School of Social Work, Louisiana State University, 2167 Pleasant Hall, Baton Rouge, LA, 70803, USA.
School of Public Health, Louisiana State University Health Sciences Center New Orleans, New Orleans, LA, USA.
J Racial Ethn Health Disparities. 2023 Apr;10(2):775-787. doi: 10.1007/s40615-022-01265-y. Epub 2022 Mar 3.
Early COVID-19 pandemic data suggested racial/ethnic minority and low-income earning people bore the greatest burden of infection. Structural racism, the reinforcement of racial and ethnic discrimination via policy, provides a framework for understanding disparities in health outcomes like COVID-19 infection. Residential racial and economic segregation is one indicator of structural racism. Little attention has been paid to the relationship of infection to relative overall concentrations of risk (i.e., segregation of the most privileged from the most disadvantaged). We used ordinary least squares and geographically weighted regression models to evaluate the relationship between racial and economic segregation, measured by the Index of Concentration at the Extremes, and COVID-19 cases in Louisiana. We found a significant global association between racial segregation and cumulative COVID-19 case rate in Louisiana and variation across the state during the study period. The northwest and central regions exhibited a strong negative relationship indicating greater risk in areas with high concentrations of Black residents. On the other hand, the southeastern part of the state exhibited more neutral or positive relationships indicating greater risk in areas with high concentrations of White residents. Our findings that the relationship between racial segregation and COVID-19 cases varied within a state further support evidence that social and political determinants, not biological, drive racial disparities. Small area measures and measures of polarization provide localized information better suited to tailoring public health policy according to the dynamics of communities at the census tract level, which may lead to better health outcomes.
早期的 COVID-19 疫情数据表明，少数族裔和低收入人群感染的负担最大。结构性种族主义通过政策加强种族和族裔歧视，为理解 COVID-19 等感染等健康结果的差异提供了一个框架。居住的种族和经济隔离是结构性种族主义的一个指标。人们很少关注感染与相对总体风险集中程度（即最特权者与最弱势群体的隔离）之间的关系。我们使用普通最小二乘法和地理加权回归模型来评估路易斯安那州的种族和经济隔离（以极端集中指数衡量）与 COVID-19 病例之间的关系。我们发现，路易斯安那州的种族隔离与 COVID-19 累计病例率之间存在显著的全球关联，并且在研究期间整个州都存在差异。西北部和中部地区表现出强烈的负相关关系，表明黑人居民高度集中的地区风险更大。另一方面，该州东南部的关系更为中性或积极，表明白人居民高度集中的地区风险更大。我们发现，种族隔离与 COVID-19 病例之间的关系在一个州内存在差异，这进一步支持了这样一种证据，即社会和政治决定因素而非生物学因素导致了种族差异。小区域措施和两极化措施提供了本地化信息，更适合根据社区在普查区层面的动态制定公共卫生政策，这可能会带来更好的健康结果。
