All Stressors Are Not Equal: The Salience of Racial Discrimination and Appraisal for Blood Pressure in African American Women.

OBJECTIVE: Psychosocial stress is a major predictor of chronic disease among African American (AA) women. Stress is a process involving exposure, appraisal of threat, coping, and psychobiologic adaptation. However, many studies focus on the frequency of stress events and/or coping; few explicitly study stress events and their appraisals; and AA women experience high levels of racial discrimination, a well-known form of social identity threat (i.e., negative experiences due to judgment based on identity). Stressors related to social identity threat may be differentially appraised and associated with divergent physiologic outcomes. This study examined the differences in the frequency and stressfulness associated with general stressors and racial discrimination in relation to blood pressure (BP) among AA women. METHODS: Multivariable regression was used on cross-sectional data from 208 middle-aged AA women residing in the San Francisco Bay Area. RESULTS: AA women reported less frequency of racial discrimination compared with general stressors, but were more likely to appraise racial discrimination events as stressful. Racial discrimination stressfulness was more strongly associated with systolic BP (SBP) than the number of racial discrimination events. There was a U-shaped association between racial discrimination stress and SBP, with those reporting "none" and "high/very high" distress having the highest SBP ( b = 12.2 [2.7 to 21.8] and b = 15.7 [1.5-29.8], respectively, versus moderate stress). Conversely, those reporting "very low" general stressfulness had the lowest SBP ( b = -7.9 [-15.8 to -0.1], versus moderate stress). Diastolic BP followed a similar pattern, although results were nonsignificant. CONCLUSIONS: This study highlights the importance of stress appraisal measures and adds to the body of evidence documenting racial discrimination as a salient psychosocial stressor for AA women.

Traveling Together: A Road Map for Researching Neighborhood Effects on Population Health and Health Inequities.

As evidence of the relationship between place and health mounts, more epidemiologists and clinical science researchers are becoming interested in incorporating place-based measures and analyses into their examination of population health and health inequities. Given the extensive literature on place and health, it can be challenging for researchers new to this area to develop neighborhood-effects research questions and apply the appropriate measures and methods. This paper provides a road map for guiding health researchers through the conceptual and methodological stages of incorporating various dimensions of place into their quantitative health research. Synthesizing across reviews, commentaries, and empirical investigations, the road map consists of 4 broad stages for considering place and health: 1) why?: articulating the motivation for assessing place and health and grounding the motivation in theory; 2) what?: identifying the relevant place-based characteristics and specifying their link to health to build a conceptual framework; 3) how?: determining how to operationalize the conceptual framework by defining, measuring, and assessing place-based characteristics and quantifying their effect on health; and 4) now what?: discussing the implications of neighborhood research findings for future research, policy, and practice. This road map supports efforts to develop conceptually and analytically rigorous neighborhood research projects.

The Water Surrounding the Iceberg: Cultural Racism and Health Inequities.

Policy Points Cultural racism-or the widespread values that privilege and protect Whiteness and White social and economic power-permeates all levels of society, uplifts other dimensions of racism, and contributes to health inequities. Overt forms of racism, such as racial hate crimes, represent only the "tip of the iceberg," whereas structural and institutional racism represent its base. This paper advances cultural racism as the "water surrounding the iceberg," allowing it to float while obscuring its base. Considering the fundamental role of cultural racism is needed to advance health equity. CONTEXT: Cultural racism is a pervasive social toxin that surrounds all other dimensions of racism to produce and maintain racial health inequities. Yet, cultural racism has received relatively little attention in the public health literature. The purpose of this paper is to 1) provide public health researchers and policymakers with a clearer understanding of what cultural racism is, 2) provide an understanding of how it operates in conjunction with the other dimensions of racism to produce health inequities, and 3) offer directions for future research and interventions on cultural racism. METHODS: We conducted a nonsystematic, multidisciplinary review of theory and empirical evidence that conceptualizes, measures, and documents the consequences of cultural racism for social and health inequities. FINDINGS: Cultural racism can be defined as a culture of White supremacy, which values, protects, and normalizes Whiteness and White social and economic power. This ideological system operates at the level of our shared social consciousness and is expressed in the language, symbols, and media representations of dominant society. Cultural racism surrounds and bolsters structural, institutional, personally mediated, and internalized racism, undermining health through material, cognitive/affective, biologic, and behavioral mechanisms across the life course. CONCLUSIONS: More time, research, and funding is needed to advance measurement, elucidate mechanisms, and develop evidence-based policy interventions to reduce cultural racism and promote health equity.

Home mortgage discrimination and incidence of triple-negative and Luminal A breast cancer among non-Hispanic Black and non-Hispanic White females in California, 2006-2015.

PURPOSE: In the United States, Black females are burdened by more aggressive subtypes and increased mortality from breast cancer compared to non-Hispanic (NH) White females. Institutional racism may contribute to these inequities. We aimed to characterize the association between home mortgage discrimination, a novel measure of institutional racism, and incidence of Luminal A and triple-negative breast cancer (TNBC) subtypes among NH Black and NH White females in California metropolitan areas. METHODS: We merged data from the California Cancer Registry on females aged 20 + diagnosed with primary invasive breast cancer between 2006 and 2015 with a census tract-level index of home mortgage lending bias measuring the odds of mortgage loan denial for Black versus White applicants, generated from the 2007-2013 Home Mortgage Disclosure Act database. Poisson regression estimated cross-sectional associations of census tract-level racial bias in mortgage lending with race/ethnicity- and Luminal A and TNBC-specific incidence rate ratios, adjusting for neighborhood confounders. RESULTS: We identified n = 102,853 cases of Luminal A and n = 15,528 cases of TNBC over the study period. Compared to NH Whites, NH Black females had higher rates of TNBC, lower rates of Luminal A breast cancer, and lived in census tracts with less racial bias in home mortgage lending. There was no evidence of association between neighborhood racial bias in mortgage lending at the time of diagnosis and either subtype among either racial/ethnic group. CONCLUSION: Future research should incorporate residential history data with measures of institutional racism to improve estimation and inform policy interventions.

Prone during pandemic: development and implementation of a quality-based protocol for proning severe COVID-19 hypoxic lung failure patients in situationally or historically low resource hospitals.

BACKGROUND: Intermittent Prone Positioning (IPP) for Acute Respiratory Distress Syndrome (ARDS) decreases mortality. We present a program for IPP using expedient materials for settings of significant limitations in both overwhelmed established ICUs and particularly in low- and middle-income countries (LMICs) treating ARDS due to COVID-19 caused by SARS CoV-2. METHODS: The proning program evolved based on the principles of High Reliability Organizations (HROs) and Crew Resource Management (CRM). Patients with severe ARDS [PaO2:FiO2 ratio (PFr) ≤ 150 on FiO2 ≥ 0.6 and PEEP ≥ 5 cm H2O] received IPP. Patients were placed prone 16 h each day. When PFr was ≥ 200 for > 8 h supine IPP ceased. IPP used available materials without requiring additional work from the bedside team. Changes in PFr, PaCO2, and the SaO2:FiO2 ratio (SaFr) positionally were evaluated using t-statistics and ANOVA with Bonferroni correction (p < 0.017). RESULTS: Between 14APR2020 and 09MAY2020, at the peak of deaths in New York, there were 202 IPPs in 29 patients. Patients were 58.5 ± 1.7 years of age (37, 73), 76% male and had a body mass index (BMI) of 27.8 ± 0.8 (21, 38). Pressor agents were used in 76% and 17% received dialysis. The PFr prior to IPP was 107.5 ± 5.6 and 1 h after IPP was 155.7 ± 11.2 (p < 0.001 compared to pre-prone). PFr after the patients were placed supine was 131.5 ± 9.1 (p = 0.02). Pre-prone PaCO2 was 60.0 ± 2.5 and the 1-h post-prone PaCO2 was 67.2 ± 3.1 (p = 0.02). Supine PaCO2 after IPP was 60.4 ± 3.4 (p = 0.90). The SaFr prior to IPP was 121.3 ± 4.2 and the SaFr 1 h after positioning was 131.5 ± 5.1 (p = 0.03). The post-IPP supine SaFr was 139.7 ± 5.9 (p < 0.001). With ANOVA and Bonferroni correction there were statistically significant changes in PFr (p < 0.001) and SaFr (p < 0.001) and no significant changes in PaCO2 over the four time points measured. Using regression coefficients, the SaFrs predicted by PFrs of 150 and 200 at baseline are 133.2 and 147.3, respectively. CONCLUSIONS: An IPP program for patients with COVID-19 ARDS can be instituted rapidly, safely, and effectively during an overwhelming mass casualty scenario. This approach may be equally applicable in both traditionally austere environments in LMICs and in otherwise capable centers facing situational resource limitations.

Solidarity and strife after the Atlanta spa shootings: A mixed methods study characterizing Twitter discussions by qualitative analysis and machine learning.

Background: On March 16, 2021, a white man shot and killed eight victims, six of whom were Asian women at Atlanta-area spa and massage parlors. The aims of the study were to: (1) qualitatively summarize themes of tweets related to race, ethnicity, and racism immediately following the Atlanta spa shootings, and (2) examine temporal trends in expressions hate speech and solidarity before and after the Atlanta spa shootings using a new methodology for hate speech analysis. Methods: A random 1% sample of publicly available tweets was collected from January to April 2021. The analytic sample included 708,933 tweets using race-related keywords. This sample was analyzed for hate speech using a newly developed method for combining faceted item response theory with deep learning to measure a continuum of hate speech, from solidarity race-related speech to use of violent, racist language. A qualitative content analysis was conducted on random samples of 1,000 tweets referencing Asians before the Atlanta spa shootings from January to March 15, 2021 and 2,000 tweets referencing Asians after the shooting from March 17 to 28 to capture the immediate reactions and discussions following the shootings. Results: Qualitative themes that emerged included solidarity (4% before the shootings vs. 17% after), condemnation of the shootings (9% after), racism (10% before vs. 18% after), role of racist language during the pandemic (2 vs. 6%), intersectional vulnerabilities (4 vs. 6%), relationship between Asian and Black struggles against racism (5 vs. 7%), and discussions not related (74 vs. 37%). The quantitative hate speech model showed a decrease in the proportion of tweets referencing Asians that expressed racism (from 1.4% 7 days prior to the event from to 1.0% in the 3 days after). The percent of tweets referencing Asians that expressed solidarity speech increased by 20% (from 22.7 to 27.2% during the same time period) (p < 0.001) and returned to its earlier rate within about 2 weeks. Discussion: Our analysis highlights some complexities of discrimination and the importance of nuanced evaluation of online speech. Findings suggest the importance of tracking hate and solidarity speech. By understanding the conversations emerging from social media, we may learn about possible ways to produce solidarity promoting messages and dampen hate messages.

Area-level racial prejudice and health: A systematic review.

BACKGROUND: In recent years, there has been growing interest in "moving beyond the individual" to measure area-level racism as a social determinant of health. Much of this work has aggregated racial prejudice data collected at the individual-level to the area-level. OBJECTIVE: As this is a rapidly emerging area of research, we conducted a systematic literature review to describe evidence of the relationship between area-level racial prejudice and health, whether results differed by race/ethnicity, and to characterize key conceptual and methodological considerations to guide future research. METHOD: We searched four interdisciplinary databases for US-based, peer-reviewed articles measuring area level racial prejudice by aggregating individual-level indicators of racial prejudice and examining associations with mental or physical health outcome(s). Data extraction followed PRISMA guidelines and also included theory and conceptualization, pathways to health, and strengths and limitations. RESULTS: Fourteen of 14,632 identified articles met inclusion criteria and were included in the review. Health outcomes spanned all-cause (n = 4) and cause-specific (n = 4) mortality, birth outcomes (n = 4), cardiovascular outcomes (n = 2), mental health (n = 1), and self-rated health (n = 1). All studies found a positive association between area-level racial prejudice and adverse health outcomes among racial/ethnic minoritized groups, with four studies also showing a similar association among Whites. Engagement with formal theory was limited and exposure conceptualization was mixed. Methodological considerations included unmeasured confounding and trade-offs between generalizability, self-censorship, and specificity of measurement. CONCLUSIONS: Future research should continue to develop the conceptual and methodological rigor of this work and test hypotheses to inform evidence-based interventions to advance population health and reduce racial health inequities. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Structurally vulnerable neighborhood environments and racial/ethnic COVID-19 inequities.

Preliminary evidence suggests that the experience of the novel coronavirus is not shared equally across geographic areas. Findings in the United States suggest that the burden of COVID-19 morbidity and mortality may be hardest felt in disadvantaged and racially segregated places. Deprived neighborhoods are disproportionately populated by people of color, the same populations that are becoming sicker and dying more often from COVID-19. This commentary examines how structurally vulnerable neighborhoods contribute to racial/ethnic inequities in SARS-COV-2 exposure and COVID-19 morbidity and mortality and considers opportunities to intervene through place-based initiatives and the implementation of a Health in All Policies strategy.

US law enforcement policy predictors of race-specific police fatalities during 2015-16.

Mounting evidence suggests that law enforcement organizational factors contribute to higher incidence and racial disparities in police killings. To determine whether agency policies contribute to race-specific civilian fatalities, this exploratory study compared fatality rates among agencies with and without selected policies expected to reduce killings. A cross-section of 1085 fatalities in the 2015-2016 The Counted public-use database were matched to 481 agencies in the 2013 Law Enforcement Management and Administrative Statistics (LEMAS) database. Negative binomial regression estimated incidence rate ratios (IRR) adjusted for agency type, number of officers, percent female personnel, median income, percent with a bachelor's degree, violent crime rate, and population size, with inference using robust standard errors. Agencies with greater proportions of full-time personnel (range 43-100%) had lower rates of all (IRR = 0.85; 95% confidence interval [CI] = 0.77-0.93) and non-White civilian killings (IRR = 0.85; CI = 0.73-0.99). Mission statements predicted lower rates of all (IRR = 0.70; CI = 0.58-0.84) and White killings (IRR = 0.60; CI = 0.40-0.90). Community evaluation and more types of personnel incentives predicted lower rates of White (IRR = 0.82; CI = 0.68-0.99) and non-White killings (IRR = 0.94; CI = 0.89-1.00), respectively. Increasing video use predicted higher rates of White killings (IRR = 1.13; CI = 1.01-1.28). No policies were significantly associated with Black civilian killings. Law enforcement policies that help reduce police killings may vary across racial groups with the least benefit for Black civilians. Impact evaluations and meta-analyses of initiatives aimed to mitigate fatalities should be explored, particularly policies to address anti-Black bias. A national registry tracking all police killings and agency policies is urgently needed to inform law enforcement policies aimed to mitigate civilian fatalities.

Twitter Fingers and Echo Chambers: Exploring Expressions and Experiences of Online Racism Using Twitter.

Social media sites, such as Twitter, represent a growing setting in which racism and related stress may manifest. The aims of this exploratory qualitative study were to (1) understand the essence of Twitter users' lived experience with and response to content about race and racism on the platform, and (2) explore their perceptions of how discussions about race and racism on Twitter may impact health and well-being. We conducted six focus groups and four interviews with adult Twitter users (n = 27) from Berkeley, California, and Greenville, South Carolina. We managed the data with NVivo and conducted an interpretative phenomenological analysis to identify themes. Participants described Twitter content as displaying both overt and subtle expressions of racism, particularly for Black and Latinx people, and serving as an echo chamber where similar viewpoints are amplified. Participants described how Twitter users may feel emboldened to type offensive tweets based on the perception of anonymity, and that these tweets were sometimes met with community disapproval used to provide a collective calibration to restore the social norms of the online space. Participants perceived harmful mental, emotional, and physical health impacts of exposure to racist content on Twitter. Our participants responded to harmful race-related content through blocking users and following others in order to curate their Twitter feeds, actively engaging in addressing content, and reducing Twitter use. Twitter users reported witnessing racism on the platform and have found ways to protect their mental health and cope with discussions of race and racism in this social media environment.

Evaluating associations between area-level Twitter-expressed negative racial sentiment, hate crimes, and residents' racial prejudice in the United States.

BACKGROUND: The objective of the current study is to investigate whether an area-level measure of racial sentiment derived from Twitter data is associated with state-level hate crimes and existing measures of racial prejudice at the individual-level. METHODS: We collected 30,977,757 tweets from June 2015-July 2018 containing at least one keyword pertaining to specific groups (Asians, Arabs, Blacks, Latinos, Whites). We characterized sentiment of each tweet (negative vs all other) and averaged at the state-level. These racial sentiment measures were merged with other measures based on: hate crime data from the FBI Uniform Crime Reporting Program; implicit and explicit racial bias indicators from Project Implicit; and racial attitudes questions from General Social Survey (GSS). RESULTS: Living in a state with 10% higher negative sentiment in tweets referencing Blacks was associated with 0.57 times the odds of endorsing a GSS question that Black-White disparities in jobs, income, and housing were due to discrimination (95% CI: 0.40, 0.83); 1.64 times the odds of endorsing the belief that disparities were due to lack to will (95% CI: 0.95, 2.84); higher explicit racial bias (ß: 0.11; 95% CI: 0.04, 0.18); and higher implicit racial bias (ß: 0.09; 95% CI: 0.04, 0.14). Twitter-expressed racial sentiment was not statistically-significantly associated with incidence of state-level hate crimes against Blacks (IRR: 0.99; 95% CI: 0.52, 1.90), but this analysis was likely underpowered due to rarity of reported hate crimes. CONCLUSION: Leveraging timely data sources for measuring area-level racial sentiment can provide new opportunities for investigating the impact of racial bias on society and health.

Progress and push-back: How the killings of Ahmaud Arbery, Breonna Taylor, and George Floyd impacted public discourse on race and racism on Twitter.

This study examined whether killings of George Floyd, Ahmaud Arbery, and Breonna Taylor by current or former law enforcement officers in 2020 were followed by shifts in public sentiment toward Black people. Methods: Google searches for the names "Ahmaud Arbery," "Breonna Taylor," and "George Floyd" were obtained from the Google Health Application Programming Interface (API). Using the Twitter API, we collected a 1% random sample of publicly available U.S. race-related tweets from November 2019-September 2020 (N = 3,380,616). Sentiment analysis was performed using Support Vector Machines, a supervised machine learning model. A qualitative content analysis was conducted on a random sample of 3,000 tweets to understand themes in discussions of race and racism and inform interpretation of the quantitative trends. Results: The highest rate of Google searches for any of the three names was for George Floyd during the week of May 31 to June 6, the week after his murder. The percent of tweets referencing Black people that were negative decreased by 32% (from 49.33% in November 4-9 to 33.66% in June 1-7) (p < 0.001), but this decline was temporary, lasting just a few weeks. Themes that emerged during the content analysis included discussion of race or racism in positive (14%) or negative (38%) tones, call for action related to racism (18%), and counter movement/arguments against racism-related changes (6%). Conclusion: Although there was a sharp decline in negative Black sentiment and increased public awareness of structural racism and desire for long-lasting social change, these shifts were transitory and returned to baseline after several weeks. Findings suggest that negative attitudes towards Black people remain deeply entrenched.

Whites' County-Level Racial Bias, COVID-19 Rates, and Racial Inequities in the United States.

Mounting evidence reveals considerable racial inequities in coronavirus disease 2019 (COVID-19) outcomes in the United States (US). Area-level racial bias has been associated with multiple adverse health outcomes, but its association with COVID-19 is yet unexplored. Combining county-level data from Project Implicit on implicit and explicit anti-Black bias among non-Hispanic Whites, Johns Hopkins Coronavirus Resource Center, and The New York Times, we used adjusted linear regressions to estimate overall COVID-19 incidence and mortality rates through 01 July 2020, Black and White incidence rates through 28 May 2020, and Black-White incidence rate gaps on average area-level implicit and explicit racial bias. Across 2994 counties, the average COVID-19 mortality rate (standard deviation) was 1.7/10,000 people (3.3) and average cumulative COVID-19 incidence rate was 52.1/10,000 (77.2). Higher racial bias was associated with higher overall mortality rates (per 1 standard deviation higher implicit bias b = 0.65/10,000 (95% confidence interval: 0.39, 0.91); explicit bias b = 0.49/10,000 (0.27, 0.70)) and higher overall incidence (implicit bias b = 8.42/10,000 (4.64, 12.20); explicit bias b = 8.83/10,000 (5.32, 12.35)). In 957 counties with race-specific data, higher racial bias predicted higher White and Black incidence rates, and larger Black-White incidence rate gaps. Anti-Black bias among Whites predicts worse COVID-19 outcomes and greater inequities. Area-level interventions may ameliorate health inequities.

After "The China Virus" Went Viral: Racially Charged Coronavirus Coverage and Trends in Bias Against Asian Americans.

On March 8, 2020, there was a 650% increase in Twitter retweets using the term "Chinese virus" and related terms. On March 9, there was an 800% increase in the use of these terms in conservative news media articles. Using data from non-Asian respondents of the Project Implicit "Asian Implicit Association Test" from 2007-2020 (n = 339,063), we sought to ascertain if this change in media tone increased bias against Asian Americans. Local polynomial regression and interrupted time-series analyses revealed that Implicit Americanness Bias-or the subconscious belief that European American individuals are more "American" than Asian American individuals-declined steadily from 2007 through early 2020 but reversed trend and began to increase on March 8, following the increase in stigmatizing language in conservative media outlets. The trend reversal in bias was more pronounced among conservative individuals. This research provides evidence that the use of stigmatizing language increased subconscious beliefs that Asian Americans are "perpetual foreigners." Given research that perpetual foreigner bias can beget discriminatory behavior and that experiencing discrimination is associated with adverse mental and physical health outcomes, this research sounds an alarm about the effects of stigmatizing media on the health and welfare of Asian Americans.

Everyday Racial Discrimination and Hypertension among Midlife African American Women: Disentangling the Role of Active Coping Dispositions versus Active Coping Behaviors.

Racial discrimination, a psychosocial stressor, may contribute to disproportionate rates of hypertension among African American women. Coping moderates the effects of psychosocial stress on health. Coping dispositions describe stable personality characteristics, whereas contextual frameworks emphasize flexible coping behaviors in response to specific stressful encounters. Using data from the African American Women's Heart and Health Study-a non-probability cross-section of 208 midlife African American women in Northern California-we estimated the association between everyday racial discrimination (Everyday Discrimination Scale, EDS) and prevalence of hypertension (HTN), and evaluated moderation by coping disposition (John Henryism Active Coping scale, JH) versus context-specific active coping behavior (Active Coping with Racism scale, ACR). There were no main associations between EDS, JH, or ACR on HTN prevalence. There was evidence of statistical interaction between EDS and ACR (p-int = 0.05), but not JH (p-int = 0.90). Among those with high levels of ACR, reporting monthly (prevalence ratio (PR) = 2.35, 95% confidence interval (CI) = 1.13, 4.87), weekly (PR = 2.15, 95% CI = 1.01, 4.61), or daily (PR = 2.36, 95% CI = 1.14, 4.88) EDS was associated with higher HTN prevalence, versus reporting racial discrimination yearly or less. In contrast, among those with low levels of ACR, reporting more chronic racial discrimination was associated with lower hypertension prevalence, although results were less precise. Findings suggest that ongoing active coping with chronic racial discrimination may contribute to hypertension risk among African American women.

Racial discrimination, educational attainment, and biological dysregulation among midlife African American women.

OBJECTIVE: To examine the association between self-reported racial discrimination and allostatic load, and whether the association differs by socioeconomic position. METHODS: We recruited a purposive cross-section of midlife (ages 30-50) African American women residing in four San Francisco Bay area counties (n = 208). Racial discrimination was measured using the Experience of Discrimination scale. Allostatic load was measured as a composite of 15 biomarkers assessing cardiometabolic, neuroendocrine, and inflammatory activity. We calculated four composite measures of allostatic load and three system-specific measures of biological dysregulation. Multivariable regression was used to examine associations, while adjusting for relevant confounders. RESULTS: In the high education group, reporting low (b = -1.09, P = .02, 95% CI = -1.99, -0.18) and very high (b = -1.88, P = .003, 95% CI = -3.11, -0.65) discrimination was associated with lower allostatic load (reference=moderate). Among those with lower education, reporting low (b = 2.05, P = .008, 95% CI = 0.55,3.56) discrimination was associated with higher allostatic load. Similar but less consistent associations were found for poverty status. Associations were similar for cardiometabolic functioning, but not for neuroendocrine or inflammatory activity. CONCLUSIONS: Racial discrimination may be an important predictor of cumulative physiologic dysregulation. Factors associated with educational attainment may mitigate this association for African American women and other groups experiencing chronic social stress.