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Abstract: Many small grocery stores or “bodegas” sell prepared or ready-to-eat items, filling a niche in the food environment similar to fast-food restaurants. However, little comparative information is available about the nutrition environments of bodegas and fast-food outlets. This study compared the nutrition environments of bodegas and national chain fast-food restaurants using a common audit instrument, the Nutrition Environment Measures Study in Restaurants (NEMS-R) protocol. The analytic sample included 109 bodegas and 107 fast-food restaurants located in New York City neighborhoods in the upper third and lower third of the census tract poverty rate distribution. Inter-rater reliability was evaluated in 102 food outlets, including 31 from the analytic sample and 71 from a supplementary convenience sample. The analysis compared scores on individual NEMS-R items, a total summary score, and subscores indicating healthy food availability, nutrition information, promotions of healthy or unhealthy eating, and price incentives for healthy eating, using t tests and χ2 statistics to evaluate differences by outlet type and neighborhood poverty. Fast-food restaurants were more likely to provide nutrition information, and bodegas scored higher on healthy food availability, promotions, and pricing. Bodegas and fast-food restaurants had similar NEMS-R total scores (bodegas 13.09, fast food 14.31; P=0.22). NEMS-R total scores were higher (indicating healthier environments) in low- than high-poverty neighborhoods among both bodegas (14.79 vs 11.54; P=0.01) and fast-food restaurants (16.27 vs 11.60; P<0.01). Results imply different policy measures to improve nutrition environments in the two types of food outlets. [Copyright &y& Elsevier]

Background: Studies of the food environment near schools have focused on fast food. Research is needed that describes patterns of exposure to a broader range of food outlet types and that examines the influence of neighborhood built environments. Purpose: Using data for New York City, this paper describes the prevalence of five different food outlet types near schools, examines disparities by economic status and race/ethnicity in access to these food outlets, and evaluates the extent to which these disparities are explained by the built environment surrounding the school. Methods: National chain and local fast-food restaurants, pizzerias, small grocery stores (“bodegas”), and convenience stores within 400 m of public schools in New York City were identified by matching 2005 Dun & Bradstreet data to 2006–2007 school locations. Associations of student poverty and race/ethnicity with food outlet density, adjusted for school level, population density, commercial zoning, and public transit access, were evaluated in 2009 using negative binomial regression. Results: New York City''s public school students have high levels of access to unhealthy food near their schools: 92.9% of students had a bodega within 400 m, and pizzerias (70.6%); convenience stores (48.9%); national chain restaurants (43.2%); and local fast-food restaurants (33.9%) were also prevalent within 400 m. Racial/ethnic minority and low-income students were more likely to attend schools with unhealthy food outlets nearby. Bodegas were the most common source of unhealthy food, with an average of nearly ten bodegas within 400 m, and were more prevalent near schools attended by low-income and racial/ethnic minority students; this was the only association that remained significant after adjustment for school and built-environment characteristics. Conclusions: Nearly all New York City public school students have access to inexpensive, energy-dense foods within a 5-minute walk of school. Low-income and Hispanic students had the highest level of exposure to the food outlets studied here. [Copyright &y& Elsevier]

To examine the association between cumulative exposure to neighborhood walkability (NW) and diabetes risk. A total of 11,037 women free of diabetes at enrollment were included. We constructed a 4-item NW index at baseline, and a 2-item average annual NW across years of follow-up that captured both changes in neighborhood features and residential moves. We used multivariable Cox PH regression models with robust variance to estimate the hazard ratios (HRs) of diabetes by NW scores. Compared with women living in areas with lowest NW (Q1), those living in areas with highest NW (Q4) had 33 % (26 %−39 %) reduced risk of incident diabetes, using baseline NW, and 25 % (95 % CI 11 %−36 %), using average annual NW. Analysis using time-varying exposure showed that diabetes risks decreased by 13 % (10 %−16 %) per -standard deviation increase in NW. The associations remained similar when using inverse probability of attrition weights and/or competing risk models to account for the effect of censoring due to death or non-response. The associations of average annual NW with incident diabetes were stronger in postmenopausal women as compared to premenopausal women. Long-term residence in more walkable neighborhoods may be protective against diabetes in women, especially postmenopausal women. • We constructed a 4-item baseline and a 2-item average annual walkability index. • Women living in the most walkable neighborhood had 25 %−33 % reduced risk in diabetes. • The protective associations remained apparent in older women and postmenopausal women. [ABSTRACT FROM AUTHOR]

Public health research has shown that neighborhood conditions are associated with health behaviors and outcomes. Systematic neighborhood audits have helped researchers measure neighborhood conditions that they deem theoretically relevant but not available in existing administrative data. Systematic audits, however, are expensive to conduct and rarely comparable across geographic regions. We describe the development of an online application, the Computer Assisted Neighborhood Visual Assessment System (CANVAS), that uses Google Street View to conduct virtual audits of neighborhood environments. We use this system to assess the inter-rater reliability of 187 items related to walkability and physical disorder on a national sample of 150 street segments in the United States. We find that many items are reliably measured across auditors using CANVAS and that agreement between auditors appears to be uncorrelated with neighborhood demographic characteristics. Based on our results we conclude that Google Street View and CANVAS offer opportunities to develop greater comparability across neighborhood audit studies. [ABSTRACT FROM AUTHOR]

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: 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]

Disparities in availability of food retailers in the residential environment may help explain racial/ethnic and socio-economic differences in obesity risk. Research is needed that describes whether food environment dynamics may contribute to equalizing conditions across neighborhoods or to amplifying existing inequalities over time. This study improves the understanding of how the BMI-unhealthy food environment has evolved over time in New York City. We use longitudinal census tract-level data from the National Establishment Time-Series (NETS) for New York City in the period 1990–2010 and implement latent class growth analysis (LCGA) to (1) examine trajectories of change in the number of unhealthy food outlets (characterized as selling calorie-dense foods such as pizza and pastries) at the census tract-level, and (2) examine how trajectories are related to socio-demographic characteristics of the census tract. Overall, the number of BMI-unhealthy food outlets increased between 1990 and 2010. We summarized trajectories of evolutions with a 5-class model that indicates a pattern of fanning out, such that census tracts with a higher initial number of BMI-unhealthy food outlets in 1990 experienced a more rapid increase over time. Finally, fully adjusted logistic regression models reveal a greater increase in BMI-unhealthy food outlets in census tracts with: higher baseline population size, lower baseline income, and lower proportion of Black residents. Greater BMI-unhealthy food outlet increases were also noted in the context of census tracts change suggestive of urbanization (increasing population density) or increasing purchasing power (increasing income). • Exposure to the unhealthy food environment increased between 1990 and 2010. • We observed divergent trajectories of changes in the unhealthy food environment. • Greater increases in exposure occurred in poorer and non-Black neighborhoods. • Greater exposure was related to urbanization and increasing purchasing power. [ABSTRACT FROM AUTHOR]

Introduction: Urban form characteristics intended to support pedestrian activity, collectively referred to as neighborhood walkability, are thought to increase total physical activity. However, little is known about how neighborhood walkability influences utilization of neighborhood space by residents and their overall physical activity.Methods: Sociodemographic information and data on mobility and physical activity over 1-week periods measured by GPS loggers and accelerometers were collected from 803 residents of New York City between November 2010 and November 2011. Potentially accessible neighborhood areas were defined as land area within a 1-kilometer distance of the subject's home (radial buffer) and within a 1-kilometer journey on the street network from the home (network buffer). To define actual areas utilized by subjects, a minimum convex polygon was plotted around GPS waypoints falling within 1 kilometer of the home. A neighborhood walkability scale was calculated for each neighborhood area. Data were analyzed in 2014.Results: Total residential neighborhood space utilized by subjects was significantly associated with street intersection density and was significantly negatively associated with residential density and subway stop density within 1 kilometer of the home. Walkability scale scores were significantly higher within utilized as compared with non-utilized neighborhood areas. Neighborhood walkability in the utilized neighborhood area was positively associated with total weekly physical activity (32% [95% CI=17%, 49%] more minutes of moderate-equivalent physical activity across the interquartile range of walkability).Conclusion: Neighborhood walkability is associated with neighborhood spaces utilized by residents and total weekly physical activity. [ABSTRACT FROM AUTHOR]