Walkability indices and travel behavior: Insights from Montréal, Canada

Hisham Negm

McGill University

https://orcid.org/0000-0002-1464-2640

Ahmed El-Geneidy

McGill University

https://orcid.org/0000-0002-0942-4016

DOI: https://doi.org/10.5198/jtlu.2025.2612

Keywords: Walkability, Index, Travel behavior, Shopping, North America


Abstract

Walkability indices are developed to evaluate the quality of the built environment and its suitability for walking. Over the past decade, several walkability indices were developed and promoted by public and private entities around the world. Comparing and validating these indices are essential to ensuring their reliability for adoption in practice. One method to validate such indices is to examine their predictive power for utilitarian and discretionary walking behavior. This study uses data from a large-scale travel survey (N=4,715), conducted in Montréal, Canada, to examine the predictive power of six region-specific walkability indices on weekly walking mode share for various purposes, namely work, school, shopping, leisure, and healthcare. We find that the Canadian Active Living Environments (Can-ALE) index and its extended version, Can-ALE/Transit, are the best predictors of overall weekly walking mode share for all purposes combined, shopping, and leisure activities. Walk Score® had the highest predictive power on walking behavior for healthcare purposes. While the cumulative opportunities measure (30-minute travel time) was the most effective for predicting commute walking behavior. This research provides valuable insights for practitioners and policymakers, guiding them in selecting the most suitable walkability indices to promote walking behavior in the Canadian context.


References

Anik, M., & Habib, M. (2023). COVID-19 and teleworking: Lessons, current issues and future directions for transport and land-use planning. Transportation Research Record, 2678(12), 554–566. https://doi.org/10.1177/03611981231166384

Arvidsson, D., Kawakami, N., Ohlsson, H., & Sundquist, K. (2012). Physical activity and concordance between objective and perceived walkability. Medicine and Science Sports and Exercise, 44(2), 280–287. https://doi.org/10.1249/MSS.0b013e31822a9289

Aziz, H., Nagle, N., Morton, A., Hilliard, M., White, D., & Stewart, R. (2018). Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: A random parameter model using New York City commuter data. Transportation, 45(5), 1207–1229. https://doi.org/10.1007/s11116-017-9760-8

Birkenfeld, C., Victoriano-Habit, R., Alousi-Jones, M., Soliz, A., & El-Geneidy, A. (2023). Who is living a local lifestyle? Towards a better understanding of the 15-minute-city and 30-minute-city concepts from a behavioral perspective in Montréal, Canada. Journal of Urban Mobility, 3, 100048. https://doi.org/10.1016/j.urbmob.2023.100048

Björnberg, E., Hansson, S., Belin, M., & Tingvall, C. (2019). The vision zero handbook: Theory, technology and management for a zero casualty policy. New York; Springer.

Cambra, P., & Moura, F. (2020). How does walkability change relate to walking behavior change? Effects of a street improvement in pedestrian volumes and walking experience. Journal of Transport & Health, 16, 100797. https://doi.org/10.1016/j.jth.2019.100797

Carr, L., Dunsiger, S., & Marcus, B. (2011). Validation of walk score for estimating access to walkable amenities. British Journal of Sports Medicine, 45(14), 1144–1148. https://doi.org/10.1136/bjsm.2009.069609

Cepeda, M., Schoufour, J., Freak-Poli, R., Koolhaas, C., Dhana, K., Bramer, W., & Franco, O. (2017). Levels of ambient air pollution according to mode of transport: A systematic review. The Lancet Public Health, 2(1), e23–e34. https://doi.org/10.1016/S2468-2667(16)30021-4

Cervero, R. (2002). Built environments and mode choice: Toward a normative framework. Transportation Research Part D: Transport and Environment, 7(4), 265–284. https://doi.org/10.1016/S1361-9209(01)00024-4

Christian, H., Bull, F., Middleton, N., Knuiman, M., Divitini, M., Hooper, P., …, & Giles-Corti, B. (2011). How important is the land use mix measure in understanding walking behavior? Results from the RESIDE study. International Journal of Behavioral Nutrition and Physical Activity, 8(1), 55. https://doi.org/10.1186/1479-5868-8-55

Clifton, K., Livi Smith, A., & Rodriguez, D. (2007). The development and testing of an audit for the pedestrian environment. Landscape and Urban Planning, 80(1), 95–110. https://doi.org/10.1016/j.landurbplan.2006.06.008

Cui, B., Boisjoly, G., Miranda-Moreno, L., & El-Geneidy, A. (2020). Accessibility matters: Exploring the determinants of public transport mode share across income groups in Canadian cities. Transportation Research Part D: Transport and Environment, 80, 102276. https://doi.org/10.1016/j.trd.2020.102276

De Vos, J., Lättman, K., van der Vlugt, A., Welsch, J., & Otsuka, N. (2023). Determinants and effects of perceived walkability: A literature review, conceptual model and research agenda. Transport Reviews, 43(2), 303–324. https://doi.org/10.1080/01441647.2022.2101072

DeBell, M., & Krosnick, J. (2009). Computing weights for American National Election Study survey data (ANES technical report series, no. nes012427). Retrieved from http://www.electionstudies.org

Ewing, R., & Cervero, R. (2010). Travel and the built environment. Journal of the American Planning Association, 76(3), 265–294. https://doi.org/10.1080/01944361003766766

Ewing, R., & Handy, S. (2009). Measuring the unmeasurable: Urban design qualities related to walkability. Journal of Urban Design, 14(1), 65–84. https://doi.org/10.1080/13574800802451155

Ferdman, A. (2019). Walking and its contribution to Objective well-being. Journal of Planning Education and Research, 43(2), 294–304. https://doi.org/10.1177/0739456X19875195

Frank, L., Sallis, J., Conway, T., Chapman, J., Saelens, B., & Bachman, W. (2006). Many pathways from land use to health: Associations between neighborhood walkability and active transportation, body mass index, and air quality. Journal of the American Planning Association, 72(1), 75–87. https://doi.org/10.1080/01944360608976725

Gebel, K., Bauman, A., & Owen, N. (2009). Correlates of non-concordance between perceived and objective measures of walkability. Annals of Behavioral Medicine, 37(2), 228_238. https://doi.org/10.1007/s12160-009-9098-3

Giles-Corti, B., Macaulay, G., Middleton, N., Boruff, B., Bull, F., Butterworth, I., …, & Christian, H. (2014). Developing a research and practice tool to measure walkability: A demonstration project. Health Promotion Journal of Australia, 25(3), 160–166. https://doi.org/10.1071/HE14050

Hall, M., & Ram, Y. (2018). Walk score® and its potential contribution to the study of active transport and walkability: A critical and systematic review. Transportation Research Part D: Environment, 61, 310–324.

Herrmann, T., Boisjoly, G., Ross, N., & El-Geneidy, A. (2017). The missing middle: Filling the gap between walkability and observed walking behavior. Transportation Research Record, 2661, 103–110.

Herrmann, T., Gleckner, W., Wasfi, R., Thierry, B., Kestens, Y., & Ross, N. (2019). A pan-Canadian measure of active living environments using open data. Health Reports, 30(5), 16–25. https://doi.org/10.25318/82-003-x201900500002-eng

Hino, K., Baba, H., Kim, H., & Shimizu, C. (2022). Validation of a Japanese walkability index using large-scale step count data of Yokohama citizens. Cities, 123, 103614. https://doi.org/10.1016/j.cities.2022.103614

Javadinasr, M., Maggasy, T., Mohammadi, M., Mohammadain, K., Rahimi, E., Salon, D., …, & Derrible, S. (2022). The long-term effects of COVID-19 on travel behavior in the United States: A panel study on work from home, mode choice, online shopping, and air travel. Transportation Research Part F: Traffic Psychology and Behavior, 90, 466–484. https://doi.org/10.1016/j.trf.2022.09.019

Johansson, R. (2009). Vision zero–Implementing a policy for traffic safety. Safety Science, 47(6), 826–831. https://doi.org/10.1016/j.ssci.2008.10.023

Ki, D., Chen, Z., Lee, S., & Lieu, S. (2023). A novel walkability index using google street view and deep learning. Sustainable Cities and Society, 99, 104896. https://doi.org/10.1016/j.scs.2023.104896

Kim, E., Muennig, P., & Rosen, Z. (2017). Vision zero: A toolkit for road safety in the modern era. Injury Epidemiology, 4(1), 1. https://doi.org/10.1186/s40621-016-0098-z

Krambeck, H. (2006). The global walkability index. Cambridge, MA: Massachusetts Institute of Technology.

Kuzmyak, J., Baber, C., & Savory, D. (2005). Use of walk opportunities index to quantify local accessibility. Transportation Research Record, 1977, 145–153.

Labdaoui, K., Mazouz, S., Acidi, A., Cools, M., Moeinaddini, M., & Teller, J. (2021). Utilizing thermal comfort and walking facilities to propose a comfort walkability index (CWI) at the neighborhood level. Building and Environment, 193, 107627. https://doi.org/10.1016/j.buildenv.2021.107627

Lam, T., Wang, Z., Vaartjes, I., Karssenberg, D., Ettema, D., Helbich, M., …, & Lakerveld, J. (2022). Development of an objectively measured walkability index for the Netherlands. International Journal of Behavioral Nutrition and Physical Activity, 19(1), 50. https://doi.org/10.1186/s12966-022-01270-8

Lefebvre-Ropars, G., & Morency, C. (2018). Walkability: Which measure to choose, where to measure it, and how? Transportation Research Record, 2672(35), 139–150. https://doi.org/10.1177/0361198118787095

Logan, T., Hobbs, M., Conrow, L., Reid, N., Young, R., & Anderson, M. (2022). The x-minute city: Measuring the 10, 15, 20-minute city and an evaluation of its use for sustainable urban design. Cities, 131, 103924. https://doi.org/10.1016/j.cities.2022.103924

Lu, M., & Diab, E. (2023). Understanding the determinants of x-minute city policies: A review of the North American and Australian cities’ planning documents. Journal of Urban Mobility, 3, 100040. https://doi.org/10.1016/j.urbmob.2022.100040

Manaugh, K., & El-Geneidy, A. (2011). Validating walkability indices: How do different households respond to the walkability of their neighborhood? Transportation Research Part D: Transport and Environment, 16(4), 309–315. https://doi.org/10.1016/j.trd.2011.01.009

Mayne, D., Morgan, G., Willmore, A., Rose, N., Jalaludin, B., Bambrick, H., & Bauman, A. (2013). An objective index of walkability for research and planning in the Sydney metropolitan region of New South Wales, Australia: An ecological study. International Journal of Health Geographics, 12(1), 61. https://doi.org/10.1186/1476-072X-12-61

Millstein, R., Cain, K., Sallis, J., Conway, T., Geremia, C., Frank, L., …, & Saelens, B. (2013). Development, scoring, and reliability of the microscale audit of pedestrian streetscapes (MAPS). BMC Public Health, 13(1), 403. https://doi.org/10.1186/1471-2458-13-403

Mueller, N., Rojas-Rueda, D., Cole-Hunter, T., de Nazelle, A., Dons, E., Gerike, R., …, & Nieuwenhuijsen, M. (2015). Health impact assessment of active transportation: A systematic review. Preventive Medicine, 76, 103–114. https://doi.org/10.1016/j.ypmed.2015.04.010

Negm, H., & El-Geneidy, A. (2024). Exploring the changes in the interrelation between public transit mode share and accessibility across income groups in major Canadian cities in the post-pandemic era. Journal of Transport Geography, 115, 103792. https://doi.org/10.1016/j.jtrangeo.2024.103792

Negm, H., Miller, H., & El-Geneidy, A. (2023). Exploring the x-minute city by travel purpose in Montréal, Canada. Findings. https://doi.org/10.32866/001c.77506.

Panter, J., & Jones, A. (2010). Attitudes and the environment as determinants of active travel in adults: What do and don’t we know? Journal of Physical Activity and Health, 7(4), 551–561. https://doi.org/10.1123/jpah.7.4.551

Pasek, J. (2018). Anesrake: ANES raking implementation. R package version 0.80. Retrieved from https://CRAN.R-project.org/package=anesrake

Pereira, R., Saraiva, M., Herszenhut, D., Braga, C., & Conway, M. (2021). r5r: Rapid realistic routing on multimodal transport networks with R5 in R. Findings, 21262. https://doi.org/10.32866/001c.21262

Pfeffermann, D. (1993). The role of sampling weights when modeling survey data. International Statistical Review, 61(2), 317–337. https://doi.org/10.2307/1403631

Porta, S., & Renne, J. (2005). Linking urban design to sustainability: Formal indicators of social urban sustainability field research in Perth, Western Australia. Urban Design International, 10(1), 51–64. http://dx.doi.org/10.1057/palgrave.udi.9000136

Ramel-Delobel, M., Heydari, S., de Nazelle, A., Praud, D., Salizzoni, P., Fervers, B., & Coudon, T. (2024). Air pollution exposure in active versus passive travel modes across five continents: A Bayesian random-effects meta-analysis. Environmental Research, 261, 119666. https://doi.org/10.1016/j.envres.2024.119666

Rodrı́guez, D., & Joo, J. (2004). The relationship between non-motorized mode choice and the local physical environment. Transportation Research Part D: Transport and Environment, 9(2), 151–173. https://doi.org/https://doi.org/10.1016/j.trd.2003.11.001

Ross, N., Wasfi, R., Herrmann, T., & Gleckner, W. (2018). Canadian active living environments database (Can-ALE): User manual and technical document. Montreal, Canada: D. o. G. Geo-Social Determinants of Health Research Group, McGill University.

Rundle, A., Chen, Y., Quinn, J., Rahai, N., Bartley, K., Mooney, S., …, & Neckerman, K. (2019). Development of a neighborhood walkability index for studying neighborhood physical activity contexts in communities across the U.S. over the past three decades. Journal of Urban Health, 96(4), 583–590. https://doi.org/10.1007/s11524-019-00370-4

Rundle, A., Sheehan, D., Quinn, J., Bartley, K., Eisenhower, D., Bader, M., …, & Neckerman, K. (2016). Using GPS data to study neighborhood walkability and physical activity. American Journal of Preventive Medicine, 50(3), e65–e72. https://doi.org/https://doi.org/10.1016/j.amepre.2015.07.033

Saelens, B., & Handy, S. (2008). Built environment correlates of walking: A review. Medicine and Sciencie Sports and Exercise, 40(7 Suppl), S550–566. https://doi.org/10.1249/MSS.0b013e31817c67a4

Saelens, B., Sallis, J., Black, J., & Chen, D. (2003). Neighborhood-based differences in physical activity: An environment scale evaluation. American Journal of Public Health, 93(9), 1552–1558. https://doi.org/10.2105/AJPH.93.9.1552

Sallis, J., Saelens, B., Frank, L., Conway, T., Slymen, D., Cain, K., …, & Kerr, J. (2009). Neighborhood built environment and income: Examining multiple health outcomes. Social Science & Medicine, 68(7), 1285–1293. https://doi.org/10.1016/j.socscimed.2009.01.017

Scheiner, J., & Holz-Rau, C. (2007). Travel mode choice: Affected by objective or subjective determinants? Transportation, 34(4), 487–511. https://doi.org/10.1007/s11116-007-9112-1

Shashank, A., & Schuurman, N. (2019). Unpacking walkability indices and their inherent assumptions. Health & Place, 55, 145–154. https://doi.org/10.1016/j.healthplace.2018.12.005

Singleton, P. (2019). Walking (and cycling) to well-being: Modal and other determinants of subjective well-being during the commute. Travel Behavior and Society, 16, 249–261. https://doi.org/10.1016/j.tbs.2018.02.005

Statistics Canada. (2017). 2016 census of population. Statistics Canada catalogue no. 98-316-X2016001. Retrieved from https://www12.statcan.gc.ca/census-recensement/2016/dp-pd/prof/index.cfm?Lang=E

Statistics Canada. (2023a). 2021 census of population. Statistics Canada catalogue no. 98-316-X2021001. Retrieved from https://www12.statcan.gc.ca/census-recensement/2021/dp-pd/prof/index.cfm?Lang=E

Statistics Canada. (2023b). Spatial access measures. Retrieved from https://www150.statcan.gc.ca/n1/pub/27-26-0001/272600012023001-eng.htm

Stockton, J., Duke-Williams, O., Stamatakis, E., Mindell, J., Brunner, E., & Shelton, N. (2016). Development of a novel walkability index for London, United Kingdom: Cross-sectional application to the Whitehall II Study. BMC Public Health, 16(1), 416. https://doi.org/10.1186/s12889-016-3012-2

Tainio, M., Andersen, Z., Nieuwenhuijsen, M., Hu, L., de Nazelle, A., An, R., … , & Sá, T. (2021). Air pollution, physical activity and health: A mapping review of the evidence. Environment International, 147, 105954. https://doi.org/10.1016/j.envint.2020.105954

Tainio, M., de Nazelle, A., Götschi, T., Kahlmeier, S., Rojas-Rueda, D., Nieuwenhuijsen, M., ... , & Woodcock, J. (2016). Can air pollution negate the health benefits of cycling and walking? Preventive Medicine, 87, 233–236. https://doi.org/10.1016/j.ypmed.2016.02.002

Teixeira, J., Silva, C., Seisenberger, S., Büttner, B., McCormick, B., Papa, E., & Cao, M. (2024). Classifying 15-minute cities: A review of worldwide practices. Transportation Research Part A: Policy and Practice, 189, 104234. https://doi.org/10.1016/j.tra.2024.104234

Ton, D., Duives, D., Cats, O., Hoogendoorn-Lanser, S., & Hoogendoorn, S. (2019). Cycling or walking? Determinants of mode choice in the Netherlands. Transportation Research Part A: Policy and Practice, 123, 7–23. https://doi.org/https://doi.org/10.1016/j.tra.2018.08.023

Vale, D., Saraiva, M., & Pereira, M. (2015). Active accessibility: A review of operational measures of walking and cycling accessibility. Journal of Transport and Land Use, 9(1), 209–235. https://doi.org/10.5198/jtlu.2015.593

van Buuren, S., & Groothuis-Oudshoorn, K. (2011). Mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3), 1–67. https://doi.org/10.18637/jss.v045.i03

Victoriano-Habit, R., Negm, H., James, M., Goudis, P., & El-Geneidy, A. (2024). Measuring the impacts of the Réseau express métropolitain (REM): Progress report 2019-2023. Montreal, Canada: M. U. Transportation Research at McGill.

Ville de Montréal. (2022). Plan d’action vision zéro décès et blessé grave 2022–2024. Montreal, Canada: Ville de Montréal.

Vohra, K., Vodonos, A., Schwartz, J., Marais, E., Sulprizio, M., & Mickley, L. (2021). Global mortality from outdoor fine particle pollution generated by fossil fuel combustion: Results from GEOS-Chem. Environmental Research, 195, 110754. https://doi.org/10.1016/j.envres.2021.110754

von Bergmann, J., Shkolnik, D., & Jacobs, A. (2021). Cancensus: R package to access, retrieve, and work with Canadian census data and geography. R package version 0.4.2. Retrieved from https://mountainmath.github.io/cancensus/

Walk Score. (2024a). Walk Score API. Retrieved from https://www.walkscore.com/professional/api.php

Walk Score. (2024b). Walk Score methodology. Retrieved from https://www.walkscore.com/methodology.shtml

Watson, K., Whitfield, G., Thomas, J., Berrigan, D., Fulton, J., & Carlson, S. (2020). Associations between the national walkability index and walking among US adults — National health interview survey, 2015. Preventive Medicine, 137, 106122. https://doi.org/10.1016/j.ypmed.2020.106122

Woodcock, J., Edwards, P., Tonne, C., Armstrong, B., Ashiru, O., Banister, D., … , & Roberts, I. (2009). Public health benefits of strategies to reduce greenhouse-gas emissions: Urban land transport. The Lancet, 374(9705), 1930–1943. https://doi.org/10.1016/S0140-6736(09)61714-1

Yang, S., Chen, X., Wang, L., Wu, T., Fei, T., Xiao, Q., … , & Jia, P. (2021). Walkability indices and childhood obesity: A review of epidemiologic evidence. Obesity Reviews, 22(S1), e13096. https://doi.org/10.1111/obr.13096