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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  

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.



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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