Socioeconomic and Racial Segregation and COVID-19: Concentrated Disadvantage and Black Concentration in Association with COVID-19 Deaths in the USA

Racial Composition of Social Environments Over the Life Course Using the Pictorial Racial Composition Measure: Development and Validation Study

BACKGROUND

Studies investigating the impact of racial segregation on health have reported mixed findings and tended to focus on the racial composition of neighborhoods. These studies use varying racial composition measures, such as census data or investigator-adapted questions, which are currently limited to assessing one dimension of neighborhood racial composition.

OBJECTIVE

This study aims to develop and validate a novel racial segregation measure, the Pictorial Racial Composition Measure (PRCM).

METHODS

The PRCM is a 10-item questionnaire of pictures representing social environments across adolescence and adulthood: neighborhoods and blocks (adolescent and current), schools and classrooms (junior high and high school), workplace, and place of worship. Cognitive interviews (n=13) and surveys (N=549) were administered to medically underserved patients at a primary care clinic at the Barnes-Jewish Hospital. Development of the PRCM occurred across pilot and main phases. For each social environment and survey phase (pilot and main), we computed positive versus negative pairwise comparisons: mostly Black versus all other categories, half Black versus all other categories, and mostly White versus all other categories. We calculated the following validity metrics for each pairwise comparison: sensitivity, specificity, correct classification rate, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, false positive rate, and false negative rate.

RESULTS

For each social environment, the mostly Black and mostly White dichotomizations generated better validity metrics relative to the half Black dichotomization. Across all 10 social environments in the pilot and main phases, mostly Black and mostly White dichotomizations exhibited a moderate-to-high sensitivity, specificity, correct classification rate, positive predictive value, and negative predictive value. The positive likelihood ratio values were >1, and the negative likelihood ratio values were close to 0. The false positive and negative rates were low to moderate.

CONCLUSIONS

These findings support that using either the mostly Black versus other categories or the mostly White versus other categories dichotomizations may provide accurate and reliable measures of racial composition across the 10 social environments. The PRCM can serve as a uniform measure across disciplines, capture multiple social environments over the life course, and be administered during one study visit. The PRCM also provides an added window into understanding how structural racism has impacted minoritized communities and may inform equitable intervention and prevention efforts to improve lives.

Still Separate, Still Not Equal: An Ecological Examination of Redlining and Racial Segregation with COVID-19 Vaccination Administration in Washington D.C

Racial residential segregation has been deemed a fundamental cause of health inequities. It is a result of historical and contemporary policies such as redlining that have created a geographic separation of races and corresponds with an inequitable distribution of health-promoting resources. Redlining and racial residential segregation may have contributed to racial inequities in COVID-19 vaccine administration in the early stages of public accessibility. We use data from the National Archives (historical redlining), Home Mortgage Disclosure Act (contemporary redlining), American Community Survey from 1940 (historical racial residential segregation) and 2015-2019 (contemporary racial residential segregation), and Washington D.C. government (COVID-19 vaccination administration) to assess the relationships between redlining, racial residential segregation, and COVID-19 vaccine administration during the early stages of vaccine distribution when a tiered system was in place due to limited supply. Pearson correlation was used to assess whether redlining and racial segregation, measured both historically and contemporarily, were correlated with each other in Washington D.C. Subsequently, linear regression was used to assess whether each of these measures associate with COVID-19 vaccine administration. In both historical and contemporary analyses, there was a positive correlation between redlining and racial residential segregation. Further, redlining and racial residential segregation were each positively associated with administration of the novel COVID-19 vaccine. This study highlights the ongoing ways in which redlining and segregation contribute to racial health inequities. Eliminating racial health inequities in American society requires addressing the root causes that affect access to health-promoting resources.

Gender-Based Socio-Economic Inequalities in the Pre-Vaccination Era of the COVID-19 Pandemic in Istanbul: A Neighborhood-Level Analysis of Excess Mortality

Worldwide excess mortality (EM) data have the potential to provide a better estimation of the impact of the pandemic. This study aims to investigate and map the inequalities in EM in Istanbul during the pre-vaccination era of the COVID-19 pandemic in 2020 and its association with selected demographic and socio-economic variables at the neighborhood level according to gender. This ecological study was conducted with the EM data of Istanbul. The EM data were obtained from the Istanbul Metropolitan Municipality (IMM) and analyzed according to socio-demographic indicators (gender, age), neighborhood-level indicators (population density, educational attainment) and neighborhood vulnerability (socio-economic and transportation) for the 808 neighborhoods, then presented separately according to gender to examine gender-specific factors. Socio-economic and transportation vulnerability indexes are provided the IMM. The excess mortality rate per 1000 (EMR) in 2020 has been calculated by using the number of deaths in the years 2018-2019. We have mapped EMRs of each neighborhood and used linear regression analysis in three datasets to examine gender specific factors. EMRs in Istanbul showed two peaks one in April and one in November. Male EMRs were higher compared to females in Istanbul during the pre-vaccination era of the pandemic. Higher EMRs were observed in neighborhoods with a higher share of 50+ year old age groups and higher neighborhood socio-economic vulnerability scores. Neighborhood socio-economic vulnerability was significantly associated with EMRs in males but not in females. Unequal distribution of EM between neighborhoods underlines the need for gender-specific pandemic measures to alleviate the burden of the COVID-19 pandemic, especially in socio-economically vulnerable settings. Increased use of area-based indicators with a gender perspective can enhance pandemic measures.

Food insecurity in urban American Indian and Alaska Native populations during the COVID-19 pandemic

BACKGROUND

Food insecurity is an important social determinant of health that was exacerbated by the COVID-19 pandemic. Both food insecurity and COVID-19 infection disproportionately affect racial and ethnic minority groups, particularly American Indian and Alaska Native communities; however, there is little evidence as to whether food insecurity is associated with COVID-19 infection or COVID-19 preventive behaviors such as vaccination uptake. The purpose of this study was to evaluate associations between food insecurity, COVID-19 infection, and vaccination status among urban American Indian and Alaska Native adults seen at 5 clinics serving urban Native people.

METHODS

In partnership with health organizations in Alaska, Colorado, Kansas, Minnesota, and New Mexico, the study team conducted a cross-sectional survey in 2021 to assess food security status and attitudes, barriers, and facilitators for COVID-19 testing and vaccination. Logistic regression was used to examine the association of food security status with sociodemographic factors and COVID-19 infection and vaccination status. Marginal standardization was applied to present results as prevalence differences.

RESULTS

Among 730 American Indian and Alaska Native adults, the prevalence of food insecurity measured during the pandemic was 38%. For participants who reported persistent food security status before and during the pandemic (n = 588), the prevalence of food insecurity was 25%. Prevalence of COVID-19 infection and vaccination did not vary by food security status after adjustment for confounders.

CONCLUSIONS

High rates of food insecurity among American Indian and Alaska Native communities likely increased during the COVID-19 pandemic. However, despite the high prevalence of food insecurity, community-led efforts to reduce COVID-19 infection and increase vaccination uptake across Indian Health Service and Tribal healthcare facilities may have mitigated the negative impacts of the pandemic for families experiencing food insecurity. These successful approaches serve as an important reference for future public health efforts that require innovative strategies to improve overall health in American Indian and Alaska Native communities.

Racial Disparities in Occupational Distribution Among Black and White Adults with Similar Educational Levels: Analysis of Middle-Aged and Older Individuals in the Health and Retirement Study

Background

Occupational classes play a significant role in influencing both individual and population health, serving as a vital conduit through which higher education can lead to better health outcomes. However, the pathway from education to corresponding occupational classes does not apply uniformly across different racial and ethnic groups, hindered by factors such as social stratification, labor market discrimination, and job segregation.

Aims

This study seeks to investigate the relationship between educational attainment and occupational classes among Black, Latino, and White middle-aged and older adults, with a focus on their transition into retirement.

Methods

Using cross-sectional data from the Health and Retirement Study (HRS), this research examines the impact of race/ethnicity, educational attainment, occupational classes, and timing of retirement among middle-aged and older adults. The analysis includes a sample of 7,096 individuals identified as White, Black, or Latino. Through logistic regression, we assess the additive and multiplicative effects of race/ethnicity and education on six defined occupational classes: 1. Managerial and specialty operations, 2. Professional Specialty, 3. Sales, 4. Clerical/administrative support, 5. Services, and 6. Manual labor.

Results

Participants were Black (n = 1,143) or White (n =5,953). This included Latino (N =459) or non-Latino (n = 6,634). Our analysis reveals a skewed distribution of Black and Latino adults in manual and service occupations, in stark contrast to White adults who were more commonly found in clerical/administrative and managerial positions. Educational attainment did not equate to similar occupational outcomes across racial groups. Key findings include: Firstly, Black individuals with a college degree or higher were less likely to occupy clerical and administrative positions compared to their White counterparts. Secondly, holding a General Educational Development (GED) credential or some college education was generally linked to reduced likelihood of being in managerial roles; however, this inverse relationship was less evident among Black middle-aged and older adults than White ones. Thirdly, having a GED reduced the chances of working in sales roles, while having a college degree increased such chances. An interaction between race and some college education revealed that the impact of some college education on sales roles was more significant for Black adults than for White ones. We did not observe any interaction between ethnicity (Latino) and educational attainment on occupational classes. Given the stability of occupational classes, these findings could also apply to the last occupation held prior to retirement.

Conclusion

This study highlights significant racial disparities in occupational classes among individuals with comparable levels of education, underscoring the profound implications for health and wellbeing disparities. Future research should explore strategies to alleviate labor market discrimination and job segregation as ways to close these occupational gaps. Additionally, the influence of social stratification, job segregation, and historical legacies, such as the repercussions of the Jim Crow era, on these disparities merits further investigation. Addressing these issues is crucial for enhancing the health and wellbeing of all populations.

Neighborhood Factors Associated with COVID-19 Cases in California

BACKGROUND

There is a need to assess neighborhood-level factors driving COVID-19 disparities across racial and ethnic groups.

OBJECTIVE

To use census tract-level data to investigate neighborhood-level factors contributing to racial and ethnic group-specific COVID-19 case rates in California.

DESIGN

Quasi-Poisson generalized linear models were used to identify neighborhood-level factors associated with COVID-19 cases. In separate sequential models for Hispanic, Black, and Asian, we characterized the associations between neighborhood factors on neighborhood COVID-19 cases. Subanalyses were conducted on neighborhoods with majority Hispanic, Black, and Asian residents to identify factors that might be unique to these neighborhoods. Geographically weighted regression using a quasi-Poisson model was conducted to identify regional differences.

MAIN MEASURES

All COVID-19 cases and tests reported through January 31, 2021, to the California Department of Public Health. Neighborhood-level data from census tracts were obtained from American Community Survey 5-year estimates (2015-2019), United States Census (2010), and United States Department of Housing and Urban Development.

KEY RESULTS

The neighborhood factors associated with COVID-19 case rate were racial and ethnic composition, age, limited English proficiency (LEP), income, household size, and population density. LEP had the largest influence on the positive association between proportion of Hispanic residents and COVID-19 cases (- 2.1% change). This was also true for proportion of Asian residents (- 1.8% change), but not for the proportion of Black residents (- 0.1% change). The influence of LEP was strongest in areas of the Bay Area, Los Angeles, and San Diego.

CONCLUSION

Neighborhood-level contextual drivers of COVID-19 burden differ across racial and ethnic groups.

Racial Capitalism and Neighborhood Health Disparities: the COVID-19 in California Counties

PURPOSE

This article explores the association between racial capitalism and neighborhood-level health disparities, with a particular focus on COVID-19 in California.

METHODS

This article investigates COVID-19 incidence in 58 California counties. To account for racial capitalism, the study looks at the per capita incomes ratios (1) between whites and Blacks and (2) between whites and Hispanics. Other county-level neighborhood characteristics were controlled.

RESULTS

Findings from spatial autoregressive models indicate that increases in white-Black and white-Hispanic income disadvantages lead to an increase in COVID-19 incidence in 58 California counties. Findings also reveal that the disadvantage that results from the white-Black income ratio in COVID-19 spread decreases in counties that report high levels of income inequality between whites and Hispanics.

DISCUSSION

Findings indicate that a greater income disadvantage for racial minorities is connected to a more COVID-19 incidence. With regard to racial demographics in California, the interaction effect between measures for racial income disadvantages is discussed.

Association Between Racial Segregation and COVID-19 Vaccination Rates

OBJECTIVE

To examine the association between county-level Black-White residential segregation and COVID-19 vaccination rates.

DESIGN

Observational cross-sectional study using multivariable generalized linear models with state fixed effects to estimate the average marginal effects of segregation on vaccination rates.

SETTING

National analysis of county-level vaccination rates.

MAIN OUTCOME MEASURE

County-level vaccination rates across the United States.

RESULTS

We found an overall positive association between county-level segregation and the proportion population fully vaccinated, with a 6.8, 11.3, and 12.8 percentage point increase in the proportion fully vaccinated by May 3, September 27, and December 6, 2021, respectively. Effects were muted after adjustment for sociodemographic variables. Furthermore, in analyses including an interaction term between the county proportion of Black residents and the county dissimilarity index, the association between segregation and vaccination is positive in counties with a lower proportion of Black residents (ie, 5%) but negative in counties with the highest proportions of Black residents (ie, 70%).

CONCLUSIONS

Findings highlight the importance of methodological decisions when modeling disparities in COVID-19 vaccinations. Researchers should consider mediating and moderating factors and examine interaction effects and stratified analyses taking racial group distributions into account. Results can inform policies around the prioritization of vaccine distribution and outreach.

COVID-19 challenges, responses, and resilience among rural Black women: a study protocol

Despite the aggregated burdens and challenges experienced by rural Black women during the COVID-19 pandemic, many likely also demonstrated strength and resilience to overcome challenges. A mixed methodology and a community-based participatory approach will be used to collect multilevel data on challenges, responses, resilience, and lessons during the pandemic from Black women, community health workers, and community leaders in rural areas in South Carolina (SC). Specifically, the unique circumstances and lived experiences of rural Black women during the COVID-19 pandemic will be documented to understand their needs regarding effective management of social, physical, and mental health challenges through focus group discussions and in-depth interviews with Black women, community health workers, and local community leaders recruited from rural SC communities. Barriers, facilitators, and potential impacts of multilevel resilience development will be identified through a survey administered among rural Black women recruited from 11 rural counties (with one as site for a pilot testing of the questionnaire). A report for public health practice will be developed, including recommended strategies to optimize health systems' emergency preparedness and responses through triangulation of qualitative and quantitative data from multiple sources. Findings in the proposed study will provide valuable references in terms of addressing social determinants of health factor challenges during the pandemic, fostering resilience, and informing evidence-based decision-making for policymakers. The study will contribute to the development of public health emergency preparedness plans, which can promote the resilience of women, their families, and local communities as well as optimize effective preparedness and response of health systems for rural Black women and their families during infectious disease outbreaks and other public health emergencies.

County-Level Segregation and Racial Disparities in COVID-19 Outcomes

CONTEXT

Segregation has been linked to unequal life chances. Individuals from marginalized communities experience more crime, higher levels of poverty, poorer health, and less civic engagement. In addition, segregated metropolitan regions have been found to display inequality in access to basic services. This article builds on these findings by linking segregation to infection and deaths from COVID-19.

METHODS

Using census data matched to COVID infection and death statistics at the county level, this article offers a theoretical basis for the researchers' choice of segregation measures and predictions for different racial groups. It analyzes the relationship between two dimensions of segregation-racial isolation and racial unevenness-and COVID outcomes for different racial and ethnic groups.

FINDINGS

In counties where Black and Latino residents lived in more racially isolated neighborhoods, they were much more likely to contract COVID-19. This pattern was exacerbated in counties with a high proportion of frontline workers. In addition, racial segregation increased COVID-19 death rates for Black, Latino, and white residents.

CONCLUSIONS

These findings suggest that devastating outcomes of the coronavirus pandemic were linked to a long history of racial marginalization and entrenched discrimination produced by structural inequalities embedded in our geographies. This knowledge should be used to inform public health planning.

Understanding mobility change in response to COVID-19: A Los Angeles case study

The COVID-19 pandemic has affected people's lives throughout the world. Governments have imposed restrictions on business and social activities to reduce the spread of the virus. In the US, the pandemic response has been largely left to state and local governments, resulting in a patchwork of policies that frequently changed. We examine travel behavior across income and race/ethnic groups in Los Angeles County over several stages of the pandemic. We use a difference-in-difference model based on mobile device data to compare mobility patterns before and during the various stages of the pandemic. We find a strong relationship between income/ethnicity and mobility. Residents of low-income and ethnic minority neighborhoods reduced travel less than residents of middle- and high-income neighborhoods during the shelter-in-place order, consistent with having to travel for work or other essential purposes. As public health rules were relaxed and COVID vaccines became available, residents of high-income and White neighborhoods increased travel more than other groups, suggesting more discretionary travel. Our trip purpose model results show that residents of low-income and ethnic minority neighborhoods reduced work and shopping travel less than those of White and high-income neighborhoods during the shelter-in-place order. Results are consistent with higher-income workers more likely being able to work at home than lower-income workers. In contrast, low-income/minorities apparently have more constraints associated with work or household care. The consequence is less capacity to avoid virus risk. Race and socioeconomic disparities are revealed in mobility patterns observed during the COVID-19 pandemic.

The Impact of COVID-19 on Education Experiences of High School Students in Semi-Rural Georgia

BACKGROUND

This study examines the consequences of COVID-19 pandemic on academic and career concerns of high school students; relationship between attendance and grades with educational concerns; and association between student perception of the pandemic and decision to attend school virtually or in-person.

METHODS

Diverse students in grades 9-12 from two public high schools in semi-rural Georgia (n = 666) completed a survey shortly after school closures. Survey results were linked to academic and demographic data. Analyses were examined for differences by demographic and education measures.

RESULTS

Overall, 60% expressed academic worry and reported obstacles to virtual learning. Hispanic students expressed more worry and less confidence while black students reported less worry than peers. Females indicated more worry than males. Grade 12 students reported greater academic and career worry than younger students. Students eligible for free and reduced lunch expressed more worry and obstacles than peers. Non-honors and low-attendance students reported more worry about grades and graduation than their counterparts.

CONCLUSIONS

Results can inform targeted multi-level interventions to reduce the pandemic's effects on learning and ensure healthy trajectories for development across demographics. Stakeholders must take proactive measures to recover from academic loss to ensure our youth's healthy development.

Political Economy of the COVID-19 Pandemic: How State Policies Shape County-Level Disparities in COVID-19 Deaths

The authors examine how two state-level coronavirus disease 2019 (COVID-19) policy indices (one capturing economic support and one capturing stringency measures such as stay-at-home orders) were associated with county-level COVID-19 mortality from April through December 2020 and whether the policies were more beneficial for certain counties. Using multilevel negative binominal regression models, the authors found that high scores on both policy indices were associated with lower county-level COVID-19 mortality. However, the policies appeared to be most beneficial for counties with fewer physicians and larger shares of older adults, low-educated residents, and Trump voters. They appeared to be less effective in counties with larger shares of non-Hispanic Black and Hispanic residents. These findings underscore the importance of examining how state and local factors jointly shape COVID-19 mortality and indicate that the unequal benefits of pandemic policies may have contributed to county-level disparities in COVID-19 mortality.

Effects of the Affordable Care Act Medicaid Expansions on Mental Health During the COVID-19 Pandemic in 2020-2021

To examine whether previous Affordable Care Act (ACA) Medicaid expansions had an added effect on the mental health of low-income adults during the COVID-19 pandemic in 2020 and 2021. We use the 2017-2021 Behavioral Risk Factor Surveillance System (BRFSS) data. We use an event study difference-in-differences model to compare the number of days in poor mental health in the past 30 days and the likelihood of frequent mental distress among 18 to 64 year old individuals with household incomes below 100% of the federal poverty level who participated in BRFSS in one of the surveys from 2017 to 2021 and who resided in states that expanded Medicaid by 2016 or states that had not expanded by 2021. We also examine the heterogeneity of the expansion effects across subpopulation groups. We find some evidence that the Medicaid expansion was associated with better mental health during the pandemic for adults younger than 45, females, and non-Hispanic Black and other non-Hispanic non-White individuals. There is some evidence of an added benefit to mental health from Medicaid expansion status during the pandemic for some subgroups among low-income adults, suggesting potential health benefits from Medicaid eligibility during public health and economic crises.

Increased COVID-19 Infection Risk Drives Racial and Ethnic Disparities in Severe COVID-19 Outcomes

COVID-19 inequities have been well-documented. We evaluated whether higher rates of severe COVID-19 in racial and ethnic minority groups were driven by higher infection rates by evaluating if disparities remained when analyses were restricted to people with infection. We conducted a retrospective cohort study of adults insured through Kaiser Permanente (Colorado, Northwest, Washington), follow-up in March-September 2020. Laboratory results and hospitalization diagnosis codes identified individuals with COVID-19. Severe COVID-19 was defined as invasive mechanical ventilation or mortality. Self-reported race and ethnicity, demographics, and medical comorbidities were extracted from health records. Modified Poisson regression estimated adjusted relative risks (aRRs) of severe COVID-19 in full cohort and among individuals with infection. Our cohort included 1,052,774 individuals, representing diverse racial and ethnic minority groups (e.g., 68,887 Asian, 41,243 Black/African American, 93,580 Hispanic or Latino/a individuals). Among 7,399 infections, 442 individuals experienced severe COVID-19. In the full cohort, severe COVID-19 aRRs for Asian, Black/African American, and Hispanic individuals were 2.09 (95% CI: 1.36, 3.21), 2.02 (1.39, 2.93), and 2.09 (1.57, 2.78), respectively, compared to non-Hispanic Whites. In analyses restricted to individuals with COVID-19, all aRRs were near 1, except among Asian Americans (aRR 1.82 [1.23, 2.68]). These results indicate increased incidence of severe COVID-19 among Black/African American and Hispanic individuals is due to higher infection rates, not increased susceptibility to progression. COVID-19 disparities most likely result from social, not biological, factors. Future work should explore reasons for increased severe COVID-19 risk among Asian Americans. Our findings highlight the importance of equity in vaccine distribution.

Investigating the relationships between concentrated disadvantage, place connectivity, and COVID-19 fatality in the United States over time

BACKGROUND

Concentrated disadvantaged areas have been disproportionately affected by COVID-19 outbreak in the United States (US). Meanwhile, highly connected areas may contribute to higher human movement, leading to higher COVID-19 cases and deaths. This study examined the associations between concentrated disadvantage, place connectivity, and COVID-19 fatality in the US over time.

METHODS

Concentrated disadvantage was assessed based on the spatial concentration of residents with low socioeconomic status. Place connectivity was defined as the normalized number of shared Twitter users between the county and all other counties in the contiguous US in a year (Y = 2019). COVID-19 fatality was measured as the cumulative COVID-19 deaths divided by the cumulative COVID-19 cases. Using county-level (N = 3,091) COVID-19 fatality over four time periods (up to October 31, 2021), we performed mixed-effect negative binomial regressions to examine the association between concentrated disadvantage, place connectivity, and COVID-19 fatality, considering potential state-level variations. The moderation effects of county-level place connectivity and concentrated disadvantage were analyzed. Spatially lagged variables of COVID-19 fatality were added to the models to control for the effect of spatial autocorrelations in COVID-19 fatality.

RESULTS

Concentrated disadvantage was significantly associated with an increased COVID-19 fatality in four time periods (p < 0.01). More importantly, moderation analysis suggested that place connectivity significantly exacerbated the harmful effect of concentrated disadvantage on COVID-19 fatality in three periods (p < 0.01), and this significant moderation effect increased over time. The moderation effects were also significant when using place connectivity data from the previous year.

CONCLUSIONS

Populations living in counties with both high concentrated disadvantage and high place connectivity may be at risk of a higher COVID-19 fatality. Greater COVID-19 fatality that occurs in concentrated disadvantaged counties may be partially due to higher human movement through place connectivity. In response to COVID-19 and other future infectious disease outbreaks, policymakers are encouraged to take advantage of historical disadvantage and place connectivity data in epidemic monitoring and surveillance of the disadvantaged areas that are highly connected, as well as targeting vulnerable populations and communities for additional intervention.

COVID-19 mortality and deprivation: pandemic, syndemic, and endemic health inequalities

COVID-19 has exacerbated endemic health inequalities resulting in a syndemic pandemic of higher mortality and morbidity rates among the most socially disadvantaged. We did a scoping review to identify and synthesise published evidence on geographical inequalities in COVID-19 mortality rates globally. We included peer-reviewed studies, from any country, written in English that showed any area-level (eg, neighbourhood, town, city, municipality, or region) inequalities in mortality by socioeconomic deprivation (ie, measured via indices of multiple deprivation: the percentage of people living in poverty or proxy factors including the Gini coefficient, employment rates, or housing tenure). 95 papers from five WHO global regions were included in the final synthesis. A large majority of the studies (n=86) found that COVID-19 mortality rates were higher in areas of socioeconomic disadvantage than in affluent areas. The subsequent discussion reflects on how the unequal nature of the pandemic has resulted from a syndemic of COVID-19 and endemic inequalities in chronic disease burden.

Race, ethnicity and mortality in the United States during the first year of the COVID-19 pandemic: an assessment

The fact that a disproportionate share of the disease burden from COVID-19, including mortality, has been borne by racial and ethnic minority communities is well documented. The purpose of this paper is to reassess the "race/ethnicity effect" in COVID-19 mortality in the United States. Using an ecological regression framework and county-level data, the study aims to make two contributions. First, it estimates the race/ethnicity effect for all major racial/ethnic groups at four important junctures during the first year of the pandemic. In doing so, it seeks to provide the fullest possible picture of the nature and evolution of the race/ethnicity effect. Second, it estimates the race/ethnicity effect net of basic socioeconomic factors (SEF). This helps to identify the likely mechanisms through which the race/ethnicity effect operates. Racial/ethnic composition is flexibly measured in two ways-by percentage contributions to county population and by indicators of group plurality. The ecological regressions revealed a positive association between the size of three racial/ethnic groups-non-Hispanic Blacks, non-Hispanic American Indian and Alaskan Natives (AIAN) and Hispanics-and county mortality, although the association was stronger and more consistent for Blacks and AIANs. Furthermore, accounting for basic SEF had different impacts on the race/ethnicity-mortality association for the three groups. For Hispanics, it was almost fully mediated. For Blacks, it decreased but remained statistically significant [62-6% higher mortality associated with a 1-standard deviation increase in Black share of county population; 2.3-1.1 times higher mortality in the average Black plurality county]. For AIANs, it was largely unaffected or even increased [44-10% higher mortality associated with a 1-standard deviation increase in AIAN share; 6.2-1.8 times higher mortality in AIAN plurality county). For all groups, the race/ethnicity effect generally decreased as the pandemic wore on during the first year.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44155-022-00019-9.

Racial concentration and dynamics of COVID-19 vaccination in the United States

This article considers how county-level concentrations of Asians, Blacks, Hispanics, and Whites are associated with COVID-19 vaccination differently. I argue that racially specific mechanisms-differential concentrations of social vulnerability and political ideology by race-are likely to create diverse associations between racial concentration and COVID-19 vaccination not only across racial groups but also within racial groups over time from early rollout to the time after COVID-19 vaccines became widely available. I test this argument by drawing on data from multiple sources that include county-level information on COVID-19 vaccination rates, racial population make-ups, and measures of political ideology and community vulnerability. Results show that the association between racial concentration and COVID-19 vaccination changes substantially across and within racial groups over time. Counties with higher percent of Asians and percent of Whites have higher vaccination rates at earlier time intervals whereas counties with higher percent of Latinos and percent of Blacks show lower vaccination rates. This trend flips at later dates for percent of Blacks, percent of Latinos, and percent of Whites. Results from multilevel regression models and mediation analysis controlling for vaccine hesitancy show that social vulnerability and political ideology are the underlying factors and their differential associations with diverse racial concentrations help create the racially specific and time-varying patterns.

Racial Disparities in COVID-19 Case Positivity and Social Context: The Role of Housing, Neighborhood, and Health Insurance

Research on racial-ethnic COVID-19 disparities has yet to employ housing variables measured at the individual level, limiting our understanding of housing's role in determining early exposure to the virus. To address this gap, we linked data from SARS-CoV-2 polymerase chain reaction (PCR) tests within the Duke University Health System between March 12, 2020, and July 31, 2020 (N = 23,057 individuals), with housing parcel data. We then analyzed how housing, neighborhood, and health insurance explain disparities in case positivity between and within racial-ethnic groups in Durham County, North Carolina. We find that 55% of the Black-White disparity and 25% of the Hispanic-White disparity in positive cases are explained by these social-contextual variables. Neighborhood-fixed effects explained the largest portion (27%) of the Black-White disparity, whereas health insurance type explained the largest portion (14%) of the Hispanic-White disparity. We conclude that housing, neighborhood, and health insurance had a significant role in producing racial-ethnic disparities in COVID-19 case positivity.

Older Adults' Preventive Behaviors During COVID-19 Outbreak: Application of Multiple Disadvantage Model

This study explored older adults' preventive behaviors during the pandemic. A sample of 2982 community-dwelling older adults was extracted from the United States National Health and Aging Trends Study. Results showed that number of preventive behaviors was decreased with rundown neighborhood and age; but increased with Blacks, Hispanics, other ethnic minorities, income, female, number of persons in household, social cohesion, social network, family/peer support, severity of COVID-19 symptoms, and anxiety during COVID-19 outbreak. The study results imply that joint effort of government and ethnic minority advocacy groups in public health education should focus on preventive measures as well as racial disparities in health, and that rejuvenating rundown neighborhoods, promoting neighboring, providing stimulus checks and unemployment insurance, and maintaining connection with family and friends will promote preventive behaviors.

Aggravated social segregation during the COVID-19 pandemic: Evidence from crowdsourced mobility data in twelve most populated U.S. metropolitan areas

The notion of social segregation refers to the degrees of separation between socially different population groups. Many studies have examined spatial and residential separations among different socioeconomic or racial populations. However, with the advancement of transportation and communication technologies, people's activities and social interactions are no longer limited to their residential areas. Therefore, there is a growing necessity to investigate social segregation from a mobility perspective by analyzing people's mobility patterns. Taking advantage of crowdsourced mobility data derived from 45 million mobile devices, we innovatively quantify social segregation for the twelve most populated U.S. metropolitan statistical areas (MSAs). We analyze the mobility patterns between different communities within each MSA to assess their separations for two years. Meanwhile, we particularly explore the dynamics of social segregation impacted by the COVID-19 pandemic. The results demonstrate that New York and Washington D.C. are the most and least segregated MSA respectively among the twelve MSAs. Since the COVID-19 began, six of the twelve MSAs experienced a statistically significant increase in segregation. This study also shows that, within each MSA, the most and least vulnerable groups of communities are prone to interacting with their similar communities, indicating a higher degree of social segregation.

The Role of Poverty and Racial Discrimination in Exacerbating the Health Consequences of COVID-19

There were more than 800,000 confirmed coronavirus disease 2019 (COVID-19) deaths in the United States (U.S) by the end of 2021. The health consequences of COVID-19, however, have not affected all residents equally. In this review, we synthesize recent evidence suggesting that high levels of poverty in the U.S. compared to other high-income countries, as well as historic and ongoing racial/ethnic discrimination, have exacerbated the health consequences of COVID-19, particularly for racial/ethnic minorities. We discuss four mechanisms through which poverty and discrimination affect COVID-19-related health consequences: greater pre-existing health challenges, reduced access to healthcare, lower-quality neighbourhood and housing conditions, and unequal exposure to high-risk occupations. Evidence suggests that economic and policy institutions that contributed to higher pre-pandemic poverty rates in the U.S., particularly among racial/ethnic minorities, have been central determinants of unequal health outcomes during the COVID-19 pandemic.

Responding to Health Disparities in Behavioral Weight Loss Interventions and COVID-19 in Black Adults: Recommendations for Health Equity

COVID-19 has disproportionately impacted Black adults with high prevalence and mortality rates. Obesity is a central factor in the severity of COVID-19 and related treatment. Behavioral weight loss interventions are an efficacious treatment for obesity, but consistently, Black men and women are minimally represented, and weight loss outcomes are less than clinically significant thresholds. This commentary draws parallels between COVID-19 racial disparities, disparate obesity rates, weight loss treatment outcomes, and underlying systemic racial context. This paper also indicates paths forward to address racialized societal norms in obesity treatment to advance health equity in obesity and reduce acute disease vulnerability. Recommendations for behavioral medicine practice and policy include (1) expanding the research lens to prioritize Black scholars and institutions to generate innovative research questions, (2) creating trustworthy relationships with Black community members to bolster recruitment and retention, (3) employing qualitative methods to facilitate better intervention design and uncover influences of racialized social context, (4) centering Black adults in weight loss interventions, and (5) using multilevel approaches that integrate policy into interventions. Moving forward, this commentary aims to make plain the multilayered form and function of racism, its impact on COVID-19 and obesity, and offer pathways to improve behavioral weight loss interventions that can produce more equitable outcomes.

Estimating the effects of race and social vulnerability on hospital admission and mortality from COVID-19

Objective

To estimate the risk of hospital admission and mortality from COVID-19 to patients and measure the association of race and area-level social vulnerability with those outcomes.

Materials and Methods

Using patient records collected at a multisite hospital system from April 2020 to October 2020, the risk of hospital admission and the risk of mortality were estimated for patients who tested positive for COVID-19 and were admitted to the hospital for COVID-19, respectively, using generalized estimating equations while controlling for patient race, patient area-level social vulnerability, and time course of the pandemic.

Results

Black individuals were 3.57 as likely (95% CI, 3.18–4.00) to be hospitalized than White people, and patients living in the most disadvantaged areas were 2.61 times as likely (95% CI, 2.26–3.02) to be hospitalized than those living in the least disadvantaged areas. While Black patients had lower raw mortality than White patients, mortality was similar after controlling for comorbidities and social vulnerability.

Discussion

Our findings point to potent correlates of race and socioeconomic status, including resource distribution, employment, and shared living spaces, that may be associated with inequitable burden of disease across patients of different races.

Conclusions

Public health and policy interventions should address these social factors when responding to the next pandemic.

Using records from a hospital system spanning multiple sites and 2 states, we examined patients’ risk of hospital admission and death due to COVID-19 over the first 6 months of the pandemic. Specifically, we measured the association of race and social vulnerability with the likelihood of admission and death. Our statistical models showed that Black patients were 3.57 times more likely than White patients to be hospitalized. We also took into account how socially vulnerable a given US Census tract is, and when incorporating that into our models, we estimated that patients living in the most disadvantaged areas were 2.61 times as likely to be hospitalized as those living in the least disadvantaged areas. We found no difference in mortality by race when controlling for underlying conditions and social vulnerability. These findings suggest that public health and policy interventions should address such things as resource distribution, employment, and shared living spaces, and other social factors that may be associated with race, socioeconomic status, and the inequitable burden of disease across patients of different races.

Racial and Ethnic Disparities in Hospital Admissions from COVID-19: Determining the Impact of Neighborhood Deprivation and Primary Language

BACKGROUND

Despite past and ongoing efforts to achieve health equity in the USA, racial and ethnic disparities persist and appear to be exacerbated by COVID-19.

OBJECTIVE

Evaluate neighborhood-level deprivation and English language proficiency effect on disproportionate outcomes seen in racial and ethnic minorities diagnosed with COVID-19.

DESIGN

Retrospective cohort study SETTING: Health records of 12 Midwest hospitals and 60 clinics in Minnesota between March 4, 2020, and August 19, 2020 PATIENTS: Polymerase chain reaction-positive COVID-19 patients EXPOSURES: Area Deprivation Index (ADI) and primary language MAIN MEASURES: The primary outcome was COVID-19 severity, using hospitalization within 45 days of diagnosis as a marker of severity. Logistic and competing-risk regression models assessed the effects of neighborhood-level deprivation (using the ADI) and primary language. Within race, effects of ADI and primary language were measured using logistic regression.

RESULTS

A total of 5577 individuals infected with SARS-CoV-2 were included; 866 (n = 15.5%) were hospitalized within 45 days of diagnosis. Hospitalized patients were older (60.9 vs. 40.4 years, p < 0.001) and more likely to be male (n = 425 [49.1%] vs. 2049 [43.5%], p = 0.002). Of those requiring hospitalization, 43.9% (n = 381), 19.9% (n = 172), 18.6% (n = 161), and 11.8% (n = 102) were White, Black, Asian, and Hispanic, respectively. Independent of ADI, minority race/ethnicity was associated with COVID-19 severity: Hispanic patients (OR 3.8, 95% CI 2.72-5.30), Asians (OR 2.39, 95% CI 1.74-3.29), and Blacks (OR 1.50, 95% CI 1.15-1.94). ADI was not associated with hospitalization. Non-English-speaking (OR 1.91, 95% CI 1.51-2.43) significantly increased odds of hospital admission across and within minority groups.

CONCLUSIONS

Minority populations have increased odds of severe COVID-19 independent of neighborhood deprivation, a commonly suspected driver of disparate outcomes. Non-English-speaking accounts for differences across and within minority populations. These results support the ongoing need to determine the mechanisms that contribute to disparities during COVID-19 while also highlighting the underappreciated role primary language plays in COVID-19 severity among minority groups.

Food insecurity associated with higher COVID-19 infection in households with older adults

OBJECTIVES

As a well-documented social determinant of health, food insecurity may be associated with COVID-19 infection in households with older adults. We examined whether older adults were vulnerable to COVID-19 infection during the early pandemic if they were food insecure versus food secure.

STUDY DESIGN

A cross-sectional study using a nationally representative population-based survey of US older adults.

METHODS

We used a random subsample of Health and Retirement Study (HRS) drawn in June 2020 (N = 3212). We compared the odds of reporting COVID-19 infection in a household, COVID-19 infection and mortality among acquaintances, and respondent's perceived fair or poor health across household food insecurity status resulted from financial or non-financial barriers. Baseline health and socioeconomic circumstances were adjusted in the models.

RESULTS

Results showed a higher COVID-19 infection rate among food-insecure households than among their food-secure counterparts during the pandemic. Food insecurity due to non-financial obstacles was associated with greater likelihood of COVID-19 infection both within respondents' households (adjusted odds ratio [aOR] = 1.73, 95% confidence interval [CI]: 1.03-2.90) and among their acquaintances (aOR = 1.32, 95% CI: 1.05-1.65). Food insecurity caused by both non-financial and financial constraints was associated with twice the likelihood of knowing someone who died from COVID-19 than their food-secure counterparts (aOR = 2.14, 95% CI: 1.27-3.61).

CONCLUSIONS

Food insecurity driven by non-financial constraints played an important role in the ongoing pandemic among US older adults. Policies addressing COVID-19 need to recognize the vulnerability of food-insecure older adults beyond lack of monetary resources.

Racial/Ethnic Residential Segregation and the First Wave of SARS-CoV-2 Infection Rates: A Spatial Analysis of Four U.S. Cities

Previous research has linked racial/ethnic residential segregation to a number of poor health conditions, including infectious disease. Here, we examine how racial/ethnic residential segregation is related to the novel coronavirus, SARS-CoV-2. We examine infection rates by zip code level segregation in four major cities across the U.S.: New York City, Chicago, Houston, and San Diego. We also include a number of area-level Census variables in order to analyze how other factors may help account for the infection rate. We find that both Black and Latino residential clustering are significantly and positively related to a higher SARS-CoV-2 infection rate across all four cities, and that this effect is strong even when accounting for a number of other social conditions and factors that are salient to the transmission of infectious disease. As a result, we argue that neighborhood-level racial/ethnic patterning may serve as an important structural mechanism for disparities in SARS-CoV-2 infection.

Actual Racial/Ethnic Disparities in COVID-19 Mortality for the Non-Hispanic Black Compared to Non-Hispanic White Population in 353 US Counties and Their Association with Structural Racism

Introduction

Although disparities in COVID-19 mortality have been documented at the national and state levels, no previous study has quantified such disparities at the county level by explicitly measuring race-specific COVID-19 death rates. In this paper, we quantify the racial/ethnic disparities in COVID-19 mortality between the non-Hispanic Black and non-Hispanic White populations at the county level by estimating age-adjusted, race-specific death rates.

Methods

Using COVID-19 case data from the Centers for Disease Control and Prevention, we calculated crude and indirect age-adjusted COVID-19 mortality rates for the non-Hispanic White and non-Hispanic Black populations in each of 353 counties for the period February 2, 2020, through January 30, 2021. Using linear regression analysis, we examined the relationship between several county-level measures of structural racism and the observed differences in racial disparities in COVID-19 mortality across counties.

Results

Ninety-three percent of the counties in our study experienced higher death rates among the Black compared to the White population, with an average ratio of Black to White death rates of 1.9 and a 17.5-fold difference between the disparity in the lowest and highest counties. Three traditional measures of structural racism were significantly related to the magnitude of the Black-White racial disparity in COVID-19 mortality rates across counties.

Conclusions

There are large disparities in COVID-19 mortality rates between the Black and White populations at the county level, there are profound differences in the level of these disparities, and those differences are directly related to the level of structural racism in a given county.

Actual Racial/Ethnic Disparities in COVID-19 Mortality for the Non-Hispanic Black Compared to Non-Hispanic White Population in 35 US States and Their Association with Structural Racism

Introduction

While 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.

Methods

Using 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.

Results

Relying 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.

Conclusions

Structural 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.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40615-021-01028-1.

Health, psychosocial, and economic impacts of the COVID-19 pandemic on people with chronic conditions in India: a mixed methods study

Background

People with chronic conditions are disproportionately prone to be affected by the COVID-19 pandemic but there are limited data documenting this. We aimed to assess the health, psychosocial and economic impacts of the COVID-19 pandemic on people with chronic conditions in India.

Methods

Between July 29, to September 12, 2020, we telephonically surveyed adults (n = 2335) with chronic conditions across four sites in India. Data on participants’ demographic, socio-economic status, comorbidities, access to health care, treatment satisfaction, self-care behaviors, employment, and income were collected using pre-tested questionnaires. We performed multivariable logistic regression analysis to examine the factors associated with difficulty in accessing medicines and worsening of diabetes or hypertension symptoms. Further, a diverse sample of 40 participants completed qualitative interviews that focused on eliciting patient’s experiences during the COVID-19 lockdowns and data analyzed using thematic analysis.

Results

One thousand seven hundred thirty-four individuals completed the survey (response rate = 74%). The mean (SD) age of respondents was 57.8 years (11.3) and 50% were men. During the COVID-19 lockdowns in India, 83% of participants reported difficulty in accessing healthcare, 17% faced difficulties in accessing medicines, 59% reported loss of income, 38% lost jobs, and 28% reduced fruit and vegetable consumption. In the final-adjusted regression model, rural residence (OR, 95%CI: 4.01,2.90–5.53), having diabetes (2.42, 1.81–3.25) and hypertension (1.70,1.27–2.27), and loss of income (2.30,1.62–3.26) were significantly associated with difficulty in accessing medicines. Further, difficulties in accessing medicines (3.67,2.52–5.35), and job loss (1.90,1.25–2.89) were associated with worsening of diabetes or hypertension symptoms. Qualitative data suggest most participants experienced psychosocial distress due to loss of job or income and had difficulties in accessing in-patient services.

Conclusion

People with chronic conditions, particularly among poor, rural, and marginalized populations, have experienced difficulties in accessing healthcare and been severely affected both socially and financially by the COVID-19 pandemic.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10708-w.