How people are exposed to neighborhoods racially different from their own.

In US cities, neighborhoods have long been racially segregated. However, people do not spend all their time in their neighborhoods, and the consequences of residential segregation may be tempered by the contact people have with other racial groups as they traverse the city daily. We examine the extent to which people's regular travel throughout the city is to places "beyond their comfort zone" (BCZ), i.e., to neighborhoods of racial composition different from their own-and why. Based on travel patterns observed in more than 7.2 million devices in the 100 largest US cities, we find that the average trip is to a neighborhood less than half as racially different from the home neighborhood as it could have been given the city. Travel to grocery stores is least likely to be BCZ; travel to gyms and parks, most likely; however, differences are greatest across cities. For the first ~10 km people travel from home, neighborhoods become increasingly more BCZ for every km traveled; beyond that point, whether neighborhoods do so depends strongly on the city. Patterns are substantively similar before and after COVID-19. Our findings suggest that policies encouraging more 15-min travel-that is, to amenities closer to the home-may inadvertently discourage BCZ movement. In addition, promoting use of certain "third places" such as restaurants, bars, and gyms, may help temper the effects of residential segregation, though how much it might do so depends on city-specific conditions.

Estimating experienced racial segregation in US cities using large-scale GPS data.

We estimate a measure of segregation, experienced isolation, that captures individuals' exposure to diverse others in the places they visit over the course of their days. Using Global Positioning System (GPS) data collected from smartphones, we measure experienced isolation by race. We find that the isolation individuals experience is substantially lower than standard residential isolation measures would suggest but that experienced isolation and residential isolation are highly correlated across cities. Experienced isolation is lower relative to residential isolation in denser, wealthier, more educated cities with high levels of public transit use and is also negatively correlated with income mobility.

Using machine learning to estimate the effect of racial segregation on COVID-19 mortality in the United States.

This study examines the role that racial residential segregation has played in shaping the spread of COVID-19 in the United States as of September 30, 2020. The analysis focuses on the effects of racial residential segregation on mortality and infection rates for the overall population and on racial and ethnic mortality gaps. To account for potential confounding, I assemble a dataset that includes 50 county-level factors that are potentially related to residential segregation and COVID-19 infection and mortality rates. These factors are grouped into eight categories: demographics, density and potential for public interaction, social capital, health risk factors, capacity of the health care system, air pollution, employment in essential businesses, and political views. I use double-lasso regression, a machine learning method for model selection and inference, to select the most important controls in a statistically principled manner. Counties that are 1 SD above the racial segregation mean have experienced mortality and infection rates that are 8% and 5% higher than the mean. These differences represent an average of four additional deaths and 105 additional infections for each 100,000 residents in the county. The analysis of mortality gaps shows that, in counties that are 1 SD above the Black-White segregation mean, the Black mortality rate is 8% higher than the White mortality rate. Sensitivity analyses show that an unmeasured confounder that would overturn these findings is outside the range of plausible covariates.

Banking for the Culture: Black-owned banks as cultural assets during the subprime lending boom.

Today, black-owned banks are important financial resources challenging economic exclusion. Nevertheless, they do not associate strongly with building black wealth. Some scholars argue this signals black-owned banks are ornamental, or ineffective responses to legacies of economic exclusion in black segregated neighborhoods. To engage these critiques, I draw on the dialectical theoretical frames of cultural assets and structural deficits to examine the effectiveness of black-owned banks during the subprime lending boom-a period when bank practices exploiting a history of economic exclusion in black segregated neighborhoods intensify. Specifically, I analyze administrative data from the Federal Deposit Insurance Corporation (FDIC) and the Home Mortgage Disclosure Act (HMDA) to assess whether black-owned banks associate with access to mortgage credit when the subprime lending boom peaks in 2006. Using propensity score matching with inverse probability weighting, I find black-owned banks do not associate with mortgage originations in 2006; but neighborhoods with black-owned banks receive fewer subprime mortgage loans, compared to matched ones without them. As such, black-owned banks appear to effectively shield black segregated neighborhoods from the time period's predation. Overall, findings imply black-owned banks support protective credit markets during periods of intensifying economic exclusion and exploitation.

Disparities in Cardiovascular Mortality Between Black and White Adults in the United States, 1999 to 2019.

BACKGROUND: Black adults experience a disproportionately higher burden of cardiovascular risk factors and disease in comparison with White adults in the United States. Less is known about how sex-based disparities in cardiovascular mortality between these groups have changed on a national scale over the past 20 years, particularly across geographic determinants of health and residential racial segregation. METHODS: We used CDC WONDER (Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research) to identify Black and White adults age ≥25 years in the United States from 1999 to 2019. We calculated annual age-adjusted cardiovascular mortality rates (per 100 000) for Black and White women and men, as well as absolute rate differences and rate ratios to compare the mortality gap between these groups. We also examined patterns by US census region, rural versus urban residence, and degree of neighborhood segregation. RESULTS: From 1999 to 2019, age-adjusted mortality rates declined overall for both Black and White adults. There was a decline in age-adjusted cardiovascular mortality among Black (602.1 to 351.8 per 100 000 population) and White women (447.0 to 267.5), and the absolute rate difference (ARD) between these groups decreased over time (1999: ARD, 155.1 [95% CI, 149.9-160.3]; 2019: ARD, 84.3 [95% CI, 81.2-87.4]). These patterns were similar for Black (824.1 to 526.3 per 100 000) and White men (637.5 to 396.0; 1999: ARD, 186.6 [95% CI, 178.6-194.6]; 2019: ARD, 130.3 [95% CI, 125.6-135.0]). Despite this progress, cardiovascular mortality in 2019 was higher for Black women (rate ratio, 1.32 [95% CI, 1.30-1.33])- especially in the younger (age <65 years) subgroup (rate ratio, 2.28 [95% CI, 2.23-2.32])-as well as for Black men (rate ratio, 1.33 [95% CI, 1.32-1.34]), compared with their respective White counterparts. There was regional variation in cardiovascular mortality patterns, and the Black-White gap differed across rural and urban areas. Cardiovascular mortality rates among Black women and men were consistently higher in communities with high levels of racial segregation compared with those with low to moderate levels. CONCLUSIONS: During the past 2 decades, age-adjusted cardiovascular mortality declined significantly for Black and White adults in the United States, as did the absolute difference in death rates between these groups. Despite this progress, Black women and men continue to experience higher cardiovascular mortality rates than their White counterparts.

What Would It Take to Desegregate U.S. Metropolitan Areas? Pathways to Residential Desegregation by Race.

Patterns of household mobility across neighborhoods reproduce patterns of racial segregation at the metropolitan level. Substantial literature across the social sciences has explored the scale and predictors of household mobility as well as changes in metropolitan residential segregation over time. This study unifies these two strands of inquiry by connecting the sorting of households across neighborhoods to aggregate changes in segregation levels. Using discrete choice models of intrametropolitan mobility and restricted decennial census and American Community Survey data for 1960-2014, I model the correlates of household mobility and identify the counterfactual scenarios under which lower segregation levels can be achieved. The results show that even though the mobility flows of the White, Black, Hispanic, and Asian populations across census tracts have become more similar over time, U.S. metropolitan areas are far from experiencing large drops in segregation.

Racial Segregation and Respiratory Outcomes among Urban Black Residents with and at Risk of Chronic Obstructive Pulmonary Disease.

Rationale: Racial residential segregation has been associated with worse health outcomes, but the link with chronic obstructive pulmonary disease (COPD) morbidity has not been established.Objectives: To investigate whether racial residential segregation is associated with COPD morbidity among urban Black adults with or at risk of COPD.Methods: Racial residential segregation was assessed using isolation index, based on 2010 decennial census and baseline address, for Black former and current smokers in the multicenter SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), a study of adults with or at risk for COPD. We tested the association between isolation index and respiratory symptoms, physiologic outcomes, imaging parameters, and exacerbation risk among urban Black residents, adjusting for established COPD risk factors, including smoking. Additional mediation analyses were conducted for factors that could lie on the pathway between segregation and COPD outcomes, including individual and neighborhood socioeconomic status, comorbidity burden, depression/anxiety, and ambient pollution.Measurements and Main Results: Among 515 Black participants, those residing in segregated neighborhoods (i.e., isolation index ⩾0.6) had worse COPD Assessment Test score (ß = 2.4; 95% confidence interval [CI], 0.7 to 4.0), dyspnea (modified Medical Research Council scale; ß = 0.29; 95% CI, 0.10 to 0.47), quality of life (St. George's Respiratory Questionnaire; ß = 6.1; 95% CI, 2.3 to 9.9), and cough and sputum (ß = 0.8; 95% CI, 0.1 to 1.5); lower FEV1% predicted (ß = -7.3; 95% CI, -10.9 to -3.6); higher rate of any and severe exacerbations; and higher percentage emphysema (ß = 2.3; 95% CI, 0.7 to 3.9) and air trapping (ß = 3.8; 95% CI, 0.6 to 7.1). Adverse associations attenuated with adjustment for potential mediators but remained robust for several outcomes, including dyspnea, FEV1% predicted, percentage emphysema, and air trapping.Conclusions: Racial residential segregation was adversely associated with COPD morbidity among urban Black participants and supports the hypothesis that racial segregation plays a role in explaining health inequities affecting Black communities.

How education and racial segregation intersect in neighborhoods with persistently low COVID-19 vaccination rates in Philadelphia.

BACKGROUND: COVID-19 infection has disproportionately affected socially disadvantaged neighborhoods. Despite this disproportionate burden of infection, these neighborhoods have also lagged in COVID-19 vaccinations. To date, we have little understanding of the ways that various types of social conditions intersect to explain the complex causes of lower COVID-19 vaccination rates in neighborhoods. METHODS: We used configurational comparative methods (CCMs) to study COVID-19 vaccination rates in Philadelphia by neighborhood (proxied by zip code tabulation areas). Specifically, we identified neighborhoods where COVID-19 vaccination rates (per 10,000) were persistently low from March 2021 - May 2021. We then assessed how different combinations of social conditions (pathways) uniquely distinguished neighborhoods with persistently low vaccination rates from the other neighborhoods in the city. Social conditions included measures of economic inequities, racial segregation, education, overcrowding, service employment, public transit use, health insurance and limited English proficiency. RESULTS: Two factors consistently distinguished neighborhoods with persistently low COVID-19 vaccination rates from the others: college education and concentrated racial privilege. Two factor values together - low college education AND low/medium concentrated racial privilege - identified persistently low COVID-19 vaccination rates in neighborhoods, with high consistency (0.92) and high coverage (0.86). Different values for education and concentrated racial privilege - medium/high college education OR high concentrated racial privilege - were each sufficient by themselves to explain neighborhoods where COVID-19 vaccination rates were not persistently low, likewise with high consistency (0.93) and high coverage (0.97). CONCLUSIONS: Pairing CCMs with geospatial mapping can help identify complex relationships between social conditions linked to low COVID-19 vaccination rates. Understanding how neighborhood conditions combine to create inequities in communities could inform the design of interventions tailored to address COVID-19 vaccination disparities.

Racial Preferences for Schools: Evidence from an Experiment with White, Black, Latinx, and Asian Parents and Students.

Most U.S. students attend racially segregated schools. To understand this pattern, I employ a survey experiment with New York City families actively choosing schools and investigate whether they express racialized school preferences. I find school racial composition heterogeneously affects white, black, Latinx, and Asian parents' and students' willingness to attend schools. Independent of characteristics potentially correlated with race, white and Asian families preferred white schools over black and Latinx schools, Latinx families preferred Latinx schools over black schools, and black families preferred black schools over white schools. Results, importantly, demonstrate that racial composition has larger effects on white and Latinx parents' preferences compared with white and Latinx students and smaller effects on black parents compared with black students. To ensure results were not an artifact of experimental conditions, I validate findings using administrative data on New York City families' actual school choices in 2013. Both analyses establish that families express heterogenous racialized school preferences.

Racial Disparities in Health Among College-Educated African Americans: Can Attendance at Historically Black Colleges or Universities Reduce the Risk of Metabolic Syndrome in Midlife?

We expand on existing understandings of health disparities among middle-class African Americans by examining how the postsecondary educational context gives rise to the unequal distribution of health. We used panel data (1994-2009) from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to estimate whether the risk of developing metabolic syndrome by midlife significantly differs for African Americans who attended Historically Black College or Universities (HBCUs) versus predominantly White institutions. We found that HBCU enrollment was associated with a 35% reduction in the odds of metabolic syndrome. Furthermore, we demonstrate that HBCU attendees who grew up in more segregated environments experienced the greatest reductions in the likelihood of developing metabolic syndrome. Our results underscore the important role that HBCUs play in the lives of African Americans and suggest their impacts go far beyond traditional benchmarks of socioeconomic achievement to include key health outcomes.

A Spatial Analysis of Obesity: Interaction of Urban Food Environments and Racial Segregation in Chicago.

The obesity rate in Chicago has increased up to more than 30% in the last two decades. Obesity is a major problem in Chicago, where 36% of the city's high school students and 61% of adults in the metropolitan area are overweight or obese. Simultaneously, Chicago remains highly segregated by race-a phenomenon that begs for spatial analysis of health. Extant work exploring associations between the food retail environment and obesity has provided mixed findings, and virtually, none of this work has been done with the effects of the interaction between racial segregation and the food retail environment on obesity, where obesity rates are among the highest in the segregation area for the city defined by racial segregation. This study explores whether being overweight or obese is associated with urban food environments, such as access to different types of food retail outlets, and how its associations interact with racial factors, at the community level. This study uses the 2016-2018 data from the Healthy Chicago Survey to investigate the spatial variations in obesity and their association with food environments in Chicago. Also, this study examines the moderating effects of racial segregation on associations between obesity and access to food retail outlets. Using spatial statistics and regression models with interaction terms, this study assesses how the urban food environment can interact with racial segregation to explain the spatial distribution of obesity. The results indicate that the obesity population is highly concentrated in the African American community. In Chicago, each additional convenience store in a community is associated with a 0.42% increase in the obesity rate. Fast food restaurant access is predictive of a greater obesity rate, and grocery store access is predictive of less obesity rate in a community with a higher percentage of African American population. Findings can be used to promote equitable access to food retail outlets, which may help reduce broader health inequities in Chicago.

Racial/ethnic minority segregation and low birth weight in five North American cities.

Comparisons of communities across cities are rare in social epidemiology. Our prior work exploring racial/ethnic segregation and the prevalence of low birth weight (LBW) in communities from two large urban cities showed a strong relationship in Chicago and a very weak relationship in Toronto. This study extends that work by examining the association between racial/ethnic minority segregation and LBW in total of 307 communities in five North American cities: Baltimore, Boston, Chicago, Philadelphia, and Toronto. We used Pearson correlation coefficients and OLS regression models to examine potential variability in the association between racial/ethnic minority segregation and LBW, controlling for community-level unemployment. In a combined model with community-level data from all cities, a 10% increase in minority composition is associated with a 0.7% increase in LBW. While racial/ethnic minority segregation and unemployment are not associated with LBW in Toronto, these social determinants have strong and significant associations with LBW across communities in the four US cities in the analysis. Subsequent models revealed opposite effects for percentage non-Hispanic Black and percentage Hispanic. Across communities in the US cities in this analysis, there is considerable similarity in the strength of the effect of racial/ethnic segregation on LBW. Future work should incorporate communities from additional cities, looking to identify community assets and public policies that allow some minority communities to thrive, while other minority communities suffer from a high prevalence of LBW. More work is also needed on the generalizability of these patterns to other health outcomes.

Relationship of Racial Residential Segregation to Newly Diagnosed Cases of HIV among Black Heterosexuals in US Metropolitan Areas, 2008-2015.

Social science and public health literature has framed residential segregation as a potent structural determinant of the higher HIV burden among black heterosexuals, but empirical evidence has been limited. The purpose of this study is to test, for the first time, the association between racial segregation and newly diagnosed heterosexually acquired HIV cases among black adults and adolescents in 95 large US metropolitan statistical areas (MSAs) in 2008-2015. We operationalized racial segregation (the main exposure) using Massey and Denton's isolation index for black residents; the outcome was the rate of newly diagnosed HIV cases per 10,000 black adult heterosexuals. We tested the relationship of segregation to this outcome using multilevel multivariate models of longitudinal (2008-2015) MSA-level data, controlling for potential confounders and time. All covariates were lagged by 1 year and centered on baseline values. We preliminarily explored mediation of the focal relationship by inequalities in education, employment, and poverty rates. Segregation was positively associated with the outcome: a one standard deviation decrease in baseline isolation was associated with a 16.2% reduction in the rate of new HIV diagnoses; one standard deviation reduction in isolation over time was associated with 4.6% decrease in the outcome. Exploratory mediation analyses suggest that black/white socioeconomic inequality may mediate the relationship between segregation and HIV. Our study suggests that residential segregation may be a distal determinant of HIV among black heterosexuals. The findings further emphasize the need to address segregation as part of a comprehensive strategy to reduce racial inequities in HIV.

Triple jeopardy: the joint impact of racial segregation and neighborhood poverty on the mental health of black Americans.

PURPOSE: Because segregation may shield blacks from discrimination as well as increase their exposure to concentrated poverty, its net impact on the mental well-being of black Americans is unclear. We investigated the intersection between segregation, neighborhood poverty, race, and psychological well-being. METHODS: Using data from the nationally representative 2008-2013 National Health Interview Survey merged with U.S. Census data, we examined the association between black-white metropolitan segregation (D-index and P-index) and psychological distress (a binary indicator based on the Kessler 6 score ≥ 13) for blacks and whites. Furthermore, we assessed whether neighborhood poverty explains and/or modifies the association. Logistic regression models were estimated separately for blacks and whites as well as for each segregation index. RESULTS: Higher D- and P-indices were associated with higher odds of psychological distress for blacks. Neighborhood poverty explained some, but not all, of the association. In models that allowed for the impact of metropolitan segregation to vary by neighborhood poverty, higher segregation was found to be detrimental for blacks who resided in high poverty neighborhoods but not for those living in low poverty neighborhoods. We found no evidence that segregation impacts the mental health of whites-either detrimentally or beneficially-regardless of neighborhood poverty level. CONCLUSIONS: The impact of segregation differs by neighborhood poverty and race. The psychological harm of structural racism, resulting in segregation and concentrated poverty, is not additive but multiplicative, reflecting a "triple jeopardy" for blacks, whereby their mental health is detrimentally impacted by the compounded effects of both neighborhood distress and racial segregation.

Associations among race, residential segregation, community income, and emergency department use by adults with end-stage renal disease.

OBJECTIVE: The purpose of this study was to examine independent and interactive effects of race, community income, and racial residential segregation on the likelihood of ED revisits by persons with end-stage renal disease (ESRD). DESIGN: A retrospective analysis of de-identified data abstracted from Health Care Utilization and Cost Project's (HCUP) 2014 New Jersey State Emergency Department (ED) Database and American Community Survey (ACS) was conducted. SAMPLE: The analytic sample was comprised of 2,859 ED encounters in 2014 by non-Hispanic Black and White persons over 18 years of age with ESRD who were treated and released from the ED. MEASUREMENTS: The HCUP database was the data source for ED revisit, race, median community income, and covariate (age, gender, marital status, number of chronic conditions) variables in the study. The 2014 ACS was the source for racial segregation Dissimilarity Index scores across NJ counties. RESULTS: Living in communities with lower median income and high racial segregation was associated with a higher likelihood of ED revisits. Black race interacted with community income and racial segregation in its effect on ED revisits. CONCLUSION: Efforts are needed to direct geo-targeted interventions and resources to socially disadvantaged communities to lessen disparities in ED visits among dialysis patients.

Neighborhood characteristics and lifestyle intervention outcomes: Results from the Special Diabetes Program for Indians.

Growing evidence reveals various neighborhood conditions are associated with the risk of developing type 2 diabetes. It is unknown, however, whether the effectiveness of diabetes prevention interventions is also influenced by neighborhood characteristics. The purpose of the current study is to examine the impact of neighborhood characteristics on the outcomes of a lifestyle intervention to prevent diabetes in American Indians and Alaska Natives (AI/ANs). Year 2000 US Census Tract data were linked with those from the Special Diabetes Program for Indians Diabetes Prevention Program (SDPI-DP), an evidence-based lifestyle intervention implemented in 36 AI/AN grantee sites across the US. A total of 3394 participants started the intervention between 01/01/2006 and 07/31/2009 and were followed by 07/31/2016. In 2016-2017, data analyses were conducted to evaluate the relationships of neighborhood characteristics with intervention outcomes, controlling for individual level socioeconomic status. AI/ANs from sites located in neighborhoods with higher median household income had 38% lower risk of developing diabetes than those from sites with lower neighborhood income (adjusted hazard ratio = 0.65, 95% CI: 0.47-0.90). Further, those from sites with higher neighborhood concentrations of AI/ANs achieved less BMI reduction and physical activity increase. Meanwhile, participants from sites with higher neighborhood level of vehicle occupancy made more improvement in BMI and diet. Lifestyle intervention effectiveness was not optimal when the intervention was implemented at sites with disadvantaged neighborhood characteristics. Meaningful improvements in socioeconomic and other neighborhood disadvantages of vulnerable populations could be important in stemming the global epidemic of diabetes.

Local Residential Segregation Matters: Stronger Association of Census Tract Compared to Conventional City-Level Measures with Fatal and Non-Fatal Assaults (Total and Firearm Related), Using the Index of Concentration at the Extremes (ICE) for Racial, Economic, and Racialized Economic Segregation, Massachusetts (US), 1995-2010.

Research on residential segregation and health, primarily conducted in the USA, has chiefly employed city or regional measures of racial segregation. To test our hypothesis that stronger associations would be observed using local measures, especially for racialized economic segregation, we analyzed risk of fatal and non-fatal assault in Massachusetts (1995-2010), since this outcome is strongly associated with residential segregation. The segregation metrics comprised the Index of Concentration at the Extremes (ICE), the Index of Dissimilarity, and poverty rate, with measures computed at both the census tract and city/town level. Key results were that larger associations between fatal and non-fatal assaults and residential segregation occurred for models using the census tract vs. city/town measures, with the greatest associations observed for racialized economic segregation. For fatal assaults, comparing the bottom vs. top quintiles, the incidence rate ratio (and 95% confidence interval (CI)) in models using the census tract measures equaled 3.96 (95% CI 3.10, 5.06) for the ICE for racialized economic segregation, 3.26 (95% CI 2.58, 4.14) for the ICE for income, 3.14 (95% CI 2.47, 3.99) for poverty, 2.90 (95% CI 2.21, 3.81) for the ICE for race/ethnicity, and only 0.93 (95% CI 0.79, 1.11) for the Index of Dissimilarity; in models that included both census tract and city/town ICE measures, this risk ratio for the ICE for racialized economic segregation was higher at the census tract (3.29; 95% CI 2.43, 4.46) vs. city/town level (1.61; 95% CI 1.12, 2.32). These results suggest that, at least in the case of fatal and non-fatal assaults, research on residential segregation should employ local measures, including of racialized economic segregation, to avoid underestimating the adverse impact of segregation on health.

Irregularly-shaped school attendance zones and racial integration.

This paper investigates how much the geographic shapes of school attendance zones within urban school districts are associated with levels of attendance zone racial segregation (while holding constant levels of residential segregation). Based on an analysis of 304 school districts, findings show that more irregularly-shaped school attendance zones are correlated with lower levels of racial segregation in attendance zones after accounting for residential segregation. In fact, not one school district contains both highly irregularly-shaped attendance zones and unusually high levels of attendance zone racial segregation-although there are several school districts with irregularly-shaped zones and unusually high levels of racial integration. These findings undermine recent claims that irregularly-shaped attendance zones generally serve to segregate students by race. In addition to these empirical findings, this paper introduces a variation of the spatial information theory segregation index H˜ that is useful for predicting segregation in school attendance zones and other types of geographic boundaries containing roughly equal populations.

Residential segregation and racial disparities in self-rated health: How do dimensions of residential segregation matter?

Previous research on segregation and health has been criticized for overlooking the fact that segregation is a multi-dimensional concept (i.e., evenness, exposure, concentration, centralization, and clustering) and recent evidence drawn from non-black minorities challenges the conventional belief that residential segregation widens racial health disparities. Combining a survey data (n = 18,752) from Philadelphia with the 2010 Census tract (n = 925) data, we examine two theoretical frameworks to understand why the association of segregation with health may differ by race/ethnicity. Specifically, we investigate how each dimension of segregation contributed to racial disparities in self-rated health. We found (1) high levels of white/black concentration could exacerbate the white/black health disparities up to 25 percent, (2) the white/Hispanic health disparities was narrowed by increasing the level of white/Hispanic centralization, and (3) no single dimension of segregation statistically outperforms others. Our findings supported that segregation is bad for blacks but may be beneficial for Hispanics.

Invited Commentary: Fundamental Causes, Social Context, and Modifiable Risk Factors in the Racial/Ethnic Inequalities in Blood Pressure and Hypertension.

Racial and ethnic inequalities in blood pressure and hypertension have been well documented, but their causes remain unclear, making efforts to reduce these inequalities challenging. In this issue of the Journal, Basu et al. (Am J Epidemiol. 2015;182(4):345-353) address this gap in our knowledge by using an econometric approach to examine the role of 4 conventional risk factors for hypertension. Their results suggest that targeting certain risk factors will reduce racial inequalities in the prevalence of hypertension. However, racial differences in modifiable risk factors are enmeshed within disparate socioenvironmental contexts which are in turn determined by inequalities in the distribution of social, economic, and political resources and constraints. A small but growing body of literature suggests that targeting the intermediate risk factors that link racial group membership to hypertension, rather than the context or the inequalities in the distribution of resources and constraints, will ultimately result in little change in hypertension inequalities, increase these inequalities, or even create inequalities in poor mental health.