IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i9p1973-d168901.html
   My bibliography  Save this article

The Association of Built Environment and Physical Activity in Older Adults: Using a Citywide Public Housing Scheme to Reduce Residential Self-Selection Bias

Author

Listed:
  • Yi Lu

    (Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong, China
    City University of Hong Kong Shenzhen Research Institute, Shenzhen 518057, China)

  • Long Chen

    (School of Resources and Environmental Sciences, Wuhan University, Wuhan 430072, China)

  • Yiyang Yang

    (Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong, China)

  • Zhonghua Gou

    (Cities Research Institute, School of Environment, Gold Coast Campus, Griffith University, Gold Coast, QLD 4222, Australia)

Abstract

Previous studies have documented numerous health benefits of conducting regular physical activity among older adults. The built environment is believed to be a key factor that can hinder or facilitate daily physical activity, such as walking and exercising. However, most empirical studies focusing on environment-physical activity associations exhibited residential self-selection bias with cross-sectional research design, engendering doubts about the impact of built environment on physical activity. To reduce this bias, we assessed physical activity behaviors of 720 Hong Kong older adults (≥65 years) residing in 24 public housing estates. The Hong Kong public housing scheme currently provides affordable rental flats for 2.1 million people or approximate 30% of total population. The applicants were allocated to one of 179 housing estates largely by family size and flat availability. Built environment characteristics were measured following the ‘5Ds’ principle: (street network) design, (land-use) diversity, density, distance to transit, and destination accessibility. Multilevel mixed models were used to explore the associations between the built environment and the different domains of physical activity (transportation walking, recreational walking, and recreational moderate-to-vigorous physical activity (MVPA) while controlling for potential estate-level socioeconomic and individual confounders. We found that transportation walking was positively associated with the number of bus stops and the presence of Mass Transit Railway (MTR) stations. Recreational MVPA was positively related to the number of recreational facilities. However, land-use mix was negatively related to transportation walking, recreational walking, and recreational MVPA. The findings of this study support a threshold effect in the environment-physical activity associations. Furthermore, large-scale public housing schemes involving random or semi-random residence assignment in many cities may provide opportunities to explore built environments and physical activity behavior, with the potential to overcome residential self-selection bias.

Suggested Citation

  • Yi Lu & Long Chen & Yiyang Yang & Zhonghua Gou, 2018. "The Association of Built Environment and Physical Activity in Older Adults: Using a Citywide Public Housing Scheme to Reduce Residential Self-Selection Bias," IJERPH, MDPI, vol. 15(9), pages 1-13, September.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:1973-:d:168901
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/9/1973/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/9/1973/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mokhtarian, Patricia L. & Cao, Xinyu, 2008. "Examining the impacts of residential self-selection on travel behavior: A focus on methodologies," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 204-228, March.
    2. Patricia L. Mokhtarian & Michael N. Bagley, 2002. "The impact of residential neighborhood type on travel behavior: A structural equations modeling approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 36(2), pages 279-297.
    3. Frank, Lawrence Douglas & Saelens, Brian E. & Powell, Ken E. & Chapman, James E., 2007. "Stepping towards causation: Do built environments or neighborhood and travel preferences explain physical activity, driving, and obesity?," Social Science & Medicine, Elsevier, vol. 65(9), pages 1898-1914, November.
    4. Cerin, Ester & Conway, Terry L. & Adams, Marc A. & Barnett, Anthony & Cain, Kelli L. & Owen, Neville & Christiansen, Lars B. & van Dyck, Delfien & Mitáš, Josef & Sarmiento, Olga L. & Davey, Rachel C. , 2018. "Objectively-assessed neighbourhood destination accessibility and physical activity in adults from 10 countries: An analysis of moderators and perceptions as mediators," Social Science & Medicine, Elsevier, vol. 211(C), pages 282-293.
    5. 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.
    6. Yi Lu, 2018. "The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents’ Exposure to Urban Greenness," IJERPH, MDPI, vol. 15(8), pages 1-15, July.
    7. Yi Zhang & Yuan Li & Qixing Liu & Chaoyang Li, 2014. "The Built Environment and Walking Activity of the Elderly: An Empirical Analysis in the Zhongshan Metropolitan Area, China," Sustainability, MDPI, vol. 6(2), pages 1-17, February.
    8. Yi Lu & Guibo Sun & Chinmoy Sarkar & Zhonghua Gou & Yang Xiao, 2018. "Commuting Mode Choice in a High-Density City: Do Land-Use Density and Diversity Matter in Hong Kong?," IJERPH, MDPI, vol. 15(5), pages 1-13, May.
    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. Yufang Zhang & Terry van Dijk & Cor Wagenaar, 2022. "How the Built Environment Promotes Residents’ Physical Activity: The Importance of a Holistic People-Centered Perspective," IJERPH, MDPI, vol. 19(9), pages 1-19, May.
    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. Bhat, Chandra R. & Mondal, Aupal, 2022. "A New Flexible Generalized Heterogeneous Data Model (GHDM) with an Application to Examine the Effect of High Density Neighborhood Living on Bicycling Frequency," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 244-266.
    4. Yang, Hongtai & Luo, Peng & Li, Chaojing & Zhai, Guocong & Yeh, Anthony G.O., 2023. "Nonlinear effects of fare discounts and built environment on ridesplitting adoption rates," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    5. Ting Zhang & Bo Huang & Hung Wong & Samuel Yeung-shan Wong & Roger Yat-Nork Chung, 2022. "Public Rental Housing and Obesogenic Behaviors among Adults in Hong Kong: Mediator Role of Food and Physical Activity Environment," IJERPH, MDPI, vol. 19(5), pages 1-14, March.
    6. Kadia Saint-Onge & Paquito Bernard & Célia Kingsbury & Janie Houle, 2021. "Older Public Housing Tenants’ Capabilities for Physical Activity Described Using Walk-Along Interviews in Montreal, Canada," IJERPH, MDPI, vol. 18(21), pages 1-19, November.
    7. Faan Chen & Adriano Borges Costa, 2024. "Exploring the causal effects of the built environment on travel behavior: a unique randomized experiment in Shanghai," Transportation, Springer, vol. 51(1), pages 215-245, February.
    8. Jingjing Wang & Xueying Wu & Ruoyu Wang & Dongsheng He & Dongying Li & Linchuan Yang & Yiyang Yang & Yi Lu, 2021. "Review of Associations between Built Environment Characteristics and Severe Acute Respiratory Syndrome Coronavirus 2 Infection Risk," IJERPH, MDPI, vol. 18(14), pages 1-16, July.
    9. Jiabin Yu & Chen Yang & Xiaoguang Zhao & Zhexiao Zhou & Shen Zhang & Diankai Zhai & Jianshe Li, 2021. "The Associations of Built Environment with Older People Recreational Walking and Physical Activity in a Chinese Small-Scale City of Yiwu," IJERPH, MDPI, vol. 18(5), pages 1-12, March.
    10. Yikun Su & Hong Xue & Huakang Liang, 2019. "An Evaluation Model for Urban Comprehensive Carrying Capacity: An Empirical Case from Harbin City," IJERPH, MDPI, vol. 16(3), pages 1-25, January.

    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. 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).
    4. Yi Lu, 2018. "The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents’ Exposure to Urban Greenness," IJERPH, MDPI, vol. 15(8), pages 1-15, July.
    5. Chetan Doddamani & M. Manoj, 2023. "Analysis of the influences of built environment measures on household car and motorcycle ownership decisions in Hubli-Dharwad cities," Transportation, Springer, vol. 50(1), pages 205-243, February.
    6. Kajosaari, Anna & Hasanzadeh, Kamyar & Kyttä, Marketta, 2019. "Residential dissonance and walking for transport," Journal of Transport Geography, Elsevier, vol. 74(C), pages 134-144.
    7. van de Coevering, Paul & Maat, Kees & van Wee, Bert, 2018. "Residential self-selection, reverse causality and residential dissonance. A latent class transition model of interactions between the built environment, travel attitudes and travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 466-479.
    8. 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.
    9. Lin, Tao & Wang, Donggen & Guan, Xiaodong, 2017. "The built environment, travel attitude, and travel behavior: Residential self-selection or residential determination?," Journal of Transport Geography, Elsevier, vol. 65(C), pages 111-122.
    10. 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.
    11. 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.
    12. Wolday, Fitwi & Cao, Jason & Næss, Petter, 2018. "Examining factors that keep residents with high transit preference away from transit-rich zones and associated behavior outcomes," Journal of Transport Geography, Elsevier, vol. 66(C), pages 224-234.
    13. Cao, Xinyu (Jason) & Xu, Zhiyi & Fan, Yingling, 2010. "Exploring the connections among residential location, self-selection, and driving: Propensity score matching with multiple treatments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(10), pages 797-805, December.
    14. Rahman, Mashrur & Sciara, Gian-Claudia, 2022. "Travel attitudes, the built environment and travel behavior relationships: Causal insights from social psychology theories," Transport Policy, Elsevier, vol. 123(C), pages 44-54.
    15. Li, Jianling, 2018. "Residential and transit decisions: Insights from focus groups of neighborhoods around transit stations," Transport Policy, Elsevier, vol. 63(C), pages 1-9.
    16. Cao, Xinyu & Mokhtarian, Patricia & Handy, Susan, 2008. "Examining The Impacts of Residential Self-Selection on Travel Behavior: Methodologies and Empirical Findings," Institute of Transportation Studies, Working Paper Series qt08x1k476, Institute of Transportation Studies, UC Davis.
    17. 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.
    18. Arefeh Nasri & Carlos Carrion & Lei Zhang & Babak Baghaei, 2020. "Using propensity score matching technique to address self-selection in transit-oriented development (TOD) areas," Transportation, Springer, vol. 47(1), pages 359-371, February.
    19. Mitra, Suman K. & Saphores, Jean-Daniel M., 2019. "Why do they live so far from work? Determinants of long-distance commuting in California," Journal of Transport Geography, Elsevier, vol. 80(C).
    20. Coogan, Matthew A. & Adler, Thomas & Karash, Karla, 2012. "The paths from walk preference to walk behavior: Applying latent factors in structural equation modeling," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(3), pages 68-82.

    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:15:y:2018:i:9:p:1973-:d:168901. 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.