You are here:
Joint Effects of Ambient Air Pollutants on Pediatric Asthma Emergency Department Visits in Atlanta, 1998–2004
Citation:
Winquist, A., E. Kirrane, M. Klein, M. Strickland, L. Darrow, S. Ebelt Sarnat, K. Gass, J. Mulholland, A. Russell, AND P. Tolbert. Joint Effects of Ambient Air Pollutants on Pediatric Asthma Emergency Department Visits in Atlanta, 1998–2004. EPIDEMIOLOGY. Lippincott Williams & Wilkins, Philadelphia, PA, 25(5):666-673, (2014).
Impact/Purpose:
This publication will be discussed and evaluated in the Multipollutant Science Document - its major contribution is to determine the effect of combinations of pollutants.
Description:
Background: Because ambient air pollution exposure occurs in the form of mixtures, consideration of joint effects of multiple pollutants may advance our understanding of air pollution health effects. Methods: We assessed the joint effect of selected ambient air pollutant combinations (groups of oxidant, secondary, traffic, power plant, and criteria pollutants constructed using combinations of criteria gases, fine particulate matter (PM2.5) and PM2.5 components) on warm season pediatric asthma emergency department (ED) visits in Atlanta during 1998-2004. Joint effects were assessed using multi-pollutant Poisson generalized linear models controlling for time trends, meteorology and daily non-asthma respiratory ED visit counts. Rate ratios (RR) were calculated for the combined effect of an interquartile-range increment in the concentration of each pollutant. Results: Increases in all of the selected pollutant combinations were associated with increases in pediatric asthma ED visits [e.g., joint effect rate ratio=1.13 (95% confidence interval 1.06-1.21) for criteria pollutants (including ozone, carbon monoxide, nitrogen dioxide, sulfur dioxide, and PM2.5)]. Joint effect estimates were smaller than estimates calculated based on summing results from single-pollutant models, due to control for confounding. Compared with models without interactions, joint effect estimates from models including first-order pollutant interactions were similar for oxidant and secondary pollutants, but slightly higher for criteria, traffic and power plant pollutants. Model variables were correlated, but the study size allowed calculation of joint effects with ample precision. Conclusions: Consideration of joint effects adds to our understanding of pollutants acting together to impact health, and of the total morbidity associated with these pollutant combinations.
