Abstract
Background: As population exposure to ambient air pollution generally occurs in the form of mixtures, consideration of joint effects of multiple pollutants may advance our understanding of associated health effects. Aims: We assess the joint effect of selected pollutant combinations of interest (groups of oxidant, secondary, traffic, industrial, and 5 criteria pollutants) on warm season pediatric asthma emergency department (ED) visits in Atlanta during 1998-2004. Methods: Daily ambient air pollutant concentrations were obtained from several ambient monitoring networks. We examined associations between ambient air pollutant concentrations and the daily count of pediatric asthma ED visits using multi-pollutant Poisson generalized linear models controlling for time trends, meteorology and the number of non-asthma respiratory ED visits. Joint effects of groups of pollutants were calculated for a simultaneous IQR change in the concentration of each pollutant. Results: Statistically significant joint effects were observed for all of the pollutant groups. Joint effects were overestimated if calculated based on results from single-pollutant models rather than multi-pollutant models. Compared with joint effects estimated from multi-pollutant models without interactions, joint effect estimates from models including first order pollutant interactions were not substantially different for oxidant and secondary pollutants, but were slightly higher for criteria pollutants, traffic pollutants and industrial pollutants. Concurvities were high, but power was adequate to calculate joint effects with ample precision. Conclusions: The vast majority of air pollution health effects studies have focused on single pollutant effects, even if multi-pollutant models have been used. Consideration of joint effects can add to our knowledge of how pollutants act together with respect to health effects, and aligns with the recent emphasis on air pollution mixtures.
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