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Epidemiology. 2016 Mar;27(2):221-7. doi: 10.1097/EDE.0000000000000422.

PM2.5 and Mortality in 207 US Cities: Modification by Temperature and City Characteristics.

Author information

1
From the Departments of aEnvironmental Health, bEpidemiology, & cBiostatistics, Harvard T.H. Chan School of Public Health, Boston, MA.

Abstract

BACKGROUND:

The reported estimated effects between long-term PM2.5 exposures and mortality vary spatially. We assessed whether community-level variables, including socioeconomic status indicators and temperature, modify this association.

METHODS:

We used data from >35 million Medicare enrollees from 207 US cities (2000-2010). For each city, we calculated annual PM2.5 averages, measured at ambient central monitoring sites. We used a variation of a causal modeling approach and fitted city-specific Cox models, which we then pooled using a random effects meta-regression. In this second stage, we assessed whether temperature and city-level variables, including smoking and obesity rates, poverty, education and greenness, modify the long-term PM2.5-mortality association.

RESULTS:

We found an association between long-term PM2.5 and survival (hazard ratio = 1.2; 95% confidence interval [CI]: 1.1, 1.3 per 10 μg/m increase in the annual PM2.5 average concentrations). We observed elevated estimates in the Southeastern, South and Northwestern US (hazard ratio = 1.9; 95% CI: 1.7, 2.2, and 1.4; 95% CI: 1.2, 1.7, and 1.4; 95% CI: 1.1, 1.9, respectively). We observed a higher association between long-term PM2.5 exposure and mortality in warmer cities. Furthermore, we observed increasing estimates with increasing obesity rates, %residents and families in poverty, %black residents and %population without a high school degree, and lower effects with increasing median household income and %white residents.

CONCLUSIONS:

To the best of our knowledge, this is the first study to assess modification by temperature and community-level characteristics on the long-term PM2.5-survival association. Our findings suggest that living in cities with high temperatures and low socio economic status (SES) is associated with higher effect estimates.

PMID:
26600257
PMCID:
PMC4748718
[Available on 2017-03-01]
DOI:
10.1097/EDE.0000000000000422
[Indexed for MEDLINE]
Free PMC Article

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