Koohsari, J., Sugiyama, T., Hanibuchi, T., Shibata, A., Ishii, K., Liao, Y. & Oka, K. (2018). Validity of Walk Score® as a measure of neighborhood walkability in Japan. Preventive Medicine Reports,9E. L. Franco, Z. Rosberger. 114-117. United States: Elsevier BV. Retrieved from https://doi.org/10.1016/j.pmedr.2018.01.001
Objective measures of environmental attributes have been used to understand how neighborhood environments relate to physical activity. However, this method relies on detailed spatial data, which are often not easily available. Walk Score® is a free, publicly available web-based tool that shows how walkable a given location is based on objectively-derived proximity to several types of local destinations and street connectivity. To date, several studies have tested the concurrent validity of Walk Score as a measure of neighborhood walkability in the USA and Canada. However, it is unknown whether Walk Score is a valid measure in other regions. The current study examined how Walk Score is correlated with objectively-derived attributes of neighborhood walkability, for residential addresses in Japan. Walk Scores were obtained for 1072 residential addresses in urban and rural areas in Japan. Five environmental attributes (residential density, intersection density, number of local destinations, sidewalk availability, and access to public transportation) were calculated using geographic information systems for each address. Pearson's correlation coefficients between Walk Score and these environmental attributes were calculated (conducted in May 2017). Significant positive correlations were observed between Walk Score and environmental attributes relevant to walking. Walk Score was most closely associated with intersection density (r = 0.82) and with the number of local destinations (r = 0.77). Walk Score appears to be a valid measure of neighborhood walkability in Japan. Walk Score will allow urban designers and public health practitioners to identify walkability of local areas without relying on detailed geographic data
Mary MacKillop Institute for Health Research
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