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. 2018 Sep 18;115(38):9592-9597.
doi: 10.1073/pnas.1803222115. Epub 2018 Sep 4.

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

Richard Burnett  1 , Hong Chen  1   2 , Mieczysław Szyszkowicz  3 , Neal Fann  4 , Bryan Hubbell  5 , C Arden Pope 3rd  6 , Joshua S Apte  7 , Michael Brauer  8 , Aaron Cohen  9 , Scott Weichenthal  10   11 , Jay Coggins  12 , Qian Di  13 , Bert Brunekreef  14 , Joseph Frostad  15 , Stephen S Lim  15 , Haidong Kan  16 , Katherine D Walker  9 , George D Thurston  17 , Richard B Hayes  18 , Chris C Lim  19 , Michelle C Turner  20 , Michael Jerrett  21 , Daniel Krewski  22 , Susan M Gapstur  23 , W Ryan Diver  23 , Bart Ostro  24 , Debbie Goldberg  25 , Daniel L Crouse  26 , Randall V Martin  27 , Paul Peters  28   29   30 , Lauren Pinault  31 , Michael Tjepkema  31 , Aaron van Donkelaar  27 , Paul J Villeneuve  28 , Anthony B Miller  32 , Peng Yin  33 , Maigeng Zhou  33 , Lijun Wang  33 , Nicole A H Janssen  34 , Marten Marra  34 , Richard W Atkinson  35   36 , Hilda Tsang  37 , Thuan Quoc Thach  37 , John B Cannon  6 , Ryan T Allen  6 , Jaime E Hart  38 , Francine Laden  38 , Giulia Cesaroni  39 , Francesco Forastiere  39 , Gudrun Weinmayr  40 , Andrea Jaensch  40 , Gabriele Nagel  40 , Hans Concin  41 , Joseph V Spadaro  42
Affiliations

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

Richard Burnett et al. Proc Natl Acad Sci U S A. .

Abstract

Exposure to ambient fine particulate matter (PM2.5) 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 PM2.5 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 PM2.5-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 PM2.5 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 PM2.5 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.

Keywords: concentration; exposure; fine particulate matter; mortality; risk.

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Conflict of interest statement

Conflict of interest statement: J.V.S. is an independent consultant and not benefiting commercially from the results of this research.

Figures

Fig. 1.
Fig. 1.
GEMM hazard ratio predictions over PM2.5 exposure range for noncommunicable diseases plus LRIs (NCD+LRI). (Top) With 95% confidence interval (gray shaded area). (Bottom) GEMM predictions for each of the five causes of death displayed. GEMM NCD+LRI, GEMM IHD, and GEMM stroke were based on the 60- to 64-y-old age group.
Fig. 2.
Fig. 2.
Country-specific estimates of excess mortality rates associated with 100% reduction to the counterfactual concentration in population-weighted country average fine particulate matter concentrations by age-adjusted GEMM NCD+LRI vs. IER (blue dots) and GEMM 5 Causes of Death (COD) vs. IER (red dots). Dotted line represents 1:1 association.
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