Pan, WeiMiyazaki, YasuoTsumura, HideyoMiyazaki, EmiYang, Wei2021-09-092021-09-092020-11-011674-8301PMC7718079http://hdl.handle.net/10919/104954Many 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.Pages 437-445application/pdfenCreative Commons Attribution 4.0 InternationalCOVID-19health disparityhealth factorshierarchical generalized linear modelmortality1004 Medical BiotechnologyArticle - Refereed2021-09-09https://doi.org/10.7555/JBR.34.20200129346Miyazaki, Yasuo [0000-0001-8781-387X]331097782352-4685