The social, demographic, and clinical predictors of COVID-19 severity: A national study of United States Veterans Open Access
Greenhouse, Alyssa (Spring 2022)
Abstract
Introduction: Understanding the risk factors for COVID-19 disease and severity remains a public
health priority. Demographic and clinical factors put individuals at higher risk. These
characteristics do not operate in a vacuum but coexist with social determinants of health (SDOH)
to influence health outcomes. This study aims to identify how individual and community level
SDOH characteristics along with demographic and clinical factors are associated with COVID-
19 disease severity.
Methods: This national cross-sectional study investigated 220,848 active Veterans tested for
COVID-19 between February 20, 2020 and October 20, 2021. Variables of interest included
individual demographic, clinical, and SDOH characteristics. Census variables were incorporated
for community SDOH factors. Multiple logistic regression models were constructed using a
backwards elimination approach to examine factors associated with COVID-19 hospitalization
and intensive care unit (ICU) admission.
Results: Participants were predominately male, 60 years or older, non-Hispanic white, had
completed high-school or vocational/technical school, and lived in an urban residence.
Compared to those not hospitalized, those who were hospitalized were older, more likely to be
male, of Black/African American or Asian race, have an income less than $39,999, live in an urban
residence, and have a higher Elixhauser comorbidity index. The strongest predictors for COVID-
19 hospitalization included Gini inequality index (OR=2.88), race (non-Hispanic black or
African American OR=1.48, Asian OR=1.48, and Native Hawaiian/other pacific or American
Indian/Alaska native OR=1.25 compared to white), and income less than $39,999 (OR=1.22).
Comorbid conditions with increased odds of hospitalization included heart failure (OR=1.93),
chronic kidney disease (CKD) (OR=1.86) and chronic obstructive pulmonary disease (COPD)
(OR=1.77). For COVID-19 ICU admission, Asian vs. White (OR=1.46), rural vs. urban
(OR=1.22), COPD (OR=1.34), and CKD (OR=1.24) were the strongest demographic and
comorbid predictors.
Discussion: A combination of clinical, demographic, individual SDOH, and community level
SDOH factors predict COVID-19 hospitalization and can inform patient risk stratification and
discharge planning. These factors can be incorporated into a comprehensive risk assessment tool
for COVID-19 hospitalization while ICU admission may be better explained by laboratory
values or hospital characteristics. Public health interventions should target communities of color
with higher inequality indices and SDOH risk factors.
Table of Contents
Introduction ....................................................................................................................................2
Methods ..........................................................................................................................................7
Study Design and Population ............................................................................................................7
Data Sources ....................................................................................................................................7
Data Measures ................................................................................................................................. 7
Statistical Analysis ......................................................................................................................... 10
Results ...........................................................................................................................................11
Discussion & Conclusion .................................................................................................................14
References ......................................................................................................................................19
Tables and Figures ...........................................................................................................................24
Figure 1 .......................................................................................................................................... 24
Figure 2 .......................................................................................................................................... 25
Table 1 ........................................................................................................................................... 26
Table 2 ............................................................................................................................................ 29
Table 3 ............................................................................................................................................ 31
About this Master's Thesis
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