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Validation of Walk Score ® for Estimating Neighborhood Walkability: An Analysis of Four US Metropolitan Areas

Author

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  • Dustin T. Duncan

    (Department of Society, Human Development, and Health, Harvard School of Public Health, 677 Huntington Avenue, Kresge Building 7th Floor, Boston, MA 02115, USA
    Harvard Prevention Research Center on Nutrition and Physical Activity, Harvard School of Public Health, 401 Park Drive, Landmark Center, 4th Floor West, Boston, MA 02215, USA)

  • Jared Aldstadt

    (Department of Geography, University at Buffalo, State University of New York, 105 Wilkeson Quad, Buffalo, NY 14261, USA)

  • John Whalen

    (Department of Geography, University at Buffalo, State University of New York, 105 Wilkeson Quad, Buffalo, NY 14261, USA)

  • Steven J. Melly

    (Department of Environmental Health, Harvard School of Public Health, 401 Park Drive, Landmark Center, 4th Floor West, Boston, MA 02215, USA)

  • Steven L. Gortmaker

    (Department of Society, Human Development, and Health, Harvard School of Public Health, 677 Huntington Avenue, Kresge Building 7th Floor, Boston, MA 02115, USA
    Harvard Prevention Research Center on Nutrition and Physical Activity, Harvard School of Public Health, 401 Park Drive, Landmark Center, 4th Floor West, Boston, MA 02215, USA)

Abstract

Neighborhood walkability can influence physical activity. We evaluated the validity of Walk Score ® for assessing neighborhood walkability based on GIS (objective) indicators of neighborhood walkability with addresses from four US metropolitan areas with several street network buffer distances ( i.e. , 400-, 800-, and 1,600-meters). Address data come from the YMCA-Harvard After School Food and Fitness Project, an obesity prevention intervention involving children aged 5–11 years and their families participating in YMCA-administered, after-school programs located in four geographically diverse metropolitan areas in the US (n = 733). GIS data were used to measure multiple objective indicators of neighborhood walkability. Walk Scores were also obtained for the participant’s residential addresses. Spearman correlations between Walk Scores and the GIS neighborhood walkability indicators were calculated as well as Spearman correlations accounting for spatial autocorrelation. There were many significant moderate correlations between Walk Scores and the GIS neighborhood walkability indicators such as density of retail destinations and intersection density (p ® is free and publicly available for public health researchers and practitioners. Results from our study suggest that Walk Score ® is a valid measure of estimating certain aspects of neighborhood walkability, particularly at the 1600-meter buffer. As such, our study confirms and extends the generalizability of previous findings demonstrating that Walk Score is a valid measure of estimating neighborhood walkability in multiple geographic locations and at multiple spatial scales.

Suggested Citation

  • Dustin T. Duncan & Jared Aldstadt & John Whalen & Steven J. Melly & Steven L. Gortmaker, 2011. "Validation of Walk Score ® for Estimating Neighborhood Walkability: An Analysis of Four US Metropolitan Areas," IJERPH, MDPI, vol. 8(11), pages 1-20, November.
  • Handle: RePEc:gam:jijerp:v:8:y:2011:i:11:p:4160-4179:d:14671
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    References listed on IDEAS

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    1. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    2. Michael, Y.L. & Perdue, L.A. & Orwoll, E.S. & Stefanick, M.L. & Marshall, L.M., 2010. "Physical activity resources and changes in walking in a cohort of older men," American Journal of Public Health, American Public Health Association, vol. 100(4), pages 654-660.
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    Cited by:

    1. Dustin T. Duncan & Farzana Kapadia & Perry N. Halkitis, 2014. "Examination of Spatial Polygamy among Young Gay, Bisexual, and Other Men Who Have Sex with Men in New York City: The P18 Cohort Study," IJERPH, MDPI, vol. 11(9), pages 1-22, August.
    2. Barbara B. Brown & Wyatt A. Jensen, 2020. "Dog Ownership and Walking: Perceived and Audited Walkability and Activity Correlates," IJERPH, MDPI, vol. 17(4), pages 1-14, February.
    3. Ye Sun & Wei Lu & Peijin Sun, 2021. "Optimization of Walk Score Based on Street Greening—A Case Study of Zhongshan Road in Qingdao," IJERPH, MDPI, vol. 18(3), pages 1-13, January.
    4. Zhang, Jilu & Guxue, Kaicheng, 2024. "Fostering sustainability: Exploring natural resources, mineral resources, and their impact on carbon reduction, economic growth," Resources Policy, Elsevier, vol. 92(C).
    5. Bradley Bereitschaft, 2023. "The changing ethno-racial profile of ‘very walkable’ urban neighbourhoods in the US (2010–2020): Are minorities under-represented?," Urban Studies, Urban Studies Journal Limited, vol. 60(4), pages 638-654, March.
    6. Zhang, Zhehao & Wang, Haiming & Fisher, Thomas, 2024. "The development, validation, and application of the campus walk score measurement system," Transport Policy, Elsevier, vol. 152(C), pages 40-54.
    7. Maren Reyer & Stefan Fina & Stefan Siedentop & Wolfgang Schlicht, 2014. "Walkability is Only Part of the Story: Walking for Transportation in Stuttgart, Germany," IJERPH, MDPI, vol. 11(6), pages 1-17, May.
    8. Eun Jung Kim & Jiyeong Kim & Hyunjung Kim, 2020. "Does Environmental Walkability Matter? The Role of Walkable Environment in Active Commuting," IJERPH, MDPI, vol. 17(4), pages 1-17, February.
    9. Yibang Zhang & Yukun Zou & Zhenjun Zhu & Xiucheng Guo & Xin Feng, 2022. "Evaluating Pedestrian Environment Using DeepLab Models Based on Street Walkability in Small and Medium-Sized Cities: Case Study in Gaoping, China," Sustainability, MDPI, vol. 14(22), pages 1-23, November.
    10. Richard R. Suminski & Gregory M. Dominick & Eric Plautz, 2019. "Validation of the Block Walk Method for Assessing Physical Activity occurring on Sidewalks/Streets," IJERPH, MDPI, vol. 16(11), pages 1-14, May.

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