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Examining non-linear associations between built environments around workplace and adults’ walking behaviour in Shanghai, China

Author

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  • Yang, Haoran
  • Zhang, Qinran
  • Helbich, Marco
  • Lu, Yi
  • He, Dongsheng
  • Ettema, Dick
  • Chen, Long

Abstract

Considering that most working adults spend nearly half their waking time at work, creating a supportive built environment around workplaces could be a feasible approach to maintain adequate levels of physical activity. However, the extent to which the built environment around workplaces influences walking behaviors in working adults remains unclear. Using survey data of 1009 full-time employees in Shanghai, China, this study assessed the nonlinear relationships between the built environment characteristics around workplaces and three domains of walking behaviors (commuting, utilitarian, and recreational walking). Using gradient boosting decision trees, our results showed that the built environment around workplaces is crucial for higher levels of walking behaviors, but built environment features tended to have distinctive associations with different domains of walking behaviors. Specifically, the number of physical activity facilities was positively associated with all three domains of walking behaviors, while a high floor area ratio was negatively associated with different domains of walking behaviors to some extent. Furthermore, several built environment characteristics, such as land use entropy, street view greenery, distance from home to the city center, and distance between the city center and workplaces had distinctive associations with different domains of walking behaviors. The findings of this study could provide nuanced guidance for creating pedestrian-friendly environments around workplaces to promote walking behaviors and overall physical activity levels in the working population.

Suggested Citation

  • Yang, Haoran & Zhang, Qinran & Helbich, Marco & Lu, Yi & He, Dongsheng & Ettema, Dick & Chen, Long, 2022. "Examining non-linear associations between built environments around workplace and adults’ walking behaviour in Shanghai, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 234-246.
  • Handle: RePEc:eee:transa:v:155:y:2022:i:c:p:234-246
    DOI: 10.1016/j.tra.2021.11.017
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    References listed on IDEAS

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    1. Lu, Yi & Sarkar, Chinmoy & Xiao, Yang, 2018. "The effect of street-level greenery on walking behavior: Evidence from Hong Kong," Social Science & Medicine, Elsevier, vol. 208(C), pages 41-49.
    2. Yang, Linchuan & Ao, Yibin & Ke, Jintao & Lu, Yi & Liang, Yuan, 2021. "To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults," Journal of Transport Geography, Elsevier, vol. 94(C).
    3. Mokhtarian, Patricia L. & Salomon, Ilan, 2001. "How derived is the demand for travel? Some conceptual and measurement considerations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(8), pages 695-719, September.
    4. Md. Kamruzzaman & Simon Washington & Douglas Baker & Wendy Brown & Billie Giles-Corti & Gavin Turrell, 2016. "Built environment impacts on walking for transport in Brisbane, Australia," Transportation, Springer, vol. 43(1), pages 53-77, January.
    5. Md. Kamruzzaman & Simon Washington & Douglas Baker & Wendy Brown & Billie Giles-Corti & Gavin Turrell, 2016. "Built environment impacts on walking for transport in Brisbane, Australia," Transportation, Springer, vol. 43(1), pages 53-77, January.
    6. Matthias Schonlau, 2005. "Boosted regression (boosting): An introductory tutorial and a Stata plugin," Stata Journal, StataCorp LP, vol. 5(3), pages 330-354, September.
    7. Ding, Chuan & Cao, Xinyu (Jason) & Næss, Petter, 2018. "Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 107-117.
    8. Steven R. Gehrke & Timothy F. Welch, 2017. "The built environment determinants of activity participation and walking near the workplace," Transportation, Springer, vol. 44(5), pages 941-956, September.
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