Assessing inequities underlying racial disparities of COVID-19 mortality in Louisiana parishes

COVID-19 mortality among kidney transplant candidates is strongly associated with social determinants of health.

Although social determinants of health (SDOH) are important factors in health inequities, they have not been explicitly associated with COVID-19 mortality rates across racial and ethnic groups and rural, suburban, and urban contexts. To explore the spatial and racial disparities in county-level COVID-19 mortality rates during the first year of the pandemic. This cross-sectional study analyzed data for all US counties in 50 states and the District of Columbia for the first full year of the COVID-19 pandemic (January 22, 2020, to February 28, 2021). Counties with a high concentration of a single racial and ethnic population and a high level of COVID-19 mortality rate were identified as concentrated longitudinal-impact counties. The SDOH that may be associated with mortality rate across these counties and in urban, suburban, and rural contexts were examined. The 3 largest racial and ethnic groups in the US were selected: Black or African American, Hispanic or Latinx, and non-Hispanic White populations. County-level characteristics and community health factors (eg, income inequality, uninsured rate, primary care physicians, preventable hospital stays, severe housing problems rate, and access to broadband internet) associated with COVID-19 mortality. Data on county-level COVID-19 mortality rates (deaths per 100 000 population) reported by the US Centers for Disease Control and Prevention were analyzed. Four indexes were used to measure multiple dimensions of SDOH: socioeconomic advantage index, limited mobility index, urban core opportunity index, and mixed immigrant cohesion and accessibility index. Spatial regression models were used to examine the associations between SDOH and county-level COVID-19 mortality rate. Of the 3142 counties included in the study, 531 were identified as concentrated longitudinal-impact counties. Of these counties, 347 (11.0%) had a large Black or African American population compared with other counties, 198 (6.3%) had a large Hispanic or Latinx population compared with other counties, and 33 (1.1%) had a large non-Hispanic White population compared with other counties. A total of 489 254 COVID-19-related deaths were reported. Most concentrated longitudinal-impact counties with a large Black or African American population compared with other counties were spread across urban, suburban, and rural areas and experienced numerous disadvantages, including higher income inequality (297 of 347 [85.6%]) and more preventable hospital stays (281 of 347 [81.0%]). Most concentrated longitudinal-impact counties with a large Hispanic or Latinx population compared with other counties were located in urban areas (114 of 198 [57.6%]), and 130 (65.7%) of these counties had a high percentage of people who lacked health insurance. Most concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties were in rural areas (23 of 33 [69.7%]), included a large group of older adults (26 of 33 [78.8%]), and had limited access to quality health care (24 of 33 [72.7%]). In urban areas, the mixed immigrant cohesion and accessibility index was inversely associated with COVID-19 mortality (coefficient [SE], -23.38 [6.06]; P < .001), indicating that mortality rates in urban areas were associated with immigrant communities with traditional family structures, multiple accessibility stressors, and housing overcrowding. Higher COVID-19 mortality rates were also associated with preventable hospital stays in rural areas (coefficient [SE], 0.008 [0.002]; P < .001) and higher socioeconomic status vulnerability in suburban areas (coefficient [SE], -21.60 [3.55]; P < .001). Across all community types, places with limited internet access had higher mortality rates, especially in urban areas (coefficient [SE], 5.83 [0.81]; P < .001). This cross-sectional study found an association between different SDOH measures and COVID-19 mortality that varied across racial and ethnic groups and community types. Future research is needed that explores the different dimensions and regional patterns of SDOH to address health inequity and guide policies and programs.

In the COVID-19 pandemic in Brazil, do brown lives matter?

BackgroundInequities in COVID-19 outcomes in the USA have been clearly documented for sex and race: men are dying at higher rates than women, and Black individuals are dying at higher rates than white individuals. Unexplored, however, is how sex and race interact in COVID-19 outcomes.ObjectiveUse available data to characterize COVID-19 mortality rates within and between race and sex strata in two US states, with the aim of understanding how apparent sex disparities in COVID-19 deaths vary across race.Design and ParticipantsThis observational study uses COVID-19 mortality data through September 21, 2020, from Georgia (GA) and Michigan (MI).Main MeasuresWe calculate age-specific rates for each sex-race-age stratum, and age-standardized rates for each race-sex stratum. We investigate the sex disparity within race groups and the race disparity within sex groups using age-standardized rate ratios, and rate differences.Key ResultsWithin race groups, men have a higher COVID-19 mortality rate than women. Black men have the highest rate of all race-sex groups (in MI: 254.6, deaths per 100,000, 95% CI: 241.1–268.2, in GA:128.5, 95% CI: 121.0-135.9). In MI, the COVID-19 mortality rate for Black women (147.1, 95% CI: 138.7–155.4) is higher than the rate for white men (39.1, 95% CI: 37.3–40.9), white women (29.7, 95% CI: 28.3–31.0), and Asian/Pacific Islander men and women. COVID-19 mortality rates in GA followed the same pattern. In MI, the male:female mortality rate ratio among Black individuals is 1.7 (1.5–2.0) while the rate ratio among White individuals is only 1.3 (1.2–1.5).ConclusionWhile overall, men have higher COVID-19 mortality rates than women, our findings show that this sex disparity does not hold across racial groups. This demonstrates the limitations of unidimensional reporting and analyses and highlights the ways that race and gender intersect to shape COVID-19 outcomes.

COVID-19 vaccination, incidence, and mortality rates among individuals with mental disorders in South Korea: A nationwide retrospective study.

2020 Rise to the challenge

Structural Racism as a Contributor to Lung Cancer Incidence and Mortality Rates Among Black Populations in the United States.

A range of health-related and behavioral risk factors are associated with COVID-19 incidence and mortality. In the present study, we assess the association between incidence, mortality, and case fatality rate due to COVID-19 and the prevalence of hypertension, obesity, overweight, tobacco and alcohol use in the Peruvian population aged ≥15 years during the first and second year of the COVID-19 pandemic. In this ecological study, we used the prevalence rates of hypertension, overweight, obesity, tobacco, and alcohol use obtained from the Encuesta Demográfica y de Salud Familiar (ENDES) 2020 and 2021. We estimated the crude incidence and mortality rates (per 100,000 habitants) and case fatality rate (%) of COVID-19 in 25 Peruvian regions using data from the Peruvian Ministry of Health that were accurate as of 31 December 2021. Spearman correlation and lineal regression analysis was applied to assess the correlations between the study variables as well as multivariable regression analysis adjusted by confounding factors affecting the incidence and mortality rate and case fatality rate of COVID-19. In 2020, adjusted by confounding factors, the prevalence rate of obesity (β = 0.582; p = 0.037) was found to be associated with the COVID-19 mortality rate (per 100,000 habitants). There was also an association between obesity and the COVID-19 case fatality rate (β = 0.993; p = 0.014). In 2021, the prevalence of obesity was also found to be associated with the COVID-19 mortality rate (β = 0.713; p = 0.028); however, adjusted by confounding factors, including COVID-19 vaccination coverage rates, no association was found between the obesity prevalence and the COVID-19 mortality rate (β = 0.031; p = 0.895). In summary, Peruvian regions with higher obesity prevalence rates had higher COVID-19 mortality and case fatality rates during the first year of the COVID-19 pandemic. However, adjusted by the COVID-19 vaccination coverage, no association between the obesity prevalence rate and the COVID-19 mortality rate was found during the second year of the COVID-19 pandemic.

Disparities in Cirrhosis Management of Black Patients: Do We Know What to Address?

Racism Is a Modifiable Risk Factor: Relationships Among Race, Ethnicity, and Colorectal Cancer Outcomes

IntroductionWhile the increased burden of COVID-19 among the Black population has been recognized, most attempts to quantify the extent of this racial disparity have not taken the age distribution of the population into account. In this paper, we determine the Black–White disparity in COVID-19 mortality rates across 35 states using direct age standardization. We then explore the relationship between structural racism and differences in the magnitude of this disparity across states.MethodsUsing data from the Centers for Disease Control and Prevention, we calculated both crude and age-adjusted COVID-19 mortality rates for the non-Hispanic White and non-Hispanic Black populations in each state. We explored the relationship between a state-level structural racism index and the observed differences in the racial disparities in COVID-19 mortality across states. We explored the potential mediating effects of disparities in exposure based on occupation, underlying medical conditions, and health care access.ResultsRelying upon crude death rate ratios resulted in a substantial underestimation of the true magnitude of the Black–White disparity in COVID-19 mortality rates. The structural racism index was a robust predictor of the observed racial disparities. Each standard deviation increase in the racism index was associated with an increase of 0.26 in the ratio of COVID-19 mortality rates among the Black compared to the White population.ConclusionsStructural racism should be considered a root cause of the Black–White disparity in COVID-19 mortality. Dismantling the long-standing systems of racial oppression is critical to adequately address both the downstream and upstream causes of racial inequities in the disease burden of COVID-19.

We aim to assess how COVID-19 infection and mortality varied according to facility size in 965 long-term care homes (LTCHs) in Catalonia during March and April 2020. We measured LTCH size by the number of authorised beds. Outcomes were COVID-19 infection (at least one COVID-19 case in an LTCH) and COVID-19 mortality. Risks of these were estimated with logistic regression and hurdle models. Models were adjusted for county COVID-19 incidence and population, and LTCH types. Sixty-five per cent of the LTCHs were infected by COVID-19. We found a strong association between COVID-19 infection and LTCH size in the adjusted analysis (from 45% in 10-bed homes to 97.5% in those with over 150 places). The average COVID-19 mortality in all LTCHs was 6.8% (3887 deaths) and 9.2% among the COVID-19-infected LTCHs. Very small and large homes had higher COVID-19 mortality, whereas LTCHs with 30 to 70 places had the lowest level. COVID-19 mortality sharply increased with LTCH size in counties with a cumulative incidence of COVID-19 which was higher than 250/100,000, except for very small homes, but slightly decreased with LTCH size when the cumulative incidence of COVID-19 was lower. To prevent infection and preserve life, the optimal size of an LTCH should be between 30 and 70 places.

BackgroundHousing characteristics and neighbourhood context are considered risk factors for COVID-19 mortality among older adults. The aim of this study was to investigate how individual-level housing and neighbourhood characteristics are associated with COVID-19 mortality in older adults.MethodsFor this population-based, observational study, we used data from the cause-of-death register held by the Swedish National Board of Health and Welfare to identify recorded COVID-19 mortality and mortality from other causes among individuals (aged ≥70 years) in Stockholm county, Sweden, between March 12 and May 8, 2020. This information was linked to population-register data from December, 2019, including socioeconomic, demographic, and residential characteristics. We ran Cox proportional hazards regressions for the risk of dying from COVID-19 and from all other causes. The independent variables were area (m2) per individual in the household, the age structure of the household, type of housing, confirmed cases of COVID-19 in the borough, and neighbourhood population density. All models were adjusted for individual age, sex, country of birth, income, and education.FindingsOf 279 961 individuals identified to be aged 70 years or older on March 12, 2020, and residing in Stockholm in December, 2019, 274 712 met the eligibility criteria and were included in the study population. Between March 12 and May 8, 2020, 3386 deaths occurred, of which 1301 were reported as COVID-19 deaths. In fully adjusted models, household and neighbourhood characteristics were independently associated with COVID-19 mortality among older adults. Compared with living in a household with individuals aged 66 years or older, living with someone of working age (<66 years) was associated with increased COVID-19 mortality (hazard ratio 1·6; 95% CI 1·3–2·0). Living in a care home was associated with an increased risk of COVID-19 mortality (4·1; 3·5–4·9) compared with living in independent housing. Living in neighbourhoods with the highest population density (≥5000 individuals per km2) was associated with higher COVID-19 mortality (1·7; 1·1–2·4) compared with living in the least densely populated neighbourhoods (0 to <150 individuals per km2).InterpretationClose exposure to working-age household members and neighbours is associated with increased COVID-19 mortality among older adults. Similarly, living in a care home is associated with increased mortality, potentially through exposure to visitors and care workers, but also due to poor underlying health among care-home residents. These factors should be considered when developing strategies to protect this group.FundingSwedish Research Council for Health, Working Life and Welfare (FORTE), Swedish Foundation for Humanities and Social Sciences.

In their study, Shiels and colleagues sought to capture racial and ethnic disparities in excess COVID-19 and non–COVID-19 deaths between March and December 2020. The editorialists discuss the findings and the actions needed to reverse the observed disparities.

The purpose of this study was to examine the relationship between social vulnerability and COVID-19 mortality rates during the whole outbreak in U.S. counties. COVID-19 deaths were gleaned from the USA Facts. Independent variables were gleaned from the CDC’s Social Vulnerability Index. Spatial autoregressive models were used for data analysis. Results show that counties with more social vulnerability (socioeconomic) were positively associated with higher COVID-19 mortality rates. Counties with more social vulnerability (household composition & disability) were positively associated with higher COVID-19 mortality rates. Counties with more social vulnerability (minority status & language) were negatively associated with higher COVID-19 mortality rates. Counties with more social vulnerability (housing type & transportation) were negatively associated with higher COVID-19 mortality rates. In conclusion, county-level social vulnerability provides an useful framework for identifying unequal distribution of deaths from COVID-19 in the United States.