Built environment correlates of walking for transportation: Differences between commuting and non-commuting trips
Keywords:walking, walking for transportation, built environment, commuting and non-commuting trips, China
As a sustainable mode of travel, walking for transportation has multiple environmental, social, and health-related benefits. In existing studies, however, such walking has rarely been differentiated between commuting and non-commuting trips. Using multilevel zero-inflated negative binomial regression and multilevel Tobit regression models, this study empirically examines the frequency and duration of commuting and non-commuting walking and their correlates in Xiamen, China. It finds that (1) non-commuting walking, on average, has a higher frequency and longer duration than commuting walking; (2) most socio-demographic variables are significant predictors, and age, occupation, and family size have opposite-direction effects on commuting and non-commuting walking; and (3) different sets of built environment variables are correlated with commuting and non-commuting walking, and the built environment collectively influences the latter more significantly than the former. The findings provide useful references for customized interventions concerning promoting commuting and non-commuting walking.
Bentley, R., Blakely, T., Kavanagh, A., Aitken, Z., King, T., McElwee, P., . . . Turrell, G. (2018). A longitudinal study examining changes in street connectivity, land use, and density of dwellings and walking for transport in Brisbane, Australia. Environmental Health Perspectives, 126(5), 057003.
Boakye-Dankwa, E., Barnett, A., Pachana, N. A., Turrell, G., & Cerin, E. (2019). Associations between latent classes of perceived neighborhood destination accessibility and walking behaviors in older adults of a low-density and a high-density city. Journal of Aging and Physical Activity, 27(4), 553–564.
Boakye-Dankwa, E., Nathan, A., Barnett, A., Busija, L., Lee, R. S., Pachana, N., . . . Cerin, E. (2019). Walking behaviour and patterns of perceived access to neighborhood destinations in older adults from a low-density (Brisbane, Australia) and an ultra-dense city (Hong Kong, China). Cities, 84, 23–33.
Calthorpe, P. (2016). China chokes on high-density sprawl. Retrieved from https://www.cnu.org/publicsquare/china-chokes-high-density-sprawl
Cats, O., Reimal, T., & Susilo, Y. (2014). Public transport pricing policy: Empirical evidence from a fare-free scheme in Tallinn, Estonia. Transportation Research Record, 2415(1), 89–96.
Celis-Morales, C. A., Lyall, D. M., Welsh, P., Anderson, J., Steell, L., Guo, Y., . . . Sattar, N. (2017). Association between active commuting and incident cardiovascular disease, cancer, and mortality: Prospective cohort study. The BMJ, 357, j1456.
Chan, E. T., Schwanen, T., & Banister, D. (2019). The role of perceived environment, neighbourhood characteristics, and attitudes in walking behaviour: Evidence from a rapidly developing city in China. Transportation, 48, 431–454.
Cheng, L., Caset, F., De Vos, J., Derudder, B., & Witlox, F. (2019). Investigating walking accessibility to recreational amenities for elderly people in Nanjing, China. Transportation Research Part D: Transport and Environment, 76, 85–99.
Cheng, L., Chen, X., Yang, S., Cao, Z., De Vos, J., & Witlox, F. (2019). Active travel for active aging in China: The role of built environment. Journal of Transport Geography, 76, 142–152.
Cheng, L., De Vos, J., Zhao, P., Yang, M., & Witlox, F. (2020). Examining non-linear built environment effects on elderly’s walking: A random forest approach. Transportation Research Part D: Transport and Environment, 88, 102552.
Cho, G.-H., & Rodríguez, D. A. (2015). Neighborhood design, neighborhood location, and three types of walking: Results from the Washington, DC area. Environment and Planning B: Planning and Design, 42(3), 526–540.
Christiansen, L. B., Cerin, E., Badland, H., Kerr, J., Davey, R., Troelsen, J., . . . Sugiyama, T. (2016). International comparisons of the associations between objective measures of the built environment and transport-related walking and cycling: IPEN adult study. Journal of Transport & Health, 3(4), 467–478.
Chudyk, A. M., Winters, M., Moniruzzaman, M., Ashe, M. C., Gould, J. S., & McKay, H. (2015). Destinations matter: The association between where older adults live and their travel behavior. Journal of Transport & Health, 2(1), 50–57.
Day, K. (2016). Built environmental correlates of physical activity in China: A review. Preventive Medicine Reports, 3, 303–316.
Ding, C., Liu, C., Zhang, Y., Yang, J., & Wang, Y. (2017). Investigating the impacts of built environment on vehicle miles traveled and energy consumption: Differences between commuting and non-commuting trips. Cities, 68, 25–36.
Ding, C., Wang, Y., Tang, T., Mishra, S., & Liu, C. (2018). Joint analysis of the spatial impacts of built environment on car ownership and travel mode choice. Transportation Research Part D: Transport and Environment, 60, 28–40.
Ewing, R., & Cervero, R. (2001). Travel and the built environment: A synthesis. Transportation Research Record, 1780(1), 87–114.
Ewing, R., & Cervero, R. (2010). Travel and the built environment: A meta-analysis. Journal of the American Planning Association, 76(3), 265–294.
Ewing, R., Greenwald, M., Zhang, M., Walters, J., Feldman, M., Cervero, R., & Thomas, J. (2009). Measuring the impact of urban form and transit access on mixed use site trip generation rates—Portland pilot study. Washington, DC: US Environmental Protection Agency.
Ewing, R., Tian, G., Goates, J., Zhang, M., Greenwald, M. J., Joyce, A., . . . Greene, W. (2015). Varying influences of the built environment on household travel in 15 diverse regions of the United States. Urban Studies, 52(13), 2330–2348.
Fan, J. X., Wen, M., & Wan, N. (2017). Built environment and active commuting: Rural-urban differences in the US. SSM-Population Health, 3, 435–441.
Forsyth, A., Hearst, M., Oakes, J. M., & Schmitz, K. H. (2008). Design and destinations: Factors influencing walking and total physical activity. Urban Studies, 45(9), 1973–1996.
Forsyth, A., Oakes, J. M., Lee, B., & Schmitz, K. H. (2009). The built environment, walking, and physical activity: Is the environment more important to some people than others? Transportation Research Part D: Transport and Environment, 14(1), 42–49.
Ghani, F., Rachele, J. N., Washington, S., & Turrell, G. (2016). Gender and age differences in walking for transport and recreation: Are the relationships the same in all neighborhoods? Preventive Medicine Reports, 4, 75–80.
Giles-Corti, B., Timperio, A., Bull, F., & Pikora, T. (2005). Understanding physical activity environmental correlates: Increased specificity for ecological models. Exercise and Sport Sciences Reviews, 33(4), 175–181.
Handy, S., Cao, X., & Mokhtarian, P. L. (2006). Self-selection in the relationship between the built environment and walking: Empirical evidence from Northern California. Journal of the American Planning Association, 72(1), 55–74.
Hanson, S., & Jones, A. (2015). Is there evidence that walking groups have health benefits? A systematic review and meta-analysis. British Journal of Sports Medicine, 49(11), 710–715.
Hatamzadeh, Y., Habibian, M., & Khodaii, A. (2020). Measuring walking behavior in commuting to work: Investigating the role of subjective, environmental and socioeconomic factors in a structural model. International Journal of Urban Sciences, 24(2), 173–188.
Herrmann-Lunecke, M. G., Mora, R., & Vejares, P. (2021). Perception of the built environment and walking in pericentral neighbourhoods in Santiago, Chile. Travel Behavior and Society, 23, 192–206.
Hou, Y. (2019). Polycentric urban form and non-work travel in Singapore: A focus on seniors. Transportation Research Part D: Transport and Environment, 73, 245–275.
Hox, J. (1998). Multilevel modeling: When and why. In Classification, data analysis, and data highways (pp. 147–154). New York: Springer.
Huang, R., Moudon, A. V., Zhou, C., & Saelens, B. E. (2019). Higher residential and employment densities are associated with more objectively measured walking in the home neighborhood. Journal of Transport & Health, 12, 142–151.
Kamruzzaman, M., Washington, S., Baker, D., Brown, W., Giles-Corti, B., & Turrell, G. (2016). Built environment impacts on walking for transport in Brisbane, Australia. Transportation, 43(1), 53–77.
Kang, B., Moudon, A. V., Hurvitz, P. M., & Saelens, B. E. (2017). Differences in behavior, time, location, and built environment between objectively measured utilitarian and recreational walking. Transportation Research Part D: Transport and Environment, 57, 185–194.
Kang, C.-D. (2017). Measuring the effects of street network configurations on walking in Seoul, Korea. Cities, 71, 30–40.
Kang, C.-D. (2018). The S + 5Ds: Spatial access to pedestrian environments and walking in Seoul, Korea. Cities, 77, 130–141.
Koohsari, M. J., Sugiyama, T., Lamb, K. E., Villanueva, K., & Owen, N. (2014). Street connectivity and walking for transport: Role of neighborhood destinations. Preventive Medicine, 66, 118–122.
Koohsari, M. J., Sugiyama, T., Shibata, A., Ishii, K., Liao, Y., Hanibuchi, T., . . . Oka, K. (2017). Associations of street layout with walking and sedentary behaviors in an urban and a rural area of Japan. Health & Place, 45, 64–69.
Lachapelle, U., & Jean-Germain, F. (2019). Personal use of the Internet and travel: Evidence from the Canadian General Social Survey’s 2010 time use module. Travel Behavior and Society, 14, 81–91.
Larrañaga, A. M., Rizzi, L. I., Arellana, J., Strambi, O., & Cybis, H. B. B. (2016). The influence of built environment and travel attitudes on walking: A case study of Porto Alegre, Brazil. International Journal of Sustainable Transportation, 10(4), 332–342.
Lee, I.-M., & Buchner, D. M. (2008). The importance of walking to public health. Medicine & Science in Sports & Exercise, 40(7), S512–S518.
Lin, L., & Moudon, A. V. (2010). Objective versus subjective measures of the built environment, which are most effective in capturing associations with walking? Health & Place, 16(2), 339–348.
Litman, T. (2010). Quantifying the benefits of nonmotorized transportation for achieving mobility management objectives. Victoria, BC, Canada: Victoria Transport Policy Institute.
Liu, C., Susilo, Y. O., & Karlström, A. (2017). Jointly modelling individual’s daily activity-travel time use and mode share by a nested multivariate Tobit model system. Transportmetrica A: Transport Science, 13(6), 491–518.
Liu, J., Wang, B., & Xiao, L. (2021). Non-linear associations between built environment and active travel for working and shopping: An extreme gradient boosting approach. Journal of Transport Geography, 92, 103034.
Lu, Y., Sun, G., Sarkar, C., Gou, Z., & Xiao, Y. (2018). Commuting mode choice in a high-density city: Do land-use density and diversity matter in Hong Kong? International Journal of Environmental Research and Public Health, 15(5), 920.
Lu, Y., Xiao, Y., & Ye, Y. (2017). Urban density, diversity and design: Is more always better for walking? A study from Hong Kong. Preventive Medicine, 103, S99–S103.
Maizlish, N., Linesch, N. J., & Woodcock, J. (2017). Health and greenhouse gas mitigation benefits of ambitious expansion of cycling, walking, and transit in California. Journal of Transport & Health, 6, 490–500.
McDonald, J. F., & Moffitt, R. A. (1980). The uses of Tobit analysis. The Review of Economics and Statistics, 62(2)318–321.
McKenzie, B. (2017). Modes less traveled—bicycling and walking to work in the United States: 2008–2012. Washington, DC: U.S. Census Bureau.
Næss, P., Strand, A., Wolday, F., & Stefansdottir, H. (2019). Residential location, commuting and non-work travel in two urban areas of different size and with different center structures. Progress in Planning, 128, 1–36.
Neves, C. E. T., da Silva, A. R., & de Arruda, F. S. (2021). Exploring the link between built environment and walking choice in São Paulo city, Brazil. Journal of Transport Geography, 93, 103064.
Ng, S. W., Norton, E. C., & Popkin, B. M. (2009). Why have physical activity levels declined among Chinese adults? Findings from the 1991–2006 China Health and Nutrition Surveys. Social Science & Medicine, 68(7), 1305–1314.
Ozbilen, B., Wang, K., & Akar, G. (2021). Revisiting the impacts of virtual mobility on travel behavior: An exploration of daily travel time expenditures. Transportation Research Part A: Policy and Practice, 145, 49–62.
Paul, P., Carlson, S. A., Carroll, D. D., Berrigan, D., & Fulton, J. E. (2015). Walking for transportation and leisure among US adults—National Health Interview Survey 2010. Journal of Physical Activity and Health, 12(s1), S62–S69.
Pucher, J., Buehler, R., Bassett, D. R., & Dannenberg, A. L. (2010). Walking and cycling to health: A comparative analysis of city, state, and international data. American Journal of Public Health, 100(10), 1986–1992.
Saelens, B. E., & Handy, S. L. (2008). Built environment correlates of walking: A review. Medicine and Science in Sports and Exercise, 40(7 Suppl), S550.
Schneider, R. J. (2015). Local environment characteristics associated with walking and taking transit to shopping districts. Journal of Transport and Land Use, 8(2), 125–147.
Shen, J., Cheng, J., Huang, W., & Zeng, F. (2020). An exploration of spatial and social inequalities of urban sports facilities in Nanning City, China. Sustainability, 12(11), 4353.
Sun, B., Zhang, T., He, Z., & Wang, R. (2017). Urban spatial structure and motorization in China. Journal of Regional Science, 57(3), 470–486.
Ta, N., Chai, Y., Zhang, Y., & Sun, D. (2017). Understanding job-housing relationship and commuting pattern in Chinese cities: Past, present and future. Transportation Research Part D: Transport and Environment, 52, 562–573.
Tobin, J. (1958). Estimation of relationships for limited dependent variables. Econometrica: Journal of the Econometric Society, 24–36.
Tschentscher, M., Niederseer, D., & Niebauer, J. (2013). Health benefits of Nordic walking: A systematic review. American Journal of Preventive Medicine, 44(1), 76–84.
Vale, D. S., & Pereira, M. (2016). Influence on pedestrian commuting behavior of the built environment surrounding destinations: A structural equations modeling approach. International Journal of Sustainable Transportation, 10(8), 730–741.
Wang, J., & Cao, X. (2017). Exploring built environment correlates of walking distance of transit egress in the Twin Cities. Journal of Transport Geography, 64, 132–138.
Wang, R., & Yuan, Q. (2013). Parking practices and policies under rapid motorization: The case of China. Transport Policy, 30, 109–116.
Wang, Z., Ettema, D., & Helbich, M. (2021). Objective environmental exposures correlate differently with recreational and transportation walking: A cross-sectional national study in the Netherlands. Environmental Research, 194, 110591.
Wood, L., Frank, L. D., & Giles-Corti, B. (2010). Sense of community and its relationship with walking and neighborhood design. Social Science & Medicine, 70(9), 1381–1390.
Yang, L., Wang, Y., Han, S., & Liu, Y. (2019). Urban transport carbon dioxide (CO2) emissions by commuters in rapidly developing cities: The comparative study of Beijing and Xi’an in China. Transportation Research Part D: Transport and Environment, 68, 65–83.
Yau, K. K., Wang, K., & Lee, A. H. (2003). Zero‐inflated negative binomial mixed regression modeling of over‐dispersed count data with extra zeros. Biometrical Journal: Journal of Mathematical Methods in Biosciences, 45, 437-452.
Zhang, Y., Li, Y., Liu, Q., & Li, C. (2014). The built environment and walking activity of the elderly: An empirical analysis in the Zhongshan metropolitan area, China. Sustainability, 6(2), 1076–1092.
Zhao, P., & Wan, J. (2020). Examining the effects of neighborhood design on walking in growing megacity. Transportation Research Part D: Transport and Environment, 86, 102417.
How to Cite
Copyright (c) 2021 Jixiang Liu, Jiangping Zhou, Longzhu Xiao
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with JTLU agree to the following terms: 1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution-Noncommercial License 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. 2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. 3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.