Ride-hailing technology mitigates effects of driver racial discrimination, but effects of residential segregation persist.

We assess racial disparities in the service quality of app-based ride-hailing services, like Uber and Lyft, by simulating their operations in the city of Chicago using empirical data. To generate driver cancellation rate disparities consistent with controlled experiments (up to twice as large for Black riders as for White riders), we estimate that more than 3% of drivers discriminate by race. We find that the capabilities of ride-hailing technology to rapidly rematch after a cancellation and prioritize long-waiting customers heavily mitigates the effects of driver discrimination on rider wait times, reducing average discrimination-induced disparities to less than 1 min-an order of magnitude less than traditional taxis. However, our results suggest that even in the absence of direct driver discrimination, Black riders in Chicago wait about 50% longer, on average, than White riders because of historically informed geographic residential patterns. We estimate that if Black riders in the city had the same wait times as White riders, the collective travel time saved would be worth $4.2 million to $7.0 million per year.

The Role of Neighborhood Air Pollution in Disparate Racial and Ethnic Asthma Acute Care Use.

Rationale: The share of Black or Latinx residents in a census tract remains associated with asthma-related emergency department (ED) visit rates after controlling for socioeconomic factors. The extent to which evident disparities relate to the within-city heterogeneity of long-term air pollution exposure remains unclear. Objectives: To investigate the role of intraurban spatial variability of air pollution in asthma acute care use disparity. Methods: An administrative database was used to define census tract population-based incidence rates of asthma-related ED visits. We estimate the associations between census tract incidence rates and 1) average fine and coarse particulate matter, nitrogen dioxide (NO2), and sulfur dioxide (SO2), and 2) racial and ethnic composition using generalized linear models controlling for socioeconomic and housing covariates. We also examine for the attenuation of incidence risk ratios (IRRs) associated with race/ethnicity when controlling for air pollution exposure. Measurements and Main Results: Fine and coarse particulate matter and SO2 are all associated with census tract-level incidence rates of asthma-related ED visits, and multipollutant models show evidence of independent risk associated with coarse particulate matter and SO2. The association between census tract incidence rate and Black resident share (IRR, 1.51 [credible interval (CI), 1.48-1.54]) is attenuated by 24% when accounting for air pollution (IRR, 1.39 [CI, 1.35-1.42]), and the association with Latinx resident share (IRR, 1.11 [CI, 1.09-1.13]) is attenuated by 32% (IRR, 1.08 [CI, 1.06-1.10]). Conclusions: Neighborhood-level rates of asthma acute care use are associated with local air pollution. Controlling for air pollution attenuates associations with census tract racial/ethnic composition, suggesting that intracity variability in air pollution could contribute to neighborhood-to-neighborhood asthma morbidity disparities.

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

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.

Association between racial residential segregation and screening uptake for colorectal and cervical cancer among Black and White patients in five US health care systems.

BACKGROUND: Despite increased recognition that structural racism contributes to poorer health outcomes for racial and ethnic minorities, there are knowledge gaps about how current patterns of racial residential segregation are associated with cancer screening uptake. The authors examined associations between Black residential segregation and screening for colorectal cancer (CRC) and cervical cancer among non-Hispanic Black and non-Hispanic White adults. METHODS: This was a retrospective study of CRC and cervical cancer screening-eligible adults from five health care systems within the Population-Based Research to Optimize the Screening Process (PROSPR II) Consortium (cohort entry, 2010-2012). Residential segregation was measured using site-specific quartiles of the Black local isolation score (LIS). The outcome was receipt of CRC or cervical cancer screening within 3 years of cohort entry (2010-2015). Logistic regression was used to calculate associations between the LIS and screening completion, adjusting for patient-level covariates. RESULTS: Among CRC (n = 642,661) and cervical cancer (n = 163,340) screening-eligible patients, 456,526 (71.0%) and 106,124 (65.0%), respectively, received screening. Across PROSPR sites, living in neighborhoods with higher LIS tended to be associated with lower odds of CRC screening (Kaiser Permanente Northern California: adjusted odds ratio [aOR] LIS trend in Black patients, 0.95 [p < .001]; aOR LIS trend in White patients, 0.98 [p < .001]; Kaiser Permanente Southern California: aOR LIS trend in Black patients, 0.98 [p = .026]; aOR LIS trend in White patients, 1.01 [p = .023]; Kaiser Permanente Washington: aOR LIS trend in White patients, 0.97 [p = .002]. However, for cervical cancer screening, associations with the LIS varied by site and race (Kaiser Permanente Washington: aOR LIS trend in White patients, 0.95 [p < .001]; Mass General Brigham: aOR LIS trend in Black patients, 1.12 [p < .001]; aOR LIS trend in White patients, 1.03 [p < .001]). CONCLUSIONS: Across five diverse health care systems, the direction of the association between Black residential segregation and screening varied by PROSPR site, race, and screening type. Additional research, including studies that examine multiple dimensions of segregation and structural racism using intersectional approaches, are needed to further disentangle these relationships.

Associations of neighborhood sociodemographic environment with mortality and circulating metabolites among low-income black and white adults living in the southeastern United States.

BACKGROUND: Residing in a disadvantaged neighborhood has been linked to increased mortality. However, the impact of residential segregation and social vulnerability on cause-specific mortality is understudied. Additionally, the circulating metabolic correlates of neighborhood sociodemographic environment remain unexplored. Therefore, we examined multiple neighborhood sociodemographic metrics, i.e., neighborhood deprivation index (NDI), residential segregation index (RSI), and social vulnerability index (SVI), with all-cause and cardiovascular disease (CVD) and cancer-specific mortality and circulating metabolites in the Southern Community Cohort Study (SCCS). METHODS: The SCCS is a prospective cohort of primarily low-income adults aged 40-79, enrolled from the southeastern United States during 2002-2009. This analysis included self-reported Black/African American or non-Hispanic White participants and excluded those who died or were lost to follow-up ≤ 1 year. Untargeted metabolite profiling was performed using baseline plasma samples in a subset of SCCS participants. RESULTS: Among 79,631 participants, 23,356 deaths (7214 from CVD and 5394 from cancer) were documented over a median 15-year follow-up. Higher NDI, RSI, and SVI were associated with increased all-cause, CVD, and cancer mortality, independent of standard clinical and sociodemographic risk factors and consistent between racial groups (standardized HRs among all participants were 1.07 to 1.20 in age/sex/race-adjusted model and 1.04 to 1.08 after comprehensive adjustment; all P < 0.05/3 except for cancer mortality after comprehensive adjustment). The standard risk factors explained < 40% of the variations in NDI/RSI/SVI and mediated < 70% of their associations with mortality. Among 1110 circulating metabolites measured in 1688 participants, 134 and 27 metabolites were associated with NDI and RSI (all FDR < 0.05) and mediated 61.7% and 21.2% of the NDI/RSI-mortality association, respectively. Adding those metabolites to standard risk factors increased the mediation proportion from 38.4 to 87.9% and 25.8 to 42.6% for the NDI/RSI-mortality association, respectively. CONCLUSIONS: Among low-income Black/African American adults and non-Hispanic White adults living in the southeastern United States, a disadvantaged neighborhood sociodemographic environment was associated with increased all-cause and CVD and cancer-specific mortality beyond standard risk factors. Circulating metabolites may unveil biological pathways underlying the health effect of neighborhood sociodemographic environment. More public health efforts should be devoted to reducing neighborhood environment-related health disparities, especially for low-income individuals.

Association of Racial Residential Segregation and Other Social Determinants of Health with HIV Late Presentation.

Understanding social determinants of HIV late presentation with advanced disease (LPWA) beyond individual-level factors could help decrease LPWA and improve population-level HIV outcomes. This study aimed to examine county-level social determinants of health (SDOH) with HIV late presentation. We aggregated datasets for analysis by linking statewide HIV diagnosis data from the South Carolina (SC) Enhanced HIV/AIDS Reporting System and multiple social contextual datasets (e.g., the American Community Survey). All adult (18 years and older) people with HIV diagnosed from 2014 to 2019 in SC were included. Linear mixed models with forward selection were employed to explore the association of county-level SDOH with the county-level three-year moving average percentage of LPWA and average delay time from HIV infection to diagnosis. Around 30% of new HIV diagnoses were LPWA in SC, and the mean delay time for people with LPWA was approximately 13 years. Counties with more racial residential segregation had longer average delay time (Adjusted beta = 5.079, 95% CI: 0.268 ~ 9.889). Regarding other SDOH, the increased percentage of LPWA was associated with fewer Ryan White centers per 100,000 population (Adjusted beta = -0.006, 95% CI: -0.011~-0.001) and higher percentages of the population with less than a high school education (Adjusted beta = 0.008, 95% CI: 0 ~ 0.015). Reducing county-level disparities in LPWA requires multifaceted interventions addressing multiple dimensions of SDOH. Targeted interventions are needed for counties with more Black residential segregation, fewer Ryan White centers, and higher percentages of less than high school education.

County-level Racial/Ethnic Residential Segregation and Physical Activity Behavior among US Adults.

The relationship between racial/ethnic residential segregation and physical activity (PA) remains unclear with both positive and negative associations between segregation and PA recently reported. We aimed to examine the relationship between county-level residential segregation and total daily PA and domain-specific PA and whether these associations varied by gender. Participants (N = 2625, mean age [SD] = 45.2 [15.4]) were recruited from the AmeriSpeak panel who completed up to two Activities Completed over Time in 24 Hours (ACT24) previous day recalls in 2019. PA outcomes were created for the following: (1) light PA (LPA), (2) moderate-to-vigorous PA (MVPA), (3) total active time, and (4) domain-specific PA, including leisure, work, household, transport, personal, and other activities. County-level residential segregation based on isolation. Weighted generalized linear models were used to examine the relationship between county-level segregation and each PA outcome, controlling for age, gender, race/ethnicity, income, employment, body mass index, county-level poverty, and census region. Overall, results showed no association between county-level residential segregation and LPA, MVPA, total active time, and domain-specific PA among NH Black and Hispanic populations. Among NH Black females, greater residential segregation was associated with more total hours/day of activity (ß = 3.54, 95% CI [0.23, 6.85]). Only NH Black females living in segregated neighborhoods had more total active time. Additionally, it is important to acknowledge that these relationships may vary among NH Black and Hispanic populations. Future studies should examine the interaction between segregation and a broader range of individual, contextual, and environmental factors in relation to PA and domain-specific PA.

Individual and Neighborhood Level Predictors of Children's Exposure to Residential Greenspace.

Inequities in urban greenspace have been identified, though patterns by race and socioeconomic status vary across US settings. We estimated the magnitude of the relationship between a broad mixture of neighborhood-level factors and residential greenspace using weighted quantile sum (WQS) regression, and compared predictive models of greenspace using only neighborhood-level, only individual-level, or multi-level predictors. Greenspace measures included the Normalized Difference Vegetation Index (NDVI), tree canopy, and proximity of the nearest park, for residential locations in Shelby County, Tennessee of children in the CANDLE cohort. Neighborhood measures include socioeconomic and education resources, as well as racial composition and racial residential segregation. In this sample of 1012 mother-child dyads, neighborhood factors were associated with higher NDVI and tree canopy (0.021 unit higher NDVI [95% CI: 0.014, 0.028] per quintile increase in WQS index); homeownership rate, proximity of and enrollment at early childhood education centers, and racial composition, were highly weighted in the WQS index. In models constrained in the opposite direction (0.028 unit lower NDVI [95% CI: - 0.036, - 0.020]), high school graduation rate and teacher experience were highly weighted. In prediction models, adding individual-level predictors to the suite of neighborhood characteristics did not meaningfully improve prediction accuracy for greenspace measures. Our findings highlight disparities in greenspace for families by neighborhood socioeconomic and early education factors, and by race, suggesting several neighborhood indicators for consideration both as potential confounders in studies of greenspace and pediatric health as well as in the development of policies and programs to improve equity in greenspace access.

Still Separate, Still Not Equal: An Ecological Examination of Redlining and Racial Segregation with COVID-19 Vaccination Administration in Washington D.C.

Racial residential segregation has been deemed a fundamental cause of health inequities. It is a result of historical and contemporary policies such as redlining that have created a geographic separation of races and corresponds with an inequitable distribution of health-promoting resources. Redlining and racial residential segregation may have contributed to racial inequities in COVID-19 vaccine administration in the early stages of public accessibility. We use data from the National Archives (historical redlining), Home Mortgage Disclosure Act (contemporary redlining), American Community Survey from 1940 (historical racial residential segregation) and 2015-2019 (contemporary racial residential segregation), and Washington D.C. government (COVID-19 vaccination administration) to assess the relationships between redlining, racial residential segregation, and COVID-19 vaccine administration during the early stages of vaccine distribution when a tiered system was in place due to limited supply. Pearson correlation was used to assess whether redlining and racial segregation, measured both historically and contemporarily, were correlated with each other in Washington D.C. Subsequently, linear regression was used to assess whether each of these measures associate with COVID-19 vaccine administration. In both historical and contemporary analyses, there was a positive correlation between redlining and racial residential segregation. Further, redlining and racial residential segregation were each positively associated with administration of the novel COVID-19 vaccine. This study highlights the ongoing ways in which redlining and segregation contribute to racial health inequities. Eliminating racial health inequities in American society requires addressing the root causes that affect access to health-promoting resources.

Daily Diversity Flows: Racial and Ethnic Context Between Home and Work.

The racial and ethnic diversification of the U.S. population has transformed the demographic makeup of communities and rapidly increased exposure to diversity in American neighborhoods. Although diversity exposure occurs throughout people's daily lives, the conventional approach to describing diversity only at places of residence potentially understates the full extent of this phenomenon. In this study, we explore short-term, within-day changes in the diversity of different neighborhoods by considering U.S. workers' work and residential locations. Using estimates for daytime and nighttime populations among metropolitan census tracts, our empirical analyses investigate the extent to which the process of daytime mobility for work relates to changes in the racial and ethnic diversity of different spaces. Our results indicate widespread daily shifts toward diversity for most neighborhood types, especially those with residential (nighttime) populations that are predominantly Black, Latino, or Asian. We find that patterns of intraday diversification experienced minor declines across recent decades but are present in most metropolitan areas. Our findings also show that intraday changes in racial and ethnic diversity overlap with nonracial forms of daily diversity change. Further, average within-day changes in diversity are more pronounced in areas with greater residential segregation.

New Evidence From Census 2020 on the Residential Segregation of Same-Sex Households: A Research Note.

The 2020 decennial census provides new insights into the demography of same-sex households and can shed light on ongoing debates in urban and gayborhood studies. Although the U.S. Census gives a vast undercount of the LGBTQ population, it is still the largest source of nationally representative data on same-sex households and is accessible over three time points (2000, 2010, 2020). In this research note, we use 2020 census data to examine the residential patterns of same-sex households down to the neighborhood level. By employing the index of dissimilarity, we present results for the 100 largest U.S. cities and 100 largest metropolitan areas that demonstrate moderate yet persistent segregation. In a continuation of prior trends, male same-sex households remain more segregated from different-sex households than do female same-sex households. We find moderate levels of within-group segregation by gender and marital status-representing new demographic trends. Finally, metropolitan areas have a higher dissimilarity index than cities, revealing greater levels of segregation when factoring in suburban areas. We discuss these trends in light of debates regarding the spatial organization of sexuality in residential contexts and outline future avenues for research utilizing recently released 2020 census data.

Relationship between body mass index and residential segregation in large cities of Latin America.

BACKGROUND: Obesity is a global health problem, and its connection with social and environmental factors is well-established. Social factors, such as urban segregation, may impact obesity through various mechanisms, including food and physical activity environments, as well as social norms and networks. This multilevel study aims to examine the effect of socio-economic residential segregation of Latin American cities on the obesity of individuals within those cities. METHODS: We analyzed data from national surveys for a total of 59,340 individuals of 18-70 years of age, conducted in 156 cities across Brazil, Chile, Colombia, and Mexico between 2007 and 2013. We adjusted two-level linear mixed models for body mass index (BMI) stratified by sex and country, controlling for age, educational level and poverty. Separate models were built for dissimilarity and isolation segregation indices. RESULTS: The relationships between segregation indices and BMI were mostly not statistically significant, and in some cases, they were opposite to what was expected. The only significant relationships were observed in Colombian men, using the dissimilarity index (-7.5 [95% CI: -14.4, -0.5]) and in Colombian women, using the isolation index (-7.9 [95% CI: -14.1, -1.7]). CONCLUSIONS: While individual-level factors cannot fully explain differences among people in the same city, segregation indices may help. However, we found that in some cases, the relationship between BMI and segregation indices is opposite to what is expected based on prior literature. This should be considered in examining the phenomenon. Further research on obesogenic environments in segregated neighborhoods could provide valuable evidence.

"You're Just Stuck in a Hole, Really": Mechanisms of Structural Racism Through Migrant Agricultural Worker Housing in Canada.

Worldwide, migrant agricultural workers face poor housing conditions and related health challenges. A growing body of research has documented the substandard housing often occupied by this largely racialized population. Yet limited health research has examined mechanisms of structural racism that determine this group's poor housing and health. Drawing on interviews with 151 migrant farmworkers in Ontario and British Columbia, Canada, we documented the housing experiences faced by migrant agricultural workers and examined the role of structural racism in determining housing and health inequities. Our analysis identified four overlapping mechanisms by which migrants' housing and health were determined by structural racism: (1) scarcity, (2) segregation, (3) sacrifice, and (4) stagnation. These mechanisms both reinforced and normalized housing hardships, making it difficult for migrants to escape unsafe or inadequate housing. Our findings point to the need for immediate action to improve housing conditions for this population and to interrogate the racist design that keeps migrant workers at the margins of society.

In Search of the Promised Land: County-Level Disadvantage and Low Birth Weight among Black Mothers of the Great Migration.

The Great Migration was a movement of roughly eight million Black Southerners relocating to the North and West from 1910 to 1980. Despite being one of the most significant mass internal migrations during the twentieth century, little is known about the health outcomes resulting from migration and whether migrators' destination choices were potential mechanisms. This study measured the association between destination county disadvantage and odds of low birth weight during the last decade of the Great Migration. We used the US Census from 1970 as well as the birth records of first-time Black mothers who migrated from the South collected through the National Center of Health Statistics from 1973 to 1980 (n = 154,145). We examined three measures of area-based opportunity: Black male high school graduation rate, Black poverty rate, and racialized economic residential segregation. We used multilevel logistic regression, where mothers were nested within US counties, to quantify the relationship between county disadvantage and low birth weight. After adjusting for individual risk and protective factors for infant health, there was no relationship between county opportunity measures and low birth weight among migrators. Although high socioeconomic opportunity is typically associated with protection of low birth weight, we did not see these outcomes in this study. These results may support that persistent racial discrimination encountered in the North inhibited infant health even as migrators experienced higher economic opportunity relative to the South.

Association between Racial Residential Segregation and COVID-19 Mortality.

This study investigates the impact of racial residential segregation on COVID-19 mortality during the first year of the US epidemic. Data comes from the Center for Disease Control and Prevention (CDC), and the Robert Wood Johnson Foundation's and the University of Wisconsin's joint county health rankings project. The observation includes a record of 8,670,781 individuals in 1488 counties. We regressed COVID-19 deaths, using hierarchical logistic regression models, on individual and county-level predictors. We found that as racial residential segregation increased, mortality rates increased. Controlling for segregation, Blacks and Asians had a greater risk of mortality, while Hispanics and other racial groups had a lower risk of mortality, compared to Whites. The impact of racial residential segregation on COVID-19 mortality did not vary by racial group.

Neighborhood-level Residential Isolation and Neighborhood Composition: Similar but Different.

Residential segregation has been considered as a potential cause of racial and/or ethnic disparities in health. Among the five dimensions of residential segregation, the isolation dimension has been conceived to play an essential role in disproportionately shaping the health of racial and ethnic minorities, particularly in urban or metropolitan areas. However, a noticeable amount of research studies has been using informal measures of neighborhood composition (i.e., proportions or percentages), which do not capture any of the five dimensions of residential segregation. Since the inappropriateness of measurement may obstruct a meaningful interpretation and an effective dissemination of research findings, a combination of graphical and non-graphical techniques was used to demonstrate the similarities and differences between formal measures of neighborhood-level residential isolation and informal measures of neighborhood composition. These were intended to provide intuitive and mutual understandings across academic disciples (e.g., city or urban planning, geography, public health, and sociology) and practitioners or professionals in multiple fields (e.g., community development workers, health service providers, policymakers, and social workers). Conceptual and methodological explanations with analytical discussions are also provided to differentiate and/or distinguish the two types of measures. While the concepts, methodologies, and research implications discussed herein are most relevant for research studies in urban or metropolitan areas of the United States, the general framework is also applicable to those of other industrialized counties.

Geographic and social economic disparities in the risk of exposure to ambient air respiratory toxicants at Oklahoma licensed early care and education facilities.

BACKGROUND: Early life exposures to hazardous air pollutants has been associated with adverse asthma-related outcomes. Neighborhood-level social and economic factors play an essential role in the distribution of hazardous air pollutants and children spend a substantial amount of time at early care and education (ECE) facilities. While the indoor air quality of these facilities has been described, particularly for criteria air pollutants such as volatile organic compounds and particulate matter, little is known about the ambient air quality of ECE facilities. OBJECTIVES: We conducted a cross-sectional study to estimate the ambient air quality of Oklahoma licensed ECE facilities and to explore associations between ambient air quality and select geographic predictors. METHODS: We estimated ambient air quality using the total respiratory hazard quotient from the National Air Toxics Assessment according to the geographical location of licensed Oklahoma ECE facilities (N = 3184). We then determined whether urban and rural ECE facilities' air respiratory toxicant exposure risk differed by ECE facilities' neighborhood-level social and economic inequities including: 1) racial-ethnic minority community, 2) neighborhood socioeconomic status, and 3) residential segregation. RESULTS: Urban ECE facilities in Hispanic segregated counties were five times more likely to be at risk of high air respiratory exposure, adjusted for integrated urban counties (p < 0.0001, 95% CI [3.824, 7.699]). Rural ECE facilities in African American segregated counties were nine times more likely to be at risk of high air respiratory toxicant exposure, adjusted for integrated rural counties (p < 0.0001, 95% CI [5.641, 15.928]). CONCLUSION: We found geographically and socially disparate patterns of higher exposures to ambient air respiratory toxicants at Oklahoma ECE facilities. Safer siting policies and interventions are needed to mitigate air respiratory toxicant exposures, which may help to reduce asthma control disparities and improve respiratory health outcomes in Oklahoma ECE facilities.

It Is Surprisingly Difficult to Measure Income Segregation.

Recent studies have shown that U.S. Census- and American Community Survey (ACS)-based estimates of income segregation are subject to upward finite sampling bias (Logan et al. 2018; Logan et al. 2020; Reardon et al. 2018). We identify two additional sources of bias that are larger and opposite in sign to finite sampling bias: measurement error-induced attenuation bias and temporal pooling bias. The combination of these three sources of bias make it unclear how income segregation has trended. We formalize the three types of bias, providing a method to correct them simultaneously using public data from the decennial census and ACS from 1990 to 2015-2019. We use these methods to produce bias-corrected estimates of income segregation in the United States from 1990 to 2019. We find that (1) segregation is on the order of 50% greater than previously believed; (2) the increase from 2000 to the 2005-2009 period was much greater than indicated by previous estimates; and (3) segregation has declined since 2005-2009. Correcting these biases requires good estimates of the reliability of self-reported income and of the year-to-year volatility in neighborhood mean incomes.

Racial residential segregation and COVID-19 vaccine uptake: an analysis of Georgia USA county-level data.

BACKGROUND: Foundational literature demonstrates that racial residential segregation results in poorer health outcomes for Black people than white people due to a variety of social determinants of health. COVID-19 vaccine uptake is important for better health outcomes, regardless of race. The COVID-19 pandemic has elevated concerns about racial health disparities but with little discussion of racial residential segregation as a predictor of disparate health outcomes. This paper investigates the relationship between racial residential segregation and COVID-19 vaccine uptake using county level data from the State of Georgia (USA). METHODS: Using publicly available data, regression analysis is conducted for 138 of the 159 counties in Georgia USA, using a dissimilarity index that describes county level differences in racial residential segregation. The primary independent variable is Black-white differences in vaccine uptake at the county level. The analytic methods focus on a spatial analysis to support information for county level health departments as the basis for health policy and resource allocation. RESULTS: Constructing a variable of the difference in vaccination rates between Black and white residents we find that Black-white differences in COVID-19 vaccination are most notable in the 69 most segregated of the 159 counties in Georgia. A ten-point lower segregation index is associated with an improvement in the Black-white vaccination gap of 1.5 percentage points (95% CI -0.31, -0.00). Income inequality and access to health care resources, such as access to a primary care physician, also predict Black-white differences in vaccination rates at the county level. Suggested mapping approaches of publicly available data at a state county level, provides a resource for local policy makers to address future challenges for epidemic and pandemic situations. CONCLUSION: County level and geospatial data analysis can inform policy makers addressing the impact of racial residential segregation on local health outcomes, even for pandemic and epidemic issues.

Segmented information, segregated outcomes: Housing affordability and neighborhood representation on a voucher-focused online housing platform and three mainstream alternatives.

Online platforms have become an integral component of the housing search process in the United States and other developed contexts, but recent studies have demonstrated that these platforms offer uneven representation of different neighborhoods. In this study, we use listings covering the largest 50 U.S. metropolitan areas to assess how GoSection8, a platform uniquely focused on affordable housing and voucher-assisted households, compares with "mainstream" alternatives of Craigslist, Apartments.com and Zillow. Through descriptive and regression analyses of the housing and neighborhoods represented on these websites and a new way of measuring the distribution of rental housing opportunities, we advance a multisource perspective on the role of online information exchanges in housing search processes. Specifically, we find that GoSection8 and mainstream alternatives capture spatially-segmented information about housing markets, with GoSection8 ads representing units that are more affordable but also more constrained to higher-poverty neighborhoods where assisted households are already concentrated. The findings suggest that disadvantaged households are potentially funneled toward high-poverty, isolated neighborhoods by the operation of stratified information systems available for online housing searches.