Gender Differences in the Influence of Protective Factors, Risk Factors, and Health Risk Behaviors on HIV Risk Behaviors Among Youth in South Florida

Adolescents engage in a range of risk behaviors during their transition from childhood to adulthood. Identifying and understanding interpersonal and socio-environmental factors that may influence risk-taking is imperative in order to meet the Healthy People 2020 goals of reducing the incidence of unintended pregnancies, HIV, and other sexually transmitted infections among youth. The purpose of this study was to investigate gender differences in the predictors of HIV risk behaviors among South Florida youth. More specifically, this study examined how protective factors, risk factors, and health risk behaviors, derived from a guiding framework using the Theory of Problem Behavior and Theory of Gender and Power, were associated with HIV risk behavior. A secondary analysis of 2009 Youth Risk Behavior Survey data sets from Miami-Dade, Broward, and Palm Beach school districts tested hypotheses for factors associated with HIV risk behaviors. The sample consisted of 5,869 high school students (mean age 16.1 years), with 69% identifying as Black or Hispanic. Logistic regression analyses revealed gender differences in the predictors of HIV risk behavior. An increase in the health risk behaviors was related to an increase in the odds that a student would engage in HIV risk behavior. An increase in risk factors was also found to significantly predict an increase in the odds of HIV risk behavior, but only in females. Also, the probability of participation in HIV risk behavior increased with grade level. Post-hoc analyses identified recent sexual activity (past 3 months) as the strongest predictor of condom nonuse and having four or more sexual partners for both genders. The strongest predictors of having sex under the influence of drugs/alcohol were alcohol use in both genders, marijuana use in females, and physical fighting in males. Gender differences in the predictors of unprotected sex, multiple sexual partners, and having sex under the influence were also found. Additional studies are warranted to understand the gender differences in predictors of HIV risk behavior among youth in order to better inform prevention programming and policy, as well as meet the national Healthy People 2020 goals.

Protect your body, your temple : Stroke Warning Signs, Symptoms, and Lowering Risk

These bookmarks state: African-Americans face higher risks of stroke. The more risk factors you have, the greater your chances of having a stroke. The best way to prevent a stroke is to reduce your risk factors. Common Risk Factors for Stroke: smoking, high blood pressure, high cholesterol, physical inactivity, obesity/overweight, diabetes. It also lists the warning signs of stroke.

Cardiorespiratory fitness and cardiometabolic risk factors in schoolchildren from Colombia: The FUPRECOL Study

The objectives of this study are to investigate the association between cardiorespiratory fitness and cardiovascular risk factors in schoolchildren and to evaluate the degree of association between overall and abdominal adiposity and cardiorespiratory fitness. A total of 1,875 children and adolescents attending public schools in Bogota, Colombia (56.2% girls; age range of 9–17.9 years). A cardiovascular risk score (Z-score) was calculated and participants were divided into tertiles according to low and high levels of overall (sum of the skinfold thicknesses) and abdominal adiposity. Schoolchildren with a high level of overall adiposity demonstrated significant differences in seven of the 10 variables analyzed (i.e. systolic and diastolic blood pressure, triglycerides, triglycerides/HDL-c ratio, total cholesterol, glucose and cardiovascular risk score). Schoolchildren with high levels of both overall and abdominal adiposity and low cardiorespiratory fitness had the least favorable cardiovascular risk factors score. These findings may be relevant to health promotion in Colombian youth.

The moderating effect of gender on the relationship between coping and suicide risk in a Portuguese community sample of adults

Background and aims(s): The study evaluated the contribution of coping strategies, based on the Toulousiane conceptualization of coping, to the prediction of suicide risk and tested the moderating effect of gender, controlling for depressive symptoms. Method: A two-time data collection design was used. A community sample of 195 adults (91 men and 104 women) ranging in age from 19 to 65 years and living in several Portuguese regions, mostly in Alentejo, participated in this research. Results: Gender, depressive symptoms, control, and withdrawal and conversion significantly predicted suicide risk and gender interacted with control, withdrawal and conversion, and social distraction in the prediction of suicide risk. Coping predicted suicide risk only for women. Conclusions: Results have important implications for assessment and intervention with suicide at-risk individuals. In particular,the evaluation and development of coping skills is indicated as a goal for therapists having suicide at-risk women as clients.

Convexity, Classification, and Risk Bounds

Many of the classification algorithms developed in the machine learning literature, including the support vector machine and boosting, can be viewed as minimum contrast methods that minimize a convex surrogate of the 0–1 loss function. The convexity makes these algorithms computationally efficient. The use of a surrogate, however, has statistical consequences that must be balanced against the computational virtues of convexity. To study these issues, we provide a general quantitative relationship between the risk as assessed using the 0–1 loss and the risk as assessed using any nonnegative surrogate loss function. We show that this relationship gives nontrivial upper bounds on excess risk under the weakest possible condition on the loss function—that it satisfies a pointwise form of Fisher consistency for classification. The relationship is based on a simple variational transformation of the loss function that is easy to compute in many applications. We also present a refined version of this result in the case of low noise, and show that in this case, strictly convex loss functions lead to faster rates of convergence of the risk than would be implied by standard uniform convergence arguments. Finally, we present applications of our results to the estimation of convergence rates in function classes that are scaled convex hulls of a finite-dimensional base class, with a variety of commonly used loss functions.

Aligning off-balance sheet risk, on-balance sheet risk and audit fees: a PLS path modelling analysis

This study focuses on using the partial least squares (PLS) path modelling technique in archival auditing research by replicating the data and research questions from prior bank audit fee studies. PLS path modelling allows for inter-correlations among audit fee determinants by establishing latent constructs and multiple relationship paths in one simultaneous PLS path model. Endogeneity concerns about auditor choice can also be addressed with PLS path modelling. With a sample of US bank holding companies for the period 2003-2009, we examine the associations among on-balance sheet financial risks, off-balance sheet risks and audit fees, and also address the pervasive client size effect, and the effect of the self-selection of auditors. The results endorse the dominating effect of size on audit fees, both directly and indirectly via its impacts on other audit fee determinants. By simultaneously considering the self-selection of auditors, we still find audit fee premiums on Big N auditors, which is the second important factor on audit fee determination. On-balance-sheet financial risk measures in terms of capital adequacy, loan composition, earnings and asset quality performance have positive impacts on audit fees. After allowing for the positive influence of on-balance sheet financial risks and entity size on off-balance sheet risk, the off-balance sheet risk measure, SECRISK, is still positively associated with bank audit fees, both before and after the onset of the financial crisis. The consistent results from this study compared with prior literature provide supporting evidence and enhance confidence on the application of this new research technique in archival accounting studies.

Aligning off-balance sheet risk, on-balance sheet risk and audit fees: a PLS path modelling analysis

This study focuses on using the partial least squares (PLS) path modelling methodology in archival auditing research by replicating the data and research questions from prior bank audit fee studies. PLS path modelling allows for inter-correlations among audit fee determinants by establishing latent constructs and multiple relationship paths in one simultaneous PLS path model. Endogeneity concerns about auditor choice can also be addressed with PLS path modelling. With a sample of US bank holding companies for the period 2003-2009, we examine the associations among on-balance sheet financial risks, off-balance sheet risks and audit fees, and also address the pervasive client size effect, and the effect of the self-selection of auditors. The results endorse the dominating effect of size on audit fees, both directly and indirectly via its impacts on other audit fee determinants. By simultaneously considering the self-selection of auditors, we still find audit fee premiums on Big N auditors, which is the second important factor on audit fee determination. On-balance-sheet financial risk measures in terms of capital adequacy, loan composition, earnings and asset quality performance have positive impacts on audit fees. After allowing for the positive influence of on-balance sheet financial risks and entity size on off-balance sheet risk, the off-balance sheet risk measure, SECRISK, is still positively associated with bank audit fees, both before and after the onset of the financial crisis. The consistent results from this study compared with prior literature provide supporting evidence and enhance confidence on the application of this new research technique in archival accounting studies.

Predicting intentions and behaviours in populations with or at-risk of diabetes: A systematic review

Purpose To systematically review the Theory of Planned Behaviour studies predicting self-care intentions and behaviours in populations with and at-risk of diabetes. Methods A systematic review using six electronic databases was conducted in 2013. A standardised protocol was used for appraisal. Studies eligibility included a measure of behaviour for healthy eating, physical activity, glucose monitoring, medication use (ii) the TPB variables (iii) the TPB tested in populations with diabetes or at-risk. Results Sixteen studies were appraised for testing the utility of the TPB. Studies included cross-sectional (n=7); prospective (n=5) and randomised control trials (n=4). Intention (18% – 76%) was the most predictive construct for all behaviours. Explained variance for intentions were similar across cross-sectional (28 -76%); prospective (28 -73%); and RCT studies (18 - 63%). RCTs (18 - 43%) provided slightly stronger evidence for predicting behaviour. Conclusions Few studies tested predictability of the TPB in populations with or at-risk of diabetes. This review highlighted differences in the predictive utility of the TPB suggesting that the model is behaviour and population specific. Findings on key determinants of specific behaviours contribute to a better understanding of mechanisms of behaviour change and are useful in designing targeted behavioural interventions for different diabetes populations.

Quantitative Trait Loci for CD4:CD8 Lymphocyte Ratio Are Associated with Risk of Type 1 Diabetes and HIV-1 Immune Control

Abnormal expansion or depletion of particular lymphocyte subsets is associated with clinical manifestations such as HIV progression to AIDS and autoimmune disease. We sought to identify genetic predictors of lymphocyte levels and reasoned that these may play a role in immune-related diseases. We tested 2.3 million variants for association with five lymphocyte subsets, measured in 2538 individuals from the general population, including CD4+ T cells, CD8+ T cells, CD56+ natural killer (NK) cells, and the derived measure CD4:CD8 ratio. We identified two regions of strong association. The first was located in the major histocompatibility complex (MHC), with multiple SNPs strongly associated with CD4:CD8 ratio (rs2524054, p = 2.1 × 10−28). The second region was centered within a cluster of genes from the Schlafen family and was associated with NK cell levels (rs1838149, p = 6.1 × 10−14). The MHC association with CD4:CD8 replicated convincingly (p = 1.4 × 10−9) in an independent panel of 988 individuals. Conditional analyses indicate that there are two major independent quantitative trait loci (QTL) in the MHC region that regulate CD4:CD8 ratio: one is located in the class I cluster and influences CD8 levels, whereas the second is located in the class II cluster and regulates CD4 levels. Jointly, both QTL explained 8% of the variance in CD4:CD8 ratio. The class I variants are also strongly associated with durable host control of HIV, and class II variants are associated with type-1 diabetes, suggesting that genetic variation at the MHC may predispose one to immune-related diseases partly through disregulation of T cell homeostasis.

A novel inflammatory biomarker, GlycA, associates with disease activity in rheumatoid arthritis and cardio-metabolic risk in BMI-matched controls

BACKGROUND: RA and CVD both have inflammation as part of the underlying biology. Our objective was to explore the relationships of GlycA, a measure of glycosylated acute phase proteins, with inflammation and cardiometabolic risk in RA, and explore whether these relationships were similar to those for persons without RA. METHODS: Plasma GlycA was determined for 50 individuals with mild-moderate RA disease activity and 39 controls matched for age, gender, and body mass index (BMI). Regression analyses were performed to assess relationships between GlycA and important markers of traditional inflammation and cardio-metabolic health: inflammatory cytokines, disease activity, measures of adiposity and insulin resistance. RESULTS: On average, RA activity was low (DAS-28 = 3.0 ± 1.4). Traditional inflammatory markers, ESR, hsCRP, IL-1β, IL-6, IL-18 and TNF-α were greater in RA versus controls (P < 0.05 for all). GlycA concentrations were significantly elevated in RA versus controls (P = 0.036). In RA, greater GlycA associated with disease activity (DAS-28; RDAS-28 = 0.5) and inflammation (RESR = 0.7, RhsCRP = 0.7, RIL-6 = 0.3: P < 0.05 for all); in BMI-matched controls, these inflammatory associations were absent or weaker (hsCRP), but GlycA was related to IL-18 (RhsCRP = 0.3, RIL-18 = 0.4: P < 0.05). In RA, greater GlycA associated with more total abdominal adiposity and less muscle density (Rabdominal-adiposity = 0.3, Rmuscle-density = -0.3, P < 0.05 for both). In BMI-matched controls, GlycA associated with more cardio-metabolic markers: BMI, waist circumference, adiposity measures and insulin resistance (R = 0.3-0.6, P < 0.05 for all). CONCLUSIONS: GlycA provides an integrated measure of inflammation with contributions from traditional inflammatory markers and cardio-metabolic sources, dominated by inflammatory markers in persons with RA and cardio-metabolic factors in those without.

Spatial attentional bias as a marker of genetic risk, symptom severity, and stimulant response in ADHD

Attention-deficit hyperactivity disorder (ADHD) is a heritable childhood onset disorder that is marked by variability at multiple levels including clinical presentation, cognitive profile, and response to stimulant medications. It has been suggested that this variability may reflect etiological differences, particularly, at the level of underlying genetics. This study examined whether an attentional phenotype-spatial attentional bias could serve as a marker of symptom severity, genetic risk, and stimulant response in ADHD. A total of 96 children and adolescents with ADHD were assessed on the Landmark Task, which is a sensitive measure of spatial attentional bias. All children were genotyped for polymorphisms (30 untranslated (UTR) and intron 8 variable number of tandem repeats (VNTRs)) of the dopamine transporter gene (DAT1). Spatial attentional bias correlated with ADHD symptom levels and varied according to DAT1 genotype. Children who were homozygous for the 10-repeat allele of the DAT1 30-UTR VNTR displayed a rightward attentional bias and had higher symptom levels compared to those with the low-risk genotype. A total of 26 of these children who were medication naive performed the Landmark Task at baseline and then again after 6 weeks of stimulant medication. Left-sided inattention (rightward bias) at baseline was associated with an enhanced response to stimulants at 6 weeks. Moreover, changes in spatial bias with stimulant medications, varied as a function of DAT1 genotype. This study suggests an attentional phenotype that relates to symptom severity and genetic risk for ADHD, and may have utility in predicting stimulant response in ADHD.

Risk of fatal injury in older adult drivers, passengers, and pedestrians

Objectives To compare risk of fatal injury in elderly road users (drivers, passengers, pedestrians) with that of younger age groups and to assess the contribution of elderly road users to the number of reported fatalities in the population. Design Fatality age was categorized as 21 to 29, 30 to 39, 40 to 49, 50 to 59, 60 to 69, or 70 and older, and road user was categorized as driver, passenger, or pedestrian. Estimated number of trips made by each age group was used to adjust for exposure and to measure individual risk. Setting Fatalities recorded in Britain between 1989 and 2009. Participants Population-wide fatal injury counts in Britain. Measurements Age of fatally injured drivers, passengers, and pedestrians. Estimated number of trips made per year by drivers, passengers, and pedestrians. Results Risk of fatal injury, but not fatality numbers in the population, were higher for older adult (=70) drivers than for younger age groups. Risk of fatal injury was also high for older adult passengers and pedestrians, who represented the majority of older adult fatalities. Conclusion Previous emphasis on driver impairment in older age has unduly focussed attention on elderly drivers, who represent a minority of all driver fatalities. Older adults represent a much larger proportion of passenger and pedestrian fatalities. Additional policy schemes and initiatives should be targeted at safeguarding older adult passengers and making the road environment safer for elderly pedestrians. © 2012, Copyright the Authors Journal compilation © 2012, The American Geriatrics Society.

Enhancement of an implemented rating model and impact on existing risk management processes: A hands-on approach from financial supplier risk management within the automotive industry

The purpose of this paper is to conduct a methodical drawback analysis of a financial supplier risk management approach which is currently implemented in the automotive industry. Based on identified methodical flaws, the risk assessment model is further developed by introducing a malus system which incorporates hidden risks into the model and by revising the derivation of the most central risk measure in the current model. Both methodical changes lead to significant enhancements in terms of risk assessment accuracy, supplier identification and workload efficiency.

A STUDY ON SOFTWARE DEVELOPMENT PROJECT RISK, RISK MANAGEMENT, PROJECT OUTCOMES AND THEIR INTER-RELATIONSHIP

This research was undertaken with an objective of studying software development project risk, risk management, project outcomes and their inter-relationship in the Indian context. Validated instruments were used to measure risk, risk management and project outcome in software development projects undertaken in India. A second order factor model was developed for risk with five first order factors. Risk management was also identified as a second order construct with four first order factors. These structures were validated using confirmatory factor analysis. Variation in risk across categories of select organization / project characteristics was studied through a series of one way ANOVA tests. Regression model was developed for each of the risk factors by linking it to risk management factors and project /organization characteristics. Similarly regression models were developed for the project outcome measures linking them to risk factors. Integrated models linking risk factors, risk management factors and project outcome measures were tested through structural equation modeling. Quality of the software developed was seen to have a positive relationship with risk management and negative relationship with risk. The other outcome variables, namely time overrun and cost over run, had strong positive relationship with risk. Risk management did not have direct effect on overrun variables. Risk was seen to be acting as an intervening variable between risk management and overrun variables.

Human exposure modelling for chemical risk assessment: a review of current approaches and research and policy implications

A wide variety of exposure models are currently employed for health risk assessments. Individual models have been developed to meet the chemical exposure assessment needs of Government, industry and academia. These existing exposure models can be broadly categorised according to the following types of exposure source: environmental, dietary, consumer product, occupational, and aggregate and cumulative. Aggregate exposure models consider multiple exposure pathways, while cumulative models consider multiple chemicals. In this paper each of these basic types of exposure model are briefly described, along with any inherent strengths or weaknesses, with the UK as a case study. Examples are given of specific exposure models that are currently used, or that have the potential for future use, and key differences in modelling approaches adopted are discussed. The use of exposure models is currently fragmentary in nature. Specific organisations with exposure assessment responsibilities tend to use a limited range of models. The modelling techniques adopted in current exposure models have evolved along distinct lines for the various types of source. In fact different organisations may be using different models for very similar exposure assessment situations. This lack of consistency between exposure modelling practices can make understanding the exposure assessment process more complex, can lead to inconsistency between organisations in how critical modelling issues are addressed (e.g. variability and uncertainty), and has the potential to communicate mixed messages to the general public. Further work should be conducted to integrate the various approaches and models, where possible and regulatory remits allow, to get a coherent and consistent exposure modelling process. We recommend the development of an overall framework for exposure and risk assessment with common approaches and methodology, a screening tool for exposure assessment, collection of better input data, probabilistic modelling, validation of model input and output and a closer working relationship between scientists and policy makers and staff from different Government departments. A much increased effort is required is required in the UK to address these issues. The result will be a more robust, transparent, valid and more comparable exposure and risk assessment process. (C) 2006 Elsevier Ltd. All rights reserved.