Bootstrap-after-Bootstrap Model Averaging for Reducing Model Uncertainty in Model Selection for Air Pollution Mortality Studies

Ba c k g r o u n d: Concerns have been raised about findings of associations between particulate matter (PM) air pollution and mortality that have been based on a single “best ” model arising from a model selection procedure, because such a strategy may ignore model uncertainty inherently involved in searching through a set of candidate models to find the best model. Model averaging has been proposed as a method of allowing for model uncertainty in this context. Objectives: To propose an extension (double BOOT) to a previously described bootstrap modelaveraging procedure (BOOT) for use in time series studies of the association between PM and mortality. We compared double BOOT and BOOT with Bayesian model averaging (BMA) and a standard method of model selection [standard Akaike’s information criterion (AIC)]. Me t h o d: Actual time series data from the United States are used to conduct a simulation study to compare and contrast the performance of double BOOT, BOOT, BMA, and standard AIC. Re s u l t s: Double BOOT produced estimates of the effect of PM on mortality that have had smaller root mean squared error than did those produced by BOOT, BMA, and standard AIC. This performance boost resulted from estimates produced by double BOOT having smaller variance than those produced by BOOTand BMA. Co n c l u s i o n s: Double BOOT is a viable alternative to BOOT and BMA for producing estimates of the mortality effect of PM. Key w o r d s: air pollution, Bayesian, bootstrap, model averaging, mortality, particulate matter. Environ Health Perspect 118:131–136 (2010). doi:10.1289/ehp.0901007 available vi

Confounding and exposure measurement error in air pollution epidemiology

Studies in air pollution epidemiology may suffer from some specific forms of confounding and exposure measurement error. This contribution discusses these, mostly in the framework of cohort studies. Evaluation of potential confounding is critical in studies of the health effects of air pollution. The association between long-term exposure to ambient air pollution and mortality has been investigated using cohort studies in which subjects are followed over time with respect to their vital status. In such studies, control for individual-level confounders such as smoking is important, as is control for area-level confounders such as neighborhood socio-economic status. In addition, there may be spatial dependencies in the survival data that need to be addressed. These issues are illustrated using the American Cancer Society Cancer Prevention II cohort. Exposure measurement error is a challenge in epidemiology because inference about health effects can be incorrect when the measured or predicted exposure used in the analysis is different from the underlying true exposure. Air pollution epidemiology rarely if ever uses personal measurements of exposure for reasons of cost and feasibility. Exposure measurement error in air pollution epidemiology comes in various dominant forms, which are different for time-series and cohort studies. The challenges are reviewed and a number of suggested solutions are discussed for both study domains

A cautionary note regarding count models of alcohol consumption in randomized controlled trials

BACKGROUND: Alcohol consumption is commonly used as a primary outcome in randomized alcohol treatment studies. The distribution of alcohol consumption is highly skewed, particularly in subjects with alcohol dependence. METHODS: In this paper, we will consider the use of count models for outcomes in a randomized clinical trial setting. These include the Poisson, over-dispersed Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial. We compare the Type-I error rate of these methods in a series of simulation studies of a randomized clinical trial, and apply the methods to the ASAP (Addressing the Spectrum of Alcohol Problems) trial. RESULTS: Standard Poisson models provide a poor fit for alcohol consumption data from our motivating example, and did not preserve Type-I error rates for the randomized group comparison when the true distribution was over-dispersed Poisson. For the ASAP trial, where the distribution of alcohol consumption featured extensive over-dispersion, there was little indication of significant randomization group differences, except when the standard Poisson model was fit. CONCLUSION: As with any analysis, it is important to choose appropriate statistical models. In simulation studies and in the motivating example, the standard Poisson was not robust when fit to over-dispersed count data, and did not maintain the appropriate Type-I error rate. To appropriately model alcohol consumption, more flexible count models should be routinely employed

A promoting early presentation intervention increases breast cancer awareness in older women after 2 years: a randomised controlled trial

BACKGROUND: We have developed the Promoting Early Presentation (PEP) Intervention to equip older women with the knowledge, skills, confidence and motivation to present promptly with breast symptoms, and thereby improve survival from breast cancer. The PEP Intervention consists of a 10-min interaction between a radiographer and an older woman, supported by a booklet. Our previous report showed that at 1 year, the PEP intervention increased the proportion who were breast cancer aware compared with usual care.METHODS: We randomised 867 women aged 67-70 years attending for their final routine appointment on the National Health Service Breast Screening Programme to receive the PEP Intervention, a booklet alone or usual care. The primary outcome was breast cancer awareness measured using a validated questionnaire asking about knowledge of breast cancer symptoms, knowledge that the risk of breast cancer increases with age and breast checking behaviour.RESULTS: At 2 years, the PEP Intervention increased the proportion who were breast cancer aware compared with usual care (21 vs 6%; odds ratio 8.1, 95% confidence interval 2.7-25.0).CONCLUSIONS: The uniquely large and sustained effect of the PEP Intervention on breast cancer awareness increases the likelihood that a woman will present promptly should she develop breast cancer symptoms up to many years later. British Journal of Cancer (2011) 105, 18-21. doi: 10.1038/bjc.2011.205 www.bjcancer.com Published online 7 June 2011 (C) 2011 Cancer Research U

Local population and regional environmental drivers of cholera in Bangladesh

<p>Abstract</p> <p>Background</p> <p>Regional environmental factors have been shown to be related to cholera. Previous work in Bangladesh found that temporal patterns of cholera are positively related to satellite-derived environmental variables including ocean chlorophyll concentration (OCC).</p> <p>Methods</p> <p>This paper investigates whether local socio-economic status (SES) modifies the effect of regional environmental forces. The study area is Matlab, Bangladesh, an area of approximately 200,000 people with an active health and demographic surveillance system. Study data include (1) spatially-referenced demographic and socio-economic characteristics of the population; (2) satellite-derived variables for sea surface temperature (SST), sea surface height (SSH), and OCC; and (3) laboratory confirmed cholera case data for the entire population. Relationships between cholera, the environmental variables, and SES are measured using generalized estimating equations with a logit link function. Additionally two separate seasonal models are built because there are two annual cholera epidemics, one pre-monsoon, and one post-monsoon.</p> <p>Results</p> <p>SES has a significant impact on cholera occurrence: the higher the SES score, the lower the occurrence of cholera. There is a significant negative association between cholera incidence and SSH during the pre-monsoon period but not for the post-monsoon period. OCC is positively associated with cholera during the pre-monsoon period but not for the post-monsoon period. SST is not related to cholera incidence.</p> <p>Conclusions</p> <p>Overall, it appears cholera is influenced by regional environmental variables during the pre-monsoon period and by local-level variables (e.g., water and sanitation) during the post-monsoon period. In both pre- and post-monsoon seasons, SES significantly influences these patterns, likely because it is a proxy for poor water quality and sanitation in poorer households.</p

Culturally-adapted and audio-technology assisted HIV/AIDS awareness and education program in rural Nigeria: a cohort study

Background: HIV-awareness programs tailored toward the needs of rural communities are needed. We sought to quantify change in HIV knowledge in three rural Nigerian villages following an integrated culturally adapted and technology assisted educational intervention. Methods: A prospective 14-week cohort study was designed to compare short-term changes in HIV knowledge between seminar-based education program and a novel program, which capitalized on the rural culture of small-group oral learning and was delivered by portable digital-audio technology. Results: Participants were mostly Moslem (99%), male (53.5%), with no formal education (55%). Baseline HIV knowledge was low (\u3c 80% correct answers for 9 of the 10 questions). Knowledge gain was higher (p \u3c 0.0001 for 8 of 10 questions) in the integrated culturally adapted and technology-facilitated (n = 511) compared with the seminar-based (n = 474) program. Conclusions: Baseline HIV-awareness was low. Culturally adapted, technology-assisted HIV education program is a feasible cost-effective method of raising HIV awareness among low-literacy rural communities

Acute symptoms related to air pollution in urban areas: a study protocol

BACKGROUND: The harmful effects of urban air pollution on general population in terms of annoying symptoms are not adequately evaluated. This is in contrast to the hospital admissions and short term mortality. The present study protocol is designed to assess the association between the level of exposure to certain ambient air pollutants and a wide range of relevant symptoms. Awareness of the impact of pollution on the population at large will make our estimates of the pertinent covert burden imposed on the society more accurate. METHODS/DESIGN: A cross sectional study with spatial analysis for the addresses of the participants was conducted. Data were collected via telephone interviews administered to a representative sample of civilians over age four in the city. Households were selected using random digit dialling procedures and randomization within each household was also performed to select the person to be interviewed. Levels of exposure are quantified by extrapolating the addresses of the study population over the air pollution matrix of the city at the time of the interview and also for different lag times. This information system uses the data from multiple air pollution monitoring stations in conjunction with meteorological data. General linear models are applied for statistical analysis. DISCUSSION: The important limitations of cross-sectional studies on acute effects of air pollution are personal confounders and measurement error for exposure. A wide range of confounders in this study are controlled for in the statistical analysis. Exposure error may be minimised by employing a validated geographical information system that provides accurate estimates and getting detailed information on locations of individual participants during the day. The widespread operation of open air conditioning systems in the target urban area which brings about excellent mixing of the outdoor and indoor air increases the validity of outdoor pollutants levels that are taken as exposure levels

Effects of Particulate Air Pollution on Cardiovascular Health: A Population Health Risk Assessment

Particulate matter (PM) air pollution is increasingly recognized as an important and modifiable risk factor for adverse health outcomes including cardiovascular disease (CVD). However, there are still gaps regarding large population risk assessment. Results from the nationwide Behavioral Risk Factor Surveillance System (BRFSS) were used along with air quality monitoring measurements to implement a systematic evaluation of PM-related CVD risks at the national and regional scales. CVD status and individual-level risk factors were collected from more than 500,000 BRFSS respondents across 2,231 contiguous U.S. counties for 2007 and 2009. Chronic exposures to PM pollutants were estimated with spatial modeling from measurement data. CVD outcomes attributable to PM pollutants were assessed by mixed-effects logistic regression and latent class regression (LCR), with adjustment for multicausality. There were positive associations between CVD and PM after accounting for competing risk factors: the multivariable-adjusted odds for the multiplicity of CVD outcomes increased by 1.32 (95% confidence interval: 1.23–1.43) and 1.15 (1.07–1.22) times per 10 µg/m3 increase in PM2.5 and PM10 respectively in the LCR analyses. After controlling for spatial confounding, there were moderate estimated effects of PM exposure on multiple cardiovascular manifestations. These results suggest that chronic exposures to ambient particulates are important environmental risk factors for cardiovascular morbidity