We have conducted a series of analyses investigating whether “neighborhood walkability” is associated with lower body mass index (BMI), greater levels of physical activity and more pedestrian activity among residents of New York City.
Urban planners refer “neighborhood walkability” as the extent to which neighborhood design supports walking and they describe neighborhood walkability in terms of “the D’s” – density, diversity, design, destination accessibility and distance to transit. Density refers to attributes of interest per geographic area, diversity refers to the mix of land uses, design pertains to the layout of the street grid, destination accessibility is the availability of destinations to travel to such as stores, and distance to transit is the physical distance to public transportation. Additional neighborhood characteristics such as aesthetics and safety can also promote walking and are often described as being part of neighborhood walkability.
Our initial studies funded by NIEHS showed that indicators of neighborhood walkability described in the urban planning literature – population density, land use mix and access to public transit – were associated with lower BMI among adults and higher levels of physical activity in children [1, 2, 3]. However, further analyses showed that associations between these indicators of neighborhood walkability and BMI were only apparent in more socioeconomically advantaged individuals , a finding that is fairly consistent among the literature . We were also able to show that measures of neighborhood aesthetic qualities were also associated with lower BMI.
In an effort to understand why neighborhood walkability was associated with lower BMI only for those living in higher income neighborhoods, we conducted neighborhood audits and performed GIS based analyses of high and low income neighborhoods that were matched on neighborhood walkability as measured by urban planning considerations . We found that poorer areas had more social disorder and safety issues that might deter walking and that the sidewalks were in poorer condition.
We were also funded by the Robert Wood Johnson Foundation Active Living Research Program to develop new measures of urban design qualities thought to promote walking. We adapted an existing neighborhood audit instrument, Reid Ewing’s Maryland Urban Design Inventory, so that its measures could be derived from administrative and GIS data. During this project we created our first multi-dimensional scale to measure neighborhood walkability, which combined data on residential density, commercial density and subway ridership to estimate pedestrian activity on streets  (NYC neighborhood walkability index V1.0). The figure below shows the adjusted mean BMI of our ~13,000 study subjects by quintiles of neighborhood walkability using this measure.
We were subsequently funded by NIDDK to collaborate with the NYC Department of Health and Mental Hygiene to study obesity and physical activity using the NYC Community Health Survey (CHS) data. We pooled data from the 2002 to 2006 surveys and used the respondent’s zip codes of residence to link the survey data to a new measure of neighborhood walkability. For this project we used a measure of walkability that we have adapted from Frank et al’s walkability index . Our NYC neighborhood walkability index V2.0 uses data on 1) residential density; 2) intersection density; 3) land use mix for five types of land use – residential, office, retail, education, and entertainment; 4) subway stop density; and 5) the ratio of retail building floor area to retail land area to measure neighborhood walkability. The map below shows how neighborhood walkability varies across Census tract in NYC in 2011.
Using data from the CHS we have shown that neighborhood walkability is associated with greater engagement in active transport . Respondents to the 2003 CHS reported the frequency of walking or biking ten blocks or more in the past month. Survey responses were linked to zip code level measures of neighborhood walkability, measured using V2.0 of the NYC neighborhood walkability index. Overall, 44% of the respondents reported that they had not engaged in active travel in the past month and among those who reported any episodes of active travel, the mean number was 43.2 episodes per month. Data were analyzed using zero-inflated negative binomial regression incorporating survey sample weights and adjusting for respondents’ sociodemographic characteristics. Overall, higher neighborhood walkability was associated with a significantly lower odds of reporting no active transport, an association that was stronger among Caucasian as compared to African American and Hispanic respondents, and was stronger among those living in higher income zip codes than among those living in lower income zip codes (see Figure 3).
Figure 3. Neighborhood Walkability and Odds of Reporting No Engagement in Active Transport
Figure 3. Odds ratio calculated comparing the 75th percentile zip code to the 25th percentile zip code for walkability.
Among those reporting any episodes of active transport in the month before the survey higher neighborhood walkability was associated with more episodes of active transport (see Figure 4).
Figure 4. Neighborhood Walkability and Episodes of Engaging in Active Transport
Figure 4. rate ratio calculated comparing the 75th percentile zip code to the 25th percentile zip code for walkability.
In other work we are in the midst of conducting a systematic literature review and meta-analysis of studies that assessed associations between neighborhood walkability and BMI or physical activity. One of the goals of the review is to determine whether associations between neighborhood walkability and these outcomes are consistent across different regions and urban forms.