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Impact of Housing and Community Conditions on Multidimensional Health among Middle- and Low-Income Groups in Hong Kong

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  • Jionghua Wang

    (Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China
    Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, China)

  • Bo Huang

    (Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China
    Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, China
    Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, China)

  • Ting Zhang

    (Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China)

  • Hung Wong

    (Department of Social Work, The Chinese University of Hong Kong, Hong Kong, China)

  • Yifan Huang

    (Department of Psychology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada)

Abstract

With decades of urbanization, housing and community problems (e.g., poor ventilation and lack of open public spaces) have become important social determinants of health that require increasing attention worldwide. Knowledge regarding the link between health and these problems can provide crucial evidence for building healthy communities. However, this link has heretofore not been identified in Hong Kong, and few studies have compared the health impact of housing and community conditions across different income groups. To overcome this gap, we hypothesize that the health impact of housing and community problems may vary across income groups and across health dimensions. We tested these hypotheses using cross-sectional survey data from Hong Kong. Several health outcomes, e.g., chronic diseases and the SF-12 v. 2 mental component summary scores, were correlated with a few types of housing and community problems, while other outcomes, such as the DASS-21–Stress scores, were sensitive to a broader range of problems. The middle- and low-income group was more severely affected by poor built environments. These results can be used to identify significant problems in the local built environment, especially amongst the middle- and low-income group.

Suggested Citation

  • Jionghua Wang & Bo Huang & Ting Zhang & Hung Wong & Yifan Huang, 2018. "Impact of Housing and Community Conditions on Multidimensional Health among Middle- and Low-Income Groups in Hong Kong," IJERPH, MDPI, vol. 15(6), pages 1-14, May.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:6:p:1132-:d:149959
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    References listed on IDEAS

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    1. Srinivasan, S. & O'Fallon, L.R. & Dearry, A., 2003. "Creating Healthy Communities, Healthy Homes, Healthy People: Initiating a Research Agenda on the Built Environment and Public Health," American Journal of Public Health, American Public Health Association, vol. 93(9), pages 1446-1450.
    2. de Goeij, Moniek C.M. & Suhrcke, Marc & Toffolutti, Veronica & van de Mheen, Dike & Schoenmakers, Tim M. & Kunst, Anton E., 2015. "How economic crises affect alcohol consumption and alcohol-related health problems: A realist systematic review," Social Science & Medicine, Elsevier, vol. 131(C), pages 131-146.
    3. Rebecca Chiu, 2010. "The Transferability of Hong Kong's Public Housing Policy," International Journal of Housing Policy, Taylor & Francis Journals, vol. 10(3), pages 301-323.
    4. Pratt, L., 1971. "The relationship of socioeconomic status to health," American Journal of Public Health, American Public Health Association, vol. 61(2), pages 281-291.
    5. Herzer, Dierk & Nunnenkamp, Peter, 2015. "Income inequality and health: Evidence from developed and developing countries," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-56.
    6. Lui, Hon-Kwong & Suen, Wing, 2011. "The effects of public housing on internal mobility in Hong Kong," Journal of Housing Economics, Elsevier, vol. 20(1), pages 15-29, March.
    7. Alaimo, K. & Olson, C.M. & Frongillo E.A., Jr. & Briefel, R.R., 2001. "Food insufficiency, family income, and health in US preschool and school-aged children," American Journal of Public Health, American Public Health Association, vol. 91(5), pages 781-786.
    8. Hon-Kwong Lui, 2007. "The Redistributive Effect of Public Housing in Hong Kong," Urban Studies, Urban Studies Journal Limited, vol. 44(10), pages 1937-1952, September.
    9. Edwin Chan & Grace Lee, 2008. "Critical factors for improving social sustainability of urban renewal projects," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 85(2), pages 243-256, January.
    10. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    11. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
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    Cited by:

    1. Alessia Riva & Andrea Rebecchi & Stefano Capolongo & Marco Gola, 2022. "Can Homes Affect Well-Being? A Scoping Review among Housing Conditions, Indoor Environmental Quality, and Mental Health Outcomes," IJERPH, MDPI, vol. 19(23), pages 1-25, November.
    2. 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.
    3. Lijian Xie & Suhong Zhou & Lin Zhang, 2021. "Associations between Objective and Subjective Housing Status with Individual Mental Health in Guangzhou, China," IJERPH, MDPI, vol. 18(3), pages 1-14, January.
    4. Siu-Ming Chan & Hung Wong & Yikang Chen & Mun-Yu Vera Tang, 2023. "Determinants of depression and anxiety in homeless people: A population survey of homeless people in Hong Kong," International Journal of Social Psychiatry, , vol. 69(5), pages 1145-1156, August.

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