Evaluating the impact of long-term exposure to fine particulate matter on mortality among the elderly

被引:128
|
作者
Wu, X. [1 ]
Braun, D. [1 ,2 ]
Schwartz, J. [3 ]
Kioumourtzoglou, M. A. [4 ]
Dominici, F. [1 ]
机构
[1] Harvard TH Chan Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA
[2] Dana Farber Canc Inst, Dept Data Sci, Boston, MA 02115 USA
[3] Harvard TH Chan Sch Publ Hlth, Dept Environm Hlth, Boston, MA 02115 USA
[4] Columbia Univ, Dept Environm Hlth Sci, Mailman Sch Publ Hlth, New York, NY USA
来源
SCIENCE ADVANCES | 2020年 / 6卷 / 29期
关键词
MARGINAL STRUCTURAL MODELS; CAUSAL INFERENCE; AIR-POLLUTION; PROPENSITY SCORE; COVARIATE BALANCE; COUNTERFACTUALS; ASSOCIATION; SURVIVAL; DESIGN;
D O I
10.1126/sciadv.aba5692
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Many studies link long-term fine particle (PM2.5) exposure to mortality, even at levels below current U.S. air quality standards (12 micrograms per cubic meter). These findings have been disputed with claims that the use of traditional statistical approaches does not guarantee causality. Leveraging 16 years of data-68.5 million Medicare enrollees-we provide strong evidence of the causal link between long-term PM2.5 exposure and mortality under a set of causal inference assumptions. Using five distinct approaches, we found that a decrease in PM2.5 (by 10 micro-grams per cubic meter) leads to a statistically significant 6 to 7% decrease in mortality risk. Based on these models, lowering the air quality standard to 10 micrograms per cubic meter would save 143,257 lives (95% confidence interval, 115,581 to 170,645) in one decade. Our study provides the most comprehensive evidence to date of the link between long-term PM2.5 exposure and mortality, even at levels below current standards.
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页数:9
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