The influence of urban form and socio-demographics on active transport: A 40-neighborhoods study in Chengdu, China

Authors

  • ChengHe Guan Harvard University
  • Ann Forsyth Harvard University

DOI:

https://doi.org/10.5198/jtlu.2020.1697

Keywords:

Urban form; active transport; non-motorized transport; neighborhood type; China

Abstract

In China, a centralized planning culture has created similar neighborhoods across the country. Using a survey of 1,048 individuals conducted in 2016 in Chengdu—located in a carefully conceptualized typology of neighborhood forms—we analyzed the associations between individual and neighborhood characteristics and active or nonmotorized transport behavior. Using several multiple logistic and multilevel models, we show how neighborhoods were categorized and how the number of categories or neighborhood types affected the magnitude of the associations with active transport but not the direction. People taking non-work trips were more likely to use active compared with motorized modes in all neighborhood types. Neighborhood type was significant in models but so too were many other individual-level variables and infrastructural and locational features such as bike lanes and location near the river. Of the 3-D physical environment variables, floor area ratio (a proxy for density) was only significant in one model for nonwork trips. Intersection density and dissimilarity (land-use diversity) were only significant in a model for work trips. This study shows that to develop strong theories about the connections between active transport and environments, it is important to examine different physical and cultural contexts and perform sensitivity analyses. Research in different parts of China can help provide a more substantial base for evidence-informed policymaking. Planning and design recommendations were made related to active transport need to consider how neighborhoods, built environments, and personal characteristics interact in different kinds of urban environments.

References

Baranowski, T., Cullen., K, Micklas, T., Thompson, D., and Baranowski, J. (2003). Are current health behavioral change models helpful in guiding prevention of weight gain efforts. Obesity Research, 11, 23–43.

Ben-Akiva, M., and Lerman, S. (1985). Discrete choice analysis. Cambridge, MA: MIT Press.

Boussauw, K., and Witlox, F. (2011). Linking expected mobility production to sustainable residential location planning: some evidence from Flanders. Journal of Transport Geography, 19 (4) 936–942.

Cerin, E., Nathan, A., van Cauwenberg, J., Barnett, D.W., & Barnett, A. (2017). The neighborhood hysical environment and active travel in older adults: A systematic review and meta-analysis. International Journal of Behavioral Nutrition and Physical Activity, 14, 15–38.

Cervero, R. (2013). Linking urban transport and land use in developing countries. Journal of Transport and Land Use, 6, 7–24.

Cervero, R., and Kockelman, K. (1997). Travel demand and the 3Ds: Density, diversity, and design. Transportation Research Part D: Transport and Environment, 2(3), 199–219.

Chengdu Statistics Bureau (CSB). (2017). Chengdu statistics yearbook, 2016. Chengdu: Chengdu Statistics Press.

China Sustainable Transportation Center (2012). China urban non-motorized transport system planning and design guideline. http://www.chinastc.org/en/project/50/397

Day, K. (2016). Built environmental correlates of physical activity in China: A review. Preventive Medicine Reports, 3, 303–316.

D’Haese, S., Vanwolleghem, G., Hinckson, E., De Bourdeaudhuij, I., Deforche, B., Van Dyck, D., & Cardon, G. (2015). Cross-continental comparison of the association between the physical environment and active transportation in children: A systematic review. International Journal of Behavioral Nutrition and Physical Activity, 12, 145–157.

Ewing, R., & Cervero, R. (2010). Travel and the built environment: a meta-analysis. Journal of American Planning Association, 76(3), 265–294.

Feng, J., Dijst, M., Wissink, B., & Prillwitz, J. (2014). Understanding mode choice in the Chinese context: The case of Nanjing metropolitan area. Tijdschrift Voor Economische En Sociale Geografie, 105(3), 315–330.

Forsyth, A., & Crewe, K. (2009). A typology of comprehensive designed communities since the second

world war. Landscape Journal, 28(1), 56–78.

Forsyth, A., & Krizek, K. (2010). Promoting walking and bicycling: Assessing the evidence to assist planners. Built Environment, 36(4), 429–446.

Gao, M., Ahern, J., & Koshland, C. P. (2016). Perceived built environment and health-related quality of life in four types of neighborhoods in Xi’an, China. Health and Place, 39, 110–115.

Guan, C., Srinivasan, S., & Nielsen, C. (2019) Does neighborhood form influence low-carbon transportation in China? Transportation and Research Part D: Transport and Environment 67, 406–420.

Guan, C., Srinivasan, S., Zhang, B., Da, L., Liu, J., & Nielsen, C. (2020) The influence of neighborhood types on active transport in China’s growing cities. Transportation and Research Part D: Transport and Environment 80, 102273. doi: 10.1016/j.trd.2020.102273

He, S., & Lin, G. (2015). Producing and consuming China’s new urban space: State, market and society, Urban Studies, 52(15), 2757–2773.

Hu, L., Yang, J., Yang, T., Tu, Y., & Zhu, J. (2019). Urban spatial structure and travel in China. Journal of Planning Literature. Online first.

Kaufman, L., & Rousseeuw, P. J. (1990). Finding groups in data. John Wiley & Sons, New York, 1990.

Krizek, K., Handy, S., & Forsyth, A. (2009). Explaining changes in walking and bicycling behavior: Challenges for transportation research. Environment and Planning B 36: 725–740.

Lin, L. (2018). Leisure-time physical activity, objective urban neighborhood built environment, and overweight and obesity of Chinese school-age children. Journal of Transport & Health. In press.

Lu, Y., Xiao, Y., & Ye, Y. (2016). Urban density, diversity and design: Is more always better for walking? A study from Hong Kong. Preventive Medicine 103: S99–S103.

National Bureau of Statistics of China (2016). China statistical yearbook. China Statistics Press: Beijing.

National Resources Defense Council (2017). The China urban walkability report. https://www.nrdc.org/china

Nilsson, I., & Delmelle, E. (2018). Transit investments and neighborhood change: On the likelihood of change. Journal of Transport Geography, 66, 167–179.

Pan, H., Shen, Q., & Zhang, M. (2009). Influence of urban form on travel behaviour in four neighborhoods of Shanghai. Urban Studies, 46(2), 275–294.

Pindyck, R., & Rubinfeld, D. (1998). Econometric models and economic forecasts, 4th edition. New York: McGraw-Hill.

Qin, B. (2015). City profile: Chengdu. Cities, 43, 18–27.

Research Center for Contemporary China, Peking University. (2016). Chengdu Survey, 2016, The Sampling and Fieldwork Report. Collection of the authors.

Sakar, C., Webster, C., & Gallacher, J. (2017). Association between adiposity outcomes and residential density: A full-data, cross-sectional analysis of 419 562 UK Biobank adult participants. Lancet Planet Health 1: e277–288.

Shen, Y., Chai, Y., & Kwan, M. (2015). Space-time fixity and flexibility of daily activities and the built environment: A case study of different types of communities in Beijing suburbs. Journal of Transport Geography, 47, 90–99.

Smith, M., Hosking, J., Woodward, A., Witten, K., MacMillan, A.,…Mackie, H. (2017). Systematic literature review of built environment effects on physical activity and active transport—an update and new findings on health equity. International Journal of Behavioral Nutrition and Physical Activity, 14, 158 (27pp).

Srinivasan, S., Guan, C., Nielsen, C. (2019) Built environment, income and travel behavior: Change in the city of Chengdu, China 2005-2016. International Journal of Sustainable Transportation 14(10), 749–760. doi: 10.1080/15568318.2019.1625088

Su, X. (2015) Urban entrepreneurialism and the commodification of heritage in China. Urban Studies, 52(15) 2874-2889. doi: 10.1177/0042098014528998

Wang, D., & Chai, Y. (2009). The jobs-housing relationship and commuting to Beijing, China: The legacy of Danwei. Journal of Transport Geography 17, 30–38.

Wang, D., & Zhou, M. (2017). The built environment and travel behavior in urban China: A literature review. Transportation Research Part D, 52, 574–585.

Wu, H., Chen, Y., & Jiao, J. (2019). Impact of neighborhood built environments on shopping travel modes in Shanghai, China. Transportation Research Record, 2673(8), 669–681.

Yang, J. (2010). Spatial and social characteristics of urban transportation in Beijing. Transportation Research Record: Journal of the Transportation Research Board, 2193, 59–67.

Zhao, Y., & Chai, Y. (2013). Residents’ activity-travel behavior variation by communities in Beijing, China. Chinese Geographical Science, 23(4), 492–505.

Zhao, P., Lu, B., & Roo, G. (2011). Impact of the jobs-housing balance on urban commuting in Beijing in the transformation era. Journal of Transport Geography, 19, 59–69.

Downloads

Published

2020-11-05

How to Cite

Guan, C., & Forsyth, A. (2020). The influence of urban form and socio-demographics on active transport: A 40-neighborhoods study in Chengdu, China. Journal of Transport and Land Use, 13(1), 367–388. https://doi.org/10.5198/jtlu.2020.1697

Issue

Section

Articles