Department of Sociology, California State University, East Bay, 25800 Carlos Bee Blvd, Hayward, CA, 94542, USA.
J Racial Ethn Health Disparities. 2024 Aug;11(4):2304-2317. doi: 10.1007/s40615-023-01698-z. Epub 2023 Aug 2.
A complex interplay of social, economic, and environmental factors drove the COVID-19 epidemic. Understanding these factors is crucial in explaining the racial disparities observed in COVID-19 deaths. This research investigated various hypotheses, including ecological, racial, demographic, economic, and political party factors, to determine their impact on COVID-19 deaths. The study utilized data from the National Center for Health Statistics (NCHS), specifically focusing on COVID-19 deaths categorized by race and Hispanic origin in US counties, with over 100 recorded deaths as of July 11, 2022.
To analyze the data, the study employed partial least squares (PLS) as the statistical approach, considering the presence of multicollinearity in the county-level socioeconomic data. SmartPLS4 software was utilized to illustrate paths depicting variance and covariance and to conduct significance tests. The analysis encompassed overall COVID-19 deaths and deaths among White, Black, and Hispanic Americans, utilizing the same latent variables and paths.
The results revealed that the number of residents aged 65 years or older in a county was the most influential predictor of COVID-19 deaths, irrespective of race. Economic factors emerged as the second strongest predictors. However, when considering each racial group separately, distinct factors aligned with the five hypotheses emerged as significant contributors to COVID-19 deaths. Furthermore, the diagrams illustrating the relationships between these factors (covariates) varied among racial groups, indicating that the underlying social influences differed across races.
In light of these findings, it becomes evident that a "one-size-fits-all" approach to prevention strategies is suboptimal. Instead, targeted prevention efforts tailored to specific racial and social classes at high risk of COVID-19 death could have provided more precise messaging and necessitate direct engagement.
社会、经济和环境因素的复杂相互作用推动了 COVID-19 疫情。了解这些因素对于解释 COVID-19 死亡中观察到的种族差异至关重要。本研究调查了各种假设,包括生态、种族、人口统计学、经济和政党因素,以确定它们对 COVID-19 死亡的影响。该研究利用了国家卫生统计中心(NCHS)的数据,特别是关注了截至 2022 年 7 月 11 日美国县按种族和西班牙裔起源分类的 COVID-19 死亡人数,超过 100 人死亡。
为了分析数据,该研究采用了偏最小二乘(PLS)作为统计方法,考虑到县一级社会经济数据中存在多重共线性。使用 SmartPLS4 软件来说明描绘方差和协方差的路径,并进行显著性检验。分析包括总体 COVID-19 死亡人数以及白种人、黑人和西班牙裔美国人的死亡人数,使用相同的潜在变量和路径。
结果表明,县中 65 岁或以上居民的数量是 COVID-19 死亡的最主要预测因素,与种族无关。经济因素是第二大最强预测因素。然而,当分别考虑每个种族群体时,与五个假设一致的不同因素成为 COVID-19 死亡的重要贡献者。此外,说明这些因素(协变量)之间关系的图表因种族群体而异,表明不同种族之间的社会影响存在差异。
根据这些发现,显然,预防策略的“一刀切”方法并不理想。相反,针对特定种族和社会阶层的有针对性的预防措施,这些阶层有高风险患上 COVID-19 死亡,可以提供更精确的信息,并需要直接参与。