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

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  • 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
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    References listed on IDEAS

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    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.
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