Identification of county-level health factors associated with COVID-19 mortality in the United States

Pan, Wei; Miyazaki, Yasuo; Tsumura, Hideyo; Miyazaki, Eriko; Yang, Wei

doi:10.7555/jbr.34.20200129

Cited by 13 publications

(16 citation statements)

References 24 publications

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“…Our findings build on this work by evaluating variability in the strength of the association between income inequality and COVID-19 cases and deaths at the county level over time. 12 Moreover, our work accounts for additional potential confounding factors, such as crowding and urban or rural living, as well as measures of deprivation (poverty, housing situation, educational level, and health system presence).…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…11 Moreover, individuals with lower incomes are more likely to reside in crowded housing and have public-facing jobs, such as service, child and elder care, and cleaning or janitorial services, which can increase the risk of exposure to SARS-CoV-2. 12 In this study, we sought to evaluate the correlation between county-level income inequality, measured by the Gini coefficient, and county-level COVID-19 case and death counts across the United States at different time epochs in 2020 and 2021. County-level income inequality reflects the lived experience of those residing in these regions better than state-level measures.…”

Section: Introductionmentioning

confidence: 99%

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Association Between Income Inequality and County-Level COVID-19 Cases and Deaths in the US

et al. 2021

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Key Points Question How does the association between county-level income inequality, measured by the Gini coefficient, and COVID-19 cases and deaths change over time? Findings This ecological cohort study found that there was a positive correlation between Gini coefficients and county-level COVID-19 cases and deaths during the study period. The association between income inequality and COVID-19 cases and deaths varied over time and was strongest in the summer months of 2020. Meaning The findings suggest that, during the COVID-19 pandemic, areas of higher income inequality may serve as effective targets for interventions to mitigate the spread of SARS-CoV-2.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Association Between Income Inequality and County-Level COVID-19 Cases and Deaths in the US

et al. 2021

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“…If this is the case, then the collective health factors are likely predictive of other health activities and behaviors. For example, researchers [30,31] have adopted portions of Hood et al's model to show that a variety of county-level health factors were associated with COVID-19 mortality rates. Similarly, primary care physician rate (a factor of clinical care in Hood et al's model) is predictive of COVID-19 deaths at the county level [32].…”

Section: Introductionmentioning

confidence: 99%

Demographics, politics, and health factors predict mask wearing during the COVID-19 pandemic: a cross-sectional study

Cunningham

Nite

2021

BMC Public Health

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Background Wearing a protective face covering can reduce the spread of COVID-19, but Americans’ compliance with wearing a mask is uneven. The purpose of this study is to examine the association between health determinants (Health Behaviors, Clinical Care, Social and Economic Conditions, and the Physical Environment) and mask wearing at the county level. Methods Data were collected from publicly available sources, including the County Health Rankings and the New York Times. The dependent variable was the percent of county residents who reported frequently or always wearing a mask when in public. County demographics and voting patterns served as controls. Two-levels random effects regression models were used to examine the study hypotheses. Results Results indicate that, after considering the effects of the controls, Health Behaviors were positively associated with mask wearing, the Physical Environment held a negative association, and Clinical Care and Social and Behavioral Factors were unrelated. Conclusions Results indicate that patterns of healthy behaviors can help predict compliance with public health mandates that can help reduce the spread of COVID-19. From an instutitional theory perspective, the data suggest counties develop collective values and norms around health. Thus, public health officials can seek to alter governance structures and normative behaviors to improve healthy behaviors.

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“…Second, we adopted a within-subject research design with a standard spatial sampling unit across the country, giving a representative study for USA urban counties. In contrast with previous studies on COVID-19 that examined associations between SARS-CoV-2 infection rate or COVID-19 mortality rate across counties or cities 10, 101, 102 , our study focused on comparing difference in SARS-CoV-2 infection rates among white and black people in the same county. By comparing racial disparity in infection rates within each county we obtain greater statistical validity, as this approach mitigates bias caused by uneven spread of infections across counties due to differences in national road network accessibility, airports and railway connectivity, governmental regulations, social norms, and quantity and quality of healthcare services.…”

Section: Discussionmentioning

confidence: 99%

A higher ratio of green spaces means a lower racial disparity in severe acute respiratory syndrome coronavirus 2 infection rates: A nationwide study of the United States

Lü

Chen

Liu

et al. 2020

Preprint

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There is striking racial disparity in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates in the United States. We hypothesize that the disparity is significantly smaller in areas with a higher ratio of green spaces at the county level. This study used the 135 most urbanized counties across the United States as sample sites. County level data on the SARS-CoV-2 infection rates of black and white individuals in each county were collected. The ratio of green spaces by land-cover type at the county level was calculated from satellite imagery. An ecological hierarchical regression analysis measured cross-sectional associations between racial disparity in infection rates and green spaces, after controlling for socioeconomic, demographic, pre-existing chronic disease, and built-up area factors. We found significantly higher infection rate among black individuals compared to white individuals. More importantly, a higher ratio of green spaces at the county level is significantly associated with a lower racial disparity in the SARS-CoV-2 infection rate. Further, we identified four green space factors that have significant negative associations with the racial disparity in SARS-CoV-2 infection rates, including open space in developed areas, forest, shrub and scrub, and grassland and herbaceous. We suggest that green spaces are an equalizing salutogenic factor, modifying infection exposure.HighlightsThe first study to identify significant relationships between green spaces and the racial disparity of SARS-CoV-2 infection rates.A nationwide study of the 135 most urbanized counties of the United States.A within-subject study: The black-white racial disparity of SARS-CoV-2 infection rates was measured within each county.A higher ratio of green spaces in a county is associated with a lower racial disparity of SARS-CoV-2 infection rates after controlling for socio-economic, demographic, pre-existing chronic disease, and built-up area factors.Four green space factors are significantly associated with a lower racial disparity of SARS-CoV-2 infection rates.

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Identification of county-level health factors associated with COVID-19 mortality in the United States

Cited by 13 publications

References 24 publications

Association Between Income Inequality and County-Level COVID-19 Cases and Deaths in the US

Association Between Income Inequality and County-Level COVID-19 Cases and Deaths in the US

Demographics, politics, and health factors predict mask wearing during the COVID-19 pandemic: a cross-sectional study

A higher ratio of green spaces means a lower racial disparity in severe acute respiratory syndrome coronavirus 2 infection rates: A nationwide study of the United States

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