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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 Roadmap to guide 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, this Roadmap consists of four 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 Roadmap supports efforts to develop conceptually and analytically rigorous neighborhood research projects.

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. 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 associations differed by race/ethnicity, and to characterize key conceptual and methodological considerations to guide future research. 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. 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. We suggest directions for future research to further develop the conceptual and methodological rigor of this work and inform evidence-based interventions to advance population health and reduce racial health inequities.

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.

Background/Aim: Evidence suggests a beneficial effect of prone positioning (PP) in COVID-19. Materials and Methods: Meta-analysis of individual (7 investigators’ groups) and aggregate data (PubMed/EMBASE) regarding the impact of PP on the ratio of arterial partial pressure of oxygen to fraction of inspired oxygen (PO2/FiO2) in patients with COVID-19. Results: Among 121 patients (mean age±SD 59.1±10.7 years, 55% males, 57% intubated) the mean post-versus pre- PP PO2/FiO2 difference was: (i) 50.4±64.3 mmHg, p

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, Highlights • Transitory decline in negative Black sentiment following the murder of George Floyd. • Greater public awareness of structural racism and desire for social change. • Though brief, these periods may provide opportunities for sustainable change.

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.

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.

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&ndash, 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&ndash, White incidence rate gaps. Anti-Black bias among Whites predicts worse COVID-19 outcomes and greater inequities. Area-level interventions may ameliorate health inequities.

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.

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 (β: 0.11; 95% CI: 0.04, 0.18); and higher implicit racial bias (β: 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., Highlights • This study confirms that Twitter-derived measures of racial bias are associated with more traditional measures of racial bias. • Social media data can be used for timely and cost-efficient measurement of area-level racial climate. • Development of area-level measures may improve understanding of the multilevel ways in which racism impacts health.

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.

Introduction:The use of prone positional therapy for moderate and severe hypoxicAcute Respiratory Distress Syndrome (ARDS) is known to decrease mortality. There are barriers to the routine use of Intermittent Prone Positioning (IPP), yet medical facilities are being overwhelmed with hypoxic patients due to COVID 19. We present the evolution of a high reliability protocolized program for IPP using minimal materials at the peak of the surge of COVID 19 patients that is applicable in settings of significant limitations and austerity.Methods:In the second week of April 2020 the program evolved through a series of short loop quality-based changes based in the principles of High Reliability Organizations (HROs) and Crew Resource Management (CRM). Patients with moderate to severe ARDS [PaO2:FiO2 ratio (PFr) was < 150 on an FiO2> 0.6 and a PEEP > 5 cm H2O] were eligible to receive IPP.The prone team consists of five to seven persons and patients were placed in the prone position for 16 hours and supine for 8 hours each day. When their PFr was > 200 for > 8 hours supine, positional therapy ceased. Patients were positioned prone using only available materials without additional work from the bedside physicians, registered nurses (RNs) or respiratory therapists (RTs).Arterial blood gases (ABGs) provided the measures of PaO2, PaCO2 and FiO2 and enabled calculation of the PFr and the SaO2:FiO2 ratio (SaFr). Data were collected concurrently by prospective intention for quality assessment. Data are reported as number (n) and percent (%) or mean ± standard error of the mean (SEM) and range. Changes in PaCO2, PF ratios, and SaF ratios are made by paired sample t-tests (2-tailed). Associations of PFr and SaFr at one hour pre-prone are evaluated using Pearson’s correlation and simple linear regression. Data were evaluated using R® Version 1.2.1335 (R Foundation for Statistical Computing, Vienna Austria) and significance is noted at α < 0.05 (p < 0.05).Results:Patients were treated between 14APR2020 and 09MAY2020. The peak of COVID 19 related deaths in New York was the 15th of April 2020. There have been 202 movements to the prone position and patients have received between 1 and 15 IPPs. There are 32 patients in the reported cohort and currently 12 patients are receiving IPP each day. Patients were 58.3± 1.7 years of age (37 to 73 years), 77% were male and had a BMI (body mass index) of 27.9 ± 0.7 (21 to 35). Pressor agents were being used in 74%, 16% were receiving dialysis, the white blood cell counts were 17.0 ± 1.5 (103/mcL) and their D dimers were 4630.0 ± 1588.0 ng/mL. At the time of consultation for prone positional therapy the patient’s arterial blood gas analyses were pH 7.28 ± 0.02, PaCO2 63.1 ± 3.53 mmHg, PaO2 of 80.5 ± 5.3 mmHg, HCO3 of 27.8 ± 1.0 mmol/L.The PFr prior to IPP was 108.0 ± 5.4and 1 hour after IPP was 152.8 ± 11.2 (p < 0.001). PFr after the patients were placed supine was 128.8 ± 9.2 (p = 0.014). Pre-prone PaCO2 was 59.7 ± 2.4 and the 1-hour post-prone PaCO2 was 68.9 ± 3.5 (p = 0.017 compared to pre-prone). The PaCO2measured supine one hour after IPP was 60.7 ± 3.3 (NS compared to pre-prone).The SaFr prior to IPP was 121.3 ± 4.2 and the SaFr 1 hour after positioning was 131.5 ± 5.1 (p = 0.012). The SaFr after the patients were placed supine was 139.7 ± 5.9 (p < 0.001 compared to pre-prone).Using regression coefficients, the SaF ratios predicted by PF ratios of 150 and 200 are 133.2 and 147.3, respectively.Conclusions:A program for prone positioning of adult patients with severe hypoxic ARDS due to COVID 19 can be designed and implemented rapidly, safely, and effectively during an overwhelming mass casualty scenario. This report describes one simple method that does not require any additional materials or labor from the already overburdened staff at the bedside. This approach may be equally applicable in both traditionally austere environments and in otherwise capable centers facing situational resource challenges.

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.

BACKGROUND: Determinants of racial inequities in risk of subtype-specific breast cancers are poorly understood. Features of the neighborhood context may contribute to racial inequities along the breast cancer continuum, however few have examined subtype-specific incidence. Therefore, this study aimed to characterize the association between the neighborhood racial context (housing discrimination and racial composition) and race- and subtype-specific breast cancer incidence among NH Black and NH White women in California. METHODS: We merged data from the California Cancer Registry on women aged 20+ diagnosed with primary breast cancer between 2006-2015 with neighborhood racial context at time of diagnosis: census tract % NH Black and a new racial bias index derived using 2007-2013 data from the Home Mortgage Disclosure Act. We used Poisson regression to estimate associations between neighborhood racial context and race- and Luminal A and TNBC (triple-negative breast cancer)-specific incidence rates, adjusting for neighborhood confounders. RESULTS: We identified n=104,716 cases of Luminal A and n=15,739 cases of TNBC over the study period. Among Black women, living in a high % Black census tract was associated with higher incidence of Luminal A (IRRadj=1.16 (1.08, 1.24)) and TNBC (IRRadj=1.17 (1.04, 1.32)) subtypes, relative to residence in low % Black tracts. No statistically significant association between neighborhood racial composition and either subtype was observed among NH Whites, nor between racial bias in mortgage lending and breast cancer among either racial group. CONCLUSION: Neighborhood racial composition may proxy cross-cutting social and environmental risk factors for breast cancer, regardless of subtype. These exposures may disproportionately burden Black versus White women with respect to breast cancer risk. Citation Format: Eli K. Michaels, Kirsten M.M. Beyer, Yuhong Zhou, Alison J. Canchola, Salma Shariff-Marco, Scarlett L. Gomez. Neighborhood racial context and race- and subtype-specific breast cancer incidence among non-Hispanic Black and non-Hispanic White women in California, 2006-2015 [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr C061.

BackgroundStudies suggest that racial discrimination impacts health via biological dysregulation due to continual adaptation to chronic psychosocial stress. Therefore, quantifying chronicity is critical for operationalising the relevant aetiological exposure and hence maximising internal validity. Using one of the most common discrimination scales in the epidemiological literature, we develop a novel approach for more accurately assessing chronicity and compare it with conventional approaches to determine whether coding influences differential exposure classification and associations with hypertension and depression among African American women.MethodsData are from a socioeconomically diverse cross section of 208 mid-life African American women in Northern California (data collection: 2012–2013). Racial discrimination was assessed using the Everyday Discrimination Scale (α=0.95), and was coded using two conventional approaches: (1) situation-based coding: number of different situations ever experienced; (2) frequency-based coding: sum of Likert scale responses ranging from 'never' to 'almost everyday'; and (3) a new chronicity-based coding approach: sum of responses, weighted to capture annual chronicity (eg, ‘a few times a month’=3×12=36×/year). Outcomes are hypertension and depressive symptomatology (10-item Center for Epidemiologic Studies-Depression Scale).FindingsExposure classification differed by coding approach, by up to 41%. There was a positive association between racial discrimination and hypertension prevalence for chronicity coding only (prevalence ratio=1.61, 95% CI 1.03 to 2.49). For depressive symptoms, a dose–response relationship of similar magnitude was observed for all three coding approaches.ConclusionScale coding is an important methodological consideration for valid exposure assessment in epidemiological research. Coding can impact exposure classification and associations with important indicators of African American women’s mental and physical health.

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&rsquo, s Heart and Health Study&mdash, a non-probability cross-section of 208 midlife African American women in Northern California&mdash, 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.