ArticleBMC public health2022
Geographic disparities and predictors of COVID-19 hospitalization risks in the St. Louis Area, Missouri (USA).
Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Sociodemographic and ecological factors associated with malaria and malaria recurrence risk in children in Msambweni, Kwale County, Kenya.Malaria journal · 2025Article
- Variation in COVID-19 vaccination and adverse outcomes: a state of Georgia case study.BMC public health · 2025Article
- Article
- Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States.BMC public health · 2023Article
- The effect of changing COVID-19 restrictions on the transmission rate in a veterinary clinic.Infectious Disease Modelling · 2023Article
- Article
- Geographic disparities and temporal changes of COVID-19 hospitalization risks in North Dakota.Frontiers in public health · 2023Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThere is evidence of geographic disparities in COVID-19 hospitalization risks that, if identified, could guide control efforts. Therefore, the objective of this study was to investigate Zip Code Tabulation Area (ZCTA)-level geographic disparities and identify predictors of COVID-19 hospitalization risks 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 American Community Survey. Geographic disparities in distribution of COVID-19 age-adjusted hospitalization risks, 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.
resultsCOVID-19 hospitalization risks were significantly higher in ZCTAs with high diabetes hospitalization risks (p < 0.0001), COVID-19 risks (p < 0.0001), black population (p = 0.0416), and populations with some college education (p = 0.0005). The associations between COVID-19 hospitalization risks and the first three predictors varied by geographic location.
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 implying that a 'one-size-fits-all' approach may not be appropriate for management and control. Using both global and local models leads to a better understanding of geographic disparities. 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.
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Registered trials
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