Tan Shin Bin, deSouza Priyanka, Raifman Matthew
Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA, USA.
Lee Kuan Yew School of Public Policy, National University of Singapore, Singapore, Singapore.
J Racial Ethn Health Disparities. 2022 Feb;9(1):236-246. doi: 10.1007/s40615-020-00948-8. Epub 2021 Jan 19.
Substantial health disparities exist across race/ethnicity in the USA, with Black Americans often most affected. The current COVID-19 pandemic is no different. While there have been ample studies describing racial disparities in COVID-19 outcomes, relatively few have established an empirical link between these disparities and structural racism. Such empirical analyses are critically important to help defuse "victim-blaming" narratives about why minority communities have been badly hit by COVID-19. In this paper, we explore the empirical link between structural racism and disparities in county-level COVID-19 outcomes by county racial composition. Using negative binomial regression models, we examine how five measures of county-level residential segregation and racial disparities in socioeconomic outcomes as well as incarceration rates are associated with county-level COVID-19 outcomes. We find significant associations between higher levels of measured structural racism and higher rates of COVID-19 cases and deaths, even after adjusting for county-level population sociodemographic characteristics, measures of population health, access to healthcare, population density, and duration of the COVID-19 outbreak. One percentage point more Black residents predicted a 1.1% increase in county case rate. This association decreased to 0.4% when structural racism indicators were included in our model. Similarly, one percentage point more Black residents predicted a 1.8% increase in county death rates, which became non-significant after adjustment for structural racism. Our findings lend empirical support to the hypothesis that structural racism is an important driver of racial disparities in COVID-19 outcomes, and reinforce existing calls for action to address structural racism as a fundamental cause of health disparities.
美国不同种族/族裔之间存在巨大的健康差异，美国黑人往往受影响最大。当前的新冠疫情也不例外。虽然有大量研究描述了新冠疫情结果中的种族差异，但相对较少的研究在这些差异与结构性种族主义之间建立了实证联系。这种实证分析对于化解关于少数族裔社区为何受新冠疫情重创的“指责受害者”言论至关重要。在本文中，我们通过县种族构成探讨结构性种族主义与县级新冠疫情结果差异之间的实证联系。使用负二项回归模型，我们研究县级居住隔离的五项指标、社会经济结果中的种族差异以及监禁率与县级新冠疫情结果之间的关联。我们发现，即使在调整了县级人口社会人口特征、人口健康指标、医疗保健可及性、人口密度和新冠疫情爆发持续时间之后，所衡量的结构性种族主义水平较高与新冠病例和死亡发生率较高之间仍存在显著关联。黑人居民比例每增加一个百分点，预测县病例率将增加1.1%。当我们的模型纳入结构性种族主义指标时，这种关联降至0.4%。同样，黑人居民比例每增加一个百分点，预测县死亡率将增加1.8%，在调整结构性种族主义后这一关联变得不显著。我们的研究结果为结构性种族主义是新冠疫情结果中种族差异的重要驱动因素这一假设提供了实证支持，并强化了现有呼吁，即采取行动解决结构性种族主义这一健康差异的根本原因。
