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.]{\bfWhich epidemiological designs and statistical methods are
available to estimate associations between air pollution and health?}
\item[2.]{\bfWhat are the recent methodological advances in the estimation
of the health effects of air pollution in time series studies?}
\item[3.]{\bfWhat are the the main methodological challenges and future research opportunities relevant to regulatory policy?}
\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.