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Background Neighborhood evictions are a key component of community-level housing instability and disproportionately impact communities of color. Increased neighborhood evictions may be associated with increased preterm birth (PTB). Previous research suggests familial distress as a potential driver of increased PTB among Black birthing parents exposed to high neighborhood eviction rates. In this study, we explore whether the association of neighborhood evictions with PTB differs depending on the presence or absence of children in the household during pregnancy. Methods We used information from 400 Black participants in the Newborn Epigenetics Study in Durham, NC. Our primary exposure, neighborhood eviction rate, was defined as the participant’s block group eviction rate during the year of last menstrual period. Preterm birth, defined as gestational age < 37 completed weeks at delivery was based on information abstracted from medical records at delivery. Using logistic regression, we estimated the change in odds of preterm birth associated with a 1 SD increase in neighborhood eviction rate. Models were adjusted for educational attainment, relationship status, participant age at delivery, and proportion of block group households below the federal poverty line. To determine whether associations between neighborhood evictions and preterm birth differ depending on household composition, we stratified the study sample by presence of children in the household during pregnancy (0, ≥  1 children). Results Among the total sample, we observed an increase in odds of preterm birth for every 1-SD increase in neighborhood eviction rate (OR: 1.21, 95% CI: 0.83, 1.73). Association between neighborhood eviction rate and preterm birth differed by household composition. Increased neighborhood eviction rates were associated with increased odds of PTB among participants with children in the household (OR: 1.89, 95% CI: 1.09, 3.28), but not among participants without children in the household (OR: 0.85, 95% CI: 0.49, 1.39). Conclusions We found that higher neighborhood evictions increase odds of preterm birth among Black birthing parents living with children. Our findings support the prioritization of Black families and communities for interventions to prevent evictions and promote housing stability.

Objectives. To investigate the association between vacant lot redevelopment and violent crime and firearm violent crime. Methods. We used a quasi-experimental study with a difference-in-difference (DID) design. The study population was 254 vacant lots located in Philadelphia, Pennsylvania. The exposure was redevelopment, defined as repurposing the vacant lot into a permanent structure (e.g., housing) between 2007 and 2023. The outcome was violent crime subtypes and firearm violent crime subtypes reported to the police. Our primary analysis used a staggered DID estimator. Results. We found a negative association between redevelopment and aggravated assault (DID = −56.55 crimes per square mile per year; 95% confidence interval [CI] = −97.86, −15.24), firearm aggravated assault (DID = −35.11 crimes per square mile per year; 95% CI = −55.41, −14.82), and overall firearm violent crime (DID = −27.26 crimes per square mile per year; 95% CI = −52.97, −1.54). We did not find significant associations for the other outcomes tested. Conclusions. Our results support the hypothesis that vacant lot redevelopment may prevent or displace violent crime. Public Health Implications. Built environment investments may prevent or displace violence. ( Am J Public Health. Published online ahead of print October 23, 2025:e1–e8. https://doi.org/10.2105/AJPH.2025.308269 )

ObjectiveTo examine inequities in tobacco retailer availability by neighbourhood-level socioeconomic, racial/ethnic and same-sex couple composition.Data sourcesWe conducted a 10 November 2022 search of PubMed, PsycINFO, Global Health, LILACS, Embase, ABI/Inform, CINAHL, Business Source Complete, Web of Science and Scopus.Study selectionWe included records from Organisation for Economic Co-operation and Development member countries that tested associations of area-level measures of tobacco retailer availability and neighbourhood-level sociodemographic characteristics. Two coders reviewed the full text of eligible records (n=58), including 41 records and 205 effect sizes for synthesis.Data extractionWe used dual independent screening of titles, abstracts and full texts. One author abstracted and a second author confirmed the study design, location, unit of analysis, sample size, retailer data source, availability measure, statistical approach, sociodemographic characteristic and unadjusted effect sizes.Data synthesisOf the 124 effect sizes related to socioeconomic inequities (60.5% of all effect sizes), 101 (81.5%) indicated evidence of inequities. Of 205 effect sizes, 69 (33.7%) tested associations between retailer availability and neighbourhood composition of racially and ethnically minoritised people, and 57/69 (82.6%) documented inequities. Tobacco availability was greater in neighbourhoods with more Black, Hispanic/Latine and Asian residents (82.8%, 90.3% and 40.0% of effect sizes, respectively). Two effect sizes found greater availability with more same-sex households.ConclusionsThere are stark inequities in tobacco retailer availability. Moving beyond documenting inequities to partnering with communities to design, implement, and evaluate interventions that reduce and eliminate inequities in retail availability is needed to promote an equitable retail environment.PROSPERO registration numberCRD42019124984.

Socioeconomic inequities in early access to kidney transplantation among patients with end-stage kidney disease (ESKD) are well documented. It is unknown whether these inequities can be mitigated through access to nephrology care prior to starting dialysis. This study evaluated whether pre-ESKD nephrology care meaningfully explained the association between neighborhood poverty and referral for kidney transplantation among patients initiating treatment for ESKD. In this retrospective cohort study using United States Renal Data System data (January 1, 2012 to June 30, 2021), we identified 192,318 adults with incident ESKD from dialysis facilities in Southeast, Northeast, New York, and Ohio River Valley US regions. Neighborhood poverty exposure was dichotomized based on zip code poverty rates (≥20% vs 0%–19%), and referral outcomes were assessed from 28 transplant centers. We used marginal structural Cox models with inverse probability of treatment weighting to estimate the direct effect of neighborhood poverty on referral for kidney transplantation, controlling for access to pre-ESKD nephrology care (controlled direct effect). Findings show that 68% had pre-ESKD nephrology care, and 25% lived in high-poverty areas. Pre-ESKD nephrology care was associated with increased referral (hazard ratio (HR): 1.26, 95% CI: 1.22, 1.30). Adjusted analyses using marginal structural Cox models with inverse probability weighting revealed that pre-ESKD nephrology care did not fully explain the association between neighborhood poverty and referral for kidney transplantation (controlled direct effect HR: 0.87, 95% CI: 0.85, 0.89; total effect HR: 0.90, 95% CI: 0.88, 0.91). These results underscore the beneficial role of pre-ESKD nephrology care in enhancing transplant referral access. However, persistent disparities linked to neighborhood poverty remain evident. The study emphasizes the continued importance of pre-ESKD nephrology care as a clinical standard for all patients with ESKD. Future research should explore interventions earlier in the kidney disease continuum to address socioeconomic disparities and improve equitable access to kidney transplantation. For people with end-stage kidney disease (ESKD), survival depends on either regular dialysis treatments or a kidney transplant. For most people, a kidney transplant offers the best long-term survival and quality of life compared to dialysis. People living in poorer neighborhoods face significant challenges in getting referred for a kidney transplant. Our study aimed to investigate if receiving care from a kidney specialist (nephrologist) before needing dialysis (pre-ESKD nephrology care) could help overcome these income-related disparities in transplant access. We looked at records from nearly 200,000 adults across 4 US regions who started treatment for ESKD. We categorized neighborhoods as “high-poverty” (where 20% or more residents live below the poverty line) or “low-poverty” areas. Using advanced statistical methods, we analyzed how neighborhood poverty affected transplant referral, specifically assessing the role of pre-ESKD nephrology care. Our findings showed that most patients (68%) had seen a nephrologist before dialysis. Seeing a nephrologist was associated with a 26% higher chance of being referred for a transplant. However, even among those who received predialysis nephrology care, living in a high-poverty neighborhood still meant they were 13% less likely to be referred for a transplant. This study highlights that while pre-ESKD nephrology care is beneficial and increases the likelihood of transplant referral, it alone does not fully close the gap in access influenced by neighborhood poverty. To achieve equitable access to kidney transplantation for all patients, future efforts must target broader interventions that address the underlying socioeconomic factors affecting health throughout a patient's kidney disease journey. Key findings•Pre–ESKD nephrology care was associated with higher transplant referral rates.•Patients in high-poverty areas were less likely to be referred for transplant.•Pre-ESKD care did not explain lower referral rates in high poverty neighborhoods.What this adds to what is known?•Pre-ESKD care improves referrals but doesn't eliminate poverty-related disparities.What is the implication and should change now?•Maintain pre-ESKD care; other strategies needed to address poverty-driven barriers.

This study investigates the association between neighborhood socioeconomic status, measured by the Distressed Communities Index (DCI), and short-term outcomes following colon resection. Utilizing the Maryland State Inpatient Sample database (SID 2018–2020), we determined the association between DCI and post-op outcomes following colon resection including length of stay, readmissions, 30-day in-hospital mortality, and non-routine discharges. Multivariate regression analysis was performed to control for potential confounding factors. Of the 13,839 patients studied, median age was 63, with 54.3 ​% female and 64.5 ​% elective admissions. Laparoscopic surgery was performed in 36.9 ​% cases, with a median hospital stay of 5 days. Patients in distressed communities faced higher risks of emergency admission (OR: 1.31), prolonged hospitalization (OR: 1.29), non-routine discharges (OR: 1.36), and readmission (OR: 1.33). Black patients had longer stays than White patients (OR: 1.3). Despite adjustments, in-hospital mortality did not significantly differ among neighborhoods. Our study reveals that patients residing in distressed neighborhoods face a higher risk of prolonged hospitalization, non-routine discharges, and readmission rate after colon resection. •Patients from distressed neighborhoods have worse postoperative outcomes after colon resection.•The Distressed Communities Index (DCI) is a comprehensive measure of neighborhood socioeconomic status.•The DCI can serve as a preoperative risk assessment tool to optimaze patients' surgical outcome.

Recent research has demonstrated that domains of social determinants of health (SDOH) (e.g. air pollution and social context) are associated with psychosis. However, SDOHs have often been studied in isolation. This study investigated distinct exposure profiles, estimated their associations with persistent distressing psychotic-like experiences (PLE), and evaluated whether involvement in physical activity partially explains this association. Analyses included 8,145 young adolescents from the Adolescent Brain and Cognitive Development Study. Data from the baseline and three follow-ups were included. Area-level geocoded variables spanning various domains of SDOH, including socioeconomic status, education, crime, built environment, social context, and crime, were clustered using a self-organizing map method to identify exposure profiles. Generalized linear mixed modeling tested the association between exposure profiles and persistent distressing PLE and physical activities (i.e. team and individual sports), adjusting for individual-level covariates including age, sex, race/ethnicity, highest level of parent education, family-relatedness, and study sites. Five exposure profiles were identified. Compared to the reference Profile 1 (suburban affluent areas), Profile 3 (rural areas with low walkability and high ozone), and Profile 4 (urban areas with high SES deprivation, high crime, and high pollution) were associated with greater persistent distressing PLE. Team sports mediated 6.14% of the association for Profile 3. This study found that neighborhoods characterized by rural areas with low walkability and urban areas with high socioeconomic deprivation, pollution concentrations, and crime were associated with persistent distressing PLE. Findings suggest that various social-environmental factors may differentially impact the development of psychosis.

Suicide attempt is a complex behavior influenced by a combination of factors including clinical, neurocognitive, and environmental. We aimed to leverage multimodal data collected during pre/early adolescence in research settings to predict self-report of suicide attempts by mid-late adolescence reported in pediatric settings. We hypothesized that different data types contribute to suicide attempt prediction and that clinical features would be most predictive of future suicide attempts. We applied machine learning methods to clinical, neurocognitive, and geocoded neighborhood environmental data from the Philadelphia Neurodevelopmental Cohort study (Mean age [SD] = 11.1 [2.2], 53.3% female, 51.4% Black participants) to predict suicide attempt reported ~5 years later in two independent pediatric settings: primary care (n = 922, 5.3% suicide attempt) or emergency department (n = 497, 8.2% suicide attempt). We tested prediction performance using all data versus using subsets of features identified by three feature selection algorithms (Lasso, Relief, Random Forest). In the primary care sample, suicide attempt prediction using subsets of selected features (predictors) was good, achieving AUC = 0.75, sensitivity/specificity 0.76/0.77. The use of highest-ranking features yielded similar prediction performance in external validation using the independent emergency department sample with AUC = 0.74, sensitivity/specificity 0.66/0.70. Different algorithms identified different high-ranking features, but overall multiple data domains were represented among the highest-ranking features. Besides suicidal ideation, the highest-ranking clinical predictive symptoms were from psychosis or mania spectrum. Results suggest that data collected at a single timepoint during preadolescence can inform suicide attempt prediction during mid-late adolescence, in different clinical settings. Findings encourage incorporation of multiple data types including neurocognitive and geocoded data, alongside clinical data, in machine learning suicide attempt prediction pipelines.

There is limited information on the association between walkability and health in Asian countries. Our study aimed to investigate the association between neighborhood walkability and mortality in Taiwanese adults. We selected 457,874 participants ( y of age) from Taiwan who joined a standard medical examination program between 1998 and 2016 and followed them until 31 July 2021. Three walkability measures were estimated within a walking distance of of participant's addresses: points of interest (POI), transit stations, and impedance (restrictions to walking due to absence of intersections and physical barriers). Walkability measures were applied as continuous and categorical (tertiles) variables in data analyses. Mortality data were obtained from the National Death Registry maintained by the Ministry of Health and Welfare in Taiwan. A time-varying Cox regression model was used to investigate the association of neighborhood walkability with deaths from natural causes and specific causes. This study identified 24,744 deaths over a median follow-up of 16.9 y. In comparison with participants living with the first tertile for numbers of POI and transit stations, those living with higher numbers of POI and transit stations were associated with a lower risk of natural-cause mortality, with hazard ratios (HRs) of 0.97 [95% confidence intervals (CIs): 0.94, 1.00] and 0.93 (95% CI: 0.90, 0.96) for second and third tertiles of numbers of POI, and 0.99 (95% CI: 0.96, 1.02) and 0.94 (95% CI: 0.92, 0.98) for second and third tertiles of numbers of transit stations, respectively. Each unit increase in POI and transit stations was associated with a 3% ( 0.97; 95% CI: 0.96, 0.99) and 2% ( 0.98; 95% CI: 0.97, 0.99) reduced risk of natural-cause mortality, respectively. In addition, in comparison with living in areas with the first tertile of impedance, living with the third tertile of impedance was associated a higher risk of natural-cause mortality, with HRs of 1.01 (95% CI: 1.00, 1.03). One unit increase in impedance was associated with a 1% ( 1.01; 95% CI: 1.00, 1.03) increased risk of natural-cause mortality. We also found significantly inverse associations between three walkability measures with deaths from cardiovascular diseases and between POI and death from chronic respiratory diseases. Our findings indicate that a higher level of neighborhood walkability was associated with a lower risk of mortality. Our data suggest that it is important to take into account neighborhood walkability in urban planning and health guideline development. https://doi.org/10.1289/EHP15209.

BackgroundObesity prevalence differs by neighbourhood. One such characteristic of these neighbourhoods is the level of socioeconomic disadvantage. Understanding the nature of neighbourhood socioeconomic inequalities is important for shaping targeted interventions and policies to promote equitable access to resources and opportunities that support healthy living. The aim of this study was to examine associations between neighbourhood socioeconomic disadvantage and body mass index (BMI) over a 16-year period among a population-representative Australian sample.MethodsThis study used data from 208 309 observations collected between 2006 and 2021 from the Household, Income and Labour Dynamics in Australia Survey. Neighbourhood disadvantage was measured via a census-derived index, and participants self-reported height and weight, which was computed to BMI. Data were analysed using multilevel and fixed effects regression to examine overall associations, trends over time and changes in neighbourhoods with changes in BMI.ResultsThere was an overall association between neighbourhood socioeconomic disadvantage and BMI. BMI was higher among those in the most disadvantaged neighbourhoods compared with the least disadvantaged neighbourhoods (β=1.31, 95% CI 1.15 to 1.46). BMI trends over time were widening with greater increases in BMI among those in the most disadvantaged neighbourhoods (Q1: β=0.04, 95% CI 0.02 to 0.06 and Q2: β=0.05, 95% CI 0.03 to 0.06). Changes in the level of neighbourhood socioeconomic disadvantage were positively associated with changes in BMI, with the strongest association among those transitioning to more disadvantaged neighbourhoods (Q1: β=0.10, 95% CI 0.02 to 0.18 and Q2: β=0.08, 95% CI 0.02 to 0.15).ConclusionsUsing methodologically rigorous epidemiological approaches along with longitudinal, national data, this study found strong evidence of neighbourhood socioeconomic inequalities in BMI. Understanding the neighbourhood-level mechanisms likely to exacerbate these inequalities remains a future research priority.

Prior research has established the greater exposure of African Americans from all income groups to disadvantaged environments compared to whites, but the traditional focus in studies of neighborhood stratification obscures heterogeneity within racial/ethnic groups in residential attainment over time. Also obscured are the moderating influences of broader social changes on the life-course and the experiences of Latinos, a large and growing presence in American cities. We address these issues by examining group-based trajectory models of residential neighborhood disadvantage among white, Black, and Latino individuals in a multi-cohort longitudinal research design of over 1,000 children from Chicago as they transitioned to adulthood over the last quarter century. We find considerable temporal consistency among white individuals compared to dynamic heterogeneity among nonwhite individuals in exposure to residential disadvantage, especially Black individuals and those born in the 1980s compared to the 1990s. Racial and cohort differences are not accounted for by early-life characteristics that predict long-term attainment. Inequalities by race in trajectories of neighborhood disadvantage are thus at once more stable and more dynamic than previous research suggests, and they are modified by broader social changes. These findings offer insights on the changing pathways by which neighborhood racial inequality is produced.