新冠病毒风险的差异：种族和县级健康社会决定因素在退伍军人中的体现。
Differences in COVID-19 Risk by Race and County-Level Social Determinants of Health among Veterans.
机构信息
VA Palo Alto Healthcare System, US Department of Veterans Affairs, Palo Alto, CA 94304, USA.
Department of Epidemiology and Population Health, Stanford University, Stanford, CA 94305, USA.
出版信息
Int J Environ Res Public Health. 2021 Dec 13;18(24):13140. doi: 10.3390/ijerph182413140.
Abstract
COVID-19 disparities by area-level social determinants of health (SDH) have been a significant public health concern and may also be impacting U.S. Veterans. This retrospective analysis was designed to inform optimal care and prevention strategies at the U.S. Department of Veterans Affairs (VA) and utilized COVID-19 data from the VAs EHR and geographically linked county-level data from 18 area-based socioeconomic measures. The risk of testing positive with Veterans' county-level SDHs, adjusting for demographics, comorbidities, and facility characteristics, was calculated using generalized linear models. We found an exposure-response relationship whereby individual COVID-19 infection risk increased with each increasing quartile of adverse county-level SDH, such as the percentage of residents in a county without a college degree, eligible for Medicaid, and living in crowded housing.
摘要
COVID-19 在美国退伍军人中也存在地区社会决定因素（SDH）差异，这是一个重大的公共卫生关注点。本回顾性分析旨在为美国退伍军人事务部（VA）提供最佳护理和预防策略，并利用 VA 的电子健康记录（EHR）中的 COVID-19 数据以及 18 个基于地区的社会经济措施的县级地理链接数据。使用广义线性模型计算退伍军人县级 SDH 与检测呈阳性的风险，调整人口统计学、合并症和设施特征。我们发现了一种暴露反应关系，即每个县级不利 SDH 的四分位数增加，个体 COVID-19 感染风险就会增加，例如一个县没有大学学历的居民比例、有资格享受医疗补助和居住在拥挤住房的居民比例。
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