Validation of Walk Scores and Transit Scores for estimating neighborhood walkability and transit availability: A small-area analysis

被引:102
作者
Duncan D.T. [1 ]
Aldstadt J. [2 ]
Whalen J. [2 ]
Melly S.J. [3 ]
机构
[1] Department of Society, Human Development, and Health, Harvard School of Public Health, Boston, MA, 02115, 677 Huntington Avenue
[2] Department of Geography, University at Buffalo, State University of New York, Buffalo, NY
[3] Department of Environmental Health, Harvard School of Public Health, Boston, MA
关键词
Neighborhood walkability; Small-area analysis; Transit availability; Transit score; Validity; Walk Score;
D O I
10.1007/s10708-011-9444-4
中图分类号
学科分类号
摘要
We investigated the validity of Walk Scores and Transit Scores from the Walk Score website using several objective geographic information systems (GIS) measures of neighborhood walkabiltiy and transit availability based on 400- and 800-m street network buffers. Address data come from the 2008 Boston Youth Survey Geospatial Dataset, a school-based sample of public high school students in Boston, MA with complete residential address information (n = 1,292). GIS data were used to create multiple objective measures of neighborhood walkability and transit availability. We also obtained Walk Scores and Transit Scores. We calculated Spearman correlations of Walk Scores and Transit Scores with the GIS neighborhood walkability/transit availability measures as well as Spearman correlations accounting for spatial autocorrelation. Several significant correlations were observed between Walk Score and 400-m buffer GIS measures of neighborhood walkability; all significant correlations were found for the 800-m buffer. All correlations between Transit Scores and GIS measures of neighborhood transit availability were also significant (all p < 0. 0001). However, the magnitude of correlations varied by the GIS measure and neighborhood definition. Relative to the 400-m buffer, correlations for the 800-m buffer were higher. This study suggests that Walk Score is a good, convenient tool to measure certain aspects of neighborhood walkability and transit availability (such as density of retail destinations, density of recreational open space, intersection density, residential density and density of subway stops). However, Walk Score works best at larger spatial scales. © 2012 Springer Science+Business Media B.V.
引用
收藏
页码:407 / 416
页数:9
相关论文
共 37 条
[1]  
Azrael D., Johnson R.M., Molnar B.E., Vriniotis M., Dunn E.C., Duncan D.T., Hemenway D., Et al., Creating a youth violence data system for Boston, Massachusetts, Australian and New Zealand Journal of Criminology, 42, 3, pp. 406-421, (2009)
[2]  
Bailey T.C., Gatrell A.C., Interactive Spatial Data Analysis, (1995)
[3]  
Ball K., Jeffery R.W., Crawford D.A., Roberts R.J., Salmon J., Timperio A.F., Mismatch between perceived and objective measures of physical activity environments, Preventive Medicine, 47, 3, pp. 294-298, (2008)
[4]  
Brewer C., Harrower M., Color Brewer 2. 0, (2011)
[5]  
Brownson R.C., Hoehner C.M., Day K., Forsyth A., Sallis J.F., Measuring the built environment for physical activity: State of the science, American Journal of Preventive Medicine, 36, SUPPL. 4, pp. 99-123, (2009)
[6]  
Carr L.J., Dunsiger S.I., Marcus B.H., Walk score<sup>™</sup> as a global estimate of neighborhood walkability, American Journal of Preventive Medicine, 39, 5, pp. 460-463, (2010)
[7]  
Carr L.J., Dunsiger S.I., Marcus B.H., Validation of Walk Score for estimating access to walkable amenities, British Journal of Sports Medicine, 45, 14, pp. 1144-1148, (2011)
[8]  
Cerin E., Leslie E., du Toit L., Owen N., Frank L.D., Destinations that matter: Associations with walking for transport, Health & Place, 13, 3, pp. 713-724, (2007)
[9]  
Clifford P., Richardson S., Testing the association between two spatial processes, Statistics and Decisions, 2, SUPPL., pp. 155-160, (1985)
[10]  
Delmelle E., Spatial sampling, The SAGE Handbook of Spatial Analysis, pp. 183-206, (2009)