Air pollution epidemiologic studies are intrinsically difficult because the expected effect size at general environmental levels is small, exposure and misclassification of exposure are common, and exposure is not selective to a specific pollutant. In this review paper, epidemiologic study designs and analytic methods are described, and two nationwide projects on air pollution epidemiology are introduced. This paper also demonstrates that possible confounding issues in time-series analysis can be resolved and the impact on the use of data from ambient monitoring stations may not be critical. In this paper we provide a basic understanding of the types of air pollution epidemiologic study designs that be subdivided by the mode of air pollution effects on human health (acute or chronic). With the improvements in the area of air pollution epidemiologic studies, we should emphasize that elaborate models and statistical techniques cannot compensate for inadequate study design or poor data collection.
OBJECTIVES To reexamine the association between air pollution and daily mortality in Seoul, Korea using a method of meta-analysis with the data filed for 1991 through 1995. METHODS: A separate Poisson regression analysis on each district within the metropolitan area of Seoul was conducted to regress daily death counts on levels of each ambient air pollutant, such as total suspended particulates (TSP), sulfur dioxide (SO2), and ozone (O3), controlling for variability in the weather condition. We calculated a weighted mean as a meta-analysis summary of the estimates and its standard error. RESULTS: We found that the p value from each pollutant model to test the homogeneity assumption was small (p<0.01) because of the large disparity among district-specific estimates. Therefore, all results reported here were estimated from the random effect model. Using the weighted mean that we calculated, the mortality at a 100 microgram/m3 increment in a 3-day moving average of TSP levels was 1.034 (95% CI 1.009-1.059). The mortality was estimated to increase 6% (95% CI 3-10%) and 3% (95% CI 0-6%) with each 50 ppb increase for 3-day moving average of SO2 and 1-hr maximum O3, respectively. CONCLUSIONS: Like most of air pollution epidemiologic studies, this meta-analysis cannot avoid fleeing from measurement misclassification since no personal measurement was taken. However, we can expect that a measurement bias be reduced in a district-specific estimate since a monitoring station is better representative of air quality of the matched district. The similar results to those from the previous studies indicated existence of health effect of air pollution at current levels in many industrialized countries, including Korea.