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Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter

Authors :
Bart Ostro
Richard Atkinson
Randall V. Martin
Susan M. Gapstur
Joseph V. Spadaro
Andrea Jaensch
Ryan Allen
Michelle C. Turner
Michael Brauer
Jaime E. Hart
Lauren Pinault
Anthony B. Miller
Maigeng Zhou
Lijun Wang
Joshua S. Apte
Haidong Kan
Gabriele Nagel
Dan L. Crouse
Nicole A.H. Janssen
Gudrun Weinmayr
John B. Cannon
Paul J. Villeneuve
Bert Brunekreef
Aaron van Donkelaar
Hilda Tsang
Debbie Goldberg
C. Arden Pope
Paul A. Peters
Qian Di
Thuan-Quoc Thach
Jay S. Coggins
Marten Marra
Aaron Cohen
Francesco Forastiere
Bryan Hubbell
Chris C. Lim
Richard T. Burnett
Joseph Frostad
Neal Fann
Hong Chen
W. Ryan Diver
Michael Tjepkema
Stephen S Lim
George D. Thurston
Peng Yin
Daniel Krewski
Francine Laden
Hans Concin
Richard B. Hayes
Scott Weichenthal
Michael Jerrett
Katherine Walker
Mieczyslaw Szyszkowicz
Giulia Cesaroni
Source :
Proceedings of the National Academy of Sciences of the United States of America, 115(38), 9592. National Academy of Sciences, Proceedings of the National Academy of Sciences of the United States of America, vol 115, iss 38
Publication Year :
2018

Abstract

Exposure to ambient fine particulate matter (PM 2.5 ) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM 2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM 2.5 -mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM 2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries—the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5–10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9–8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3–4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM 2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

Details

Language :
English
ISSN :
00278424 and 10916490
Database :
OpenAIRE
Journal :
Proceedings of the National Academy of Sciences of the United States of America, 115(38), 9592. National Academy of Sciences, Proceedings of the National Academy of Sciences of the United States of America, vol 115, iss 38
Accession number :
edsair.doi.dedup.....1da940362ef5ec1ba3d47bbbd9fed552