气候变化领域集成服务门户

Exposure error in ambient air pollution epidemiologic studies may introduce bias and/or attenuation of the health risk estimate, reduce statistical significance, and lower statistical power. Alternative exposure metrics are increasingly being used in place of central-site measurements, with the intent of reducing exposure error. Dependent on the study design, health outcome, and pollutant of interest, these metrics may provide a means of reducing error (leading to less bias and uncertainty in health risk estimates) if they capture variability in exposure which is not represented when central-site measurements are used. We examine the current evidence for answering the question of when the choice of exposure metric matters and why, focusing on studies which examined multiple exposure metrics in the same epidemiologic study. We conclude that for time-series and case-crossover studies, central-site measurements may be sufficient, especially for homogeneous pollutants, and in cohort and panel studies, approaches that increase spatial resolution of the exposure metrics do impact the health effect estimates. We note that while the current literature is widely dispersed across exposure metrics and health outcomes, the largest collective, common body of literature is focused on birth/pregnancy outcomes and traffic-related pollution. Also additional discussion and agreement is needed on how to classify metrics as "different" and "better." Primary recommendations are to provide context for the reasons behind selection of exposure metrics and to encourage collaboration between exposure scientists and epidemiologists when designing and implementing a study, as results can have important implications for the development of policies and regulations.