Low-poverty Neighborhoods Research Articles

Racial and Ethnic Disparities in Health Care Usage and Death by Neighborhood Poverty Among Individuals With Congenital Heart Defects, 4 US Surveillance Sites, 2011 to 2013.

Socioeconomic factors may lead to a disproportionate impact on health care usage and death among individuals with congenital heart defects (CHD) by race, ethnicity, and socioeconomic factors. How neighborhood poverty affects racial and ethnic disparities in health care usage and death among individuals with CHD across the life span is not well described. Individuals aged 1 to 64 years, with at least 1 CHD-related International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code were identified from health care encounters between January 1, 2011, and December 31, 2013, from 4 US sites. Residence was classified into lower- or higher-poverty neighborhoods on the basis of zip code tabulation area from the 2014 American Community Survey 5-year estimates. Multivariable logistic regression models, adjusting for site, sex, CHD anatomic severity, and insurance-evaluated associations between race and ethnicity, and health care usage and death, stratified by neighborhood poverty. Of 31 542 individuals, 22.2% were non-Hispanic Black and 17.0% Hispanic. In high-poverty neighborhoods, non-Hispanic Black (44.4%) and Hispanic (47.7%) individuals, respectively, were more likely to be hospitalized (adjusted odds ratio [aOR], 1.2 [95% CI, 1.1-1.3]; and aOR, 1.3 [95% CI, 1.2-1.5]) and have emergency department visits (aOR, 1.3 [95% CI, 1.2-1.5] and aOR, 1.8 [95% CI, 1.5-2.0]) compared with non-Hispanic White individuals. In high poverty neighborhoods, non-Hispanic Black individuals with CHD had 1.7 times the odds of death compared with non-Hispanic White individuals in high-poverty neighborhoods (95% CI, 1.1-2.7). Racial and ethnic disparities in health care usage were similar in low-poverty neighborhoods, but disparities in death were attenuated (aOR for non-Hispanic Black, 1.2 [95% CI=0.9-1.7]). Racial and ethnic disparities in health care usage were found among individuals with CHD in low- and high-poverty neighborhoods, but mortality disparities were larger in high-poverty neighborhoods. Understanding individual- and community-level social determinants of health, including access to health care, may help address racial and ethnic inequities in health care usage and death among individuals with CHD.

Residential mobility and persistently depressed voting among disadvantaged adults in a large housing experiment

This study examines the impact of residential mobility on electoral participation among the poor by matching data from Moving to Opportunity, a US-based multicity housing-mobility experiment, with nationwide individual voter data. Nearly all participants in the experiment were Black and Hispanic families who originally lived in high-poverty public housing developments. Notably, the study finds that receiving a housing voucher to move to a low-poverty neighborhood decreased adult participants' voter participation for nearly two decades-a negative impact equal to or outpacing that of the most effective get-out-the-vote campaigns in absolute magnitude. This finding has important implications for understanding residential mobility as a long-run depressant of voter turnout among extremely low-income adults.

Does Poor Health Influence Residential Selection? Understanding Mobility Among Low-Income Housing Voucher Recipients in the Moving to Opportunity Study

Housing-mobility programs and housing choice vouchers provide low-income families with a potentially transformative opportunity to move to low-poverty neighborhoods. However, families often face barriers to attaining upward residential mobility; poor health may be one important barrier, although few studies have examined this hypothesis. We used the experimental Moving to Opportunity for Fair Housing Demonstration Project (MTO) Study, constructed residential trajectories, and linked neighborhood opportunity measures to over 14,000 addresses of 3526 families across 7 years. We used latent growth curve longitudinal models to test how baseline health modified effects of MTO housing voucher treatment on neighborhood opportunity trajectories. Results show that poor baseline health adversely influenced how the voucher induced upward mobility. Voucher receipt strongly promoted residential mobility if families were healthy; moreover, the low-poverty neighborhood voucher plus counseling treatment promoted higher-opportunity neighborhood attainment than controls, regardless of the baseline health of the family. However, families with health vulnerabilities did not retain the same initial neighborhood gains conferred by the housing choice voucher (HCV) treatment as families without health vulnerabilities. These results suggest that housing counseling may be one necessary element to expand neighborhood choice into higher-opportunity neighborhoods for families with health challenges. Providing housing vouchers alone is insufficient to promote low-income-family high-opportunity moves, for families who have disabilities or special needs. The implications of these results point to scaling up housing-mobility programs, to provide tailored support for low-income families to use HCVs to make high-opportunity moves, which is particularly necessary for families with health challenges.

Identifying groups of children's social mobility opportunity for public health applications using k-means clustering

BackgroundThe Opportunity Atlas project is a pioneering effort to trace social mobility and adulthood socioeconomic outcomes back to childhood residence. Half of the variation in adulthood socioeconomic outcomes was explainable by neighborhood-level socioeconomic characteristics during childhood. Clustering census tracts by Opportunity Atlas characteristics would allow for further exploration of variance in social mobility. Our objectives here are to identify and describe spatial clustering trends within Opportunity Atlas outcomes. MethodsWe utilized a k-means clustering machine learning approach with four outcome variables (individual income, incarceration rate, employment, and percent of residents living in a neighborhood with low levels of poverty) each given at five parental income levels (1st, 25th, 50th, 75th, and 100th percentiles of the national distribution) to create clusters of census tracts across the contiguous United States (US) and within each Environmental Protection Agency region. ResultsAt the national level, the algorithm identified seven distinct clusters; the highest opportunity clusters occurred in the Northern Midwest and Northeast, and the lowest opportunity clusters occurred in rural areas of the Southwest and Southeast. For regional analyses, we identified between five to nine clusters within each region. PCA loadings fluctuate across parental income levels; income and low poverty neighborhood residence explain a substantial amount of variance across all variables, but there are differences in contributions across parental income levels for many components. ConclusionsUsing data from the Opportunity Atlas, we have taken four social mobility opportunity outcome variables each stratified at five parental income levels and created nationwide and EPA region-specific clusters that group together census tracts with similar opportunity profiles. The development of clusters that can serve as a combined index of social mobility opportunity is an important contribution of this work, and this in turn can be employed in future investigations of factors associated with children's social mobility.

0233 Racial/ethnic Residential Segregation - a Component of Structural Racism - and Sleep Health by Neighborhood-level Poverty

Abstract Introduction Racial/ethnic residential segregation may contribute to sleep disparities by concentrating poverty and impairing sleep among minoritized groups. Yet, due to racism, equitable access to sleep-promoting resources may not occur in integrated neighborhoods. Further, social/cultural factors within ethnic enclaves could be protective. Methods To investigate whether relationships between racial/ethnic residential segregation and sleep vary by census tract-level poverty among US adults, we linked nationally-representative National Health Interview Survey data (2011-2017) to 2012 and 2017 American Community Survey census tract-level data. We used the local Getis-Ord Gi* statistic to categorize residential segregation (high, medium, low [reference]), considering differences between racial/ethnic composition within a census tract to the surrounding county. Survey-weighted, Poisson regressions with robust variance estimation were stratified by race/ethnicity and approximate census tract-level poverty tertile (high [>16.9% of residents below poverty level], medium [>7.9%-16.9%], low [0%-7.9%]) to estimate prevalence ratios (PRs) and 95% confidence intervals (CIs) for self-reported sleep health measures. Results Among 126,539 participants (mean age±SE=46±0.1 years), non-Hispanic (NH)-Black and Latino adults were most likely to report short sleep (41%) and non-restorative sleep (37%), respectively. Racial/ethnic residential segregation was most common among NH-Black (38%), followed by non-Mexican Latino (34%) and NH-Asian adults (34%), and was least prevalent among NH-White adults (17%) but was not associated with sleep among Mexican, non-Mexican Latino, or NH-Black adults. Among NH-Asian adults, high segregation was marginally associated with a higher prevalence of short sleep (< 7-hours vs. recommended [7-9 hours]) in low-poverty neighborhoods (PR=1.17 [95% CI:0.97-1.42]) but was associated with recommended sleep in medium-poverty neighborhoods (PRshort sleep=0.79 [0.63-0.99]). Among NH-White adults, high residential segregation was associated with more restorative sleep only in high-poverty (PR=1.13 [1.06-1.20]) and low-poverty (PR=1.03 [1.00-1.07]) neighborhoods. Conclusion Associations between racial/ethnic residential segregation and sleep health varied by neighborhood-level poverty among NH-Asian and NH-White adults. The lack of differences among most minoritized groups may be related to the close proximity of higher-income and lower-income neighborhoods due to structural racism. Future studies including spatial analyses are warranted. The findings/conclusions in this research are those of the authors and do not necessarily represent the views of the Research Data Center, National Center for Health Statistics, or CDC. Support (if any)

The Prevalence, Profitability, and Risks of Milking Among Low-End Small Rental Properties

Low-cost but unsubsidized one- to four-unit rental properties provide a critical source of housing for millions of low- and moderate-income renters. These properties are disproportionately in high-poverty neighborhoods and, until recently, studies of these low-end small rental properties (SRPs) primarily focused on their financial viability. Scholars found that, in general, these properties were marginally profitable at best and carried serious financial risks. Recently, however, studies have found that low-end SRPs may be as profitable as or even more profitable than properties in lower-poverty neighborhoods, and have suggested that these profits are driven by exploitative management. I surveyed the owners and managers of SRPs to understand whether low-end properties were more likely to be profitable and whether the owners who did achieve profits at the low end used “milking” strategies. I found that SRPs in high-poverty neighborhoods are about as likely to be profitable as the rest of the market, but are also financially riskier. I found no compelling evidence of a link between profit and more exploitative management practices at the low end of the market. These findings call for a change in policymakers’ understanding of profit and exploitative management among low-end SRPs.

Association of a Housing Mobility Program With Childhood Asthma Symptoms and Exacerbations

Structural racism has been implicated in the disproportionally high asthma morbidity experienced by children living in disadvantaged, urban neighborhoods. Current approaches designed to reduce asthma triggers have modest impact. To examine whether participation in a housing mobility program that provided housing vouchers and assistance moving to low-poverty neighborhoods was associated with reduced asthma morbidity among children and to explore potential mediating factors. Cohort study of 123 children aged 5 to 17 years with persistent asthma whose families participated in the Baltimore Regional Housing Partnership housing mobility program from 2016 to 2020. Children were matched to 115 children enrolled in the Urban Environment and Childhood Asthma (URECA) birth cohort using propensity scores. Moving to a low-poverty neighborhood. Caregiver-reported asthma exacerbations and symptoms. Among 123 children enrolled in the program, median age was 8.4 years, 58 (47.2%) were female, and 120 (97.6%) were Black. Prior to moving, 89 of 110 children (81%) lived in a high-poverty census tract (>20% of families below the poverty line); after moving, only 1 of 106 children with after-move data (0.9%) lived in a high-poverty tract. Among this cohort, 15.1% (SD, 35.8) had at least 1 exacerbation per 3-month period prior to moving vs 8.5% (SD, 28.0) after moving, an adjusted difference of -6.8 percentage points (95% CI, -11.9% to -1.7%; P = .009). Maximum symptom days in the past 2 weeks were 5.1 (SD, 5.0) before moving and 2.7 (SD, 3.8) after moving, an adjusted difference of -2.37 days (95% CI, -3.14 to -1.59; P < .001). Results remained significant in propensity score-matched analyses with URECA data. Measures of stress, including social cohesion, neighborhood safety, and urban stress, all improved with moving and were estimated to mediate between 29% and 35% of the association between moving and asthma exacerbations. Children with asthma whose families participated in a program that helped them move into low-poverty neighborhoods experienced significant improvements in asthma symptom days and exacerbations. This study adds to the limited evidence suggesting that programs to counter housing discrimination can reduce childhood asthma morbidity.

A Missed Opportunity? The 4% Low-Income Housing Tax Credit Program

The Low-Income Housing Tax Credit program is the largest housing production subsidy in the U.S. Two types of credit, known as the 9% credit and the 4% credit, are subject to different allocation criteria. The 4% program has been flying under the radar of policymakers, housing advocates, and researchers since its inception. Whereas newly constructed 9% units are increasingly sited in lower poverty neighborhoods, 4% investment is made in high-poverty and low-opportunity neighborhoods. This paper reveals that states have not actively influenced the locational outcomes of 4% projects credit until recently. Policy levers have a more substantial impact on the outcomes of the 9% program. However, the results indicate that increased competition and strong policy levers have enabled some states to influence the siting outcomes of 4% projects. As states have significant power over tax credit allocations and additional financing required to enable the 4% credit, they could consider explicitly using this credit to further fair housing goals and help low-income households reach opportunities. However, careful consideration is needed to balance these goals with neighborhood revitalization.

Abstract P359: Long-Term Exposure to Neighborhood Poverty Throughout Midlife and Subclinical Cardiovascular Disease Burden in Subsequent Years: The Study of Women's Health Across the Nation

Purpose: To examine whether longitudinal exposure to neighborhood poverty throughout midlife influences the degree of subclinical CVD (SCVD) burden experienced in early old age in a racially and ethnically-diverse cohort of women transitioning through menopause. Methods: We used longitudinal data on 1,212 women (aged 42-52 at baseline) from The Study of Women’s Health Across the Nation . Residential address histories were collected annually for eleven years across midlife (1996-2007). The following carotid ultrasound SCVD measures were collected during a subsequent follow-up visit (2009-2013): intima media thickness (CIMT), inter-adventitial diameter (IAD), and plaque presence. Values &gt;75th percentile of each were considered high (CIMT &gt; 0.79 mm; IAD &gt; 7.21 mm; plaque index &gt;=2) and were summed together to create our composite SCVD index (range: 0-3). We used longitudinal latent class analysis to identify distinct patterns of exposure to high neighborhood poverty among women across midlife, and used ordinal logistic regression models to determine if a woman’s neighborhood poverty class throughout midlife was associated with her future SCVD burden. Results: We identified five longitudinal neighborhood poverty classes across midlife: consistent low (72% of total), decreasing (6.4%), early-increasing (7.3%), late-increasing (5.5%), and consistent high (8.4%). In age and site-adjusted models, the odds of having greater SCVD burden were 70% higher among women living in consistently high poverty neighborhoods (OR=1.70, 95% CI: 1.14-2.54), 52% higher among women experiencing early increases in neighborhood poverty (OR=1.52, 95% CI: 0.97-2.38), and 69% higher among women experiencing late increases in neighborhood poverty (OR=1.69, 95% CI: 1.04-2.74), compared to women living in consistent low poverty throughout midlife. Controlling for social, behavioral, and menopause-associated factors reduced the magnitude and significance of the estimated effects towards the null. Adjusting for baseline age, race/ethnicity, site, education, marital status, employment, alcohol use, smoking, depressive symptoms, physical activity, menopausal status, hypertension, diabetes, and obesity, the estimated odds of greater SCVD burden were 6% higher among women living in consistently high poverty neighborhoods (95% CI: 0.69-1.63), 10% higher among women experiencing early increases in poverty (95% CI: 0.68-1.76), and 17% higher among women experiencing late increases in poverty (95% CI: 0.70-1.94), relative to women living in consistent low poverty neighborhoods across midlife. Conclusions: Women living in neighborhoods with higher levels of poverty throughout midlife had greater SCVD burden in early old age. Associations between neighborhood poverty trajectories and SCVD burden were largely accounted for by individual-level social, behavioral, and biomedical confounders.

Housing mobility protects against alcohol use for children with socioemotional health vulnerabilities: An experimental design.

Neighborhood context may influence alcohol use, but effects may be heterogeneous, and prior evidence is threatened by confounding. We leveraged a housing voucher experiment to test whether housing vouchers' effects on alcohol use differed for families of children with and without socioemotional health or socioeconomic vulnerabilities. In the Moving to Opportunity (MTO) study, low-income families in public housing in five US cities were randomized in 1994 to 1998 to receive one of three treatments: (1) a housing voucher redeemable in a low-poverty neighborhood plus housing counseling, (2) a housing voucher without locational restriction, or (3) no voucher (control). Alcohol use was assessed 10 to 15 years later (2008 to 2010) in youth ages 13 to 20, N=4600, and their mothers, N=3200. Using intention-to-treat covariate-adjusted regression models, we interacted MTO treatment with baseline socioemotional health vulnerabilities, testing modifiers of treatment on alcohol use. We found treatment effect modification by socioemotional factors. For youth, MTO voucher treatment, compared with controls, reduced the odds of ever drinking alcohol if youth had behavior problems (OR=0.26, 95% CI [0.09, 0.72]) or problems at school (OR=0.46, [0.26, 0.82]). MTO low-poverty treatment (vs. controls) also reduced the number of drinks if their health required special medicine/equipment (OR=0.50 [0.32, 0.80]). Yet treatment effects were nonsignificant among youth without socioemotional vulnerabilities. Among mothers of children with learning problems, MTO voucher treatment (vs. controls) reduced past-month drinking (OR=0.69 [0.47, 0.99]), but was harmful otherwise (OR=1.22 [0.99, 1.45]). For low-income adolescents with special needs/socioemotional problems, housing vouchers protect against alcohol use.

Racial, Ethnic, and Socioeconomic Disparities in Treatment Delay Among Patients With Hepatocellular Carcinoma in the United States

Failures have been reported across the cancer care continuum in patients with hepatocellular carcinoma (HCC); however, the impact of treatment delays on outcomes has not been well-characterized. We described the prevalence of treatment delays in a racially and ethnically diverse cohort of patients and its association with overall survival. Using the Surveillance, Epidemiology, and End Results-Medicare database, we identified patients diagnosed with HCC between 2001 and 2015. We performed multivariable logistic regression analysis to identify factors associated with treatment delay (ie, receipt of HCC-directed therapy >3 months after diagnosis). Cox proportional hazards regression analysis with a 5-month landmark was used to characterize the association between treatment delay and overall survival, accounting for immortal time bias. Of 8450 patients with treatment within 12 months of HCC diagnosis, 1205 (14.3%) experienced treatment delays. The proportion with treatment delays ranged from 6.8% of patients undergoing surgical resection to 21.6% of those undergoing liver transplantation. In multivariable analysis, Black patients (odds ratio, 1.96; 95% confidence interval [CI], 1.21-3.15) and those living in high poverty neighborhoods (odds ratio, 1.55; 95% CI, 1.25-1.92) were more likely to experience treatment delays than white patients and those living in low poverty neighborhoods, respectively. Treatment delay was independently associated with worse survival (hazard ratio 1.15, 95% CI, 1.05-1.25). Nearly 1 in 7 patients with HCC experience treatment delays, with higher odds in Black patients and those living in high poverty neighborhoods. Treatment delays are associated with worse survival, highlighting a need for interventions to improve time-to-treatment.

Examining the interactive association of family- and neighborhood-level socio-economic characteristics on children's sleep beyond the associations of residency and neighborhood violence

ObjectiveTo examine the interactive association of neighborhood and family socio-economic characteristics (SEC) on children's sleep. DesignSecondary data analyses were completed on the 2014 Ontario Child Health Study, a cross-sectional sample of 10,802 children aged 4-17. ParticipantsChildren (aged 4-11, 50% male; N = 6264) with available sleep outcome data. MethodsMultilevel modeling was used to assess the interactive relationship between family- and neighborhood-level poverty in relation to child sleep outcomes (problems falling asleep, problems staying asleep, weekday and weekend time in bed), above the associations of variables known to be related to sleep at the child (ie, child age, sex, internalizing problems, externalizing problems, chronic illness), family (ie, negative parenting behaviors, family structure, parent mental health, years lived in neighborhood, parent education level), and neighborhood levels (ie, neighborhood size, antisocial behavior). ResultsNeighborhood poverty (p < .01, ß = -0.001, 95% confidence interval [-0.007, -0.002]) was significantly related to shorter weekday time in bed and the interactive association of family and neighborhood poverty was significantly related to weekend time in bed (p < .05, ß = 0.012, 95% confidence interval [0.004, 0.021]). Children living in low poverty neighborhoods with families of higher SEC backgrounds, and children living in high poverty neighborhoods with families of lower SEC backgrounds had the shortest weekend time in bed (9.7 hours). ConclusionsThere is a compound relationship of family and neighborhood poverty on children's sleep above and beyond family- and child-level risk factors.

Early intervention and special education in New York City: Patterns of service use and disparities affecting children of colour.

Compliance with the requirements of the Individuals with Disabilities Education Act (IDEA) in the United States is monitored through review of cross-sectional reports from three discrete, age-defined programmes (early intervention [EI], early childhood special education [ECSE)] and school-age special education [SE]) to promote the timely, efficient and effective delivery of appropriate services to all eligible children. Analysis of longitudinal data is required to discern how children use services across programmes to provide the necessary context for IDEA oversight and to identify areas for programme or policy interventions to reduce barriers to service use and promote equity. We applied sequence analysis to a data linkage across five public record systems among 15 626 New York City children born in 1998 who had records from birth through third grade. Five predominant patterns of service use were identified: (1) multiple therapies across EI/ECSE/SE (13%), (2) EI without transition to Department of Education schools or services (24%), (3) EI and intermittent ECSE/SE (16%), (4) older entry into EI and both speech and occupational therapy throughout ECSE/SE (9%) and (5) limited EI use and mostly speech therapy in ECSE/SE (38%). Each pattern had distinct demographics (e.g., pattern 2 was disproportionately White and from low poverty neighbourhoods; pattern 4 was disproportionately male and Black; pattern 5 was disproportionately Latino) and academic outcomes (e.g., pattern 1 had largest proportion in a SE school and not tested in third grade; pattern 3 had third grade tests scores that were similar to overall citywide mean scores). The differences in demographic profiles across the five patterns of service use illustrate the systemic inequities in the delivery of these important services. Delayed entry and limited use of EI services among children of colour underscore the need for equity goals to increase early referral and optimize service use.

The Effects of Rental Assistance Programs on Neighborhood Outcomes for U.S. Children: Nationwide Evidence by Program and Race/Ethnicity

Project-based housing programs and tenant-based housing programs (vouchers) may have differential effects on neighborhood outcomes for residents. Theoretically, vouchers should enhance access to low-poverty neighborhoods for low-income families thereby promoting economic mobility for children, though vouchers’ success may vary by race and ethnicity. Drawing on a national survey-administrative data linkage and a quasi-experimental approach, we examine the impact of project-based housing and vouchers on an index of socioeconomic neighborhood disadvantage among children. We find that living in project-based housing leads to greater exposure to neighborhood disadvantage while receiving vouchers leads to reduced exposure. Reductions in neighborhood disadvantage for children receiving vouchers are found only for non-Hispanic Black and Hispanic/Latino children. For non-White families, vouchers are associated with a reduced likelihood of living in high-poverty neighborhoods and increased likelihood of living in low-poverty neighborhoods, presenting an opportunity to narrow racial and ethnic differences in children's neighborhood attainment.

Neighborhood disadvantage and prescription drug misuse in low-income urban mothers

BackgroundPrescription drug misuse remains a persistent problem in the United States. Residents living in disadvantaged neighborhoods are at greater risk of substance abuse such as alcohol, tobacco, or drugs. However, whether neighborhood disadvantage affects prescription drug misuse remains underexplored. MethodsThis study uses data on 3444 mothers from the Fragile Families and Child Wellbeing Study to examine the role of neighborhood disadvantage in prescription drug misuse. In addition, we examine whether social support and neighborhood collective efficacy (social cohesion and social control) explain this relationship. The analysis uses multivariate logistic regression and delineated between the following neighborhoods: affluent (3% poverty), low poverty (3–10%), moderate poverty (10–20%), and high poverty neighborhoods (20% or more). ResultsMothers living in moderately poor neighborhoods were more than twice as likely (odds = 2.17, 95% CI: 1.43–3.27) to misuse prescription drugs than mothers living in neighborhoods with high poverty. Mothers living in neighborhoods with high poverty did not have a statistically significant difference in prescription drug misuse than those living in affluent or low poverty neighborhoods. Social support and neighborhood collective efficacy did not explain these associations. The association between moderate poverty and prescription drug misuse was mostly direct and there was no indirect association. ConclusionThe study highlights the higher risk of prescription drug misuse among mothers living in neighborhoods with moderate poverty. Interventions aimed at reducing opioid misuse should focus on demographic groups that are more vulnerable such as low-income mothers living in disadvantaged neighborhoods.

You Can’t Get There from Here: Mobility Networks and the Housing Choice Voucher Program

The Housing Choice Voucher (HCV) program represents the largest subsidized housing program in the United States. While families with vouchers can, in theory, lease any housing of reasonable quality renting below a rent ceiling, the empirical evidence suggests that they rarely use their vouchers to move to lower poverty neighborhoods. This paper examines the question of how spatial boundaries impact the residential possibilities of HCV subsidized families, both the visible boundaries of Public Housing Authority (PHA) catchment areas and the invisible boundaries of racial and economic segregation. I use administrative data supplied by the Department of Housing and Urban Development, which includes all moves by HCV families between 2005 and 2015 in the Baltimore, MD, Cleveland, OH, and Dallas, TX, metropolitan areas. Using a Louvain method of network cluster detection, I subdivide each metro into distinct mobility clusters—sets of census tracts within which voucher holders move but between which they rarely do. I find that the empirical mobility clusters at the metropolitan level are highly defined by PHA’s catchment areas. Even though families are technically allowed to “port” their voucher from one PHA catchment area to another, such behavior is rare. Within the PHA catchment areas, HCV mobility clusters are defined by patterns of race, income, and history. These findings suggest that patterns of racial and economic segregation seem to partially define the mobility clusters within PHA catchment areas, but not across them.

Race, Adolescent Exposure to Segregation, and Adulthood Residential Mobility into and out of Lower-Poverty Neighborhoods

Race, Adolescent Exposure to Segregation, and Adulthood Residential Mobility into and out of Lower-Poverty Neighborhoods

Neighborhood Poverty and Incident Heart Failure: an Analysis of Electronic Health Records from 2005 to 2018.

Neighborhood-level characteristics, such as poverty, have been associated with risk factors for heart failure (HF), including hypertension and diabetes mellitus. However, the independent association between neighborhood poverty and incident HF remains understudied. To evaluate the association between neighborhood poverty and incident HF using a "real-world" clinical cohort. Retrospective cohort study of electronic health records from a large healthcare network. Individuals' residential addresses were geocoded at the census-tract level and categorized by poverty tertiles based on American Community Survey data (2007-2011). Patients from Northwestern Medicine who were 30-80 years, free of cardiovascular disease at index visit (January 1, 2005-December 1, 2013), and followed for at least 5 years. The association of neighborhood-level poverty tertile (low, intermediate, and high) and incident HF was analyzed using generalized linear mixed effect models adjusting for demographics (age, sex, race/ethnicity) and HF risk factors (body mass index, diabetes mellitus, hypertension, smoking status). Of 28,858 patients included, 75% were non-Hispanic (NH) White, 43% were men, 15% lived in a high-poverty neighborhood, and 522 (1.8%) were diagnosed with incident HF. High-poverty neighborhoods were associated with a 1.80 (1.35, 2.39) times higher risk of incident HF compared with low-poverty neighborhoods after adjustment for demographics and HF risk factors. In a large healthcare network, incident HF was associated with neighborhood poverty independent of demographic and clinical risk factors. Neighborhood-level interventions may be needed to complement individual-level strategies to prevent and curb the growing burden of HF.

Not the Great Equalizer: Which Neighborhoods are Most Economically Vulnerable to the Coronavirus Crisis?

This report and its accompanying interactive map show the vulnerability of every U.S. neighborhood to the economic impact of the COVID-19 crisis. Using data from the American Community Survey, they show that:• High-Poverty Communities Are the Most Economically Vulnerable. About 78 percent of high-poverty neighborhoods but only 15 percent of low-poverty neighborhoods are highly vulnerable to the economic effects of the crisis.• Economic Vulnerability Is Concentrated in Communities of Color. Of the tenth of neighborhoodsthat are most vulnerable to the crisis’ economic fallout, 87 percent are communities of color.• Even Among High-Poverty Communities, Communities of Color Are the Most Vulnerable. Ninetypercent of high-poverty neighborhoods whose residents are primarily people of color are highly vulnerable, compared to only 56 percent of high-poverty tracts that are at least 50 percent white.To prevent highly vulnerable neighborhoods from falling further behind the rest of the nation, state and local policymakers and assistance providers should target economic assistance to those neighborhoods, redirect existing funding to those neighborhoods as permitted by law, and ensure that residents of highly vulnerable neighborhoods know how to access the federal, state, and local government aid that is available to them. In the long term, policies that improve access to the internet, mobility, affordable housing, and affordable health coverage in those communities are needed to make highly vulnerable neighborhoods less vulnerable.

Change in the Spatial Clustering of Poor Neighborhoods within U.S. Counties and Its Impact on Homicide: An Analysis of Metropolitan Counties, 1980-2010

ABSTRACT Recent scholarship has examined changes in the geographic distribution of poor persons in America, but it remains unclear whether high- and low- poverty neighborhoods have become more, or less, spatially clustered over the past several decades. Additionally, while many have argued that growth in both high-poverty spatial clusters and high-low poverty spatial clusters could yield conditions that are conducive to increases in homicide, previous research has not considered that possibility. We contribute to knowledge by examining whether there have been important shifts in the spatial clustering of poverty in America between 1980 and 2010, and if so, whether those shifts were related to changes in homicide during the period. The descriptive results of our study reveal that there were notable changes in population exposure to both high- poverty and high-low poverty spatial clusters between 1980 and 2010. Fixed-effects negative binomial regression models yield limited support for the idea that changes in spatial inequality, as measured by the clustering of high- and low-poverty neighborhoods, are associated with changes in homicide rates. In contrast, the results indicate a significant positive association between changes in exposure to very high-poverty spatial clusters and homicide trends. The findings affirm the importance of considering the spatial dynamics of demographic conditions when explaining changes in violence across communities.