Colorado Department of Public Health and Environment, United States.
Colorado Department of Public Health and Environment, United States.
Environ Pollut. 2021 Oct 15;287:117584. doi: 10.1016/j.envpol.2021.117584. Epub 2021 Jun 14.
Previous nationwide studies have reported links between long-term concentrations of fine particulate matter (PM2.5) and COVID-19 infection and mortality rates. In order to translate these results to the state level, we use Bayesian hierarchical models to explore potential links between long-term PM2.5 concentrations and census tract-level rates of COVID-19 outcomes (infections, hospitalizations, and deaths) in Colorado. We explicitly consider how the uncertainty in PM2.5 estimates affects our results by comparing four different PM2.5 surfaces from academic and governmental organizations. After controlling for 20 census tract-level covariates, we find that our results depend heavily on the choice of PM2.5 surface. Using PM2.5 estimates from the United States EPA, we find that a 1 μg/m increase in long-term PM2.5 concentrations is associated with a statistically significant 26% increase in the relative risk of hospitalizations and a 34% increase in mortality. Results for all other surfaces and outcomes were not statistically significant. At the same time, we find a clear association between communities of color and COVID-19 outcomes at the Colorado census tract level that is minimally affected by the choice of PM2.5 surface. A per-interquartile range (IQR) increase in the percent of non-African American people of color was associated with a 31%, 43%, and 56% increase in the relative risk of infection, hospitalization, and mortality respectively, while a per-IQR increase in the proportion of non-Hispanic African Americans was associated with a 4% and 7% increase in the relative risk of infections and hospitalizations. The current disagreement among the different PM2.5 estimates is a key factor limiting our ability to link environmental exposures and health outcomes at the census tract level. These results have strong implications for the implementation of an equitable public health response during the crisis and suggest targeted areas for additional air monitoring in Colorado.
先前的全国性研究报告表明，细颗粒物（PM2.5）的长期浓度与 COVID-19 感染率和死亡率之间存在关联。为了将这些结果转化为州一级的情况，我们使用贝叶斯层次模型来探索科罗拉多州长期 PM2.5 浓度与普查区 COVID-19 结果（感染、住院和死亡）之间的潜在联系。我们通过比较来自学术和政府组织的四种不同的 PM2.5 面，明确考虑了 PM2.5 估计值的不确定性如何影响我们的结果。在控制了 20 个普查区层面的协变量后，我们发现我们的结果在很大程度上取决于 PM2.5 面的选择。使用美国环保署的 PM2.5 估计值，我们发现长期 PM2.5 浓度每增加 1μg/m，住院的相对风险就会显著增加 26%，死亡率增加 34%。其他所有表面和结果的结果均不具有统计学意义。同时，我们发现科罗拉多州普查区层面的有色人种社区与 COVID-19 结果之间存在明显关联，而 PM2.5 面的选择对其影响很小。非非裔美国人的有色人种比例每增加一个四分位距（IQR），感染、住院和死亡的相对风险分别增加 31%、43%和 56%，而非西班牙裔非裔美国人的比例每增加一个 IQR，感染和住院的相对风险分别增加 4%和 7%。目前，不同 PM2.5 估计值之间存在分歧，这是限制我们在普查区一级将环境暴露与健康结果联系起来的关键因素。这些结果对在危机期间实施公平的公共卫生应对措施具有重要意义，并表明科罗拉多州需要在特定领域进行额外的空气质量监测。
