Evidence map›Paper›PMID 35402766›Full record

ArticleHealth equity2022

Health Inequity in Georgia During the COVID-19 Pandemic: An Ecological Analysis Assessing the Relationship Between County-Level Racial/Ethnic and Economic Polarization Using the ICE and SARS-CoV-2 Cases, Hospitalizations, and Deaths in Georgia as of October 2020.

Amit Eichenbaum, Allan D Tate

Open access · goldAbstract read
In one paragraph

Article in Health equity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Amit EichenbaumCollege of Veterinary Medicine, University of Georgia, Athens, Georgia, USA.ORCID https://orcid.org/0000-0001-6749-164X
Allan D TateEpidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia, USA.
University of Georgia · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The coronavirus disease 2019 (COVID-19) pandemic disproportionately burdens communities of color in the United States. The prevalence of preexisting conditions in these populations has not accounted for the observed health inequities. A growing body of research indicates a significant role of racialized residential segregation and income inequality on health outcomes. The Index of Concentration at the Extremes (ICE) is a metric which captures socio-spatial and economic polarization that has proven to be a valuable predictor of a large variety of health outcomes. Objectives: The primary objective of this ecologic study was to determine the impact of socio-spatial and economic segregation on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) morbidity and mortality in Georgia. Methods: The ICE scores for racial/ethnic, economic, and racialized economic segregation for each county in Georgia ( Results: Counties with the largest income disparity had 1.57 times the case rate ( Conclusion: Racialized economic segregation is a strong correlate of pandemic health inequities in Georgia and highlights the need for structural interventions to address barriers to minority and vulnerable population health. Increased focus and efforts to address the structural and systematic barriers faced by communities of color is necessary to address health inequities.

Indexed as

COVID-19income inequalityracial inequalityresidential segregation

Identifiers

PMID35402766
PMCPMC8985538
OpenAlexW4220751154

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.