Evidence map›Paper›PMID 37531017›Full record

ArticleJournal of racial and ethnic health disparities2024

Social-Economic Backgrounds to US County-Based COVID-19 Deaths: PLS-SEM Analysis.

Benjamin P Bowser

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Article in Journal of racial and ethnic health disparities, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

1 author.

Benjamin P BowserDepartment of Sociology, California State University, East Bay, 25800 Carlos Bee Blvd, Hayward, CA, 94542, USA. Benjamin.bowser@csueastbay.edu.ORCID 0000-0002-9479-5822

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A complex interplay of social, economic, and environmental factors drove the COVID-19 epidemic. Understanding these factors is crucial in explaining the racial disparities observed in COVID-19 deaths. This research investigated various hypotheses, including ecological, racial, demographic, economic, and political party factors, to determine their impact on COVID-19 deaths. The study utilized data from the National Center for Health Statistics (NCHS), specifically focusing on COVID-19 deaths categorized by race and Hispanic origin in US counties, with over 100 recorded deaths as of July 11, 2022.

methodTo analyze the data, the study employed partial least squares (PLS) as the statistical approach, considering the presence of multicollinearity in the county-level socioeconomic data. SmartPLS4 software was utilized to illustrate paths depicting variance and covariance and to conduct significance tests. The analysis encompassed overall COVID-19 deaths and deaths among White, Black, and Hispanic Americans, utilizing the same latent variables and paths.

resultsThe results revealed that the number of residents aged 65 years or older in a county was the most influential predictor of COVID-19 deaths, irrespective of race. Economic factors emerged as the second strongest predictors. However, when considering each racial group separately, distinct factors aligned with the five hypotheses emerged as significant contributors to COVID-19 deaths. Furthermore, the diagrams illustrating the relationships between these factors (covariates) varied among racial groups, indicating that the underlying social influences differed across races. DISCUSSION: In light of these findings, it becomes evident that a "one-size-fits-all" approach to prevention strategies is suboptimal. Instead, targeted prevention efforts tailored to specific racial and social classes at high risk of COVID-19 death could have provided more precise messaging and necessitate direct engagement.

Indexed as

COVID-19Health Status DisparitiesSocioeconomic FactorsAgedBlack or African AmericanHispanic or LatinoHumansLeast-Squares AnalysisUnited StatesWhiteCountiesCOVID-19 deathsPartial least squaresRaceSocioeconomic factorsStructural equation models

Identifiers

PMID37531017

What Socratic holds

Textmetadata
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Registered trials

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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 Socratic graph.