Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis.
Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis.
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DOI：
10.1126/sciadv.abd4049
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发表时间：
2020-11
期刊：
影响因子：
13.6
通讯作者：
Dominici F
中科院分区：
文献类型：
--
作者：
Wu X;Nethery RC;Sabath MB;Braun D;Dominici F
我们描述了分析暴露于空气污染与新冠肺炎易感性之间的联系所面临的挑战和机遇。评估长期暴露在空气污染中是否会增加包括死亡在内的新冠肺炎健康后果的严重性，是一项重要的公共卫生目标。新冠肺炎数据可获得性和质量的限制仍然是对这一主题进行结论性研究的障碍。目前，公开可获得的具有代表性人群的新冠肺炎结果数据只能作为地区一级的统计数据。因此，使用这些数据对长期暴露在空气污染中和新冠肺炎结果进行研究必须使用生态回归分析，这排除了对个人水平的新冠肺炎风险因素的控制。我们在美国对这个问题进行的首批初步调查之一的背景下描述了这些挑战，我们发现，在考虑了许多地区层面的混杂因素后，历史上较高的PM2.5值暴露与较高的县级新冠肺炎死亡率呈正相关。在这项研究的激励下，我们为这一重要主题的未来研究奠定了基础，描述了挑战，并勾勒出了有前途的方向和机遇。
We describe the challenges and opportunities of analyzing links between exposure to air pollution and vulnerability to COVID-19. Assessing whether long-term exposure to air pollution increases the severity of COVID-19 health outcomes, including death, is an important public health objective. Limitations in COVID-19 data availability and quality remain obstacles to conducting conclusive studies on this topic. At present, publicly available COVID-19 outcome data for representative populations are available only as area-level counts. Therefore, studies of long-term exposure to air pollution and COVID-19 outcomes using these data must use an ecological regression analysis, which precludes controlling for individual-level COVID-19 risk factors. We describe these challenges in the context of one of the first preliminary investigations of this question in the United States, where we found that higher historical PM2.5 exposures are positively associated with higher county-level COVID-19 mortality rates after accounting for many area-level confounders. Motivated by this study, we lay the groundwork for future research on this important topic, describe the challenges, and outline promising directions and opportunities.
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影响因子：
1
作者：
Booth, JG;Casella, G;Hobert, JP
通讯作者：
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影响因子：
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DOI：
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发表时间：
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影响因子：
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作者：
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