Health Effects of Air Pollution:\\ A Statistical Review

Abstract

We critically review and compare epidemiological designs and statistical approaches to estimate associations between air pollution and health. More specifically, we aim to address the following questions: \begin{enumerate} \item[1.]{\bf<i>Which epidemiological designs and statistical methods are available to estimate associations between air pollution and health?</i>} \item[2.]{\bf<i>What are the recent methodological advances in the estimation of the health effects of air pollution in time series studies?</i>} \item[3.]{\bf<i>What are the the main methodological challenges and future research opportunities relevant to regulatory policy?</i>} \end{enumerate} In question 1, we identify strengths and limitations of time series, cohort, case-crossover and panel sampling designs. In question 2, we focus on time series studies and we review statistical methods for: 1) combining information across multiple locations to estimate overall air pollution effects; 2) estimating the health effects of air pollution taking into account of model uncertainties; 3) investigating the consequences of exposure measurement error in the estimation of the health effects of air pollution; and 4) estimating air pollution-health exposure-response curves. Here, we also discuss the extent to which these statistical contributions have addressed key substantive questions. In question 3, within a set of policy-relevant-questions, we identify research opportunities and point out current data limitations.