Measures Of Residential Segregation Research Articles

Residential segregation and summertime air temperature across 13 northeastern U.S. states: potential implications for energy burden

High ambient summertime temperatures are an increasing health concern with climate change. This is a particular concern for minoritized households in the United States, for which differential energy burden may compromise adaptive capacity to high temperatures. Our research question was: Do minoritized groups experience hotter summers than the area average, and do non-Hispanic white people experience cooler summers? Using a fine-scaled spatiotemporal air temperature model and U.S. census data, we examined local (within-county) differences in warm season cooling degree days (CDDs) by ethnoracial group as a proxy for local energy demand for space cooling across states of the northeast and mid-Atlantic U.S. in 2003–2019. Using state-specific regression models adjusted for year and county, we found that Black and Latino people consistently experienced more CDDs, non-Hispanic white people experienced fewer CDDs, and Asian populations showed mixed results. We also explored a concentration-based measure of residential segregation for each ethnoracial group as one possible pathway towards temperature disparities. We included the segregation measure as a smooth term in a regression model adjusted for county and year. The results were nonlinear, but higher concentrations of white people were associated with lower annual CDDs and higher concentrations of Latino people were associated with higher annual CDDs than the county average. Concentrations for Black and Asian people were nonmonotonic, sometimes with bowed associations. These findings suggest that present-day residential segregation, as modeled by spatially smoothed ethnoracial subgroup concentrations, may contribute to summertime air temperature disparities and influence adaptive capacity. We hope these findings can support place-based interventions, including targeting of energy insecurity relief programs.

Conceptual and Methodological Arguments against the Use of Location Quotient as an Area-Based Measure of Residential Segregation: A Measurement Perspective

Among a wide range of practical applications, the location quotient (LQ) has been used as an area-based measure of residential segregation by race/ethnicity in some studies. However, it does not correspond to any of the five dimensions of residential segregation. Rather, an application of LQ in demographic data analyses brings about an atypical way to quantify the population composition of areal units by race/ethnicity. To clarify misconceptions, the purpose of this study was to demonstrate the relationships between proportions, percentages, and LQs of six racial/ethnic groups in the conterminous United States (US). Since populations change over time, demographic data on race and ethnicity were obtained from the 2000, 2010, and 2020 Census through the US Census Bureau’s website. Using census tracts and counties as the units of analysis, a sequence of scatterplots and associated Pearson’s correlation coefficients (r) was used to display the analytical results of census-tract- and county-based measures at three different time periods. Despite the different levels of aggregation, the relationships between proportions, percentages, and LQs of six racial/ethnic groups consistently showed perfect positive correlations at three different time periods (r = 1.00). These suggest that census-tract- and county-based measures expressed as the proportion, percentage, and LQ of a racial/ethnic group capture the same distributional pattern, but the units of measurement simply differ from one another. Hence, the study of residential segregation and its societal consequences needs to be specific to the dimension under study and to build upon the conceptual and methodological foundations established by sociologists-demographers and geographers.

Area deprivation index and segregation on the risk of HIV: a U.S. Veteran case–control study

Preventing HIV infection remains a critically important tool in the continuing fight against HIV/AIDS. The primary aim is to evaluate the effect and interactions between a composite area-level social determinants of health measure and an area-level measure of residential segregation on the risk of HIV/AIDS in U.S. Veterans. Using the individual-level patient data from the U.S. Department of Veterans Affairs, we constructed a case-control study of veterans living with HIV/AIDS (VLWH) and age-, sex assigned at birth- and index date-matched controls. We geocoded patient's residential address to ascertain their neighborhood and linked their information to two measures of neighborhood-level disadvantage: area deprivation index (ADI) and isolation index (ISOL). We used logistic regression to estimate the odds ratio (OR) and 95% confidence interval (CI) for comparing VLWH with matched controls. We performed analyses for the entire U.S. and separately for each U.S. Census division. Overall, living in minority-segregated neighborhoods was associated with a higher risk of HIV (OR: 1.88 (95% CI: 1.79-1.97) while living in higher ADI neighborhoods was associated with a lower risk of HIV (OR: 0.88; 95% CI: 0.84-0.92). The association between living in a higher ADI neighborhood and HIV was inconsistent across divisions, while living in minority-segregated neighborhoods was consistently associated with increased risk across all divisions. In the interaction model, individuals from low ADI and high ISOL neighborhoods had a higher risk of HIV in three divisions: East South Central; West South Central, and Pacific. Our results suggest that residential segregation may prevent people in disadvantaged neighborhoods from protecting themselves from HIV independent from access to health care. There is the need to advance knowledge about the neighborhood-level social-structural factors that influence HIV vulnerability toward developing interventions needed to achieve the goal of ending the HIV epidemic. US National Cancer Institute.

Abstract P150: Residential Segregation and Hypertension Risk in Black and White Americans

Introduction: Black adults experience the highest hypertension burden of any American group. Evidence indicates social factors adversely affecting Black people explain some of the excess hypertension burden. It’s unclear whether residential segregation, a key cause of health inequities, has a differential impact on Black and White people. Hypothesis: The magnitude of the association of residential segregation and risk of incident hypertension will be greater in Black than White people. Methods: Our sample included 6,143 Black and White REasons for Geographic And Racial Differences in Stroke (REGARDS) study participants without prevalent hypertension (2003-7), and with a follow-up visit 9.3 years later. Baseline county-level segregation was measured with the (1) dissimilarity index (DI, the difference in race distribution of census tracts relative to their county), (2) isolation index (ISI, the degree to which Black people are exposed only to one another in a county), and (3) interaction index (ITI, the degree to which Black people are exposed to White people in a county). Modified Poisson regression estimated the risk ratios (RR) of incident hypertension per SD increment of baseline residential segregation. Results: The mean (SD) age was 61(8) years for Black people and 62(8) years for White people. Hypertension incidence was 46% for Black people and 33% for White people. There was no association of any of the three measures of residential segregation (DI, ISI and ITI) with incident hypertension, with RRs all around 1.0 ( Figure ). Conclusions: Three measures of residential segregation were not associated with incident hypertension risk in Black and White participants of the REGARDS cohort. Findings differ from a previous study that reported that a measure of racial clustering was associated with higher risk of hypertension in Black people. Taken together, findings suggest that, in Black people, different domains of residential segregation capture factors related differently to hypertension development.

Is there greater ethnic mixing in residential or workplace spaces?

ABSTRACT While much of the ethnic and racial segregation literature concentrates on residential neighbourhoods, a growing body of research demonstrates how levels of inter-ethnic mixing vary between home and other spaces, including workplace environments. Using alternative population bases from the 2011 Census for England and Wales, we explore how levels of ethnic segregation and diversity compare for working-age people in residential (‘nighttime’), workday (‘daytime’) and workplace (‘employment’) environments. Analyses of Middle Layer Super Output Areas reveal that a larger number of these zones had low residential ethnic diversity than had low workday or workplace diversity. We also find higher levels of residential segregation than workplace segregation for all ethnic groups, including the White British (majority) and minoritised groups. Notable differences in segregation between residential and workplace spaces for the Pakistani and Bangladeshi ethnic groups, for example, demonstrate that more commonly applied measures of residential segregation fail to capture the extent of inter-ethnic mixing across spaces, and at different times of the day. Commuting data are analysed to explore the role of daily mobilities in shaping these patterns. The findings nuance understandings of levels of ethnic mixing, and emphasise the need for segregation analyses across multiple spatio-temporal contexts.

Abstract 09: Readmission Risk And The Role Of Racial Residential Segregation Following Out-of-hospital Cardiac Arrest Among Medicare Beneficiaries

Introduction: Among out-of-hospital cardiac arrest (OHCA) survivors, high rates of mortality and readmissions have been reported after discharge. Racial residential segregation, a result of longstanding US institutional racism, has been associated with worse health outcomes across multiple conditions, but its relationship to readmission risk for OHCA is unknown. We investigated if the index of concentration at the extremes (ICE) is associated with increased risk of readmission for Medicare beneficiaries after survival from index hospitalization for OHCA. Methods: Using age-eligible Medicare fee-for-service claims from 2013-2015, we identified beneficiaries with a primary OHCA diagnosis (using ICD-CM diagnosis codes) who survived to discharge. The primary predictors were three ICE measures (race, income, and racialized income) calculated at the ZIP code level and binned into quintiles. The primary outcome was all-cause readmission after discharge from inpatient OHCA hospitalization. Competing risks regression models were fitted with a frailty term with readmission as the event of interest and mortality prior to readmission as the competing event, while accounting for beneficiary demographics, comorbidities, length of stay, and cardiac procedures. Results: We identified 200,509 OHCA claims; 29,847 (14.8%) survived to discharge. Mean beneficiary age was 75 years (SD 8), 40% were female, 79% White, and 15% Black. Within 30 days of discharge 8839 (29.6%) had died and 12075 (40%) were readmitted; congestive heart failure was the leading cause of readmission (12.5 %). In univariate analysis, we found a decreased risk of readmission in the more racially and economically privileged quintiles (Q2-Q5) of ICE race (HR 0.87-0.99) and ICE racialized income measures (HR 0.91-0.96) as compared to reference (Q1) but this was not significant across all quintiles. In fully adjusted competing risk regression models, we did not find a significant association with risk of readmission and measures of residential segregation. Conclusion: Measures of racial residential segregation are associated with increased risk of readmission among Medicare beneficiaries residing in less privileged ZIP codes, but not present after adjusting for important covariates.

7EMF Racial Residential Segregation and Long-term Outcomes Among Medicare Beneficiaries After Out-of-Hospital Cardiac Arrest

Racial and ethnic disparities in incidence and survival to hospital discharge following out-of-hospital cardiac arrest (OHCA) exist in the US, but impact on long-term outcomes are less well understood. Racial residential segregation, a product of long-standing systemic and institutional racism, has been associated with worse outcomes for several health conditions, but has not been evaluated in OHCA. Our objective was to examine the association of the index of concentration at the extremes (ICE), a set of measures of residential segregation, with differences in long-term survival after OHCA.

Population-Based Disparities in U.S. Urban Heat Exposure from 2003 to 2018.

Previous studies have shown, in the United States (U.S.), that communities of color are exposed to significantly higher temperatures in urban environments than complementary White populations. Studies highlighting this disparity have generally been cross-sectional and are therefore “snapshots” in time. Using surface urban heat island (SUHI) intensity data, U.S. Census 2020 population counts, and a measure of residential segregation, this study performs a comparative analysis between census tracts identified as prevalent for White, Black, Hispanic and Asian populations and their thermal exposure from 2003 to 2018. The analysis concentrates on the top 200 most populous U.S. cities. SUHI intensity is shown to be increasing on average through time for the examined tracts. However, based on raw observations the increase is only statistically significant for White and Black prevalent census tracts. There is a 1.25 K to ~2.00 K higher degree of thermal exposure on average for communities of color relative to White prevalent areas. When examined on an inter-city basis, White and Black prevalent tracts had the largest disparity, as measured by SUHI intensity, in New Orleans, LA, by <6.00 K. Hispanic (>7.00 K) and Asian (<6.75 K) prevalent tracts were greatest in intensity in San Jose, CA. To further explore temporal patterns, two models were developed using a Bayesian hierarchical spatial temporal framework. One models the effect of varying the percentages of each population group relative to SUHI intensity within all examined tracts. Increases in percentages of Black, Hispanic, and Asian populations contributed to statistically significant increases in SUHI intensity. White increases in population percentage witnessed a lowering of SUHI intensity. Throughout all modeled tracts, there is a statistically significant 0.01 K per year average increase in SUHI intensity. A second model tests the effect of residential segregation on thermal inequity across all examined cities. Residential segregation, indeed, has a statistically significant positive association with SUHI intensity based on this portion of the analysis. Similarly, there is a statistically significant 0.01 K increase in average SUHI intensity per year for all cities. Results from this study can be used to guide and prioritize intervention strategies and further urgency related to social, climatic, and environmental justice concerns.

Analysis of Eligibility for Lung Cancer Screening by Race After 2021 Changes to US Preventive Services Task Force Screening Guidelines

Lung cancer incidence and mortality have disproportionate consequences for racial and ethnic minority populations. The extent to which the 2021 changes to the US Preventive Services Task Force (USPSTF) screening guidelines have reduced the racial disparity gap in lung cancer screening eligibility is not known. To assess the consequences of the changes in USPSTF low-dose computed tomography eligibility criteria for lung cancer screening between 2013 and 2021 among Black and White community-dwelling adults. This cohort study analyzed data from the Reasons for Geographic and Racial Differences in Stroke study, a prospective longitudinal cohort study of community-dwelling Black and White adults 45 years and older who were initially recruited across the US between January 2003 and October 2007, with ongoing follow-up. All participants who would have been potentially eligible for lung cancer screening based on the 2021 USPSTF guidelines (N = 14 285) were included. Follow-up data for the current cohort study were collected and analyzed between January 2013 and December 2017, with final analysis performed in 2021. Self-reported Black vs White race. Differences in the proportion of Black vs White participants eligible for lung cancer screening according to 2013 and 2021 guidelines were assessed using modified Poisson models with robust SEs. Associations between important covariates (demographic characteristics and social factors associated with health), including interaction and dissimilarity indices (2 measures of residential segregation), and differences in screening eligibility were also examined. Among 14 285 participants (mean [SD] age, 64.7 [7.5] years; 7675 men [53.7%]), 5787 (40.5%) self-identified as Black and 8498 (59.5%) as White. Based on the 2013 USPSTF guidelines, 1109 of 5787 Black participants (19.2%) and 2313 of 8498 White participants (27.2%) were eligible for lung cancer screening (difference, -8.06 percentage points; 95% CI, -9.44 to -6.67 percentage points). Based on the 2021 guidelines, 1667 of 5787 Black participants (28.8%) and 2940 of 8498 White participants (34.6%) were eligible for screening (difference, -5.73 percentage points; 95% CI, -7.28 to -4.19 percentage points). After adjustment for differences in individual characteristics and residential segregation, the 2013 difference in screening eligibility among Black vs White participants was -12.66 percentage points (95% CI, -14.71 to -10.61 percentage points), and the 2021 difference was -12.15 percentage points (95% CI, -14.37 to -9.93 percentage points). In this study, 2021 changes to the USPSTF lung cancer screening guidelines were associated with reductions in but not elimination of existing eligibility disparities in lung cancer screening among Black and White adults. These findings suggest that accounting for factors beyond age and pack-years of smoking is needed when tailoring guidelines to improve screening eligibility among groups at high risk of lung cancer.

Assessing the Impact of Differential Privacy on Measures of Population and Racial Residential Segregation

The U.S. Census Bureau plans to use a new disclosure avoidance technique based on differential privacy to protect respondent confidentiality for the 2020 Decennial Census of Population and Housing. Their new technique injects noise based on a number of parameters into published statistics. While the noise injection does protect respondent confidentiality, it achieves the protection at the cost of less accurate data. To better understand the impact that differential privacy has on accuracy, we compare data from the complete-count 1940 Census with multiple differentially private versions of the same data set. We examine the absolute and relative accuracy of population counts in total and by race for multiple geographic levels, and we compare commonly used measures of residential segregation computed from these data sets. We find that accuracy varies by the global privacy-loss budget and the allocation of the privacy-loss budget to geographic levels (e.g., states, counties, enumeration district) and queries. For measures of segregation, we observe situations where the differentially private data indicate less segregation than the original data and situations where the differentially private data indicate more segregation than the original data. The sensitivity of accuracy to the overall global privacy-loss budget and its allocation highlight the fundamental importance of these policy decisions. Data producers like the U.S. Census Bureau must collaborate with users not only to determine the most useful set of parameters to receive allocations of the privacy-loss budget, but also to provide documentation and tools for users to gauge the reliability and validity of statistics from publicly released data products. If they do not, producers may create statistics that are unusable or misleading for the wide variety of use cases that rely on those statistics.

Abstract PO-171: Local economic and racial/ethnic segregation and breast cancer risk: The Multiethnic Cohort Study

Abstract Introduction: Residential segregation has been documented to contribute to health inequities. The Index of Concentration at the Extremes (ICE) is a local measure of residential segregation that can capture economic, racial, and combined racialized economic residential segregation. ICE measures have only recently been examined in cancer studies, few of which have focused on breast cancer risk and none among Asian American or Pacific Islander (AAPI) groups. In the Multiethnic Cohort Study (MEC), we examined the associations of neighborhood ICE measures with breast cancer incidence among 101,811 female participants in five racial/ethnic groups (African American, Latino, Japanese American, Native Hawaiian, and White). Methods: ICE measures were developed based on 1990 U.S. census tract-level data, categorized in quintiles based on Los Angeles county and Hawai'i state-specific distributions, and assigned to the residential census tract of MEC female participants residing, at study baseline, in California (CA) (primarily Los Angeles, n=56,880), and Hawai'i (HI) (n=44,931). Separate ICE measures were created for household income, education, race/ethnicity, and combined household income and race/ethnicity. Women, aged 45-75 at enrollment, completed a comprehensive lifestyle questionnaire and were followed from baseline (1993-1996) to earliest date of invasive breast cancer diagnosis (n=6,398), death, or end-of-follow-up (12/31/2014). Invasive breast cancer incidence was modeled using Cox proportional hazards regression adjusted for demographics, family history of breast cancer, reproductive and lifestyle factor factors. Stratified analyses were conducted by race/ethnicity and stage at diagnosis. Results: For women in CA MEC, there were significantly higher risks of breast cancer for those living in neighborhoods with more versus less concentrated privilege [Q5 v Q1 Hazard Ratios (HR): ICE income 1.16 (1.03-1.31), ICE education 1.21 (1.05-1.39)]. In stratified analyses, these patterns of associations were seen for African Americans, Latinos, and Japanese Americans. Risks were also higher among Japanese American women living in neighborhoods with greater concentrations of Whites versus AAPI [Q5 v Q1 ICE Race HR: 1.77 (1.22-2.57)] and for Latino women living in neighborhoods with greater concentrations of high income-White households versus low income-Hispanic households [Q4 v Q1 ICE Race + Income HR: 1.48 (1.20-1.82)]. For women in HI MEC, those living in neighborhoods with higher versus lower ICE income or ICE education had higher risk of localized stage at diagnosis and lower risk of regional &amp; distant diagnosis (p Het &amp;lt;0.01). No associations were found among White or Native Hawaiian women. Conclusions: Our findings suggest economic residential segregation plays an important role in breast cancer risk among African American, Latino, and Japanese American women. This study also highlights the importance of examining racial and racialized economic residential segregation separately across racial/ethnic groups. Citation Format: Jenna Khan-Gates, Salma Shariff-Marco, Katherine Lin, Pushkar Inamdar, Juan Yang, Yuqing Li, Meera Sangaramoorthy, Christopher Haiman, Loïc Le Marchand, Lynne R Wilkens, Scarlett L Gomez, Iona Cheng. Local economic and racial/ethnic segregation and breast cancer risk: The Multiethnic Cohort Study [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-171.

Neighborhood racial/ethnic segregation and cognition in older adults

AbstractBackgroundSocial determinants of health, including neighborhood factors, play a key role in the health of diverse older adults. Yet few longitudinal studies have examined the role of neighborhood racial/ethnic segregation on cognitive function and cognitive decline in both Latinos and Blacks, two populations at greater risk for Alzheimer’s disease and related dementias. We examined how one measure of residential segregation is associated with cognitive outcomes in a diverse cohort.MethodsWe evaluated older non‐Hispanic White (NHW), Black, and Latino participants evaluated at the UC Davis Alzheimer’s Disease Research Center. Individual level addresses were geocoded at the initial visit and appended to U.S. Census 2010 data. Residential segregation was measured using the Getis‐Ord Gi* statistic; this spatial measure of clustering was created for Latino and Black clustering separately. Cognitive outcomes included validated measures of episodic memory, semantic memory, and executive function. We used mixed effects multivariate regression models to evaluate associations between segregation and cognitive function and decline, controlling for age, sex, education, cognitive status at initial visit, clinic versus community recruited, site, vascular risk score, number of visits, neighborhood SES, and population density.ResultsThe sample included 452 participants (mean age=75, SD = 7), 64% female, and 46% NHW, 26% Black, and 21% Latino, in 309 census tracts/neighborhoods. In race‐stratified adjusted analyses, Blacks demonstrated worse episodic memory at baseline among those living in neighborhoods with a higher clustering of Blacks (ß = ‐0.046; 95% CI: ‐0.075, ‐0.016) and worse executive function at baseline among those living in neighborhoods with a higher clustering of Latinos (ß = ‐0.025; 95% CI: ‐0.042, ‐0.008). Latinos demonstrated slower annual declines on episodic memory when living in neighborhoods with a greater clustering of Blacks (ß = 0.008; 95% CI: 0.004, 0.011) and/or Latinos (ß = 0.003; 95% CI: 0.001, 0.005). NHWs had slower annual declines on semantic memory when living in neighborhoods with a greater clustering of Latinos (ß = 0.005; 95% CI: 0.001, 0.008).ConclusionsThere may be some benefit for Latinos and NHWs living in ethnically clustered neighborhoods. Future research is needed to further investigate these findings.

Impact of Residential Racial Integration on Postoperative Outcomes Among Medicare Beneficiaries Undergoing Resection for Cancer.

While social determinants of health may adversely affect various populations, the impact of residential segregation on surgical outcomes remains poorly defined. The objective of the current study was to examine the association between residential segregation and the likelihood to achieve a textbook outcome (TO) following cancer surgery. The Medicare 100% Standard Analytic Files were reviewed to identify Medicare beneficiaries who underwent resection of lung, esophageal, colon, or rectal cancer between 2013 and 2017. Shannon's integration index, a measure of residential segregation, was calculated at the county level and its impact on composite TO [no complications, no prolonged length of stay (LOS), no 90-day readmission, and no 90-day mortality] was examined. Among 200,509 patients who underwent cancer resection, the overall incidence of TO was 56.0%. The unadjusted likelihood of achieving a TO was lower among patients in low integration areas [low integration: n=19,978 (55.0%) vs. high integration: n=18,953 (59.3%); p<0.001]. On multivariable analysis, patients residing in low integration areas had higher odds of complications [odds ratio (OR) 1.07, 95% confidence interval (CI) 1.03-1.11], extended LOS (OR 1.13, 95% CI 1.09-1.18), and 90-day mortality (OR 1.29, 95% CI 1.22-1.38) and, in turn, lower odds of achieving a TO (OR 0.87, 95% CI 0.84-0.90) versus patients from highly integrated communities. Patients who resided in counties with a lower integration index were less likely to have an optimal TO following resection of cancer compared with patients who resided in more integrated counties. The data highlight the importance of increasing residential racial diversity and integration as a means to improve patient outcomes.

Residential Racial Segregation and Disparities in Breast Cancer Presentation, Treatment, and Survival.

To understand the role of racial residential segregation on Black-White disparities in breast cancer presentation, treatment, and outcomes. Racial disparities in breast cancer treatment and outcomes are well documented. Black individuals present at advanced stage, are less likely to receive appropriate surgical and adjuvant treatment, and have lower overall and stage-specific survival relative to White individuals. Using data from the Surveillance, Epidemiology, and End Results program, we performed a retrospective cohort study of Black and White patients diagnosed with invasive breast cancer from 2005 to 2015 within the 100 most populous participating counties. The racial index of dissimilarity was used as a validated measure of residential segregation. Multivariable regression was performed, predicting advanced stage at diagnosis (stage III/IV), surgery for localized disease (stage I/II), and overall stage-specific survival. After adjusting for age at diagnosis, estrogen/progesterone receptor status, and region, Black patients have a 49% greater risk (relative risk [RR] 1.49 95% confidence interval [CI] 1.27, 1.74) of presenting at advanced stage with increasing segregation, while there was no observed difference in Whites (RR 1.04, 95% CI 0.93, 1.16). Black patients were 3% less likely to undergo surgical resection for localized disease (RR 0.97, 95% CI 0.95, 0.99) with increasing segregation, while Whites saw no significant difference. Black patients had a 29% increased hazard of death (RR 1.29, 95% CI 1.04, 1.60) with increasing segregation; there was no significant difference among White patients. Our data suggest that residential racial segregation has a significant association with Black-White racial disparities in breast cancer. These findings illustrate the importance of addressing structural racism and residential segregation in efforts to reduce Black-White breast cancer disparities.

The shape of segregation: The role of urban form in immigrant assimilation

The built environment can mediate or constrain the opportunities for social interaction, essential to the formation of social ties. This study uses the large inflow of immigrants in Barcelona between 1998 and 2008 to study whether the configuration of buildings and open urban areas in a block is associated with the residential segregation of immigrants—a proxy for social interaction. Based on a rich set of shape metrics, I use machine learning techniques to classify each block in Barcelona into one of eight typologies, which provide a summary measure of their built environment. I then combine these data with measures of residential segregation constructed at the building level using data on the exact address of each resident of Barcelona. The findings show that some features of the built environment of a block—as measured by the typologies—are systematically associated with reduced residential segregation of Spaniards and newly arrived immigrants in that block.

Accounting for Demography and Preferences: New Estimates of Residential Segregation with Minimum Segregation Measures

The index of dissimilarity (D) has historically been and continues to be a widely used quantitative measure of residential segregation. Conventional interpretations of D imply that normatively desirable residential patterns occur when ethnoracial compositions of lower-order geographic units (such as neighborhoods) match those of higher-order units (such as metropolitan areas). However, it is likely that average preferences for same-group contact in neighborhoods sometimes exceed group population shares in metropolitan areas. In such situations, there is mathematical tension between the capacity for group preferences for co-ethnic neighbors to be satisfied and the degree of residential segregation. In this article, I quantify this tension by calculating DΔ, or the difference between D and the minimum segregation measure D*, which returns the lower bound on segregation for a given average in-group preference level and ethnoracial share. Positive scores on DΔ indicate that a metropolitan area is more segregated than necessary to satisfy average group preferences, while negative scores indicate that observed residential patterns do not satisfy such preferences. I use data from the 2010 decennial census and 2006–2010 American Community Survey to analyze the associations between predictors of residential segregation and DΔ.

Rural Segregation and Racial Violence: Historical Effects of Spatial Racism

AbstractTo review the evidence of changes in segregation over time, we use a newly developed household‐level measure of residential segregation that can distinguish between the effects of increasing racial homogeneity of a location and the tendency to segregate within a location given a particular racial composition (Logan and Parman ). This household measure of segregation reveals high levels of segregation in the South and rising levels of segregation in both cities and rural communities over the first half of the 20th century. We review new evidence that this segregation was highly correlated with interracial violence in the form or lynchings. We conclude with a discussion of the interaction between residential segregation, racial animosity, and violence.

Unpacking Summary Measures of Ethnic Residential Segregation Using an Age Group and Age Cohort Perspective

The residential segregation literature has underplayed the significance of age in shaping the ethnic compositions of neighbourhoods. This paper develops an age group and age cohort perspective as a way to unpack summary measures of residential segregation. Harmonised small area data for England and Wales (2001–2011) are used as a case study to explore the potential of this methodology for understanding better the role of age in the evolution of ethnic residential geographies. Our findings demonstrate the age-specificity of residential segregation, for both cross-sectional patterns and change over time. Levels of segregation vary among age groups and age cohorts and between ethnic groups, with a changing pattern of segregation as people age. Exploring change over a 10-year period, we observe that residential segregation decreases during young adulthood for all age cohorts, then increases during the late 20s and early 30s, and continues to increase until retirement. These trends are, for the most, consistent between ethnic groups. Our findings emphasise how residential segregation is a dynamic process with a significant life cycle component, with commonalities in residential decision-making between ethnic groups through the life course.

Racial Segregation and Southern Lynching

The literature on ethnic fractionalization and conflict has yet to be extended to the American past. In particular, the empirical relationship between racial residential segregation and lynching is unknown. The existing economic, social, and political theories of lynching contain implicit hypotheses about the relationship between racial segregation and racial violence, consistent with more general theories of social conflict. Because Southern lynching occurred in rural and urban areas, traditional urban measures of racial segregation cannot be used to estimate the relationship. Earlier analysis has analyzed the relationship between lynching and racial proportions, a poor proxy for racial segregation. We use a newly developed household-level measure of residential segregation (Logan and Parman 2017) that can distinguish between the effects of increasing racial homogeneity of a location and the tendency to segregate within a location given a particular racial composition to estimate the correlation between racial segregation and lynching in the southern counties of the United States. We find that conditional on racial composition, racially segregated counties were much more likely to experience lynchings. Consistent with the hypothesis that segregation is related to interracial violence, we find that segregation is highly correlated with African American lynching but uncorrelated with white lynching. These results extend the analysis of racial/ethnic conflict into the past and show that the effects of social interactions and interracial proximity in rural areas are as important as those in urban areas.

African American Digital Practices: Mobile E-Health and Residential Segregation

ABSTRACTWe ask two questions about the relationship between race, using mobile phones for e-health, and living in segregated neighborhoods: Are racial differences associated with using mobile phones for e-health, especially as they relate to African Americans? Is living in segregated neighborhoods associated with changes in mobile phone usage? We merge the National Trends Survey (HINTS) conducted by the National Cancer Institute, for information on e-health, and the US 2010 project, for the necessary measures of residential segregation. Multilevel models (Level 1 N = 2,023, Level 2 N = 183) produced two major conclusions. First, African Americans exhibit unique “digital practices” vis-à-vis e-health, such that they use e-health to share personal diagnostic information less than whites but use e-health for more practical, logistical uses than do whites. Second, residential segregation is associated with digital practices; however, considering racial differences in where people live does not reduce racial differences in e-health patterns.