Historical Redlining, Contemporary Gentrification, and Severe Maternal Morbidity in California, 2005-2018.

Importance: Historically redlined neighborhoods may experience disinvestment, influencing their likelihood of gentrification, a process of neighborhood (re-)development that unequally distributes harms and benefits by race and class. Understanding the combined outcomes of redlining and gentrification informs how the mutually constitutive systems of structural racism and racial capitalism affect pregnancy outcomes. Objective: To examine if historical redlining and contemporary gentrification is associated with increased severe maternal morbidity (SMM) odds. Design, Setting, and Participants: This cross-sectional study used data from a statewide population-based sample of all live hospital births at 20 weeks' gestation or more between 2005 and 2018 in California. Analysis was conducted from March 2023 to January 2024. Exposure: Redlining (as characterized by the federal Home Owners' Loan Corporation mortgage security maps) and displacement (using present-day sociodemographic and housing market information). Main Outcomes and Measures: Mixed-effects logistic regression models were used to assess the association of census tract-level exposure to historical redlining and contemporary gentrification with increased SMM odds, adjusting for sociodemographic and pregnancy related factors. Outcome classification was based on the Centers for Disease Control and Prevention SMM index, which defines SMM as having any of the 21 procedures and diagnoses based on the International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes. Results: The study sample included 1 554 837 births (median [SD] maternal age, 29.0 [6.4] years; 3464 American Indian or Alaskan Native [0.2%], 224 774 Asian [14.5%], 132 240 Black [8.5%], 880 104 Hispanic [56.6%], 312 490 White [20.1%]), with 22 993 cases of SMM (1.4%). Residents in historically redlined neighborhoods that were undergoing gentrification or displacement were more likely to be Black, Hispanic, and American Indian or Alaskan Native. Independent of individual-level characteristics, SMM odds were greater for individuals living in redlined neighborhoods that experienced displacement (OR, 1.21; 95% CI, 1.14-1.28) and in redlined neighborhoods undergoing gentrification (OR, 1.21; 95% CI, 1.13-1.29) compared with those in continuously advantaged neighborhoods. Conclusions and Relevance: Findings from this cross-sectional study demonstrate that the legacies of redlining, intertwined with current dynamics of displacement and gentrification, affect SMM. Place-based sociopolitical mechanisms that inequitably distribute resources may be important intervention points to address structural drivers of adverse pregnancy outcomes and their racial inequities.

Links between ethnic discrimination, mental health, protective factors, and hair cortisol concentrations in asylum seekers living in Germany.

Objective: Asylum seekers often experience ethnic discrimination on the flight or in the host country, which may be associated with chronic stress and impaired mental health. Dysregulation of the hypothalamic-pituitary-adrenal axis, a known physiological correlate of chronic stress, can be assessed using hair cortisol concentrations (HCC). The present study aimed to investigate how different forms of perceived ethnic discrimination are associated with mental health outcomes, HCC, and protective factors in asylum seekers living in Germany.Methods: Somatic symptoms (PHQ-15), symptoms of posttraumatic stress (PDS), depressive symptoms (PHQ-9), different forms of ethnic discrimination (active harm, passive harm, institutional discrimination), and protective factors (in-group identification, social support) were assessed cross-sectionally in 144 asylum seekers (average age 32 years, average duration of stay in Germany nine months; 67% men). HCC were obtained from 68 participants. Multiple regression analyses were conducted and social support and in-group identification were tested as potential moderators.Results: Active ethnic discrimination was positively associated with all assessed mental health outcomes, and all forms of ethnic discrimination positively correlated with depressive symptoms. Ethnic discrimination was not associated with HCC. When controlling for other possible influences (e.g. age, gender, traumatic events), passive harm was negatively associated with depressive symptoms (ß = -0.17, p = .033) and active harm was positively associated (ß = 0.28, p = .022) with somatic symptoms. After the inclusion of the protective factors, the associations were no longer significant. Lower social support was associated with higher depressive symptoms (ß = -0.35, p < .001), posttraumatic stress (ß = -0.77, p < .001), and somatic symptoms (ß = -0.32, p < .001), but did not moderate the associations between ethnic discrimination and the mental health outcomes.Conclusions: Perceived ethnic discrimination may negatively influence asylum seekers' mental health but does not seem to be associated with HCC. Social support was associated with psychological symptom severity, but did not buffer the effects of ethnic discrimination on mental health.

The study examined the relationship between ethnic and institutional discrimination, protective factors (social support and in-group identification), hair cortisol concentrations (HCC) and mental health in asylum seekers.Ethnic discrimination was associated with mental health outcomes and social support, but not with HCC.Lower social support was associated with higher depressive and somatic symptoms, but did not moderate the relationship between ethnic discrimination and mental health.

Prolonged Boarding and Racial Discrimination and Dissatisfaction Among Emergency Department Patients.

Importance: Emergency department (ED) boarding times have increased rapidly, but their health equity outcomes are unknown. Objective: To investigate whether prolonged ED boarding is associated with increased perceived racial discrimination and dissatisfaction and whether associations vary between patients from marginalized racial and ethnic groups vs non-Hispanic White patients. Design, Setting, and Participants: This is a cross-sectional study of hospitalized adults who boarded in the ED during internal medicine admissions at a large, urban hospital in Boston, Massachusetts, from June 2023 to January 2024. Equal proportions of non-Hispanic White patients and patients from marginalized racial and ethnic groups (American Indian or Alaska Native, Hispanic, non-Hispanic Black and/or African American, and multiracial) were selected randomly. Exposure: The duration of ED boarding was categorized as less than 4 hours (reference), 4 to less than 24 hours, and 24 or more hours. Main Outcomes and Measures: Primary outcomes were odds of reporting (1) discrimination via the Discrimination in Medical Settings scale, and (2) dissatisfaction via the adapted Picker Patient Experience-15 questionnaire. Marginalized race and ethnicity was tested as an effect modifier. Multivariable logistic regression models adjusted for patient age, sex, language, and insurance payer. Results: Of 598 patients approached, 527 were enrolled, and 525 completed the surveys (response rate, 87.8%). The mean age (SD) was 60.6 (18.7) years, 300 patients (57.1%) were female, 246 patients (47.3%) identified as non-Hispanic White, and 274 (52.7%) were from a marginalized racial or ethnic group. In total, 135 (25.7%) boarded less than 4 hours (reference), 202 (38.5%) boarded 4 to less than 24 hours, and 188 (35.8%) boarded 24 hours or longer. Compared with less than 4 hours, boarding 24 hours or longer was associated with increased perceived discrimination (odds ratio [OR], 1.84; 95% CI, 1.14-2.99; P = .01). An increased association was observed in the subgroup of patients from racial and ethnic marginalized groups (OR, 2.36; 95% CI, 1.20-4.65; P = .01); effect modification was not significant (P for interaction, .10). For all patients, boarding 24 hours or longer was associated with increased dissatisfaction with care (OR, 1.77; 95% CI, 1.03-3.06; P = .04); effect modification was not significant (P for interaction, .80). Conclusions and Relevance: In this cross-sectional study, hospitalized patients who boarded in the ED 24 hours or longer reported more discrimination and dissatisfaction with care, which may disproportionately affect patients from marginalized racial and ethnic groups. As ED boarding times increase nationally, it is critical to recognize their potential to exacerbate health inequities and to respond with equity-focused solutions.

Skin tone discrimination and birth control avoidance among women in Harris County, Texas: a cross-sectional study.

INTRODUCTION: Structural racism plays a major role in reproductive health inequities. Colorism, discrimination based on skin color, may profoundly impact reproductive health access and service delivery. However, quantitative research in this area is limited. METHODS: We administered an online survey of women (n = 1,299) aged 18-44 from Harris County, Texas to assess the relationship between skin color discrimination and reproductive health service avoidance. The survey included questions on demographics, self-reported skin tone, and dichotomous measures of previous discrimination experiences and avoidance of care because of perceived discrimination. Binary logistic regression was used to examine whether race/ethnicity, skin tone, and previous discrimination experiences were related to avoidance of contraceptive care because of perceived discrimination. RESULTS: Approximately one-third (31.5%) of the sample classified themselves as non-Hispanic Whites (31.5%), 22.4% as Black, 27.4% as Hispanic and born within the US, and 7.6% as Hispanic born outside of the US. Approximately one-third of women classified themselves in the lightest skin tones, whereas almost one in five women classified themselves in the darkest skin tone palates. Darker skin tones had increasingly greater odds of reporting that they avoided seeking birth control out of a concern for discrimination compared to the lightest skin tone. After adjusting for race/ethnicity and sociodemographic variables (model 3), darker skin tones remained significantly associated with avoiding birth control. DISCUSSION: This study demonstrates the role that skin color discrimination plays in negative reproductive health experiences. While this is not surprising given that those with racist ideologies developed the concept of these racial and ethnic categories, the apparent association with darker skin colors and avoidance of seeking birth control provides evidence that structural and individual racism continues to have far-reaching and insidious consequences. CONCLUSION: Contraception is recognized for reducing maternal mortality, improving child health, increasing female empowerment, and decreasing poverty. However, not all women equally enjoy the benefits of access to contraception. Addressing colorism within reproductive healthcare has become critically important as the nation becomes increasingly diverse. Focusing on skin tone-based discrimination and its roots in anti-blackness expands our understanding beyond a Black-White binary traditionally applied when addressing racism in healthcare delivery.

The War on Drugs, Racialized Capitalism, and Health Care Utilization Among White People Who Use Drugs in 22 Rural Appalachian Counties.

Objectives. To analyze War on Drugs encounters and their relationships to health care utilization among White people who use drugs (PWUD) in 22 Appalachian rural counties in Kentucky, West Virginia, Ohio, and North Carolina. Methods. We recruited White PWUD using chain referral sampling in 2018 to 2020. Surveys asked about criminal-legal encounters, unmet health care needs, and other covariates. We used generalized estimating equations to regress unmet need on criminal-legal encounters in multivariable models. Results. In this sample (n = 957), rates of stop and search, arrest, incarceration, and community supervision were high (44.0%, 26.8%, 36.3%, and 31.1%, respectively), as was unmet need (68.5%). Criminal-legal encounters were unrelated to unmet need (stops: adjusted prevalence ratio [APR] = 1.13; 95% confidence interval [CI] = 0.97, 1.32; arrest: APR = 0.95; 95% CI = 0.78, 1.15; incarceration: APR = 1.01; 95% CI = 0.89, 1.14; community supervision: APR = 0.99; 95% CI = 0.90, 1.09). Conclusions. Contrasting with findings from predominantly Black urban areas, criminal-legal encounters and unmet need were unrelated among White Appalachian PWUD. Research should explore whether and under what conditions White supremacy's benefits might buffer adverse impacts of the War on Drugs in Appalachia. (Am J Public Health. 2024;114(10):1086-1096. https://doi.org/10.2105/AJPH.2024.307744).

Spatial and spatio-temporal statistical implications for measuring structural racism: A review of three widely used residential segregation measures.

Social determinants of health are the conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning and quality of life outcomes and risks - these social determinants of health often aid in explaining the racial and ethnic health inequities present in the United States (US). The root cause of these social determinants of health has been tied to structural racism, and residential segregation is one such domain of structural racism that allows for the operationalization of the geography of structural racism. This review focuses on three residential segregation measures that are often utilized to capture segregation as a function of race/ethnicity, income, and simultaneously race/ethnicity and income. Empirical findings related to the spatial and spatio-temporal heterogeneity of these residential segregation measures are presented. We also discuss some of the implications of utilizing these three residential segregation measures.

Associations between Structural Racism, Environmental Burden, and Cancer Rates: An Ecological Study of US Counties.

Objective: In this study, we examined associations between county-level measures of structural racism and county-level cancer incidence and mortality rates between race groups while accounting for factors associated with cancer rates and county-level measures of environmental burden. Methods: To explore this relationship, we conducted multiple linear regression analyses. Data for these analyses came from an index of county-level structural racism and publicly available data on 2015 to 2019 age-adjusted cancer rates from the US Cancer Statistics Data Visualization Tool, 2019 County Health Rankings and Roadmaps, the Environmental Protection Agency's 2006 to 2010 Environmental Quality Index, and 2015 to 2019 estimates from the US Census American Community Survey. Results: County-level structural racism was associated with higher county cancer incidence rates among Black (adjusted incidence rate: 17.4, 95% confidence interval [95% CI]: 9.3, 25.5) and Asian/Pacific Islander populations (adjusted incidence rate: 9.3, 95% CI: 1.8, 16.9) and higher mortality rates for American Indian/Alaskan Native (adjusted mortality rate [AMR]: 17.4, 95% CI: 4.2, 30.6), Black (AMR: 11.9, 95% CI: 8.9, 14.8), and Asian/Pacific Islander (AMR: 4.7, 95% CI: 1.3, 8.1) populations than White populations. Conclusion: Our findings highlight the detrimental impact of structural racism on cancer outcomes among minoritized populations. Strategies aiming to mitigate cancer disparities must embed processes to recognize and address systems, policies, laws, and norms that create and reproduce patterns of discrimination.

Assessment of unmeasured confounding in the association between perceived discrimination and mental health in a predominantly African American cohort using g-estimation.

BACKGROUND: Perceived discrimination in health care settings can have adverse consequences on mental health in minority groups. However, the association between perceived discrimination and mental health is prone to unmeasured confounding. The study aims to quantitatively evaluate the influence of unmeasured confounding in this association, using g-estimation. METHODS: In a predominantly African American cohort, we applied g-estimation to estimate the association between perceived discrimination and mental health, adjusted and unadjusted for measured confounders. Mental health was measured using clinical diagnoses of anxiety, depression and bipolar disorder. Perceived discrimination was measured as the number of patient-reported discrimination events in health care settings. Measured confounders included demographic, socioeconomic, residential and health characteristics. The influence of confounding was denoted as α1 from g-estimation. We compared α1 for measured and unmeasured confounding. RESULTS: Strong associations between perceived discrimination in health care settings and mental health outcomes were observed. For anxiety, the odds ratio (95% confidence interval) unadjusted and adjusted for measured confounders were 1.30 (1.21, 1.39) and 1.26 (1.17, 1.36), respectively. The α1 for measured confounding was -0.066. Unmeasured confounding with α1=0.200, which was over three times that of measured confounding, corresponds to an odds ratio of 1.12 (1.01, 1.24). Similar results were observed for other mental health outcomes. CONCLUSION: Compared with measured confounding, unmeasured that was three times measured confounding was not enough to explain away the association between perceived discrimination and mental health, suggesting that this association is robust to unmeasured confounding. This study provides a novel framework to quantitatively evaluate unmeasured confounding.

Maori Medical Student and Physician Exposure to Racism, Discrimination, Harassment, and Bullying.

Importance: Discrimination, bullying, and harassment in medicine have been reported internationally, but exposures for Indigenous medical students and physicians, and for racism specifically, remain less examined. Objective: To examine the prevalence of racism, discrimination, bullying, and harassment for Maori medical students and physicians in New Zealand and associations with demographic and clinical characteristics. Design, Setting, and Participants: This cross-sectional study used data from an anonymous national survey of Maori medical students and physicians in New Zealand in late 2021 and early 2022. Data were analyzed from March 2022 to April 2024. Exposures: Age, gender, marginalized status (ie, in addition to being Maori, belonging to other groups traditionally marginalized or underrepresented in medicine), year of medical school, year of graduation, and main work role. Main Outcomes and Measures: Direct and witnessed racism, discrimination, bullying, and harassment were measured as any experience in the last year and ever. Any exposure to negative comments about social groups and witnessing discriminatory treatment toward Maori patients or whanau (extended family). Considering leaving medicine, including because of mistreatment, was measured. Results: Overall, 205 Maori medical students (median [IQR] age, 23.1 [21.6-24.3] years; 137 [67.2%] women) and 200 physicians (median [IQR] age, 36.6 [30.1-45.3] years; 123 [62.8%] women) responded. Direct and witnessed exposure to racism (184 students [91.5%]; 176 physicians [90.7%]) and discrimination (176 students [85.9%]; 179 physicians [89.5%]) ever in medical education, training, or work environments was common. Ever exposure to witnessed and direct bullying (123 students [66.5%]; 150 physicians [89.3%]) and harassment (73 students [39.5%]; 112 physicians [66.7%]) was also common. Most respondents reported witnessing Maori patients or their whanau being treated badly in clinical settings, in direct interactions (67 students [57.8%]; 112 physicians [58.9%]) or behind their backs (87 students [75.0%]; 138 physicians [72.6%]). One-quarter of Maori medical students (45 students), and 37.0% of physicians (61 physicians) had considered leaving or taken a break from medicine because of these experiences. Additional marginalized statuses were significantly associated with any direct experience of mistreatment in the last year for students and physicians. Exposure to some forms of mistreatment were also significantly associated with higher likelihood of thinking about leaving or taking a break from medicine for physicians. Conclusions and Relevance: In this study, Maori medical students and physicians reported high exposure to multiple forms of racism, discrimination, bullying, and harassment in medical education, training, and work environments, requiring an urgent response from medical institutions.

Fairness in Predicting Cancer Mortality Across Racial Subgroups.

Importance: Machine learning has potential to transform cancer care by helping clinicians prioritize patients for serious illness conversations. However, models need to be evaluated for unequal performance across racial groups (ie, racial bias) so that existing racial disparities are not exacerbated. Objective: To evaluate whether racial bias exists in a predictive machine learning model that identifies 180-day cancer mortality risk among patients with solid malignant tumors. Design, Setting, and Participants: In this cohort study, a machine learning model to predict cancer mortality for patients aged 21 years or older diagnosed with cancer between January 2016 and December 2021 was developed with a random forest algorithm using retrospective data from the Mount Sinai Health System cancer registry, Social Security Death Index, and electronic health records up to the date when databases were accessed for cohort extraction (February 2022). Exposure: Race category. Main Outcomes and Measures: The primary outcomes were model discriminatory performance (area under the receiver operating characteristic curve [AUROC], F1 score) among each race category (Asian, Black, Native American, White, and other or unknown) and fairness metrics (equal opportunity, equalized odds, and disparate impact) among each pairwise comparison of race categories. True-positive rate ratios represented equal opportunity; both true-positive and false-positive rate ratios, equalized odds; and the percentage of predictive positive rate ratios, disparate impact. All metrics were estimated as a proportion or ratio, with variability captured through 95% CIs. The prespecified criterion for the model's clinical use was a threshold of at least 80% for fairness metrics across different racial groups to ensure the model's prediction would not be biased against any specific race. Results: The test validation dataset included 43 274 patients with balanced demographics. Mean (SD) age was 64.09 (14.26) years, with 49.6% older than 65 years. A total of 53.3% were female; 9.5%, Asian; 18.9%, Black; 0.1%, Native American; 52.2%, White; and 19.2%, other or unknown race; 0.1% had missing race data. A total of 88.9% of patients were alive, and 11.1% were dead. The AUROCs, F1 scores, and fairness metrics maintained reasonable concordance among the racial subgroups: the AUROCs ranged from 0.75 (95% CI, 0.72-0.78) for Asian patients and 0.75 (95% CI, 0.73-0.77) for Black patients to 0.77 (95% CI, 0.75-0.79) for patients with other or unknown race; F1 scores, from 0.32 (95% CI, 0.32-0.33) for White patients to 0.40 (95% CI, 0.39-0.42) for Black patients; equal opportunity ratios, from 0.96 (95% CI, 0.95-0.98) for Black patients compared with White patients to 1.02 (95% CI, 1.00-1.04) for Black patients compared with patients with other or unknown race; equalized odds ratios, from 0.87 (95% CI, 0.85-0.92) for Black patients compared with White patients to 1.16 (1.10-1.21) for Black patients compared with patients with other or unknown race; and disparate impact ratios, from 0.86 (95% CI, 0.82-0.89) for Black patients compared with White patients to 1.17 (95% CI, 1.12-1.22) for Black patients compared with patients with other or unknown race. Conclusions and Relevance: In this cohort study, the lack of significant variation in performance or fairness metrics indicated an absence of racial bias, suggesting that the model fairly identified cancer mortality risk across racial groups. It remains essential to consistently review the model's application in clinical settings to ensure equitable patient care.

Quantification and visualization of US racial geography using the National Racial Geography Dataset 2020.

Racial geography studies the spatial distributions of multiracial populations. Technical challenges arise from the fact that US Census data, upon which all US-based studies rely, is only available in the form of spatial aggregates at a few levels of granularity. This negatively affects spatial analysis and, consequently, the quantification of racial segregation, especially on a smaller length scale. A recent methodology called the Racial Landscape (RL) stochastically disaggregates racial data at the level of census block aggregates into a grid of monoracial cells. RL-transformed racial data makes possible pattern-based, zoneless analysis, and visualization of racial geography. Here, we introduce the National Racial Geography Dataset 2020 (NRGD2020)-a collection of RL-based grids calculated from the 2020 census data and covering the entire conterminous US. It includes a virtual image layer for a bird's-eye-like view visualization of the spatial distribution of racial sub-populations, numerical grids for calculating racial diversity and segregation within user-defined regions, and precalculated maps of racial diversity and segregation on various length scales. NRGD2020 aims to facilitate and extend spatial analyses of racial geography and to make it more interpretable by tightly integrating quantitative analysis with visualization (mapping).

Epigenetic Aging and Racialized, Economic, and Environmental Injustice: NIMHD Social Epigenomics Program.

Importance: Epigenetic age acceleration is associated with exposure to social and economic adversity and may increase the risk of premature morbidity and mortality. However, no studies have included measures of structural racism, and few have compared estimates within or across the first and second generation of epigenetic clocks. Objective: To determine whether epigenetic age acceleration is positively associated with exposures to diverse measures of racialized, economic, and environmental injustice measured at different levels and time periods. Design, Setting, and Participants: This cross-sectional study used data from the My Body My Story (MBMS) study between August 8, 2008, and December 31, 2010, and examination 5 of the Multi-Ethnic Atherosclerosis Study (MESA) from April 1, 2010, to February 29, 2012. In the MBMS, DNA extraction was performed in 2021; linkage of structural measures to the MBMS and MESA, in 2022. US-born individuals were randomly selected from 4 community health centers in Boston, Massachusetts (MBMS), and 4 field sites in Baltimore, Maryland; Forsyth County, North Carolina; New York City, New York; and St Paul, Minnesota (MESA). Data were analyzed from November 13, 2021, to August 31, 2023. Main Outcomes and Measures: Ten epigenetic clocks (6 first-generation and 4 second-generation), computed using DNA methylation data (DNAm) from blood spots (MBMS) and purified monocytes (MESA). Results: The US-born study population included 293 MBMS participants (109 men [37.2%], 184 women [62.8%]; mean [SD] age, 49.0 [8.0] years) with 224 Black non-Hispanic and 69 White non-Hispanic participants and 975 MESA participants (492 men [50.5%], 483 women [49.5%]; mean [SD] age, 70.0 [9.3] years) with 229 Black non-Hispanic, 191 Hispanic, and 555 White non-Hispanic participants. Of these, 140 (11.0%) exhibited accelerated aging for all 5 clocks whose estimates are interpretable on the age (years) scale. Among Black non-Hispanic MBMS participants, epigenetic age acceleration was associated with being born in a Jim Crow state by 0.14 (95% CI, 0.003-0.27) SDs and with birth state conservatism by 0.06 (95% CI, 0.01-0.12) SDs, pooling across all clocks. Low parental educational level was associated with epigenetic age acceleration, pooling across all clocks, for both Black non-Hispanic (0.24 [95% CI, 0.08-0.39] SDs) and White non-Hispanic (0.27 [95% CI, 0.03-0.51] SDs) MBMS participants. Adult impoverishment was positively associated with the pooled second-generation clocks among the MESA participants (Black non-Hispanic, 0.06 [95% CI, 0.01-0.12] SDs; Hispanic, 0.07 [95% CI, 0.01-0.14] SDs; White non-Hispanic, 0.05 [95% CI, 0.01-0.08] SDs). Conclusions and Relevance: The findings of this cross-sectional study of MBMS and MESA participants suggest that epigenetic age acceleration was associated with racialized and economic injustice, potentially contributing to well-documented inequities in premature mortality. Future research should test the hypothesis that epigenetic accelerated aging may be one of the biological mechanisms underlying the well-documented elevated risk of premature morbidity and mortality among social groups subjected to racialized and economic injustice.

Risk management or racial Bias? The disparate use of restraints in the Emergency Department of an Urban Safety-Net Hospital.

OBJECTIVES: Limited data exist on racial-ethnic differences in the application of restraints for patients visitng the emergency department (ED). This study examines whether there is an association between race and patient ED visit type with the application of four-point mechanical restraints in a high acuity safety-net urban academic hospital. METHODS: The study retrospectively reviewed 198,610 visits to the ED at Boston Medical Center made by patients between 18 and 89 years old between May 1, 2014 and May 1, 2019. ED visit type was categorized based on primary billing code for the visit as either medical or behavioral; behavioral visits were further categorized into 5 groups based on corresponding primary psychiatric billing code category. The relationships between race/ethnicity and four-point mechanical restraints were analyzed using binary logistic regression models in SPSS. RESULTS: 1.4% of unique visits involved the use of four-point mechanical restraints. Patients with a behavioral visit were significantly over 16 times more likely to be restrained than those with a medical visit. Black patients were significantly more likely to be restrained than white patients for behavioral visits but less likely for medical visits. Black and Hispanic patients were also significantly more likely to be restrained for a behavioral visit regardless of psychiatric diagnosis. Asian patients were less likely to be restrained regardless of ED visit type. CONCLUSIONS: Significant racial differences in restraints for White patients with medical visits and Black and Hispanic patients with behavioral visits prompts further investigation on the role of clinician bias when managing acute patients.

Discrimination in Medical Settings across Populations: Evidence From the All of Us Research Program.

INTRODUCTION: Discrimination in medical settings (DMS) contributes to healthcare disparities in the United States, but few studies have determined the extent of DMS in a large national sample and across different populations. This study estimated the national prevalence of DMS and described demographic and health-related characteristics associated with experiencing DMS in seven different situations. METHODS: Survey data from 41,875 adults participating in the All of Us Research Program collected in 2021-2022 and logistic regression were used to examine the association between sociodemographic and health-related characteristics and self-reported DMS among adults engaged with a healthcare provider within the past 12 months. Statistical analysis was performed in 2023-2024. RESULTS: About 36.89% of adults reported having experienced at least one DMS situation. Adults with relative social and medical disadvantages had higher prevalence of experiencing DMS. Compared to their counterparts, respondents with higher odds of experiencing DMS in at least one situation identified as female, non-Hispanic Black, having at least some college, living in the South, renter, having other living arrangement, being publicly insured, not having a usual source of care, having multiple chronic conditions, having any disability, and reporting fair or poor health, p<0.05. CONCLUSIONS: The findings indicate a high prevalence of DMS, particularly among some population groups. Characterizing DMS may be a valuable tool for identifying populations at risk within the healthcare system and optimizing the overall patient care experience. Implementing relevant policies remains an essential strategy for mitigating the prevalence of DMS and reducing healthcare disparities.

Neighborhood Racial Composition and Unequal Exposure to Violent Crime in Everyday Contexts.

Exposure to violence is a critical aspect of contemporary racial inequality in the United States. While extensive research has examined variations in violent crime rates across neighborhoods, less attention has been given to understanding individuals' everyday exposure to violent crimes. This study investigates patterns of exposure to violent crimes among neighborhood residents using cell phone mobility data and violent crime reports from Chicago. The analysis reveals a positive association between the proportion of Black residents in a neighborhood and the level of exposure to violent crimes experienced by residents. Controlling for a neighborhood's level of residential disadvantage and other neighborhood characteristics did not substantially diminish the relationship between racial composition and exposure to violent crimes in everyday life. Even after controlling for violence within residents' neighborhoods, individuals residing in Black neighborhoods continue to experience significantly higher levels of violence in their day-to-day contexts compared to those living in White neighborhoods. This suggests that racial segregation in everyday exposures, rather than residential segregation, plays a central role in racial inequality in exposure to violence. Additionally, the analysis suggests that neighborhoods with more Hispanic and Asian residents are exposed to less and more violent crime, respectively, compared to neighborhoods with more White residents. However, this is only observed when not adjusting for the volume of visits points of interest receive; otherwise, the finding is reversed. This study offers valuable insights into potentially novel sources of racial disparities in exposure to violent crimes in everyday contexts, highlighting the need for further investigation.

Do digital technologies reduce racially biased reporting? Evidence from NYPD administrative data.

Recent work has emphasized the disproportionate bias faced by minorities when interacting with law enforcement. However, research on the topic has been hampered by biased sampling in administrative data, namely that records of police interactions with citizens only reflect information on the civilians that police elect to investigate, and not civilians that police observe but do not investigate. In this work, we address a related bias in administrative police data which has received less empirical attention, namely reporting biases around investigations that have taken place. Further, we investigate whether digital monitoring tools help mitigate this reporting bias. To do so, we examine changes in reports of interactions between law enforcement and citizens in the wake of the New York City Police Department's replacement of analog memo books with mobile smartphones. Results from a staggered difference in differences estimation indicate a significant increase in reports of citizen stops once the new smartphones are deployed. Importantly, we observe that the rise is driven by increased reports of "unproductive" stops, stops involving non-White citizens, and stops occurring in areas characterized by a greater concentration of crime and non-White residents. These results reinforce the recent observation that prior work has likely underestimated the extent of racial bias in policing. Further, they highlight that the implementation of digital monitoring tools can mitigate the issue to some extent.

Food insecurity and childhood outcomes: a cross-sectional analysis of 2016-2020 National Survey of Children's Health data.

CONTEXT: Racial inequalities across social determinants of health (SDOHs) are often influenced by discriminatory policies that reinforce systems that further uphold these disparities. There is limited data describing the influence of food insecurity (FI) on childhood racial discrimination. OBJECTIVES: Our objective was to determine if the likelihood of experiencing racial discrimination was exacerbated by FI. METHODS: We conducted a cross-sectional analysis of the 2016-2020 National Survey of Children's Health (NSCH) to extract data on childhood racial discrimination and food security. We extracted sociodemographic variables to utilize as controls and constructed logistic regression models to determine associations, via odds ratios (ORs), between food security and whether the child experienced racial discrimination. RESULTS: We found statistically significant associations between experiencing FI and childhood racial discrimination. Individuals who experienced food shortages were significantly more likely to experience racial discrimination compared to those without food limitations when controlling for race, food voucher usage, age, and % federal poverty guidelines (FPG, adjusted odds ratio [AOR]: 3.34; 95 % CI: 2.69-4.14). CONCLUSIONS: Our study found that parents of minority children all reported high rates of racial discrimination, which was exacerbated by concurrent FI. Children of families that were the most food insecure reported the highest percentage of racial discrimination at 11.13 %, compared with children who always had enough nutritious meals to eat at 2.87 %. Acknowledging the intersection that exists between FI, race, gender, and socioeconomic status (SES), might be a way forward in addressing the adverse health effects experienced by food-insecure children and adults.

White men can't jump, but do they still get picked first? Race and player selection in the NBA draft, 1980-2021.

Despite excelling at recruiting Black players, studies have repeatedly produced evidence of racial discrimination in the National Basketball Association (NBA). Through this study, we re-examine the topic of racial discrimination within the NBA through an analysis of the Association's annual entry draft. Using a novel dataset, we statistically model the relationship between player race and draft pick number using pooled data from 1980 to 2021. Overall, we find only limited evidence of racial discrimination. These findings are generally robust to sub-sample analyses, alternative specifications of our race variable, and alternate statistical modeling techniques. However, analyses performed on sub-samples of draft picks that participated in the NBA combine-and for whom we have measurements of player athleticism-produce some evidence of racial discrimination. Through such models we estimate that Black players are picked roughly three picks later in the draft. We consider the implications of these findings for contemporary theorizing about racial discrimination in the NBA and more mainstream labor markets.

Bien qu'elle excelle dans le recrutement de joueurs noirs, des études ont démontré à plusieurs reprises l'existence d'une discrimination raciale au sein de la National Basketball Association (NBA). Dans le cadre de cette étude, nous réexaminons le sujet de la discrimination raciale au sein de la NBA en analysant la sélection annuelle (draft) de l'association. À l'aide d'un nouvel ensemble de données, nous modélisons statistiquement la relation entre la race du joueur et le numéro de sélection à la draft en utilisant des données regroupées de 1980 à 2021. Dans l'ensemble, nous ne trouvons que des preuves limitées de discrimination raciale. Ces résultats sont généralement robustes aux analyses de sous­échantillons, aux spécifications alternatives de notre variable raciale et aux autres techniques de modélisation statistique. Toutefois, les analyses effectuées sur des sous­échantillons de sélectionnés ayant participé au NBA combine­et pour lesquels nous disposons de mesures de l'athlétisme des joueurs­produisent certains éléments de preuve de la discrimination raciale. Grâce à ces modèles, nous estimons que les joueurs noirs sont sélectionnés environ 3 fois plus tard dans la draft. Nous théorisons les implications de ces résultats pour les théories contemporaines sur la discrimination raciale dans la NBA et les marchés du travail ordinaires.