Comparing objective measures of environmental supports for pedestrian travel in adults
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Shay, Elizabeth, et al. Comparing Objective Measures of Environmental Supports for Pedestrian Travel In Adults. BioMed Central Ltd, 2009. https://doi.org/10.17615/2ymg-h112APA
Shay, E., Rodriguez, D., Cho, G., Clifton, K., & Evenson, K. (2009). Comparing objective measures of environmental supports for pedestrian travel in adults. BioMed Central Ltd. https://doi.org/10.17615/2ymg-h112Chicago
Shay, Elizabeth, Daniel Rodriguez, Gihyoug Cho, Kelly J Clifton, and Kelly Evenson. 2009. Comparing Objective Measures of Environmental Supports for Pedestrian Travel In Adults. BioMed Central Ltd. https://doi.org/10.17615/2ymg-h112- Creator
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Shay, Elizabeth
- Affiliation: UNC Institute for the Environment
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Rodriguez, Daniel
- Affiliation: College of Arts and Sciences, Department of City and Regional Planning
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Cho, Gihyoug
- Affiliation: College of Arts and Sciences, Department of City and Regional Planning
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Clifton, Kelly J
- Other Affiliation: National Center for Smart Growth, University of Maryland, College Park MD, USA
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Evenson, Kelly
- Affiliation: Gillings School of Global Public Health, Department of Epidemiology
- Abstract
- Abstract Background Evidence is growing that the built environment has the potential to influence walking--both positively and negatively. However, uncertainty remains on the best approaches to representing the pedestrian environment in order to discern associations between walking and the environment. Research into the relationship between environment and walking is complex; challenges include choice of measures (objective and subjective), quality and availability of data, and methods for managing quantitative data through aggregation and weighting. In particular, little research has examined how to aggregate built environment data to best represent the neighborhood environments expected to influence residents' behavior. This study examined associations between walking and local pedestrian supports (as measured with an environmental audit), comparing the results of models using three different methods to aggregate and weight pedestrian features. Methods Using data collected in 2005-2006 for a sample of 251 adult residents of Montgomery County, MD, we examined associations between pedestrian facilities and walking behaviors (pedestrian trips and average daily steps). Adjusted negative binomial and ordinary least-squares regression models were used to compare three different data aggregation techniques (raw averages, length weighting, distance weighting) for measures of pedestrian facilities that included presence, condition, width and connectivity of sidewalks, and presence of crossing aids and crosswalks. Results Participants averaged 8.9 walk trips during the week; daily step counts averaged 7042. The three aggregation techniques revealed different associations between walk trips and the various pedestrian facilities. Crossing aids and good sidewalk conditions were associated with walk trips more than were other pedestrian facilities, while sidewalk facilities and features showed associations with steps not observed for crossing aids and crosswalks. Conclusion Among three methods of aggregation examined, the method that accounted for distance from participant's home to the pedestrian facility (distance weighting) is promising; at the same time, it requires the most time and effort to calculate. This finding is consistent with the behavioral assumption that travelers may respond to environmental features closer to their residence more strongly than to more distant environmental qualities.
- Date of publication
- November 19, 2009
- DOI
- Identifier
- Resource type
- Article
- Rights statement
- In Copyright
- Rights holder
- Elizabeth Shay et al.; licensee BioMed Central Ltd.
- License
- Journal title
- International Journal of Health Geographics
- Journal volume
- 8
- Journal issue
- 1
- Page start
- 62
- Language
- English
- Is the article or chapter peer-reviewed?
- Yes
- ISSN
- 1476-072X
- Bibliographic citation
- International Journal of Health Geographics. 2009 Nov 19;8(1):62
- Publisher
- BioMed Central Ltd
- Access right
- Open Access
- Date uploaded
- August 23, 2012
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