Structural racism contributes to health disparities between U.S. non-Hispanic Black and non-Hispanic white populations by differentially distributing resources used to maintain health. Policies that equitably redistribute resources may mitigate racialized health disparities. Using National Longitudinal Study of Adolescent to Adult Health data and time-to-event parametric g-formula methods, we investigate a hypothetical intervention to reduce Black-white family income inequities on racialized differences in self-rated health (N=11,312) and obesity (N=10,547). We first intervene to increase individual Black family incomes by $11,000, creating Black-white equity in median incomes in 1995. Then, we measure social multiplier effects by additionally increasing county-level Black median household incomes by $11,000. By Wave 4, individual, direct effects models comparing Black intervention to Black control groups show no risk differences in self-rated health (RD=-0.009; 95% CI: -0.026, 0.008) or obesity (RD=0.003; 95% CI: -0.017, 0.023). Social multiplier effects models suggestively reduce Black-white inequalities in obesity by increasing obesity in white intervention versus white control groups (RD=0.050=; 95% CI: -0.011, 0.110), but exacerbate Black-white disparities in self-rated health by reducing self-rated health in Black intervention versus white control groups (RD=0.184; 95% CI: 0.018, 0.351). In this cohort, income transfers may not reduce racialized disparities in obesity and self-rated health.

UNASSIGNED: To determine whether Black women in Michigan communities outside of Flint were more likely than women in other racial and ethnic groups to report negative emotional reactions to the Flint Water Crisis, an ongoing public health disaster that has been widely attributed to anti-Black structural racism.
UNASSIGNED: Data were from a 2020 survey of Michigan women aged 18-45 in communities outside of Flint (N=888). We used logistic regression models to examine racial and ethnic differences in the odds of negative emotional reactions to the Flint Water Crisis.
UNASSIGNED: Compared with Black women, White women had lower odds of feeling scared (odds ratio [OR]=0.58; 95% CI, 0.40-0.84), hopeless (OR=0.53; 95% CI, 0.38-0.74), tired (OR=0.45; 95% CI, 0.32-0.64), and numb (OR=0.52; 95% CI, 0.35-0.75) when thinking about the water crisis. There were no differences between Black and Hispanic women, whereas women of other races or ethnicities had lower odds than Black women of feeling numb (OR=0.32; 95% CI, 0.14-0.72).
UNASSIGNED: The Flint Water Crisis was a racialized stressor, with potential implications for mental health inequities among Michigan women who were not directly affected by the crisis.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.

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.

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.

UNASSIGNED: The incidence of sudden unexpected infant death (SUID) in the United States has persisted at roughly the same level since the mid-2000s, despite intensive prevention efforts around safe sleep. Disparities in outcomes across racial and socioeconomic lines also persist. These disparities are reflected in the spatial distribution of cases across neighborhoods. Strategies for prevention should be targeted precisely in space and time to further reduce SUID and correct disparities.
UNASSIGNED: We sought to aid neighborhood-level prevention efforts by characterizing communities where SUID occurred in Cook County, IL, from 2015 to 2019 and predicting where it would occur in 2021-2025 using a semiautomated, reproducible workflow based on open-source software and data.
UNASSIGNED: This cross-sectional retrospective study queried geocoded medical examiner data from 2015-2019 to identify SUID cases in Cook County, IL, and aggregated them to \"communities\" as the unit of analysis. We compared demographic factors in communities affected by SUID versus those unaffected using Wilcoxon rank sum statistical testing. We used social vulnerability indicators from 2014 to train a negative binomial prediction model for SUID case counts in each given community for 2015-2019. We applied indicators from 2020 to the trained model to make predictions for 2021-2025.
UNASSIGNED: Validation of our query of medical examiner data produced 325 finalized cases with a sensitivity of 95% (95% CI 93%-97%) and a specificity of 98% (95% CI 94%-100%). Case counts at the community level ranged from a minimum of 0 to a maximum of 17. A map of SUID case counts showed clusters of communities in the south and west regions of the county. All communities with the highest case counts were located within Chicago city limits. Communities affected by SUID exhibited lower median proportions of non-Hispanic White residents at 17% versus 60% (P<.001) and higher median proportions of non-Hispanic Black residents at 32% versus 3% (P<.001). Our predictive model showed moderate accuracy when assessed on the training data (Nagelkerke R2=70.2% and RMSE=17.49). It predicted Austin (17 cases), Englewood (14 cases), Auburn Gresham (12 cases), Chicago Lawn (12 cases), and South Shore (11 cases) would have the largest case counts between 2021 and 2025.
UNASSIGNED: Sharp racial and socioeconomic disparities in SUID incidence persisted within Cook County from 2015 to 2019. Our predictive model and maps identify precise regions within the county for local health departments to target for intervention. Other jurisdictions can adapt our coding workflows and data sources to predict which of their own communities will be most affected by SUID.

The purpose of this article is to discuss the evolution of the University of New Mexico (UNM) Nurse-Midwifery Education Program, its impact on New Mexico communities, and the vision moving forward for the program in a rural and culturally diverse state. New Mexico has a rich history of community-based midwifery and the UNM Nurse-Midwifery Education Program, founded in 1991, is rooted in this tradition. Graduates are prepared to practice in rural and underserved communities, advance birth equity, and decrease perinatal health disparities. Faculty have advanced the program mission to improve the health and well-being of New Mexico families through diversifying the midwifery workforce, growing community collaboration, and engaging in research and scholarship activities aimed at promoting access to care. Program faculty recognize the critical need to address factors underpinning the rising maternal morbidity and mortality crisis, including rurality, poverty, and structural racism. These efforts have yielded positive results, with 60% of program graduates serving New Mexico communities and increasingly diverse midwifery student cohorts (70% of currently enrolled students). Efforts to support midwifery student success are bolstered through a recently awarded Health Resources and Services Administration Maternity Care Nursing Workforce Expansion grant. Through such endeavors, the program will continue to strive toward social justice and human dignity.

The health outcomes of an individual are shaped by a combination of genetic predisposition and environmental influences. While some diseases stem solely from environmental factors, others like atopic eczema, also known as neurodermatitis or atopic dermatitis, are multifaceted, with environmental variables playing a significant role in its initiation and severity. Atopic eczema is a prevalent chronic condition observed globally, particularly in Western industrialized nations where its prevalence is estimated to range from 2.5% to 3.5% in adults and 10% to 15% among children. The increasing incidence of atopic eczema in industrialized countries over recent decades suggests that this trend may be due to environmental changes rather than genetic predispositions. Therefore, by thoroughly examining environmental factors and their role in atopic dermatitis, one may be able to gain a better understanding of its disease pattern and develop possible preventative measures. This article provides a comprehensive analysis of how the surrounding environment contributes to the pathogenesis of atopic eczema.

BACKGROUND: Structural racism contributes to geographical inequalities in pre-exposure prophylaxis (PrEP) coverage in the United States (US). This study aims to investigate county-level variability in PrEP utilization across diverse dimensions of structural racism.
METHODS: The 2013-2021 nationwide county-level PrEP rate and PrEP-to-need ratio (PNR) data were retrieved from AIDSVu. PrEP rate was defined as the number of PrEP users per 100,000 population, and PNR was defined as the ratio of PrEP users to new HIV diagnoses per calendar year. Linear mixed effect regression was employed to identify associations of county-level structural racism (e.g., structural racism in housing and socioeconomic status) with PrEP rate and PNR on a nationwide scale of the US.
RESULTS: From 2013 to 2021, the mean PrEP rate and PNR increased from 3.62 to 71.10 and from 0.39 to 10.20, respectively. Counties with more structural racism in housing were more likely to have low PrEP rates (adjusted β =  - 5.80, 95% CI [- 8.84, - 2.75]). Higher PNR was found in counties with lower structural racism in socioeconomic status (adjusted β =  - 2.64, 95% CI [- 3.68, - 1.61]). Regionally, compared to the Midwest region, counties in the West region were more likely to have higher PrEP rate (adjusted β = 30.99, 95% CI [22.19, 39.80]), and counties in the South had lower PNR (adjusted β =  - 1.87, 95% CI [- 2.57, - 1.17]).
CONCLUSIONS: County-level structural racism plays a crucial role in understanding the challenges of scaling up PrEP coverage. The findings underscore the importance of tailored strategies across different regions and provide valuable insights for future interventions to optimize PrEP implementation.

This commentary highlights a need for comprehensive measures of structural racism tailored to cancer health disparities, in particular Black-White disparities in multiple myeloma (MM). Recent political and social calls and advances in the ability to quantitate structural racism have led to rapidly growing research on the health consequences of structural racism. However, to date, most studies have used unidimensional measures of structural racism that do not capture cumulative influences or enable the identification of factors most responsible for driving disparities. Furthermore, measures may not reflect aspects of structural racism most relevant to underlying disease processes and risks. This study proposes a multifaceted approach to measuring structural racism relevant to MM that includes comprehensive, disease- and at-risk population-tailored social and environmental data and biomarkers of susceptibility and progression related to underlying biological changes associated with structural racism. Such novel measures of structural racism may improve the ability to assess the influence of structural racism on cancer health disparities, which may advance understanding of disease etiology and differences observed by racialized groups.