IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i6p1132-d149959.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/6/1132/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/6/1132/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    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.
    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. 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. 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.
    4. 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.

    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. Tutz, Gerhard & Pößnecker, Wolfgang & Uhlmann, Lorenz, 2015. "Variable selection in general multinomial logit models," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 207-222.
    2. Oxana Babecka Kucharcukova & Jan Bruha, 2016. "Nowcasting the Czech Trade Balance," Working Papers 2016/11, Czech National Bank.
    3. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    4. Hou-Tai Chang & Ping-Huai Wang & Wei-Fang Chen & Chen-Ju Lin, 2022. "Risk Assessment of Early Lung Cancer with LDCT and Health Examinations," IJERPH, MDPI, vol. 19(8), pages 1-12, April.
    5. Margherita Giuzio, 2017. "Genetic algorithm versus classical methods in sparse index tracking," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 40(1), pages 243-256, November.
    6. Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
    7. Wang, Qiao & Zhou, Wei & Cheng, Yonggang & Ma, Gang & Chang, Xiaolin & Miao, Yu & Chen, E, 2018. "Regularized moving least-square method and regularized improved interpolating moving least-square method with nonsingular moment matrices," Applied Mathematics and Computation, Elsevier, vol. 325(C), pages 120-145.
    8. Dmitriy Drusvyatskiy & Adrian S. Lewis, 2018. "Error Bounds, Quadratic Growth, and Linear Convergence of Proximal Methods," Mathematics of Operations Research, INFORMS, vol. 43(3), pages 919-948, August.
    9. Mkhadri, Abdallah & Ouhourane, Mohamed, 2013. "An extended variable inclusion and shrinkage algorithm for correlated variables," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 631-644.
    10. Lucian Belascu & Alexandra Horobet & Georgiana Vrinceanu & Consuela Popescu, 2021. "Performance Dissimilarities in European Union Manufacturing: The Effect of Ownership and Technological Intensity," Sustainability, MDPI, vol. 13(18), pages 1-19, September.
    11. Candelon, B. & Hurlin, C. & Tokpavi, S., 2012. "Sampling error and double shrinkage estimation of minimum variance portfolios," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 511-527.
    12. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
    13. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Specification Choices in Quantile Regression for Empirical Macroeconomics," Working Papers 22-25, Federal Reserve Bank of Cleveland.
    14. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
    15. Shuichi Kawano, 2014. "Selection of tuning parameters in bridge regression models via Bayesian information criterion," Statistical Papers, Springer, vol. 55(4), pages 1207-1223, November.
    16. Yize Zhao & Matthias Chung & Brent A. Johnson & Carlos S. Moreno & Qi Long, 2016. "Hierarchical Feature Selection Incorporating Known and Novel Biological Information: Identifying Genomic Features Related to Prostate Cancer Recurrence," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1427-1439, October.
    17. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
    18. Enrico Bergamini & Georg Zachmann, 2020. "Exploring EU’s Regional Potential in Low-Carbon Technologies," Sustainability, MDPI, vol. 13(1), pages 1-28, December.
    19. Jie Jian & Peijun Sang & Mu Zhu, 2024. "Two Gaussian Regularization Methods for Time-Varying Networks," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 29(4), pages 853-873, December.
    20. Qianyun Li & Runmin Shi & Faming Liang, 2019. "Drug sensitivity prediction with high-dimensional mixture regression," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-18, February.

    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:6:p:1132-:d:149959. 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.