Race, explicit racial attitudes, implicit racial attitudes, and COVID-19 cases and deaths: An analysis of counties in the United States

Sexual harassment and implicit gender-career biases negatively impact women's life expectancy in the US: a state-level analysis, 2011-2019

BACKGROUND

Despite some gains, women continue to have less access to work and poorer experiences in the workplace, relative to men. The purpose of this study was to examine the relationships among women's life expectancy and two work-related factors, sexual harassment and gender-career biases.

METHOD

We examined the associations at the state level of analysis (and District of Columbia) in the US from 2011 to 2019 (n = 459) using archival data from various sources. Measures of the ratio of population to primary health providers, year, the percent of adults who are uninsured, the percent of residents aged 65 or older, and percent of residents who are Non-Hispanic White all served as controls.

RESULTS

Results of linear regression models showed that, after accounting for the controls, sexual harassment and gender-career biases among people in the state held significant, negative associations with women's life expectancy.

CONCLUSION

The study contributes to the small but growing literature showing that negative workplace experiences and bias against women in the workplace negatively impact women's health.

Racial implicit bias: Perspectives of nursing students

BACKGROUND

Racial implicit bias contributes to healthcare disparities. While research has been conducted on other health professionals, there is a lack of evidence about nursing students' experiences with racial implicit bias.

PURPOSE

This study described the perspectives of pre-licensure nursing students regarding racial implicit bias (RIB) and its impact on patient care.

METHOD

A qualitative descriptive methodology utilizing focus groups was used to describe the students' perspectives.

RESULTS

Data analysis revealed three main themes: RIB may not be on purpose, but wrong is wrong; Bad nurse versus good nurse; and This is not okay.

CONCLUSION

As RIB continues to contribute to health care disparities, this study reveals the need for it to be addressed in nursing education, while students prepare to be front line health care professionals.

Sick, Hungry, and Vulnerable: Federal Stimulus and Food Security on Marginalized Populations During the COVID-19 Pandemic

In addition to the threat of serious illness, COVID-19 and subsequent restrictions had devastating economic consequences for many US citizens. This study examines the evolution of food security over the first months of the COVID-19 pandemic testing whether the initial economic stimulus payment improved the nutritional well-being of vulnerable populations. We use data from phase 1 of the Census Bureau's Household Pulse Survey among a nationally representative sample of adults and the 2017-2018 Current Population Survey Food Security Supplement. Using an ordered logistic regression, we assess differences in the incidence and severity of food security across demographic, income, geographic, and employment status cohorts and assess the effects of the first economic stimulus payment. Our results show that marginalized groups faced greater food insecurity and had food-related outcomes worsen over time. Blacks, Hispanics, and individuals living in rural areas became less food secure as the pandemic progressed. However, receipt of a stimulus payment appears to have improved conditions. Rising food prices and persistent high unemployment have the potential to exacerbate food insecurity among marginalized and at-risk groups.

Anti-Black attitudes predict decreased concern about COVID-19 among Whites in the U.S. and Brazil

RATIONALE

From the earliest days of the COVID-19 pandemic, public health officials and news organizations reported pervasive racial disparities in the infection, morbidity, and mortality of the virus. In both the U.S. and Brazil, Black, Native, and mixed-race individuals were more negatively impacted by COVID-19 than White people. Simultaneously, significant social factions downplayed the threat and insisted on living "normally". We examined how these two factors coexisted.

OBJECTIVE

We sought to establish whether Whites' anti-Black attitudes predicted their concern about the pandemic and tendency to behave in ways that exacerbated the pandemic.

METHODS

and Results: In five studies, conducted in two countries (total N = 3425), we found that anti-Black attitudes (above and beyond political orientation, White racial identification, and perceptions of racial disparities) were associated with less concern about COVID-19, lower adoption of health and social distancing behaviors, and greater interest in returning to normalcy.

DISCUSSION

We discuss how efforts to combat anti-Blackness may improve the health of the general population.

Bias among managers: Its prevalence across a decade and comparison across occupations

Employees from minoritized and subjugated groups have poorer work experiences and fewer opportunities for advancement than do their peers. Biases among decision makers likely contributes to these patterns. The purposes of this study were to (a) examine the explicit biases and implicit biases among people in management occupations (e.g., chief executives, operations managers, advertising and promotions managers, financial managers, and distributions managers, among others) and (b) compare their biases with people in 22 other occupations. The authors analyzed responses from visitors to the Project Implicit website, including assessments of their racial, gender, disability, and sexual orientation biases from 2012 to 2021. Results indicate that managers expressed moderate levels of explicit and implicit bias across all dimensions. Managers differed from people in other occupations in roughly one-third of the comparisons. The biggest differences came in their implicit biases, with managers expressing more bias than people in other occupations. The study's originality rests in the scope of the work (the authors analyzed data from over 5 million visitors representing 23 broad occupations); comparison of people in management occupations to those in other work settings; and empirically demonstrating the biases that managers have.

Prejudicial reactions to the removal of Native American mascots

As Native American mascots are discontinued, research is needed to understand the impact on intergroup relations. Such discontinuations may be threatening to some and increase prejudice against Native Americans. In Study 1 ( N = 389), exposure to information about a Native American mascot removal increased punitive judgments against a Native American in a hypothetical legal scenario, particularly among those high in racial colorblindness and those residing in the implicated geographical location. Study 2 ( N = 358,644) conceptually replicated and extended these findings, using population-level implicit bias data to perform a natural quasi-experiment. Prejudice against Native Americans increased in the year following the removal of two Native American mascots: “Chief Illiniwek” and “Chief Wahoo.” However, in the case of Chief Illiniwek, the effect diminished after 6 years. Together, the studies contribute to understanding the psychological impact of Native American mascots, offering a first look at how their removal influence intergroup relations.

High SARS-CoV-2 seroprevalence in persons experiencing homelessness and shelter workers from a day-shelter in São Paulo, Brazil

Brazil presents one of the highest COVID-19 death tolls in the world. The initial SARS-CoV-2 epicenter was São Paulo city. As of 2019, the homeless population of São Paulo city was estimated at 24,344 individuals, the largest national homeless population. The present study aimed to concomitantly assess the molecular and serological prevalence and associated risk factors of SARS-CoV-2 infection in a homeless population and related shelter workers from a day-shelter. Serum samples, nasopharyngeal and oropharyngeal swabs of persons who are homeless and shelter workers collected from August 25^th to 27^th, 2020 were tested for the presence of anti-SARS-CoV-2 IgM and IgG antibodies by ELISA and SARS-CoV-2 RNA by RT-qPCR, respectively. All swab samples tested negative by RT-qPCR. Seropositivity of IgM and IgG was 5/203 (2.5%) and 111/203 (54.7%) in persons who are homeless, and 5/87 (5.7%) and 41/87 (47.1%) in shelter workers, respectively, with no statistical differences between groups. The high seroprevalence found herein indicates early environmental and urban spreading of SARS-CoV-2, associated with sociodemographic and economic vulnerability.

Brazil is one of the world’s most social-economically unequal countries, with a rising homeless population potentialized by the SARS-CoV-2 pandemic, particularly in its largest city, São Paulo. While few studies, mostly in high-income countries, have addressed the impact of the coronavirus pandemic on homeless populations, none has been carried out in Brazil. Herein, we report a high SARS-CoV-2 IgG seroprevalence in a homeless population, with 111/203 (54.7%) seropositive individuals. At the time of the study (August 25^th- 27^th 2020), both homeless and social worker populations showed no active SARS-CoV-2 infection, indicating that they were likely exposed sometime within the pandemic’s first peak in the city. Our study has also shown significant risk and protective factors for SARS-CoV-2 infection, including that Black shelter workers were at higher risk of SARS-CoV-2 infection when compared with the white shelter workers.

Temporal Geospatial Analysis of COVID-19 Pre-Infection Determinants of Risk in South Carolina

Disparities and their geospatial patterns exist in morbidity and mortality of COVID-19 patients. When it comes to the infection rate, there is a dearth of research with respect to the disparity structure, its geospatial characteristics, and the pre-infection determinants of risk (PIDRs). This work aimed to assess the temporal-geospatial associations between PIDRs and COVID-19 infection at the county level in South Carolina. We used the spatial error model (SEM), spatial lag model (SLM), and conditional autoregressive model (CAR) as global models and the geographically weighted regression model (GWR) as a local model. The data were retrieved from multiple sources including USAFacts, U.S. Census Bureau, and the Population Estimates Program. The percentage of males and the unemployed population were positively associated with geodistributions of COVID-19 infection (p values < 0.05) in global models throughout the time. The percentage of the white population and the obesity rate showed divergent spatial correlations at different times of the pandemic. GWR models fit better than global models, suggesting nonstationary correlations between a region and its neighbors. Characterized by temporal-geospatial patterns, disparities in COVID-19 infection rate and their PIDRs are different from the mortality and morbidity of COVID-19 patients. Our findings suggest the importance of prioritizing different populations and developing tailored interventions at different times of the pandemic.

Physical activity and its relationship with COVID-19 cases and deaths: Analysis of U.S. counties

PURPOSE

The study was to examine county-level associations of physical activity with coronavirus disease 2019 (COVID-19) cases and deaths, per 100,000 county residents.

METHODS

Data were collected from publicly available data sources for 3142 counties and equivalents, including the District of Columbia. Subjective health ratings, percentage uninsured, percentage unemployed, median household income, percentage female residents, percentage White residents, percentage of residents 65 years of age or older, and rural designation served as controls.

RESULTS

The two-level random intercept regression showed that physical activity rates at the county level were statistically and negatively associated with COVID-19 cases and deaths. Additional analyses showed that physical activity rates moderated the relationship between cases and deaths, such that the relationship was strongest when physical activity rates were low.

CONCLUSION

The results presented here offer empirical evidence of the benefits of county-level physical activity during a pandemic. Implications for public health and physical activity provision are discussed.

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.

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

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.

COVID-19 and excess mortality in the United States: A county-level analysis

BACKGROUND

Coronavirus Disease 2019 (COVID-19) excess deaths refer to increases in mortality over what would normally have been expected in the absence of the COVID-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to COVID-19. In this study, we take advantage of county-level variation in COVID-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to COVID-19 varies across subsets of counties defined by sociodemographic and health characteristics.

METHODS AND FINDINGS

In this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct COVID-19 and all-cause mortality occurring in US counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a 10-week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more COVID-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black, and 59.6% non-Hispanic White. A total of 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and COVID-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to COVID-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than COVID-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to COVID-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of COVID-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to COVID-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics.

CONCLUSIONS

In this study, we found that direct COVID-19 death counts in the US in 2020 substantially underestimated total excess mortality attributable to COVID-19. Racial and socioeconomic inequities in COVID-19 mortality also increased when excess deaths not assigned to COVID-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.

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.

Assessing the Impact of the Covid-19 Pandemic on US Mortality: A County-Level Analysis

Background.

Covid-19 excess deaths refer to increases in mortality over what would normally have been expected in the absence of the Covid-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to Covid-19. In this study, we take advantage of county-level variation in Covid-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to Covid-19 varies across subsets of counties defined by sociodemographic and health characteristics.

Methods and Findings.

In this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct Covid-19 and all-cause mortality occurring in U.S. counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a ten week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more Covid-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black and 59.6% non-Hispanic White. 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and Covid-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to Covid-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than Covid-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to Covid-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of Covid-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to Covid-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics.

Conclusions.

In this study, we found that direct Covid-19 death counts in the United States in 2020 substantially underestimated total excess mortality attributable to Covid-19. Racial and socioeconomic inequities in Covid-19 mortality also increased when excess deaths not assigned to Covid-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.

Uncloaking a Lost Cause: Decolonizing ancestry estimation in the United States

Since the professionalization of US‐based forensic anthropology in the 1970s, ancestry estimation has been included as a standard part of the biological profile, because practitioners have assumed it necessary to achieve identifications in medicolegal contexts. Simultaneously, forensic anthropologists have not fully considered the racist context of the criminal justice system in the United States related to the treatment of Black, Indigenous, and People of Color; nor have we considered that ancestry estimation might actually hinder identification efforts because of entrenched racial biases. Despite ongoing criticisms from mainstream biological anthropology that ancestry estimation perpetuates race science, forensic anthropologists have continued the practice. Recent years have seen the prolific development of retooled typological approaches with 21st century statistical prowess to include methods for estimating ancestry from cranial morphoscopic traits, despite no evidence that these traits reflect microevolutionary processes or are suitable genetic proxies for population structure; and such approaches have failed to critically evaluate the societal consequences for perpetuating the biological race concept. Around the country, these methods are enculturated in every aspect of the discipline ranging from university classrooms, to the board‐certification examination marking the culmination of training, to standard operating procedures adopted by forensic anthropology laboratories. Here, we use critical race theory to interrogate the approaches utilized to estimate ancestry to include a critique of the continued use of morphoscopic traits, and we assert that the practice of ancestry estimation contributes to white supremacy. Based on the lack of scientific support that these traits reflect evolutionary history, and the inability to disentangle skeletal‐based ancestry estimates from supporting the biological validity of race, we urge all forensic anthropologists to abolish the practice of ancestry estimation.