Evidence map›Paper›PMID 35337382›Full record

ArticleArchives of public health = Archives belges de sante publique2022

Population distribution by ethnicities and the disparities in health risk and coping in the United States during the pandemic: the spatial and time dynamics.

Jiannan Li, Xinmeng Wang, Bocong Yuan

Abstract read
In one paragraph

Article in Archives of public health = Archives belges de sante publique, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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

2 citing papers in PubMed.

  1. Article
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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

3 authors.

Jiannan LiInstitute of Advanced Studies in Humanities and Social Sciences, Beijing Normal University, Zhuhai, China.
Xinmeng WangSchool of Tourism Management, Sun Yat-Sen University, West Xingang Rd. 135, Guangzhou, 510275, China.
Bocong YuanSchool of Tourism Management, Sun Yat-Sen University, West Xingang Rd. 135, Guangzhou, 510275, China. yuanbc@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-6918-5483

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs a multi-ethnic country, the US is increasingly concerned about ethnic minorities facing disproportionate health risks of the coronavirus disease 2019 (COVID-19) pandemic. This study attempted to provide a macro picture of the associations between population distribution by ethnicity and the vulnerability to COVID-19 in terms of infection risk and vaccination coverage in the US.

methodsThis study used multi-source data from New York Times, County Health Rankings & Roadmap Program (2020), and the Center for Disease Control and Prevention. Multiple linear regressions were performed at equidistant time points (May 2020-Jan 2021, with one-month interval between each time point) to reveal the association between population distribution by ethnicities and the infection risk and the dynamics over time. Besides, multiple linear regressions were also conducted at equidistant time points (Jan 2021-Aug 2021) to reveal whether health disparities between ethnicities would hold true for the COVID-19 vaccination coverage (in total population, and among those > 12, > 18, and > 65 years of age).

resultsBoth the COVID-19 confirmed cases (population standardized) and the vaccination coverage (in total population, and among those > 12, > 18, and > 65 years of age) were significantly associated with the population distribution by ethnicity (e.g., population percentage of ethnic minorities). Above associations were statistically significant for non-Hispanic blacks and Hispanics, but not for Asian Americans.

conclusionsA proportion of socioeconomically-disadvantageous population could be a key intuitive reflection of the risk level of this public health crisis. The policy focusing on the vulnerable population is important in this pandemic.

Indexed as

Ethnic minoritiesHealth riskPandemicPopulation distributionVaccination coverage

Identifiers

PMID35337382
PMCPMC8948454

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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 OpenQuestion graph.