reported that bone fractures and intracranial haemorrhages were two major fall-related injuries and that risk assessment score for osteoporotic bone fracture was significantly associated not only with bone fractures after falls but also with intracranial haemorrhage after falls. Based on the results, we tried to establish a risk assessment tool for predicting fall-related severe injuries in a hospital. Possible risk factors related to fall-related serious injuries were extracted from data on inpatients that were admitted to a tertiary-care university hospital by using multivariate Cox’ s regression analysis and multiple logistic regression analysis. We found that fall risk score and fracture risk score were the two significant factors, and we constructed models to predict fall-related severe injuries incorporating these factors. When the prediction model was applied to another independent dataset, the constructed model could detect patients with fall-related severe injuries efficiently. The new assessment system could identify patients prone to severe injuries after falls in a reproducible fashion. PMID:25168984

Multi -risk assessment at a national level in Georgia

NASA Astrophysics Data System (ADS)

Tsereteli, Nino; Varazanashvili, Otar; Amiranashvili, Avtandil; Tsereteli, Emili; Elizbarashvili, Elizbar; Saluqvadze, Manana; Dolodze, Jemal

2013-04-01

Work presented here was initiated by national GNSF project " Reducing natural disasters multiple risk: a positive factor for Georgia development " and two international projects: NATO SFP 983038 "Seismic hazard and Rusk assessment for Southern Caucasus-eastern Turkey Energy Corridors" and EMME " Earthquake Model for Middle east Region". Methodology for estimation of "general" vulnerability, hazards and multiple risk to natural hazards (namely, earthquakes, landslides, snow avalanches, flash floods, mudflows, drought, hurricanes, frost, hail) where developed for Georgia. The electronic detailed databases of natural disasters were created. These databases contain the parameters of hazardous phenomena that caused natural disasters. The magnitude and intensity scale of the mentioned disasters are reviewed and the new magnitude and intensity scales are suggested for disasters for which the corresponding formalization is not yet performed. The associated economic losses were evaluated and presented in monetary terms for these hazards. Based on the hazard inventory, an approach was developed that allowed for the calculation of an overall vulnerability value for each individual hazard type, using the Gross Domestic Product per unit area (applied to population) as the indicator for elements at risk exposed. The correlation between estimated economic losses, physical exposure and the magnitude for each of the six types of hazards has been investigated in detail by using multiple linear regression analysis. Economic losses for all past events and historical vulnerability were estimated. Finally, the spatial distribution of general vulnerability was assessed, and the expected maximum economic loss was calculated as well as a multi-risk map was set-up.

Hybrid Modeling Approach to Estimate Exposures of Hazardous Air Pollutants (HAPs) for the National Air Toxics Assessment (NATA).

PubMed

Scheffe, Richard D; Strum, Madeleine; Phillips, Sharon B; Thurman, James; Eyth, Alison; Fudge, Steve; Morris, Mark; Palma, Ted; Cook, Richard

2016-11-15

A hybrid air quality model has been developed and applied to estimate annual concentrations of 40 hazardous air pollutants (HAPs) across the continental United States (CONUS) to support the 2011 calendar year National Air Toxics Assessment (NATA). By combining a chemical transport model (CTM) with a Gaussian dispersion model, both reactive and nonreactive HAPs are accommodated across local to regional spatial scales, through a multiplicative technique designed to improve mass conservation relative to previous additive methods. The broad scope of multiple pollutants capturing regional to local spatial scale patterns across a vast spatial domain is precedent setting within the air toxics community. The hybrid design exhibits improved performance relative to the stand alone CTM and dispersion model. However, model performance varies widely across pollutant categories and quantifiably definitive performance assessments are hampered by a limited observation base and challenged by the multiple physical and chemical attributes of HAPs. Formaldehyde and acetaldehyde are the dominant HAP concentration and cancer risk drivers, characterized by strong regional signals associated with naturally emitted carbonyl precursors enhanced in urban transport corridors with strong mobile source sector emissions. The multiple pollutant emission characteristics of combustion dominated source sectors creates largely similar concentration patterns across the majority of HAPs. However, reactive carbonyls exhibit significantly less spatial variability relative to nonreactive HAPs across the CONUS.

Software forecasting as it is really done: A study of JPL software engineers

NASA Technical Reports Server (NTRS)

Griesel, Martha Ann; Hihn, Jairus M.; Bruno, Kristin J.; Fouser, Thomas J.; Tausworthe, Robert C.

1993-01-01

This paper presents a summary of the results to date of a Jet Propulsion Laboratory internally funded research task to study the costing process and parameters used by internally recognized software cost estimating experts. Protocol Analysis and Markov process modeling were used to capture software engineer's forecasting mental models. While there is significant variation between the mental models that were studied, it was nevertheless possible to identify a core set of cost forecasting activities, and it was also found that the mental models cluster around three forecasting techniques. Further partitioning of the mental models revealed clustering of activities, that is very suggestive of a forecasting lifecycle. The different forecasting methods identified were based on the use of multiple-decomposition steps or multiple forecasting steps. The multiple forecasting steps involved either forecasting software size or an additional effort forecast. Virtually no subject used risk reduction steps in combination. The results of the analysis include: the identification of a core set of well defined costing activities, a proposed software forecasting life cycle, and the identification of several basic software forecasting mental models. The paper concludes with a discussion of the implications of the results for current individual and institutional practices.

The incremental value of troponin biomarkers in risk stratification of acute coronary syndromes: is the relationship multiplicative?

PubMed

Amin, Amit P; Nathan, Sandeep; Vassallo, Patricia; Calvin, James E

2009-05-20

To emphasize the importance of troponin in the context of a new score for risk stratifying acute coronary syndromes (ACS) patients. Although troponins have powerful prognostic value, current ACS scores do not fully capitalize this prognostic ability. Here, we weigh troponin status in a multiplicative manner to develop the TRACS score from previously published Rush score risk factors (RRF). 2,866 ACS patients (46.7% troponin positive) from 9 centers comprising the TRACS registry, were randomly split into derivation (n=1,422) and validation (n=1,444) cohorts. In the derivation sample, RRF sum was multiplied by 3 if troponins were positive to yield the TRACS score, which was grouped into five categories of 0-2, 3-5, 6-8, 9-11, 12-15 (multiples of 3). Predictive performance of this score to predict hospital death was ascertained in the validation sample. The TRACS score had ROC AUC of 0.71 in the validation cohort. Logistic regression, Kaplan-Meier analysis, likelihood-ratio and Bayesian Information Criterion (BIC) test indicated that weighing troponin status with 3 in the TRACS score improved the prediction of mortality. Hosmer-Lemeshow test indicated sound model fit. We demonstrate that weighing troponin as a multiple of 3 yields robust prognostication of hospital mortality in ACS patients, when used in the context of the TRACS score.

The Incremental Value of Troponin Biomarkers in Risk Stratification of Acute Coronary Syndromes: Is the Relationship Multiplicative?

PubMed Central

Amin, Amit P; Nathan, Sandeep; Vassallo, Patricia; Calvin, James E

2009-01-01

Structured Abstract Objective: To emphasize the importance of troponin in the context of a new score for risk stratifying acute coronary syndromes (ACS) patients. Although troponins have powerful prognostic value, current ACS scores do not fully capitalize this prognostic ability. Here, we weigh troponin status in a multiplicative manner to develop the TRACS score from previously published Rush score risk factors (RRF). Methods: 2,866 ACS patients (46.7% troponin positive) from 9 centers comprising the TRACS registry, were randomly split into derivation (n=1,422) and validation (n=1,444) cohorts. In the derivation sample, RRF sum was multiplied by 3 if troponins were positive to yield the TRACS score, which was grouped into five categories of 0-2, 3-5, 6-8, 9-11, 12-15 (multiples of 3). Predictive performance of this score to predict hospital death was ascertained in the validation sample. Results: The TRACS score had ROC AUC of 0.71 in the validation cohort. Logistic regression, Kaplan-Meier analysis, likelihood-ratio and Bayesian Information Criterion (BIC) test indicated that weighing troponin status with 3 in the TRACS score improved the prediction of mortality. Hosmer-Lemeshow test indicated sound model fit. Conclusions: We demonstrate that weighing troponin as a multiple of 3 yields robust prognostication of hospital mortality in ACS patients, when used in the context of the TRACS score. PMID:19557150

Multiple Risks, Emotion Regulation Skill, and Cortisol in Low-Income African American Youth: A Prospective Study

ERIC Educational Resources Information Center

Kliewer, Wendy; Reid-Quinones, Kathryn; Shields, Brian J.; Foutz, Lauren

2009-01-01

Associations between multiple risks, emotion regulation skill, and basal cortisol levels were examined in a community sample of 69 African American youth (mean age = 11.30 years; 49% male) living in an urban setting. Multiple risks were assessed at Time 1 and consisted of 10 demographic and psychosocial risk factors including parent, child, and…

Proximity to Pollution Sources and Risk of Amphibian Limb Malformation

PubMed Central

Taylor, Brynn; Skelly, David; Demarchis, Livia K.; Slade, Martin D.; Galusha, Deron; Rabinowitz, Peter M.

2005-01-01

The cause of limb deformities in wild amphibian populations remains unclear, even though the apparent increase in prevalence of this condition may have implications for human health. Few studies have simultaneously assessed the effect of multiple exposures on the risk of limb deformities. In a cross-sectional survey of 5,264 hylid and ranid metamorphs in 42 Vermont wetlands, we assessed independent risk factors for nontraumatic limb malformation. The rate of nontraumatic limb malformation varied by location from 0 to 10.2%. Analysis of a subsample did not demonstrate any evidence of infection with the parasite Ribeiroia. We used geographic information system (GIS) land-use/land-cover data to validate field observations of land use in the proximity of study wetlands. In a multiple logistic regression model that included land use as well as developmental stage, genus, and water-quality measures, proximity to agricultural land use was associated with an increased risk of limb malformation (odds ratio = 2.26; 95% confidence interval, 1.42–3.58; p < 0.001). The overall discriminant power of the statistical model was high (C = 0.79). These findings from one of the largest systematic surveys to date provide support for the role of chemical toxicants in the development of amphibian limb malformation and demonstrate the value of an epidemiologic approach to this problem. PMID:16263502

Evaluation of Revised International Staging System (R-ISS) for transplant-eligible multiple myeloma patients.

PubMed

González-Calle, Verónica; Slack, Abigail; Keane, Niamh; Luft, Susan; Pearce, Kathryn E; Ketterling, Rhett P; Jain, Tania; Chirackal, Sintosebastian; Reeder, Craig; Mikhael, Joseph; Noel, Pierre; Mayo, Angela; Adams, Roberta H; Ahmann, Gregory; Braggio, Esteban; Stewart, A Keith; Bergsagel, P Leif; Van Wier, Scott A; Fonseca, Rafael

2018-04-06

The International Myeloma Working Group has proposed the Revised International Staging System (R-ISS) for risk stratification of multiple myeloma (MM) patients. There are a limited number of studies that have validated this risk model in the autologous stem cell transplant (ASCT) setting. In this retrospective study, we evaluated the applicability and value for predicting survival of the R-ISS model in 134 MM patients treated with new agents and ASCT at the Mayo Clinic in Arizona and the University Hospital of Salamanca in Spain. The patients were reclassified at diagnosis according to the R-ISS: 44 patients (33%) had stage I, 75 (56%) had stage II, and 15 (11%) had stage III. After a median follow-up of 60 months, R-ISS assessed at diagnosis was an independent predictor for overall survival (OS) after ASCT, with median OS not reached, 111 and 37 months for R-ISS I, II and III, respectively (P < 0.001). We also found that patients belonging to R-ISS II and having high-risk chromosomal abnormalities (CA) had a significant shorter median OS than those with R-ISS II without CA: 70 vs. 111 months, respectively. Therefore, this study lends further support for the R-ISS as a reliable prognostic tool for estimating survival in transplant myeloma patients and suggests the importance of high-risk CA in the R-ISS II group.

A Stochastic Model of Space Radiation Transport as a Tool in the Development of Time-Dependent Risk Assessment

NASA Technical Reports Server (NTRS)

Kim, Myung-Hee Y.; Nounu, Hatem N.; Ponomarev, Artem L.; Cucinotta, Francis A.

2011-01-01

A new computer model, the GCR Event-based Risk Model code (GERMcode), was developed to describe biophysical events from high-energy protons and heavy ions that have been studied at the NASA Space Radiation Laboratory (NSRL) [1] for the purpose of simulating space radiation biological effects. In the GERMcode, the biophysical description of the passage of heavy ions in tissue and shielding materials is made with a stochastic approach that includes both ion track structure and nuclear interactions. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model [2]. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections

Absolute fracture risk assessment using lumbar spine and femoral neck bone density measurements: derivation and validation of a hybrid system.

PubMed

Leslie, William D; Lix, Lisa M

2011-03-01

The World Health Organization (WHO) Fracture Risk Assessment Tool (FRAX) computes 10-year probability of major osteoporotic fracture from multiple risk factors, including femoral neck (FN) T-scores. Lumbar spine (LS) measurements are not currently part of the FRAX formulation but are used widely in clinical practice, and this creates confusion when there is spine-hip discordance. Our objective was to develop a hybrid 10-year absolute fracture risk assessment system in which nonvertebral (NV) fracture risk was assessed from the FN and clinical vertebral (V) fracture risk was assessed from the LS. We identified 37,032 women age 45 years and older undergoing baseline FN and LS dual-energy X-ray absorptiometry (DXA; 1990-2005) from a population database that contains all clinical DXA results for the Province of Manitoba, Canada. Results were linked to longitudinal health service records for physician billings and hospitalizations to identify nontrauma vertebral and nonvertebral fracture codes after bone mineral density (BMD) testing. The population was randomly divided into equal-sized derivation and validation cohorts. Using the derivation cohort, three fracture risk prediction systems were created from Cox proportional hazards models (adjusted for age and multiple FRAX risk factors): FN to predict combined all fractures, FN to predict nonvertebral fractures, and LS to predict vertebral (without nonvertebral) fractures. The hybrid system was the sum of nonvertebral risk from the FN model and vertebral risk from the LS model. The FN and hybrid systems were both strongly predictive of overall fracture risk (p < .001). In the validation cohort, ROC analysis showed marginally better performance of the hybrid system versus the FN system for overall fracture prediction (p = .24) and significantly better performance for vertebral fracture prediction (p < .001). In a discordance subgroup with FN and LS T-score differences greater than 1 SD, there was a significant improvement in overall fracture prediction with the hybrid method (p = .025). Risk reclassification under the hybrid system showed better alignment with observed fracture risk, with 6.4% of the women reclassified to a different risk category. In conclusion, a hybrid 10-year absolute fracture risk assessment system based on combining FN and LS information is feasible. The improvement in fracture risk prediction is small but supports clinical interest in a system that integrates LS in fracture risk assessment. Copyright © 2011 American Society for Bone and Mineral Research.

Intervening with High Risk Youth: A Program Model.

ERIC Educational Resources Information Center

Davis, Ruth B.; And Others

1994-01-01

Describes a program for older adolescents exhibiting substance use problems. After initial assessment and referral, most patients enter outpatient treatment groups. Groups fulfill three purposes: (1) Staff monitors clients; (2) Help clients recognize the promise of recovery; and (3) Change behavior. Difficulties of working with multiple community…

A STATISTICAL MODELING METHODOLOGY FOR THE DETECTION, QUANTIFICATION, AND PREDICTION OF ECOLOGICAL THRESHOLDS

EPA Science Inventory

This study will provide a general methodology for integrating threshold information from multiple species ecological metrics, allow for prediction of changes of alternative stable states, and provide a risk assessment tool that can be applied to adaptive management. The integr...

Possibilities and Challenges for Modeling Flow and Pollutant Transport in a Karst Watershed with SWAT

USDA-ARS?s Scientific Manuscript database

Karst hydrology is characterized by multiple springs, sinkholes, and losing streams resulting from acidic water percolating through limestone. These features provide direct connections between surface water and groundwater and increase the risk of groundwater, spring and stream contamination. Anthro...

Childhood Trauma and Illicit Drug Use in Adolescence: A Population-Based National Comorbidity Survey Replication–Adolescent Supplement Study

PubMed Central

Carliner, Hannah; Keyes, Katherine M.; McLaughlin, Katie A.; Meyers, Jacquelyn L.; Dunn, Erin C.; Martins, Silvia S.

2016-01-01

Objective Although potentially traumatic events (PTEs) are established risk factors for substance use disorders among adults, little is known about associations with drug use during adolescence, an important developmental stage for drug use prevention. We examined whether childhood PTEs were associated with illicit drug use among a representative sample of US adolescents. Method Data were drawn from the National Comorbidity Survey Replication–Adolescent Supplement (NCS-A), which included adolescents aged 13-18 years (N=9,956). Weighted logistic regression models estimated risk ratios for lifetime use of marijuana, cocaine, nonmedical prescription drugs, other drugs, and multiple drugs. Results Exposure to any PTE prior to age 11 was reported by 36% of the sample and was associated with higher risk for use of marijuana (risk ratio [RR] = 1.50), cocaine (RR = 2.78), prescription drugs (RR=1.80), other drugs (RR=1.90), and multiple drugs (RR=1.74). A positive monotonic relationship was observed between number of PTEs and marijuana, other drug, and multiple drug use. Interpersonal violence was associated with all drug use outcomes. Accidents and unspecified events were associated with higher risk for marijuana, cocaine, and prescription drug use. Conclusion Potentially traumatic events in childhood are associated with risk for illicit drug use among US adolescents. These findings add to the literature by illustrating a potentially modifiable health behavior that may be a target for intervention; and that adolescents with a trauma history are a high-risk group for illicit drug use and may benefit from trauma-focused prevention efforts that specifically address traumatic memories and coping strategies for dealing with stressful life events. PMID:27453084

Social environments, risk-taking and injury in farm adolescents.

PubMed

Pickett, William; Berg, Richard L; Marlenga, Barbara

2017-12-01

Farm environments are especially hazardous for young people. While much is known about acute physical causes of traumatic farm injury, little is known about social factors that may underlie their aetiology. In a nationally representative sample of young Canadians aged 11-15 years, we described and compared farm and non-farm adolescents in terms of the qualities of their social environments, engagement in overt multiple risk-taking as well as how such exposures relate aetiologically to their reported injury experiences. Cross-sectional analysis of survey reports from the 2014 (Cycle 7) Canadian Health Behaviour in School-Aged Children study was conducted. Children (n=2567; 2534 weighted) who reported living or working on farms were matched within schools in a 1:1 ratio with children not living or working on farms. Scales examining quality of social environments and overt risk-taking were compared between the two groups, stratified by gender. We then related the occurrence of any serious injury to these social exposures in direct and interactive models. Farm and non-farm children reported social environments that were quite similar, with the exception of overt multiple risk-taking, which was demonstrably higher in farm children of both genders. Engagement in overt risk-taking, but not the other social environmental factors, was strongly and consistently associated with risks for serious injury in farm as well as non-farm children, particularly among males. Study findings highlight the strength of associations between overt multiple risk-taking and injury among farm children. This appears to be a normative aspect of adolescent farm culture. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Childhood Trauma and Illicit Drug Use in Adolescence: A Population-Based National Comorbidity Survey Replication-Adolescent Supplement Study.

PubMed

Carliner, Hannah; Keyes, Katherine M; McLaughlin, Katie A; Meyers, Jacquelyn L; Dunn, Erin C; Martins, Silvia S

2016-08-01

Although potentially traumatic events (PTEs) are established risk factors for substance use disorders among adults, little is known about associations with drug use during adolescence, an important developmental stage for drug use prevention. We examined whether childhood PTEs were associated with illicit drug use among a representative sample of US adolescents. Data were drawn from the National Comorbidity Survey Replication-Adolescent Supplement (NCS-A), which included adolescents aged 13 to 18 years (N = 9,956). Weighted logistic regression models estimated risk ratios for lifetime use of marijuana, cocaine, nonmedical prescription drugs, other drugs, and multiple drugs. Exposure to any PTE before age 11 years was reported by 36% of the sample and was associated with higher risk for use of marijuana (risk ratio [RR] = 1.50), cocaine (RR = 2.78), prescription drugs (RR = 1.80), other drugs (RR = 1.90), and multiple drugs (RR = 1.74). A positive monotonic relationship was observed between number of PTEs and marijuana, other drug, and multiple drug use. Interpersonal violence was associated with all drug use outcomes. Accidents and unspecified events were associated with higher risk for marijuana, cocaine, and prescription drug use. Potentially traumatic events in childhood are associated with risk for illicit drug use among US adolescents. These findings add to the literature by illustrating a potentially modifiable health behavior that may be a target for intervention. The results also highlight that adolescents with a trauma history are a high-risk group for illicit drug use and may benefit from trauma-focused prevention efforts that specifically address traumatic memories and coping strategies for dealing with stressful life events. Copyright © 2016 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Lung and stomach cancer associations with groundwater radon in North Carolina, USA

PubMed Central

Messier, Kyle P; Serre, Marc L

2017-01-01

Abstract Background: The risk of indoor air radon for lung cancer is well studied, but the risks of groundwater radon for both lung and stomach cancer are much less studied, and with mixed results. Methods: Geomasked and geocoded stomach and lung cancer cases in North Carolina from 1999 to 2009 were obtained from the North Carolina Central Cancer Registry. Models for the association with groundwater radon and multiple confounders were implemented at two scales: (i) an ecological model estimating cancer incidence rates at the census tract level; and (ii) a case-only logistic model estimating the odds that individual cancer cases are members of local cancer clusters. Results: For the lung cancer incidence rate model, groundwater radon is associated with an incidence rate ratio of 1.03 [95% confidence interval (CI) = 1.01, 1.06] for every 100 Bq/l increase in census tract averaged concentration. For the cluster membership models, groundwater radon exposure results in an odds ratio for lung cancer of 1.13 (95% CI = 1.04, 1.23) and for stomach cancer of 1.24 (95% CI = 1.03, 1.49), which means groundwater radon, after controlling for multiple confounders and spatial auto-correlation, increases the odds that lung and stomach cancer cases are members of their respective cancer clusters. Conclusion: Our study provides epidemiological evidence of a positive association between groundwater radon exposure and lung cancer incidence rates. The cluster membership model results find groundwater radon increases the odds that both lung and stomach cancer cases occur within their respective cancer clusters. The results corroborate previous biokinetic and mortality studies that groundwater radon is associated with increased risk for lung and stomach cancer. PMID:27639278

Lung and stomach cancer associations with groundwater radon in North Carolina, USA.

PubMed

Messier, Kyle P; Serre, Marc L

2017-04-01

The risk of indoor air radon for lung cancer is well studied, but the risks of groundwater radon for both lung and stomach cancer are much less studied, and with mixed results. Geomasked and geocoded stomach and lung cancer cases in North Carolina from 1999 to 2009 were obtained from the North Carolina Central Cancer Registry. Models for the association with groundwater radon and multiple confounders were implemented at two scales: (i) an ecological model estimating cancer incidence rates at the census tract level; and (ii) a case-only logistic model estimating the odds that individual cancer cases are members of local cancer clusters. For the lung cancer incidence rate model, groundwater radon is associated with an incidence rate ratio of 1.03 [95% confidence interval (CI) = 1.01, 1.06] for every 100 Bq/l increase in census tract averaged concentration. For the cluster membership models, groundwater radon exposure results in an odds ratio for lung cancer of 1.13 (95% CI = 1.04, 1.23) and for stomach cancer of 1.24 (95% CI = 1.03, 1.49), which means groundwater radon, after controlling for multiple confounders and spatial auto-correlation, increases the odds that lung and stomach cancer cases are members of their respective cancer clusters. Our study provides epidemiological evidence of a positive association between groundwater radon exposure and lung cancer incidence rates. The cluster membership model results find groundwater radon increases the odds that both lung and stomach cancer cases occur within their respective cancer clusters. The results corroborate previous biokinetic and mortality studies that groundwater radon is associated with increased risk for lung and stomach cancer. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

Risk-adjusted econometric model to estimate postoperative costs: an additional instrument for monitoring performance after major lung resection.

PubMed

Brunelli, Alessandro; Salati, Michele; Refai, Majed; Xiumé, Francesco; Rocco, Gaetano; Sabbatini, Armando

2007-09-01

The objectives of this study were to develop a risk-adjusted model to estimate individual postoperative costs after major lung resection and to use it for internal economic audit. Variable and fixed hospital costs were collected for 679 consecutive patients who underwent major lung resection from January 2000 through October 2006 at our unit. Several preoperative variables were used to develop a risk-adjusted econometric model from all patients operated on during the period 2000 through 2003 by a stepwise multiple regression analysis (validated by bootstrap). The model was then used to estimate the postoperative costs in the patients operated on during the 3 subsequent periods (years 2004, 2005, and 2006). Observed and predicted costs were then compared within each period by the Wilcoxon signed rank test. Multiple regression and bootstrap analysis yielded the following model predicting postoperative cost: 11,078 + 1340.3X (age > 70 years) + 1927.8X cardiac comorbidity - 95X ppoFEV1%. No differences between predicted and observed costs were noted in the first 2 periods analyzed (year 2004, $6188.40 vs $6241.40, P = .3; year 2005, $6308.60 vs $6483.60, P = .4), whereas in the most recent period (2006) observed costs were significantly lower than the predicted ones ($3457.30 vs $6162.70, P < .0001). Greater precision in predicting outcome and costs after therapy may assist clinicians in the optimization of clinical pathways and allocation of resources. Our economic model may be used as a methodologic template for economic audit in our specialty and complement more traditional outcome measures in the assessment of performance.

Multiple myeloma and family history of lymphohaematopoietic cancers: Results from the International Multiple Myeloma Consortium.

PubMed

Schinasi, Leah H; Brown, Elizabeth E; Camp, Nicola J; Wang, Sophia S; Hofmann, Jonathan N; Chiu, Brian C; Miligi, Lucia; Beane Freeman, Laura E; de Sanjose, Silvia; Bernstein, Leslie; Monnereau, Alain; Clavel, Jacqueline; Tricot, Guido J; Atanackovic, Djordje; Cocco, Pierluigi; Orsi, Laurent; Dosman, James A; McLaughlin, John R; Purdue, Mark P; Cozen, Wendy; Spinelli, John J; de Roos, Anneclaire J

2016-10-01

Family clusters of multiple myeloma (MM) suggest disease heritability. Nevertheless, patterns of inheritance and the importance of genetic versus environmental risk factors in MM aetiology remain unclear. We pooled data from eleven case-control studies from the International Multiple Myeloma Consortium to characterize the association of MM risk with having a first-degree relative with a history of a lympho-haematapoietic cancer. Unconditional logistic regression models, adjusted for study, sex, age and education level, were used to estimate associations between MM risk and having a first-degree relative with a history of non-Hodgkin lymphoma, Hodgkin lymphoma, leukaemia or MM. Sex, African American race/ethnicity and age were explored as effect modifiers. A total of 2843 cases and 11 470 controls were included. MM risk was elevated in association with having a first-degree relative with any lympho-haematapoietic cancer (Odds Ratio (OR) = 1·29, 95% Confidence Interval (CI): 1·08-1·55). The association was particularly strong for having a first-degree relative with MM (OR = 1·90, 95% CI: 1·26-2·87), especially among men (OR = 4·13, 95% CI: 2·17-7·85) and African Americans (OR = 5·52, 95% CI: 1·87-16·27).These results support the hypothesis that genetic inheritance plays a role in MM aetiology. Future studies are warranted to characterize interactions of genetic markers with environmental exposures. © 2016 John Wiley & Sons Ltd.

Comparison of three lifecourse models of poverty in predicting cardiovascular disease risk in youth.

PubMed

Kakinami, Lisa; Séguin, Louise; Lambert, Marie; Gauvin, Lise; Nikiema, Béatrice; Paradis, Gilles

2013-08-01

Childhood poverty heightens the risk of adulthood cardiovascular disease (CVD), but the underlying pathways are poorly understood. Three lifecourse models have been proposed but have never been tested among youth. We assessed the longitudinal association of childhood poverty with CVD risk factors in 10-year-old youth according to the timing, accumulation, and mobility models. The Québec Longitudinal Study of Child Development birth cohort was established in 1998 (n = 2120). Poverty was defined as annual income below the low-income thresholds defined by Statistics Canada. Multiple imputation was used for missing data. Multivariable linear regression models adjusted for gender, pubertal stage, parental education, maternal age, whether the household was a single parent household, whether the child was overweight or obese, the child's physical activity in the past week, and family history. Approximately 40% experienced poverty at least once, 16% throughout childhood, and 25% intermittently. Poverty was associated with significantly elevated triglycerides and insulin according to the timing and accumulation models, although the timing model was superior for predicting insulin and the accumulation model was superior for predicting triglycerides. Early and prolonged exposure to poverty significantly increases CVD risk among 10-year-old youth. Copyright © 2013 Elsevier Inc. All rights reserved.

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Managing Analysis Models in the Design Process

NASA Technical Reports Server (NTRS)

Briggs, Clark

2006-01-01

Design of large, complex space systems depends on significant model-based support for exploration of the design space. Integrated models predict system performance in mission-relevant terms given design descriptions and multiple physics-based numerical models. Both the design activities and the modeling activities warrant explicit process definitions and active process management to protect the project from excessive risk. Software and systems engineering processes have been formalized and similar formal process activities are under development for design engineering and integrated modeling. JPL is establishing a modeling process to define development and application of such system-level models.

Health Risks of an Inactive Lifestyle - Multiple Languages

MedlinePlus

... Are Here: Home → Multiple Languages → All Health Topics → Health Risks of an Inactive Lifestyle URL of this page: https://medlineplus.gov/languages/ ... V W XYZ List of All Topics All Health Risks of an Inactive Lifestyle - Multiple Languages To use the sharing features on ...

Estimating the personal cure rate of cancer patients using population-based grouped cancer survival data.

PubMed

Binbing Yu; Tiwari, Ram C; Feuer, Eric J

2011-06-01

Cancer patients are subject to multiple competing risks of death and may die from causes other than the cancer diagnosed. The probability of not dying from the cancer diagnosed, which is one of the patients' main concerns, is sometimes called the 'personal cure' rate. Two approaches of modelling competing-risk survival data, namely the cause-specific hazards approach and the mixture model approach, have been used to model competing-risk survival data. In this article, we first show the connection and differences between crude cause-specific survival in the presence of other causes and net survival in the absence of other causes. The mixture survival model is extended to population-based grouped survival data to estimate the personal cure rate. Using the colorectal cancer survival data from the Surveillance, Epidemiology and End Results Programme, we estimate the probabilities of dying from colorectal cancer, heart disease, and other causes by age at diagnosis, race and American Joint Committee on Cancer stage.

Estimating risk of foreign exchange portfolio: Using VaR and CVaR based on GARCH-EVT-Copula model

NASA Astrophysics Data System (ADS)

Wang, Zong-Run; Chen, Xiao-Hong; Jin, Yan-Bo; Zhou, Yan-Ju

2010-11-01

This paper introduces GARCH-EVT-Copula model and applies it to study the risk of foreign exchange portfolio. Multivariate Copulas, including Gaussian, t and Clayton ones, were used to describe a portfolio risk structure, and to extend the analysis from a bivariate to an n-dimensional asset allocation problem. We apply this methodology to study the returns of a portfolio of four major foreign currencies in China, including USD, EUR, JPY and HKD. Our results suggest that the optimal investment allocations are similar across different Copulas and confidence levels. In addition, we find that the optimal investment concentrates on the USD investment. Generally speaking, t Copula and Clayton Copula better portray the correlation structure of multiple assets than Normal Copula.

Comparison of time series models for predicting campylobacteriosis risk in New Zealand.

PubMed

Al-Sakkaf, A; Jones, G

2014-05-01

Predicting campylobacteriosis cases is a matter of considerable concern in New Zealand, after the number of the notified cases was the highest among the developed countries in 2006. Thus, there is a need to develop a model or a tool to predict accurately the number of campylobacteriosis cases as the Microbial Risk Assessment Model used to predict the number of campylobacteriosis cases failed to predict accurately the number of actual cases. We explore the appropriateness of classical time series modelling approaches for predicting campylobacteriosis. Finding the most appropriate time series model for New Zealand data has additional practical considerations given a possible structural change, that is, a specific and sudden change in response to the implemented interventions. A univariate methodological approach was used to predict monthly disease cases using New Zealand surveillance data of campylobacteriosis incidence from 1998 to 2009. The data from the years 1998 to 2008 were used to model the time series with the year 2009 held out of the data set for model validation. The best two models were then fitted to the full 1998-2009 data and used to predict for each month of 2010. The Holt-Winters (multiplicative) and ARIMA (additive) intervention models were considered the best models for predicting campylobacteriosis in New Zealand. It was noticed that the prediction by an additive ARIMA with intervention was slightly better than the prediction by a Holt-Winter multiplicative method for the annual total in year 2010, the former predicting only 23 cases less than the actual reported cases. It is confirmed that classical time series techniques such as ARIMA with intervention and Holt-Winters can provide a good prediction performance for campylobacteriosis risk in New Zealand. The results reported by this study are useful to the New Zealand Health and Safety Authority's efforts in addressing the problem of the campylobacteriosis epidemic. © 2013 Blackwell Verlag GmbH.

Enhanced project management tool

NASA Technical Reports Server (NTRS)

Hsu, Chen-Jung (Inventor); Patel, Hemil N. (Inventor); Maluf, David A. (Inventor); Moh Hashim, Jairon C. (Inventor); Tran, Khai Peter B. (Inventor)

2012-01-01

A system for managing a project that includes multiple tasks and a plurality of workers. Input information includes characterizations based upon a human model, a team model and a product model. Periodic reports, such as one or more of a monthly report, a task plan report, a schedule report, a budget report and a risk management report, are generated and made available for display or further analysis or collection into a customized report template. An extensible database allows searching for information based upon context and upon content. Seven different types of project risks are addressed, including non-availability of required skill mix of workers. The system can be configured to exchange data and results with corresponding portions of similar project analyses, and to provide user-specific access to specified information.

Parental Depression and Child Cognitive Vulnerability Predict Children’s Cortisol Reactivity

PubMed Central

Hayden, Elizabeth P.; Hankin, Benjamin L.; Mackrell, Sarah V.M.; Sheikh, Haroon I.; Jordan, Patricia L.; Dozois, David J.A.; Singh, Shiva M.; Olino, Thomas M.; Badanes, Lisa S.

2015-01-01

Risk for depression is expressed across multiple levels of analysis. For example, parental depression and cognitive vulnerability are known markers of depression risk, but no study has examined their interactive effects on children’s cortisol reactivity, a likely mediator of early depression risk. We examined relations across these different levels of vulnerability using cross-sectional and longitudinal methods in two community samples of children. Children were assessed for cognitive vulnerability using self-reports (Study 1; n = 244) and tasks tapping memory and attentional bias (Study 2; n = 205), and their parents were assessed for depression history using structured clinical interviews. In both samples, children participated in standardized stress tasks and cortisol reactivity was assessed. Cross-sectionally and longitudinally, parental depression history and child cognitive vulnerability interacted to predict children’s cortisol reactivity; specifically, associations between parent depression and elevated child cortisol activity were found when children also showed elevated depressotypic attributions, as well as attentional and memory biases. Findings indicate that models of children’s emerging depression risk may benefit from the examination of the interactive effects of multiple sources of vulnerability across levels of analysis. PMID:25422972

Multiple Chronic Conditions and Disparities in 30-Day Hospital Readmissions Among Nonelderly Adults.

PubMed

Basu, Jayasree; Hanchate, Amresh; Koroukian, Siran

2018-05-15

This study examines the patterns of 30-day hospital readmissions by race/ethnicity and multiple chronic conditions (MCC) burden among nonelderly adult patients. We used hospital discharge data of patients in the 18- to 64-year age group in 5 US states, California, Florida, Missouri, New York, and Tennessee, for 2009 from the Healthcare Cost and Utilization Project State Inpatient Database (HCUP-SID) of the Agency for Healthcare Research and Quality, linked to contextual and provider data from the Health Resources and Services Administration. A multilevel logistic regression model was used for data pooled over 5 states, adjusting for patient, hospital, and community characteristics. Controlling for other covariates, the study found that a higher MCC burden was associated with a higher all-cause 30-day readmission risk. We found considerable heterogeneity in levels of readmission risk among racial/ethnic subgroups stratified by chronic conditions. Among patients with a lowest MCC burden, African Americans had the highest risk of readmission, but with a higher MCC burden, the risk of readmission increased most for Hispanics.

Finding the numerical compensation in multiple criteria decision-making problems under fuzzy environment

NASA Astrophysics Data System (ADS)

Gupta, Mahima; Mohanty, B. K.

2017-04-01

In this paper, we have developed a methodology to derive the level of compensation numerically in multiple criteria decision-making (MCDM) problems under fuzzy environment. The degree of compensation is dependent on the tranquility and anxiety level experienced by the decision-maker while taking the decision. Higher tranquility leads to the higher realisation of the compensation whereas the increased level of anxiety reduces the amount of compensation in the decision process. This work determines the level of tranquility (or anxiety) using the concept of fuzzy sets and its various level sets. The concepts of indexing of fuzzy numbers, the risk barriers and the tranquility level of the decision-maker are used to derive his/her risk prone or risk averse attitude of decision-maker in each criterion. The aggregation of the risk levels in each criterion gives us the amount of compensation in the entire MCDM problem. Inclusion of the compensation leads us to model the MCDM problem as binary integer programming problem (BIP). The solution to BIP gives us the compensatory decision to MCDM. The proposed methodology is illustrated through a numerical example.

Prognostic factors in multiple myeloma: definition of risk groups in 410 previously untreated patients: a Grupo Argentino de Tratamiento de la Leucemia Aguda study.

PubMed

Corrado, C; Santarelli, M T; Pavlovsky, S; Pizzolato, M

1989-12-01

Four hundred ten previously untreated multiple myeloma patients entered onto two consecutive Grupo Argentino de Tratamiento de la Leucemia Aguda (GATLA) protocols were analyzed to identify significant prognostic factors influencing survival. The univariate analysis selected the following variables: performance status, renal function, percentage of bone marrow plasma cells at diagnosis, hemoglobin, and age. A multivariate analysis showed that performance status, renal function, percentage of bone marrow plasma cells, hemoglobin, and age were the best predictive variables for survival. A score was assigned to each patient according to these variables, which led to their classification in three groups: good, intermediate, and poor risk, with a probability of survival of 26% and 10% at 96 months, and 5% at 56 months, and median survival of 60, 37, and 14 months, respectively (P = .0000). In our patient population, this model proved to be superior to the Durie-Salmon staging system in defining prognostic risk groups, and separating patients with significantly different risks within each Durie-Salmon stage.

NASA Human Research Program Space Radiation Program Element

NASA Technical Reports Server (NTRS)

Chappell, Lori; Huff, Janice; Patel, Janapriya; Wang, Minli; Hu, Shaowwen; Kidane, Yared; Myung-Hee, Kim; Li, Yongfeng; Nounu, Hatem; Plante, Ianik;

Conflict effects without conflict in anterior cingulate cortex: multiple response effects and context specific representations

PubMed Central

Brown, Joshua W.

2009-01-01

The error likelihood computational model of anterior cingulate cortex (ACC) (Brown & Braver, 2005) has successfully predicted error likelihood effects, risk prediction effects, and how individual differences in conflict and error likelihood effects vary with trait differences in risk aversion. The same computational model now makes a further prediction that apparent conflict effects in ACC may result in part from an increasing number of simultaneously active responses, regardless of whether or not the cued responses are mutually incompatible. In Experiment 1, the model prediction was tested with a modification of the Eriksen flanker task, in which some task conditions require two otherwise mutually incompatible responses to be generated simultaneously. In that case, the two response processes are no longer in conflict with each other. The results showed small but significant medial PFC effects in the incongruent vs. congruent contrast, despite the absence of response conflict, consistent with model predictions. This is the multiple response effect. Nonetheless, actual response conflict led to greater ACC activation, suggesting that conflict effects are specific to particular task contexts. In Experiment 2, results from a change signal task suggested that the context dependence of conflict signals does not depend on error likelihood effects. Instead, inputs to ACC may reflect complex and task specific representations of motor acts, such as bimanual responses. Overall, the results suggest the existence of a richer set of motor signals monitored by medial PFC and are consistent with distinct effects of multiple responses, conflict, and error likelihood in medial PFC. PMID:19375509

A Decision Model for Supporting Task Allocation Processes in Global Software Development

NASA Astrophysics Data System (ADS)

Lamersdorf, Ansgar; Münch, Jürgen; Rombach, Dieter

Today, software-intensive systems are increasingly being developed in a globally distributed way. However, besides its benefit, global development also bears a set of risks and problems. One critical factor for successful project management of distributed software development is the allocation of tasks to sites, as this is assumed to have a major influence on the benefits and risks. We introduce a model that aims at improving management processes in globally distributed projects by giving decision support for task allocation that systematically regards multiple criteria. The criteria and causal relationships were identified in a literature study and refined in a qualitative interview study. The model uses existing approaches from distributed systems and statistical modeling. The article gives an overview of the problem and related work, introduces the empirical and theoretical foundations of the model, and shows the use of the model in an example scenario.

Young Adult and Usual Adult Body Mass Index and Multiple Myeloma Risk: A Pooled Analysis in the International Multiple Myeloma Consortium (IMMC).

PubMed

Birmann, Brenda M; Andreotti, Gabriella; De Roos, Anneclaire J; Camp, Nicola J; Chiu, Brian C H; Spinelli, John J; Becker, Nikolaus; Benhaim-Luzon, Véronique; Bhatti, Parveen; Boffetta, Paolo; Brennan, Paul; Brown, Elizabeth E; Cocco, Pierluigi; Costas, Laura; Cozen, Wendy; de Sanjosé, Silvia; Foretová, Lenka; Giles, Graham G; Maynadié, Marc; Moysich, Kirsten; Nieters, Alexandra; Staines, Anthony; Tricot, Guido; Weisenburger, Dennis; Zhang, Yawei; Baris, Dalsu; Purdue, Mark P

2017-06-01

Background: Multiple myeloma risk increases with higher adult body mass index (BMI). Emerging evidence also supports an association of young adult BMI with multiple myeloma. We undertook a pooled analysis of eight case-control studies to further evaluate anthropometric multiple myeloma risk factors, including young adult BMI. Methods: We conducted multivariable logistic regression analysis of usual adult anthropometric measures of 2,318 multiple myeloma cases and 9,609 controls, and of young adult BMI (age 25 or 30 years) for 1,164 cases and 3,629 controls. Results: In the pooled sample, multiple myeloma risk was positively associated with usual adult BMI; risk increased 9% per 5-kg/m 2 increase in BMI [OR, 1.09; 95% confidence interval (CI), 1.04-1.14; P = 0.007]. We observed significant heterogeneity by study design ( P = 0.04), noting the BMI-multiple myeloma association only for population-based studies ( P trend = 0.0003). Young adult BMI was also positively associated with multiple myeloma (per 5-kg/m 2 ; OR, 1.2; 95% CI, 1.1-1.3; P = 0.0002). Furthermore, we observed strong evidence of interaction between younger and usual adult BMI ( P interaction <0.0001); we noted statistically significant associations with multiple myeloma for persons overweight (25-<30 kg/m 2 ) or obese (30+ kg/m 2 ) in both younger and usual adulthood (vs. individuals consistently <25 kg/m 2 ), but not for those overweight or obese at only one time period. Conclusions: BMI-associated increases in multiple myeloma risk were highest for individuals who were overweight or obese throughout adulthood. Impact: These findings provide the strongest evidence to date that earlier and later adult BMI may increase multiple myeloma risk and suggest that healthy BMI maintenance throughout life may confer an added benefit of multiple myeloma prevention. Cancer Epidemiol Biomarkers Prev; 26(6); 876-85. ©2017 AACR . ©2017 American Association for Cancer Research.

Household-level disparities in cancer risks from vehicular air pollution in Miami

NASA Astrophysics Data System (ADS)

Collins, Timothy W.; Grineski, Sara E.; Chakraborty, Jayajit

2015-09-01

Environmental justice (EJ) research has relied on ecological analyses of socio-demographic data from areal units to determine if particular populations are disproportionately burdened by toxic risks. This article advances quantitative EJ research by (a) examining whether statistical associations found for geographic units translate to relationships at the household level; (b) testing alternative explanations for distributional injustices never before investigated; and (c) applying a novel statistical technique appropriate for geographically-clustered data. Our study makes these advances by using generalized estimating equations to examine distributive environmental inequities in the Miami (Florida) metropolitan area, based on primary household-level survey data and census block-level cancer risk estimates of hazardous air pollutant (HAP) exposure from on-road mobile emission sources. In addition to modeling determinants of on-road HAP cancer risk among all survey participants, two subgroup models are estimated to examine whether determinants of risk differ based on disadvantaged minority (Hispanic and non-Hispanic Black) versus non-Hispanic white racial/ethnic status. Results reveal multiple determinants of risk exposure disparities. In the model including all survey participants, renter-occupancy, Hispanic and non-Hispanic black race/ethnicity, the desire to live close to work/urban services or public transportation, and higher risk perception are associated with greater on-road HAP cancer risk; the desire to live in an amenity-rich environment is associated with less risk. Divergent subgroup model results shed light on the previously unexamined role of racial/ethnic status in shaping determinants of risk exposures. While lower socioeconomic status and higher risk perception predict significantly greater on-road HAP cancer risk among disadvantaged minorities, the desire to live near work/urban services or public transport predict significantly greater risk among non-Hispanic whites. Findings have important implications for EJ research and practice in Miami and elsewhere.

Pre- and Perinatal Risk for Attention-Deficit Hyperactivity Disorder: Does Neuropsychological Weakness Explain the Link?

PubMed

Wiggs, Kelsey; Elmore, Alexis L; Nigg, Joel T; Nikolas, Molly A

2016-11-01

Etiological investigations of attention-deficit hyperactivity disorder (ADHD) and disruptive behavior problems support multiple causal pathways, including involvement of pre- and perinatal risk factors. Because these risks occur early in life, well before observable ADHD and externalizing symptoms emerge, the relation between risk and symptoms may be mediated by neurodevelopmental effects that manifest later in neuropsychological functioning. However, potential dissociable effects of pre/perinatal risk elements on ADHD and familial confounds must also be considered to test alternative hypotheses. 498 youth aged 6-17 years (55.0 % male) completed a multi-stage, multi-informant assessment including parent and teacher symptom reports of symptoms and parent ratings of pre/perinatal health risk indicators. Youth completed a neuropsychological testing battery. Multiple mediation models examined direct effects of pre- and perinatal health risk on ADHD and other disruptive behavior disorder symptoms and indirect effects via neuropsychological functioning. Parental ADHD symptoms and externalizing status was covaried to control for potential familial effects. Effects of prenatal substance exposure on inattention were mediated by memory span and temporal processing deficits. Further, effects of perinatal health risk on inattention, hyperactivity-impulsivity, and ODD were mediated by deficits in response variability and temporal processing. Further, maternal health risks during pregnancy appeared to exert direct rather than indirect effects on outcomes. Results suggest that after controlling for familial relatedness of ADHD between parent and child, early developmental health risks may influence ADHD via effects on neuropsychological processes underpinning the disorder.

Saturation of tobacco smoking models and risk of alcohol and tobacco use among adolescents.

PubMed

Taylor, Jennifer E; Conard, Mark W; Koetting O'Byrne, Kristin; Haddock, C Keith; Poston, W S Carlos

2004-09-01

To examine how saturation of an adolescent's environment with models of cigarette smoking (e.g., parents, siblings, friends) affects the probability of tobacco and alcohol use among junior high and high school students. The Health and Smoking Questionnaire was administered to 806 adolescents (182 smokers and 624 nonsmokers; 57.2% female) average age of 15.1 years (SD = 1.6) in a mid-size Midwestern town. The questionnaire contains standardized items in five domains: demographics, smoking status and history, perceptions of risk and risk reduction, risk factors for tobacco use, and parenting style. Risk for smoking or using alcohol increased dramatically as the number of models who smoke increased in an adolescent's environment. For instance, adolescents with one significant other who smoked were nearly four times (OR = 3.76, p <.001) more likely to smoke than someone with no significant others who smoked. However, if an adolescent had four significant others who smoked, they were over 160 times more likely to smoke (OR = 161.25, p <.001). Similar results were found for alcohol use; adolescents who had one significant other who smoked were more than 2.5 (OR = 2.66, p <.001) times more likely to drink than those without smoking models. Adolescents who had four significant other smoking models were 13 times (OR = 13.08, p <.001) more likely to drink. As the number of cigarette smokers in an adolescent's environment increases, risk of tobacco and alcohol use increases substantially. These data suggest that multiple models of tobacco use will substantially increase risk for substance use in adolescents.

A Risk Score for Predicting Multiple Sclerosis.

PubMed

Dobson, Ruth; Ramagopalan, Sreeram; Topping, Joanne; Smith, Paul; Solanky, Bhavana; Schmierer, Klaus; Chard, Declan; Giovannoni, Gavin

2016-01-01

Multiple sclerosis (MS) develops as a result of environmental influences on the genetically susceptible. Siblings of people with MS have an increased risk of both MS and demonstrating asymptomatic changes in keeping with MS. We set out to develop an MS risk score integrating both genetic and environmental risk factors. We used this score to identify siblings at extremes of MS risk and attempted to validate the score using brain MRI. 78 probands with MS, 121 of their unaffected siblings and 103 healthy controls were studied. Personal history was taken, and serological and genetic analysis using the illumina immunochip was performed. Odds ratios for MS associated with each risk factor were derived from existing literature, and the log values of the odds ratios from each of the risk factors were combined in an additive model to provide an overall score. Scores were initially calculated using log odds ratio from the HLA-DRB1*1501 allele only, secondly using data from all MS-associated SNPs identified in the 2011 GWAS. Subjects with extreme risk scores underwent validation studies. MRI was performed on selected individuals. There was a significant difference in the both risk scores between people with MS, their unaffected siblings and healthy controls (p<0.0005). Unaffected siblings had a risk score intermediate to people with MS and controls (p<0.0005). The best performing risk score generated an AUC of 0.82 (95%CI 0.75-0.88). The risk score demonstrates an AUC on the threshold for clinical utility. Our score enables the identification of a high-risk sibling group to inform pre-symptomatic longitudinal studies.

Risk distribution across multiple health insurance funds in rural Tanzania.

PubMed

Chomi, Eunice Nahyuha; Mujinja, Phares Gamba; Enemark, Ulrika; Hansen, Kristian; Kiwara, Angwara Dennis

2014-01-01

Multiple insurance funds serving different population groups may compromise equity due to differential revenue raising capacity and an unequal distribution of high risk members among the funds. This occurs when the funds exist without mechanisms in place to promote income and risk cross-subsidisation across the funds. This paper analyses whether the risk distribution varies across the Community Health Fund (CHF) and National Health Insurance Fund (NHIF) in two districts in Tanzania. Specifically we aim to 1) identify risk factors associated with increased utilisation of health services and 2) compare the distribution of identified risk factors among the CHF, NHIF and non-member households. Data was collected from a survey of 695 households. A multivariate logisitic regression model was used to identify risk factors for increased health care utilisation. Chi-square tests were performed to test whether the distribution of identified risk factors varied across the CHF, NHIF and non-member households. There was a higher concentration of identified risk factors among CHF households compared to those of the NHIF. Non-member households have a similar wealth status to CHF households, but a lower concentration of identified risk factors. Mechanisms for broader risk spreading and cross-subsidisation across the funds are necessary for the promotion of equity. These include risk equalisation to adjust for differential risk distribution and revenue raising capacity of the funds. Expansion of CHF coverage is equally important, by addressing non-financial barriers to CHF enrolment to encourage wealthy non-members to join, as well as subsidised membership for the poorest.

Suicide Risk Among College Student. The Intersection of Sexual Orientation and Race.

PubMed

Shadick, Richard; Backus Dagirmanjian, Faedra; Barbot, Baptiste

2015-01-01

Research on young adults in the general population has identified a relationship between sexual minority identification and risk for suicide. Differential rates of suicidal ideation and attempts have also been found across racial and ethnic groups. This study examined risk for suicide among university students, based on membership in one or more marginalized groups (sexual minority and racial minority identification). Data were collected from first-year college students (N = 4,345) at an urban university. Structural equation modeling was employed to model a suicidality construct, based on which a "risk for suicide" category system was derived. Chi-square and logistic regression analyses were then conducted to estimate the relationship between the background variables of interest and suicide risk. Students who identified as lesbian, gay, or bisexual (LGB) were associated with higher suicide risk than their heterosexual peers. Students of color were slightly less at risk than their heterosexual peers. However, LGB students of color were associated with elevated suicide risk relative to heterosexual peers. Results indicate that belonging to multiple marginalized groups may increase one's risk for suicide, though these effects are not simply additive. Findings highlight the complexity of the intersection between marginalized identities and suicidality.

The Abdominal Aortic Aneurysm Statistically Corrected Operative Risk Evaluation (AAA SCORE) for predicting mortality after open and endovascular interventions.

PubMed

Ambler, Graeme K; Gohel, Manjit S; Mitchell, David C; Loftus, Ian M; Boyle, Jonathan R

2015-01-01

Accurate adjustment of surgical outcome data for risk is vital in an era of surgeon-level reporting. Current risk prediction models for abdominal aortic aneurysm (AAA) repair are suboptimal. We aimed to develop a reliable risk model for in-hospital mortality after intervention for AAA, using rigorous contemporary statistical techniques to handle missing data. Using data collected during a 15-month period in the United Kingdom National Vascular Database, we applied multiple imputation methodology together with stepwise model selection to generate preoperative and perioperative models of in-hospital mortality after AAA repair, using two thirds of the available data. Model performance was then assessed on the remaining third of the data by receiver operating characteristic curve analysis and compared with existing risk prediction models. Model calibration was assessed by Hosmer-Lemeshow analysis. A total of 8088 AAA repair operations were recorded in the National Vascular Database during the study period, of which 5870 (72.6%) were elective procedures. Both preoperative and perioperative models showed excellent discrimination, with areas under the receiver operating characteristic curve of .89 and .92, respectively. This was significantly better than any of the existing models (area under the receiver operating characteristic curve for best comparator model, .84 and .88; P < .001 and P = .001, respectively). Discrimination remained excellent when only elective procedures were considered. There was no evidence of miscalibration by Hosmer-Lemeshow analysis. We have developed accurate models to assess risk of in-hospital mortality after AAA repair. These models were carefully developed with rigorous statistical methodology and significantly outperform existing methods for both elective cases and overall AAA mortality. These models will be invaluable for both preoperative patient counseling and accurate risk adjustment of published outcome data. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Spatial and Temporal Flood Risk Assessment for Decision Making Approach

NASA Astrophysics Data System (ADS)

Azizat, Nazirah; Omar, Wan-Mohd-Sabki Wan

2018-03-01

Heavy rainfall, adversely impacting inundation areas, depends on the magnitude of the flood. Significantly, location of settlements, infrastructure and facilities in floodplains result in many regions facing flooding risks. A problem faced by the decision maker in an assessment of flood vulnerability and evaluation of adaptation measures is recurrent flooding in the same areas. Identification of recurrent flooding areas and frequency of floods should be priorities for flood risk management. However, spatial and temporal variability become major factors of uncertainty in flood risk management. Therefore, dynamic and spatial characteristics of these changes in flood impact assessment are important in making decisions about the future of infrastructure development and community life. System dynamics (SD) simulation and hydrodynamic modelling are presented as tools for modelling the dynamic characteristics of flood risk and spatial variability. This paper discusses the integration between spatial and temporal information that is required by the decision maker for the identification of multi-criteria decision problems involving multiple stakeholders.

Socioeconomic disadvantage and psychological deficits: Pathways from early cumulative risk to late-adolescent criminal conviction.

PubMed

Savolainen, Jukka; Eisman, Andria; Mason, W Alex; Schwartz, Joseph A; Miettunen, Jouko; Järvelin, Marjo-Riitta

2018-06-01

Early exposure to multiple risk factors has been shown to predict criminal offending, but the mechanisms responsible for this association are poorly understood. Integrating social-environmental and dispositional theories of crime this research investigated the capacity of family socioeconomic disadvantage and individual psychological deficits to mediate the association between childhood cumulative risk and late adolescent criminal convictions. Male participants in the 1986 Northern Finland Birth Cohort Study (n = 3414) were followed from the prenatal period through age 19-20. The data were analyzed by estimating a structural equation model of the hypothesized pathways. The results found support for both processes of influence, and the model sustained a statistically significant direct effect of cumulative risk on crime. Socioeconomic disadvantage and psychological deficits contribute to criminal offending independently and with roughly equal magnitude. The results point to the utility of both environmental and psychological interventions to prevent criminality among children at risk. Copyright © 2018. Published by Elsevier Ltd.

Effects of interactions between common genetic variants and alcohol consumption on colorectal cancer risk

PubMed Central

Song, Nan; Shin, Aesun; Oh, Jae Hwan; Kim, Jeongseon

2018-01-01

Background Genome-wide association studies (GWAS) have identified approximately 40 common genetic loci associated with colorectal cancer risk. To investigate possible gene-environment interactions (GEIs) between GWAS-identified single-nucleotide polymorphisms (SNPs) and alcohol consumption with respect to colorectal cancer, a hospital-based case-control study was conducted. Results Higher levels of alcohol consumption as calculated based on a standardized definition of a drink (1 drink=12.5g of ethanol) were associated with increased risk of colorectal cancer (OR=2.47, 95% CI=1.62-3.76 for heavy drinkers [>50g/day] compared to never drinkers; ptrend<0.01). SNP rs6687758 near the DUSP10 gene at 1q41 had a statistically significant interaction with alcohol consumption in analyses of standardized drinks (p=4.6×10-3), although this did not surpass the corrected threshold for multiple testing. When stratified by alcohol consumption levels, in an additive model the risk of colorectal cancer associated with the G allele of rs6687758 tended to increase among individuals in the heavier alcohol consumption strata. A statistically significant association between rs6687758 and colorectal cancer risk was observed among moderate alcohol drinkers who consumed between >12.5 and ≤50g of alcohol per day (OR=1.46, 95% CI=1.01-2.11). Methods A total of 2,109 subjects (703 colorectal cancer patients and 1,406 healthy controls) were recruited from the Korean National Cancer Center. For genotyping, 30 GWAS-identified SNPs were selected. A logistic regression model was used to evaluate associations of SNPs and alcohol consumption with colorectal cancer risk. We also tested GEIs between SNPs and alcohol consumption using a logistic model with multiplicative interaction terms. Conclusions Our results suggest that SNP rs6687758 at 1q41 may interact with alcohol consumption in the etiology of colorectal cancer. PMID:29464080

Effects of interactions between common genetic variants and alcohol consumption on colorectal cancer risk.

PubMed

Song, Nan; Shin, Aesun; Oh, Jae Hwan; Kim, Jeongseon

2018-01-19

Genome-wide association studies (GWAS) have identified approximately 40 common genetic loci associated with colorectal cancer risk. To investigate possible gene-environment interactions (GEIs) between GWAS-identified single-nucleotide polymorphisms (SNPs) and alcohol consumption with respect to colorectal cancer, a hospital-based case-control study was conducted. Higher levels of alcohol consumption as calculated based on a standardized definition of a drink (1 drink=12.5g of ethanol) were associated with increased risk of colorectal cancer (OR=2.47, 95% CI=1.62-3.76 for heavy drinkers [>50g/day] compared to never drinkers; p trend <0.01). SNP rs6687758 near the DUSP10 gene at 1q41 had a statistically significant interaction with alcohol consumption in analyses of standardized drinks ( p =4.6×10 -3 ), although this did not surpass the corrected threshold for multiple testing. When stratified by alcohol consumption levels, in an additive model the risk of colorectal cancer associated with the G allele of rs6687758 tended to increase among individuals in the heavier alcohol consumption strata. A statistically significant association between rs6687758 and colorectal cancer risk was observed among moderate alcohol drinkers who consumed between >12.5 and ≤50g of alcohol per day (OR=1.46, 95% CI=1.01-2.11). A total of 2,109 subjects (703 colorectal cancer patients and 1,406 healthy controls) were recruited from the Korean National Cancer Center. For genotyping, 30 GWAS-identified SNPs were selected. A logistic regression model was used to evaluate associations of SNPs and alcohol consumption with colorectal cancer risk. We also tested GEIs between SNPs and alcohol consumption using a logistic model with multiplicative interaction terms. Our results suggest that SNP rs6687758 at 1q41 may interact with alcohol consumption in the etiology of colorectal cancer.

Comparative risk of cerebrovascular adverse events in community-dwelling older adults using risperidone, olanzapine and quetiapine: a multiple propensity score-adjusted retrospective cohort study.

PubMed

Chatterjee, Satabdi; Chen, Hua; Johnson, Michael L; Aparasu, Rajender R

2012-10-01

Atypical antipsychotic agents have been associated with cerebrovascular adverse events, particularly in elderly dementia patients. However, limited evidence exists regarding comparative cerebrovascular profiles of individual atypical agents, particularly in community settings. The objective of this study was to evaluate the risk of cerebrovascular events associated with use of risperidone, olanzapine and quetiapine in community-dwelling older adults in the US. A propensity score-adjusted retrospective cohort design involving the IMS LifeLink™ Health Plan Claims Database was used for the study. The study population included all older adults (aged ≥50 years) who initiated risperidone, olanzapine or quetiapine anytime during 1 July 2000 to 30 June 2008. Patients were followed until hospitalization or an emergency room visit for a cerebrovascular event, or the end of the study period, whichever occurred earlier. The Cox proportional hazard regression model with time-varying covariates was used to evaluate the risk of cerebrovascular events during the follow-up period, using olanzapine as the reference. The covariates adjusted for in the final model included multiple propensity scores and exposure to other medications that could be associated with the risk of cerebrovascular events. A total of 2,458 cerebrovascular events were identified in the study cohort: 1,081 (21.38%) for risperidone users, 816 (18.75%) for olanzapine users and 561 (21.05%) for quetiapine users. After adjusting for propensity scores and other covariates, the Cox proportional hazard model revealed that use of quetiapine [hazard ratio (HR) 0.88; 95% CI 0.78, 0.99] but not risperidone (HR 1.05; 95% CI 0.95, 1.16) was associated with a decrease in the risk of cerebrovascular adverse events compared with olanzapine. The study suggested that quetiapine use may be associated with a moderately lower risk of cerebrovascular events than olanzapine in older adults. Prescribers should closely monitor the patients treated with atypical agents for the incidence of cerebrovascular adverse events.

Spotted Towhee population dynamics in a riparian restoration context

Treesearch

Stacy L. Small; Frank R., III Thompson; Geoffery R. Geupel; John Faaborg

2007-01-01

We investigated factors at multiple scales that might influence nest predation risk for Spotted Towhees (Pipilo maculates) along the Sacramento River, California, within the context of large-scale riparian habitat restoration. We used the logistic-exposure method and Akaike's information criterion (AIC) for model selection to compare predator...

Summer School Effects in a Randomized Field Trial

ERIC Educational Resources Information Center

Zvoch, Keith; Stevens, Joseph J.

2013-01-01

This field-based randomized trial examined the effect of assignment to and participation in summer school for two moderately at-risk samples of struggling readers. Application of multiple regression models to difference scores capturing the change in summer reading fluency revealed that kindergarten students randomly assigned to summer school…

Young people's and stakeholders' perspectives of adolescent sexual risk behavior in Kilifi County, Kenya: A qualitative study.

PubMed

Ssewanyana, Derrick; Mwangala, Patrick N; Marsh, Vicki; Jao, Irene; van Baar, Anneloes; Newton, Charles R; Abubakar, Amina

2018-02-01

A lack of research exists around the most common forms of sexual risk behaviors among adolescents, including their underlying factors, in Sub-Saharan Africa. Using an Ecological Model of Adolescent Behavior, we explore the perceptions of 85 young people and 10 stakeholders on sexual risk behavior of adolescents in Kilifi County on the coast of Kenya. Our findings show that transactional sex, early sexual debut, coerced sex, and multiple sexual partnerships are prevalent. An urgent need exists to develop measures to counter sexual risk behaviors. The results contribute to understanding the range of risks and protective factors in differing contexts, tackling underlying issues at individual, family, local institutional, wider socio-economic, and political levels.

Young people’s and stakeholders’ perspectives of adolescent sexual risk behavior in Kilifi County, Kenya: A qualitative study

PubMed Central

Ssewanyana, Derrick; Mwangala, Patrick N; Marsh, Vicki; Jao, Irene; van Baar, Anneloes; Newton, Charles R; Abubakar, Amina

2017-01-01

A lack of research exists around the most common forms of sexual risk behaviors among adolescents, including their underlying factors, in Sub-Saharan Africa. Using an Ecological Model of Adolescent Behavior, we explore the perceptions of 85 young people and 10 stakeholders on sexual risk behavior of adolescents in Kilifi County on the coast of Kenya. Our findings show that transactional sex, early sexual debut, coerced sex, and multiple sexual partnerships are prevalent. An urgent need exists to develop measures to counter sexual risk behaviors. The results contribute to understanding the range of risks and protective factors in differing contexts, tackling underlying issues at individual, family, local institutional, wider socio-economic, and political levels. PMID:29076401

Risk factors for accident death in the U.S. Army, 2004-2009.

PubMed

Lewandowski-Romps, Lisa; Peterson, Christopher; Berglund, Patricia A; Collins, Stacey; Cox, Kenneth; Hauret, Keith; Jones, Bruce; Kessler, Ronald C; Mitchell, Colter; Park, Nansook; Schoenbaum, Michael; Stein, Murray B; Ursano, Robert J; Heeringa, Steven G

2014-12-01

Accidents are one of the leading causes of death among U.S. active-duty Army soldiers. Evidence-based approaches to injury prevention could be strengthened by adding person-level characteristics (e.g., demographics) to risk models tested on diverse soldier samples studied over time. To identify person-level risk indicators of accident deaths in Regular Army soldiers during a time frame of intense military operations, and to discriminate risk of not-line-of-duty from line-of-duty accident deaths. Administrative data acquired from multiple Army/Department of Defense sources for active duty Army soldiers during 2004-2009 were analyzed in 2013. Logistic regression modeling was used to identify person-level sociodemographic, service-related, occupational, and mental health predictors of accident deaths. Delayed rank progression or demotion and being male, unmarried, in a combat arms specialty, and of low rank/service length increased odds of accident death for enlisted soldiers. Unique to officers was high risk associated with aviation specialties. Accident death risk decreased over time for currently deployed, enlisted soldiers and increased for those never deployed. Mental health diagnosis was associated with risk only for previous and never-deployed, enlisted soldiers. Models did not discriminate not-line-of-duty from line-of-duty accident deaths. Adding more refined person-level and situational risk indicators to current models could enhance understanding of accident death risk specific to soldier rank and deployment status. Stable predictors could help identify high risk of accident deaths in future cohorts of Regular Army soldiers. Copyright © 2014 American Journal of Preventive Medicine. All rights reserved.

Risk Factors for Accident Death in the U.S. Army, 2004–2009

PubMed Central

Lewandowski-Romps, Lisa; Peterson, Christopher; Berglund, Patricia A.; Collins, Stacey; Cox, Kenneth; Hauret, Keith; Jones, Bruce; Kessler, Ronald C.; Mitchell, Colter; Park, Nansook; Schoenbaum, Michael; Stein, Murray B.; Ursano, Robert J.; Heeringa, Steven G.

2014-01-01

Background Accidents are one of the leading causes of death among U.S. active duty Army soldiers. Evidence-based approaches to injury prevention could be strengthened by adding person-level characteristics (e.g., demographics) to risk models tested on diverse soldier samples studied over time. Purpose To identify person-level risk indicators of accident deaths in Regular Army soldiers during a time frame of intense military operations, and to discriminate risk of not-line-of-duty (NLOD) from line-of-duty (LOD) accident deaths. Methods Administrative data acquired from multiple Army/Department of Defense sources for active duty Army soldiers during 2004–2009 were analyzed in 2013. Logistic regression modeling was used to identify person-level sociodemographic, service-related, occupational, and mental health predictors of accident deaths. Results Delayed rank progression or demotion and being male, unmarried, in a combat arms specialty, and of low rank/service length increased odds of accident death for enlisted soldiers. Unique to officers was high risk associated with aviation specialties. Accident death risk decreased over time for currently deployed, enlisted soldiers while increasing for those never deployed. Mental health diagnosis was associated with risk only for previous and never-deployed, enlisted soldiers. Models did not discriminate NLOD from LOD accident deaths. Conclusions Adding more refined person-level and situational risk indicators to current models could enhance understanding of accident death risk specific to soldier rank and deployment status. Stable predictors could help identify high risk of accident deaths in future cohorts of Regular Army soldiers. PMID:25441238

Multiple births associated with assisted human reproduction in Canada.

PubMed

Cook, Jocelynn L; Geran, Leslie; Rotermann, Michelle

2011-06-01

Assisted human reproduction has been associated with increased rates of multiple births. Data suggest that twins and higher order multiple pregnancies are at risk for pre- and postnatal health complications that contribute to stress on both the family and the Canadian health care system. No published Canadian data estimate the contribution of assisted human reproduction to multiple birth rates. This study was designed to determine the contributions of age and assisted human reproduction to multiple birth rates in Canada. We performed analyses of existing Canadian databases, using a mathematical model from the Centers for Disease Control and Prevention. More specifically, data from the Canadian Vital Statistics: Births and Stillbirths database were combined with data from the Canadian Assisted Reproductive Technologies Register collected by the Canadian Fertility and Andrology Society. Datasets were standardized to age distributions of mothers in 1978. RESULTS suggest that in vitro fertilization, ovulation induction, and age each contribute more to the rates of triplets than to twins. As expected, the contribution of natural factors was higher to twins than to triplets. These are the first Canadian data analyzed to separate and measure the contributions of age and assisted reproductive technologies to multiple birth rates. Our findings are important for guiding physician and patient education and informing the development of treatment protocols that will result in lower-risk pregnancies and improved long-term health for women and their offspring.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-01-01

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

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.

Combining multiple imputation and meta-analysis with individual participant data

PubMed Central

Burgess, Stephen; White, Ian R; Resche-Rigon, Matthieu; Wood, Angela M

2013-01-01

Multiple imputation is a strategy for the analysis of incomplete data such that the impact of the missingness on the power and bias of estimates is mitigated. When data from multiple studies are collated, we can propose both within-study and multilevel imputation models to impute missing data on covariates. It is not clear how to choose between imputation models or how to combine imputation and inverse-variance weighted meta-analysis methods. This is especially important as often different studies measure data on different variables, meaning that we may need to impute data on a variable which is systematically missing in a particular study. In this paper, we consider a simulation analysis of sporadically missing data in a single covariate with a linear analysis model and discuss how the results would be applicable to the case of systematically missing data. We find in this context that ensuring the congeniality of the imputation and analysis models is important to give correct standard errors and confidence intervals. For example, if the analysis model allows between-study heterogeneity of a parameter, then we should incorporate this heterogeneity into the imputation model to maintain the congeniality of the two models. In an inverse-variance weighted meta-analysis, we should impute missing data and apply Rubin's rules at the study level prior to meta-analysis, rather than meta-analyzing each of the multiple imputations and then combining the meta-analysis estimates using Rubin's rules. We illustrate the results using data from the Emerging Risk Factors Collaboration. PMID:23703895

Reduced Incidence of Invasive Breast Cancer With Raloxifene Among Women at Increased Coronary Risk

PubMed Central

Grady, Deborah; Cauley, Jane A.; Geiger, Mary Jane; Kornitzer, Marcel; Mosca, Lori; Collins, Peter; Wenger, Nanette K.; Song, Jingli; Mershon, John; Barrett-Connor, Elizabeth

2013-01-01

Background In the Raloxifene Use for The Heart trial, 10 101 postmenopausal women with coronary heart disease (CHD) or multiple CHD risk factors were randomly assigned to 60 mg/d raloxifene or to placebo and followed for a median of 5.6 years. Raloxifene, a selective estrogen receptor modulator, was found to reduce the risk of invasive breast cancer and vertebral fractures but not the risk of cardiovascular events. Here, we provide further details about breast cancer incidence by tumor characteristics, duration of treatment, and subgroup. Methods Reported breast cancer was adjudicated by an independent committee based on medical records and pathology reports. The primary analyses used Cox proportional hazards models with time to first breast cancer as the outcome. Subgroup effects were analyzed using similar models with terms for treatment by subgroup. All statistical tests were two-sided. Results As previously reported, raloxifene reduced the incidence of invasive breast cancer by 44% (hazard ratio [HR] = 0.56; 95% confidence interval [CI] = 0.38 to 0.83; absolute risk reduction = 1.2 invasive breast cancers per 1000 women treated for 1 year). The lower incidence of invasive breast cancer reflected a 55% lower incidence of invasive estrogen receptor (ER)–positive tumors (HR = 0.45; 95% CI = 0.28 to 0.72). However, raloxifene treatment did not reduce the incidence of noninvasive breast cancer or of invasive ER-negative breast cancer. The reduced incidence of invasive breast cancer was similar across subgroups, including those defined by age, body mass index, family history of breast cancer, prior use of postmenopausal hormones, and 5-year estimated risk of invasive breast cancer. Conclusion Raloxifene reduces risk of invasive ER-positive breast cancer regardless of a woman's baseline breast cancer risk but does not reduce risk of noninvasive or ER-negative breast cancers. These results confirm those of the Multiple Outcomes of Raloxifene Evaluation, a previous randomized trial among women with osteoporosis. PMID:18544744

Multiple ecosystem services in a working landscape

PubMed Central

Eastburn, Danny J.; O’Geen, Anthony T.; Tate, Kenneth W.; Roche, Leslie M.

2017-01-01

Policy makers and practitioners are in need of useful tools and models for assessing ecosystem service outcomes and the potential risks and opportunities of ecosystem management options. We utilize a state-and-transition model framework integrating dynamic soil and vegetation properties to examine multiple ecosystem services—specifically agricultural production, biodiversity and habitat, and soil health—across human created vegetation states in a managed oak woodland landscape in a Mediterranean climate. We found clear tradeoffs and synergies in management outcomes. Grassland states maximized agricultural productivity at a loss of soil health, biodiversity, and other ecosystem services. Synergies existed among multiple ecosystem services in savanna and woodland states with significantly larger nutrient pools, more diversity and native plant richness, and less invasive species. This integrative approach can be adapted to a diversity of working landscapes to provide useful information for science-based ecosystem service valuations, conservation decision making, and management effectiveness assessments. PMID:28301475

Multiple ecosystem services in a working landscape.

PubMed

Eastburn, Danny J; O'Geen, Anthony T; Tate, Kenneth W; Roche, Leslie M

2017-01-01

Policy makers and practitioners are in need of useful tools and models for assessing ecosystem service outcomes and the potential risks and opportunities of ecosystem management options. We utilize a state-and-transition model framework integrating dynamic soil and vegetation properties to examine multiple ecosystem services-specifically agricultural production, biodiversity and habitat, and soil health-across human created vegetation states in a managed oak woodland landscape in a Mediterranean climate. We found clear tradeoffs and synergies in management outcomes. Grassland states maximized agricultural productivity at a loss of soil health, biodiversity, and other ecosystem services. Synergies existed among multiple ecosystem services in savanna and woodland states with significantly larger nutrient pools, more diversity and native plant richness, and less invasive species. This integrative approach can be adapted to a diversity of working landscapes to provide useful information for science-based ecosystem service valuations, conservation decision making, and management effectiveness assessments.

External Validity of a Risk Stratification Score Predicting Early Distant Brain Failure and Salvage Whole Brain Radiation Therapy After Stereotactic Radiosurgery for Brain Metastases.

PubMed

Press, Robert H; Boselli, Danielle M; Symanowski, James T; Lankford, Scott P; McCammon, Robert J; Moeller, Benjamin J; Heinzerling, John H; Fasola, Carolina E; Burri, Stuart H; Patel, Kirtesh R; Asher, Anthony L; Sumrall, Ashley L; Curran, Walter J; Shu, Hui-Kuo G; Crocker, Ian R; Prabhu, Roshan S

2017-07-01

A scoring system using pretreatment factors was recently published for predicting the risk of early (≤6 months) distant brain failure (DBF) and salvage whole brain radiation therapy (WBRT) after stereotactic radiosurgery (SRS) alone. Four risk factors were identified: (1) lack of prior WBRT; (2) melanoma or breast histologic features; (3) multiple brain metastases; and (4) total volume of brain metastases <1.3 cm 3 , with each factor assigned 1 point. The purpose of this study was to assess the validity of this scoring system and its appropriateness for clinical use in an independent external patient population. We reviewed the records of 247 patients with 388 brain metastases treated with SRS between 2010 at 2013 at Levine Cancer Institute. The Press (Emory) risk score was calculated and applied to the validation cohort population, and subsequent risk groups were analyzed using cumulative incidence. The low-risk (LR) group had a significantly lower risk of early DBF than did the high-risk (HR) group (22.6% vs 44%, P=.004), but there was no difference between the HR and intermediate-risk (IR) groups (41.2% vs 44%, P=.79). Total lesion volume <1.3 cm 3  (P=.004), malignant melanoma (P=.007), and multiple metastases (P<.001) were validated as predictors for early DBF. Prior WBRT and breast cancer histologic features did not retain prognostic significance. Risk stratification for risk of early salvage WBRT were similar, with a trend toward an increased risk for HR compared with LR (P=.09) but no difference between IR and HR (P=.53). The 3-level Emory risk score was shown to not be externally valid, but the model was able to stratify between 2 levels (LR and not-LR [combined IR and HR]) for early (≤6 months) DBF. These results reinforce the importance of validating predictive models in independent cohorts. Further refinement of this scoring system with molecular information and in additional contemporary patient populations is warranted. Copyright © 2017 Elsevier Inc. All rights reserved.

Multisite external validation of a risk prediction model for the diagnosis of blood stream infections in febrile pediatric oncology patients without severe neutropenia.

PubMed

Esbenshade, Adam J; Zhao, Zhiguo; Aftandilian, Catherine; Saab, Raya; Wattier, Rachel L; Beauchemin, Melissa; Miller, Tamara P; Wilkes, Jennifer J; Kelly, Michael J; Fernbach, Alison; Jeng, Michael; Schwartz, Cindy L; Dvorak, Christopher C; Shyr, Yu; Moons, Karl G M; Sulis, Maria-Luisa; Friedman, Debra L

2017-10-01

Pediatric oncology patients are at an increased risk of invasive bacterial infection due to immunosuppression. The risk of such infection in the absence of severe neutropenia (absolute neutrophil count ≥ 500/μL) is not well established and a validated prediction model for blood stream infection (BSI) risk offers clinical usefulness. A 6-site retrospective external validation was conducted using a previously published risk prediction model for BSI in febrile pediatric oncology patients without severe neutropenia: the Esbenshade/Vanderbilt (EsVan) model. A reduced model (EsVan2) excluding 2 less clinically reliable variables also was created using the initial EsVan model derivative cohort, and was validated using all 5 external validation cohorts. One data set was used only in sensitivity analyses due to missing some variables. From the 5 primary data sets, there were a total of 1197 febrile episodes and 76 episodes of bacteremia. The overall C statistic for predicting bacteremia was 0.695, with a calibration slope of 0.50 for the original model and a calibration slope of 1.0 when recalibration was applied to the model. The model performed better in predicting high-risk bacteremia (gram-negative or Staphylococcus aureus infection) versus BSI alone, with a C statistic of 0.801 and a calibration slope of 0.65. The EsVan2 model outperformed the EsVan model across data sets with a C statistic of 0.733 for predicting BSI and a C statistic of 0.841 for high-risk BSI. The results of this external validation demonstrated that the EsVan and EsVan2 models are able to predict BSI across multiple performance sites and, once validated and implemented prospectively, could assist in decision making in clinical practice. Cancer 2017;123:3781-3790. © 2017 American Cancer Society. © 2017 American Cancer Society.

A simple rapid approach using coupled multivariate statistical methods, GIS and trajectory models to delineate areas of common oil spill risk

NASA Astrophysics Data System (ADS)

Guillen, George; Rainey, Gail; Morin, Michelle

2004-04-01

Currently, the Minerals Management Service uses the Oil Spill Risk Analysis model (OSRAM) to predict the movement of potential oil spills greater than 1000 bbl originating from offshore oil and gas facilities. OSRAM generates oil spill trajectories using meteorological and hydrological data input from either actual physical measurements or estimates generated from other hydrological models. OSRAM and many other models produce output matrices of average, maximum and minimum contact probabilities to specific landfall or target segments (columns) from oil spills at specific points (rows). Analysts and managers are often interested in identifying geographic areas or groups of facilities that pose similar risks to specific targets or groups of targets if a spill occurred. Unfortunately, due to the potentially large matrix generated by many spill models, this question is difficult to answer without the use of data reduction and visualization methods. In our study we utilized a multivariate statistical method called cluster analysis to group areas of similar risk based on potential distribution of landfall target trajectory probabilities. We also utilized ArcView™ GIS to display spill launch point groupings. The combination of GIS and multivariate statistical techniques in the post-processing of trajectory model output is a powerful tool for identifying and delineating areas of similar risk from multiple spill sources. We strongly encourage modelers, statistical and GIS software programmers to closely collaborate to produce a more seamless integration of these technologies and approaches to analyzing data. They are complimentary methods that strengthen the overall assessment of spill risks.

Integrative assessment of multiple pesticides as risk factors for non-Hodgkin's lymphoma among men.

PubMed

De Roos, A J; Zahm, S H; Cantor, K P; Weisenburger, D D; Holmes, F F; Burmeister, L F; Blair, A

2003-09-01

An increased rate of non-Hodgkin's lymphoma (NHL) has been repeatedly observed among farmers, but identification of specific exposures that explain this observation has proven difficult. During the 1980s, the National Cancer Institute conducted three case-control studies of NHL in the midwestern United States. These pooled data were used to examine pesticide exposures in farming as risk factors for NHL in men. The large sample size (n = 3417) allowed analysis of 47 pesticides simultaneously, controlling for potential confounding by other pesticides in the model, and adjusting the estimates based on a prespecified variance to make them more stable. Reported use of several individual pesticides was associated with increased NHL incidence, including organophosphate insecticides coumaphos, diazinon, and fonofos, insecticides chlordane, dieldrin, and copper acetoarsenite, and herbicides atrazine, glyphosate, and sodium chlorate. A subanalysis of these "potentially carcinogenic" pesticides suggested a positive trend of risk with exposure to increasing numbers. Consideration of multiple exposures is important in accurately estimating specific effects and in evaluating realistic exposure scenarios.

Child, Parent, and Peer Predictors of Early-Onset Substance Use: A Multisite Longitudinal Study

PubMed Central

Kaplow, Julie B.; Curran, Patrick J.; Dodge, Kenneth A.

2009-01-01

The purpose of this study was to identify kindergarten-age predictors of early-onset substance use from demographic, environmental, parenting, child psychological, behavioral, and social functioning domains. Data from a longitudinal study of 295 children were gathered using multiple-assessment methods and multiple informants in kindergarten and 1st grade. Annual assessments at ages 10, 11, and 12 reflected that 21% of children reported having initiated substance use by age 12. Results from longitudinal logistic regression models indicated that risk factors at kindergarten include being male, having a parent who abused substances, lower levels of parental verbal reasoning, higher levels of overactivity, more thought problems, and more social problem solving skills deficits. Children with no risk factors had less than a 10% chance of initiating substance use by age 12, whereas children with 2 or more risk factors had greater than a 50% chance of initiating substance use. Implications for typology, etiology, and prevention are discussed. PMID:12041707