The relation of residential segregation to all-cause mortality: a study in black and white

Racial disparities in Death rates and Death incidences in Xinjiang: A study of multilevel ecological mechanisms

Health disparities based on racial status are well-researched by social scientists, but this field of knowledge has rarely been investigated beyond the Western context. As the largest province in China, Xinjiang has over 50% non-Han populace-and this group is subjected to various forms of inequalities. The current study is the first to quantitatively demonstrate the disparity in mortality between the Han majority and Turkic minority in Xinjiang. We have developed a theory-driven framework to approach race as a fundamental cause of mortality disparity through both individual and context-level pathways that trigger the proximate determinants of death. We compiled the 2015 China Microcensus with the Sixth Decennial Census (2010) and web-extracted point-of-interest information for data at different ecological levels. The results reveal that the mortality rate is significantly pronounced for Turks at the county-level and Turks' death incidence is elevated at the household level. The inclusion of variables at the individual- and context-level explains about 38% of the mortality disparity between Han and Turks, but the significant disparity remains strong after considering the covariates, the "healthy migrant" scenario, geographical clustering, and exposure risk. We cautiously suggest the remaining unexplained portion of the mortality disparity may be due to unobserved racial inequity and urge the academic community to further investigate this underexplored subject.

Empirical evidence supporting the inclusion of multi-axes segregation in assessing US county health

To facilitate community action toward health equity, the County Health Rankings & Roadmaps program (CHR&R) assigns health rankings to US counties. The CHR&R conceptual model considers White-Black and White-non-White dissimilarity values to represent residential segregation as part of the family and social support subcomponent. As the US is greying and becoming more multi-racial-ethnic, the two-group White-centered segregation measures are inadequate to capture segregation among population subgroups in the US. Thus, we evaluate the relevancy of segregation measures that consider multiple racial, ethnic, and age groups in assessing US county health. Besides using the two-group dissimilarity index to measure White-centered racial segregation as conceptualized by CHR&R, the study also uses the multi-group generalized dissimilarity index to measure racial-ethnic-age segregation by counties, employing both aspatial and spatial versions of these measures. These indices are computed for counties using the 2015-2019 American Community Survey data at the census tract level. Descriptive statistics and regressions controlling for sociodemographic factors and healthcare access are used to assess the contributions of individual segregation measures to mortality (life expectancy, years of potential life lost and premature mortality) and morbidity (frequent mental distress, frequent physical distress, and low birth weight) indicators representing county health. Overall, correlations between these indicators and most segregation measures are significant but weak. Regression results show that many segregation measures are not significantly related to mortality indicators, but most are significantly associated with morbidity indicators, with the magnitudes of these associations higher for the multi-group racial-ethnic-age segregation index and its spatial version. Results provide evidence that racial-ethnic-age segregation is associated with county-level morbidity and that spatial measures capturing segregation of multiple population axes should be considered for ranking county health.

Association between racial residential segregation and Black-White disparities in cardiovascular disease mortality

BACKGROUND

Racial residential segregation is associated with racial health inequities, but it is unclear if segregation may exacerbate Black-White disparities in cardiovascular disease (CVD) mortality. This study aimed to assess associations between Black-White residential segregation, CVD mortality rates among non-Hispanic (NH) Black and NH White populations, and Black-White disparities in CVD mortality.

METHODS

This cross-sectional study analyzed Black-White residential segregation, as measured by county-level interaction index, of US counties, county-level CVD mortality among NH White and NH black adults aged 25 years and older, and county-level Black-White disparities in CVD mortality in years 2014 to 2017. Age-adjusted, county-level NH Black CVD mortality rates and NH White cardiovascular disease mortality rates, as well as group-level relative risk ratios for Black-White cardiovascular disease mortality, were calculated. Sequential generalized linear models adjusted for county-level socioeconomic and neighborhood factors were used to estimate associations between residential segregation and cardiovascular mortality rates among NH Black and NH White populations. Relative risk ratio tests were used to compare Black-White disparities in the most segregated counties to disparities in the least segregated counties.

RESULTS

We included 1,286 counties with ≥5% Black populations in the main analysis. Among adults aged ≥25 years, there were 2,611,560 and 408,429 CVD deaths among NH White and NH Black individuals, respectively. In the unadjusted model, counties in the highest tertile of segregation had 9% higher (95% CI, 1%-20% higher, P = .04) rates of NH Black CVD mortality than counties in the lowest tertile of segregation. In the multivariable adjusted model, the most segregated counties had 15% higher (95% CI, 0.5% to 38% higher, P = .04) rates of NH Black CVD mortality than the least segregated counties. In the most segregated counties, NH Black individuals were 33% more likely to die of CVD than NH White individuals (RR 1.33, 95% CI 1.32 to 1.33, P < .001).

CONCLUSIONS

Counties with increased Black-White residential segregation have higher rates of NH Black CVD mortality and larger Black-White disparities in CVD mortality. Identifying the causal mechanisms through which racial residential segregation widens disparities in CVD mortality requires further study.

Segregation and Childhood Blood Lead Levels in North Carolina

BACKGROUND AND OBJECTIVES

Using a local measure of racial residential segregation, estimate the association between racial residential segregation and childhood blood lead levels between the early 1990s and 2015 in North Carolina.

METHODS

This population-based observational study uses individual-level blood lead testing records obtained from the NC Department of Health and Human Services for 320 916 children aged <7 years who were tested between 1992 and 1996 or 2013 and 2015. NC childhood blood lead levels were georeferenced to the census tract. Neighborhood racial residential segregation, assessed using a local, spatial measure of the racial isolation of non-Hispanic Blacks (RINHB), was calculated at the census tract level.

RESULTS

From 1990 to 2015, RINHB increased in 50% of 2195 NC census tracts, although the degree of change varied by geographic region. In 1992 to 1996 blood lead testing data, a 1-standard-deviation increase in tract-level RINHB was associated with a 2.86% (95% confidence interval: 0.96%-4.81%) and 2.44% (1.34%-3.56%) increase in BLL among non-Hispanic Black and non-Hispanic White children, respectively. In 2013 to 2015 blood lead testing data, this association was attenuated but persisted with a 1-standard-deviation increase in tract-level RINHB associated with a 1.59% (0.50%-2.70%) and 0.76% (0.08%-1.45%) increase in BLL among non-Hispanic Black and non-Hispanic White children, respectively. In the supplemental information, we show the change in racial residential segregation across the entire United States, demonstrating that RINHB increased in 69% of 72 899 US census tracts.

CONCLUSIONS

Racially isolated neighborhoods are associated with higher childhood lead levels, demonstrating the disproportionate environmental burdens borne by segregated communities and warranting attention to providing whole child health care.

Explaining the higher COVID-19 mortality rates among disproportionately Black counties: A decomposition analysis

Background

Why is COVID-19 mortality higher in counties with a disproportionately large (>13.4%) share of Black residents (hereafter "Black counties") relative to others ("non-Black counties")? Existing literature points to six categories of determinants: (1) social distancing, (2) COVID-19 testing, (3) socioeconomic characteristics, (4) environmental characteristics, (5) prevalence of (pre-existing) chronic health conditions, and (6) demographic characteristics. The relative importance of these determinants has not yet been thoroughly examined.

Methods

We built a dataset consisting of 21 sub-indicators across the six categories of determinants for 3108 US counties and their COVID-19 mortality over the period of January 22, 2020-December 31, 2020. Applying the Gelbach's decomposition, we quantified which determinants were most (or least) associated with the COVID-19 mortality disparity between Black and non-Black counties.

Results

We find that COVID-19 death rates were 26 percent higher in Black counties compared to non-Black counties. This disparity was almost completely explained by the six categories of determinants included in our model. Decomposition analyses indicate that county-level demographic and population health characteristics explained most of this disparity. Among all sub-indicators considered, the greater proportion of females and smaller proportion of rural residents in Black counties were the two largest contributors to the COVID-19 mortality gap between Black and non-Black counties. Proportions of diabetic residents, uninsured residents, and the degree of income inequality also significantly contributed to the gap in COVID-19 mortality.

Conclusion

The COVID-19 mortality gap between Black and non-Black counties was largely explained by pre-pandemic differences in demographic and population health characteristics. Policies aiming to reduce the prevalence of chronic conditions and uninsured residents in Black counties would have helped narrow the COVID-19 mortality gap between Black and non-Black counties in 2020.

Racialized economic segregation and potentially preventable hospitalizations among Medicaid/CHIP-enrolled children

OBJECTIVE

To examine geographic variation in preventable hospitalizations among Medicaid/CHIP-enrolled children and to test the association between preventable hospitalizations and a novel measure of racialized economic segregation, which captures residential segregation within ZIP codes based on race and income simultaneously.

DATA SOURCES

We supplement claims and enrollment data from the Transformed Medicaid Statistical Information System (T-MSIS) representing over 12 million Medicaid/CHIP enrollees in 24 states with data from the Public Health Disparities Geocoding Project measuring racialized economic segregation.

STUDY DESIGN

We measure preventable hospitalizations by ZIP code among children. We use logistic regression to estimate the association between ZIP code-level measures of racialized economic segregation and preventable hospitalizations, controlling for sex, age, rurality, eligibility group, managed care plan type, and state.

DATA EXTRACTION METHODS

We include children ages 0-17 continuously enrolled in Medicaid/CHIP throughout 2018. We use validated algorithms to identify preventable hospitalizations, which account for characteristics of the pediatric population and exclude children with certain underlying conditions.

PRINCIPAL FINDINGS

Preventable hospitalizations vary substantially across ZIP codes, and a quarter of ZIP codes have rates exceeding 150 hospitalizations per 100,000 Medicaid-enrolled children per year. Preventable hospitalization rates vary significantly by level of racialized economic segregation: children living in the ZIP codes that have the highest concentration of low-income, non-Hispanic Black residents have adjusted rates of 181 per 100,000 children, compared to 110 per 100,000 for children in ZIP codes that have the highest concentration of high-income, non-Hispanic white residents (p < 0.01). This pattern is driven by asthma-related preventable hospitalizations.

CONCLUSIONS

Medicaid-enrolled children's risk of preventable hospitalizations depends on where they live, and children in economically and racially segregated neighborhoods-specifically those with higher concentrations of low-income, non-Hispanic Black residents-are at particularly high risk. It will be important to identify and implement Medicaid/CHIP and other policies that increase access to high-quality preventive care and that address structural drivers of children's health inequities.

Association of racial residential segregation with all-cause and cancer-specific mortality in the reasons for geographic and racial differences in stroke (REGARDS) cohort study

•Increased racial residential segregation increased the risk of all-cause mortality among White participants.•Higher interaction lowered the risk of all-cause mortality among White participants.•Higher isolation lowered the risk of cancer mortality among Black participants.

Racial residential segregation shapes the relationship between early childhood lead exposure and fourth-grade standardized test scores

Racial residential segregation (RRS) – defined here as the geographic separation of Black individuals and communities from other racial/ethnic groups into separate, unequal neighborhoods – fosters environments inimical to health through disinvestment of resources and concentration of disadvantages. Neighborhood environments influence children’s health and development, but relationships between RRS and cognitive development are poorly understood. We find that: (1) non-Hispanic Black children were more likely to experience multiple adverse exposures in early childhood, and (2) among non-Hispanic Black children, high levels of RRS augmented the detrimental effect of elevated blood levels on reading test scores. Non-linear models were used to model exposure to lead and RRS, and their interaction.

Racial/ethnic disparities in academic performance may result from a confluence of adverse exposures that arise from structural racism and accrue to specific subpopulations. This study investigates childhood lead exposure, racial residential segregation, and early educational outcomes. Geocoded North Carolina birth data is linked to blood lead surveillance data and fourth-grade standardized test scores (n = 25,699). We constructed a census tract-level measure of racial isolation (RI) of the non-Hispanic Black (NHB) population. We fit generalized additive models of reading and mathematics test scores regressed on individual-level blood lead level (BLL) and neighborhood RI of NHB (RINHB). Models included an interaction term between BLL and RINHB. BLL and RINHB were associated with lower reading scores; among NHB children, an interaction was observed between BLL and RINHB. Reading scores for NHB children with BLLs of 1 to 3 µg/dL were similar across the range of RINHB values. For NHB children with BLLs of 4 µg/dL, reading scores were similar to those of NHB children with BLLs of 1 to 3 µg/dL at lower RINHB values (less racial isolation/segregation). At higher RINHB levels (greater racial isolation/segregation), children with BLLs of 4 µg/dL had lower reading scores than children with BLLs of 1 to 3 µg/dL. This pattern becomes more marked at higher BLLs. Higher BLL was associated with lower mathematics test scores among NHB and non-Hispanic White (NHW) children, but there was no evidence of an interaction. In conclusion, NHB children with high BLLs residing in high RINHB neighborhoods had worse reading scores.

A Bibliometric Analysis on Research Regarding Residential Segregation and Health Based on CiteSpace

Considerable scholarly attention has been directed to the adverse health effects caused by residential segregation. We aimed to visualize the state-of-the-art residential segregation and health research to provide a reference for follow-up studies. Employing the CiteSpace software, we uncovered popular themes, research hotspots, and frontiers based on an analysis of 1211 English-language publications, including articles and reviews retrieved from the Web of Science Core Collection database from 1998 to 2022. The results revealed: (1) The Social Science & Medicine journal has published the most studies. Roland J. Thorpe, Thomas A. LaVeist, Darrell J. Gaskin, David R. Williams, and others are the leading scholars in residential segregation and health research. The University of Michigan, Columbia University, Harvard University, the Johns Hopkins School of Public Health, and the University of North Carolina play the most important role in current research. The U.S. is the main publishing country with significant academic influence. (2) Structural racism, COVID-19, mortality, multilevel modelling, and environmental justice are the top five topic clusters. (3) The research frontier of residential segregation and health has significantly shifted from focusing on community, poverty, infant mortality, and social class to residential environmental exposure, structural racism, and health care. We recommend strengthening comparative research on the health-related effects of residential segregation on minority groups in different socio-economic and cultural contexts.

Residential Segregation, Social Cohesion, and Aging in Place: Health and Mental Health Inequities

BACKGROUND AND OBJECTIVES

Research shows that living in segregated neighborhoods may have deleterious health outcomes via social, physical, and socioeconomic contexts that deepen existing inequities. However, there has been limited scholarship examining the effects of segregation on older adults, despite an increasing focus on aging in place. Guided by the Ecological Model of Aging, we examined the effects of segregation on older adults' self-rated health and mental health, accounting for both individual characteristics and neighborhood opportunities and risks (e.g., social cohesion) and the potential moderating role of race and economic vulnerability.

RESEARCH DESIGN AND METHODS

We used data from the first four rounds of the National Health & Aging Trends Study (2011-2014) merged with tract-level census data for a final sample size of 3084 community-dwelling older adults in urban areas. We conducted multivariate regression analyses after conditioning on residential location selection variables.

RESULTS

There was no significant association between neighborhood segregation and self-rated health or between segregation and anxiety and depression symptoms. Consistent with the literature, perceived social cohesion was protective of health in each model.

DISCUSSION AND IMPLICATIONS

Our findings highlight the need for more rigorous research on segregation and older residents that utilize longitudinal and spatial data. Our findings also have implications for policies and programs that aim to support the ability to age in place for older adults who have different racial identities and live in different neighborhood contexts. Since social cohesion can be a protective factor for older adults' health and mental health, policymakers and practitioners should support initiatives to increase social cohesion.

The Impact of the COVID-19 Pandemic on Cancer Care and Health-Related Quality of Life of Non-Hispanic Black/African American, Hispanic/Latina and Non-Hispanic White Women Diagnosed with Breast Cancer in the U.S.: A Mixed-Methods Study Protocol

The COVID-19 pandemic has had critical consequences for cancer care delivery, including altered treatment protocols and delayed services that may affect patients’ quality of life and long-term survival. Breast cancer patients from minoritized racial and ethnic groups already experience worse outcomes, which may have been exacerbated by treatment delays and social determinants of health (SDoH). This protocol details a mixed-methods study aimed at comparing cancer care disruption among a diverse sample of women (non-Hispanic White, non-Hispanic Black/African American, and Hispanic/Latina) and assessing how proximal, intermediate, and distal SDoH differentially contribute to care continuity and health-related quality of life. An embedded mixed-methods design will be implemented. Eligible participants will complete an online survey, followed by a semi-structured interview (with a subset of participants) to further understand factors that influence continuity of care, treatment decision-making, and self-reported engagement. The study will identify potentially modifiable factors to inform future models of care delivery and improve care transitions. These data will provide the necessary evidence to inform whether a subsequent, multilevel intervention is warranted to improve quality of care delivery in the COVID-19 aftermath. Additionally, results can be used to identify ways to leverage existing social resources to help manage and support patients’ outcomes.

Assessing Disparity Using Measures of Racial and Educational Isolation

We develop a local, spatial measure of educational isolation (EI) and characterize the relationship between EI and our previously developed measure of racial isolation (RI). EI measures the extent to which non-college educated individuals are exposed primarily to other non-college educated individuals. To characterize how the RI-EI relationship varies across space, we propose a novel measure of local correlation. Using birth records from the State of Michigan (2005–2012), we estimate associations between RI, EI, and birth outcomes. EI was lower in urban communities and higher in rural communities, while RI was highest in urban areas and parts of the southeastern United States (US). We observed greater heterogeneity in EI in low RI tracts, especially in non-urban tracts; residents of high RI tracts are likely to be both educationally and racially isolated. Associations were also observed between RI, EI, and gestational length (weeks) and preterm birth (PTB). For example, moving from the lowest to the highest quintile of RI was associated with a 1.11 (1.07, 1.15) and 1.16 (1.10, 1.22) increase in odds of PTB among NHB and NHW women, respectively. Moving from the lowest to the highest quintile of EI was associated with a 1.07 (1.02, 1.12) and 1.03 (1.00, 1.05) increase in odds of PTB among NHB and NHW women, respectively. This work provides three tools (RI, EI, and the local correlation measure) to researchers and policymakers interested in how residential isolation shapes disparate outcomes.

Barriers to Access to Hematopoietic Cell Transplantation among Patients with Acute Myeloid Leukemia in Virginia

Allogeneic hematopoietic cell transplantation (HCT) is a standard therapy for patients with intermediate to high-risk acute myeloid leukemia (AML) and is associated with improved long-term disease-free survival. Disparity exists in access to HCT among different patient populations and requires further study. In this study, we compared HCT rates for AML among different regions in the state of Virginia and identified geographic and socioeconomic factors associated with the likelihood of receiving HCT. We conducted a retrospective, cohort study of patients 18 to 74 years of age diagnosed with AML in Virginia from 2013 to 2017 as reported to the Virginia Cancer Registry (VCR); the VCR was further linked with the Center for International Blood and Marrow Transplant Research database for identification of patients who had undergone HCT within 2 years of diagnosis. Socioeconomic data were generated from the VCR and the American Community Survey. Univariate and multivariable logistic regression models were used to examine selected socioeconomic factors of interest, including patient-level information such as sex, age, race, marital status, and primary insurance payer, as well as factors associated with geography, including the Social Vulnerability Index (SVI) and percentage of African Americans residing in the region. In Virginia, 818 patients were diagnosed with AML from 2013 to 2017, and, of these, 168 patients (21%) underwent HCT within 2 years of diagnosis. Median age was lower in the HCT cohort (55 years) versus the non-HCT cohort (64 years) (P < .001). There was a higher proportion of married patients in the HCT cohort (67%) versus the non-HCT cohort (53%) (P = .005). The rate of HCT varied by geographic region (P = .004). The multivariable analyses (without including SVI) showed decreased likelihood of HCT with increasing age (odds ratio [OR], .96; 95% confidence interval [CI], .95 to .98). Patients from regions that had a greater than 25% African American population were less likely to undergo HCT (OR, .58; 95% CI, .38 to .89). Patients who were not married were less likely to undergo HCT compared with married patients (OR, .56; 95% CI, .36 to .88). Patients with government-sponsored insurance as the primary payer were less likely to undergo HCT compared with patients with private insurance (OR, .49; 95% CI, .32 to .77). Patients living in Zip Code areas with a greater percentage of population with a bachelor's or graduate degree were more likely to undergo HCT (OR, 1.02; 95% CI, 1.00 to 1.03). In a separate multivariate model with SVI, patients residing in a Zip Code with higher SVI were less likely to undergo HCT (OR, .37; 95% CI, .16 to .82). From 2013 to 2017, we found that the likelihood of a patient undergoing HCT in Virginia for AML within 2 years of diagnosis was negatively associated with increasing age, percent of African Americans residing in the region, not-married relationship status, government-sponsored insurance as primary payer, higher SVI, and decreased percent of population with a bachelor's or graduate degree. Resources should be directed toward at-risk patient populations to remove barriers to improve access to HCT. The SVI can be used to identify communities at risk nationwide.

Effects of accumulated environmental, social and host exposures on early childhood educational outcomes

BACKGROUND

Persistent disparities in academic performance may result from a confluence of adverse exposures accruing disproportionately to specific subpopulations.

OBJECTIVE

Our overarching objective was to investigate how multiple exposures experienced over time affect early childhood educational outcomes. We were specifically interested in whether there were: racial/ethnic disparities in prevalence of adverse exposures; racial/ethnic disparities in associations observed between adverse exposures and early childhood educational outcomes; and interactions between exposures, suggesting that one exposure augments susceptibility to adverse effects of another exposure.

METHODS

We link geocoded North Carolina birth data for non-Hispanic white (NHW) and non-Hispanic black (NHB) children to blood lead surveillance data and 4th grade end-of-grade (EOG) standardized test scores (n = 65,151). We construct a local, spatial index of racial isolation (RI) of NHB at the block group level. We fit race-stratified multi-level models of reading and mathematics EOG scores regressed on birthweight percentile for gestational age, blood lead level, maternal smoking, economic disadvantage, and RI, adjusting for maternal- and child-level covariates and median household income.

RESULTS

There were marked racial/ethnic disparities in prevalence of adverse exposures. Specifically, NHB children were more likely than NHW children to be economically disadvantaged (80% vs. 40%), live in block groups with the highest quintile of RI (46% vs. 5%), have higher blood lead levels (4.6 vs. 3.7 μg/dL), and lower birthweight percentile for gestational age (mean: 39th percentile vs. 51st percentile). NHB children were less likely to have mothers who reported smoking during pregnancy (11% and 22%). We observed associations between key adverse exposures and reading and math EOG scores in 4th grade. Higher birthweight percentile for gestational age was associated with higher EOG scores, while economic disadvantage, maternal smoking, and elevated blood lead levels were associated with lower EOG scores. Associations observed for NHB and NHW children were generally not statistically different from one another, with the exception of neighborhood RI. NHB children residing in block groups in the highest RI quintile had reading and math scores 1.54 (0.74, 2.34) and 1.12 (0.38, 1.87) points lower, respectively, compared to those in the lowest RI quintile; statistically significant decrements in EOG scores associated with RI were not observed for NHW children. We did not find evidence of multiplicative interactions between exposures for NHB or NHW children.

DISCUSSION

Key adverse host, environmental, and social exposures accrue disproportionately to NHB children. Decrements in test scores associated with key adverse exposures were often but not always larger for NHB children, but were not significantly different from those estimated for NHW children. While we did not observe interactive effects, NHB children on average experience more deleterious combined exposures, resulting in larger decrements to test scores compared to NHW children.

A retrospective cohort study of 12,306 pediatric COVID-19 patients in the United States

Children and adolescents account for ~ 13% of total COVID-19 cases in the United States. However, little is known about the nature of the illness in children. The reopening of schools underlines the importance of understanding the epidemiology of pediatric COVID-19 infections. We sought to assess the clinical characteristics and outcomes in pediatric COVID-19 patients. We conducted a retrospective cross-sectional analysis of pediatric patients diagnosed with COVID-19 from healthcare organizations in the United States. The study outcomes (hospitalization, mechanical ventilation, critical care) were assessed using logistic regression. The subgroups of sex and race were compared after propensity score matching. Among 12,306 children with lab-confirmed COVID-19, 16.5% presented with respiratory symptoms (cough, dyspnea), 13.9% had gastrointestinal symptoms (nausea, vomiting, diarrhea, abdominal pain), 8.1% had dermatological symptoms (rash), 4.8% had neurological (headache), and 18.8% had other non-specific symptoms (fever, malaise, myalgia, arthralgia and disturbances of smell or taste). In the study cohort, the hospitalization frequency was 5.3%, with 17.6% needing critical care services and 4.1% requiring mechanical ventilation. Following propensity score matching, the risk of all outcomes was similar between males and females. Following propensity score matching, the risk of hospitalization was greater in non-Hispanic Black (RR 1.97 [95% CI 1.49–2.61]) and Hispanic children (RR 1.31 [95% CI 1.03–1.78]) compared with non-Hispanic Whites. In the pediatric population infected with COVID-19, a substantial proportion were hospitalized due to the illness and developed adverse clinical outcomes.

Social norms, social identities and the COVID-19 pandemic: Theory and recommendations

Sustained mass behaviour change is needed to tackle the COVID-19 pandemic, but many of the required changes run contrary to existing social norms (e.g., physical closeness with in-group members). This paper explains how social norms and social identities are critical to explaining and changing public behaviour. Recommendations are presented for how to harness these social processes to maximise adherence to COVID-19 public health guidance. Specifically, we recommend that public health messages clearly define who the target group is, are framed as identity-affirming rather than identity-contradictory, include complementary injunctive and descriptive social norm information, are delivered by in-group members and that support is provided to enable the public to perform the requested behaviours.

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.

Geographic Variation in Racial Disparities in Health and Coronavirus Disease-2019 (COVID-19) Mortality

Objective

To evaluate the race-stratified state-level prevalence of health determinants and the racial disparities in coronavirus disease 2019 (COVID-19) cumulative incidence and mortality in the United States.

Patients and Methods

The age-adjusted race-stratified prevalence of comorbidities (hypertension, diabetes, dyslipidemia, and obesity), preexisting medical conditions (pulmonary disease, heart disease, stroke, kidney disease, and malignant neoplasm), poor health behaviors (smoking, alcohol abuse, and physical inactivity), and adverse socioeconomic factors (education, household income, and health insurance) was computed in 435,139 American adult participants from the 2017 Behavioral Risk Factor Surveillance System survey. Correlation was assessed between health determinants and the race-stratified COVID-19 crude mortality rate and infection-fatality ratio computed from respective state public health departments in 47 states.

Results

Blacks had a higher prevalence of comorbidities (63.3%; 95% CI, 62.4% to 64.2% vs 55.1%; 95% CI, 54.7% to 55.5%) and adverse socioeconomic factors (47.0%; 95% CI, 46.0% to 47.9% vs 30.9%; 95% CI, 30.6% to 31.3%) than did whites. The prevalence of preexisting medical conditions was similar in blacks (30.4%; 95% CI, 28.8% to 32.1%) and whites (30.8%; 95% CI, 30.2% to 31.4%). The prevalence of poor health behaviors was higher in whites (57.2%; 95% CI, 56.3% to 58.0%) than in blacks (50.2%; 95% CI,46.2% to 54.2%). Comorbidities and adverse socioeconomic factors were highest in the southern region, and poor health behaviors were highest in the western region. The cumulative incidence rate (per 100,000 persons) was 3-fold higher in blacks (1546.4) than in whites (540.4). The crude mortality rate (per 100,000 persons) was 2-fold higher in blacks (83.2) than in whites (33.2). However, the infection-fatality ratio (per 100 cases) was similar in whites (6.2) and blacks (5.4). Within racial groups, the geographic distribution of health determinants did not correlate with the state-level COVID-19 mortality and infection-fatality ratio (P>.05 for all).

Conclusion

Racial disparities in COVID-19 are largely driven by the higher cumulative incidence of infection in blacks. There is a discordance between the geographic dispersion of COVID-19 mortality and the regional distribution of health determinants.

Independent and joint contributions of economic, social and physical environmental characteristics to mortality in the Detroit Metropolitan Area: A study of cumulative effects and pathways

OBJECTIVE

Previous studies have demonstrated associations between race-based residential segregation, neighborhood socioeconomic and physical environmental characteristics, and mortality. Relatively few studies have examined independent and joint effects of these multiple neighborhood characteristics and mortality, including potential mediating pathways. In this study we examine the extent to which associations between race-based residential segregation and all-cause mortality may be explained by multiple socioeconomic indicators and exposure to air pollutants.

METHODS

Drawing on data from multiple sources, we assessed bivariate associations between race-based residential segregation (operationalized as percent non-Hispanic Black), education (percent with graduate equivalency degree), poverty (percent below poverty), income inequality (GINI coefficient) and air pollution (ambient PM2.5) and age adjusted all-cause, all race mortality (henceforth all cause mortality) at the census tract level in the Detroit Metropolitan Area. We used inequality curves to assess the (in)equitable distribution of economic and environmental characteristics by census tract racial composition. Finally, we used generalized estimating equations (GEE) to examine independent and joint associations among percent NHB, education, income inequality, and air pollution to all-cause mortality, and test for mediating effects.

RESULTS

Bivariate associations between racial composition, education, poverty, income inequality, PM2.5 and all-cause mortality were statistically significant. Census tracts with higher concentrations of NHB residents had significantly lower educational attainment, higher poverty, and greater exposure to PM2.5. In multivariate models, education, income inequality and PM2.5 fully attenuated associations between racial composition and all-cause mortality.

CONCLUSIONS

Results are consistent with the hypothesis that race-based residential segregation is associated with heightened all-cause mortality, and that those effects are mediated by education, income inequality, and exposure to air pollution at the census tract level. Public health and cross-sector interventions to eliminate race-based residential segregation or to eliminate the maldistribution of educational and economic resources, and environmental exposures, across census tracts could substantially reduce regional inequities in all-cause mortality.

Inequalities and identity processes in crises: Recommendations for facilitating safe response to the COVID-19 pandemic

Structural inequalities and identity processes are pivotal to understanding public response to COVID-19. We discuss how identity processes can be used to promote community-level support, safe normative behaviour, and increase compliance with guidance. However, we caution how government failure to account for structural inequalities can alienate vulnerable groups, inhibit groups from being able to follow guidance, and lead to the creation of new groups in response to illegitimate treatment. Moreover, we look ahead to the longitudinal impacts of inequalities during pandemics and advise government bodies should address identity-based inequalities to mitigate negative relations with the public and subsequent collective protest.

Understanding the role of service providers, land use, and resident characteristics on the occurrence of mental health crisis calls to the police

Similar to concentrations of crime, mental health calls have been found to concentrate at a small number of places, but few have considered the context of places where mental health calls occur. The current study examines the influence of the physical and social context of street segments, particularly the role of service providers, land use features of the street and nearby area, and characteristics of residents on the likelihood of a mental health crisis call to the police occurring on the street. The findings demonstrate that the social context, such as offending and drug use among residents, levels of social cohesion and community involvement, and drug and violent crime influenced the occurrence of mental health crisis calls. Findings from this study make theoretical and practical contributions to a number of disciplines by improving our understanding of where mental health crisis calls occur and why they are found at specific places.

Divergent trends in life expectancy across the rural-urban gradient and association with specific racial proportions in the contiguous USA 2000-2005

OBJECTIVES

To estimate county-level adult life expectancy for Whites, Black/African Americans (Black), American Indian/Alaska Native (AIAN) and Asian/Pacific Islander (Asian) populations and assess the difference across racial groups in the relationship among life expectancy, rurality and specific race proportion.

METHODS

We used individual-level death data to estimate county-level life expectancy at age 25 (e25) for Whites, Black, AIAN and Asian in the contiguous USA for 2000-2005. Race-sex-stratified models were used to examine the associations among e25, rurality and specific race proportion, adjusted for socioeconomic variables.

RESULTS

Lower e25 was found in the central USA for AIANs and in the west coast for Asians. We found higher e25 in the most rural areas for Whites but in the most urban areas for AIAN and Asians. The associations between specific race proportion and e25 were positive or null for Whites but were negative for Blacks, AIAN, and Asians. The relationship between specific race proportion and e25 varied across rurality.

CONCLUSIONS

Identifying differences in adult life expectancy, both across and within racial groups, provides new insights into the geographic determinants of life expectancy disparities.

Hot Spots of Crime are Not Just Hot Spots of Crime: Examining Health Outcomes at Street Segments

In this paper we seek to identify whether the relationship between health disparities and crime occurs at a micro geographic level. Do hot spot streets evidence much higher levels of mental and physical illness than streets with little crime? Are residents of crime hot spots more likely to have health problems that interfere with their normal daily activities? To answer these questions, we draw upon a large National Institutes of Health study of a sample of hot spots and non-hot spots in Baltimore, Maryland. This is the first study we know of to report on this relationship, and accordingly we present unique descriptive data. Our findings show that both physical and mental health problems are much more likely to be found on hot spot streets than streets with little crime. This suggests that crime hot spots are not simply places with high levels of crime, but also places that evidence more general disadvantage. We argue that these findings have important policy implications for the targeting of health services and for developing proactive prevention programs.

Separate and Sick: Residential Segregation and the Health of Children and Youth in Metropolitan Statistical Areas

The purpose of this study was to better understand residential segregation and child/youth health by examining the relationship between a measure of Black-White residential segregation, the index of dissimilarity, and a suite of child and youth health measures in 235 U.S. metropolitan statistical areas (MSAs). MSAs are urban areas with a population of 50,000 or more and adjacent communities that share a high degree of economic and social integration. MSAs are defined by the Office of Management and Budget. Health-related measures included child mortality (CDC WONDER), teen births (NCHS natality data), children in poverty (SAIPE program), and disconnected youth (Measure of America). Simple linear regression and two-level hierarchical linear regression models, controlling for income, total population, % Black, and census region, examined the association between segregation and Black health, White health, and Black-White disparities in health. As segregation increased, Black children and youth had worse health across all four measures, regardless of MSA total and Black population size. White children and youth in small MSAs with large Black populations had worse levels of disconnected youth and teen births with increasing segregation, but no associations were found for White children and youth in other MSAs. Segregation worsened Black-White health disparities across all four measures, regardless of MSA total and Black population size. Segregation adversely affects the health of Black children in all MSAs and White children in smaller MSAs with large Black populations, and these effects are seen in measures that span all of childhood. Residential segregation may be an important target to consider in efforts to improve neighborhood conditions that influence the health of families and children.

Residential Racial Isolation and Spatial Patterning of Hypertension in Durham, North Carolina

INTRODUCTION

Neighborhood characteristics such as racial segregation may be associated with hypertension, but studies have not examined these relationships using spatial models appropriate for geographically patterned health outcomes. The objectives of our study were to 1) evaluate the geographic heterogeneity of hypertension; 2) describe whether and how patient-level risk factors and racial isolation relate to geographic heterogeneity in hypertension; and 3) examine cross-sectional associations of hypertension with racial isolation.

METHODS

We obtained electronic health records from the Duke Medicine Enterprise Data Warehouse for 2007-2011. We linked patient data with data on racial isolation determined by census block of residence. We constructed a local spatial index of racial isolation for non-Hispanic black patients; the index is scaled from 0 to 1, with 1 indicating complete isolation. We used aspatial and spatial Bayesian models to assess spatial variation in hypertension and estimate associations with racial isolation.

RESULTS

Racial isolation ranged from 0 (no isolation) to 1 (completely isolated). A 0.20-unit increase in racial isolation was associated with 1.06 (95% credible interval, 1.03-1.10) and 1.11 (95% credible interval, 1.07-1.16) increased odds of hypertension among non-Hispanic black and non-Hispanic white patients, respectively. Across Durham, census block-level odds of hypertension ranged from 0.62 to 1.88 among non-Hispanic black patients and from 0.32 to 2.41 among non-Hispanic white patients. Compared with spatial models that included patient age and sex, residual heterogeneity in spatial models that included age, sex, and block-level racial isolation was 33% lower for non-Hispanic black patients and 20% lower for non-Hispanic white patients.

CONCLUSION

Racial isolation of non-Hispanic black patients was associated with increased odds of hypertension among both non-Hispanic black and non-Hispanic white patients. Further research is needed to identify latent spatially patterned factors contributing to hypertension.

Residential Racial Isolation and Spatial Patterning of Type 2 Diabetes Mellitus in Durham, North Carolina

Neighborhood characteristics such as racial segregation may be associated with type 2 diabetes mellitus, but studies have not examined these relationships using spatial models appropriate for geographically patterned health outcomes. We constructed a local, spatial index of racial isolation (RI) for black residents in a defined area, measuring the extent to which they are exposed only to one another, to estimate associations of diabetes with RI and examine how RI relates to spatial patterning in diabetes. We obtained electronic health records from 2007-2011 from the Duke Medicine Enterprise Data Warehouse. Patient data were linked to RI based on census block of residence. We used aspatial and spatial Bayesian models to assess spatial variation in diabetes and relationships with RI. Compared with spatial models with patient age and sex, residual geographic heterogeneity in diabetes in spatial models that also included RI was 29% and 24% lower for non-Hispanic white and black residents, respectively. A 0.20-unit increase in RI was associated with an increased risk of diabetes for white (risk ratio = 1.24, 95% credible interval: 1.17, 1.31) and black (risk ratio = 1.07, 95% credible interval: 1.05, 1.10) residents. Improved understanding of neighborhood characteristics associated with diabetes can inform development of policy interventions.

Barrios, ghettos, and residential racial composition: Examining the racial makeup of neighborhood profiles and their relationship to self-rated health

Racial/ethnic disparities in self-rated health persist and according to the social determinants of health framework, may be partially explained by residential context. The relationship between neighborhood factors and self-rated health has been examined in isolation but a more holistic approach is needed to understand how these factors may cluster together and how these neighborhood typologies relate to health. To address this gap, we conducted a latent profile analysis using data from the Chicago Community Adult Health Study (CCAHS; N = 2969 respondents in 342 neighborhood clusters) to identify neighborhood profiles, examined differences in neighborhood characteristics among the identified typologies and tested their relationship to self-rated health. Results indicated four distinct classes of neighborhoods that vary significantly on most neighborhood-level social determinants of health and can be defined by racial/ethnic composition and class. Residents in Hispanic, majority black disadvantaged, and majority black non-poor neighborhoods all had significantly poorer self-rated health when compared to majority white neighborhoods. The difference between black non-poor and white neighborhoods in self-rated health was not significant when controlling for individual race/ethnicity. The results indicate that neighborhood factors do cluster by race and class of the neighborhood and that this clustering is related to poorer self-rated health.

Hispanic Segregation and Poor Health: It's Not Just Black and White

Despite the importance of understanding the fundamental determinants of Hispanic health, few studies have investigated how metropolitan segregation shapes the health of the fastest-growing population in the United States. Using 2006-2013 data from the National Health Interview Survey, we 1) examined the relationship between Hispanic metropolitan segregation and respondent-rated health for US-born and foreign-born Hispanics and 2) assessed whether neighborhood poverty mediated this relationship. Results indicated that segregation has a consistent, detrimental effect on the health of US-born Hispanics, comparable to findings for blacks and black-white segregation. In contrast, segregation was salutary (though not always significant) for foreign-born Hispanics. We also found that neighborhood poverty mediates some, but not all, of the associations between segregation and poor health. Our finding of divergent associations between health and segregation by nativity points to the wide range of experiences within the diverse Hispanic population and suggests that socioeconomic status and structural factors, such as residential segregation, come into play in determining Hispanic health for the US-born in a way that does not occur among the foreign-born.

Black-white metropolitan segregation and self-rated health: Investigating the role of neighborhood poverty

While black-white segregation has been consistently linked to detrimental health outcomes for blacks, whether segregation is necessarily a zero-sum arrangement in which some groups accrue health advantages at the expense of other groups and whether metropolitan segregation impacts the health of racial groups uniformly within the metropolitan area, remains unclear. Using nationally representative data from the 2008-2013 National Health Interview Survey linked to Census data, we investigate whether the association between metropolitan segregation and health is invariant within the metropolitan area or whether it is modified by neighborhood poverty for black and white Americans. In doing so, we assess the extent to which segregation involves direct health tradeoffs between blacks and whites. We conduct race-stratified multinomial and logistic regression models to assess the relationship between 1) segregation and level of neighborhood poverty and 2) segregation, neighborhood poverty, and poor health, respectively. We find that, for blacks, segregation was associated with a higher likelihood of residing in high poverty neighborhoods, net of individual-level socioeconomic characteristics. Segregation was positively associated with poor health for blacks in high poverty neighborhoods, but not for those in lower poverty neighborhoods. Hence, the self-rated health of blacks clearly suffers as a result of black-white segregation - both directly, and indirectly through exposure to high poverty neighborhoods. We do not find consistent evidence for a direct relationship between segregation and poor health for whites. However, we find some suggestive evidence that segregation may indirectly benefit whites through decreasing their exposure to high poverty environments. These findings underscore the critical role of concentrated disadvantage in the complex interconnection between metropolitan segregation and health. Weakening the link between racial segregation and concentrated poverty via local policy and planning has the potential for broad population-based health improvements and significant reductions in black-white health disparities.

Changing Patterns of Residential Segregation in a Prismatic Metropolis: A Lacunarity-Based Study in Houston, 1980–2000

The role of race versus class in shaping residential segregation patterns has been a contentious issue in segregation studies for decades. Despite the voluminous, interdisciplinary literature, scholars have reported conflicting evidence on the role of race versus class in residential segregations. We attribute the current inconclusive literature partially to the failure to consider scale explicitly in residential segregation measures, and partially to the growing complexity of a multiethnic melting pot in most cities in the United States. Inspired by new metrics employed by landscape ecologists to measure landscape heterogeneity, residential segregation is reconceived as a scale-dependent social phenomenon in this paper. We also present an alternative to existing structural or spatial segregation measures, considered as less efficient because most of the existing indices measure only a few dimensions of segregation at a single scale. We have developed a multiscale, lacunarity-based segregation measure, and have used it to examine the role of race versus class in residential segregation patterns in Houston, Texas. Using census-tract-level data from 1980 to 2000, we found that race is still the most important factor in explaining residential segregation despite the overall decline of segregation by both income and race. It was also found that the changing segregation patterns over time are contingent upon the scale as well as the race or income group considered.

Racial/Ethnic Residential Segregation, Obesity, and Diabetes Mellitus

Persistent racial/ethnic disparities in obesity and type 2 diabetes mellitus seen in the US are likely due to a combination of social, biological, and environmental factors. A growing number of studies have examined the role of racial/ethnic residential segregation with respect to these outcomes because this macro-level process is believed to be a fundamental cause of many of the factors that contribute to these disparities. This review provides an overview of findings from studies of racial/ethnic residential segregation with obesity and diabetes published between 2013 and 2015. Findings for obesity varied by geographic scale of the segregation measure, gender, ethnicity, and racial identity (among Hispanics/Latinos). Recent studies found no association between racial/ethnic residential segregation and diabetes prevalence, but higher segregation of Blacks was related to higher diabetes mortality. Implications of these recent studies are discussed as well as promising areas of future research.

Spatio-temporal determinants of mental health and well-being: advances in geographically-explicit ecological momentary assessment (GEMA)

PURPOSE

Overview of geographically explicit momentary assessment research, applied to the study of mental health and well-being, which allows for cross-validation, extension, and enrichment of research on place and health.

METHODS

Building on the historical foundations of both ecological momentary assessment and geographic momentary assessment research, this review explores their emerging synergy into a more generalized and powerful research framework.

RESULTS

Geographically explicit momentary assessment methods are rapidly advancing across a number of complimentary literatures that intersect but have not yet converged. Key contributions from these areas reveal tremendous potential for transdisciplinary and translational science.

CONCLUSIONS

Mobile communication devices are revolutionizing research on mental health and well-being by physically linking momentary experience sampling to objective measures of socio-ecological context in time and place. Methodological standards are not well-established and will be required for transdisciplinary collaboration and scientific inference moving forward.

Distinguishing the race-specific effects of income inequality and mortality in U.S. metropolitan areas

In the United States, the association between income inequality and mortality has been fairly consistent. However, few studies have explicitly examined the impact of race. Studies that have either stratified outcomes by race or conducted analyses within race-specific groups suggest that the income inequality/mortality relation may differ for blacks and whites. The factors explaining the association may also differ for the two groups. Multivariate ordinary least squares regression analysis was used to examine associations between study variables. We used three measures of income inequality to examine the association between income inequality and age-adjusted all-cause mortality among blacks and whites separately. We also examined the role of racial residential segregation and concentrated poverty in explaining associations among groups. Metropolitan areas were included if they had a population of at least 100,000 and were at least 10 percent black. There was a positive income inequality/mortality association among blacks and an inverse association among whites. Racial residential segregation completely attenuated the income inequality/mortality relationship for blacks, but was not significant among whites. Concentrated poverty was a significant predictor of mortality rates in both groups but did not confound associations. The implications of these findings and directions for future research are discussed.

Advancing research on racial-ethnic health disparities: improving measurement equivalence in studies with diverse samples

To conduct meaningful, epidemiologic research on racial-ethnic health disparities, racial-ethnic samples must be rendered equivalent on other social status and contextual variables via statistical controls of those extraneous factors. The racial-ethnic groups must also be equally familiar with and have similar responses to the methods and measures used to collect health data, must have equal opportunity to participate in the research, and must be equally representative of their respective populations. In the absence of such measurement equivalence, studies of racial-ethnic health disparities are confounded by a plethora of unmeasured, uncontrolled correlates of race-ethnicity. Those correlates render the samples, methods, and measures incomparable across racial-ethnic groups, and diminish the ability to attribute health differences discovered to race-ethnicity vs. to its correlates. This paper reviews the non-equivalent yet normative samples, methodologies and measures used in epidemiologic studies of racial-ethnic health disparities, and provides concrete suggestions for improving sample, method, and scalar measurement equivalence.

Neighborhood-level racial/ethnic residential segregation and incident cardiovascular disease: the multi-ethnic study of atherosclerosis

BACKGROUND

Previous research suggests that neighborhood-level racial/ethnic residential segregation is linked to health, but it has not been studied prospectively in relation to cardiovascular disease (CVD).

METHODS AND RESULTS

Participants were 1595 non-Hispanic black, 2345 non-Hispanic white, and 1289 Hispanic adults from the Multi-Ethnic Study of Atherosclerosis free of CVD at baseline (aged 45-84 years). Own-group racial/ethnic residential segregation was assessed by using the Gi* statistic, a measure of how the neighborhood racial/ethnic composition deviates from surrounding counties' racial/ethnic composition. Multivariable Cox proportional hazards modeling was used to estimate hazard ratios for incident CVD (first definite angina, probable angina followed by revascularization, myocardial infarction, resuscitated cardiac arrest, coronary heart disease death, stroke, or stroke death) over 10.2 median years of follow-up. Among blacks, each standard deviation increase in black segregation was associated with a 12% higher hazard of developing CVD after adjusting for demographics (95% confidence interval, 1.02-1.22). This association persisted after adjustment for neighborhood-level characteristics, individual socioeconomic position, and CVD risk factors (hazard ratio, 1.12; 95% confidence interval, 1.02-1.23). For whites, higher white segregation was associated with lower CVD risk after adjusting for demographics (hazard ratio, 0.88; 95% confidence interval, 0.81-0.96), but not after further adjustment for neighborhood characteristics. Segregation was not associated with CVD risk among Hispanics. Similar results were obtained after adjusting for time-varying segregation and covariates.

CONCLUSIONS

The association of residential segregation with cardiovascular risk varies according to race/ethnicity. Further work is needed to better characterize the individual- and neighborhood-level pathways linking segregation to CVD risk.

Ethnic density and depressive symptoms among African Americans: threshold and differential effects across social and demographic subgroups

OBJECTIVES

We examined the association between Black ethnic density and depressive symptoms among African Americans. We sought to ascertain whether a threshold exists in the association between Black ethnic density and an important mental health outcome, and to identify differential effects of this association across social, economic, and demographic subpopulations.

METHODS

We analyzed the African American sample (n = 3570) from the National Survey of American Life, which we geocoded to the 2000 US Census. We determined the threshold with a multivariable regression spline model. We examined differential effects of ethnic density with random-effects multilevel linear regressions stratified by sociodemographic characteristics.

RESULTS

The protective association between Black ethnic density and depressive symptoms changed direction, becoming a detrimental effect, when ethnic density reached 85%. Black ethnic density was protective for lower socioeconomic positions and detrimental for the better-off categories. The masking effects of area deprivation were stronger in the highest levels of Black ethnic density.

CONCLUSIONS

Addressing racism, racial discrimination, economic deprivation, and poor services-the main drivers differentiating ethnic density from residential segregation-will help to ensure that the racial/ethnic composition of a neighborhood is not a risk factor for poor mental health.

Capturing the two dimensions of residential segregation at the neighborhood level for health research

Two conceptual and methodological foundations of segregation studies are that (i) segregation involves more than one group, and (ii) segregation measures need to quantify how different population groups are distributed across space. Therefore, percentage of population belonging to a group is not an appropriate measure of segregation because it does not describe how populations are spread across different areal units or neighborhoods. In principle, evenness and isolation are the two distinct dimensions of segregation that capture the spatial patterns of population groups. To portray people’s daily environment more accurately, segregation measures need to account for the spatial relationships between areal units and to reflect the situations at the neighborhood scale. For these reasons, the use of local spatial entropy-based diversity index (SH_i) and local spatial isolation index (S_i) to capture the evenness and isolation dimensions of segregation, respectively, are preferable. However, these two local spatial segregation indexes have rarely been incorporated into health research. Rather ineffective and insufficient segregation measures have been used in previous studies. Hence, this paper empirically demonstrates how the two measures can reflect the two distinct dimensions of segregation at the neighborhood level, and argues conceptually and set the stage for their future use to effectively and meaningfully examine the relationships between residential segregation and health.

Use of segregation indices, Townsend Index, and air toxics data to assess lifetime cancer risk disparities in metropolitan Charleston, South Carolina, USA

BACKGROUND

Studies have demonstrated a relationship between segregation and level of education, occupational opportunities, and risk behaviors, yet a paucity of research has elucidated the association between racial residential segregation, socioeconomic deprivation, and lifetime cancer risk.

OBJECTIVES

We examined estimated lifetime cancer risk from air toxics by racial composition, segregation, and deprivation in census tracts in Metropolitan Charleston.

METHODS

Segregation indices were used to measure the distribution of groups of people from different races within neighborhoods. The Townsend Index was used to measure economic deprivation in the study area. Poisson multivariate regressions were applied to assess the association of lifetime cancer risk with segregation indices and Townsend Index along with several sociodemographic measures.

RESULTS

Lifetime cancer risk from all pollution sources was 28 persons/million for half of the census tracts in Metropolitan Charleston. Isolation Index and Townsend Index both showed significant correlation with lifetime cancer risk from different sources. This significance still holds after adjusting for other sociodemographic measures in a Poisson regression, and these two indices have stronger effect on lifetime cancer risk compared to the effects of sociodemographic measures.

CONCLUSIONS

We found that material deprivation, measured by the Townsend Index and segregation measured by the Isolation index, introduced high impact on lifetime cancer risk by air toxics at the census tract level.

Neighborhoods and mental health: exploring ethnic density, poverty, and social cohesion among Asian Americans and Latinos

This study examines the associations of neighborhood ethnic density and poverty with social cohesion and self-rated mental health among Asian Americans and Latinos. Path analysis is employed to analyze data from the 2002-2003 National Latino and Asian American Study (NLAAS) and the 2000 U.S. Census (N = 2095 Asian Americans living in N = 259 neighborhoods; N = 2554 Latinos living in N = 317 neighborhoods). Findings reveal that neighborhood ethnic density relates to poor mental health in both groups. Social cohesion partially mediates that structural relationship, but is positively related to ethnic density among Latinos and negatively related to ethnic density among Asian Americans. Although higher neighborhood poverty is negatively associated with mental health for both groups, the relationship does not hold in the path models after accounting for social cohesion and covariates. Furthermore, social cohesion fully mediates the association between neighborhood poverty and mental health among Latinos. This study highlights the necessity of reconceptualizing existing theories of social relationships to reflect complex and nuanced mechanisms linking neighborhood structure and mental health for diverse racial and ethnic groups.

Racial differences in age at first sexual intercourse: residential racial segregation and the black-white disparity among U.S. adolescents

OBJECTIVES

The age of adolescents at first sexual intercourse is an important risk factor for sexually transmitted diseases (STDs) and adolescent pregnancy. Black adolescents are at higher risk than white adolescents for first sexual intercourse at younger ages as well as STDs and pregnancy. Individual- and family-level factors do not fully explain this disparity. We examined whether five dimensions of black-white residential racial segregation can help explain the racial disparity in age at first sexual intercourse.

METHODS

Using the National Longitudinal Survey of Youth 1997 and U.S. Census 2000 data, we performed multiple hierarchical discrete time-to-event analyses on a nationally representative cohort of adolescents followed since 1997. Although the cohort study is ongoing, we used data from 1997 through 2005.

RESULTS

Concentration and unevenness significantly modified the association of race and age at first sexual intercourse. However, stratified results suggested differences in the effect of race on age at first sexual intercourse at each level of segregation across dimensions of segregation.

CONCLUSIONS

Residential racial segregation may modify the black-white disparity in risk of first sexual intercourse at younger ages, but these associations are complex. Future studies should be conducted to elucidate the causal mechanisms.

Residential segregation, geographic proximity and type of services used: evidence for racial/ethnic disparities in mental health

Residential characteristics influence opportunities, life chances and access to health services in the United States but what role does residential segregation play in differential access and mental health service utilization? We explore this issue using secondary data from the 2006 Medical Expenditure Panel Survey, 2006 American Medical Association Area Research File and the 2000 Census. Our sample included 9737 whites, 3362 African Americans and 5053 Latinos living in Metropolitan Statistical Areas. Using logistic regression techniques, results show respondents high on Latino isolation and Latino centralization resided in psychiatrist shortage areas whereas respondents high on African American concentration had access to psychiatrists in their neighborhoods. Predominant race of neighborhood was associated with the type of mental health professional used where respondents in majority African American neighborhoods were treated by non-psychiatrists and general doctors whereas respondents in majority Latino neighborhoods saw general doctors. Respondents high on Latino Isolation and Latino Centralization were more likely to utilize non-psychiatrists. These findings suggest that living in segregated neighborhoods influence access and utilization of mental health services differently for race/ethnic groups which contradicts findings that suggest living in ethnic enclaves is beneficial to health.

Ethnic density effects on physical morbidity, mortality, and health behaviors: a systematic review of the literature

It has been suggested that people in racial/ethnic minority groups are healthier when they live in areas with a higher concentration of people from their own ethnic group, a so-called ethnic density effect. Ethnic density effects are still contested, and the pathways by which ethnic density operates are poorly understood. The aim of this study was to systematically review the literature examining the ethnic density effect on physical health, mortality, and health behaviors. Most studies report a null association between ethnic density and health. Protective ethnic density effects are more common than adverse associations, particularly for health behaviors and among Hispanic people. Limitations of the literature include inadequate adjustment for area deprivation and limited statistical power across ethnic density measures and study samples.

Impact of ethnic variation and residential segregation on long-term survival following myocardial perfusion SPECT

BACKGROUND

Ethnic characteristics of a neighborhood may impact upon all-cause mortality (ACM). It is not known whether this consideration remains a risk modifier among those being evaluated for CAD.

METHODS

6,477 pts (60 ± 13 years, male 38%) residing in NYC with normal or abnormal stress SPECT studies were assessed for ACM during a mean follow-up of 9 ± 3.8 years. Baseline CAD risk factors and ethnic characteristics of patient neighborhoods were considered. Zip-codes with >70% of one ethnicity was considered to be predominant of that ethnicity.

RESULTS

There were 573 (20%) Hispanics (HS), 765 (27%) African-Americans (AA), and 250 (30%) Caucasians (CC) residing in areas >70% of their own ethnicity. Compared to CC, the risk for ACM was lower in HS (hazard ratio (HR) 0.68, 95% CI 0.57-0.8, P < .0001) and similar among AA (HR 1.1, 95% CI 0.95-1.41, P = .2). Among HS, there was a lower ACM among those residing in HS areas compared to those residing in a non-HS areas (HR 0.7 95% CI 0.56-0.9, P = .03) despite a lower median household income ($27,838 ± 3,328 vs $37,751 ± 17,036; P < .0001). This survival difference was not seen in CC and AA.

CONCLUSION

Among patients referred for nuclear SPECT studies for suspected CAD, HS ethnicity was an independent predictor of a favorable prognosis. Among HS, the ethnic characteristic of patients' neighborhoods was an independent predictor of ACM. These results imply that ethnic social support is a potentially powerful modifier of patient outcomes among certain patient groups.

Residential segregation and infant mortality: a multilevel study using Iranian census data

BACKGROUND

There is a great amount of literature concerning the effect of racial segregation on health outcomes but few papers have discussed the effect of segregation on the basis of social, demographic and economic characteristics on health. We estimated the independent effect of segregation of determinants of socioeconomic status on infant mortality in Iranian population.

METHODS

For measuring segregation, we used generalized dissimilarity index for two group and multi group nominal variables and ordinal information theory index for ordinal variables. Sample data was obtained from Iranian latest national census and multilevel modeling with individual variables at level one and segregation indices measured at province level for socioeconomic status variables at level two were used to assess the effect of segregation on infant mortality.

RESULTS

Among individual factors, mother activity was a risk factor for infant mortality. Segregated provinces in regard to size of the house, ownership of a house and motorcycle, number of literate individual in the family and use of natural gas for cooking and heating had higher infant mortality. Segregation indices measured for education level, migration history, activity, marital status and existence of bathroom were negatively associated with infant mortality.

CONCLUSION

Segregation of different contextual characteristics of neighborhood had different effects on health outcomes. Studying segregation of social, economic, and demographic factors, especially in communities, which are racially homogenous, might reveal new insights into dissimilarities in health.

Black preterm birth risk in nonblack neighborhoods: effects of Hispanic, Asian, and non-Hispanic white ethnic densities

PURPOSE

Studies of ethnic density and health in the United States have documented poorer health outcomes among black individuals living in black compared with nonblack neighborhoods, but few studies have considered the identities of the populations in nonblack neighborhoods.

METHODS

New York City birth records from 1995 through 2003 and a spatial measure of ethnic density were used to examine preterm birth risks among non-Hispanic black women associated with non-Hispanic white, Hispanic, Asian, and non-Hispanic black neighborhood densities. Logistic regression models were used to estimate the effect on black preterm birth risks of replacing white neighbors with Hispanic, Asian, and black neighbors. Risk differences were computed for changes from the 10th to the 90th percentiles of ethnic density.

RESULTS

Increasing Hispanic density was associated with reduced preterm birth risks among non-Hispanic black women, especially if the black women were foreign-born (RD = -19.1 per 1,000 births; 95% confidence interval. -28.6 to -9.5). Estimates for increasing Asian density were null. Increasing black density was associated with increasing black preterm birth risk, with a threshold at greater levels of black density.

CONCLUSIONS

The low risks of preterm birth among foreign-born non-Hispanic black women in majority-Hispanic neighborhoods may be related to protective psychosocial or lifestyle and warrant further investigation.

THE RELATIONSHIP BETWEEN NEIGHBORHOOD RACIAL CONCENTRATION AND VERBAL ABILITY: AN INVESTIGATION USING THE INSTITUTIONAL RESOURCES MODEL

Relatively few studies examine the relationship between racial residential segregation and educational or cognitive outcomes. Using data from the National Longitudinal Study of Adolescent Health and the institutional resources model of neighborhood effects, I investigate one account of how macrostructural arrangements between race, neighborhood segregation, and school quality interact to produce inequalities in test scores. Consistent with the institutional resources model, results suggest that school quality varies across neighborhoods based, in part, on their degree of racial concentration. Indeed, school quality and other school characteristics mediate the relationship between racial concentration and verbal skills, particularly among black males. These findings have implications not only for inequalities in cognitive skills among blacks across residential space, but also between blacks and whites given high levels of residential segregation in the United States. In sum, findings illustrate yet another way in which residential segregation contributes to, and not merely reflects, racial inequalities.

Racial/ethnic residential segregation: framing the context of health risk and health disparities

An increasing body of public health literature links patterns of racial/ethnic residential segregation to health status and health disparities. Despite substantial new empirical work, meaningful understanding of the pathways through which segregation operates to influence health remains elusive. The literature on segregation and health was appraised with an emphasis on select conceptual, methodological, and analytical issues. Recommendations for advancing the next generation of racial/ethnic residential segregation and health research will require closer attention to sharpening the methodology of measuring segregation, testing mediating pathways and effect modification, incorporating stronger test of causality, exploring factors of resilience in segregated areas, applying a life-course perspective, broadening the scope of the investigation of segregation to include nativity status in blacks and other racial/ethnic groups, and linking segregation measures with biological data.

Racial/ethnic heterogeneity in the socioeconomic patterning of CVD risk factors: in the United States: the multi-ethnic study of atherosclerosis

Many studies document racial variation, gender differences, and socioeconomic status (SES) patterning in cardiovascular disease (CVD) risk factors but few studies have investigated heterogeneity in SES differences by race/ethnicity or gender. Using data from the Multi-Ethnic Study of Atherosclerosis (N=6,814) and stratified regression models, we investigated race/ethnic differences in the SES patterning of diabetes, hypertension, smoking, and body mass index (BMI). Inverse socioeconomic gradients in hypertension, diabetes, smoking, and BMI were observed in White and Black women but associations were weaker or absent in Hispanic and Chinese women (except in the case of diabetes for Hispanic women). Even greater heterogeneity in social patterning of risk factors was observed in men. In White men all four risk factors were inversely associated with socioeconomic position, although often associations were only present or were stronger for education than for income. The inverse socioeconomic patterning was much less consistent in men of other races/ethnic groups, and higher SES was associated with higher BMI in non-White men. These findings have implications for understanding the causes of social patterning, for the analysis of SES adjusted race/ethnic differences, and for the targeting of interventions.