We examined whether a housing voucher intervention influenced adolescent risky sexual behavior (RSB) across 15 years in the Moving to Opportunity Study. Low-income families in public housing that resided in 5 cities were randomized to one of three treatment groups: a housing voucher to move to low-poverty neighborhoods (i.e., < 10% poverty rate), a Sect. 8 voucher but no housing relocation counseling, or a control group that could remain in public housing. Youth and their caregivers completed baseline surveys, as well as two uniform follow-ups: interim (2001–2002; 4–7 years after baseline) and final (2008–2010; 10–15 years after baseline). Approximately 4,600 adolescents (50.5% female) aged 13–20 years participated at the final timepoint. Adolescents reported on their RSB, including condom use, other contraceptive use, early sexual initiation (< 15 years old), and 2+ sexual partners in the past year. We modeled each indicator separately and as part of a composite index. We tested baseline health vulnerabilities as potential effect modifiers. The low-poverty voucher group and the Sect. 8 voucher group were combined due to homogeneity of their effects. Applying intent-to-treat (ITT) regression analyses, we found no significant main effects of voucher receipt (vs. control) on any RSB. However, we found protective effects of voucher receipt on RSB among youth with health problems that limited activity, and youth < 7 at baseline but adverse effects among females, youth > 7 at baseline, and youth who were suspended/expelled from school. Results highlight the importance of understanding how housing interventions differentially influence adolescent health and behaviors.

A large body of research has established that neighborhood poverty is associated with a range of poor outcomes including poor health, and racial health disparities (Arcaya et al., 2016; Duncan & Ka...

Since immigrants and their descendants represent a growing proportion of the US population, there is a strong demographic imperative for scientists to better understand the cancer risk factors at multiple levels that exist for these populations. Understanding the upstream causes of cancer, including neighborhood context, may help prevention efforts. Residence in ethnic enclaves may be one such contextual cause; however, the evidence is mixed, and past research has not utilized prospective designs examining cancer incidence or mortality. We examined the association between residency in ethnic enclaves and cancer events among Hispanic (n = 753) and Chinese (n = 451) participants without a history of cancer in the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective cohort study that enrolled participants ages 45–84 in six US cities. Cancer events included deaths and hospitalization for any cancer diagnosis from 2000–2012. Residency in an ethnic enclave was operationalized as their geocoded baseline census tract having a concentration of residents of the same ethnicity greater than the 75th percentile (compared to non-ethnic enclave otherwise). Potential confounders were blocked into three categories: sociodemographic, acculturation, and biomedical/health behavior variables. To examine the association between ethnic enclaves and cancer, we estimated hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox proportional hazards models. Among Hispanic participants, residing in ethnic enclaves (vs. not) was associated with a 39% reduction in cancer risk (HR 0.61, 95%CI: 0.31, 1.21) after adjusting for sociodemographic variables. Among Chinese participants, residing in ethnic enclaves was associated with a 2.8-fold increase in cancer risk (HR 2.86, 95%CI; 1.38, 5.94) after adjusting for sociodemographic variables. Our results suggest that the association between ethnic enclaves and cancer events differs by ethnic group, suggesting that different social and contextual factors may operate in different communities.

The objective of this study was to examine sexual orientation-based disparities in six self-reported health outcomes among millennial aged military veterans. We collected data using The Millennial ...

Purpose: 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. Trial design: 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. Methods: Using intention-to-treat covariate-adjusted regression models, we interacted MTO treatment with baseline socioemotional health vulnerabilities, testing modifiers of treatment on alcohol use. Results: 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]). Conclusions: For low-income adolescents with special needs/socioemotional problems, housing vouchers protect against alcohol use.

Tenant-based rental assistance has received much attention as a tool to ameliorate American poverty and income segregation. We examined whether a tenant-based voucher program improves long-term exp...

<p>Racism is embedded in society, and higher education is an important structure for patterning economic and health outcomes. Historically Black Colleges and Universities (HBCUs) were founded on anti-racism while predominantly white institutions (PWIs) were often founded on white supremacy. This contrast provides an opportunity to study the association between structural racism and health among Black Americans. We used the National Longitudinal Study of Adolescent to Adult Health (Add Health) to estimate the long-term causal effect of attending an HBCU (vs. PWI) on depressive symptoms among Black students in the United States from 1994-2018. While we found no overall association with attending an HBCU (vs. PWI) on depressive symptoms, we found that this association varied by baseline mental health and region, and across time. For example, among those who attended high school outside of the South, HBCU attendance was protective against depressive symptoms 7 years later, and the association was strongest for those with higher baseline depressive symptoms. We recommend equitable state and federal funding for HBCUs, and that PWIs implement and evaluate antiracist policies to improve mental health of Black students.</p>

Objective: To estimate associations of residential mobility with body mass index (BMI), physical activity, and diet and whether associations differ across demographics. Design: Longitudinal cohort with 4 waves of survey follow-up over 15 years. Participants and Setting: A total of 2,110 adolescents and young adults originally from the Twin Cities of Minnesota responded to at least 2 waves of follow-up, beginning at ages 15 to 23 years. Main Outcome Measure(s): Self-reported BMI, physical activity, fast food consumption, breakfast frequency, sugary drink consumption, fruit and vegetable consumption, and screen time. Analysis: Each outcome was modeled as a continuous variable using hierarchical linear regression. Residential mobility—change in residential address—was the main effect of interest. Models adjusted for demographics, marriage during follow-up, and previous level of the outcome. Inverse propensity weights accounted for loss to follow up. Results: No weight-related outcomes differed between movers and nonmovers in the whole sample. When examining effect modification by age, as participants aged, moving was increasingly associated with improvements in weight-related outcomes, particularly BMI. Conclusions and Implications: Results suggest that moving may be associated with poorer weight-related outcomes during a brief window from late teens and early-20s and less associated with weight-related outcomes in the mid-20s and 30s.

Background: Housing mobility impacts adolescent alcohol use, and the neighborhood built environment may impact this relationship. Methods: Moving to Opportunity (MTO) was a multi-site, three-arm, household-level experiment. MTO randomly assigned one of three treatment arms (1994–1997) allowing families living in public housing to (1) receive a voucher to be redeemed any neighborhood (2) receive a voucher to be redeemed in a neighborhood with less than 10% poverty (3) remain in public housing (control). MTO decreased girls’ alcohol use, but increased boys’ alcohol use. Treatment groups were pooled because they are similar conceptually and statistically on our primary outcome. Among youth aged 12–19 in 2001–2002 (N = 2829), we estimated controlled direct effects mediation of MTO treatment effects on youth with housing vouchers (N = 1950) vs. controls (N = 879) on past 30-day number of drinks per day on days drank, using gender-stratified Poisson regression. Mediators were density of on- and off-premises alcohol outlets per square mile at the families’ census tract of residence in 1997. Results: Treatment group youth were randomized to live in 1997 census tracts with lower off-premises, but higher on-premises, outlet density. MTO treatment (vs. controls) decreased drinking for girls via alcohol outlet density, but only at higher levels of outlet density. Treatment was 18% more beneficial when girls moved to high density neighborhoods, compared to controls who stayed living in public housing in high density neighborhoods. Conclusion: Additional social processes unmeasured in the current study may play an important role in the alcohol use and other health risks for girls.

In the 1930’s, the Home Owner Loan Corporation (HOLC) drafted maps to quantify variation in real estate credit risk across US city neighborhoods. The letter grades and associated risk ratings assigned to neighborhoods discriminated against those with black, lower class, or immigrant residents and benefitted affluent white neighborhoods. An emerging literature has begun linking current individual and community health effects to government redlining, but each study faces the same measurement problem: HOLC graded area boundaries and neighborhood boundaries in present-day health datasets do not match. Previous studies have taken different approaches to classify present day neighborhoods (census tracts) in terms of historical HOLC grades. This study reviews these approaches, examines empirically how different classifications fare in terms of predictive validity, and derives a predictively optimal present-day neighborhood redlining classification for neighborhood and health research.

<p>Substantial evidence suggests that economic hardship causes violence. However, a large majority of this research relies on observational studies that use traditional violence surveillance systems that suffer from selection bias and over-represent vulnerable populations, such as people of color. To overcome limitations of prior work, we employed a quasi-experimental design to assess the impact of the Great Recession on explicit violence diagnoses (injuries identified to be caused by a violent event) and proxy violence diagnoses (injuries highly correlated with violence) for child maltreatment, intimate partner violence (IPV), elder abuse, and their combination. We used Minnesota hospital data from 2004 to 2014, conducting a difference-in-differences analysis at the county level (N=86) using linear regression to compare changes in violence rates from pre-recession (2004-2007) to post-recession (2008-2014) in counties most affected by the recession, versus changes over the same time period in counties less affected by the recession. The findings suggested that the Great Recession had little or no impact on explicit-identified violence, however it affected proxy-identified violence. Counties that were more highly affected by the Great Recession saw a greater increase in the average rate of proxy-identified child abuse, elder abuse, IPV, and combined violence when compared to less affected counties.</p>

<h3>Rational & Objective</h3><p>Neighborhood socioeconomic status (SES) and health insurance status may be important upstream social determinants of chronic kidney disease (CKD), but their relationship remains unclear. The aim of this study was to determine whether neighborhood SES and individual-level health insurance status were independently associated with CKD prevalence.</p><h3>Study Design</h3><p>Observational study using electronic health records (EHRs).</p><h3>Setting & Participants</h3><p>EHRs of patients (n=185,269) seen at a health care system in the 7-county Minneapolis/St Paul area (2017-2018).</p><h3>Exposures</h3><p>Census tract neighborhood SES measures (median value of owner-occupied housing units [wealth], percentage of residents aged>25 years with bachelor's degree or higher [education]) and individual-level health insurance status (aged<65 years: Medicaid vs other insurance; ≥65 years: Medicare vs Medicare and supplemental insurance plan) were obtained from the American Community Survey and EHR data. Neighborhood SES was operationalized into quartiles, comparing low (first quartile) versus high (fourth quartile) neighborhood SES.</p><h3>Outcomes</h3><p>CKD prevalence: estimated glomerular filtration rate<60mL/min/1.73m² or proteinuria.</p><h3>Analytic Approach</h3><p>Multilevel Poisson regression with robust error variance with a random intercept at the census-tract level, adjusted for demographic and clinical covariates, was used to estimate the association between neighborhood SES, insurance, and CKD.</p><h3>Results</h3><p>Neighborhood SES and insurance were independently associated with CKD prevalence. In covariate-adjusted models, patients living in low versus high neighborhood SES had a higher CKD prevalence among both younger and older patients. For example, the prevalence ratios of CKD in low versus high neighborhood SES as defined by education among patients younger than 65 and 65 years and older were 1.11 (95% CI, 1.05-1.18) and 1.08 (95% CI, 1.04-1.12), respectively. Patients younger than 65 years receiving Medicaid had higher CKD prevalence versus those with other insurance (1.51 [95% CI, 1.43-1.6]). For patients 65 years and older, insurance was not associated with prevalence of CKD in the fully adjusted model.</p><h3>Limitations</h3><p>One health care system and selection bias.</p><h3>Conclusions</h3><p>Living in low neighborhood SES as defined by wealth and education and having Medicaid for patients younger than 65 years were associated with higher CKD prevalence.</p>

Background Intimate partner violence (IPV) is high among married women in Bangladesh. Social isolation is a well-established correlate of women’s exposure to IPV, but the role of such factors in low-income and middle-income countries is not well understood. In this study, we explore whether social connection is protective against IPV among married women in rural Bangladesh. Methods Data were drawn from a multistage, stratified, population-based longitudinal sample of 3355 married women in rural Bangladesh, who were surveyed on individual and contextual risk factors of IPV. Negative binomial regression models were used to estimate the association between three different domains of social connection (natal family contact, female companionship and instrumental social support), measured at baseline in 2013, and the risk of three different forms of IPV (psychological, physical and sexual), approximately 10 months later, adjusted for woman’s level of education, spouse’s level of education, level of household wealth, age and age of marriage. Results Adjusted models showed that instrumental social support was associated with a lower risk of past year psychological IPV (risk ratio (RR)=0.84, 95% CI 0.769 to 0.914), sexual IPV (RR=0.90, 95% CI 0.822 to 0.997) and physical IPV (RR=0.81, 95% CI 0.718 to 0.937). Natal family contact was also associated with a lower risk of each type of IPV, but not in a graded fashion. Less consistent associations were observed with female companionship. Conclusion Our findings suggest that social connection, particularly in the form of instrumental support, may protect married women in rural Bangladesh from experiencing IPV. Data are available upon reasonable request. An individual who wishes to use the data must send a written request to the Principal Investigator stating the name and affiliation of the applicant, the purpose of the analysis, how the data will be used and disseminated, and a brief summary of the analyses to be performed. Following approval of the request by the PI, datasets and codebooks will be made available. Identified data will not be shared.

Intimate partner violence (IPV) is highly prevalent globally and associated with adverse mental health outcomes among women. In IPV-endemic contexts like Bangladesh, previous research has found no association between low levels of IPV and depression. Although IPV and attitudes justifying IPV against women are highly prevalent in this context, nothing is known about how related contextual norms affect associations between individual-level IPV exposure and depression. The present study examines if village-level IPV norms, characterized using village-level (Level 2) prevalence of a) IPV-justifying attitudes (injunctive norms) and b) physical IPV (descriptive norms), modifies the individual-level (Level 1) associations between the severity of recent IPV and major depressive episode (MDE) among women in rural Bangladesh. Data were drawn from a nationally-representative sample consisting of 3290 women from 77 villages. Multilevel models tested cross-level interactions between village-level IPV norms and recently experienced individual-level IPV on the association with past 30-day MDE. The prevalence of IPV was 44.4% (range: 9.6–76.2% across villages) and attitudes justifying IPV ranged from 1.6% to 49.8% across villages. The prevalence of MDE was 16.8%. The risk of MDE at low levels of IPV severity (versus none) was greater in villages with the least tolerant attitudes toward IPV compared to villages where IPV was more normative, e.g., interaction RR = 1.42 (95% CI: 0.64, 3.15) for low physical IPV frequency and injunctive norms. The association between IPV and depression may be modified by contextual-level IPV norms, whereby it is exacerbated in low-normative contexts.

Rationale & Objective: Screening for chronic kidney disease (CKD) is recommended for patients with diabetes and hypertension as stated by the respective professional societies. However, CKD, a silent disease usually detected at later stages, is associated with low socioeconomic status (SES). We assessed whether adding census tract SES status to the standard screening approach improves our ability to identify patients with CKD. Study Design: Screening test analysis. Settings & Participants: Electronic health records (EHR) of 256,162 patients seen at a health care system in the 7-county Minneapolis/St. Paul area and linked census tract data. Exposure: The first quartile of census tract SES (median value of owner-occupied housing units <$165,200; average household income <$35,935; percentage of residents >25 years of age with a bachelor's degree or higher <20.4%), hypertension, and diabetes. Outcomes: CKD (eGFR <60 mL/min/1.73 m2, or urinary albumin-creatinine ratio >30 mg/g, or urinary protein-creatinine ratio >150 mg/g, or urinary analysis [albuminuria] >30 mg/d). Analytical Approach: Sensitivity, specificity, and number needed to screen (NNS) to detect CKD if we screened patients who had hypertension and/or diabetes and/or who lived in low-SES tracts (belonging to the first quartile of any of the 3 measures of tract SES) versus the standard approach. Results: CKD was prevalent in 13% of our cohort. Sensitivity, specificity, and NNS of detecting CKD after adding tract SES to the screening approach were 67% (95% CI, 66.2%-67.2%), 61% (95% CI, 61.1%-61.5%), and 5, respectively. With the standard approach, sensitivity of detecting CKD was 60% (95% CI, 59.4%-60.4%), specificity was 73% (95% CI, 72.4%-72.7%), and NNS was 4. Limitations: One health care system and selection bias. Conclusions: Leveraging patients’ addresses from the EHR and adding tract-level SES to the standard screening approach modestly increases the sensitivity of detecting patients with CKD at a cost of decreased specificity. Identifying further factors that improve CKD detection at an early stage are needed to slow the progression of CKD and prevent cardiovascular complications.

Rational & Objective: Electronic health records can be leveraged to assess quality-of-care measures in patients with chronic kidney disease (CKD). Neighborhood socioeconomic status could be a potential barrier to receiving appropriate evidence-based therapy and follow-up. We examined whether neighborhood socioeconomic status is independently associated with quality of care received by patients with CKD. Study Design: Observational study using electronic health record data. Setting & Participants: Retrospective study of patients seen at a health care system in the 7-county Minneapolis/St Paul area. Exposures: Census tract socioeconomic status measures (wealth, income, and education). Outcomes: Indicators of CKD quality of care: (1) prescription for angiotensin-converting enzyme inhibitor/angiotensin receptor blocker in patients with stage ≥ 3 CKD or stage 1 or 2 CKD with urinary albumin-creatinine ratio (UACR) > 300 mg/d, (2) UACR measurement among patients with laboratory-based CKD (estimated glomerular filtration rate < 60 mL/min/1.72 m2), and (3) CKD identified on the problem list or coded for at an encounter among patients with laboratory-based CKD. Analytic Approach: Multilevel Poisson regression with robust error variance with a random intercept at the census tract level. Results: Of the 16,776 patients who should be receiving an angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, 65% were prescribed these medications. Among patients with laboratory-based CKD (n = 25,097), UACR was measured in 27% and CKD was identified in the electronic health record in 55%. We found no independent association between any neighborhood socioeconomic status measures and CKD quality-of-care indicators. Limitations: 1 health care system and selection bias. Conclusions: We found no association of neighborhood socioeconomic status with quality of CKD care in our cohort. However, adherence to CKD guidelines is low, indicating an opportunity to improve care for all patients regardless of neighborhood socioeconomic status.

Purpose: Commonly-used violence surveillance systems are biased towards certain populations due to overreporting or over-scrutinized. Hospital discharge data may offer a more representative view of violence, through use of proxy codes, i.e. diagnosis of injuries correlated with violence. The goals of this paper are to compare the trends in violence in Minnesota, and associations of county-level demographic characteristics with violence rates, measured through explicitly diagnosed violence and proxy codes. It is an exploration of how certain sub-populations are overrepresented in traditional surveillance systems. Methods: Using Minnesota hospital discharge data linked with census data from 2004 to 2014, this study examined the distribution and time trends of explicit, proxy, and combined (proxy and explicit) codes for child abuse, intimate partner violence (IPV), and elder abuse. The associations between county-level risk factors (e.g., poverty) and county violence rates were estimated using negative binomial regression models with generalized estimation equations to account for clustering over time. Results: The main finding was that the patterns of county-level violence differed depending on whether one used explicit or proxy codes. In particular, explicit codes suggested that child abuse and IPV trends were flat or decreased slightly from 2004 to 2014, while proxy codes suggested the opposite. Elder abuse increased during this timeframe for both explicit and proxy codes, but more dramatically when using proxy codes. In regard to the associations between county level characteristics and each violence subtype, previously identified county-level risk factors were more strongly related to explicitly-identified violence than to proxy-identified violence. Given the larger number of proxy-identified cases as compared with explicit-identified violence cases, the trends and associations of combined codes align more closely with proxy codes, especially for elder abuse and IPV. Conclusions: Violence surveillance utilizing hospital discharge data, and particularly proxy codes, may add important information that traditional surveillance misses. Most importantly, explicit and proxy codes indicate different associations with county sociodemographic characteristics. Future research should examine hospital discharge data for violence identification to validate proxy codes that can be utilized to help to identify the hidden burden of violence.