Identification of county-level health factors associated with COVID-19 mortality in the United States
dc.contributor.author | Pan, Wei | en |
dc.contributor.author | Miyazaki, Yasuo | en |
dc.contributor.author | Tsumura, Hideyo | en |
dc.contributor.author | Miyazaki, Emi | en |
dc.contributor.author | Yang, Wei | en |
dc.contributor.department | School of Education | en |
dc.coverage.country | United States | en |
dc.date.accessioned | 2021-09-09T12:25:29Z | en |
dc.date.available | 2021-09-09T12:25:29Z | en |
dc.date.issued | 2020-11-01 | en |
dc.date.updated | 2021-09-09T12:25:23Z | en |
dc.description.abstract | Many studies have investigated causes of COVID-19 and explored safety measures for preventing COVID-19 infections. Unfortunately, these studies fell short to address disparities in health status and resources among decentralized communities in the United States. In this study, we utilized an advanced modeling technique to examine complex associations of county-level health factors with COVID-19 mortality for all 3141 counties in the United States. Our results indicated that counties with more uninsured people, more housing problems, more urbanized areas, and longer commute are more likely to have higher COVID-19 mortality. Based on the nationwide population-based data, this study also echoed prior research that used local data, and confirmed that county-level sociodemographic factors, such as more Black, Hispanic, and older subpopulations, are attributed to high risk of COVID-19 mortality. We hope that these findings will help set up priorities on high risk communities and subpopulations in future for fighting the novel virus. | en |
dc.description.version | Published version | en |
dc.format.extent | Pages 437-445 | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.doi | https://doi.org/10.7555/JBR.34.20200129 | en |
dc.identifier.eissn | 2352-4685 | en |
dc.identifier.issn | 1674-8301 | en |
dc.identifier.issue | 6 | en |
dc.identifier.orcid | Miyazaki, Yasuo [0000-0001-8781-387X] | en |
dc.identifier.other | PMC7718079 | en |
dc.identifier.pmid | 33109778 | en |
dc.identifier.uri | http://hdl.handle.net/10919/104954 | en |
dc.identifier.volume | 34 | en |
dc.language.iso | en | en |
dc.publisher | Journal of Biomedical Research | en |
dc.relation.uri | https://www.ncbi.nlm.nih.gov/pubmed/33109778 | en |
dc.rights | Creative Commons Attribution 4.0 International | en |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
dc.subject | COVID-19 | en |
dc.subject | health disparity | en |
dc.subject | health factors | en |
dc.subject | hierarchical generalized linear model | en |
dc.subject | mortality | en |
dc.subject | 1004 Medical Biotechnology | en |
dc.title | Identification of county-level health factors associated with COVID-19 mortality in the United States | en |
dc.title.serial | Journal of Biomedical Research | en |
dc.type | Article - Refereed | en |
dc.type.dcmitype | Text | en |
dc.type.other | Journal Article | en |
pubs.organisational-group | /Virginia Tech | en |
pubs.organisational-group | /Virginia Tech/All T&R Faculty | en |
pubs.organisational-group | /Virginia Tech/Liberal Arts and Human Sciences | en |
pubs.organisational-group | /Virginia Tech/Liberal Arts and Human Sciences/School of Education | en |
pubs.organisational-group | /Virginia Tech/Liberal Arts and Human Sciences/CLAHS T&R Faculty | en |
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