Neighborhood Measures Research Articles

Association of Sociodemographic Characteristics With US Medical Student Attrition

Diversity in the medical workforce is critical to improve health care access and achieve equity for resource-limited communities. Despite increased efforts to recruit diverse medical trainees, there remains a large chasm between the racial and ethnic and socioeconomic composition of the patient population and that of the physician workforce. To analyze student attrition from medical school by sociodemographic identities. This retrospective cohort study included allopathic doctor of medicine (MD)-only US medical school matriculants in academic years 2014-2015 and 2015-2016. The analysis was performed from July to September 2021. The main outcome was attrition, defined as withdrawal or dismissal from medical school for any reason. Attrition rate was explored across 3 self-reported marginalized identities: underrepresented in medicine (URiM) race and ethnicity, low income, and underresourced neighborhood status. Logistic regression was assessed for each marginalized identity and intersections across the 3 identities. Among 33 389 allopathic MD-only medical school matriculants (51.8% male), 938 (2.8%) experienced attrition from medical school within 5 years. Compared with non-Hispanic White students (423 of 18 213 [2.3%]), those without low income (593 of 25 205 [2.3%]), and those who did not grow up in an underresourced neighborhood (661 of 27 487 [2.4%]), students who were URiM (Hispanic [110 of 2096 (5.2%); adjusted odds ratio (aOR), 1.41; 95% CI, 1.13-1.77], non-Hispanic American Indian/Alaska Native/Native Hawaiian/Pacific Islander [13 of 118 (11.0%); aOR, 3.20; 95% CI, 1.76-5.80], and non-Hispanic Black/African American [120 of 2104 (5.7%); aOR, 1.41; 95% CI, 1.13-1.77]), those who had low income (345 of 8184 [4.2%]; aOR, 1.33; 95% CI, 1.15-1.54), and those from an underresourced neighborhood (277 of 5902 [4.6%]; aOR, 1.35; 95% CI, 1.16-1.58) were more likely to experience attrition from medical school. The rate of attrition from medical school was greatest among students with all 3 marginalized identities (ie, URiM, low income, and from an underresourced neighborhood), with an attrition rate 3.7 times higher than that among students who were not URiM, did not have low income, and were not from an underresourced neighborhood (7.3% [79 of 1086] vs 1.9% [397 of 20 353]; P < .001). This retrospective cohort study demonstrated a significant association of medical student attrition with individual (race and ethnicity and family income) and structural (growing up in an underresourced neighborhood) measures of marginalization. The findings highlight a need to retain students from marginalized groups in medical school.

Multiagent Self-Redundancy Identification and Tuned Greedy-Exploration.

The constant development of sensing applications using innovative and affordable measurement devices has increased the amount of data transmitted through networks, carrying in many cases, redundant information that requires more time to be analyzed or larger storage centers. This redundancy is mainly present because the network nodes do not recognize environmental variations requiring exploration, which causes a repetitive data collection in a set of limited locations. In this work, we propose a multiagent learning framework that uses the Gaussian process regression (GPR) to allow the agents to predict the environmental behavior by means of the neighborhood measurements, and the rate distortion function to establish a border in which the environmental information is neither misunderstood nor redundant. We apply this framework to a mobile sensor network and demonstrate that the nodes can tune the parameter s of the Blahut-Arimoto algorithm in order to adjust the gathered environment information and to become more or less exploratory within a sensing area.

Disentangling social capital – Understanding the effect of bonding and bridging on urban activity participation

Social capital is a critical glue for economic and social development in urban areas. Yet, to effectively guide research and practice, there is a need for careful measurement of social capital and how it links to important aspects of urban system functions. This study is aimed at examining the multi-dimensional nature of social capital and the relationship between these dimensions and travel behavior. Prior research has shown connections between stand-alone social capital concepts, such as resources gathered via social networks, with specific aspects of travel behavior. In this work, we expand the definition of social capital to cover separate dimensions, modeled via multiple indicators. Specifically, we make use of over 1400 observations from the Pew Internet Networks and Community Survey dataset to build a Structural Equation Model dividing social capital into two latent dimensions: bonding and bridging to examine the relationship of both these dimensions with discretionary urban activity participation diversity and frequency. Moreover, broader measures of neighborhood and community engagement are included in the model to explain how such engagement can help with the accumulation of social capital. Our results indicate a positive but differential relationship between both social capital dimensions and activity participation. Further, the results also suggest an absence of correlation between bonding and bridging capital, strengthening the hypothesis that social capital is multi-dimensional. In terms of explaining the social capital accrual, we find that while community engagement is positively correlated to bridging capital, no evidence was found for a relationship between community engagement and bonding capital. Further, neighborhood engagement was not found to be associated with any of the social capital dimensions. This suggests that individuals predominantly rely on close-knit and stronger relationships for social/emotional support, while instead, community engagement significantly helps in the accumulation of bridging capital. The result from the study can be used by policy makers to improve transportation planning, management, and community well-being.

Individual, interpersonal, and neighborhood measures associated with opioid use stigma: Evidence from a nationally representative survey

Despite growing awareness of opioid use disorder (OUD), fatal overdoses and downstream health conditions (e.g., hepatitis C and HIV) continue to rise in some populations. Various interrelated structural forces, together with social and economic determinants, contribute to this ongoing crisis; among these, access to medications for opioid use disorder (MOUD) and stigma towards people with OUD remain understudied. We combined data on methadone, buprenorphine, and naltrexone providers from SAMHSA's 2019 directory, additional naltrexone providers from Vivitrol's location finder service, with a nationally representative survey called “The AmeriSpeak survey on stigma toward people with OUD.” Integrating the social-ecological framework, we focus on individual characteristics, personal and family members' experience with OUD, and spatial access to MOUD at the community level. We use nationally representative survey data from 3008 respondents who completed their survey in 2020. Recognizing that stigma is a multifaceted construct, we also examine how the process varies for different types of stigma, specifically perceived dangerousness and untrustworthiness, as well as social distancing measures under different scenarios. We found a significant association between stigma and spatial access to MOUD — more resources are related to weaker stigma. Respondents had a stronger stigma towards people experiencing current OUD (versus past OUD), and they were more concerned about OUD if the person would marry into their family (versus being their coworkers). Additionally, respondents' age, sex, education, and personal experience with OUD were also associated with their stigma, and the association can vary depending on the specific type of stigma. Overall, stigma towards people with OUD was associated with both personal experiences and environmental measures.

EDITORIAL COMMENT

Using a measure of neighborhood “disadvantage” known as the Area Deprivation Index (ADI), Knorr et al report higher rates of post radical cystectomy morbidity/mortality among patients that live in the most socioeconomically disadvantaged areas. Several prior studies have evaluated the impact socioeconomic position (SEP) has on post-cystectomy outcomes. However, this study is unique in that the exposure tested extends beyond solitary measures of socioeconomic position (such as income or education) to a validated composite measure that also provides a more nuanced understanding of neighborhood dwelling absent in prior studies.

Child Opportunity Index and Changes in Pediatric Acute Care Utilization in the COVID-19 Pandemic.

Pediatric acute care utilization decreased dramatically during the coronavirus disease 2019 (COVID-19) pandemic. This study examined the association between the Child Opportunity Index (COI), a multidimensional neighborhood measure of childhood opportunity, and changes in acute care utilization at US pediatric hospitals during the COVID-19 pandemic compared with the previous 3 years. This observational study used administrative data across 41 US-based pediatric hospitals. Children aged 0 to 17 years with emergency department (ED) encounters during the study period were included. The COVID-19 pandemic time period (March 15, 2020-March 14, 2021) was the primary exposure. The primary outcome was the relative volume drop in ED encounters and observation/inpatient admissions through the ED by COI quintile. Of 12 138 750 encounters, 3 705 320 (30.5%) were among the very low COI quintile. Overall, there was a 46.8% relative volume reduction in the pandemic period compared with the prepandmic period. This drop in volume occurred disproportionately among the very low COI quintile (51.1%) compared with the very high COI quintile (42.8%). The majority of clinical diagnosis groups demonstrated larger relative volume drops among the very low COI quintile. Acute care utilization decreased the most among children from very low COI neighborhoods, narrowing previously described acute care utilization disparities. Additional study of patient perspectives on health care needs and access during this period is required to understand these changes.

The influence of structural racism, pandemic stress, and SARS-CoV-2 infection during pregnancy with adverse birth outcomes

BACKGROUNDStructural racism and pandemic-related stress from the COVID-19 pandemic may increase the risk of adverse birth outcomes.OBJECTIVEOur objective was to examine associations between neighborhood measures of structural racism and pandemic stress with 3 outcomes: SARS-CoV-2 infection, preterm birth, and delivering small-for-gestational-age newborns. Our secondary objective was to investigate the joint association of SARS-CoV-2 infection during pregnancy and neighborhood measures with preterm birth and delivering small-for-gestational-age newborns.STUDY DESIGNWe analyzed data of 967 patients from a prospective cohort of pregnant persons in New York City, comprising 367 White (38%), 169 Black (17%), 293 Latina (30%), and 87 Asian persons (9%), 41 persons of other race or ethnicity (4%), and 10 of unknown race or ethnicity (1%). We evaluated structural racism (social/built structural disadvantage, racial-economic segregation) and pandemic-related stress (community COVID-19 mortality, community unemployment rate increase) in quartiles by zone improvement plan code. SARS-CoV-2 serologic enzyme-linked immunosorbent assay was performed on blood samples from pregnant persons. We obtained data on preterm birth and small-for-gestational-age newborns from an electronic medical record database. We used log-binomial regression with robust standard error for clustering by zone improvement plan code to estimate associations of each neighborhood measure separately with 3 outcomes: SARS-CoV-2 infection, preterm birth, and small-for-gestational-age newborns. Covariates included maternal age, parity, insurance status, and body mass index. Models with preterm birth and small-for-gestational-age newborns as the dependent variables additionally adjusted for SARS-CoV-2 infection.RESULTSA total of 193 (20%) persons were SARS-CoV-2–seropositive, and the overall risks of preterm birth and small-for-gestational-age newborns were 8.4% and 9.8%, respectively. Among birthing persons in neighborhoods in the highest quartile of structural disadvantage (n=190), 94% were non-White, 50% had public insurance, 41% were obese, 32% were seropositive, 11% delivered preterm, and 12% delivered a small-for-gestational-age infant. Among birthing persons in neighborhoods in the lowest quartile of structural disadvantage (n=360), 39% were non-White, 17% had public insurance, 15% were obese, 9% were seropositive, 6% delivered preterm, and 10% delivered a small-for-gestational-age infant. In adjusted analyses, structural racism measures and community unemployment were associated with both SARS-CoV-2 infection and preterm birth, but not small-for-gestational-age infants. High vs low structural disadvantage was associated with an adjusted relative risk of 2.6 for infection (95% confidence interval, 1.7–3.9) and 1.7 for preterm birth (95% confidence interval, 1.0–2.9); high vs low racial-economic segregation was associated with adjusted relative risk of 1.9 (95% confidence interval, 1.3–2.8) for infection and 2.0 (95% confidence interval, 1.3–3.2) for preterm birth; high vs low community unemployment increase was associated with adjusted relative risk of 1.7 (95% confidence interval, 1.2–1.5) for infection and 1.6 (95% confidence interval, 1.0–2.8) for preterm birth. COVID-19 mortality rate was associated with SARS-CoV-2 infection but not preterm birth or small-for-gestational-age infants. SARS-CoV-2 infection was not independently associated with birth outcomes. We found no interaction between SARS-CoV-2 infection and neighborhood measures on preterm birth or small-for-gestational-age infants.CONCLUSIONNeighborhood measures of structural racism were associated with both SARS-CoV-2 infection and preterm birth, but these associations were independent and did not have a synergistic effect. Community unemployment rate increases were also associated with an increased risk of preterm birth independently of SARS-CoV-2 infection. Mitigating these factors might reduce the impact of the pandemic on pregnant people.

Accounting for Social Risk Does not Eliminate Race/Ethnic Disparities in COVID-19 Infection Among Insured Adults: a Cohort Study.

BackgroundCommunities of color have been disproportionately impacted by the COVID-19 epidemic in the USA.ObjectivesTo examine the relationship of self-reported social health needs with SARS-COV-2 infection by race/ethnicity among insured adults with access to high-quality health care.Design and ParticipantsA prospective cohort study of 26,741 adult Kaiser Permanente Northern California members insured by Medicaid and 58,802 Kaiser Permanente Colorado members insured by Medicare Advantage who completed social risk assessments prior to the onset of the COVID-19 pandemic.Main MeasuresWe examined the independent relationships of demographic, medical, and social factors on SARS-COV-2 testing and positivity between March 1, 2020, and November 30, 2020, by race/ethnicity.Key ResultsFindings were similar in the two cohorts, with Latino (16–18%), Asian (11–14%), and Black (11–12%) members having the highest prevalence of SARS-COV-2 infection (ORs adjusted for age, gender, and use of interpreter ranging from 1.68 to 2.23 compared to White member [7–8%], p < 0.001). Further adjustment for medical comorbidity (e.g., obesity, diabetes, chronic lung disease); neighborhood measures; and self-reported social risk factors (e.g., trouble paying for basics, food insecurity, housing concerns, transportation barriers) did not appreciably change these results.ConclusionsCompared to non-Latino White members, members of other race/ethnic groups had higher positivity rates that were only minimally reduced after controlling for medical and neighborhood conditions and self-reported social risk factors. These findings suggest that traditional infection transmission factors such as essential work roles and household size that have disproportionate representation among communities of color may be important contributors to SARS-COV-2 infection among insured adults.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11606-021-07261-y.

Structural racism is a mediator of disparities in acute myeloid leukemia outcomes

AbstractNon-Hispanic Black (NHB) and Hispanic patients with acute myeloid leukemia (AML) have higher mortality rates than non-Hispanic White (NHW) patients despite more favorable genetics and younger age. A discrete survival analysis was performed on 822 adult patients with AML from 6 urban cancer centers and revealed inferior survival among NHB (hazard ratio [HR] = 1.59; 95% confidence interval [CI]: 1.15, 2.22) and Hispanic (HR = 1.25; 95% CI: 0.88, 1.79) patients compared with NHW patients. A multilevel analysis of disparities was then conducted to investigate the contribution of neighborhood measures of structural racism on racial/ethnic differences in survival. Census tract disadvantage and affluence scores were individually calculated. Mediation analysis of hazard of leukemia death between groups was examined across 6 composite variables: structural racism (census tract disadvantage, affluence, and segregation), tumor biology (European Leukemia Network risk and secondary leukemia), health care access (insurance and clinical trial enrollment), comorbidities, treatment patterns (induction intensity and transplant utilization), and intensive care unit (ICU) admission during induction chemotherapy. Strikingly, census tract measures accounted for nearly all of the NHB-NHW and Hispanic-NHW disparity in leukemia death. Treatment patterns, including induction intensity and allogeneic transplant, and treatment complications, as assessed by ICU admission during induction chemotherapy, were additional mediators of survival disparities in AML. This is the first study to formally test mediators for observed disparities in AML survival and highlights the need to investigate the mechanisms by which structural racism interacts with known prognostic and treatment factors to influence leukemia outcomes.

Assessing School Communities Using Google Street View: A Virtual Systematic Social Observation Approach

Little research in education has focused on school neighborhoods. We employ a novel systematic social observation tool—the internet-based School Neighborhood Assessment Protocol (iSNAP)—within Google Street View to quantify the physical characteristics of 291 preschool communities in nine U.S. cities. We find low to moderate correlations (r = −.03 to −.57) between iSNAP subscales and Census tract poverty, density, and crime, suggesting that the characteristics captured by the iSNAP are related to, yet ultimately distinct from, existing neighborhood structural measures. We find few positive associations between iSNAP community characteristics and 1,230 low-income preschoolers’ end-of-year outcomes. Specifically, resources for outdoor play (e.g., playgrounds, open fields) on school grounds predicted stronger child self-regulation skills, whereas global ratings of safety and care for both the school grounds and surrounding neighborhood predicted stronger approaches to learning skills. Indicators of physical order were not associated with child outcomes.

At-Homeness Influences the Cognition of Multimorbid Older Adults: Longitudinal Path Analysis Through Loneliness

Approximately two-thirds of older adults’ experience multimorbidity in North America. Challenges of symptoms management and reduced mobility often coincide with late-life depression which is associated with a 2 to 5-fold increased dementia risk. Loneliness and depression are connected in the prodromal phases. We examine the effects of physical environment (e.g., housing and neighborhood factors) and social environment (e.g., social support) on loneliness, depression, and cognition using path analysis, controlling for baseline. Data(n=15,087) was drawn from the Canadian Longitudinal Study on Aging. Measures of housing, neighborhood and life satisfaction were used to construct an index of “at-homeness” based on theory. We found good model fit (TLI=.989; CFI=.999; RMSEA=.026; SRMR=.006). At-homeness(B=-.20, p<.001) rivaled the effect of social environment(B=-.19, p<.001) on loneliness. Together, physical environment and loneliness had as much effect on cognition as depression. If causality is supported, modifying older adults’ satisfaction with their home environment may reduce loneliness and cognitive decline.

At‐homeness: A novel psycho‐socio‐environmental construct for an eMental Health controlled trial to prevent loneliness and cognitive decline among older adults with multimorbidity

AbstractBackgroundApproximately two‐thirds of older adults’ experience multimorbidity in Canada and the US. Challenges of symptoms management and reduced mobility often coincide with late‐life depression which is associated with a 2 to 5‐fold increased dementia risk. Loneliness and depression are connected in the prodromal phases. Loneliness is distinct from social isolation and has direct neurological impact on the brain (Cacioppo et al., 2014). Yet, recent umbrella review of RCTs on loneliness reported “limited effects” (Jarvis et al., 2020). Following recommendations for theory‐based non‐pharmacological interventions (Sikkes et al., 2020), this paper develops a novel construct as an antidote to loneliness for eMental Health intervention among MMOA.MethodFindings from three sequential studies were combined to examine the preventive potential of a measurable construct. (1) Systematic review identified 28 studies on the experiences people living with dementia in the community. Comparative synthesis was conducted ethnographic data (e.g., in‐depth interviews) since Chaudhury (2001). (2) Primary qualitative data were extracted to generate items for a preliminary scale. Factor analysis was conducted to examine construct validity. (3) An index was constructed using comprehensive data from the Canadian Longitudinal Study on Aging (CLSA). Path analysis was conducted to examine direct and indirect effects on loneliness, depression, and cognition, controlling for baseline. Social environment (e.g., social support) was included for comparison.Result(1) Understanding behavioral symptoms as non‐verbal expressions and employing Deweyan person‐place integration, at‐homeness emerged as a psychological construct that could address prodromal loneliness. (2) Factor analysis (n=212) reduced 28 items to 20 items (α=.920) At‐homeness includes three factors: identity‐stability(α=.886), social experiences (α=.887), self‐expression (α=.767)(SRMR=.075). Convergent validity with neighborhood factors was found (B=.43, p&lt;.001). (3) Measures of housing, neighborhood, and life satisfaction were used. Path analysis (n=15,087) showed good model fit indexes (TLI=.989; CFI=.999; RMSEA=.026; SRMR=.006). At‐homeness (B=‐.20, p&lt;.001) rivals the effect of social environment (B=‐.19, p&lt;.001) on loneliness. Structural equation modelling showed that, together, at‐homeness and loneliness have as much effect on cognition as depression.ConclusionAt‐homeness is a promising novel psycho‐socio‐environmental construct to reduce loneliness and cognitive decline among MMOA. Its factors may be influenced through customized activity suggestions. A pilot study is underway.

Some New Covering-Based Multigranulation Fuzzy Rough Sets and Corresponding Application in Multicriteria Decision Making

Multigranulation rough set theory is an important tool to deal with the problem of multicriteria information system. The notion of fuzzy β -neighborhood has been used to construct some covering-based multigranulation fuzzy rough set (CMFRS) models through multigranulation fuzzy measure. But the β -neighborhood has not been used in these models, which can be seen as the bridge of fuzzy covering-based rough sets and covering-based rough sets. In this paper, the new concept of multigranulation fuzzy neighborhood measure and some types of covering-based multigranulation fuzzy rough set (CMFRS) models based on it are proposed. They can be seen as the further combination of fuzzy sets: covering-based rough sets and multigranulation rough sets. Moreover, they are used to solve the problem of multicriteria decision making. Firstly, the definition of multigranulation fuzzy neighborhood measure is given based on the concept of β -neighborhood. Moreover, four types of CMFRS models are constructed, as well as their characteristics and relationships. Then, novel matrix representations of them are investigated, which can satisfy the need of knowledge discovery from large-scale covering information systems. The matrix representations can be more easily implemented than set representations by computers. Finally, we apply them to manage the problem of multicriteria group decision making (MCGDM) and compare them with other methods.

Residential proximity to greenness and adverse birth outcomes in urban areas: Findings from a national Canadian population-based study

BackgroundOver the last decade, several studies have reported that residential proximity to vegetation, or ‘greenness’, is associated with improved birth outcomes, including for term birth weight (TBW), preterm birth (PTB), and small for gestational age (SGA). However, there remain several uncertainties about these possible benefits including the role of air pollution, and the extent to they are influenced socioeconomic status. MethodsWe addressed these gaps using a national population-based study of 2.2 million singleton live births in Canadian metropolitan areas between 1999 and 2008. Exposures to greenness, fine particulate matter (PM2.5), and nitrogen dioxide (NO2) were assigned to infants using the postal code of their mother's residence at the time of birth. The Normalized Difference Vegetation Index (NDVI) was used to characterize greenness, while estimates of ambient PM2.5 and NO2 were estimated using remote sensing, and a national land-use regression surface, respectively. Multivariable regression analysis was performed to describe associations between residential greenness and the birth outcomes. Stratified analyses explored whether these associations were modified by neighbourhood measures of socioeconomic status. ResultsMothers who lived in greener areas had a lower risk of low TBW, PTB, and SGA babies. These associations persisted after adjustment for ambient NO2 and PM2.5. Specifically, in fully adjusted models, an interquartile range (IQR = 0.16) increase in the NDVI within a residential buffer of 250 m yielded odds ratios of 0.93 (95% confidence interval (CI): 0.92, 0.94), 0.94 (95% CI: 0.92, 0.95), and 0.94 (95% CI: 0.93, 0.95) for the outcomes of PTB, low TBW, and SGA, respectively. Similarly, an IQR increase in greenness was associated with a 16.3 g (95% CI: 15.3, 17.4) increase in TBW. We found inverse associations between greenness and the occurrence of adverse birth outcomes regardless of the socioeconomic status of the neighbourhood. InterpretationOur findings support the hypothesis that residential greenness contributes to healthier pregnancies, that these associations are independent from exposure to air pollution. , and that proximity to greenness benefits all mothers regardless of socioeconomic status.

Environmental Heat Exposure Among Pet Dogs in Rural and Urban Settings in the Southern United States.

With advancing global climate change, heat-related illnesses and injuries are anticipated to become more prevalent for humans and other species. Canine hyperthermia is already considered an important seasonal emergency. Studies have been performed on the risk factors for heat stroke in canine athletes and military working dogs; however there is limited knowledge on environmental risk factors for the average pet dog. This observational study explores variation in individually experienced environmental temperatures of pet dogs (N = 30) in rural and urban environments in central Alabama. Temperature data from dogs and their owners was collected using wearable personal thermometers. Demographic data on the dogs was collected using a brief survey instrument completed by their owners. Dogs included in the study varied in signalment, activity level, and home environment. Linear mixed effects regression models were used to analyze repeated measure temperature and heat index values from canine thermometers to explore the effect of environmental factors on the overall heat exposure risk of canine pets. Specifically, the heat exposures of dogs were modeled considering their owner's experienced temperatures, as well as neighborhood and local weather station measurements, to identify factors that contribute to the heat exposure of individual dogs, and therefore potentially contribute to heat stress in the average pet dog. Results show hourly averaged temperatures for dogs followed a diurnal pattern consistent with both owner and ambient temperature measurements, except for indoor dogs whose recordings remained stable throughout the day. Heat index calculations showed that owners, in general, had more hours categorized into the National Weather Station safe category compared to their dogs, and that indoor dogs had a greater proportion of hours categorized as safe compared to outdoor dogs. Our results suggest that the risk of the average pet dog to high environmental heat exposure may be greater than traditional measures indicate, emphasizing that more localized considerations of temperature are important when assessing a dog's environmental risk for heat-related injury or illness.

Impact of paternal education on epigenetic ageing in adolescence and mid-adulthood: a multi-cohort study in the USA and Mexico.

Both parental and neighbourhood socio-economic status (SES) are linked to poorer health independently of personal SES measures, but the biological mechanisms are unclear. Our objective was to examine these influences via epigenetic age acceleration (EAA)-the discrepancy between chronological and epigenetic ages. We examined three USA-based [Coronary Artery Risk Disease in Adults (CARDIA) study, Fragile Families and Child Wellbeing Study (FFCWS) and Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS)] and one Mexico-based (Project Viva) cohort. DNA methylation was measured using Illumina arrays, personal/parental SES by questionnaire and neighbourhood disadvantage from geocoded address. In CARDIA, we examined the most strongly associated personal, parental and neighbourhood SES measures with EAA (Hannum's method) at study years 15 and 20 separately and combined using a generalized estimating equation (GEE) and compared with other EAA measures (Horvath's EAA, PhenoAge and GrimAge calculators, and DunedinPoAm). EAA was associated with paternal education in CARDIA [GEEs: βsome college = -1.01 years (-1.91, -0.11) and β<high school = 1.05 (0.09, 2.01) vs college graduates] and FFCWS [GEEs: β<high school = 0.62 (0.00, 1.24)]. We found stronger associations for some paternal education categories among White adults (for GEE, βsome college = -1.39 (-2.41, -0.38)], men (βsome college = -1.76 (-3.16, -0.35)] and women [β<high school = 1.77 (0.42, 3.11)]. These findings suggest that EAA captures epigenetic impacts of paternal education independently of personal SES later in life. Longitudinal studies should explore these associations at different life stages and link them to health outcomes. EAA could be a useful biomarker of SES-associated health and provide important insight into the pathogenesis and prevention of chronic disease.

112Neighbourhood environment and health-related quality of life, Limassol, Cyprus

Abstract Background The extent and magnitude of socio-geographical inequalities in health in Cyprus is not clear as neither “place” nor “health inequalities” feature on the public health agenda. Methods In the context of a wider Neighbourhood Environment and Health programme, the magnitude of inequality in health-related quality of life (HRQoL) among Limassol citizens was explored in a door-to-door SF-36 survey of residents aged 45-64 (N = 450, 50:50 gender quota) across 45 randomly selected neighbourhoods stratified by socio-economic disadvantage and profiled using a culturally-adapted Systematic Social Observation neighbourhood audit tool. Results The social gradient was steeper for physical than mental component scores of HRQoL irrespective of the indicator of social position. Education and income captured the gradient better in women, and occupational-based social class in men, with large effect (0.7-1 SD) on the SF-36 scale at opposite ends of the continuum. Lower HRQoL and more adverse health behaviours observed in disadvantaged neighborhoods according to census area-level measures and neighbourhood audit profiles, with generally larger differences in women. Conclusions This study profiled the variability in the urban neighbourhood environment,and documented the magnitude of social gradient in health and health-related quality of life in a representative sample of late working-life population in Cyprus. Key messages Social gradient in health behaviours and quality of life in late working-life Cypriot population. Gradient apparent in both men and women across individual and neighborhood measures of social position.

A study of climatic comfort conditions in the spatial-physical patterns of tradi-tional neighborhoods’ fabric: The case of Hamadan’s old neighborhoods

Backgrounds and research goals: The unbridled expansion of cities in recent dec-ades has led to the inefficiency of large parts of the structure and spatial organiza-tion of cities and the decline in climate comfort in them. Numerous policies have been proposed in the face of the problem of declining environmental quality and especially their climatic comfort, and various programs have been implemented in this regard. Therefore, this study tries to review the theoretical foundations in this area, finally appropriate solutions for the development of neighborhoods and neigh-borhood spaces in the climate of Hamadan has been proposed.Research method: The method of this research is that at first the effective compo-nents on climatic comfort and urban form were obtained by studying and examining the views of experts. To analyze the data, the simulation method and Ecotect Auto-desk software were studied in three traditional neighborhoods of Hamadan and ac-cording to the results, the factors.Findings: The results of the research show that Kababian neighborhood in the cold seasons of the year has more conditions to enjoy the sun in the morning and even-ing, but in the two neighborhoods of Haji and Aghajani Bey in the cold seasons should make more arrangements to enjoy The amount of sunlight used. Due to the fact that the amount of shading in these two neighborhoods in this season is more than the Kababian neighborhood and special measures are needed to create climatic conditions.Discussion and conclusion: In general, and according to the findings, one of the im-portant factors in optimizing traditional neighborhoods can be the use of centrifugal patterns in creating neighborhoods can increase the level of climate comfort in neighborhoods.

Use of Geographic Information Systems to Explore Associations between Neighborhood Attributes and Mental Health Outcomes in Adults: A Systematic Review.

Background: Neighborhood attributes are increasingly recognized as factors shaping mental health in adults. Geographic information systems (GIS) offer an innovative approach for quantifying neighborhood attributes and studying their influence on mental health outcomes. Our aim was to describe GIS applications used in neighborhood-related mental health research and how neighborhood attributes are related to depressive symptoms or psychological distress in community-residing adults. Methods: We conducted a systematic review of studies published in English that included GIS techniques and a validated questionnaire of depressive symptoms or psychological distress. Medline, PsycInfo, Embase, Scopus, CINAHL, GEOBASE, and Compedex were searched to June 2020. Study quality was assessed by a modification of the Joanna Briggs Institute’s Checklist for Analytical Cross-sectional Studies. Results: Thirty-two studies met the inclusion criteria. Studies varied in definitions of neighborhood and GIS-derived measurements of neighborhood attributes. Neighborhood attributes were significantly associated with mental health outcomes, although findings were not consistent. Moderating factors (e.g., gender, living conditions) significantly influenced depressive symptoms or psychological distress. Conclusion: Neighborhood attributes are important factors influencing mental health in adults. Consensus may be needed on how to standardize the neighborhood unit or GIS-derived measures of neighborhoods in order to explain depression or psychological distress in diverse adult populations.

Race, Ethnicity, Neighborhood Characteristics, and In-Hospital Coronavirus Disease-2019 Mortality.

Despite many studies reporting disparities in coronavirus disease-2019 (COVID-19) incidence and outcomes in Black and Hispanic/Latino populations, mechanisms are not fully understood to inform mitigation strategies. The aim was to test whether neighborhood factors beyond individual patient-level factors are associated with in-hospital mortality from COVID-19. We hypothesized that the Area Deprivation Index (ADI), a neighborhood census-block-level composite measure, was associated with COVID-19 mortality independently of race, ethnicity, and other patient factors. Multicenter retrospective cohort study examining COVID-19 in-hospital mortality. Inclusion required hospitalization with positive SARS-CoV-2 test or COVID-19 diagnosis at three large Midwestern academic centers. The primary study outcome was COVID-19 in-hospital mortality. Patient-level predictors included age, sex, race, insurance, body mass index, comorbidities, and ventilation. Neighborhoods were examined through the national ADI neighborhood deprivation rank comparing in-hospital mortality across ADI quintiles. Analyses used multivariable logistic regression with fixed site effects. Among 5999 COVID-19 patients median age was 61 (interquartile range: 44-73), 48% were male, 30% Black, and 10.8% died. Among patients who died, 32% lived in the most disadvantaged quintile while 11% lived in the least disadvantaged quintile; 52% of Black, 24% of Hispanic/Latino, and 8.5% of White patients lived in the most disadvantaged neighborhoods.Living in the most disadvantaged neighborhood quintile predicted higher mortality (adjusted odds ratio: 1.74; 95% confidence interval: 1.13-2.67) independent of race. Age, male sex, Medicare coverage, and ventilation also predicted mortality. Neighborhood disadvantage independently predicted in-hospital COVID-19 mortality. Findings support calls to consider neighborhood measures for vaccine distribution and policies to mitigate disparities.