Chen Aokun, Zhao Yunpeng, Zheng Yi, Hu Hui, Hu Xia, Fishe Jennifer N, Hogan William R, Shenkman Elizabeth A, Guo Yi, Bian Jiang
Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL 32611, USA.
Lowe's Tech Hub, Charlotte, NC 28203, USA.
Informatics (MDPI). 2024 Mar;11(1). doi: 10.3390/informatics11010004. Epub 2024 Jan 15.
It is prudent to take a unified approach to exploring how contextual social determinants of health (SDoH) relate to COVID-19 occurrence and outcomes. Poor geographically represented data and a small number of contextual SDoH examined in most previous research studies have left a knowledge gap in the relationships between contextual SDoH and COVID-19 outcomes. In this study, we linked 199 contextual SDoH factors covering 11 domains of social and built environments with electronic health records (EHRs) from a large clinical research network (CRN) in the National Patient-Centered Clinical Research Network (PCORnet) to explore the relation between contextual SDoH and COVID-19 occurrence and hospitalization. We identified 15,890 COVID-19 patients and 63,560 matched non-COVID-19 patients in Florida between January 2020 and May 2021. We adopted a two-phase multiple linear regression approach modified from that in the exposome-wide association (ExWAS) study. After removing the highly correlated SDoH variables, 86 contextual SDoH variables were included in the data analysis. Adjusting for race, ethnicity, and comorbidities, we found six contextual SDoH variables (i.e., hospital available beds and utilization, percent of vacant property, number of golf courses, and percent of minority) related to the occurrence of COVID-19, and three variables (i.e., farmers market, low access, and religion) related to the hospitalization of COVID-19. To our best knowledge, this is the first study to explore the relationship between contextual SDoH and COVID-19 occurrence and hospitalization using EHRs in a major PCORnet CRN. As an exploratory study, the causal effect of SDoH on COVID-19 outcomes will be evaluated in future studies.
采用统一的方法来探究健康的背景性社会决定因素（SDoH）与新冠病毒病（COVID-19）的发生及结局之间的关系是明智之举。在大多数先前的研究中，地理代表性不足的数据以及少量被研究的背景性SDoH，使得背景性SDoH与COVID-19结局之间的关系存在知识空白。在本研究中，我们将涵盖社会和建筑环境11个领域的199个背景性SDoH因素与来自国家以患者为中心的临床研究网络（PCORnet）中的一个大型临床研究网络（CRN）的电子健康记录（EHR）相链接，以探究背景性SDoH与COVID-19发生及住院之间的关系。我们在2020年1月至2021年5月期间在佛罗里达州确定了15,890例COVID-19患者和63,560例匹配的非COVID-19患者。我们采用了一种在全暴露组关联（ExWAS）研究中修改而来的两阶段多元线性回归方法。在去除高度相关的SDoH变量后，86个背景性SDoH变量被纳入数据分析。在对种族、民族和合并症进行校正后，我们发现六个背景性SDoH变量（即医院可用床位及利用率、空置房产百分比、高尔夫球场数量和少数族裔百分比）与COVID-19的发生相关，以及三个变量（即农贸市场、低可及性和宗教）与COVID-19的住院相关。据我们所知，这是第一项在主要的PCORnet CRN中使用EHR探究背景性SDoH与COVID-19发生及住院之间关系的研究。作为一项探索性研究，SDoH对COVID-19结局的因果效应将在未来的研究中进行评估。
