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Exploring the link between built environment and walking choice in São Paulo city, Brazil

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  • Neves, Carlos Eduardo Teixeira
  • da Silva, Alan Ricardo
  • Arruda, Fabiana Serra de

Abstract

This study assesses the connection between the walking choice and built environment characteristics in São Paulo city, Brazil. Trips to work and school were considered because they are the most representative motives to travel in the city, corresponding to more than 70% of the trips. The traditional logit model is applied, having as the dependent variable the choice for walking and as explicative variables, the built environment and socioeconomic variables. The results indicate that, for the city of Sao Paulo, built environment variables are more relevant at the origin and the dimension most related to walking choice is diversity, probably due to socioeconomic reason. The characteristics of individuals also have significant effects, as well as age, gender and income, and this study concludes that they must be considered in the development of local public policies to encourage walking. Also, in developing countries, the D's theories might have some application limits. Apparently, the theory is applicable to a greater social equality context, and in contexts of grater social inequalities there is no influence of built environment on walking choices.

Suggested Citation

  • Neves, Carlos Eduardo Teixeira & da Silva, Alan Ricardo & Arruda, Fabiana Serra de, 2021. "Exploring the link between built environment and walking choice in São Paulo city, Brazil," Journal of Transport Geography, Elsevier, vol. 93(C).
  • Handle: RePEc:eee:jotrge:v:93:y:2021:i:c:s0966692321001174
    DOI: 10.1016/j.jtrangeo.2021.103064
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    Cited by:

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    3. Peng Zang & Hualong Qiu & Fei Xian & Linchuan Yang & Yanan Qiu & Hongxu Guo, 2022. "Nonlinear Effects of the Built Environment on Light Physical Activity among Older Adults: The Case of Lanzhou, China," IJERPH, MDPI, vol. 19(14), pages 1-15, July.
    4. Yang, Wei & Hu, Jie & Liu, Yong & Guo, Wenbo, 2023. "Examining the influence of neighborhood and street-level built environment on fitness jogging in Chengdu, China: A massive GPS trajectory data analysis," Journal of Transport Geography, Elsevier, vol. 108(C).

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