Abstract
BACKGROUND AND AIM: Many studies link long-term fine particle (PM2.5) exposure to mortality, even at levels below current US air quality standards (12 μg/m3). These findings have been disputed citing traditional approaches do not guarantee evidence of causality. METHODS: Leveraging 16 years of data—68.5 million Medicare enrollees and 570 million observations—we estimated the causal effect of annual PM2.5 exposure on mortality. We implemented five statistical approaches to estimate the effect of PM2.5 exposure on mortality, accounting for potential confounders. The two traditional approaches rely on regression modeling for confounding adjustment: 1) Cox proportional hazards model, and 2) Poisson regression. We also considered three approaches for causal inference that rely on the potential outcomes framework and generalized propensity scores (GPS). RESULTS:We found that an increase of 10 μg/m3 PM2.5 leads to a statistically significant mortality risk increase, 6 to 8%. Lowering the standards to 10 μg/m3 would save 143,257 lives (95% confidence interval: 115,581–170,645) in one decade. CONCLUSIONS:Our study provides the most robust and reproducible evidence to date of the causal link between long-term PM2.5 exposure and mortality even at levels below the standards KEYWORDS: air pollution, methods
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