Causal effects of air pollution on mortality rate in Massachusetts

Yaguang Wei, Yan Wang, Xiao Wu, Qian Di, Liuhua Shi, Petros Koutrakis, Antonella Zanobetti, Francesca Dominici, Joel D. Schwartz

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Air pollution epidemiology studies have primarily investigated long- and short-term exposures separately, have used multiplicative models, and have been associational studies. Implementing a generalized propensity score adjustment approach with 3.8 billion person-days of follow-up, we simultaneously assessed causal associations of long-term (1-year moving average) and short-term (2-day moving average) exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5), ozone, and nitrogen dioxide with all-cause mortality on an additive scale among Medicare beneficiaries in Massachusetts (2000-2012). We found that long- and short-term PM2.5, ozone, and nitrogen dioxide exposures were all associated with increased mortality risk. Specifically, per 10 million person-days, each 1-μg/m3 increase in long- and short-term PM2.5 exposure was associated with 35.4 (95% confidence interval (CI): 33.4, 37.6) and 3.04 (95% CI: 2.17, 3.94) excess deaths, respectively; each 1-part per billion (ppb) increase in long- and short-term ozone exposure was associated with 2.35 (95% CI: 1.08, 3.61) and 2.41 (95% CI: 1.81, 2.91) excess deaths, respectively; and each 1-ppb increase in long- and short-term nitrogen dioxide exposure was associated with 3.24 (95% CI: 2.75, 3.77) and 5.60 (95% CI: 5.24, 5.98) excess deaths, respectively. Mortality associated with long-term PM2.5 and ozone exposure increased substantially at low levels. The findings suggested that air pollution was causally associated with mortality, even at levels below national standards.

Original languageEnglish
Pages (from-to)1316-1323
Number of pages8
JournalAmerican Journal of Epidemiology
Volume189
Issue number11
DOIs
StatePublished - 1 Nov 2020
Externally publishedYes

Keywords

  • Air pollution
  • Big data computing
  • Causality
  • Generalized propensity score
  • Linear probability model

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