IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i13p7948-d851040.html
   My bibliography  Save this article

Correlation between Campus-Built Environment and Physical Fitness in College Students in Xi’an—A GIS Approach

Author

Listed:
  • Zijun Lu

    (Department of Exercise Science, School of Physical Education, Shaanxi Normal University, Xi’an 710119, China)

  • Zhengao Li

    (Department of Exercise Science, School of Physical Education, Shaanxi Normal University, Xi’an 710119, China)

  • Chuangui Mao

    (Department of Exercise Science, School of Physical Education, Shaanxi Normal University, Xi’an 710119, China)

  • Yuanyuan Tan

    (Department of Exercise Science, School of Physical Education, Shaanxi Normal University, Xi’an 710119, China)

  • Xingyue Zhang

    (Department of Exercise Science, School of Physical Education, Shaanxi Normal University, Xi’an 710119, China)

  • Ling Zhang

    (Department of Exercise Science, School of Physical Education, Shaanxi Normal University, Xi’an 710119, China)

  • Wenfei Zhu

    (Department of Exercise Science, School of Physical Education, Shaanxi Normal University, Xi’an 710119, China)

  • Yuliang Sun

    (Department of Exercise Science, School of Physical Education, Shaanxi Normal University, Xi’an 710119, China)

Abstract

Background: This research aimed to investigate the correlation between students’ physical fitness and campus-built environment, which could put forward some suggestions for the construction of a campus environment. Method: Four colleges in Xi’an were regarded as special “semi-closed” spaces. Combined with ArcGIS and SPSS, the correlation between the built environment of colleges and the students’ physical fitness test results in 2019 was analyzed ( n = 1498). Results: regarding the men questioned in this research, there was a significant correlation between street connectivity and vital capacity, grip strength, 50 m running, 1000 m running, a significant correlation between land use mix and vital capacity, sit-and-reach, pull-up, grip strength, a significant correlation between green space per capita and vital capacity, grip strength, 50 m running, and a significant correlation between walk score and vital capacity, pull-up, grip strength, and 50 m running. Regarding the women questioned in this research, there was a significant correlation between street connectivity and vital capacity, grip strength, 50 m running, 800 m running, curl-up, a significant correlation between land use mix and vital capacity, sit-and-reach, curl-up, grip strength, 800 m running, a significant correlation between green space per capita and vital capacity, grip strength, curl-up, sit-and-reach, and a significant correlation between walk score and vital capacity, curl-up, grip strength, and 800 m running. Conclusion: the built environment on campus can indirectly affect the physical fitness of college students. Increasing the number of intersections and short connections of campus streets, ensuring that the green space of the campus meets the standards, and reasonably arranging the site selection of buildings are conducive to improving the physical fitness of students.

Suggested Citation

  • Zijun Lu & Zhengao Li & Chuangui Mao & Yuanyuan Tan & Xingyue Zhang & Ling Zhang & Wenfei Zhu & Yuliang Sun, 2022. "Correlation between Campus-Built Environment and Physical Fitness in College Students in Xi’an—A GIS Approach," IJERPH, MDPI, vol. 19(13), pages 1-14, June.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:13:p:7948-:d:851040
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/13/7948/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/13/7948/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kirsten M. M. Beyer & Andrea Kaltenbach & Aniko Szabo & Sandra Bogar & F. Javier Nieto & Kristen M. Malecki, 2014. "Exposure to Neighborhood Green Space and Mental Health: Evidence from the Survey of the Health of Wisconsin," IJERPH, MDPI, vol. 11(3), pages 1-20, March.
    2. Yuliang Sun & Chunzhen He & Xinxin Zhang & Wenfei Zhu, 2020. "Association of Built Environment with Physical Activity and Physical Fitness in Men and Women Living inside the City Wall of Xi’an, China," IJERPH, MDPI, vol. 17(14), pages 1-13, July.
    3. Cao, Xinyu, 2006. "The Causal Relationship between the Built Environment and Personal Travel Choice: Evidence from Northern California," University of California Transportation Center, Working Papers qt07q5p340, University of California Transportation Center.
    4. Xinyu Cao & Susan Handy & Patricia Mokhtarian, 2006. "The Influences of the Built Environment and Residential Self-Selection on Pedestrian Behavior: Evidence from Austin, TX," Transportation, Springer, vol. 33(1), pages 1-20, January.
    5. Xinyu Cao & Patricia Mokhtarian & Susan Handy, 2007. "Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach," Transportation, Springer, vol. 34(5), pages 535-556, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zihan Tong & Zhenxing Kong & Xiao Jia & Jingjing Yu & Tingting Sun & Yimin Zhang, 2023. "Spatial Heterogeneity and Regional Clustering of Factors Influencing Chinese Adolescents’ Physical Fitness," IJERPH, MDPI, vol. 20(5), pages 1-18, February.

    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. Xinyu Cao & Patricia L. Mokhtarian, 2012. "The connections among accessibility, self- selection and walking behaviour: a case study of Northern California residents," Chapters, in: Karst T. Geurs & Kevin J. Krizek & Aura Reggiani (ed.), Accessibility Analysis and Transport Planning, chapter 5, pages 73-95, Edward Elgar Publishing.
    2. Jonas De Vos & Long Cheng & Frank Witlox, 2021. "Do changes in the residential location lead to changes in travel attitudes? A structural equation modeling approach," Transportation, Springer, vol. 48(4), pages 2011-2034, August.
    3. Zhao, Chunli & Nielsen, Thomas Alexander Sick & Olafsson, Anton Stahl & Carstensen, Trine Agervig & Meng, Xiaoying, 2018. "Urban form, demographic and socio-economic correlates of walking, cycling, and e-biking: Evidence from eight neighborhoods in Beijing," Transport Policy, Elsevier, vol. 64(C), pages 102-112.
    4. Li, Jingjing & Auchincloss, Amy H. & Yang, Yong & Rodriguez, Daniel A. & Sánchez, Brisa N., 2020. "Neighborhood characteristics and transport walking: Exploring multiple pathways of influence using a structural equation modeling approach," Journal of Transport Geography, Elsevier, vol. 85(C).
    5. Cao, Xinyu (Jason) & Mokhtarian, Patricia L. & Handy, Susan L., 2009. "The relationship between the built environment and nonwork travel: A case study of Northern California," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(5), pages 548-559, June.
    6. Lucas, Karen & Philips, Ian & Mulley, Corinne & Ma, Liang, 2018. "Is transport poverty socially or environmentally driven? Comparing the travel behaviours of two low-income populations living in central and peripheral locations in the same city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 622-634.
    7. 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.
    8. Faizeh Hatami & Jean-Claude Thill, 2022. "Spatiotemporal Evaluation of the Built Environment’s Impact on Commuting Duration," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    9. Doddamani, Chetan & Manoj, M., 2022. "Residential relocation and changes in household vehicle ownership and travel behavior: Exploring the context of Hubli-Dharwad twin-cities in India from a planning viewpoint," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 134-155.
    10. Jahanshahi, Kaveh & Jin, Ying & Williams, Ian, 2015. "Direct and indirect influences on employed adults’ travel in the UK: New insights from the National Travel Survey data 2002–2010," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 288-306.
    11. Van Acker, Veronique & Witlox, Frank, 2010. "Car ownership as a mediating variable in car travel behaviour research using a structural equation modelling approach to identify its dual relationship," Journal of Transport Geography, Elsevier, vol. 18(1), pages 65-74.
    12. Bojing Liao & Yifan Xu & Xiang Li & Ji Li, 2022. "Association between Campus Walkability and Affective Walking Experience, and the Mediating Role of Walking Attitude," IJERPH, MDPI, vol. 19(21), pages 1-13, November.
    13. Yuan Gao & Kun Liu & Peiling Zhou & Hongkun Xie, 2021. "The Effects of Residential Built Environment on Supporting Physical Activity Diversity in High-Density Cities: A Case Study in Shenzhen, China," IJERPH, MDPI, vol. 18(13), pages 1-16, June.
    14. Xinyu Cao & Patricia Mokhtarian & Susan Handy, 2007. "Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach," Transportation, Springer, vol. 34(5), pages 535-556, September.
    15. Mitra, Suman & Yao, Mingqi & Ritchie, Stephen G., 2021. "Gender differences in elderly mobility in the United States," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 203-226.
    16. Alessandro Rigolon & Matthew H. E. M. Browning & Olivia McAnirlin & Hyunseo (Violet) Yoon, 2021. "Green Space and Health Equity: A Systematic Review on the Potential of Green Space to Reduce Health Disparities," IJERPH, MDPI, vol. 18(5), pages 1-27, March.
    17. Sun, Bindong & Yan, Hong & Zhang, Tinglin, 2017. "Built environmental impacts on individual mode choice and BMI: Evidence from China," Journal of Transport Geography, Elsevier, vol. 63(C), pages 11-21.
    18. Daniel G Chatman, 2009. "Residential Choice, the Built Environment, and Nonwork Travel: Evidence Using New Data and Methods," Environment and Planning A, , vol. 41(5), pages 1072-1089, May.
    19. Markvica, Karin & Millonig, Alexandra & Haufe, Nadine & Leodolter, Maximilian, 2020. "Promoting active mobility behavior by addressing information target groups: The case of Austria," Journal of Transport Geography, Elsevier, vol. 83(C).
    20. Tae-Hyoung Tommy Gim, 2023. "Residential self-selection or socio-ecological interaction? the effects of sociodemographic and attitudinal characteristics on the built environment–travel behavior relationship," Transportation, Springer, vol. 50(4), pages 1347-1398, August.

    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:19:y:2022:i:13:p:7948-:d:851040. 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.