Neighborhood-level Factors Research Articles

Neighborhood factors and triple negative breast cancer: The role of cumulative exposure to area-level risk factors.

Despite similar incidence rates among Black and White women, breast cancer mortality rates are 40% higher among Black women. More than half of the racial difference in breast cancer mortality can be attributed to triple negative breast cancer (TNBC), an aggressive subtype of invasive breast cancer that disproportionately affects Black women. Recent research has implicated neighborhood conditions in the etiology of TNBC. This study investigated the relationship between cumulative neighborhood-level exposures and TNBC risk. This single-institution retrospective study was conducted on a cohort of 3316 breast cancer cases from New Castle County, Delaware (from 2012 to 2020), an area of the country with elevated TNBC rates. Cases were stratified into TNBC and "Non-TNBC" diagnosis and geocoded by residential address. Neighborhood exposures included census tract-level measures of unhealthy alcohol use, metabolic dysfunction, breastfeeding, and environmental hazards. An overall cumulative risk score was calculated based on tract-level exposures. Univariate analyses showed each tract-level exposure was associated with greater TNBC odds. In multivariate analyses that controlled for patient-level race and age, tract-level exposures were not associated with TNBC odds. However, in a second multivariate model that included patient-level variables and considered tract-level risk factors as a cumulative exposure risk score, each one unit increase in cumulative exposure was significantly associated with a 10% increase in TNBC odds. Higher cumulative exposure risk scores were found in census tracts with relatively high proportions of Black residents. Cumulative exposure to neighborhood-level risk factors that disproportionately affect Black communities was associated with greater TNBC risk.

Abstract P433: Predictors of Self-Reported Medication Non-Adherence in Older Adults: The Atherosclerosis Risk in Communities Study

Introduction: Medication non-adherence increases the risk of hospitalization and mortality in older adults. Evidence from previous studies was not conclusive due to small sample size or lack of adjustment for potential confounders. This study aims to investigate the prevalence and predictors of medication non-adherence in older adults, considering both individual-level and neighborhood-level factors. Methods: We studied participants (aged 66-90 years) who were on at least one medication at visit 5 (2011-2013) of the ARIC Study. Potential predictors included demographic factors, individual-level and neighborhood-level socioeconomic factors, behavioral factors, depressive symptoms, and cognitive function. We estimated the prevalence of self-reported medication adherence using the Morisky Green Levine medication adherence questionnaire and considered intermediate and low as medication non-adherence. We used multivariable logistic regression to identify independent predictors of medication non-adherence, further adjusting for race-center, insurance types, comorbidities, and number of medications. Results: Among 5304 participants (mean age of 75.5 [SD 5.1] years, 21.6% Black, and 58.2% female), 2.3% and 37.1% reported low and intermediate medication adherence, respectively. After adjustment, age 66-74 (odds ratio [OR]= 1.23 [95% CI, 1.10-1.38]), current drinker (1.31 [1.10-1.55]), lack of physical activity (PA) (1.18 [1.01-1.37] for intermediate PA; 1.38 [1.21-1.58] for low PA), and depressive symptoms (2.30 [1.82-2.91]) were significant predictors of medication non-adherence ( Table ). Education and ADI were not associated with medication non-adherence. Conclusions: We found that almost 40% of older adults have medication non-adherence. Unhealthy lifestyle factors and depressive symptoms were associated with medication non-adherence. Education and neighborhood-level SES were not. Depression is an important modifiable factor to improve medication adherence in older adults.

Abstract P120: Neighborhood Factors Influence Cardiovascular Outcomes for Depressed and Non-Depressed Individuals With Heart Failure With Reduced Ejection Fraction

Introduction: Neighborhood-level measures including Area Deprivation Index (ADI) and walkability are associated with increased cardiovascular disease (CVD) morbidity, higher utilization of health services, and mortality. We sought to understand the impact of these neighborhood-level factors on hospital readmissions and mortality among recently hospitalized depressed and non-depressed individuals with heart failure and reduced ejection fraction (HFrEF) who enrolled in the NHLBI-funded Hopeful Heart Trial of “blended” collaborative care for HFrEF and co-morbid depression. . Hypothesis: We hypothesized worse ADI and Walk Scores will be associated with increased 12-month incidence of all-cause or cardiac-specific hospital readmission and mortality. Methods: From 3/14-10/17, Hopeful Heart enrolled 756 hospitalized HFrEF patients (EF<45%) and NYHA class II-IV symptoms including 629 depressed (screen-positive on 2-item Patient Health Questionnaire (PHQ-2) for depression prior to discharge and scored ≥10 on the PHQ-9 administered via telephone two weeks post-discharge) and 127 non-depressed HFrEF patients (PHQ-2 negative and PHQ-9 <5). We determined participants’ ADI score (0-100 scale, higher scores indicating greater deprivation) and Walk Score (0-100 scale, higher meaning more walkable) using home addresses at the time of hospital discharge. We categorized participants into top quartile (Q4) ADI and Walk score groups versus all other quartiles combined (Q1-Q3), and then compared these two groups using unadjusted, nonparametric Kaplan-Meier analyses with log-rank tests for differences in 12-month mortality and unadjusted chi-square tests for differences in 12-month incidence of readmission. Results: Of the 756 HFrEF participants (44% female; 73% white; EF: 28.3±9.1% mean; ADI: mean 66.7±23.5; Walk Score: mean 33.4±25.9), the mean PHQ-9 score for both ADI and Walk Score Q4 groups was similar to the Q1-3 groups. Participants in the Q4 group for ADI had a higher incidence of readmission that those in Q1-Q3 (81% -144 out of 178 - versus 70% - 400 out of 572, p=0.004), while those in the Q4 group for Walk Score were readmitted at a similar level to those in Q1-Q3. Those individuals in the top quartile for ADI and Walk Score showed no differences in cardiovascular (CV) mortality (14% incidence, 24 out of 171, for ADI; 14% total incidence, 25 out of 175 for Walk Score) or all-cause mortality (23% total incidence, 171 out of 750, for ADI; 23% total incidence, 175 out of 756 for Walk Score) compared with all other quartiles. Conclusions: Worse ADI but not Walk Score is predictive of higher risk of 12-month hospital readmission, and neither measure is predictive of 12-month CV or all-cause mortality. Further studies are needed to elaborate how area deprivation and other neighborhood factors affect outcomes for individuals with heart failure and design interventions to address these disparities.

Exploring travel patterns of people with disabilities: A multilevel analysis of accessible taxi trips in Toronto, Canada

Improving transport accessibility for people with disabilities (PWD) is crucial, given that this group is more likely to encounter transport-related exclusion (Lucas, 2012). Previous studies have shown that PWD experience numerous difficulties when travelling by public/para-transit (Bezyak et al., 2017; Park et al., 2022). If public transit services and policies are not improved to remove barriers for PWD, they will continue to experience limited access.Although PWD experience public transport-related inequities and exclusions, little is known about their travel patterns, possibly because their presence and diversity are often overlooked in transport research and travel surveys, and by planning practitioners (Oliver, 2013).This study investigates how PWD use accessible taxis in Toronto, Canada. Using spatial–temporal analyses and a multilevel regression model, we engage three research questions: (1) When and where are accessible taxi trips occurring in Toronto? (2) What are the primary trip purposes? And, (3) what factors influence the wait and in-vehicle times? Study data comes from a fully accessible taxi brokerage. The dataset includes roughly-one million accessible taxi trips from June 2018 to June 2021.The results show that the primary trip purpose of PWD is home-based health-related service i.e., the riders are travelling from home to health services or vice versa. Temporal aspects of trips (i.e., departure time, day of the week, and season) influence wait and in-vehicle times. Neighbourhood-level factors, such as population density, health service density, and rate of visible minorities have significant effects on in-vehicle times.These findings contribute to current academic debates on accessibility, equity, and inclusion issues as they relate to disability. Findings may also affect the lives of PWD by informing their advocacy efforts and helping accessible taxi service providers advance much-needed policy dialogue and service improvements.

Neighborhood-level COVID vaccination and booster disparities: A population-level analysis across California

ObjectivesTo describe vaccine and booster uptake by neighborhood-level factors in California. MethodsWe examined trends in COVID-19 vaccination up to September 21, 2021, and boosters up to March 29, 2022 using data from the California Department of Public Health. Quasi-Poisson regression was used to model the association between neighborhood-level factors and fully vaccinated and boosted among ZIP codes. Sub-analyses on booster rates were compared among the 10 census regions. ResultsIn a minimally adjusted model, a higher proportion of Black residents was associated with lower vaccination (HR = 0.97; 95%CI: 0.96–0.98). However, in a fully adjusted model, proportion of Black, Hispanic/Latinx, and Asian residents were associated with higher vaccination rates (HR = 1.02; 95%CI: 1.01–1.03 for all). The strongest predictor of low vaccine coverage was disability (HR = 0.89; 95%CI: 0.86–0.91). Similar trends persisted for booster doses. Factors associated with booster coverage varied by region. ConclusionsExamining neighborhood-level factors associated with COVID-19 vaccination and booster rates uncovered significant variation within the large and geographically and demographically diverse state of California. Equity-based approaches to vaccination must ensure a robust consideration of multiple social determinants of health.

Role, race, and place: Prostate cancer disparities in Patients' and Partners' health outcomes and psychosocial factors.

This study aimed to examine the effects of participant role (patient vs. partner), race (white vs. non-white), and place (less vs. more neighborhood deprivation) on health outcomes (quality of life [QOL] and symptoms) and stress-coping-related psychosocial factors (appraisals of illness and coping resources). This descriptive study included 273 patients and their partners (dyads) who transitioned from PCa treatment to self-management. We used established, psychometrically sound measures to assess health outcomes and psychosocial factors and conducted multilevel modeling analyses. Compared to partners, patients reported worse physical QOL; less frequent anxiety; less pain and fatigue; less bothersome hormonal problems; more bothersome urinary and sexual problems; greater self-efficacy; and more instrumental support. Compared to their white counterparts, non-white dyads reported better overall, emotional, and functional QOL; less depression; more positive appraisals, and greater self-efficacy. Compared to dyads in low ADI neighborhoods, dyads in high ADI (more deprived) neighborhoods reported worse social QOL; more bothersome urinary, sexual, and hormonal symptoms; and less interpersonal support. White patients reported the highest emotional support among all groups, while white partners reported the lowest emotional support. Our findings underscore the need to consider social determinants of health at multiple levels when investigating PCa disparities. Considering neighborhood-level socioeconomic factors, in addition to race and role, improves our understanding of the PCa disparities in QOL, symptoms, and psychosocial factors among patients and partners. Targeted multilevel supportive care interventions should tailor to the needs of racially diverse PCa patients and partners residing in deprived neighborhoods are needed.

Associations between greenness and predicted COVID-19-like illness incidence in the United States and the United Kingdom.

The study population includes participants enrolled in the COVID Symptom Study smartphone application in the United Kingdom and the United States (March-November 2020). All participants were encouraged to report their current health condition and suspected risk factors for COVID-19. We used a validated symptom-based classifier that predicts COVID-19-like illness. We estimated the Normalized Difference Vegetation Index (NDVI), for each participant's reported neighborhood of residence for each month, using images from Landsat 8 (30 m2). We used time-varying Cox proportional hazards models stratified by age, country, and calendar month at study entry and adjusted for the individual- and neighborhood-level risk factors. We observed 143,340 cases of predicted COVID-19-like illness among 2,794,029 participants. Neighborhood NDVI was associated with a decreased risk of predicted COVID-19-like illness incidence in the fully adjusted model (hazard ratio = 0.965, 95% confidence interval = 0.960, 0.970, per 0.1 NDVI increase). Stratified analyses showed protective associations among U.K. participants but not among U.S. participants. Associations were slightly stronger for White individuals, for individuals living in rural neighborhoods, and for individuals living in high-income neighborhoods compared to individuals living in low-income neighborhoods. Higher levels of greenness may reduce the risk of predicted COVID-19-like illness incidence, but these associations were not observed in all populations.

Neighborhood deprivation and residential property values do not affect weight loss at 1 or 3 years after bariatric surgery.

This study examined the association between individual- and neighborhood-level sociodemographic factors and surgical weight loss at 1 year (short term) and 3 years (long term). Data were obtained from the baseline survey of the BELONG (Bariatric Experience Long Term) prospective longitudinal cohort study. Individual-level self-reported data on sex, race and ethnicity, education, and household income were obtained by survey. Data from the 2010 US Census were used to calculate area Neighborhood Deprivation Index score and median value of owner-occupied housing units at the census tract level. Patients (N=1341) had a mean age of 43.4 (SD 11.3) years, were mostly female (86%), were mostly Black or Hispanic (52%), had some college education (83%), and had annual household incomes ≥$51,000 (55%). Percentage total weight loss was 25.8% (SD 9.0%) at year 1 and 22.2% (SD 10.5%) at year 3. Race and ethnicity and age were significant predictors of weight loss at 1 and 3 years with a small effect of self-reported household income at year 1. There were no significant associations between census tract-level Neighborhood Deprivation Index score or value of owner-occupied housing units and weight loss at either time point. Health systems could improve the chances of weight-loss maintenance after surgery by addressing factors related to racial and ethnic disparities and to income disparities.

Abstract C088: Biological and neighborhood-level social determinants of prostate disease aggressiveness among Black and White men undergoing prostate biopsy

Abstract Introduction and study purpose: Prostate cancer (PCa) is the leading type of newly diagnosed cancer and second leading cause of cancer death in American men. Significant racial differences in PCa incidence and mortality have been long-reported in the U.S., with Black men demonstrating a disproportionately higher burden of disease compared to White men. Though some studies conducted in equal access health care settings have revealed equivalent PCa characteristics at diagnosis and comparable PCa outcomes for White and Black men. Identification of early predictors of prostate disease aggressiveness is essential to avoid over-treatment of clinically favorably disease that is unlikely to progress. This study examines the independent and joint roles of biological and social determinants of health (SDOHs) in predicting prostate disease aggressiveness in a racially diverse cohort of men undergoing biopsy for suspicion of PCa. Methodology: A retrospective cohort study was conducted at the University Hospitals Seidman Cancer Center in Cleveland, Ohio for the period January 1, 2005-May 2022. A retrospective chart review was conducted to identify eligible men, including White and Black men undergoing transrectal ultrasound-guided biopsy whose biopsy results included the following 3 groups: (i) negative biopsy with a history of 1+ negative biopsy (-ies) and no history of prostate cancer; (ii) biopsy-detected PCa of Gleason sum 6; and (iii) biopsy-detected PCa with metastases at initial cancer detection. Detailed clinical and biological specimen data were abstracted during retrospective chart review, and quantitative proteomics analysis of biopsy tissues is ongoing, using mass spectrometry, at the Pacific Northwest National Laboratory (PNNL). Multi-level modeling will be conducted to predict prostate disease aggressiveness as a function of protein biomarker candidates in combination with census block group-level SDOHs. Results: This study has achieved its initial goal of assembling a study cohort of 300 eligible men with available biopsy tissue, necessary clinical information, and full street address for assigning census regions. To date, proteomics data have been generated on the first 60 men (“Discovery cohort”) and SDOHs metrics have been linked to the first 180 men. Proteomic profiles and SDOH data will be examined jointly with SDOHs to predict patient clinical phenotype (i.e., metastatic, biopsy Gleason 6, biopsy negative). Conclusions: Identifying new markers of cancer aggressiveness within and across race has the potential to tailor disease management, and identify patients who are likely to benefit from earlier, timely treatment interventions, which will ultimately improve prostate cancer outcomes and quality of life. Predictive modeling that jointly considers biological determinants of cancer disparities in conjunction with neighborhood-level social factors have the potential to elucidate who can be safely spared repeat biopsies, as well as how to optimize cancer care. Citation Format: Jennifer Cullen, Tao Liu, Karin Rodland, Ranjini Ghosh, Anood Alfamy, Julia Payne, Kirsten Eom, Sweta Balaji, Nicole Diaz, Holly Hartman, Annie Liang Zhang, Daniel Spratt, Jonathan Shoag, Erika Trapl, Lee Ponsky, Gregory MacLennan. Biological and neighborhood-level social determinants of prostate disease aggressiveness among Black and White men undergoing prostate biopsy [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C088.

The impact of social and environmental factors on cancer biology in Black Americans.

Low socioeconomic status (SES) is associated with early onset of chronic diseases and reduced life expectancy. The involvement of neighborhood-level factors in defining cancer risk and outcomes for marginalized communities has been an active area of research for decades. Yet, the biological processes that underlie the impact of SES on chronic health conditions, such as cancer, remain poorly understood. To date, limited studies have shown that chronic life stress is more prevalent in low SES communities and can affect important molecular processes implicated in tumor biology such as DNA methylation, inflammation, and immune response. Further efforts to elucidate how neighborhood-level factors function physiologically to worsen cancer outcomes for disadvantaged communities are underway. This review provides an overview of the current literature on how socioenvironmental factors within neighborhoods contribute to more aggressive tumor biology, specifically in Black U.S. women and men, including the impact of environmental pollutants, neighborhood deprivation, social isolation, structural racism, and discrimination. We also summarize commonly used methods to measure deprivation, discrimination, and structural racism at the neighborhood-level in cancer health disparities research. Finally, we offer recommendations to adopt a multi-faceted intersectional approach to reduce cancer health disparities and develop effective interventions to promote health equity.

Predictors of consenting to participate in a clinical trial among urban cancer patients

BackgroundPatient participation in clinical trials is influenced by demographic and other individual level characteristics. However, there is less research on the role of geography and neighborhood-level factors on clinical trial participation. This study identifies the demographic, clinical, geographic, and neighborhood predictors of consenting to a clinical trial among cancer patients at a large, urban, NCI-designated cancer center in the Mid-Atlantic region. MethodsWe used demographic and clinical data from patients diagnosed with cancer between 2015 and 2017. We geocoded patient addresses and calculated driving distance to the cancer center. Additionally, we linked patient data to neighborhood-level educational attainment, social capital and cancer prevalence. Finally, we used generalized linear mixed-effects conditional logistic regression to identify individual and neighborhood-level predictors of consenting to a clinical trial. ResultsPatients with higher odds of consenting to trials were: Non-Hispanic White, aged 50–69, diagnosed with breast, GI, head/neck, hematologic, or certain solid tumor cancers, those with cancers at regional stage, never/former tobacco users, and those with the highest neighborhood social capital index. Patients who lived further from the cancer center had higher odds of consenting to a trial. With every 1-km increase in residential distance, there was a 4% increase in the odds that patients would consent to a trial. Neither of the additional neighborhood-level variables predicted consenting to a clinical trial. ConclusionsThis study identifies important demographic, patient-level, and geographic factors associated with consenting to cancer clinical trials, and lays the groundwork for future research exploring the role of neighborhood-level factors in clinical trial participation.

NEIGHBORHOOD CHARACTERISTICS INFLUENCE OLDER ADULTS' HEALTH AND MENTAL HEALTH OUTCOMES

Abstract Both social and physical aspects of neighborhood characteristics are related to a wide range of health and mental health outcomes. There has been increasing evidence pointing to the link between neighborhood-level factors and health among older adults. Specifically, older adults living in disadvantaged neighborhoods with under-resourced infrastructure may experience more daily activity limitations, mental health symptoms, and increased morbidity and mortality. Positive aspects of the neighborhood, such as social cohesion, may serve as a social capital resource and protect against adverse health outcomes. On the contrary, negative aspects of the neighborhood, such as physical disorder, can be a substantial stressor leading to poor health. The neighborhood environment also disproportionally affects racial and ethnic minorities in the US. This symposium session will present four studies exploring important topics related to neighborhood factors of health among older adults. Collectively, the findings will inform neighborhood-level interventions to promote health and well-being among community-dwelling older adults. This session will start with a talk by Dr. Chan on the link between neighborhood and disability across six ethnic groups of older Asian Americans residing in New York City. Dr. Perry will present a qualitative study to explore the environmental and infrastructure challenges in the neighborhood from the perspective of older adults in Detroit. This will be followed by Dr. Jiang’s talk on the relationship between neighborhood cohesion and mortality among a sample of older Chinese in Chicago. Finally, the session will conclude with Dr. Qin’s presentation on how neighborhood characteristics affect older adults’ mental health trajectories.

Decomposing neighborhood disparities in bicycle crashes: A Gelbach decomposition analysis

Despite growing evidence showing significant spatial disparities in bicycle crash rates within a city, little research has explored their contributing factors. Focusing on Seoul, South Korea, this study examines whether differences in bicycle crash rates between neighborhoods with low and high socioeconomic status (SES) exist, and if so, which and to what extent the observable neighborhood characteristics explain them. This study adopts the Gelbach decomposition method to illuminate the sources of bicycle crash disparities between neighborhoods with different SES. Results indicate that bicycle crashes are more likely to occur in low-SES neighborhoods, regardless of injury severity. However, contrary to popular expectations, the differences in bicycle infrastructure or bicycle traffic volume between high- and low-SES neighborhoods do not significantly contribute to the gaps in bicycle crash outcomes between neighborhood types. Instead, the differences in population density and road networks based on neighborhood SES are the primary drivers of these gaps. Another notable finding is that the neighborhood-level factors included in the analysis can altogether explain less than 50% of the disparities in bicycle crashes between neighborhood types. The findings of this study provide valuable policy suggestions that help address spatial equity related to bicycle crashes.

Exploring the Association between Neighborhood Blue Space and Self-Rated Health among Elderly Adults: Evidence from Guangzhou, China

Blue spaces is associated with self-rated health (SRH), but little is known about the pathways underlying this association among Chinese urban elderly individuals. Based on neighborhood effect theory, this study examined the relationship between neighborhood blue spaces and SRH among elderly individuals using data from a questionnaire survey conducted in Guangzhou, remote sensing images, street views, and environmental information in the context of a Chinese megacity. In addition, multilevel linear model and mediating effect model empirical analyses were performed. Results showed that first, the SRH of the elderly was associated with individual- and neighborhood-level factors. Second, the multilevel mediation model revealed that multiple biopsychosocial pathways existed between neighborhood blue spaces and the SRH of the elderly, specifically, the blue space characteristics related to the SRH of the elderly via the mediating effect of stress. Third, owing to demographic characteristics and socioeconomic status, the stratified analyses also indicated a strong association between neighborhood blue spaces and SRH outcomes in the older and low-income groups. The mediating effect of stress in the age and income groups was also observed, and the mediation pathways and group differences were confirmed in the context of Chinese cities. This research enriches the empirical literature on blue spaces and elderly health from a multidisciplinary perspective and suggests the need for "healthy neighborhood" and "health-aging" planning in Chinese settings.

Individual and contextual factors associated with childhood malnutrition: a multilevel analysis of the double burden of childhood malnutrition in 27 countries

BackgroundMalnutrition is a key global health challenge and a major contributor to childhood morbidity and mortality. In recent times, the contrasting coexistence of undernutrition including micronutrient deficiencies and overweight/obesity called double burden of malnutrition has been noted at individual, household or population level and/or at different times in life. The objective of this study was to examine individual, neighborhood and country level factors that are associated with the double burden of childhood malnutrition.MethodsWe conducted multivariable multilevel logistic regression analyses on the most recent demographic and health datasets from surveys conducted between 2015 and 2020 in low- and middle-income countries. We analyzed data of 138,782 children (level 1) living in 13,788 communities (level 2) from 27 countries (level 3).ResultsThe results of our analysis show variation in childhood malnutrition across the 27 countries from as low as 6.5% in Burundi to as high as 29.5% in Timor Leste. After adjusting for all level factors, we found that those who were wasted/overweight tended to have had an episode of diarrhea or fever in the last two weeks preceding the survey, were part of a multiple birth, were being breastfed at the time of the survey and born to mothers with more than one under 5-child resident in neighborhoods with high illiteracy and unemployment rates. The intra-neighbourhood and intra-country correlation coefficients were estimated using the intercept component variance; 44.3% and 21.0% of variance in odds of double burden of childhood malnutrition are consequent upon neighborhood and country level factors respectively.ConclusionsEvidence of geographical clustering in childhood malnutrition at community and country levels was found in our study with variability due to neighborhood level factors twice that of country level factors. Therefore, strategies in tackling the double burden of malnutrition must consider these shared drivers, contextual barriers and geographical clustering effects.

Neighbourhood risk factors of recurrent tuberculosis in Cape Town: a cohort study using geocoded notification data

BackgroundIndividuals with a history of tuberculosis (TB) disease are at higher risk of developing a subsequent episode than those without. Considering the role of social and environmental factors in tuberculosis,...

Neighborhood Factors Associated with COVID-19 Cases in California.

There is a need to assess neighborhood-level factors driving COVID-19 disparities across racial and ethnic groups. To use census tract-level data to investigate neighborhood-level factors contributing to racial and ethnic group-specific COVID-19 caserates in California. Quasi-Poisson generalized linear models were used to identify neighborhood-level factors associated with COVID-19 cases. In separate sequential models for Hispanic, Black, and Asian, we characterized the associations between neighborhood factors on neighborhood COVID-19 cases. Subanalyses were conducted on neighborhoods with majority Hispanic, Black, and Asian residents to identify factors that might be unique to these neighborhoods. Geographically weighted regression using a quasi-Poisson model was conducted to identify regional differences. All COVID-19 cases and tests reported through January 31, 2021, to the California Department of Public Health. Neighborhood-level data from census tracts were obtained from American Community Survey 5-year estimates (2015-2019), United States Census (2010), and United States Department of Housing and Urban Development. The neighborhood factors associated with COVID-19 case rate were racial and ethnic composition, age, limited English proficiency (LEP), income, household size, and population density. LEP had the largest influence on the positive association between proportion of Hispanic residents and COVID-19 cases (- 2.1% change). This was also true for proportion of Asian residents (- 1.8% change), but not for the proportion of Black residents (- 0.1% change). The influence of LEP was strongest in areas of the Bay Area, Los Angeles, and San Diego. Neighborhood-level contextual drivers of COVID-19 burden differ across racial and ethnic groups.

Abstract 11843: Association of Individual- And Neighborhood-Level Factors With Racial and Ethnic Differences in Cardiovascular Health During Early Pregnancy

Introduction: Individual and neighborhood-level factors are associated with racial and ethnic differences in cardiovascular health (CVH). To identify strategies to improve maternal health, we determined the relative contributions of these factors to racial and ethnic differences in early pregnancy CVH. Methods: We included pregnant individuals from nuMoM2b, a multicenter cohort who self-identified as Hispanic, non-Hispanic Black (NHB), or non-Hispanic White (NHW). We applied a Blinder-Oaxaca decomposition to evaluate the extent to which socioeconomic and psychosocial factors, discrimination experiences, and area deprivation index statistically explain racial and ethnic differences in CVH (0-8 points, based on body mass index, blood pressure, diabetes, and smoking status) in the first trimester. This method utilizes a counterfactual approach to estimate the mean change in CVH in the Hispanic and NHB groups if covariates were set to the mean in the referent group (NHW). We calculated the percent explained by each factor by dividing the predicted mean change by the total CVH difference between groups*100. Results: Of 5,695 pregnant individuals, 12.3% were Hispanic, 8.9% NHB and 78.8% NHW. Mean CVH scores were 6.4 for Hispanic, 6.0 for NHB and 6.6 for NHB individuals. After adjusting for age and immigrant status, mean CVH scores were lower (worse) by 0.83 (95% CI 0.51-1.04) points in NHB individuals and 0.49 (95% CI 0.28-0.60) points in Hispanic individuals compared with NHW individuals. Differences in social and psychologic factors explained 87% of NHB-NHW differences and 71% of Hispanic-NHW differences in CVH scores (FIGURE) ; socioeconomic factors explained the greatest difference in CVH between groups. Conclusions: Individual- and neighborhood-level social and psychologic factors statistically explained a clinically meaningful difference in CVH among racial and ethnic groups, which may inform strategies to optimize health in pregnant individuals.

Assessing associations between residential proximity to greenspace and birth defects in the National Birth Defects Prevention Study

BackgroundResidential proximity to greenspace is associated with various health outcomes. ObjectivesWe estimated associations between maternal residential proximity to greenspace (based on an index of vegetation) and selected structural birth defects, including effect modification by neighborhood-level factors. MethodsData were from the National Birth Defects Prevention Study (1997–2011) and included 19,065 infants with at least one eligible birth defect (cases) and 8925 without birth defects (controls) from eight Centers throughout the United States. Maternal participants reported their addresses throughout pregnancy. Each address was systematically geocoded and residences around conception were linked to greenspace, US Census, and US Department of Agriculture data. Greenspace was estimated using the normalized difference vegetation index (NDVI); average maximum NDVI was estimated within 100 m and 500 m concentric buffers surrounding geocoded addresses to estimate residential NDVI. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals comparing those in the highest and lowest quartiles of residential NDVI and stratifying by rural/urban residence and neighborhood median income. ResultsAfter multivariable adjustment, for the 500 m buffer, inverse associations were observed for tetralogy of Fallot, secundum atrial septal defects, anencephaly, anotia/microtia, cleft lip ± cleft palate, transverse limb deficiency, and omphalocele, (aORs: 0.54–0.86). Results were similar for 100 m buffer analyses and similar patterns were observed for other defects, though results were not significant. Significant heterogeneity was observed after stratification by rural/urban for hypoplastic left heart, coarctation of the aorta, and cleft palate, with inverse associations only among participants residing in rural areas. Stratification by median income showed heterogeneity for atrioventricular and secundum atrial septal defects, anencephaly, and anorectal atresia, with inverse associations only among participants residing in a high-income neighborhood (aORs: 0.45–0.81). DiscussionOur results suggest that perinatal residential proximity to more greenspace may contribute to a reduced risk of certain birth defects, especially among those living in rural or high-income neighborhoods.

Do neighbourhoods influence how parents and children interact? Direct observations of parent–child interactions within a large Australian study

Neighbourhood-level factors can exert unique influence on children’s development, independent of individual parent, child, and family factors. We investigated the contribution of neighbourhood socioeconomic status (using government-generated definitions) to directly-observed parent–child interactions among 596 Australian parents and their 7–8-year-old children. Parents’ sensitive responding and parent–child positive mutuality were rated according to the SCARP:7–8 Years (Short Coding of Attachment-Related Parenting). Adjusting for individual family characteristics, multilevel modelling revealed evidence of an association between neighbourhood socioeconomic status and sensitive responding (β=.10, p=.004) but not for parent–child positive mutuality (β=−.01, p=.90). Tailored, evidence-based parenting supports according to local community need are warranted.