The Urban Built Environment and Obesity in New York City: A Multilevel Analysis

Mailman School of Public Health, 722 West 168th Street, Room 730, New York, NY 10032, USA.
American journal of health promotion: AJHP (Impact Factor: 2.37). 03/2007; 21(4 Suppl):326-34. DOI: 10.4278/0890-1171-21.4s.326
Source: PubMed


To examine whether urban form is associated with body size within a densely-settled city.
Cross-sectional analysis using multilevel modeling to relate body mass index (BMI) to built environment resources.
Census tracts (n = 1989) within the five boroughs of New York City.
Adult volunteers (n = 13,102) from the five boroughs of New York City recruited between January 2000 and December 2002.
The dependent variable was objectively-measured BMI. Independent variables included land use mix; bus and subway stop density; population density; and intersection density. Covariates included age, gender, race, education, and census tract-level poverty and race/ethnicity.
Cross-sectional multilevel analyses.
Mixed land use (Beta = -.55, p < .01), density of bus stops (Beta = -.01, p < .01) and subway stops (Beta = -.06, p < .01), and population density (Beta = -.25, p < .001), but not intersection density (Beta = -. 002) were significantly inversely associated with BMI after adjustmentfor individual- and neighborhood-level sociodemographic characteristics. Comparing the 90th to the 10th percentile of each built environment variable, the predicted adjusted difference in BMI with increased mixed land use was -. 41 units, with bus stop density was -.33 units, with subway stop density was -.34 units, and with population density was -.86 units.
BMI is associated with built environment characteristics in New York City.

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Available from: Kathryn M. Neckerman, Oct 09, 2015
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    • "walked along routes with increased mixed land-use also had greater overall daily MVPA levels. These findings are consistent with the existing literature on the role of mixed-land use in promoting walking and weight control (Rundle et al., 2007; Saelens and Handy 2008; Ding et al., 2011). This study has several limitations. "
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    ABSTRACT: Active commuting to school increases children's daily physical activity. The built environment is associated with children's physical activity levels in cross-sectional studies. This study examined the role of the built environment on the outcomes of a "walking school bus" study. Geographical information systems was used to map out and compare the built environments around schools participating in a pilot walking school bus randomised controlled trial, as well as along school routes. Multi-level modelling was used to determine the built environment attributes associated with the outcomes of active commuting to school and accelerometer-determined moderate-to-vigorous physical activity (MPVA). There were no differences in the surrounding built environments of control (n = 4) and intervention (n = 4) schools participating in the walking school bus study. Among school walking routes, park space was inversely associated with active commuting to school (β = -0.008, SE = 0.004, P = 0.03), while mixed-land use was positively associated with daily MPVA (β = 60.0, SE = 24.3, P = 0.02). There was effect modification such that high traffic volume and high street connectivity were associated with greater moderate-to-vigorous physical activity. The results of this study suggest that the built environment may play a role in active school commuting outcomes and daily physical activity.
    Geospatial health 11/2014; 9(1):37-44. DOI:10.4081/gh.2014.4 · 1.19 Impact Factor
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    • "Neighborhood poverty was measured by the census tract-level percentage of individuals under the federal poverty level, which has been shown to be associated with obesity in previous studies (Black et al., 2010; Ludwig et al., 2011). It was often included as a control variable in the analysis of neighborhood context impact on obesity (Boardman et al., 2005; Rundle et al., 2007). In addition, neighborhood economic poverty measures were most robust to detect population health outcome gradients (Krieger et al., 2002). "
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    ABSTRACT: Automobile dependency and longer commuting are associated with current obesity epidemic. We aimed to examine the urban-rural differential effects of neighborhood commuting environment on obesity in the US METHODS: The 1997-2005 National Health Interview Survey (NHIS) were linked to 2000 US Census data to assess the effects of neighborhood commuting environment: census tract-level automobile dependency and commuting time, on individual obesity status. Higher neighborhood automobile dependency was associated with increased obesity risk in urbanized areas (large central metro (OR 1.11[1.09, 1.12]), large fringe metro (OR 1.17[1.13, 1.22]), medium metro (OR 1.22[1.16, 1.29]), small metro (OR 1.11[1.04, 1.19]), and micropolitan (OR 1.09[1.00, 1.19])), but not in non-core rural areas (OR 1.00[0.92, 1.08]). Longer neighborhood commuting time was associated with increased obesity risk in large central metro (OR 1.09[1.04, 1.13]), and less urbanized areas (small metro (OR 1.08[1.01, 1.16]), micropolitan (OR 1.06[1.01, 1.12]), and non-core rural areas (OR 1.08[1.01, 1.17])), but not in (large fringe metro (OR 1.05[1.00, 1.11]), and medium metro (OR 1.04[0.98, 1.10])). The link between commuting environment and obesity differed across the regional urbanization levels. Urban and regional planning policies may improve current commuting environment and better support healthy behaviors and healthy community development.
    Preventive Medicine 11/2013; 59(1). DOI:10.1016/j.ypmed.2013.11.004 · 3.09 Impact Factor
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    • "People who lived in census tracts with higher population density had significantly lower BMIs than those who lived in areas with low population density. This study also found an inverse association between BMI and other variables of the built environment such as mixed land use, the number of bus stops and subway stations and the number of street intersections [25]. "
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    ABSTRACT: Obesity is a significant global public health problem and the main cause of many chronic diseases in both developed and developing countries. The increase in obesity in different populations worldwide cannot be explained solely by metabolic and genetic factors; environmental and social factors also have a strong association with obesity. Thus, it is believed that the current obesity epidemic is the result of a complex combination of genetic factors and an obesogenic environment .The purpose of this study was to evaluate individual variables and variables within the built and social environment for their potential association with overweight and obesity in an urban Brazilian population. Cross-sectional study was carried out in a sample of 3404 adults living in the urban area of the city. Information from the surveillance system for chronic diseases of Brazilian Ministry of Health was used and individual data was collected by telephone interviews. The database was geocoded using the Brazilian System of Postal Codes for participant residences. An updated, existing list based on the current addresses of supermarkets and hypermarkets in the city was used as an indicator variable of the availability and access to food. Georeferenced information on parks, public squares, places for practicing physical activity and the population density were also used to create data on the built environment. To characterize the social environment, we used the health vulnerability index (HVI) and georeferenced data for homicide locations. The prevalence was 44% for overweight, poisson regression was used to create the final model. The environment variables that independently associated with overweight were the highest population density, very high health vulnerability index and the homicide rate adjusted for individuals variables. The results of the current study illustrate and confirm some important associations between individual and environmental variables and overweight in a representative sample of adults in the Brazilian urban context. The social environment variables relating to the socioeconomic deprivation of the neighborhood and the built environment variables relating to higher walkability were significantly associated with overweight and obesity in Belo Horizonte.
    BMC Public Health 10/2013; 13(1):988. DOI:10.1186/1471-2458-13-988 · 2.26 Impact Factor
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