TY - JOUR
T1 - Gender differences in active travel among older adults
T2 - Non-linear built environment insights
AU - Yang, Yongjiang
AU - Sasaki, Kuniaki
AU - Cheng, Long
AU - Liu, Xingwei
N1 - Funding Information:
The authors gratefully acknowledge the data support from Tokyo Metropolitan Transportation Planning Council. We also would like to thank Pengpeng E for helping to collect part of the built environment data. In addition, we would like to thank the editor and anonymous reviewers for their valuable comments and suggestions.
Publisher Copyright:
© 2022
PY - 2022/9
Y1 - 2022/9
N2 - Although many studies have revealed the relationship between the built environment and active travel among older adults, limited studies offer insights into gender differences. Using data from Chiba (Japan), this study employs a random forest method to fill this gap by revealing the non-linear associations of the built environment with active travel time among older males and females, and adopts a Shapley Additive exPlanations method to interpret the models. Results show that: (1) The dominant contributions to active travel time are gendered. For example, distance to a cafe/pachinko contributes more to males’ active travel time, while for females, population density contributes more. (2) The built environment attributes have non-linear associations with active travel time among older males and females. This, therefore, implies that built environment interventions are only effective to a certain extent. Implications of the findings offer nuanced guidance for a gender-equitable and age-friendly city.
AB - Although many studies have revealed the relationship between the built environment and active travel among older adults, limited studies offer insights into gender differences. Using data from Chiba (Japan), this study employs a random forest method to fill this gap by revealing the non-linear associations of the built environment with active travel time among older males and females, and adopts a Shapley Additive exPlanations method to interpret the models. Results show that: (1) The dominant contributions to active travel time are gendered. For example, distance to a cafe/pachinko contributes more to males’ active travel time, while for females, population density contributes more. (2) The built environment attributes have non-linear associations with active travel time among older males and females. This, therefore, implies that built environment interventions are only effective to a certain extent. Implications of the findings offer nuanced guidance for a gender-equitable and age-friendly city.
KW - Active travel
KW - Built environment
KW - Gender
KW - Machine learning
KW - Non-linear
KW - Older adults
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U2 - 10.1016/j.trd.2022.103405
DO - 10.1016/j.trd.2022.103405
M3 - Article
AN - SCOPUS:85135301239
SN - 1361-9209
VL - 110
JO - Transportation Research Part D: Transport and Environment
JF - Transportation Research Part D: Transport and Environment
M1 - 103405
ER -