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. 2017 Jan 4;16(1):1.
doi: 10.1186/s12940-016-0208-y.

Influence of exposure differences on city-to-city heterogeneity in PM2.5-mortality associations in US cities

Lisa K Baxter  1 , James L Crooks  2   3   4 , Jason D Sacks  5
Affiliations

Influence of exposure differences on city-to-city heterogeneity in PM2.5-mortality associations in US cities

Lisa K Baxter et al. Environ Health. .

Abstract

Background: Multi-city population-based epidemiological studies have observed heterogeneity between city-specific fine particulate matter (PM2.5)-mortality effect estimates. These studies typically use ambient monitoring data as a surrogate for exposure leading to potential exposure misclassification. The level of exposure misclassification can differ by city affecting the observed health effect estimate.

Methods: The objective of this analysis is to evaluate whether previously developed residential infiltration-based city clusters can explain city-to-city heterogeneity in PM2.5 mortality risk estimates. In a prior paper 94 cities were clustered based on residential infiltration factors (e.g. home age/size, prevalence of air conditioning (AC)), resulting in 5 clusters. For this analysis, the association between PM2.5 and all-cause mortality was first determined in 77 cities across the United States for 2001-2005. Next, a second stage analysis was conducted evaluating the influence of cluster assignment on heterogeneity in the risk estimates.

Results: Associations between a 2-day (lag 0-1 days) moving average of PM2.5 concentrations and non-accidental mortality were determined for each city. Estimated effects ranged from -3.2 to 5.1% with a pooled estimate of 0.33% (95% CI: 0.13, 0.53) increase in mortality per 10 μg/m3 increase in PM2.5. The second stage analysis determined that cluster assignment was marginally significant in explaining the city-to-city heterogeneity. The health effects estimates in cities with older, smaller homes with less AC (Cluster 1) and cities with newer, smaller homes with a large prevalence of AC (Cluster 3) were significantly lower than the cluster consisting of cities with older, larger homes with a small percentage of AC.

Conclusions: This is the first study that attempted to examine whether multiple exposure factors could explain the heterogeneity in PM2.5-mortality associations. The results of this study were found to explain a small portion (6%) of this heterogeneity.

Keywords: Cluster analysis; Epidemiology; Exposure; Meta-regression; Particulate matter.

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Figures

Fig. 1
Fig. 1
Percent increase in non-accidental mortality with a 10 μg/m3 increase in PM2.5 concentrations using a moving average of the previous 2-days (lag 0–1) (circles = estimate; whiskers = 95% confidence interval)
See this image and copyright information in PMC

References

    1. Dominici F, Peng RD, Bell ML, Pham L, McDermott A, Zeger SL, Samet JM. Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. JAMA. 2006;295(10):1127–1134. doi: 10.1001/jama.295.10.1127. - DOI - PMC - PubMed
    1. Franklin M, Zeka A, Schwartz J. Association between PM2.5 and all-cause and specific-cause mortality in 27 US communities. J Expo Sci Environ Epidemiol. 2007;17(3):279–287. doi: 10.1038/sj.jes.7500530. - DOI - PubMed
    1. Baxter LK, Sacks JD. Clustering cities with similar fine particulate matter exposure characteristics based on residential infiltration and in-vehicle commuting factors. Sci Total Environ. 2014;470–471:631–638. doi: 10.1016/j.scitotenv.2013.10.019. - DOI - PubMed
    1. Ozkaynak H, Baxter LK, Dionisio KL, Burke J. Air pollution exposure prediction approaches used in air pollution epidemiology studies. J Expos Sci Environ Epidemiol. 2013;23(6):566–572. doi: 10.1038/jes.2013.15. - DOI - PubMed
    1. Allen R, Larson T, Sheppard L, Wallace L, Liu LJS. Use of real-time light scattering data to estimate the contribution of infiltrated and indoor-generated particles to indoor air. Environ Sci Tech. 2003;37(16):3484–3492. doi: 10.1021/es021007e. - DOI - PubMed

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