Health effects of air pollution: a statistical review. (English) Zbl 1114.62358
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:
1. Which epidemiological designs and statistical methods are available to estimate associations between air pollution and health?
2. What are the recent methodological advances in the estimation of the health effects of air pollution in time series studies?
3. What are the the main methodological challenges and future research opportunities relevant to regulatory policy?
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.
1. Which epidemiological designs and statistical methods are available to estimate associations between air pollution and health?
2. What are the recent methodological advances in the estimation of the health effects of air pollution in time series studies?
3. What are the the main methodological challenges and future research opportunities relevant to regulatory policy?
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.
MSC:
| 62P10 | Applications of statistics to biology and medical sciences; meta analysis |
| 92D30 | Epidemiology |
| 62P12 | Applications of statistics to environmental and related topics |
Keywords:
Time series; Air Pollution; Epidemiological Designs; Hierarchical Models; Exposure Measurement error; Model ChoiceReferences:
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