Population Studies Division, Health Canada, Ottawa, ON K1A 0K9, Canada.
Department of Environmental and Occupational Health, Public Health Ontario, Toronto, ON M5G 1V2, Canada.
Proc Natl Acad Sci U S A. 2018 Sep 18;115(38):9592-9597. doi: 10.1073/pnas.1803222115. Epub 2018 Sep 4.
Exposure to ambient fine particulate matter (PM) 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 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-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 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 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.
暴露于环境细颗粒物(PM)是一个主要的全球健康关注点。归因于 PM 的死亡率的定量估计基于特定疾病的危害比模型,该模型纳入了来自多种 PM 来源(室外和室内空气污染物来自固体燃料的使用、二手烟和主动吸烟)的风险信息,这需要关于等效暴露和毒性的假设。我们通过仅基于涵盖全球暴露范围的室外空气污染队列研究构建 PM-死亡率危害比函数来放宽这些有争议的假设。我们使用来自 16 个国家的 41 个队列的数据(全球暴露死亡率模型(GEMM))来模拟 PM 与非意外死亡率之间的关联形状。然后,我们为全球疾病负担(GBD)研究的五个特定死因构建了 GEMM。GEMM 预测 2015 年将有 890 万例死亡(95%置信区间(CI):7.5-10.3),比五个特定死因的死亡总和(6.9;95%CI:4.9-8.5)预测的数字高 30%,比 GBD 中使用的风险函数(4.0;95%CI:3.3-4.8)高 120%。对于浓度降低 20%,GEMM 和 GBD 风险函数之间的差异更大,GEMM 预测超额死亡人数高出 220%。这些结果表明,PM 暴露可能与 GBD 考虑的五个原因之外的其他死因有关,并且纳入来自其他非室外颗粒源的风险信息会导致疾病负担的低估,尤其是在更高浓度下。