An exploratory study on material deprivation and loneliness among older adults in Hong Kong.

BACKGROUND: Poverty, as a risk factor for loneliness, has been understudied, and there is a need to gain a better understanding of the relationship between poverty examined by material deprivation and loneliness among older adults in Hong Kong. It also aimed to explore the possible mediation and moderation effects of social support, social networks, neighborhood collective efficacy, and social engagement in the link between material deprivation and loneliness. METHODS: 1696 Chinese older adults aged 60 years and above (Mage = 74.61; SD = 8.71) participated in a two-wave study. Older adults reported their loneliness level, material deprivation, perceived level of social support, social network, neighborhood collective efficacy, social engagement, and sociodemographic information. Logistic regression was conducted to examine the effect of material deprivation on loneliness, as well as the mediation and moderation models. RESULTS: The results indicated that material deprived older adults reported a significantly higher level of loneliness 2 years later when controlling for demographic variables, health-related factors, and loneliness at baseline. We also found that engagement in cultural activities partially mediated the effect of material deprivation and loneliness. Furthermore, neighborhood collective efficacy and engagement in cultural activities were significant moderators that buffer the relationship between material deprivation and loneliness. CONCLUSIONS: Our results suggested the need to alleviate the negative impact of material deprivation on loneliness by developing interventions focused on promoting neighborhood collective efficacy and social engagement, which could be aimed at building meaningful bonds among Chinese older adults in Hong Kong.

Longitudinal Impacts of Precision Greenness on Alzheimer's Disease.

BACKGROUND: The potential for greenness as a novel protective factor for Alzheimer's disease (AD) requires further exploration. OBJECTIVES: This study assesses prospectively and longitudinally the association between precision greenness - greenness measured at the micro-environmental level, defined as the Census block - and AD incidence. DESIGN: Older adults living in consistently high greenness Census blocks across 2011 and 2016 were compared to those living in consistently low greenness blocks on AD incidence during 2012-2016. SETTING: Miami-Dade County, Florida, USA. PARTICIPANTS: 230,738 U.S. Medicare beneficiaries. MEASUREMENTS: U.S. Centers for Medicare and Medicaid Services Chronic Condition Algorithm for AD based on ICD-9 codes, Normalized Difference Vegetation Index, age, sex, race/ethnicity, neighborhood income, and walkability. RESULTS: Older adults living in the consistently high greenness tertile, compared to those in the consistently low greenness tertile, had 16% lower odds of AD incidence (OR=0.84, 95% CI: 0.76-0.94, p=0.0014), adjusting for age, sex, race/ethnicity, and neighborhood income. Age, neighborhood income and walkability moderated greenness' relationship to odds of AD incidence, such that younger ages (65-74), lower-income, and non-car dependent neighborhoods may benefit most from high greenness. CONCLUSIONS: High greenness, compared to low greenness, is associated with lower 5-year AD incidence. Residents who are younger and/or who reside in lower-income, walkable neighborhoods may benefit the most from high greenness. These findings suggest that consistently high greenness at the Census block-level, may be associated with reduced odds of AD incidence at a population level.

Associations between the objective and perceived food environment and eating behavior in relation to socioeconomic status among adults in peri-urban settings: results from the CIVISANO study in Flanders, Belgium.

Obesity, a significant public health concern, disproportionately affects people with lower socioeconomic status (SES). Food environments have been identified as part of the causal chain of this disparity. This study investigated variations in the food environment across groups with different SES profiles residing in peri-urban municipal settings. In addition, it examined the association of the perceived and objective food environments with eating behaviour and assessed if these associations were moderated by SES. Utilizing GIS and survey data (n = 497, aged 25-65), results showed differences in the objective and perceived food environments based on SES. Respondents with higher SES perceived their food environments as better but resided farther from all food outlets compared to respondents with lower SES. However, there was no difference in outlet density or mRFEI between SES groups. SES moderated associations between the objective and perceived food environments and most eating behavior outcomes except fast food consumption frequency. For fruits and vegetables, SES moderated the association between neighborhood availability and consumption frequency (ß0.23,CI0.03;0.49). Stratified analysis revealed a positive association for both lower (ß0.15, CI0.03;0.27) and higher (ß0.37, CI 0.12;0.63) SES groups. For snack foods, SES moderated the association between healthy outlet density and consumption frequency (ß-0.60, CI-0.94; -0.23), showing statistical significance only for respondents with higher SES (ß0.36,CI 0.18;0.55). Similarly, for sugar-sweetened beverages, a statistically significant interaction was observed between unhealthy outlet density in the 1000m buffer and consumption frequency (ß 0.06, CI 0.02; 0.11). However, this association was only statistically significant for respondents with higher SES (ß-0.02,CI -0.05;-0.0002). These results emphasize the significance of SES as a crucial element in comprehending the connection between the food environment and eating behaviour. Indicating the need for policymakers to take SES into account when implementing food environment interventions, particularly when focusing on the neighborhood food environment without considering residents' SES and their perceptions.

Multidimensional Approach to Exploring Neighborhood Determinants and Symptom Severity Among Individuals With Psychosis.

Importance: The impact of cumulative exposure to neighborhood factors on psychosis, depression, and anxiety symptom severity prior to specialized services for psychosis is unknown. Objective: To identify latent neighborhood profiles based on unique combinations of social, economic, and environmental factors, and validate profiles by examining differences in symptom severity among individuals with first episode psychosis (FEP). Design, Setting, and Participants: This cohort study used neighborhood demographic data and health outcome data for US individuals with FEP receiving services between January 2017 and August 2022. Eligible participants were between ages 14 and 40 years and enrolled in a state-level coordinated specialty care network. A 2-step approach was used to characterize neighborhood profiles using census-tract data and link profiles to mental health outcomes. Data were analyzed March 2023 through October 2023. Exposures: Economic and social determinants of health; housing conditions; land use; urbanization; walkability; access to transportation, outdoor space, groceries, and health care; health outcomes; and environmental exposure. Main Outcomes and Measures: Outcomes were Community Assessment of Psychic Experiences 15-item, Patient Health Questionnaire 9-item, and Generalized Anxiety Disorder 7-item scale. Results: The total sample included 225 individuals aged 14 to 36 years (mean [SD] age, 20.7 [4.0] years; 152 men [69.1%]; 9 American Indian or Alaska Native [4.2%], 13 Asian or Pacific Islander [6.0%], 19 Black [8.9%], 118 White [55.1%]; 55 Hispanic ethnicity [26.2%]). Of the 3 distinct profiles identified, nearly half of participants (112 residents [49.8%]) lived in urban high-risk neighborhoods, 56 (24.9%) in urban low-risk neighborhoods, and 57 (25.3%) in rural neighborhoods. After controlling for individual characteristics, compared with individuals residing in rural neighborhoods, individuals residing in urban high-risk (mean estimate [SE], 0.17 [0.07]; P = .01) and urban low-risk neighborhoods (mean estimate [SE], 0.25 [0.12]; P = .04) presented with more severe psychotic symptoms. Individuals in urban high-risk neighborhoods reported more severe depression (mean estimate [SE], 1.97 [0.79]; P = .01) and anxiety (mean estimate [SE], 1.12 [0.53]; P = .04) than those in rural neighborhoods. Conclusions and Relevance: This study found that in a cohort of individuals with FEP, baseline psychosis, depression, and anxiety symptom severity differed by distinct multidimensional neighborhood profiles that were associated with where individuals reside. Exploring the cumulative effect of neighborhood factors improves our understanding of social, economic, and environmental impacts on symptoms and psychosis risk which could potentially impact treatment outcomes.

The impact of historical redlining on neurosurgeon distribution and reimbursement in modern neighborhoods.

Background: This study examines the lasting impact of historical redlining on contemporary neurosurgical care access, highlighting the need for equitable healthcare in historically marginalized communities. Objective: To investigate how redlining affects neurosurgeon distribution and reimbursement in U.S. neighborhoods, analyzing implications for healthcare access. Methods: An observational study was conducted using data from the Center for Medicare and Medicaid Services (CMS) National File, Home Owner's Loan Corporation (HOLC) neighborhood grades, and demographic data to evaluate neurosurgical representation across 91 U.S. cities, categorized by HOLC Grades (A, B, C, D) and gentrification status. Results: Of the 257 neighborhoods, Grade A, B, C, and D neighborhoods comprised 5.40%, 18.80%, 45.8%, and 30.0% of the sample, respectively. Grade A, B, and C neighborhoods had more White and Asian residents and less Black residents compared to Grade D neighborhoods (p < 0.001). HOLC Grade A (OR = 4.37, 95%CI: 2.08, 9.16, p < 0.001), B (OR = 1.99, 95%CI: 1.18, 3.38, p = 0.011), and C (OR = 2.37, 95%CI: 1.57, 3.59, p < 0.001) neighborhoods were associated with a higher representation of neurosurgeons compared to Grade D neighborhoods. Reimbursement disparities were also apparent: neurosurgeons practicing in HOLC Grade D neighborhoods received significantly lower reimbursements than those in Grade A neighborhoods ($109,163.77 vs. $142,999.88, p < 0.001), Grade B neighborhoods ($109,163.77 vs. $131,459.02, p < 0.001), and Grade C neighborhoods ($109,163.77 vs. $129,070.733, p < 0.001). Conclusion: Historical redlining continues to shape access to highly specialized healthcare such as neurosurgery. Efforts to address these disparities must consider historical context and strive to achieve more equitable access to specialized care.

Assessing structural models of neighborhood and family sociodemographic characteristics and their relations with externalizing psychopathology.

Externalizing psychopathology has been found to have small to moderate associations with neighborhood and family sociodemographic characteristics. However, prior studies may have used suboptimal operationalizations of neighborhood sociodemographic characteristics and externalizing psychopathology, potentially misestimating relations between these constructs. To address these limitations, in the current study we test different measurement models of these constructs and assess the structural relations between them. Using a population-representative sample of 2,195 twins and siblings from the Georgia Twin Study and data from the National Neighborhood Data Archive and 2000 U.S. Census, we assessed the fit of competing measurement models for family sociodemographic, neighborhood sociodemographic, and neighborhood environment characteristics. In structural models, we regressed a general externalizing dimension on different operationalizations of these variables separately and then simultaneously in a final model. Latent variable operationalizations of family sociodemographic, neighborhood sociodemographic, and neighborhood environment characteristics explained no more variance in broad externalizing psychopathology than other operationalizations. In an omnibus model, family sociodemographic characteristics showed a small association with externalizing psychopathology, while neighborhood sociodemographic and environmental characteristics did not. Family sociodemographic characteristics showed small associations with neighborhood sociodemographic and environmental characteristics, and neighborhood sociodemographic characteristics were moderately associated with neighborhood environment. These findings suggest that family sociodemographic characteristics are more associated with the development of broad externalizing psychopathology in youth than neighborhood sociodemographic characteristics and neighborhood environment. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Exploring residential relocation- differences between newcomers and settled residents in health, travel behaviour and neighbourhood perceptions.

This study explores whether people who have recently moved to an area differ from longer-term residents in their health, travel behaviour, and perceptions of the environment. Using a large, representative sample from the UKHLS, Newcomers demonstrate significantly lower mental and physical health, reduced car commuting, and a higher likelihood of liking their neighbourhood. Area deprivation, urbanicity, household income, and age emerge as influential moderators with i.e. Newcomers in affluent areas experiencing lower physical health than Settled Residents, and rural Newcomers expressing less neighbourhood satisfaction. Our findings highlight that Newcomers' perceptions of their environment diverge and environmental influences vary among population segments, potentially impacting related health behaviours such as active travel. Furthermore, residential relocation introduces Newcomers with distinct characteristics into areas, affecting the context in which potential population health interventions aiming to influence health behaviours operate. This necessitates a deeper understanding of what influences reactions to the environment as well as ongoing adaptation of environmental interventions to respond to changing contexts within the same location over time.

The moderating effects of greenspace on the association between neighbourhood disadvantage and obesity among mid-to-older aged Australian adults.

This study examined whether the association between neighbourhood disadvantage and obesity was moderated by quantity and quality of greenspace. The sample included 2848 mid-to-older aged adults residing in 200 neighbourhoods in Brisbane, Australia from the HABITAT study. Self-reported height and weight were used to calculate body mass index (BMI), neighbourhood disadvantage was measured using a census-derived composite index and greenspace was measured geospatially. We found evidence of moderation by park quality: lower average BMI at higher levels of park quality was shown in the Q3 rather than the Q1 (least disadvantaged) neighbourhood disadvantage group. The findings suggest that, for reducing socioeconomic inequalities in obesity, the quality of greenspace is imperative.

Neighborhood physical environments and change in cardiometabolic risk factors over 14 years in the study of Women's health across the nation.

BACKGROUND: Neighborhood physical environments may influence cardiometabolic health, but prior studies have been inconsistent, and few included long follow-up periods. METHODS: Changes in cardiometabolic risk factors were measured for up to 14 years in 2830 midlife women in the Study of Women's Health Across the Nation, a multi-ethnic/racial cohort of women from seven U.S. sites. Data on neighborhood food retail environments (modified Retail Food Environment Index) and walkability (National Walkability Index) were obtained for each woman's residence at each follow-up. Data on neighborhood access to green space, parks, and supermarkets were available for subsets (32-42%) of women. Models tested whether rates of change in cardiometabolic outcomes differed based on neighborhood characteristics, independent of sociodemographic and health-related covariates. RESULTS: Living in more (vs. less) walkable neighborhoods was associated with favorable changes in blood pressure outcomes (SBP: -0.27 mmHg/year, p = 0.002; DBP: -0.22 mmHg/year, p < 0.0001; hypertension status: ratio of ORs = 0.79, p < 0.0001), and small declines in waist circumference (-0.09 cm/year, p = 0.03). Small-magnitude associations were also observed between low park access and greater increases in blood pressure outcomes (SBP: 0.37 mmHg/year, p = 0.003; DBP: 0.15 mmHg/year, p = 0.04; hypertension status: ratio of ORs = 1.16, p = .04), though associations involving DBP and hypertension were only present after adjustment for sociodemographic variables. Other associations were statistically unreliable or contrary to hypotheses. CONCLUSION: Neighborhood walkability may have a meaningful influence on trajectories of blood pressure outcomes in women from midlife to early older adulthood, suggesting the need to better understand how individuals interact with their neighborhood environments in pursuit of cardiometabolic health.

Utilizing social determinants of health to identify most vulnerable neighborhoods-Latent class analysis and GIS map.

OBJECTIVES: Public Health officials are often challenged to effectively allocate limited resources. Social determinants of health (SDOH) may cluster in areas to cause unique profiles related to various adverse life events. The authors use the framework of unintended teen pregnancies to illustrate how to identify the most vulnerable neighborhoods. METHODS: This study used data from the U.S. American Community Survey, Princeton Eviction Lab, and Connecticut Office of Vital Records. Census tracts are small statistical subdivisions of a county. Latent class analysis (LCA) was employed to separate the 832 Connecticut census tracts into four distinct latent classes based on SDOH, and GIS mapping was utilized to visualize the distribution of the most vulnerable neighborhoods. GEE Poisson regression model was used to assess whether latent classes were related to the outcome. Data were analyzed in May 2021. RESULTS: LCA's results showed that class 1 (non-minority non-disadvantaged tracts) had the least diversity and lowest poverty of the four classes. Compared to class 1, class 2 (minority non-disadvantaged tracts) had more households with no health insurance and with single parents; and class 3 (non-minority disadvantaged tracts) had more households with no vehicle available, that had moved from another place in the past year, were low income, and living in renter-occupied housing. Class 4 (minority disadvantaged tracts) had the lowest socioeconomic characteristics. CONCLUSIONS: LCA can identify unique profiles for neighborhoods vulnerable to adverse events, setting up the potential for differential intervention strategies for communities with varying risk profiles. Our approach may be generalizable to other areas or other programs. KEY MESSAGES: What is already known on this topic Public health practitioners struggle to develop interventions that are universally effective. The teen birth rates vary tremendously by race and ethnicity. Unplanned teen pregnancy rates are related to multiple social determinants and behaviors. Latent class analysis has been applied successfully to address public health problems. What this study adds While it is the pregnancy that is not planned rather than the birth, access to pregnancy intention data is not available resulting in a dependency on teen birth data for developing public health strategies. Using teen birth rates to identify at-risk neighborhoods will not directly represent the teens at risk for pregnancy but rather those who delivered a live birth. Since teen birth rates often fluctuate due to small numbers, especially for small neighborhoods, LCA may avoid some of the limitations associated with direct rate comparisons. The authors illustrate how practitioners can use publicly available SDOH from the Census Bureau to identify distinct SDOH profiles for teen births at the census tract level. How this study might affect research, practice or policy These profiles of classes that are at heightened risk potentially can be used to tailor intervention plans for reducing unintended teen pregnancy. The approach may be adapted to other programs and other states to prioritize the allocation of limited resources.

Piloting a Measure of Segregation at the Census Tract Level: Associations with Place and Racial/Ethnic Disparities in Life Expectancy.

This study considers residential segregation as a critical driver of racial/ethnic health disparities and introduces a proxy measure of segregation that estimates the degree of segregation at the census tract level with a metric capturing the overrepresentation of a racialized/ethnic group in a census tract in relation to that group's representation at the city level. Using Dallas, Texas as a pilot city, the measure is used to investigate mean life expectancy at birth for relatively overrepresented Hispanic, non-Hispanic white, non-Hispanic Black, and Asian census tracts and examine for significant differences between mean life expectancy in relatively overrepresented census tracts and that group's mean life expectancy at the state level. Multivariable linear regression analysis was utilized to assess how segregation measured at the census tract level associates with life expectancy across different racialized/ethnic groups, controlling for socioeconomic disparities. This study aimed to expose the need to consider the possibility of neighborhood mechanisms beyond socioeconomic characteristics as an important determinant of health and draw attention to the importance of critically engaging the experience of place in examinations of racial and ethnic health disparities. Multivariable linear regression modeling resulted in significant findings for non-Hispanic Black, non-Hispanic white, and Asian groups, indicating increased census tract-level life expectancy for Black and white residents in highly segregated census tracts and decreased life expectancy for residents of tracts in which the Asian community is overrepresented when compared to state means. Unadjusted models demonstrated socioeconomic inequities between first and fourth quartile census tracts and pointed to the importance of mixed methods in health disparities research and the importance of including the voice of community members to account for places of daily lived experience and people's relationships with them.

Exploring the Relationship between Built Environment Attributes and Physical Activity in Lower-Income Aging Adults: Preliminary Insights from a Multi-Level Trial.

The built environment has been linked to physical activity (PA) behaviors, yet there is limited knowledge of this association among lower-income midlife and older adults who are insufficiently active. The present cross-sectional study utilized baseline data collected between October 2017 and November 2019 from a clustered randomized controlled trial to determine how built environment attributes were associated with PA behaviors among midlife and older adults (n = 255) residing in or near affordable housing sites (n = 10). At each site, perceptions of the built environment were collected and scored at the participant level via the abbreviated Neighborhood Environment Walkability Survey (NEWS-A), while objective built environment attributes were measured and scored by trained research staff using the Physical Activity Resource Assessment (PARA). Multiple PA behaviors-walking, total PA, and moderate-to-vigorous PA (MVPA) (min/wk)-were measured using the validated Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire. Adjusted linear regression models examined associations between NEWS-A measures and PA behaviors, and site-level correlations between PARA measures and PA behaviors were examined using Spearman's rank correlations. At the participant level, adjusted models revealed that a one point increase in the NEWS-A aesthetics score was associated with a 57.37 min/wk increase in walking (ß = 57.37 [95% CI: 20.84, 93.91], p = 0.002), with a similar association observed for street connectivity and MVPA (ß = 24.31 min/wk [95% CI: 3.22, 45.41], p = 0.02). At the site level, MVPA was positively correlated with the quality of the features of local, PA-supportive environmental resources (ρ = 0.82, p = 0.004). Findings indicate that participant- and site-level measures of the built environment may play a role in promoting PA behavior among this demographic and similar populations. Results also suggest that improvements in aesthetic attributes and street connectivity, along with enhancing the quality of local, PA-supportive environmental resources, may be effective strategies for promoting physical activity among lower-income midlife and older adults.

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.

BACKGROUND: 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. METHODS AND RESULTS: 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]). CONCLUSIONS: 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.

Modeling health and well-being measures using ZIP code spatial neighborhood patterns.

Individual-level assessment of health and well-being permits analysis of community well-being and health risk evaluations across several dimensions of health. It also enables comparison and rankings of reported health and well-being for large geographical areas such as states, metropolitan areas, and counties. However, there is large variation in reported well-being within such large spatial units underscoring the importance of analyzing well-being at more granular levels, such as ZIP codes. In this paper, we address this problem by modeling well-being data to generate ZIP code tabulation area (ZCTA)-level rankings through spatially informed statistical modeling. We build regression models for individual-level overall well-being index and scores from five subscales (Physical, Financial, Social, Community, Purpose) using individual-level demographic characteristics as predictors while including a ZCTA-level spatial effect. The ZCTA neighborhood information is incorporated by using a graph Laplacian matrix; this enables estimation of the effect of a ZCTA on well-being using individual-level data from that ZCTA as well as by borrowing information from neighboring ZCTAs. We deploy our model on well-being data for the U.S. states of Massachusetts and Georgia. We find that our model can capture the effects of demographic features while also offering spatial effect estimates for all ZCTAs, including ones with no observations, under certain conditions. These spatial effect estimates provide community health and well-being rankings of ZCTAs, and our method can be deployed more generally to model other outcomes that are spatially dependent as well as data from other states or groups of states.

An examination of early socioeconomic status and neighborhood disadvantage as independent predictors of antisocial behavior: A longitudinal adoption study.

The present study examined early socioeconomic status (SES) and neighborhood disadvantage (ND) as independent predictors of antisocial behavior (ASB) and addressed the etiology of the associations (i.e., genes versus the environment) using a longitudinal adoption design. Prospective data from the Colorado Adoption Project (435 adoptees, 598 nonadopted children, 526 biological grandparents of adoptees, 481 adoptive parents, and 617 nonadoptive parents including biological parents of unrelated siblings of adoptees) were examined. SES and ND were assessed during infancy and ASB was evaluated from ages four through 16 using parent and teacher report. Associations between predictors and ASB were compared across adoptive and nonadoptive families and sex. Early SES was a nominally significant, independent predictor of antisocial ASB, such that lower SES predicted higher levels of ASB in nonadoptive families only. ND was not associated with ASB. Associations were consistent across aggression and delinquency, and neither SES nor ND was associated with change in ASB over time. Nominally significant associations did not remain significant after controlling for multiple testing. As such, despite nonsignificant differences in associations across sex or adoptive status, we were unable to make definitive conclusions regarding the genetic versus environmental etiology of or sex differences in the influence of SES and ND on ASB. Despite inconclusive findings, in nonadoptees, results were consistent-in effect size and direction-with previous studies in the literature indicating that lower SES is associated with increased risk for ASB.

The association between neighborhood deprivation and DNA methylation in an autopsy cohort.

Previous research has found that living in a disadvantaged neighborhood is associated with poor health outcomes. Living in disadvantaged neighborhoods may alter inflammation and immune response in the body, which could be reflected in epigenetic mechanisms such as DNA methylation (DNAm). We used robust linear regression models to conduct an epigenome-wide association study examining the association between neighborhood deprivation (Area Deprivation Index; ADI), and DNAm in brain tissue from 159 donors enrolled in the Emory Goizueta Alzheimer's Disease Research Center (Georgia, USA). We found one CpG site (cg26514961, gene PLXNC1) significantly associated with ADI after controlling for covariates and multiple testing (p-value=5.0e-8). Effect modification by APOE ε4 was statistically significant for the top ten CpG sites from the EWAS of ADI, indicating that the observed associations between ADI and DNAm were mainly driven by donors who carried at least one APOE ε4 allele. Four of the top ten CpG sites showed a significant concordance between brain tissue and tissues that are easily accessible in living individuals (blood, buccal cells, saliva), including DNAm in cg26514961 (PLXNC1). Our study identified one CpG site (cg26514961, PLXNC1 gene) that was significantly associated with neighborhood deprivation in brain tissue. PLXNC1 is related to immune response, which may be one biological pathway how neighborhood conditions affect health. The concordance between brain and other tissues for our top CpG sites could make them potential candidates for biomarkers in living individuals.

Impact of Neighborhood Social Cohesion and Rodent Sightings on Mental Health among Residents of New York City During the COVID-19 Pandemic.

Common mental disorders such as depression and anxiety are prevalent globally, and rates are especially high in New York City (NYC) since the COVID-19 pandemic. Neighborhood social and physical environments have been found to influence mental health. We investigated the impact of neighborhood social cohesion and neighborhood rodent sightings (as an indicator of neighborhood cleanliness) on nonspecific serious psychological distress (NSPD) status using 2020 NYC Community Health Survey data from 8781 NYC residents. Multivariable logistic regression was used to evaluate the relationships among social cohesion, rodent sightings, and NSPD adjusted for confounders and complex sampling and weighted to the NYC population. Effect measure modification of rodent sightings on the effect of social cohesion on NSPD was evaluated on the multiplicative scale by adding the interaction term to the multivariable model and, if significant, stratifying on the effect modifier, and on the additive scale using the relative excess risk due to interaction (RERI). Social cohesion was found to decrease the odds of NSPD, and rodent sightings were found to increase the odds of NSPD. We found significant evidence of effect measure modification on the multiplicative scale. In the stratified models, there was a protective effect of social cohesion against NSPD among those not reporting rodent sightings, but no effect among those reporting rodent sightings. Our findings suggest that both neighborhood social cohesion and rodent sightings impact the mental health of New Yorkers and that rodent infestations may diminish the benefit of neighborhood social cohesion.

Staffing and Antipsychotic Medication Use in Nursing Homes and Neighborhood Deprivation.

Importance: Inappropriate use of antipsychotic medications in nursing homes is a growing public health concern. Residents exposed to higher levels of socioeconomic deprivation in the area around a nursing home may be currently exposed, or have a long history of exposure, to more noise pollution, higher crime rates, and have less opportunities to safely go outside the facility, which may contribute to psychological stress and increased risk of receiving antipsychotic medications inappropriately. However, it is unclear whether neighborhood deprivation is associated with use of inappropriate antipsychotic medications and whether this outcome is different by facility staffing levels. Objective: To evaluate whether reported inappropriate antipsychotic medication use differs in severely and less severely deprived neighborhoods, and whether these differences are modified by higher levels of total nurse staffing. Design, Setting, and Participants: This was a cross-sectional analysis of a national sample of nursing homes that linked across 3 national large-scale data sets for the year 2019. Analyses were conducted between April and June 2023. Exposure: Neighborhood deprivation status (severe vs less severe) and total staffing hours (registered nurse, licensed practical nurse, certified nursing assistant). Main Outcome and Measures: This study estimated the association between neighborhood deprivation and the percentage of long-stay residents who received an antipsychotic medication inappropriately in the nursing home at least once in the past week and how this varied by nursing home staffing through generalized estimating equations. Analyses were conducted on the facility level and adjusted for state fixed effects. Results: This study included 10 966 nursing homes (1867 [17.0%] in severely deprived neighborhoods and 9099 [83.0%] in less deprived neighborhoods). Unadjusted inappropriate antipsychotic medication use was greater in nursing homes located in severely deprived neighborhoods (mean [SD], 15.9% [10.7%] of residents) than in those in less deprived neighborhoods (mean [SD], 14.2% [8.8%] of residents). In adjusted models, inappropriate antipsychotic medication use was higher in severely deprived neighborhoods vs less deprived neighborhoods (19.2% vs 17.1%; adjusted mean difference, 2.0 [95% CI, 0.35 to 3.71] percentage points) in nursing homes that fell below critical levels of staffing (less than 3 hours of nurse staffing per resident-day). Conclusions and Relevance: These findings suggest that levels of staffing modify disparities seen in inappropriate antipsychotic medication use among nursing homes located in severely deprived neighborhoods compared with nursing homes in less deprived neighborhoods. These findings may have important implications for improving staffing in more severely deprived neighborhoods.

Sense of neighborhood belonging and health: geographic, racial, and socioeconomic variation in Wisconsin.

Background: Individuals' sense of belonging (SoB) to their neighborhood is an understudied psychosocial factor that may influence the association between neighborhood characteristics, health, and disparities across socio-demographic groups. Methods: Using 2014-2016 data from the Survey of the Health of Wisconsin (SHOW, N = 1,706), we conduct a detailed analysis of SoB and health in an American context. We construct OLS and logistic regressions estimating belonging's association with general, physical, and mental health. We explore geographic, racial, and socioeconomic variation to understand both the differential distribution of SoB and its heterogeneous relationship with health. Results: A higher SoB is positively associated with better physical, mental, and general health. White participants report higher SoB than Black participants, yet the association between SoB and mental health is strongest among participants of color and urban residents. Conclusion: Sense of belonging to neighborhood significantly predicts many facets of health, with place and individual characteristics appearing to moderate this relationship. Racial, geographic, and socioeconomic disparities in belonging-health associations raise important questions about who benefits from the social, economic, and physical aspects of local communities.