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Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis

机译:美国的空气污染和Covid-19死亡率:生态回归分析的优势和局限

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摘要

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 PMsub2.5/sub 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.
机译:评估航空污染的长期暴露是否会增加Covid-19卫生成果的严重程度,包括死亡,是一个重要的公共卫生目标。 Covid-19数据可用性和质量的限制仍然是对这一主题进行决定性研究的障碍。目前,代表性群体的公开的Covid-19结果数据仅适用于区域级计数。因此,使用这些数据的长期暴露于空气污染和Covid-19结果的研究必须使用生态回归分析,这排除了控制个体级Covid-19风险因素。我们在美国的第一次初步调查中描述了这些挑战,在美国的第一次初步调查之一,我们发现历史悠久的PM 2.5 曝光与高县级Covid-19死亡率正相关考虑到许多面积级混乱后的率。通过这项研究的动机,我们为未来的这一重要主题奠定了基础,描述了挑战,概述了有希望的方向和机遇。

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