Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter [Environmental Sciences],Proceedings of the National Academy of Sciences of the United States of America

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Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter [Environmental Sciences]
Proceedings of the National Academy of Sciences of the United States of America ( IF 9.4 ) Pub Date : 2018-09-18 , DOI: 10.1073/pnas.1803222115
Richard Burnett ₁ , Hong Chen _{1,

2} , Mieczysław Szyszkowicz ₃ , Neal Fann ₄ , Bryan Hubbell ₅ , C Arden Pope 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

Affiliation

Population Studies Division, Health Canada, Ottawa, ON K1A 0K9, Canada.
Department of Environmental and Occupational Health, Public Health Ontario, Toronto, ON M5G 1V2, Canada.
Population Studies Division, Health Canada, Ottawa, ON K1A 0K9, Canada;
Risk and Benefits Group, Office of Air Quality Planning and Standards, US Environmental Protection Agency, Washington, DC 20460.
Office of Research and Development, US Environmental Protection Agency, Washington, DC 20460.
Department of Economics, Brigham Young University, Provo, UT 84602.
Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, TX 78712.
School of Population and Public Health, University of British Columbia, Vancouver, BC V6T 1Z3, Canada.
Health Effects Institute, Boston, MA 02110-1817.
Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC H3A 0G4, Canada.
Gerald Bronfman Department of Oncology, McGill University, Montreal, QC H3A 0G4, Canada.
Department of Applied Economics, University of Minnesota, Minneapolis, MN 55455.
Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115.
Institute for Risk Assessment Sciences, Universiteit Utrecht, 3512 JE Utrecht, The Netherlands.
Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195.
School of Public Health, Fudan University, Shanghai 200433, China.
Environmental Medicine and Population Health, Program in Human Exposures and Health Effects, New York University School of Medicine, New York, NY 10016.
Department of Population Health, NYU Langone Medical Center, New York, NY 10016.
Department of Environmental Medicine, New York University School of Medicine, New York, NY 10016.
ISGlobal, Barcelona Institute for Global Health, 08036 Barcelona, Spain.
Department of Environmental Health Sciences, Fielding School of Public Health, University of California, Los Angeles, CA 90095.
McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, ON K1N 6N5, Canada.
Epidemiology Research Program, American Cancer Society, Inc., Atlanta, GA 30303.
Department of Civil and Environmental Engineering, University of California, Davis, CA 95616.
Cancer Prevention Institute of California, Fremont, CA 94538.
Department of Sociology, University of New Brunswick, Fredericton, NB E3B 5A3, Canada.
Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS B3H 4R2, Canada.
Department of Health Sciences, Carleton University, Ottawa, ON K1S 5B6, Canada.
Department of Geography and Environment, Carleton University, Ottawa, ON K1S 5B6, Canada.
New Brunswick Institute for Research, Data and Training, University of New Brunswick, Fredericton, NB E3B 5A3, Canada.
Health Analysis Division, Statistics Canada, Ottawa, ON K1A 0T6, Canada.
Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada.
National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands.
Population Health Research Institute, St. George's, University of London, London SW17 0RE, United Kingdom.
MRC-PHE Centre for Environment and Health, St. George's, University of London, London SW17 0RE, United Kingdom.
School of Public Health, University of Hong Kong, Hong Kong, China.
Department of Environmental Health, Harvard C.T. Channing School of Public Health, Harvard University, Boston, MA 02115.
Department of Epidemiology, Regional Health Service, ASL Roma 1, 00147 Rome, Italy.
Institute of Epidemiology and Medical Biometry, Ulm University, 89081 Ulm, Germany.
Agency for Preventive and Social Medicine, 6900 Bregenz, Austria.
Spadaro Environmental Research Consultants (SERC), Philadelphia, PA 19142.

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.

中文翻译：

与长期暴露于室外细颗粒物相关的死亡率的全球估计[环境科学]

暴露于环境细颗粒物 (PM _2.5 ) 是一个主要的全球健康问题。可归因死亡率的定量估计基于特定疾病的风险比模型，该模型包含来自多个 PM _2.5来源（使用固体燃料以及二手烟和主动吸烟造成的室外和室内空气污染）的风险信息，需要对等效暴露和毒性进行假设。我们仅基于覆盖全球暴露范围的室外空气污染队列研究构建 PM _2.5死亡风险比函数，从而放松了这些有争议的假设。我们使用来自 16 个国家的 41 个队列的数据对 PM _2.5与非意外死亡率之间的关联进行了建模——全球暴露死亡率模型 (GEMM)。然后，我们针对全球疾病负担 (GBD) 所检查的五种特定死因构建了 GEMM。 GEMM 预测 2015 年将有 890 万人死亡 [95% 置信区间 (CI)：7.5–10.3]，这一数字比五种特定原因死亡总和（6.9；95% CI：4.9–8.5）预测的数字高出 30%。），比 GBD 中使用的风险函数（4.0；95% CI：3.3–4.8）大 120%。当浓度降低 20% 时，GEMM 和 GBD 风险函数之间的差异更大，GEMM 预测超额死亡人数将增加 220%。这些结果表明，PM _2.5暴露可能与 GBD 考虑的五种死因之外的其他死因有关，并且纳入其他非室外颗粒源的风险信息会导致低估疾病负担，尤其是在浓度较高的情况下。

更新日期：2018-09-19

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