Racism and health and wellbeing among children and youth-An updated systematic review and meta-analysis.

BACKGROUND: Evidence of racism's health harms among children and youth is rapidly increasing, though attention to impacts on physical health and biomarker outcomes is more emergent. We performed a systematic review of recent publications to examine the association between racism and health among children and youth, with a meta-analysis of the specific relationships between racism and physical health and biomarkers. METHODS: We conducted a systematic literature search using four databases: Medline, PsycINFO, PubMed, and ERIC. Four inclusion criteria were used to identify eligible studies: (1) exposure was experiences of racism, (2) outcome was health and wellbeing, (3) quantitative methods were used to estimate the association between racism and health outcomes, and (4) the effect size of associations between racism and health and wellbeing was reported for participants aged 0-24 years. Correlation coefficients were used to report the pooled effect size for each outcome indicator. RESULTS: There were 463 eligible studies included in the screening process, with 42 studies focusing on physical health or biomarker outcomes. Random-effects meta-analysis found minimal to moderate positive associations between racism and C-reactive protein, Interleukin 6, body mass index (BMI), obesity, systolic blood pressure, salivary cortisol, asthma, and somatic symptoms. There were marginal positive associations between racism and Tumour Necrosis Factor-α, cortisol collected via saliva, urine and hair, BMI-z score, and diastolic blood pressure, with imprecise estimates and wide confidence intervals. CONCLUSIONS: Racism is associated with negative physical health and biomarker outcomes that relate to multiple physiological systems and biological processes in childhood and adolescence. This has implications for health and wellbeing during childhood and adolescence and future chronic disease risk. Collective and structural changes to eliminate racism and create a healthy and equitable future for all children and youth are urgently required.

Multidimensional structural racism and estimated cancer risk from traffic-related air pollution.

BACKGROUND: Traffic-related air pollutants have been associated with a variety of adverse human health impacts, including cancers. In the United States, numerous studies have documented racial inequities in neighborhood exposures to traffic-related air pollution. Emerging evidence suggests that structural racism may influence neighborhood exposures to air pollutants. However, existing research has largely focused on residential racial segregation, one indicator of structural racism. This study developed a multidimensional measure of structural racism to examine the relationship between structural racism and estimated cancer risk from air pollutants in Georgia. METHODS: Carcinogenic air toxics data were obtained from the US Environmental Protection Agency's 2019 Air Toxics Screening Assessment and sociodemographic data from the American Community Survey. Guided by stakeholder input, county-level data on residential segregation, education, employment, incarceration, economic status, political participation, and homeownership were used to create a multidimensional county-level structural racism index. Relative risks (RRs) were estimated for associations between structural racism and elevated (top 10% in Georgia) estimated cancer risk from air toxics. RESULTS: Multilevel analyses revealed a significant association between multidimensional structural racism and exposure to carcinogenic traffic-related air pollutants. Neighborhoods in the highest quartile of structural racism exhibited an elevated cancer risk from traffic-related air pollutants (RR, 7.84; 95% CI, 5.11-12.05) compared to neighborhoods with lower levels of structural racism. CONCLUSIONS: Multidimensional structural racism was associated with estimated cancer risk from traffic-related air pollution in Georgia. Findings can inform future studies and policy interventions that address racial inequalities in exposure to traffic-related air pollution.

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.

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.

Exploring the Association Between Structural Racism and Mental Health: Geospatial and Machine Learning Analysis.

BACKGROUND: Structural racism produces mental health disparities. While studies have examined the impact of individual factors such as poverty and education, the collective contribution of these elements, as manifestations of structural racism, has been less explored. Milwaukee County, Wisconsin, with its racial and socioeconomic diversity, provides a unique context for this multifactorial investigation. OBJECTIVE: This research aimed to delineate the association between structural racism and mental health disparities in Milwaukee County, using a combination of geospatial and deep learning techniques. We used secondary data sets where all data were aggregated and anonymized before being released by federal agencies. METHODS: We compiled 217 georeferenced explanatory variables across domains, initially deliberately excluding race-based factors to focus on nonracial determinants. This approach was designed to reveal the underlying patterns of risk factors contributing to poor mental health, subsequently reintegrating race to assess the effects of racism quantitatively. The variable selection combined tree-based methods (random forest) and conventional techniques, supported by variance inflation factor and Pearson correlation analysis for multicollinearity mitigation. The geographically weighted random forest model was used to investigate spatial heterogeneity and dependence. Self-organizing maps, combined with K-means clustering, were used to analyze data from Milwaukee communities, focusing on quantifying the impact of structural racism on the prevalence of poor mental health. RESULTS: While 12 influential factors collectively accounted for 95.11% of the variability in mental health across communities, the top 6 factors-smoking, poverty, insufficient sleep, lack of health insurance, employment, and age-were particularly impactful. Predominantly, African American neighborhoods were disproportionately affected, which is 2.23 times more likely to encounter high-risk clusters for poor mental health. CONCLUSIONS: The findings demonstrate that structural racism shapes mental health disparities, with Black community members disproportionately impacted. The multifaceted methodological approach underscores the value of integrating geospatial analysis and deep learning to understand complex social determinants of mental health. These insights highlight the need for targeted interventions, addressing both individual and systemic factors to mitigate mental health disparities rooted in structural racism.

Structural Racism as a Contributor to Lung Cancer Incidence and Mortality Rates Among Black Populations in the United States.

BACKGROUND: Although racial disparities in lung cancer incidence and mortality have diminished in recent years, lung cancer remains the second most diagnosed cancer among US Black populations. Many factors contributing to disparities in lung cancer are rooted in structural racism. To quantify this relationship, we examined associations between a multidimensional measure of county-level structural racism and county lung cancer incidence and mortality rates among Black populations, while accounting for county levels of environmental quality. METHODS: We merged 2016-2020 data from the United States Cancer Statistics Data Visualization Tool, a pre-existing county-level structural racism index, the Environmental Protection Agency's 2006-2010 Environmental Quality Index (EQI), 2023 County Health Rankings, and the 2021 United States Census American Community Survey. We conducted multivariable linear regressions to examine associations between county-level structural racism and county-level lung cancer incidence and mortality rates. RESULTS: Among Black males and females, each standard deviation increase in county-level structural racism score was associated with an increase in county-level lung cancer incidence of 6.4 (95% CI: 4.4, 8.5) cases per 100,000 and an increase of 3.3 (95% CI: 2.0, 4.6) lung cancer deaths per 100,000. When examining these associations stratified by sex, larger associations between structural racism and lung cancer rates were observed among Black male populations than among Black females. CONCLUSION: Structural racism contributes to both the number of new lung cancer cases and the number of deaths caused by lung cancer among Black populations. Those aiming to reduce lung cancer cases and deaths should consider addressing racism as a root-cause.

Historic Redlining and Impact of Structural Racism on Diabetes Prevalence in a Nationally Representative Sample of U.S. Adults.

OBJECTIVE: We investigated direct and indirect relationships between historic redlining and prevalence of diabetes in a U.S. national sample. RESEARCH DESIGN AND METHODS: Using a previously validated conceptual model, we hypothesized pathways between structural racism and prevalence of diabetes via discrimination, incarceration, poverty, substance use, housing, education, unemployment, and food access. We combined census tract-level data, including diabetes prevalence from the Centers for Disease Control and Prevention PLACES 2019 database, redlining using historic Home Owners' Loan Corporation (HOLC) maps from the Mapping Inequality project, and census data from the Opportunity Insights database. HOLC grade (a score between 1 [best] and 4 [redlined]) for each census tract was based on overlap with historically HOLC-graded areas. The final analytic sample consisted of 11,375 U.S. census tracts. Structural equation modeling was used to investigate direct and indirect relationships adjusting for the 2010 population. RESULTS: Redlining was directly associated with higher crude prevalence of diabetes within a census tract (r = 0.01; P = 0.008) after adjusting for the 2010 population (χ2(54) = 69,900.95; P < 0.001; root mean square error of approximation = 0; comparative fit index = 1). Redlining was indirectly associated with diabetes prevalence via incarceration (r = 0.06; P < 0.001), poverty (r = -0.10; P < 0.001), discrimination (r = 0.14; P < 0.001); substance use (measured by binge drinking: r = -0.65, P < 0.001; and smoking: r = 0.35, P < 0.001), housing (r = 0.06; P < 0.001), education (r = -0.17; P < 0.001), unemployment (r = -0.17; P < 0.001), and food access (r = 0.14; P < 0.001) after adjusting for the 2010 population. CONCLUSIONS: Redlining has significant direct and indirect relationships with diabetes prevalence. Incarceration, poverty, discrimination, substance use, housing, education, unemployment, and food access may be possible targets for interventions aiming to mitigate the impact of structural racism on diabetes.

Factors leading to disparity in lung cancer diagnosis among black/African American communities in the USA: a qualitative study.

OBJECTIVE: This study has two objectives: first, to explore the diagnostic experiences of black/African American (BAA) patients with lung cancer to pinpoint pitfalls, suboptimal experiences and instances of discrimination leading to disparities in outcomes compared with patients of other ethnic backgrounds, especially white patients. The second objective is to identify the underlying causes contributing to health disparities in the diagnosis of lung cancer among BAA patients. METHODS: We employed a phenomenological research approach, guiding in-depth interviews with patients self-identifying as BAA diagnosed with lung cancer, as well as caregivers, healthcare professionals and community advocates knowledgeable about BAA experiences with lung cancer. We performed thematic analysis to identify experiences at patient, primary care and specialist levels. Contributing factors were identified using the National Institute of Minority Health and Health Disparities (NIMHD) health disparity model. RESULTS: From March to November 2021, we conducted individual interviews with 19 participants, including 9 patients/caregivers and 10 providers/advocates. Participants reported recurring and increased pain before seeking treatment, treatment for non-cancer illnesses, delays in diagnostic tests and referrals, poor communication and bias when dealing with specialists and primary care providers. Factors contributing to suboptimal experiences included reluctance by insurers to cover costs, provider unwillingness to conduct comprehensive testing, provider bias in recommending treatment, high healthcare costs, and lack of healthcare facilities and qualified staff to provide necessary support. However, some participants reported positive experiences due to their insurance, availability of services and having an empowered support structure. CONCLUSIONS: BAA patients and caregivers encountered suboptimal experiences during their care. The NIMHD model is a useful framework to organise factors contributing to these experiences that may be leading to health disparities. Additional research is needed to fully capture the extent of these experiences and identify ways to improve BAA patient experiences in the lung cancer diagnosis pathway.

Associations among discrimination, psychological functioning, and substance use among US Black adults aged 18-28: Moderation by racial attribution and sex.

INTRODUCTION: Discrimination is associated with poor mental health and substance use among Black Americans, but research is needed on mediators and moderators of these relationships. This study tested whether: 1) discrimination is associated with current alcohol, tobacco (cigarette or e-cigarette), and cannabis use among US Black emerging adults; 2) psychological distress (PD) and positive well-being (PW) are mediators of discrimination-substance use relationships; and 3) these relationships are moderated by sex and attributions to discrimination (racial vs. nonracial). METHODS: Using data from a 2017 US nationally representative survey, we conducted bivariate and multiple-group moderated mediation analyses among 1118 Black American adults aged 18-28. The study assessed discrimination and attribution to discrimination using the Everyday Discrimination scale, past 30-day PD with the Kessler-6 scale, and past 30-day PW with the Mental Health Continuum Short Form. We utilized probit regression for all structural equation models and adjusted final models for age. RESULTS: Discrimination was positively associated with past 30-day cannabis and tobacco use directly and indirectly through PD in the overall model. Among males who reported race as the sole/main attribution to discrimination, discrimination was positively associated with alcohol, cannabis, and tobacco use through PD. Among females who reported race as the sole/main attribution to discrimination, discrimination was positively associated with cannabis use through PD. Discrimination was positively associated with tobacco use among those who reported nonracial attributions to discrimination and with alcohol use among those whose attribution was not assessed. Discrimination was positively associated with PD among those who reported race as a secondary attribution to discrimination. CONCLUSIONS: Discrimination specifically attributed to race may contribute to greater PD and in turn alcohol, cannabis, and tobacco use among Black emerging adults, especially males. Future substance use prevention and treatment efforts targeted to Black American emerging adults may benefit from addressing racial discrimination and PD.

Association between major discrimination and deficit accumulation in African American cancer survivors: The Detroit Research on Cancer Survivors Study.

BACKGROUND: Discrimination can adversely affect health and accelerate aging, but little is known about these relationships in cancer survivors. This study examines associations of discrimination and aging among self-identified African American survivors. METHODS: A population-based sample of 2232 survivors 20-79 years old at diagnosis were enrolled within 5 years of breast (n = 787), colorectal (n = 227), lung (n = 223), or prostate (n = 995) cancer between 2017 and 2022. Surveys were completed post-active therapy. A deficit accumulation index measured aging-related disease and function (score range, 0-1, where <0.20 is robust, 0.20 to <0.35 is pre-frail, and 0.35+ is frail; 0.06 is a large clinically meaningful difference). The discrimination scale assessed ever experiencing major discrimination and seven types of events (score, 0-7). Linear regression tested the association of discrimination and deficit accumulation, controlling for age, time from diagnosis, cancer type, stage and therapy, and sociodemographic variables. RESULTS: Survivors were an average of 62 years old (SD, 9.6), 63.2% reported ever experiencing major discrimination, with an average of 2.4 (SD, 1.7) types of discrimination events. Only 24.4% had deficit accumulation scores considered robust (mean score, 0.30 [SD, 0.13]). Among those who reported ever experiencing major discrimination, survivors with four to seven types of discrimination events (vs. 0-1) had a large, clinically meaningful increase in adjusted deficits (0.062, p < .001) and this pattern was consistent across cancer types. CONCLUSION: African American cancer survivors have high deficit accumulated index scores, and experiences of major discrimination were positively associated with these deficits. Future studies are needed to understand the intersectionality between aging, discrimination, and cancer survivorship among diverse populations.

Race, Concern About COVID-19 Discrimination, and Cigarette Smoking Behavior: Comparison Between US Asian and White Adults Who Use Commercial Tobacco.

Anti-Asian discrimination incidents in the USA have resurged during the COVID-19 pandemic. It is unclear how concern about being discriminatorily treated due to the COVID-19 pandemic varies between Asian and Asian American (A&AsA) and White adults. We examined A&AsA vs. White differences in concern about COVID-19 discrimination and associations of this concern with changes in cigarette smoking behaviors before and during the pandemic. Data were from a US representative sample of A&AsA and White adults (≥ 21 years) who currently and formerly used commercial tobacco (n = 1052), collected through an online panel oversampling A&AsA adults in January-February 2021. Participants reported their concern, worry, and stress about COVID-19 discrimination and past-30-day cigarette consumption before and during the pandemic. We examined the association between race and overall concern about COVID-19 discrimination, and this concern's associations with changes in past-30-day cigarette smoking consumption, smoking continuation, and return to smoking using weighted multivariable logistic and linear regression models. Overall concern about COVID-19 discrimination was higher (adjusted mean = 1.7, standard error = 0.16) among A&AsA adults who currently and formerly used commercial tobacco than their White counterparts (adjusted mean = 0.60, standard error = 0.04; p < 0.01). Overall concern about COVID-19 discrimination was associated with increased past-30-day cigarette consumption by 26.5 cigarettes (95% confidence interval [CI] = 1.2-51.9) and 4.4 times (95% CI = 2.3-8.5) greater odds of return to smoking among adults who smoke cigarettes. A&AsA adults who currently and formerly used commercial tobacco disproportionately bore higher concern about COVID-19 discrimination, and in turn could lead to increased smoking behavior and related morbidity and mortality among A&AsA adults.

Unmasking bias and perception of lead surgeons in the operating room: A simulation based study.

BACKGROUND: Perception of a surgeon based on physical attributes in the operating room (OR) environment has not been assessed, which was our primary goal. METHODS: A common OR scenario was simulated using 8 different actors as a lead surgeon with combinations of age (<40 vs. >55), race (white vs. black), and gender (male vs. female). One video scenario with a survey was electronically distributed to surgeons, residents, and OR nurses/staff. The overall rating, assessment, and perception of the lead surgeon were assessed. RESULTS: Of 974 respondents, 64.5% were females. There were significant differences in the rating and assessment based upon surgeon's age (p = .01) favoring older surgeons. There were significant differences in the assessments of surgeons by the study group (p = .03). The positive assessments as well as perceptions trended highest towards male, older, and white surgeons, especially in the stressful situation. CONCLUSION: While perception of gender bias may be widespread, age and race biases may also play a role in the OR. Inter-professional education training for OR teams could be developed to help alleviate such biases.

Mortgage Lending Bias and Breast Cancer Survival Among Older Women in the United States.

PURPOSE: The objective was to examine the relationship between contemporary redlining (mortgage lending bias on the basis of property location) and survival among older women with breast cancer in the United States. METHODS: A redlining index using Home Mortgage Disclosure Act data (2007-2013) was linked by census tract with a SEER-Medicare cohort of 27,516 women age 66-90 years with an initial diagnosis of stage I-IV breast cancer in 2007-2009 and follow-up through 2015. Cox proportional hazards models were used to examine the relationship between redlining and both all-cause and breast cancer-specific mortality, accounting for covariates. RESULTS: Overall, 34% of non-Hispanic White, 57% of Hispanic, and 79% of non-Hispanic Black individuals lived in redlined tracts. As the redlining index increased, women experienced poorer survival. This effect was strongest for women with no comorbid conditions, who comprised 54% of the sample. For redlining index values of 1 (low), 2 (moderate), and 3 (high), as compared with 0.5 (least), hazard ratios (HRs) (and 95% CIs) for all-cause mortality were HR = 1.10 (1.06 to 1.14), HR = 1.27 (1.17 to 1.38), and HR = 1.39 (1.25 to 1.55), respectively, among women with no comorbidities. A similar pattern was found for breast cancer-specific mortality. CONCLUSION: Contemporary redlining is associated with poorer breast cancer survival. The impact of this bias is emphasized by the pronounced effect even among women with health insurance (Medicare) and no comorbid conditions. The magnitude of this neighborhood level effect demands an increased focus on upstream determinants of health to support comprehensive patient care. The housing sector actively reveals structural racism and economic disinvestment and is an actionable policy target to mitigate adverse upstream health determinants for the benefit of patients with cancer.

Racial Discrimination and Stress Across the Life Course: Associations With Prenatal Inflammation, Perceived Stress, and Depressive Symptoms.

BACKGROUND: Among Black Americans, interpersonal racial discrimination is common. Stress, including following discrimination, contributes to pregnancy complications. In this secondary analysis, we provide data on associations among discrimination, stress, and their interaction across the life course and inflammation, perceived stress, and depressive symptoms during pregnancy. METHODS: During the early third trimester, Black American women (n = 93) completed the Experiences of Discrimination Scale, the Stress and Adversity Inventory, the Perceived Stress Scale, and the Center for Epidemiological Studies Depression Inventory. Plasma interleukin-6 (IL-6), IL-8, tumor necrosis factor-α (TNF-α), and IL-ß levels were quantified. Associations were examined by linear regression, controlling for demographic, behavioral, and clinical covariates. RESULTS: Associations among racial discrimination and plasma IL-8, TNF-α, and IL-ß levels depended upon average ratings of life course stress. When stress was low, discrimination in the mid tertile was associated with the highest levels of IL-8, TNF-α, and IL-ß. Subscale analyses suggested that findings related to IL-8 were driven by chronic stress whereas findings related to TNF-α and IL-ß were driven by acute stress. When examined together, greater discrimination but not greater life course stress was associated with higher prenatal perceived stress. In subscale analyses, the association between discrimination and prenatal perceived stress depended upon average ratings of life course acute stress. When acute stress was low, discrimination in the midtertile was associated with the highest levels of prenatal perceived stress. When acute stress was high, discrimination in the high tertile was associated with the highest levels of prenatal perceived stress. There were also direct associations among greater life course chronic stress, prenatal perceived stress, and prenatal depressive symptoms. Associations were attenuated when discrimination was included as a covariate. CONCLUSIONS: The current analyses suggest that, among Black Americans, prenatal inflammation, perceived stress, and depressive symptoms may be shaped by racial discrimination and stress across the life course. In many cases, associations among discrimination and prenatal parameters depended upon how stressful exposures to life course stressors had been rated. The data suggest the potential for adaptive plasticity under some stress and highlight the deleterious nature of compounding stress.

Maternal Experiences of Racial Discrimination, Child Indicators of Toxic Stress, and the Minding the Baby Early Home Visiting Intervention.

BACKGROUND: Racism is a significant source of toxic stress and a root cause of health inequities. Emerging evidence suggests that exposure to vicarious racism (i.e., racism experienced by a caregiver) is associated with poor child health and development, but associations with biological indicators of toxic stress have not been well studied. It is also unknown whether two-generation interventions, such as early home visiting programs, may help to mitigate the harmful effects of vicarious racism. OBJECTIVE: The purpose of this study was to examine associations between maternal experiences of racial discrimination and child indicators of toxic stress and to test whether relationships are moderated by prior participation in Minding the Baby (MTB), an attachment-based early home visiting intervention. METHODS: Ninety-seven maternal-child dyads (n = 43 intervention dyads, n = 54 control dyads) enrolled in the MTB Early School Age follow-up study. Mothers reported on racial discrimination using the Experiences of Discrimination Scale. Child indicators of toxic stress included salivary biomarkers of inflammation (e.g., C-reactive protein, panel of pro-inflammatory cytokines), body mass index, and maternally reported child behavioral problems. We used linear regression to examine associations between maternal experiences of racial discrimination and child indicators of toxic stress and included an interaction term between experiences of discrimination and MTB group assignment (intervention vs. control) to test moderating effects of the MTB intervention. RESULTS: Mothers identified as Black/African American (33%) and Hispanic/Latina (64%). In adjusted models, maternal experiences of racial discrimination were associated with elevated salivary interleukin-6 and tumor necrosis factor-α levels in children, but not child body mass index or behavior. Prior participation in the MTB intervention moderated the relationship between maternal experiences of discrimination and child interleukin-6 levels. DISCUSSION: Results of this study suggest that racism may contribute to the biological embedding of early adversity through influences on inflammation, but additional research with serum markers is needed to better understand this relationship. Improved understanding of the relationships among vicarious racism, protective factors, and childhood toxic stress is necessary to inform family and systemic-level intervention.

Moderate-to-Severe Tobacco Use Disorder and Discrimination Among U.S. Sexual Minority Older Adults.

OBJECTIVES: The dearth of research on age-related differences in risk factors for tobacco use disorder (TUD) among sexual minorities, particularly among older adults, can obscure the differential needs of sexual minority age groups for tobacco prevention and cessation. We examined the association of cumulative ethnic/racial discrimination and sexual orientation discrimination with moderate-to-severe TUD among U.S. sexual minority adults aged 50 years and older. METHOD: We analyzed cross-sectional data from the National Epidemiologic Survey of Alcohol and Related Conditions-III (n = 36,309 U.S. adults). Our sample consisted of 1,258 adults (lesbian/gay-, bisexual-, and heterosexual-identified adults with same-sex attraction/behavior) aged ≥50 years. Multivariable logistic regression analyses estimated the association of cumulative lifetime ethnic/racial discrimination and sexual orientation discrimination with past-year moderate-to-severe TUD and tested whether the association differed for adults aged 50-64 years versus those aged ≥65 years. RESULTS: An estimated 8.1% of the sample met criteria for moderate-to-severe TUD. Lifetime ethnic/racial discrimination and sexual orientation discrimination was not significantly associated with moderate-to-severe TUD for adults aged ≥50 years. However, a significant 2-way interaction was found between discrimination and age. In age-stratified analyses, greater discrimination was significantly associated with greater risk for moderate-to-severe TUD for adults aged ≥65 years, but not adults aged 50-64 years. DISCUSSION: Greater cumulative discrimination based on ethnicity/race and sexual orientation was associated with increased risk for moderate-to-severe TUD among sexual minority adults aged ≥65 years. Our findings underscore the importance of age considerations in understanding the role of discrimination in the assessment and treatment of TUD.

Firearm homicide mortality is influenced by structural racism in US metropolitan areas.

INTRODUCTION: Metropolitan cities in the United States suffer from higher rates of gun violence. However, the specific structural factors associated with increased gun violence are poorly defined. We hypothesized that firearm homicide in metropolitan cities would be impacted by Black-White segregation index. METHODS: This cross-sectional analysis evaluated 51 US metropolitan statistical areas (MSAs) using data from 2013 to 2017. Several measures of structural racism were examined, including the Brooking Institute's Black-White segregation index. Demographic data were derived from the US Census Bureau, US Department of Education, and US Department of Labor. Crime data and firearm homicide mortality rates were obtained from the Federal Bureau of Investigation and the Centers for Disease Control. Spearman ρ and linear regression were performed. RESULTS: Firearm mortality was associated with multiple measures of structural racism and racial disparity, including White-Black segregation index, unemployment rate, poverty rate, single parent household, percent Black population, and crime rates. In regression analysis, percentage Black population exhibited the strongest association with firearm homicide mortality (ß = 0.42, p < 0.001). Black-White segregation index (ß = 0.41, p = 0.001) and percent children living in single-parent households (ß = 0.41, p = 0.002) were also associated with higher firearm homicide mortality. Firearm legislation scores were associated with lower firearm homicide mortality (ß = -0.20 p = 0.02). High school and college graduation rates were not associated with firearm homicide mortality and were not included in the final model. CONCLUSION: Firearm homicide disproportionately impacts communities of color and is associated with measures of structural racism, such as White-Black segregation index. Public health interventions targeting gun violence must address these systemic inequities. Furthermore, given the association between firearm mortality and single-parent households, intervention programs for at-risk youth may be particularly effective. LEVEL OF EVIDENCE: Epidemiological level II.