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Overcrowding and COVID-19 mortality across U.S. counties: Are disparities growing over time?

ABSTRACT: A growing line of research underscores that sociodemographic factors may contribute to disparities in the impact of COVID-19. Further, stages of disease theory suggests that disparities may grow as the pandemic unfolds and more advantaged areas are better able to apply growing knowledge and mitigation strategies. In this paper, we focus on the role of county-level household overcrowding on disparities in COVID-19 mortality in U.S. counties. We examine this relationship across three theoretically important periods of the pandemic from April-October 2020, that mark both separate stages of community knowledge and national mortality levels. We find evidence that the percentage of overcrowded households is a stronger predictor of COVID-19 mortality during later periods of the pandemic. Moreover, despite a relationship between overcrowding and poverty at the county-level, overcrowding plays an independent role in predicting COVID-19 mortality. Our findings underscore that areas disadvantaged by overcrowding may be more vulnerable to the effects of COVID-19 and that this vulnerability may lead to changing disparities over time.

SUBMITTER: Kamis C

PROVIDER: S-EPMC8219888 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Overcrowding and COVID-19 mortality across U.S. counties: Are disparities growing over time?

Kamis Christina C Stolte Allison A West Jessica S JS Fishman Samuel H SH Brown Taylor T Brown Tyson T Farmer Heather R HR

SSM - population health 20210612

A growing line of research underscores that sociodemographic factors may contribute to disparities in the impact of COVID-19. Further, stages of disease theory suggests that disparities may grow as the pandemic unfolds and more advantaged areas are better able to apply growing knowledge and mitigation strategies. In this paper, we focus on the role of county-level household overcrowding on disparities in COVID-19 mortality in U.S. counties. We examine this relationship across three theoretically ...[more]

PMID: 34189244

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Project description:To investigate temporal trends in coronavirus disease 2019 (COVID-19)-related outcomes and to evaluate whether the impacts of potential risk factors and disparities changed over time, we conducted a retrospective cohort study with 249 075 patients tested or treated for COVID-19 at Michigan Medicine (MM), from 10 March 2020 to 3 May 2021. Among these patients, 26 289 were diagnosed with COVID-19. According to the calendar time in which they first tested positive, the COVID-19-positive cohort were stratified into three-time segments (T1: March–June, 2020; T2: July–December, 2020; T3: January–May, 2021). Potential risk factors that we examined included demographics, residential-level socioeconomic characteristics and preexisting comorbidities. The main outcomes included COVID-19-related hospitalisation and intensive care unit (ICU) admission. The hospitalisation rate for COVID-positive patients decreased from 36.2% in T1 to 14.2% in T3, and the ICU admission rate decreased from 16.9% to 2.9% from T1 to T3. These findings confirm that COVID-19-related hospitalisation and ICU admission rates were decreasing throughout the pandemic from March 2020 to May 2021. Black patients had significantly higher (compared to White patients) hospitalisation rates (19.6% vs. 11.0%) and ICU admission rates (6.3% vs. 2.8%) in the full COVID-19-positive cohort. A time-stratified analysis showed that racial disparities in hospitalisation rates persisted over time and the estimates of the odds ratios (ORs) stayed above unity in both unadjusted [full cohort: OR = 1.98, 95% confidence interval (CI) (1.79, 2.19); T1: OR = 1.70, 95% CI (1.36, 2.12); T2: OR = 1.40, 95% CI (1.17, 1.68); T3: OR = 1.55, 95% CI (1.29, 1.86)] and adjusted analysis, accounting for differences in demographics, socioeconomic status, and preexisting comorbid conditions (full cohort: OR = 1.45, 95% CI (1.25, 1.68); T1: OR = 1.26, 95% CI (0.90, 1.76); T2: OR = 1.29, 95% CI (1.01, 1.64); T3: OR = 1.29, 95% CI (1.00, 1.67)).

Dataset Information

Overcrowding and COVID-19 mortality across U.S. counties: Are disparities growing over time?

Publications

Overcrowding and COVID-19 mortality across U.S. counties: Are disparities growing over time?

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