Geographic Disparities and Predictors of COVID-19 Hospitalization Risk in the St. Louis Area, Missouri (USA)
Geographic Disparities and Predictors of COVID-19 Hospitalization Risk in the St. Louis Area, Missouri (USA)
Abstract BackgroundCOVID-19 has overwhelmed the US healthcare system, with over 44 million cases and over 700,000 deaths as of October 6, 2021. There is evidence that some communities are disproportionately affected. This may result in geographic disparities in COVID-19 hospitalization risk that, if identified, could guide control efforts. Therefore, the objective of this study is to investigate Zip Code Tabulation Area (ZCTA)-level geographic disparities and identify predictors of COVID-19 hospitalization risk in the St. Louis area. MethodsHospitalization data for COVID-19 and several chronic diseases were obtained from the Missouri Hospital Association. ZCTA-level data on socioeconomic and demographic factors were obtained from the US Census Bureau American Community Survey. Age-adjusted COVID-19 and several chronic disease hospitalization risks were calculated. Geographic disparities in distribution of COVID-19 age-adjusted hospitalization risk, socioeconomic and demographic factors as well as chronic disease risks were investigated using choropleth maps. Predictors of ZCTA-level COVID-19 hospitalization risks were investigated using global negative binomial and local geographically weighted negative binomial models. ResultsThere were geographic disparities of COVID-19 hospitalization risks. COVID-19 hospitalization risks were significantly higher in ZCTAs with high diabetes hospitalization risks (p<0.0001), high risks of COVID-19 cases (p<0.0001), as well as high percentages of black population (p=0.0416) and populations with some college education (p=0.0005). The coefficients of the first three predictors varied across ZCTAs, implying that the associations between COVID-19 hospitalization risks and these predictors varied by geographic location. This implies that a “one-size-fits-all” approach may not be appropriate for management and control. ConclusionsThere is evidence of geographic disparities in COVID-19 hospitalization risks that are driven by differences in socioeconomic, demographic and health-related factors. The impacts of these factors vary by geographical location with some factors being more important predictors in some locales than others. Use of both global and local models leads to a better understanding of the determinants of geographic disparities in health outcomes and utilization of health services. These findings are useful for informing health planning to identify geographic areas likely to have high numbers of individuals needing hospitalization as well as guiding vaccination efforts.
Igoe Morganne、Das Praachi、Lenhart Suzanne、Lanzas Cristina、Luong Lan、Odoi Agricola、Tian Dajun、Lloyd Alun L.
Department of Mathematics, University of TennesseeBiomathematics Graduate Program and Department of Mathematics, North Carolina State UniversityDepartment of Mathematics, University of TennesseeDepartment of Population Health and Pathobiology and Comparative Medicine Institute, North Carolina State UniversityBJC HealthcareDepartment of Biomedical and Diagnostics Sciences, University of TennesseeBJC HealthcareBiomathematics Graduate Program and Department of Mathematics, North Carolina State University
医学研究方法预防医学医药卫生理论
Severe Acute Respiratory Syndrome Coronavirus 2SARS-CoV-2Coronavirus Disease 2019COVID-19DisparitiesHospitalization RisksPredictorsNegative Binomial ModelsGeographically Weighted Regression ModelsEpidemiologyMissouri
Igoe Morganne,Das Praachi,Lenhart Suzanne,Lanzas Cristina,Luong Lan,Odoi Agricola,Tian Dajun,Lloyd Alun L..Geographic Disparities and Predictors of COVID-19 Hospitalization Risk in the St. Louis Area, Missouri (USA)[EB/OL].(2025-03-28)[2025-08-02].https://www.medrxiv.org/content/10.1101/2021.10.21.21265289.点此复制
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