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Residential racial segregation in the U.S. has been hypothesized as a fundamental cause driving health disparities across racial groups. Potential mechanisms include economic and social marginalization, subsequent constrained opportunities, and high stress. Yet evidence on residential segregation's association with health among Black and White children-particularly longitudinally-is sparse. This study aims to address this gap. We used data from the Panel Study of Income Dynamics (PSID), a national longitudinal study of U.S. households, analyzing information on 1,251 Black and 1,427 White children who participated in the Child Development Supplement (CDS) at least twice (survey waves 1997, 2002, 2007, 2014). We fit individual fixed-effects models to estimate the within-person association of neighborhood-level residential segregation, measured with local Getis-Ord G* statistics, with three outcomes (general health, weight status, and behavioral problems). We examined heterogeneous effects by age and sex. We also examined associations between health and childhood segregation trajectories, i.e., the pattern of children's residential segregation exposures from birth through when their health outcomes were measured, providing additional insight on dynamic experiences of segregation. In fixed effects models, among Black children, higher segregation was associated with worse self-rated health, especially for Black children who were older (aged 11-17 years). In trajectory models, among White children, moving out of highly segregated neighborhoods was associated with a lower probability of poor self-rated health, while moving into those neighborhoods or back and forth between neighborhood types were both associated with increased behavioral problems. Our findings highlight the importance of early-life residential segregation in shaping persistent racial health disparities, as well as the costs of segregation for all children living in highly segregated neighborhoods.

BackgroundCardiovascular disease (CVD) disproportionately affects Black adults in the United States. This is increasingly acknowledged to be due to inequitable distribution of health-promoting resources. One potential contributor is inequities in educational opportunities, although it is unclear what aspects of education are most salient. School racial segregation may affect cardiovascular health by increasing stress, constraining socioeconomic opportunities, and altering health behaviors. We investigated the association between school segregation and Black adults' CVD risk.Methods and findingsWe leveraged a natural experiment created by quasi-random (i.e., arbitrary) timing of local court decisions since 1991 that released school districts from court-ordered desegregation. We used the Panel Study of Income Dynamics (PSID) (1991 to 2017), linked with district-level school segregation measures and desegregation court order status. The sample included 1,053 Black participants who ever resided in school districts that were under a court desegregation order in 1991. The exposure was mean school segregation during observed schooling years. Outcomes included several adult CVD risk factors and outcomes. We fitted standard ordinary least squares (OLS) multivariable linear regression models, then conducted instrumental variables (IV) analysis, using the proportion of schooling years spent in districts that had been released from court-ordered desegregation as an instrument. We adjusted for individual- and district-level preexposure confounders, birth year, and state fixed effects. In standard linear models, school segregation was associated with a lower probability of good self-rated health (-0.05 percentage points per SD of the segregation index; 95% CI: -0.08, -0.03; p < 0.001) and a higher probability of binge drinking (0.04 percentage points; 95% CI: 0.002, 0.07; p = 0.04) and heart disease (0.01 percentage points; 95% CI: 0.002, 0.15; p = 0.007). IV analyses also found that school segregation was associated with a lower probability of good self-rated health (-0.09 percentage points; 95% CI: -0.17, -0.02, p = 0.02) and a higher probability of binge drinking (0.17 percentage points; 95% CI: 0.04, 0.30, p = 0.008). For IV estimates, only binge drinking was robust to adjustments for multiple hypothesis testing. Limitations included self-reported outcomes and potential residual confounding and exposure misclassification.ConclusionsSchool segregation exposure in childhood may have longstanding impacts on Black adults' cardiovascular health. Future research should replicate these analyses in larger samples and explore potential mechanisms. Given the recent rise in school segregation, this study has implications for policies and programs to address racial inequities in CVD.

Background: Personal Health literacy (PHL) is essential in cardiovascular risk management. Hindrances in PHL can lead to poor cardiovascular outcomes. Purpose: To investigate whether limited PHL is associated with lower likelihoods of i) overall cardiovascular health and ii) individual cardiovascular health components as defined by the American Heart Association's Life Simple (LS7). Methods: Multi-Ethnic Study of Atherosclerosis participants (N = 3719; median age[range]: 59[45-84]) completed a PHL questionnaire in 2016-2018. PHL was classified as limited (score [greater than or equal to]10) or adequate (score <10). LS7 components were measured in 2000-2002. Robust Poisson regression was employed to compute prevalence ratios and 95% confidence intervals (PR[95%CI]) of LS7 measures. Results: 14.7% of participants had limited PHL. Limited PHL was associated with lower likelihoods of optimal LS7 (0.69[0.50, 0.95], p = 0.02) and average LS7 (0.95[0.88, 1.02], p = 0.15) after adjustment. Limited PHL was significantly associated with a 7% lower likelihood of ideal fasting blood glucose level after adjustment (0.93[0.89, 0.98], p < 0.01). Discussion: Limited PHL was modestly associated with suboptimal cardiovascular health and elevated blood glucose, independent of income and education. Translation to Health Education Practice: Health educators and providers should equitably address PHL barriers to improve cardiovascular management and quality of care for patients and communities.

ObjectivesFew researchers have evaluated whether school racial segregation, a key manifestation of structural racism, affects child health, despite its potential impacts on school quality, social networks, and stress from discrimination. We investigated whether school racial segregation affects Black children's health and health behaviors.MethodsWe estimated the association of school segregation with child health, leveraging a natural experiment in which school districts in recent years experienced increased school segregation. School segregation was operationalized as the Black-White dissimilarity index. We used ordinary least squares models as well as quasi-experimental instrumental variables analysis, which can reduce bias from unobserved confounders. Data from the Child Development Supplement of the Panel Study of Income Dynamics (1997-2014, n = 1248 Black children) were linked with district-level school segregation measures. Multivariable regressions were adjusted for individual-, neighborhood-, and district-level covariates. We also performed subgroup analyses by child sex and age.ResultsIn instrumental variables models, a one standard deviation increase in school segregation was associated with increased behavioral problems (2.53 points on a 27-point scale; 95% CI, 0.26 to 4.80), probability of having ever drunk alcohol (0.23; 95% CI, 0.049 to 0.42), and drinking at least monthly (0.20; 95% CI, 0.053 to 0.35). School segregation was more strongly associated with drinking behaviors among girls.ConclusionsSchool segregation was associated with worse outcomes on several measures of well-being among Black children, which may contribute to health inequities across the life span. These results highlight the need to promote school racial integration and support Black youth attending segregated schools.

Racial residential segregation is associated with multiple adverse health outcomes in Black individuals. Yet, the influence of structural racism and racial residential segregation on brain aging is less understood. In this study, we investigated the association between cumulative exposure to racial residential segregation over 25 years (1985-2010) in young adulthood, as measured by the Getis-Ord Gi* statistic, and year 25 measures of brain volume (cerebral, gray matter, white matter, and hippocampal volumes) in midlife. We studied 290 Black participants with available brain imaging data who were enrolled in the Coronary Artery Risk Development in Young Adults (CARDIA) Study, a prospective cohort study. CARDIA investigators originally recruited 2,637 Black participants aged 18-30 years from 4 field centers across the United States. We conducted analyses using marginal structural models, incorporating inverse probability of treatment weighting and inverse probability of censoring weighting. We found that compared with low/medium segregation, greater cumulative exposure to a high level of racial residential segregation throughout young adulthood was associated with smaller brain volumes in general (e.g., for cerebral volume, β = -0.08, 95% confidence interval: -0.15, -0.02) and with a more pronounced reduction in hippocampal volume, though results were not statistically significant. Our findings suggest that exposure to segregated neighborhoods may be associated with worse brain aging.

Background Residential segregation, a geospatial manifestation of structural racism, is a fundamental driver of racial and ethnic health inequities, and longitudinal studies examining segregation's influence on cardiovascular health are limited. This study investigates the impact of segregation on hypertension in a multiracial and multiethnic cohort and explores whether neighborhood environment modifies this association. Methods and Results Leveraging data from a diverse cohort of adults recruited from 6 sites in the United States with 2 decades of follow-up, we used race- and ethnicity-stratified Cox models to examine the association between time-varying segregation with incident hypertension in 1937 adults free of hypertension at baseline. Participants were categorized as residing in segregated and nonsegregated neighborhoods using a spatial-weighted measure. We used a robust covariance matrix estimator to account for clustering within neighborhoods and assessed effect measure modification by neighborhood social or physical environment. Over an average follow-up of 7.35 years, 65.5% non-Hispanic Black, 48.1% Chinese, and 53.7% Hispanic participants developed hypertension. Net of confounders, Black and Hispanic residents in segregated neighborhoods were more likely to develop hypertension relative to residents in nonsegregated neighborhoods (Black residents: hazard ratio [HR], 1.33; 95% CI, 1.09-1.62; Hispanic residents: HR, 1.33; 95% CI, 1.04-1.70). Results were similar but not significant among Chinese residents (HR, 1.20; 95% CI, 0.83-1.73). Among Black residents, neighborhood social environment significantly modified this association such that better social environment was associated with less pronounced impact of segregation on hypertension. Conclusions This study underscores the importance of continued investigations of groups affected by the health consequences of racial residential segregation while taking contextual neighborhood factors, such as social environment, into account.

Cardiovascular disease disparities are shaped by differences in risk factors across racial and ethnic groups. Housing remains an important social determinant of health. The objective of this statement is to review and summarize research that has examined the associations of housing status with cardiovascular health and overall health. PubMed/Medline, Centers for Disease Control and Prevention data, US Census data, Cochrane Library reviews, and the annual Heart Disease and Stroke Statistics report from the American Heart Association were used to identify empirical research studies that examined associations of housing with cardiovascular health and overall well-being. Health is affected by 4 prominent dimensions of housing: stability, quality and safety, affordability and accessibility, and neighborhood environment. Vulnerable and underserved populations are adversely affected by housing insecurity and homelessness, are at risk for lower-quality and unsafe housing conditions, confront structural barriers that limit access to affordable housing, and are at risk for living in areas with substandard built environment features that are linked to cardiovascular disease. Research linking select pathways to cardiovascular health is relatively strong, but research gaps in other housing pathways and cardiovascular health remain. Efforts to eliminate cardiovascular disease disparities have recently emphasized the importance of social determinants of health. Housing is a prominent social determinant of cardiovascular health and well-being and should be considered in the evaluation of prevention efforts to reduce and eliminate racial/ethnic and socioeconomic disparities.

Socioeconomic status (SES) is a multi‐faceted theoretical construct associated with stroke risk and outcomes. Knowing which SES measures best correlate with population stroke metrics would improve its accounting in observational research and inform interventions. Using the Centers for Disease Control and Prevention's (CDC) Population Level Analysis and Community Estimates (PLACES) and other publicly available databases, we conducted an ecological study comparing correlations of different United States county‐level SES, health care access and clinical risk factor measures with age‐adjusted stroke prevalence. The prevalence of adults living below 150% of the federal poverty level most strongly correlated with stroke prevalence compared to other SES and non‐SES measures (correlation coefficient = 0.908, R2 = 0.825; adjusted partial correlation coefficient: 0.589, R2 = 0.347). ANN NEUROL 2024;96:739–744 [ABSTRACT FROM AUTHOR]

Risk factors can drive socioeconomic inequalities in cardiovascular disease (CVD) through differential exposure and differential vulnerability. In this paper, we show how econometric decomposition directly enables simultaneous, policy-oriented assessment of these 2 mechanisms. We specifically estimate contributions of neighborhood environment and proximal risk factors to socioeconomic inequality in CVD incidence via these mechanisms. We followed 5,608 participants in the Multi-Ethnic Study of Atherosclerosis (2000-2012) to their first CVD event (median length of follow-up, 12.2 years). We used a summary measure of baseline socioeconomic position (SEP). Covariates included baseline demographics, neighborhood characteristics, and psychosocial, behavioral, and biomedical risk factors. Using Poisson models, we decomposed the difference (inequality) in incidence rates between low- and high-SEP groups into contributions of 1) differences in covariate means (differential exposure) and 2) differences in CVD risk associated with covariates (differential vulnerability). Notwithstanding large uncertainty in neighborhood estimates, our analysis suggested that differential exposure to poorer neighborhood socioeconomic conditions, adverse social environment, diabetes, and hypertension accounted for most of the inequality. Psychosocial and behavioral contributions were negligible. Further, neighborhood SEP, female sex, and white race were more strongly associated with CVD among low-SEP (vs. high-SEP) participants. These differentials in vulnerability also accounted for nontrivial portions of the inequality and could have important implications for intervention.

Using data from the Multi-Ethnic Study of Atherosclerosis baseline sample from 2000 to 2002 (N=5263; mean age=62) we examined cross-sectional racial/ethnic differences in ideal CVH, defined by the American Heart Association 2020 Impact Goals as a summary measure of ideal levels of blood pressure, fasting glucose, cholesterol, body mass index, diet, physical activity, and smoking. Using three different analytical approaches, we examined differences before and after adjustment for neighborhood socioeconomic, physical, and social environments. Significant racial/ethnic differences were present for all indicators of ideal CVH (excluding physical activity). Additional adjustments for neighborhood factors produced modest reductions in racial/ethnic differences. Future research is necessary to better understand the impact of neighborhood context on health disparities using longitudinal study designs.