Sampling from a Bayesian Menu

Discussion of "Bayesian Models and Methods in Public Policy and Government Settings" by S. E. Fienberg [arXiv:1108.2177]Comment: Published in at http://dx.doi.org/10.1214/11-STS331C the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Flexible epidemiological model for estimates and short-term projections in generalised HIV/AIDS epidemics

International audienceObjective UNAIDS and country analysts use a simple infectious disease model, embedded in the Estimation and Projection Package (EPP), to generate annual updates on the global HIV/AIDS epidemic. Our objective was to develop modifications to the current model that improve fit to recently observed prevalence trends across countries. Methods Our proposed alternative to the current EPP approach simplifies the model structure and explicitly models changes in average infection risk over time, operationalised using penalised B-splines in a Bayesian framework. We also present an alternative approach to initiating the epidemic that improves standardisation and efficiency, and add an informative prior distribution for changes in infection risk beyond the last data point that enhances the plausibility of short-term extrapolations. Results The spline-based model produces better fits than the current model to observed prevalence trends in settings that have recently experienced levelling or rising prevalence following a steep decline, such as Uganda and urban Rwanda. The model also predicts a deceleration of the decline in prevalence for countries with recent experience of steady declines, such as Kenya and Zimbabwe. Estimates and projections from our alternative model are comparable to those from the current model where the latter performs well. Conclusions A more flexible epidemiological model that accommodates changing infection risk over time can provide better estimates and short-term projections of HIV/AIDS incidence, prevalence and mortality than the current EPP model. The alternative model specification can be incorporated easily into existing analytical tools that are used to produce updates on the global HIV/AIDS epidemic

Estimating Peer Effects in Longitudinal Dyadic Data Using Instrumental Variables

The identification of causal peer effects (also known as social contagion or induction) from observational data in social networks is challenged by two distinct sources of bias: latent homophily and unobserved confounding. In this paper, we investigate how causal peer effects of traits and behaviors can be identified using genes (or other structurally isomorphic variables) as instrumental variables (IV) in a large set of data generating models with homophily and confounding. We use directed acyclic graphs to represent these models and employ multiple IV strategies and report three main identification results. First, using a single fixed gene (or allele) as an IV will generally fail to identify peer effects if the gene affects past values of the treatment. Second, multiple fixed genes/alleles, or, more promisingly, time-varying gene expression, can identify peer effects if we instrument exclusion violations as well as the focal treatment. Third, we show that IV identification of peer effects remains possible even under multiple complications often regarded as lethal for IV identification of intra-individual effects, such as pleiotropy on observables and unobservables, homophily on past phenotype, past and ongoing homophily on genotype, inter-phenotype peer effects, population stratification, gene expression that is endogenous to past phenotype and past gene expression, and others. We apply our identification results to estimating peer effects of body mass index (BMI) among friends and spouses in the Framingham Heart Study. Results suggest a positive causal peer effect of BMI between friends

Health care payments in the asia pacific: validation of five survey measures of economic burden

Introduction: Many low and middle-income countries rely on out-of-pocket payments to help finance health care. These payments can pose financial hardships for households; valid measurement of this type of economic burden is therefore critical. This study examines the validity of five survey measures of economic burden caused by health care payments. Methods: We analyzed 2002/03 World Health Survey household-level data from four Asia Pacific countries to assess the construct validity of five measures of economic burden due to health care payments: any health expenditure, health expenditure amount, catastrophic health expenditure, indebtedness, and impoverishment. We used generalized linear models to assess the correlations between these measures and other constructs with which they have expected associations, such as health care need, wealth, and risk protection. Results: Measures of impoverishment and indebtedness most often correlated with health care need, wealth, and risk protection as expected. Having any health expenditure, a large health expenditure, or even a catastrophic health expenditure did not consistently predict degree of economic burden. Conclusions: Studies that examine economic burden attributable to health care payments should include measures of impoverishment and indebtedness

Patient and Physician Race and the Allocation of Time and Patient Engagement Efforts to Mental Health Discussions in Primary Care: An Observational Study of Audiorecorded Periodic Health Examinations

This study investigated racial differences in patient-physician communication around mental health versus biomedical issues. Data were collected from audiorecorded periodic health examinations of adults with mental health needs in the Detroit area (2007-2009). Patients and their primary care physicians conversed for twice as long, and physicians demonstrated greater empathy during mental health topics than during biomedical topics. This increase varied by patient and physician race. Patient race predicted physician empathy, but physician race predicted talk time. Interventions to improve mental health communication could be matched to specific populations based on the separate contributions of patient and physician race

Recovery from PTSD following Hurricane Katrina

Background: We examined patterns and correlates of speed of recovery of estimated posttraumatic stress disorder (PTSD) among people who developed PTSD in the wake of Hurricane Katrina. Method: A probability sample of prehurricane residents of areas affected by Hurricane Katrina was administered a telephone survey 7–19 months following the hurricane and again 24–27 months posthurricane. The baseline survey assessed PTSD using a validated screening scale and assessed a number of hypothesized predictors of PTSD recovery that included sociodemographics, prehurricane history of psychopathology, hurricane‐related stressors, social support, and social competence. Exposure to posthurricane stressors and course of estimated PTSD were assessed in a follow‐up interview. Results: An estimated 17.1% of respondents had a history of estimated hurricane‐related PTSD at baseline and 29.2% by the follow‐up survey. Of the respondents who developed estimated hurricane‐related PTSD, 39.0% recovered by the time of the follow‐up survey with a mean duration of 16.5 months. Predictors of slow recovery included exposure to a life‐threatening situation, hurricane‐related housing adversity, and high income. Other sociodemographics, history of psychopathology, social support, social competence, and posthurricane stressors were unrelated to recovery from estimated PTSD. Conclusions: The majority of adults who developed estimated PTSD after Hurricane Katrina did not recover within 18–27 months. Delayed onset was common. Findings document the importance of initial trauma exposure severity in predicting course of illness and suggest that pre‐ and posttrauma factors typically associated with course of estimated PTSD did not influence recovery following Hurricane Katrina. Depression and Anxiety, 2011.  © 2011 Wiley‐Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87167/1/20790_ftp.pd

Predictors of health-related quality of life in patients with colorectal cancer

<p>Abstract</p> <p>Background</p> <p>Most studies that have identified variables associated with the health-related quality of life (HRQL) of patients with colorectal cancer have been cross-sectional or included patients with other diagnoses. The objectives of this study were to identify predictors of HRQL in patients with colorectal cancer and interpret the clinical importance of the results.</p> <p>Methods</p> <p>We conducted a population-based longitudinal study of patients identified through three regions of the California Cancer Registry. Surveys were completed by 568 patients approximately 9 and 19 months post-diagnosis. Three HRQL outcomes from the Functional Assessment of Cancer Therapy – Colorectal (FACT-C) were evaluated: social/family well-being (SWB), emotional well-being (EWB) and the Trial Outcome Index (TOI), which is a colorectal cancer-specific summary measure of physical function and well-being. Sociodemographic, cancer/health, and healthcare variables were assessed in multivariable regression models. We computed the difference in predicted HRQL scores corresponding to a large difference in a predictor variable, defined as a 1 standard deviation difference for interval variables or the difference relative to the reference category for nominal variables. The effect of an explanatory variable on HRQL was considered clinically meaningful if the predicted score difference was at least as large as the minimally important difference.</p> <p>Results</p> <p>Common predictors of better TOI, SWB and EWB were better general health and factors related to better perceived quality of cancer care. Predictor variables in addition to general health and perceived quality of care were identified only for SWB. Being married/living as married was associated with better SWB, whereas being male or of Hispanic ethnicity was associated with worse SWB. Among the sociodemographic, cancer/health, and healthcare variables evaluated, only Hispanic ethnicity had a clinically meaningful effect on an HRQL outcome.</p> <p>Conclusion</p> <p>Our findings, particularly the information on the clinical importance of predictor variables, can help clinicians identify patients who may be at risk for poor future HRQL. Potentially modifiable factors were related to perceived quality of cancer care; thus, future research should evaluate whether improving these factors improves HRQL.</p

Cohort of Birth Modifies the Association between FTO Genotype and BMI

A substantial body of research has explored the relative roles of genetic and environmental factors on phenotype expression in humans. Recent research has also sought to identify gene-environment (or g-by-e) interactions, with mixed success. One potential reason for these mixed results may relate to the fact that genetic effects might be modified by changes in the environment over time. For example, the noted rise of obesity in the United States in the latter part of the 20th century might reflect an interaction between genetic variation and changing environmental conditions that together affect the penetrance of genetic influences. To evaluate this hypothesis, we use longitudinal data from the Framingham Heart Study collected over 30 y from a geographically relatively localized sample to test whether the well-documented association between the rs993609 variant of the FTO (fat mass and obesity associated) gene and body mass index (BMI) varies across birth cohorts, time period, and the lifecycle. Such cohort and period effects integrate many potential environmental factors, and this gene-by-environment analysis examines interactions with both time-varying contemporaneous and historical environmental influences. Using constrained linear age-period-cohort models that include family controls, we find that there is a robust relationship between birth cohort and the genotype-phenotype correlation between the FTO risk allele and BMI, with an observed inflection point for those born after 1942. These results suggest genetic influences on complex traits like obesity can vary over time, presumably because of global environmental changes that modify allelic penetrance