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Ordinary kriging, a spatial interpolation technique, is commonly used in social sciences to estimate neighborhood attributes such as physical disorder. Universal kriging, developed and used in physical sciences, extends ordinary kriging by supplementing the spatial model with additional covariates. We measured physical disorder on 1,826 sampled block faces across four U.S. cities (New York, Philadelphia, Detroit, and San Jose) using Google Street View imagery. We then compared leave-one-out cross-validation accuracy between universal and ordinary kriging and used random subsamples of our observed data to explore whether universal kriging could provide equal measurement accuracy with less spatially dense samples. Universal kriging did not always improve accuracy. However, a measure of housing vacancy did improve estimation accuracy in Philadelphia and Detroit (7.9 percent and 6.8 percent lower root mean square error, respectively) and allowed for equivalent estimation accuracy with half the sampled points in Philadelphia. Universal kriging may improve neighborhood measurement.

Background: Despite the links between neighbourhood walkability and physical activity, body size and risk of diabetes, there are few studies of neighbourhood walkability and risk of gestational diabetes (GD). Objectives: Assess whether higher neighbourhood walkability is associated with lower risk of GD in New York City (NYC). Methods: Cross‐sectional analyses of a neighbourhood walkability index (NWI) score and density of walkable destinations (DWD) and risk of GD in 109,863 births recorded in NYC in 2015. NWI and DWD were measured for the land area of 1 km radius circles around the geographic centroid of each Census block of residence. Mixed generalised linear models, with robust standard error estimation and random intercepts for NYC Community Districts, were used to estimate risk ratios for GD for increasing quartiles of each of the neighbourhood walkability measures after adjustment for the pregnant individual's age, race and ethnicity, parity, education, nativity, and marital status and the neighbourhood poverty rate. Results: Overall, 7.5% of pregnant individuals experienced GD. Risk of GD decreased across increasing quartiles of NWI, with an adjusted risk ratio of 0.81 (95% Confidence Interval (CI) 0.75, 0.87) comparing those living in areas in the 4th quartile of NWI to those in the first quartile. Similarly, for comparisons of the 4th to 1st quartile of DWD, the adjusted risk ratio for GD was 0.77 (95% CI 0.71, 0.84). Conclusions: These analyses find support for the hypothesis that higher neighbourhood walkability is associated with a lower risk of GD. The analyses provide further health related support for urban design policies to increase walkability. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BrCa) outcomes vary by social environmental factors, but the role of built‐environment factors is understudied. The authors investigated associations between environmental physical disorder—indicators of residential disrepair and disinvestment—and BrCa tumor prognostic factors (stage at diagnosis, tumor grade, triple‐negative [negative for estrogen receptor, progesterone receptor, and HER2 receptor] BrCa) and survival within a large state cancer registry linkage. Methods: Data on sociodemographic, tumor, and vital status were derived from adult women who had invasive BrCa diagnosed from 2008 to 2017 ascertained from the New Jersey State Cancer Registry. Physical disorder was assessed through virtual neighborhood audits of 23,276 locations across New Jersey, and a personalized measure for the residential address of each woman with BrCa was estimated using universal kriging. Continuous covariates were z scored (mean ± standard deviation [SD], 0 ± 1) to reduce collinearity. Logistic regression models of tumor factors and accelerated failure time models of survival time to BrCa‐specific death were built to investigate associations with physical disorder adjusted for covariates (with follow‐up through 2019). Results: There were 3637 BrCa‐specific deaths among 40,963 women with a median follow‐up of 5.3 years. In adjusted models, a 1‐SD increase in physical disorder was associated with higher odds of late‐stage BrCa (odds ratio, 1.09; 95% confidence interval, 1.02‐1.15). Physical disorder was not associated with tumor grade or triple‐negative tumors. A 1‐SD increase in physical disorder was associated with a 10.5% shorter survival time (95% confidence interval, 6.1%‐14.6%) only among women who had early stage BrCa. Conclusions: Physical disorder is associated with worse tumor prognostic factors and survival among women who have BrCa diagnosed at an early stage. Greater physical disorder—an indication of neighborhood disinvestment—is associated with higher odds of late‐stage breast cancer and shorter survival time. Physical disorder is a novel, potentially modifiable factor of the built environment associated with breast cancer outcomes and deserves further investigation. [ABSTRACT FROM AUTHOR]

Background: Mounting evidence supports associations between objective neighborhood disorder, perceived neighborhood disorder, and health, yet alternative explanations involving socioeconomic and neighborhood social cohesion have been understudied. We tested pathways between objective and perceived neighborhood disorder, perceived neighborhood social cohesion, and socioeconomic factors within a longitudinal cohort.Methods: Demographic and socioeconomic information before diagnosis was obtained at interviews conducted approximately 10 months post-diagnosis from participants in the Women's Circle of Health Follow-up Study - a cohort of breast cancer survivors self-identifying as African American or Black women (n = 310). Neighborhood perceptions were obtained during follow-up interviews conducted approximately 24 months after diagnosis. Objective neighborhood disorder was from 9 items audited across 23,276 locations using Google Street View and scored to estimate disorder values at each participant's residential address at diagnosis. Census tract socioeconomic and demographic composition covariates were from the 2010 U.S. Census and American Community Survey. Pathways to perceived neighborhood disorder were built using structural equation modelling. Model fit was assessed from the comparative fit index and root mean square error approximation and associations were reported as standardized coefficients and 95% confidence intervals.Results: Higher perceived neighborhood disorder was associated with higher objective neighborhood disorder (β = 0.20, 95% CI: 0.06, 0.33), lower neighborhood social cohesion, and lower individual-level socioeconomic factors (final model root mean square error approximation 0.043 (90% CI: 0.013, 0.068)). Perceived neighborhood social cohesion was associated with individual-level socioeconomic factors and objective neighborhood disorder (β = - 0.11, 95% CI: - 0.24, 0.02).Conclusion: Objective neighborhood disorder might be related to perceived disorder directly and indirectly through perceptions of neighborhood social cohesion. [ABSTRACT FROM AUTHOR]

Retail environments, such as healthcare locations, food stores, and recreation facilities, may be relevant to many health behaviors and outcomes. However, minimal guidance on how to collect, process, aggregate, and link these data results in inconsistent or incomplete measurement that can introduce misclassification bias and limit replication of existing research. We describe the following steps to leverage business data for longitudinal neighborhood health research: re-geolocating establishment addresses, preliminary classification using standard industrial codes, systematic checks to refine classifications, incorporation and integration of complementary data sources, documentation of a flexible hierarchical classification system and variable naming conventions, and linking to neighborhoods and participant residences. We show results of this classification from a dataset of locations (over 77 million establishment locations) across the contiguous U.S. from 1990 to 2014. By incorporating complementary data sources, through manual spot checks in Google StreetView and word and name searches, we enhanced a basic classification using only standard industrial codes. Ultimately, providing these enhanced longitudinal data and supplying detailed methods for researchers to replicate our work promotes consistency, replicability, and new opportunities in neighborhood health research. [ABSTRACT FROM AUTHOR]

Background: Virtual neighborhood audits have been used to visually assess characteristics of the built environment for health research. Few studies have investigated spatial predictive properties of audit item responses patterns, which are important for sampling efficiency and audit item selection. We investigated the spatial properties, with a focus on predictive accuracy, of 31 individual audit items related to built environment in a major Metropolitan region of the Northeast United States. Methods: Approximately 8000 Google Street View (GSV) scenes were assessed using the CANVAS virtual audit tool. Eleven trained raters audited the 360° view of each GSV scene for 10 sidewalk-, 10 intersection-, and 11 neighborhood physical disorder-related characteristics. Nested semivariograms and regression Kriging were used to investigate the presence and influence of both large- and small-spatial scale relationships as well as the role of rater variability on audit item spatial properties (measurement error, spatial autocorrelation, prediction accuracy). Receiver Operator Curve (ROC) Area Under the Curve (AUC) based on cross-validated spatial models summarized overall predictive accuracy. Correlations between predicted audit item responses and select demographic, economic, and housing characteristics were investigated. Results: Prediction accuracy was better within spatial models of all items accounting for both small-scale and large- spatial scale variation (vs large-scale only), and further improved with additional adjustment for rater in a majority of modeled items. Spatial predictive accuracy was considered 'Excellent' (0.8 ≤ ROC AUC < 0.9) for full models of all but four items. Predictive accuracy was highest and improved the most with rater adjustment for neighborhood physical disorder-related items. The largest gains in predictive accuracy comparing large- + small-scale to large-scale only models were among intersection- and sidewalk-items. Predicted responses to neighborhood physical disorder-related items correlated strongly with one another and were also strongly correlated with racial-ethnic composition, socioeconomic indicators, and residential mobility. Conclusions: Audits of sidewalk and intersection characteristics exhibit pronounced variability, requiring more spatially dense samples than neighborhood physical disorder audits do for equivalent accuracy. Incorporating rater effects into spatial models improves predictive accuracy especially among neighborhood physical disorder-related items. [ABSTRACT FROM AUTHOR]

Efforts to increase physical activity have traditionally included either individual-level interventions (e.g., educational campaigns) or neighborhood-level interventions (e.g., additional recreational facilities). Little work has addressed the interaction between spatial proximity and individual characteristics related to facility use. We aimed to better understand the synergistic impact of both physical activity environments and recreational facility membership on objectively measured physical activity. Using the New York City Physical Activity and Transit (PAT) survey (n = 644), we evaluated associations between counts of commercial physical activity facilities within 1 km of participants' home addresses with both facility membership and accelerometry-measured physical activity. Individuals living near more facilities were more likely to report membership (adjusted odds ratio for top versus bottom quartile of facility count: 3.77 (95% CI 1.54-9.20). Additionally, while amount of facilities within a neighborhood was associated with more physical activity, this association was stronger for individuals reporting gym membership. Interventions aiming to increase physical activity should consider both neighborhood amenities and potential barriers, including the financial and social barriers of membership. Evaluation of neighborhood opportunities must expand beyond physical presence to consider multiple dimensions of accessibility. [ABSTRACT FROM AUTHOR]

To examine how urban form shapes physical activity and health over time, a measure of neighborhood walkability is needed that can be linked to cohort studies with participants living across the United States (U.S.) that have been followed over the past decades. The Built Environment and Health-Neighborhood Walkability Index (BEH-NWI), a measure of neighborhood walkability that can be calculated for communities across the United States between 1990 and 2015, was conceptualized, developed, and tested using data from the New York City Tri-State Area. BEH-NWI measures were created for 1990 and 2010 using historical data on population density, street intersection density, density of rail stops, and density of pedestrian trip generating/supporting establishments. BEH-NWI scores were calculated for 1-km buffers around the 1990 residences of NYU Women's Health Study (NYUWHS) participants and NYC Department of Health and Mental Hygiene's Physical Activity and Transit (PAT) survey participants enrolled in 2011. Higher neighborhood BEH-NWI scores were significantly associated with greater self-reported walking per week (+ 0.31 MET-hours/week per unit BEH-NWI, 95% CI 0.23, 0.36) and lower body mass index (- 0.17 BMI units per unit BEH-NWI, 95% - 0.23, - 0.12) among NYUWHS participants. Higher neighborhood BEH-NWI scores were associated with significantly higher accelerometer-measured physical activity among PAT survey participants (39% more minutes of moderate-intensity equivalent activity/week across the interquartile range of BEH-NWI, 95% CI 21%, 60%). The BEH-NWI can be calculated using historical data going back to 1990, and BEH-NWI scores predict BMI, weekly walking, and physical activity in two NYC area datasets. [ABSTRACT FROM AUTHOR]

Street-level environment characteristics influence the health behaviors and safety of urban residents, and may particularly threaten health within informal communities. However, available data on how such characteristics vary within and among informal communities is limited. We sought to adapt street audit strategies designed to characterize the physical environment for use in a large informal community, Rio das Pedras (RdP) located in Rio de Janeiro, Brazil. A smartphone-based systematic observation protocol was used to gather street-level information for a high-density convenience sample of street segments (N = 630, estimated as 86% of all street segments in the community). We adapted items related to physical disorder and physical deterioration. Measures selected to illustrate the approach include the presence of the following: (1) low-hanging or tangled wires, (2) litter, (3) structural evidence of sinking, and (4) an unpleasant odor. Intercept-only spatial generalized additive models (GAM) were used to evaluate and visualize spatial variation within the RdP community. We also examined how our estimates and conclusions about spatial variation might have been affected by lower-density sampling from random subsets street observations. Random subsets were selected to determine the robustness of study results in scenarios with sparser street sampling. Selected characteristics were estimated to be present for between 18% (unpleasant odor) to 59% (low-hanging or tangled wires) of the street segments in RdP; estimates remain similar (± 6%) when relying on a random subset created to simulate lower-density spatial sampling. Spatial patterns of variation based on predicted probabilities across RdP differed by indicator. Structural sinking and low-hanging or tangled wires demonstrated relatively consistent spatial distribution patterns across full and random subset sample sizes. Smartphone-based systematic observations represent an efficient and potentially feasible approach to systematically studying neighborhood environments within informal communities. Future deployment of such tools will benefit from incorporating data collection across multiple time points to explore reliability and quantify neighborhood change. These tools can prove useful means to assess street-level exposures that can be modifiable health determinants across a wide range of informal urban settings. Findings can contribute to improved urban planning and provide useful information for identifying potential locations for neighborhood-scaled interventions that can improve living conditions for residents in Rio das Pedras. [ABSTRACT FROM AUTHOR]

The continuing obesity epidemic in the USA calls for the examination of antecedents to the well-known risk factors of physical activity and diet. The neighborhood built environment has been extensively studied in relation to obesity noting an increased risk of development and prevalence of obesity in relation to numerous built environment characteristics (lack of green spaces, higher number of fast food restaurants, low walkability indices). The neighborhood social environment, however, has been less extensively studied but is perhaps an equally important component of the neighborhood environment. The neighborhood social environment, particularly constructs of social capital, collective efficacy, and crime, is associated with obesity among both adults and children. Several studies have identified physical activity as a potential pathway of the neighborhood social environment and obesity association. Further work on social networks and norms and residential segregation, as well as the examination of dietary behaviors and mental health as potential mediating pathways, is necessary. Given the existing evidence, intervening on the neighborhood social environment may prove to be an effective target for the prevention on obesity. Intervention studies that promote healthy behaviors and prevent obesity while addressing aspects of the neighborhood social environment are necessary to better identify targets for obesity prevention. [ABSTRACT FROM AUTHOR]

Men who have sex with men (MSM) accounted for 61% of new HIV diagnoses in the United States in 2010. Recent analyses indicate that socio-structural factors are important correlates of HIV infection. NYCM2M was a cross-sectional study designed to identify neighborhood-level characteristics within the urban environment that influence sexual risk behaviors, substance use and depression among MSM living in New York City. The sample was recruited using a modified venue-based time-space sampling methodology and through select websites and mobile applications. This paper describes novel methodological approaches used to improve the quality of data collected for analysis of the impact of neighborhoods on MSM health. Previous research has focused predominately on residential neighborhoods and used pre-determined administrative boundaries (e.g., census tracts) that often do not reflect authentic and meaningful neighborhoods. This study included the definition and assessment of multiple neighborhoods of influence including where men live (home neighborhood), socialize (social neighborhood) and have sex (sexual neighborhood). Furthermore, making use of technological advances in mapping, we collected geo-points of reference for each type of neighborhood and identified and constructed self-identified neighborhood boundary definitions. Finally, this study collected both perceived neighborhood characteristics and objective neighborhood conditions to create a comprehensive, flexible and rich neighborhood-level set of covariates. This research revealed that men perceived their home, social and sexual neighborhoods in different ways. Few men (15%) had the same home, social and sexual neighborhoods; for 31%, none of the neighborhoods was the same. Of the three types of neighborhoods, the number of unique social neighborhoods was the lowest; the size of sexual neighborhoods was the smallest. The resultant dataset offers the opportunity to conduct analyses that will yield context-specific and nuanced understandings of the relations among neighborhood space, and the well-being and health of urban MSM. [ABSTRACT FROM AUTHOR]

Urban planners have suggested that built environment characteristics can support active travel (walking and cycling) and reduce sedentary behavior. This study assessed whether engagement in active travel is associated with neighborhood walkability measured for zip codes in New York City. Data were analyzed on engagement in active travel and the frequency of walking or biking ten blocks or more in the past month, from 8,064 respondents to the New York City 2003 Community Health Survey (CHS). A neighborhood walkability scale that measures: residential, intersection, and subway stop density; land use mix; and the ratio of retail building floor area to retail land area was calculated for each zip code. Data were analyzed using zero-inflated negative binomial regression incorporating survey sample weights and adjusting for respondents' sociodemographic characteristics. Overall, 44 % of respondents reported no episodes of active travel and among those who reported any episode, the mean number was 43.2 episodes per month. Comparing the 75th to the 25th percentile of zip code walkability, the odds ratio for reporting zero episodes of active travel was 0.71 (95 % CI 0.61, 0.83) and the exponentiated beta coefficient for the count of episodes of active travel was 1.13 (95 % CI 1.06, 1.21). Associations between lower walkability and reporting zero episodes of active travel were significantly stronger for non-Hispanic Whites as compared to non-Hispanic Blacks and to Hispanics and for those living in higher income zip codes. The results suggest that neighborhood walkability is associated with higher engagement in active travel. [ABSTRACT FROM AUTHOR]

Background: The WHO Multiple Exposures Multiple Effects (MEME) framework identifies community contextual variables as central to the study of childhood health. Here we identify multiple domains of neighborhood context, and key variables describing the dimensions of these domains, for use in the National Children's Study (NCS) site in Queens. We test whether the neighborhoods selected for NCS recruitment, are representative of the whole of Queens County, and whether there is sufficient variability across neighborhoods for meaningful studies of contextual variables. Methods: Nine domains (demographic, socioeconomic, households, birth rated, transit, playground/greenspace, safety and social disorder, land use, and pollution sources) and 53 indicator measures of the domains were identified. Geographic information systems were used to create community-level indicators for US Census tracts containing the 18 study neighborhoods in Queens selected for recruitment, using US Census, New York City Vital Statistics, and other sources of community-level information. Mean and inter-quartile range values for each indicator were compared for Tracts in recruitment and non-recruitment neighborhoods in Queens. Results: Across the nine domains, except in a very few instances, the NCS segment-containing tracts (N = 43) were not statistically different from those 597 populated tracts in Queens not containing portions of NCS segments; variability in most indicators was comparable in tracts containing and not containing segments. Conclusions: In a diverse urban setting, the NCS segment selection process succeeded in identifying recruitment areas that are, as a whole, representative of Queens County, for a broad range of community-level variables. [ABSTRACT FROM AUTHOR]

Preventing sedentary behavior and adiposity in childhood has become a public health priority. We examined urban social and built environment characteristics as correlates of physical activity and anthropometry among 428 preschool children from low-income families in New York City. We measured the children's height, weight, skinfold thicknesses, physical activity by accelerometer, and covariates. We geocoded home and Head Start center addresses and estimated the following for an area within 0.5 km of those two locations using a detailed geographic database: neighborhood composition, walkability, crime and traffic safety, and aesthetic characteristics. Generalized estimating equations were used to examine the associations of area characteristics with physical activity or adiposity, adjusted for characteristics of the child, mother, and home. Participants were 2-5 years old, 53% female, 83% Hispanic, and 43% either overweight or obese. Of the walkability indicators, land use mix was associated with physical activity (26 more activity counts/minute per standard deviation increase in mixed land use, p = 0.015) and subway stop density was associated with adiposity (1.2 mm smaller sums of skinfold thicknesses sum per standard deviation increase in subway stop density, p = 0.001). The pedestrian-auto injury rate, an indicator of traffic safety problems, was associated with physical activity and adiposity (16 fewer activity counts/minute, p = 0.033, and 1.0 mm greater skinfold thickness per standard deviation increase in pedestrian-auto injuries, p = 0.018). Children living in areas with more street trees were more physically active and those living in areas with more park access had smaller skinfolds. However, many of the tested associations were not statistically significant and some trends were not in the hypothesized direction. Efforts to enhance walkability, safety, and green spaces in the local environment may be relevant to physical activity and adiposity, and therefore to the health of preschool-aged children from low-income families. [ABSTRACT FROM AUTHOR]

With increasing concern about rising rates of obesity, public health researchers have begun to examine the availability of parks and other spaces for physical activity, particularly in cities, to assess whether access to parks reduces the risk of obesity. Much of the research in this field has shown that proximity to parks may support increased physical activity in urban environments; however, as yet, there has been limited consideration of environmental impediments or disamenities that might influence individuals' perceptions or usage of public recreation opportunities. Prior research suggests that neighborhood disamenities, for instance crime, pedestrian safety, and noxious land uses, might dissuade people from using parks or recreational facilities and vary by neighborhood composition. Motivated by such research, this study estimates the relationship between neighborhood compositional characteristics and measures of park facilities, controlling for variation in neighborhood disamenities, using geographic information systems (GIS) data for New York City parks and employing both kernel density estimation and distance measures. The central finding is that attention to neighborhood disamenities can appreciably alter the relationship between neighborhood composition and spatial access to parks. Policy efforts to enhance the recreational opportunities in urban areas should expand beyond a focus on availability to consider also the hazards and disincentives that may influence park usage. [ABSTRACT FROM AUTHOR]

Background: Research indicates that neighborhood environment characteristics such as physical disorder influence health and health behavior. In-person audit of neighborhood environments is costly and time-consuming. Google Street View may allow auditing of neighborhood environments more easily and at lower cost, but little is known about the feasibility of such data collection. Purpose: To assess the feasibility of using Google Street View to audit neighborhood environments. Methods: This study compared neighborhood measurements coded in 2008 using Street View with neighborhood audit data collected in 2007. The sample included 37 block faces in high-walkability neighborhoods in New York City. Field audit and Street View data were collected for 143 items associated with seven neighborhood environment constructions: aesthetics, physical disorder, pedestrian safety, motorized traffic and parking, infrastructure for active travel, sidewalk amenities, and social and commercial activity. To measure concordance between field audit and Street View data, percentage agreement was used for categoric measures and Spearman rank-order correlations were used for continuous measures. Results: The analyses, conducted in 2009, found high levels of concordance (≥80% agreement or ≥0.60 Spearman rank-order correlation) for 54.3% of the items. Measures of pedestrian safety, motorized traffic and parking, and infrastructure for active travel had relatively high levels of concordance, whereas measures of physical disorder had low levels. Features that are small or that typically exhibit temporal variability had lower levels of concordance. Conclusions: This exploratory study indicates that Google Street View can be used to audit neighborhood environments. [ABSTRACT FROM AUTHOR]

Objective. To characterize the influence of the residential neighborhood of older adults on the prevalence of disability. Methods. We combined Census data on disability in older adults living in New York City with environmental information from a comprehensive geospatial database. We used factor analysis to derive dimensions of compositional and physical neighborhood characteristics and linear regression to model their association with levels of disability. Measures of neighborhood collective efficacy were added to these models to explore the impact of the social environment. Results. Low neighborhood socioeconomic status, residential instability, living in areas with low proportions of foreign born and high proportions of Black residents, and negative street characteristics were associated with higher prevalence of both "physical" disability and "going outside the home" disability. High crime levels were additionally associated with physical disability, although this relationship disappeared when misdemeanor arrests were removed from the crime variable. Low levels of collective efficacy were associated with more going-outside-the-home disability, with racial/ethnic composition dropping out of this model to be replaced by an interaction term. Conclusion. The urban environment may have a substantial impact on whether an older adult with a given level of functional impairment is able to age actively and remain independent. [ABSTRACT FROM AUTHOR]

Background: Asthma prevalence varies widely among neighborhoods within New York City. Exposure to mouse and cockroach allergens has been suggested as a cause. Objective: To test the hypotheses that children living in high asthma prevalence neighborhoods (HAPNs) would have higher concentrations of cockroach and mouse allergens in their homes than children in low asthma prevalence neighborhoods (LAPNs), and that these exposures would be related to sensitization and asthma. Methods: In the New York City Neighborhood Asthma and Allergy Study, a case-control study of asthma, children 7 to 8 years old from HAPNs (n = 120) and LAPNs (n = 119) were recruited through the same middle-income health insurance plan. Children were classified as asthma cases (n = 128) or controls without asthma (n = 111) on the basis of reported symptoms or medication use. Allergens were measured in bed dust. Results: HAPN homes had higher Bla g 2 (P = .001), Mus m 1 (P = .003), and Fel d 1 (P = .003) and lower Der f 1 (P = .001) than LAPN homes. Sensitization to indoor allergens was associated with asthma, but relevant allergens differed between LAPNs and HAPNs. Sensitization to cockroach was more common among HAPN than LAPN children (23.7% vs 10.8%; P = .011). Increasing allergen exposure was associated with increased probability of sensitization (IgE) to cockroach (P < .001), dust mite (P = .009), and cat (P = .001), but not mouse (P = .58) or dog (P = .85). Conclusion: These findings further demonstrate the relevance of exposure and sensitization to cockroach and mouse in an urban community and suggest that cockroach allergen exposure could contribute to the higher asthma prevalence observed in some compared with other New York City neighborhoods. [ABSTRACT FROM AUTHOR]

Objectives: Neighborhood poverty, as a predictor of cancer treatment and outcomes, is increasingly being examined within gynecologic oncology literature. The Area Deprivation Index (ADI), a novel census block group marker for socioeconomic inequity, ranks neighborhoods against one another and provides a deeper insight into how place affects health. Our objective was to determine the association among area deprivation index, treatment, and survival for people with uterine cancer. Methods: Patients with uterine cancer diagnosed between 2004 and 2017 were extracted from the New York State Cancer Registry. This was linked with their cancer characteristics within New York State and City Vital Statistics, as well as admission-specific hospital and surgeon level factors from the New York Statewide Planning And Research Cooperative System (SPARCS). The address at the time of diagnosis and first admission was extracted and used to link to the ADI based on the 2015 census block groups. ADI rank at the state level was grouped by quintile from most affluent to most vulnerable. Affluent neighborhoods were defined as the wealthiest 20% in New York State. Vulnerable neighborhoods were defined as the poorest 20% in the state. Quality metrics were developed based on evidence-based consensus guidelines. Descriptive statistics were calculated. Mantel-Haenszel Chi-square tests and log-linear regression models were performed. QGIS software was used to map patient density across the state (Figure). Results: A total of 46,810 patients with uterine cancer were identified over the study period. Patients were equally distributed by neighborhood status, with 17.8% of patients living in affluent neighborhoods and 18.0% living in vulnerable neighborhoods. Non-Hispanic Black patients comprised 14.2% of the cohort, Non-Hispanic White patients 71.8%, and Hispanic patients 9.3%. Overall, endometrioid histology comprised 65.1%, serous histology 8.7%, and sarcoma 3.6% of the total cases. There were higher rates of aggressive histologic subtypes in affluent neighborhoods (22.1%) compared to vulnerable neighborhoods (15.0%), as well as higher rates of advanced-stage III-IV disease (20.3% vs 16.6%). Patients who lived in the most vulnerable neighborhoods were equally likely to undergo hysterectomy (90.8% vs 88.7%), less likely to undergo chemotherapy (17.7% vs 25.4%), and less likely to undergo radiation (29.7% vs 32.1%). For patients who underwent a hysterectomy, living in a vulnerable neighborhood was associated with delays in surgical care, with 36.1% of patients undergoing hysterectomy beyond six weeks of diagnosis compared to 26.2% in affluent neighborhoods (p<0.0001). Neighborhood vulnerability was not associated with rates of adjuvant radiation for high intermediate-risk disease (63.7% vs 66.7%, p=0.39) but was associated with lower rates of adjuvant chemotherapy for advanced-stage disease (62.3% vs 77.0%, p<0.0001) and worse overall survival (71.4% vs 74.0%; p<0.0001). This survival disparity persisted even after adjusting for patient demographics, cancer characteristics, and treatment variables, with a hazard ratio of 1.2 (95% CI: 1.15-1.31). Conclusions: In New York State, people with uterine cancer living in vulnerable neighborhoods are less likely to receive timely surgical care and appropriate adjuvant chemotherapy for advanced-stage disease, with inferior survival when compared to people living in affluent neighborhoods. [Display omitted] [ABSTRACT FROM AUTHOR]

Previous research has identified several individual-level factors that modify the risk of childhood trauma on adult psychiatric symptoms, including symptoms of major depression (MD) and posttraumatic stress (PTS). Neighborhood-level factors also influence the impact of individual-level exposures on adult psychopathology. However, no prior studies to our knowledge have explored cross-level interactions between childhood trauma and neighborhood-level factors on MD and PTS symptoms. The purpose of this study was therefore to explore cross-level interactions between a neighborhood-level factor – neighborhood-level crime – and childhood trauma on MD and PTS symptoms. Participants in this study ( N = 3192) were recruited from a large public hospital, and completed self-report inventories of childhood trauma and MD and PTS symptoms. Participant addresses were mapped onto 2010 census tracts, and data on crime within each tract were collected. Multilevel models found a significant cross-level interaction between childhood trauma and neighborhood crime on MD symptoms, such that the influence of high levels of childhood trauma on MD symptoms was enhanced for participants living in high-crime neighborhoods. Supplementary analyses found variation in the strength of cross-level interaction terms by types of childhood trauma and crime, with the strongest associations including emotional neglect paired with personal and property crime. The results provide preliminary support for interventions that help childhood trauma survivors find housing in less vulnerable neighborhoods and build skills to cope with neighborhood crime. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To evaluate the association between adult individuals' body mass index (BMI) and characteristics of parks (size and cleanliness) in an urban environment taking into account the physical and social environments of the neighborhood. Methods: Cross-sectional, hierarchical linear models were used to determine whether park effects were associated with BMI using self-reported height and weight data obtained from the Community Health Survey in New York City (2002–2006). Results: Both the proportion of the residential zip code that was large park space and the proportion that was small park space had significant inverse associations with BMI after controlling for individual socio-demographic and zip code built environment characteristics (−0.20 BMI units across the inter-quartile range (IQR) for large parks, 95% CI −0.32, −0.08; −0.21 BMI units across the IQR for small parks, 95% CI −0.31, −0.10, respectively). Poorer scores on the park cleanliness index were associated with higher BMI, 0.18 BMI units across the IQR of the park cleanliness index (95% CI 0.05, 0.30). Conclusions: This study demonstrated that proportion of neighborhoods that was large or small park space and park cleanliness were associated with lower BMI among NYC adults after adjusting for other neighborhood features such as homicides and walkability, characteristics that could influence park usage. [Copyright &y& Elsevier]

Abstract: Policies target fast food outlets to curb adolescent obesity. We argue that researchers should examine the entire retail ecology of neighborhoods, not just fast food outlets. We examine the association between the neighborhood retail environment and obesity using Fitnessgram data collected from 94,348 New York City public high school students. In generalized hierarchical linear models, the number of fast food restaurants predicted lower odds of obesity for adolescents (OR:0.972 per establishment; CI:0.957–0.988). In a “placebo test” we found that banks – a measure of neighborhood retail ecology – also predicted lower obesity (OR:0.979 per bank; CI:0.962–0.994). Retail disinvestment might be associated with greater obesity; accordingly, public health research should study the influence of general retail disinvestment not just food-specific investment. [Copyright &y& Elsevier]

Background: Neighborhood attractiveness and safety may encourage physical activity and help individuals maintain a healthy weight. However, these neighborhood characteristics may not be equally relevant to health across all settings and population subgroups. Purpose: To evaluate whether potentially attractive neighborhood features are associated with lower BMI, whether safety hazards are associated with higher BMI, and whether environment–environment interactions are present such that associations for a particular characteristic are stronger in an otherwise supportive environment. Methods: Survey data and measured height and weight were collected from a convenience sample of 13,102 adult New York City (NYC) residents in 2000–2002; data analyses were completed 2008–2012. Built-environment measures based on municipal GIS data sources were constructed within 1-km network buffers to assess walkable urban form (density, land-use mix, transit access); attractiveness (sidewalk cafés, landmark buildings, street trees, street cleanliness); and safety (homicide rate, pedestrian–auto collision and fatality rate). Generalized linear models with cluster-robust SEs controlled for individual and area-based sociodemographic characteristics. Results: The presence of sidewalk cafés, density of landmark buildings, and density of street trees were associated with lower BMI, whereas the proportion of streets rated as clean was associated with higher BMI. Interactions were observed for sidewalk cafés with neighborhood poverty, for street-tree density with walkability, and for street cleanliness with safety. Safety hazard indicators were not independently associated with BMI. Conclusions: Potentially attractive community and natural features were associated with lower BMI among adults in NYC, and there was some evidence of effect modification. [Copyright &y& Elsevier]