Effect of street connectivity and density on adult BMI: results from the Twin Cities Walking Study

McDonald, Kelsey; Oakes, J. Michael; Forsyth, Ann

doi:10.1136/jech.2010.122556

Cited by 22 publications

(16 citation statements)

References 29 publications

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“…Our findings are consistent with previous literatures showing that increased pedestrian network connectivity encourages walking for transportation [8,23-25]. For example, Berrigan, D. and his colleagues found that street connectivity accounted for a small but significant influence on active transportation [23], while the Twin Cities walking study also reported positive associations between street connectivity and walking for transportation [24,25]. Few studies, however, have been conducted in hilly topography environments, where pedestrian networks may not easily be established and added.…”

Section: Discussionsupporting

confidence: 93%

How do changes to the built environment influence walking behaviors? a longitudinal study within a university campus in Hong Kong

2014

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BackgroundPrevious studies testing the association between the built environment and walking behavior have been largely cross-sectional and have yielded mixed results. This study reports on a natural experiment in which changes to the built environment were implemented at a university campus in Hong Kong. Longitudinal data on walking behaviors were collected using surveys, one before and one after changes to the built environment, to test the influence of changes to the built environment on walking behavior.MethodsBuilt environment data are from a university campus in Hong Kong, and include land use, campus bus services, pedestrian network, and population density data collected from campus maps, the university developmental office, and field surveys. Walking behavior data were collected at baseline in March 2012 (n = 198) and after changes to the built environment from the same cohort of subjects in December 2012 (n = 169) using a walking diary. Geographic information systems (GIS) was used to map walking routes and built environment variables, and compare each subject’s walking behaviors and built environment exposure before and after the changes to the built environment. Walking behavior outcomes were changes in: i) walking distance, ii) destination-oriented walking, and iii) walked altitude range. Multivariable linear regression models were used to test for associations between changes to the built environment and changes in walking behaviors.ResultsGreater pedestrian network connectivity predicted longer walking distances and an increased likelihood of walking as a means of transportation. The increased use of recreational (vs. work) buildings, largely located at mid-range altitudes, as well as increased population density predicted greater walking distances.Having more bus services and a greater population density encouraged people to increase their walked altitude range.ConclusionsIn this longitudinal study, changes to the built environment were associated with changes in walking behaviors. Use of GIS combined with walking diaries presents a practical method for mapping and measuring changes in the built environment and walking behaviors, respectively. Additional longitudinal studies can help clarify the relationships between the built environment and walking behaviors identified in this natural experiment.

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Section: Discussionsupporting

confidence: 93%

How do changes to the built environment influence walking behaviors? a longitudinal study within a university campus in Hong Kong

2014

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“…29 The Walk Score application programming interface eliminates the need for a website interface, which is especially useful with large data sets. 24 To maintain confidentiality of participant addresses, Walk Score values were assigned within the WHI Clinical Coordinating Center and provided to the study team.…”

Section: Methodsmentioning

confidence: 99%

“…Covariates were selected a priori based on previous analyses of walkability and BMI 9,20–24 and existing literature on known risk factors for excess weight in this population. 33–35 …”

Section: Methodsmentioning

confidence: 99%

Neighborhood Walkability and Adiposity in the Women’s Health Initiative Cohort

Sriram

LaCroix

Barrington

et al. 2016

American Journal of Preventive Medicine

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Introduction Neighborhood environments may play a role in the rising prevalence of obesity among older adults. However, research on built environmental correlates of obesity in this age group is limited. The current study aimed to explore associations of Walk Score, a validated measure of neighborhood walkability, with BMI and waist circumference in a large, diverse sample of older women. Methods This study linked cross-sectional data on 6,526 older postmenopausal women from the Women’s Health Initiative Long Life Study (2012–2013) to Walk Scores for each participant’s address (collected in 2012). Linear and logistic regression models were used to estimate associations of BMI and waist circumference with continuous and categorical Walk Score measures. Secondary analyses examined whether these relationships could be explained by walking expenditure or total physical activity. All analyses were conducted in 2015. Results Higher Walk Score was not associated with BMI or overall obesity after adjustment for sociodemographic, medical, and lifestyle factors. However, participants in highly walkable areas had significantly lower odds of abdominal obesity (waist circumference >88 cm) as compared with those in less walkable locations. Observed associations between walkability and adiposity were partly explained by walking expenditure. Conclusions Findings suggest that neighborhood walkability is linked to abdominal adiposity, as measured by waist circumference, among older women and provide support for future longitudinal research on associations between Walk Score and adiposity in this population.

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“…Studies have found complex links between neighbourhood characteristics, activity and travel behaviour (Aditjandra 2007, Forsyth et al 2008. Some studies suggest land use patterns, particularly in terms of density and land use mix, have only a marginal impact on travel choice (Boarnet and Sarmiento 1998), and have inconsistent association with health because of social variations (McDonald et al 2011). Nevertheless there is a growing consensus that residents in more walkable neighbourhoods (with traditional or neo-traditional form) do undertake more active travel compared with those in modern cul-de-sac layouts (Handy 2005, Saelens 2003, Frank et al 2006, Pickora et al 2005, Furguson and Woods 2010.…”

Section: Previous Studies Of Active Travel and Neighbourhood Accessibmentioning

confidence: 99%

Neighbourhood Accessibility and Active Travel

Barton¹,

Horswell²,

Millar³

2012

Planning Practice and Research

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Effect of street connectivity and density on adult BMI: results from the Twin Cities Walking Study

Abstract: There is no evidence of an effect of population density by block size on BMI.

Cited by 22 publications

References 29 publications

How do changes to the built environment influence walking behaviors? a longitudinal study within a university campus in Hong Kong

How do changes to the built environment influence walking behaviors? a longitudinal study within a university campus in Hong Kong

Neighborhood Walkability and Adiposity in the Women’s Health Initiative Cohort

Neighbourhood Accessibility and Active Travel

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