IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i9p4687-d545049.html
   My bibliography  Save this article

Modes of Transport to School and Their Associations with Weight Status: A Cross-Sectional Survey of Students in Shanghai, China

Author

Listed:
  • Yuan-Shen Zhu

    (School of Public Health, Fudan University, Shanghai 200032, China
    Key Lab of Health Technology Assessment, National Health Commission of the People’s Republic of China, Fudan University, Shanghai 200032, China
    Both authors contribute equally.)

  • Zhuo Sun

    (School of Public Health, Fudan University, Shanghai 200032, China
    Key Lab of Health Technology Assessment, National Health Commission of the People’s Republic of China, Fudan University, Shanghai 200032, China
    Both authors contribute equally.)

  • Dan-Dan Ke

    (Graduate School of Health and Sports Science, Juntendo University, Chiba 2701695, Japan)

  • Jia-Qi Yang

    (School of Public Health, Fudan University, Shanghai 200032, China
    Key Lab of Health Technology Assessment, National Health Commission of the People’s Republic of China, Fudan University, Shanghai 200032, China)

  • Wen-Yun Li

    (School of Public Health, Fudan University, Shanghai 200032, China
    Key Lab of Health Technology Assessment, National Health Commission of the People’s Republic of China, Fudan University, Shanghai 200032, China)

  • Ze-Qun Deng

    (School of Public Health, Fudan University, Shanghai 200032, China
    Key Lab of Health Technology Assessment, National Health Commission of the People’s Republic of China, Fudan University, Shanghai 200032, China)

  • Yong-Zhen Li

    (School of Public Health, Fudan University, Shanghai 200032, China
    Key Lab of Health Technology Assessment, National Health Commission of the People’s Republic of China, Fudan University, Shanghai 200032, China)

  • Min Wu

    (School of Public Health, Fudan University, Shanghai 200032, China
    Key Lab of Health Technology Assessment, National Health Commission of the People’s Republic of China, Fudan University, Shanghai 200032, China)

  • Li-Ming Wen

    (School of Public Health, University of Sydney, Sydney, NSW 2006, Australia)

  • Geng-Sheng He

    (School of Public Health, Fudan University, Shanghai 200032, China
    Key Lab of Health Technology Assessment, National Health Commission of the People’s Republic of China, Fudan University, Shanghai 200032, China)

Abstract

Background: Over the past two decades, both transport modes as well as overweight/obesity have changed dramatically among students in China, but their relationships are not clear. This study aimed to investigate modes of transport to school and their associations with the weight status of Chinese students. Methods: A cross-sectional study was conducted with non-resident students aged 6 to 17 years from all 16 districts across Shanghai, China in October and November 2019. Information about sociodemographic characteristics and the models of travel to school among students was investigated using an online, self-administered, structured questionnaire (or those assisted by their parents). Weight and height were measured by school health workers, and the Chinese standard age adjusted BMI (weight/height 2 ) was used to classify students’ weight status. Cumulative logistic regression modelling was used to examine the relationships. Results: The main mode of transport to school was an active mode (46.5%, defined as walking, bicycling, or public transport), followed by an inactive mode of transport (30.5%, defined as a car or bicycle as a passenger), and a combination of both modes (23%). About one-third of the students were overweight or obese and 5% were underweight. No statistically significant association between transport modes and weight status was found in this study. Conclusions: In Shanghai, close to one-third of children travel to school by an inactive mode of transport. The findings of this study did not support the notion that an active mode to school could be beneficial for preventing overweight/obesity in students in China.

Suggested Citation

  • Yuan-Shen Zhu & Zhuo Sun & Dan-Dan Ke & Jia-Qi Yang & Wen-Yun Li & Ze-Qun Deng & Yong-Zhen Li & Min Wu & Li-Ming Wen & Geng-Sheng He, 2021. "Modes of Transport to School and Their Associations with Weight Status: A Cross-Sectional Survey of Students in Shanghai, China," IJERPH, MDPI, vol. 18(9), pages 1-8, April.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:9:p:4687-:d:545049
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/9/4687/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/9/4687/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiaoqin Wang & Zhaozhao Hui & Paul D. Terry & Mei Ma & Li Cheng & Fu Deng & Wei Gu & Bin Zhang, 2016. "Correlates of Insufficient Physical Activity among Junior High School Students: A Cross-Sectional Study in Xi’an, China," IJERPH, MDPI, vol. 13(4), pages 1-9, April.
    2. Zhang, Rui & Yao, Enjian & Liu, Zhili, 2017. "School travel mode choice in Beijing, China," Journal of Transport Geography, Elsevier, vol. 62(C), pages 98-110.
    3. Zhao, Pengjun & Bai, Yu, 2019. "The gap between and determinants of growth in car ownership in urban and rural areas of China: A longitudinal data case study," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    4. Anil Markandaya & Ben Armstrong & Simon Hales & Aline Chiabai & Patrick Criqui & Silvana Mima, 2009. "Impact on public health of strategies to reduce greenhouse gases : low carbon electricity generation," Post-Print halshs-00459664, HAL.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiaoquan Wang & Chunfu Shao & Chaoying Yin & Chengxiang Zhuge & Wenjun Li, 2018. "Application of Bayesian Multilevel Models Using Small and Medium Size City in China: The Case of Changchun," Sustainability, MDPI, vol. 10(2), pages 1-15, February.
    2. Courtney Coughenour & Hanns de la Fuente-Mella & Alexander Paz, 2019. "Analysis of Self-Reported Walking for Transit in a Sprawling Urban Metropolitan Area in the Western U.S," Sustainability, MDPI, vol. 11(3), pages 1-16, February.
    3. Wang, Xiaoquan & Yin, Chaoying & Zhang, Junyi & Shao, Chunfu & Wang, Shengyou, 2021. "Nonlinear effects of residential and workplace built environment on car dependence," Journal of Transport Geography, Elsevier, vol. 96(C).
    4. Sheng, Lu & Wu, Xiao & He, Yan, 2023. "Impact of residential relocation on activity-travel behaviors between household couples: A case study of Kunming, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    5. Yang, Hongtai & Zhai, Guocong & Liu, Xiaohan & Yang, Linchuan & Liu, Yugang & Yuan, Quan, 2022. "Determinants of city-level private car ownership: Effect of vehicle regulation policies and the relative price," Transport Policy, Elsevier, vol. 115(C), pages 40-48.
    6. Khaled Assi & Uneb Gazder & Ibrahim Al-Sghan & Imran Reza & Abdullah Almubarak, 2020. "A Nested Ensemble Approach with ANNs to Investigate the Effect of Socioeconomic Attributes on Active Commuting of University Students," IJERPH, MDPI, vol. 17(10), pages 1-17, May.
    7. Maurici Ruiz-Pérez & Joana Maria Seguí-Pons, 2020. "Transport Mode Choice for Residents in a Tourist Destination: The Long Road to Sustainability (the Case of Mallorca, Spain)," Sustainability, MDPI, vol. 12(22), pages 1-31, November.
    8. Jie Jiang & Jiaorong Wu & Xiaochun Zhang & Maopeng Sun & Shu Chen, 2023. "Association of the Built Environment with Residents’ Car Dependence: Evidence from Shenzhen, China," Sustainability, MDPI, vol. 15(13), pages 1-13, June.
    9. Solange Gould & Linda Rudolph, 2015. "Challenges and Opportunities for Advancing Work on Climate Change and Public Health," IJERPH, MDPI, vol. 12(12), pages 1-24, December.
    10. Shreya S. Shrikhande & Sonja Merten & Olga Cambaco & Tristan Lee & Ravivarman Lakshmanasamy & Martin Röösli & Mohammad Aqiel Dalvie & Jürg Utzinger & Guéladio Cissé, 2023. "“Climate Change and Health?”: Knowledge and Perceptions among Key Stakeholders in Puducherry, India," IJERPH, MDPI, vol. 20(6), pages 1-18, March.
    11. Christina Zapata & Nicholas Muller & Michael Kleeman, 2013. "PM 2.5 co-benefits of climate change legislation part 1: California’s AB 32," Climatic Change, Springer, vol. 117(1), pages 377-397, March.
    12. Zhang, Yongsheng & Yao, Enjian & Zhang, Rui & Xu, Hao, 2019. "Analysis of elderly people's travel behaviours during the morning peak hours in the context of the free bus programme in Beijing, China," Journal of Transport Geography, Elsevier, vol. 76(C), pages 191-199.
    13. Scheiner, Joachim & Huber, Oliver & Lohmüller, Stefan, 2019. "Children's independent travel to and from primary school: Evidence from a suburban town in Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 116-131.
    14. Liu, Yang & Ji, Yanjie & Shi, Zhuangbin & He, Baohong & Liu, Qiyang, 2018. "Investigating the effect of the spatial relationship between home, workplace and school on parental chauffeurs’ daily travel mode choice," Transport Policy, Elsevier, vol. 69(C), pages 78-87.
    15. Sandra Mandic & Erika Ikeda & Tom Stewart & Nicholas Garrett & Debbie Hopkins & Jennifer S. Mindell & El Shadan Tautolo & Melody Smith, 2020. "Sociodemographic and Built Environment Associates of Travel to School by Car among New Zealand Adolescents: Meta-Analysis," IJERPH, MDPI, vol. 17(23), pages 1-17, December.
    16. Hooman Farzaneh & Jose A. Puppim de Oliveira & Benjamin McLellan & Hideaki Ohgaki, 2019. "Towards a Low Emission Transport System: Evaluating the Public Health and Environmental Benefits," Energies, MDPI, vol. 12(19), pages 1-17, September.
    17. Dias, Charitha & Abdullah, Muhammad & Lovreglio, Ruggiero & Sachchithanantham, Sumana & Rekatheeban, Markkandu & Sathyaprasad, I.M.S., 2022. "Exploring home-to-school trip mode choices in Kandy, Sri Lanka," Journal of Transport Geography, Elsevier, vol. 99(C).
    18. Leung, Kevin Y.K. & Astroza, Sebastian & Loo, Becky P.Y. & Bhat, Chandra R., 2019. "An environment-people interactions framework for analysing children's extra-curricular activities and active transport," Journal of Transport Geography, Elsevier, vol. 74(C), pages 341-358.
    19. Jiemei Luo & Edwin H. W. Chan & Jinfeng Du & Linxia Feng & Peng Jiang & Ying Xu, 2022. "Developing a Health-Spatial Indicator System for a Healthy City in Small and Midsized Cities," IJERPH, MDPI, vol. 19(6), pages 1-20, March.
    20. Annabelle Workman & Grant Blashki & Kathryn J. Bowen & David J. Karoly & John Wiseman, 2018. "The Political Economy of Health Co-Benefits: Embedding Health in the Climate Change Agenda," IJERPH, MDPI, vol. 15(4), pages 1-18, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:9:p:4687-:d:545049. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.