Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter.
Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter.
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DOI：
10.1073/pnas.1803222115
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发表时间：
2018-09-18
影响因子：
11.1
通讯作者：
Spadaro JV
中科院分区：
文献类型：
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作者：
Burnett R;Chen H;Szyszkowicz M;Fann N;Hubbell B;Pope CA 3rd;Apte JS;Brauer M;Cohen A;Weichenthal S;Coggins J;Di Q;Brunekreef B;Frostad J;Lim SS;Kan H;Walker KD;Thurston GD;Hayes RB;Lim CC;Turner MC;Jerrett M;Krewski D;Gapstur SM;Diver WR;Ostro B;Goldberg D;Crouse DL;Martin RV;Peters P;Pinault L;Tjepkema M;van Donkelaar A;Villeneuve PJ;Miller AB;Yin P;Zhou M;Wang L;Janssen NAH;Marra M;Atkinson RW;Tsang H;Quoc Thach T;Cannon JB;Allen RT;Hart JE;Laden F;Cesaroni G;Forastiere F;Weinmayr G;Jaensch A;Nagel G;Concin H;Spadaro JV
暴露于室外浓度的细颗粒物被认为是一个主要的全球健康问题，这主要是基于使用综合了几种颗粒源（室外和室内空气污染以及被动/主动吸烟）的暴露和风险的信息对超额死亡的估计。这种整合需要强有力的假设，即每总吸入剂量的毒性相等。我们放松这些假设，建立风险模型，检查暴露和风险信息仅限于室外空气污染的队列研究，现在覆盖了全球大部分浓度范围。我们的估计比以前的计算大几倍，这表明室外颗粒空气污染是一个比以前认为的更重要的人口健康风险因素。暴露于环境细颗粒物（PM2.5）是一个主要的全球健康问题。可归因死亡率的定量估计是基于疾病特异性风险比模型，该模型纳入了来自多个PM2.5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。我们放松这些有争议的假设，构建一个PM2.5的死亡率风险比函数仅基于队列研究的室外空气污染，覆盖全球暴露范围。我们使用来自16个国家的41个队列的数据-全球暴露死亡率模型（GEMM），对PM2.5和非意外死亡率之间的关系进行了建模。然后，我们为全球疾病负担（GBD）检查的五种特定死亡原因构建了GEMM。GEMM预测2015年将有890万人[95%置信区间（CI）：7.5-10.3]死亡，这一数字比五种特定原因中死亡人数之和的预测值（6.9; 95% CI：4.9-8.5）大30%，比GBD中使用的风险函数（4.0; 95% CI：3.3-4.8）大120%。浓度降低20%时，GEMM和GBD风险函数之间的差异较大，GEMM预测的超额死亡率高出220%。这些结果表明，PM2.5暴露可能与GBD所考虑的五种死亡原因之外的其他原因有关，并且将其他非户外颗粒源的风险信息纳入其中会导致低估疾病负担，特别是在较高浓度下。
Exposure to outdoor concentrations of fine particulate matter is considered a leading global health concern, largely based on estimates of excess deaths using information integrating exposure and risk from several particle sources (outdoor and indoor air pollution and passive/active smoking). Such integration requires strong assumptions about equal toxicity per total inhaled dose. We relax these assumptions to build risk models examining exposure and risk information restricted to cohort studies of outdoor air pollution, now covering much of the global concentration range. Our estimates are severalfold larger than previous calculations, suggesting that outdoor particulate air pollution is an even more important population health risk factor than previously thought. 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.
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DOI：
10.1073/pnas.1612430114
发表时间：
2017-02-07
影响因子：
11.1
作者：
Lacey, Forrest G.;Henze, Daven K.;Martin, Randall V.
通讯作者：
Martin, Randall V.
影响因子：
5.1
作者：
Pope, C. Arden, III;Ezzati, Majid;Burnett, Richard T.
通讯作者：
Burnett, Richard T.
DOI：
10.1073/pnas.1703167114
发表时间：
2017-05-09
影响因子：
11.1
作者：
Qin, Yue;Wagner, Fabian;Mauzerall, Denise L.
通讯作者：
Mauzerall, Denise L.
DOI：
10.1016/s0140-6736(17)30505-6
发表时间：
2017-05-13
期刊：
Lancet (London, England)
影响因子：
--
作者：
Cohen AJ;Brauer M;Burnett R;Anderson HR;Frostad J;Estep K;Balakrishnan K;Brunekreef B;Dandona L;Dandona R;Feigin V;Freedman G;Hubbell B;Jobling A;Kan H;Knibbs L;Liu Y;Martin R;Morawska L;Pope CA 3rd;Shin H;Straif K;Shaddick G;Thomas M;van Dingenen R;van Donkelaar A;Vos T;Murray CJL;Forouzanfar MH
通讯作者：
Forouzanfar MH
影响因子：
10.4
作者：
Burnett RT;Pope CA 3rd;Ezzati M;Olives C;Lim SS;Mehta S;Shin HH;Singh G;Hubbell B;Brauer M;Anderson HR;Smith KR;Balmes JR;Bruce NG;Kan H;Laden F;Prüss-Ustün A;Turner MC;Gapstur SM;Diver WR;Cohen A
通讯作者：
Cohen A