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基于 PM 对年死亡率影响的全国双重差分分析

A national difference in differences analysis of the effect of PM on annual death rates.

机构信息

Department of Environmental Health, Harvard TH Chan School of Public Health, USA; Department of Epidemiology, Harvard TH Chan School of Public Health, USA.

Department of Environmental Health, Harvard TH Chan School of Public Health, USA.

出版信息

Environ Res. 2021 Mar;194:110649. doi: 10.1016/j.envres.2020.110649. Epub 2020 Dec 30.

Abstract

Many studies have reported that PM was associated with mortality, but these were criticized for unmeasured confounding, not using causal modeling, and not focusing on changes in exposure and mortality rates. Recent studies have used propensity scores, a causal modeling approach that requires the assumption of no unmeasured confounders. We used differences in differences, a causal modeling approach that focuses on exposure changes, and controls for unmeasured confounders by design to analyze PM and mortality in the U.S. Medicare population, with 623, 036, 820 person-years of follow-up, and 29, 481, 444 deaths. We expanded the approach by clustering ZIP codes into 32 groups based on racial, behavioral and socioeconomic characteristics, and analyzing each cluster separately. We controlled for multiple time varying confounders within each cluster. A separate analysis examined participants whose exposure was always below 12 μg/m. We found an increase of 1 μg/m in PM produced an increased risk of dying in that year of 3.85 × 10 (95% CI 1.95 × 10, 5.76 × 10). This corresponds to 14,000 early deaths per year per 1 μg/m. When restricted to exposures below 12 μg/m, the increased mortality risk was 4.26 × 10 (95% CI 1.43 × 10, 7.09 × 10). Using a causal modeling approach robust to omitted confounders, we found associations of PM with increased death rates, including below U.S. and E.U. standards.

摘要

许多研究报告称,PM 与死亡率有关,但这些研究因未测量混杂因素、未使用因果建模以及未关注暴露和死亡率变化而受到批评。最近的研究使用了倾向评分,这是一种因果建模方法,需要假设没有未测量的混杂因素。我们使用差异中的差异,这是一种关注暴露变化的因果建模方法,并通过设计控制未测量的混杂因素,分析了美国医疗保险人群中 PM 和死亡率,随访时间为 623,036,820 人年,死亡人数为 29,481,444。我们通过根据种族、行为和社会经济特征将邮政编码聚类为 32 组,扩展了这种方法,并分别分析每个组,在每个组中控制多个随时间变化的混杂因素。另外一项单独的分析检查了暴露始终低于 12μg/m 的参与者。我们发现,PM 每增加 1μg/m,当年死亡的风险就会增加 3.85×10(95%CI 1.95×10,5.76×10)。这相当于每年每 1μg/m 有 14000 人过早死亡。当限制在暴露于 12μg/m 以下时,死亡率增加的风险为 4.26×10(95%CI 1.43×10,7.09×10)。使用一种对遗漏混杂因素具有稳健性的因果建模方法,我们发现 PM 与死亡率升高之间存在关联,包括低于美国和欧盟标准的情况。

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