How School Travel Affects Children's Psychological Well-Being and Academic Achievement in China

Int J Environ Res Public Health. 2022 Oct 25;19(21):13881. doi: 10.3390/ijerph192113881.

Abstract

Previous research on the role of school travel in children's well-being (WB) has paid little attention to developing countries. Using national survey data across China, this study examines how children's psychological well-being (PWB) and academic performance differ across commute duration and mode among urban, rural, and urban fringe areas. Our findings show that commute times are significantly negatively associated with children's PWB and academic achievements, and this correlation varies across areas. Children living in the urban fringe have the longest average one-way commuting time (18.6 min), but they have a better acceptance of longer commuting duration, whereas commuting time is more influential in the city center and rural areas. Regarding travel mode, walking to school is positively associated with PWB in the center area, while bicycles and public transport positively affect the rural student scores. Results from quantile regression show that students on the lower quantiles of the conditional distribution of PWB tend to suffer more than the others when commuting time increases; students with middle scores respond similarly to marginal changes in commuting time. Recommendations for urban planners and policymakers to enhance child WB include fostering school-home balance, improving public transit services, and investing in pedestrian and bicycle infrastructure for those vulnerable groups.

Keywords: China; academic achievement; children; commuting mode; commuting time; psychological well-being; school travel.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Academic Success*
  • Bicycling
  • Child
  • China
  • Humans
  • Schools
  • Transportation
  • Walking

Grants and funding

This research was funded by National Natural Science Foundation of China (grant number 71871131) and by the Shanghai University of Finance and Economics Graduate Innovation Fund (grant number CXJJ-2021-340).