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Influence of exposure differences on city-to-city variations in PM2.5-mortality effect estimates
Citation:
Baxter, L., J. Crooks, AND J. Sacks. Influence of exposure differences on city-to-city variations in PM2.5-mortality effect estimates. ISES Annual Meeting, Henderson, NV, Henderson, NV, October 18 - 23, 2015.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
Multi-city population-based epidemiological studies have observed heterogeneity between city specific PM2.5-mortality effect estimates. One possibility is city-specific differences in overall population exposure to PM2.5. In a previous analysis we explored this latter point by clustering cities with similar exposure distributions based on factors related to residential infiltration and in-vehicle commuting patterns. The objective of this analysis is to determine whether these previously developed clusters can help explain city-to-city heterogeneity in PM2.5 mortality risk estimates. We examine the association between PM 2.5 and all-cause mortality in 94 Core-Based Statistical Areas across the continental United States for 2001-2005. Clustering cities based solely on residential infiltration factors (e.g. home age/size, prevalence of air conditioning) resulted in 5 clusters while cluster analysis based on residential infiltration factors and in-vehicle commuting patternsproduced 11 clusters. The percent increase in all-cause mortality per 10μg/m3 increase in PM2.5 using a 2 day moving average was generated for each city. We observed a range of -5.2% to 7.8% increase across the cities with an average of 0.52%. Grouping the cities into clusters based on residential infiltration factors, the average percent increase was -0.35% for Cluster 1, -0.22% for Cluster 2,0.81% for Cluster 3, 0.79% for Cluster 4, and 1.2% for Cluster 5. Most air pollution literature has focused on PM composition and demographics in identifying heterogeneity in the observed PM2.5 mortality risk estimates. However, exposure may play an important role in explaining city-to-city variation in health effect estimates. Effect modification by clusters generated based on exposure factors will determine whether these city-varying characteristics have differential associations with PM2.5.
