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首页> 美国卫生研究院文献>Proceedings of the National Academy of Sciences of the United States of America >Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter
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Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter

机译：与长期接触室外细颗粒物有关的死亡率的全球估计

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摘要

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.
机译：暴露于环境细颗粒物（PM2.5）是全球主要的健康问题。可归因的死亡率的定量估计基于特定疾病的危险比模型，该模型结合了来自多个PM2.5来源（使用固体燃料以及二手烟和主动吸烟造成的室内和室外空气污染）的风险信息，需要对当量暴露和毒性进行假设。我们仅根据覆盖全球暴露范围的室外空气污染的队列研究来构建PM2.5死亡率危害比函数，从而放松这些有争议的假设。我们使用来自16个国家/地区的41个队列的数据-全球暴露死亡率模型（GEMM），对PM2.5与非偶然死亡率之间的关联形状进行了建模。然后，我们通过全球疾病负担（GBD）检查了五个特定死因的GEMM。 GEMM预测2015年会有890万[95％置信区间（CI）：7.5–10.3]死亡，这一数字比五种特定原因导致的死亡总数所预测的数字高出30％（6.9； 95％CI：4.9–8.5） ），比GBD中使用的风险函数大120％（4.0； 95％CI：3.3-4.8）。当浓度降低20％时，GEMM和GBD风险函数之间的差异就更大，而GEMM则预测过量死亡人数会增加220％。这些结果表明，PM2.5暴露可能与GBD所考虑的5种死亡原因无关，并且与其他非室外颗粒物来源的风险信息相结合会导致疾病负担低估，尤其是在较高浓度下。

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