IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i24p7114-d297012.html
   My bibliography  Save this article

Social-Demographic Correlates of the Mental Health Conditions among the Chinese Elderly

Author

Listed:
  • Wenjuan Du

    (School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan 430071, China
    Global Health Institute, Wuhan University, 8# South Donghu Road,Wuhan 430072, China
    These authors contributed equally to this study.)

  • Jiayi Zhou

    (School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan 430071, China
    These authors contributed equally to this study.)

  • Jianjian Liu

    (School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan 430071, China)

  • Xuhao Yang

    (Bloomberg School of Public Health, Johns Hopkins University, 615 N. Wolfe Street, Baltimore, MD 21205, USA)

  • Hanxu Wang

    (Cornell Institute for Public Affairs, Cornell University, Ithaca, NY 14850, USA)

  • Meikun He

    (School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan 430071, China)

  • Zongfu Mao

    (School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan 430071, China
    Global Health Institute, Wuhan University, 8# South Donghu Road,Wuhan 430072, China)

  • Xiaojun Liu

    (School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan 430071, China
    Global Health Institute, Wuhan University, 8# South Donghu Road,Wuhan 430072, China)

Abstract

Studies on psychological problems among the elderly were mainly conducted in developed countries, which may not fit China under the context of the dramatic changes of social environment. This study aims to assess the status and social-demographic determinants of the mental health among the Chinese elderly. The Chinese version of the Symptom Checklist-90-R (SCL-90-R) was used to measure participants’ mental health. A logistic model was established to identify the main socio-demographic factors associated with the overall detection rate of SCL-90-R. The overall positive detection rate of SCL-90-R was 23.6%, and the four symptoms with the highest positive detection rate were somatization (39.5%), obsessive-compulsive disorder (28.1%), other poor mental health symptoms (mainly sleep and diet problems) (25.7%), and depression (25.1%). The results showed those aged 75–79 (OR = 0.640, 95% CI 0.452 to 0.905) and 80 or above (OR = 0.430, 95% CI 0.302 to 0.613), those received 0 (OR = 0.224, 95% CI 0.162 to 0.310) or 1–5 years of education (OR = 0.591, 95% CI 0.449 to 0.776), those were living with spouse only (OR = 0.817, 95% CI 0.563 to 0.997) and with multiple generations (OR = 0.689, 95% CI 0.472 to 0.950), those holding a non-agricultural household registration (OR = 0.727, 95% CI 0.537 to 0.984), and those with an better higher household income were less likely to be positive in overall mental health symptoms. Mental health was shown to be better among those with more advanced ages (≥75), lower levels of schooling (≤5), normal body mass index, higher household incomes, and those who are married and live with their spouse or multiple generations, and those who came from city and currently live in the county.

Suggested Citation

  • Wenjuan Du & Jiayi Zhou & Jianjian Liu & Xuhao Yang & Hanxu Wang & Meikun He & Zongfu Mao & Xiaojun Liu, 2019. "Social-Demographic Correlates of the Mental Health Conditions among the Chinese Elderly," Sustainability, MDPI, vol. 11(24), pages 1-13, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:7114-:d:297012
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/24/7114/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/24/7114/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ohrnberger, Julius & Fichera, Eleonora & Sutton, Matt, 2017. "The dynamics of physical and mental health in the older population," The Journal of the Economics of Ageing, Elsevier, vol. 9(C), pages 52-62.
    2. Huan Wang & Jianyuan Huang & Shuangyue Sun, 2019. "Assessment of the Financial Sustainability of China’s New Rural Pension Plan: Does the Demographic Policy Reform Matter?," Sustainability, MDPI, vol. 11(18), pages 1-22, September.
    3. Xin Xu & Yuan Zhao & Xinlin Zhang & Siyou Xia, 2018. "Identifying the Impacts of Social, Economic, and Environmental Factors on Population Aging in the Yangtze River Delta Using the Geographical Detector Technique," Sustainability, MDPI, vol. 10(5), pages 1-15, May.
    4. Rong Fu & Haruko Noguchi, 2016. "Does Marriage Make Us Healthier? Inter-Country Comparative Evidence from China, Japan, and Korea," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-15, February.
    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. Mas Ayu Said & Govindamal Thangiah & Hazreen Abdul Majid & Rozmi Ismail & Tan Maw Pin & Hussein Rizal & Mohd Azlan Shah Zaidi & Daniel Reidpath & Tin Tin Su, 2022. "Income Disparity and Mental Wellbeing among Adults in Semi-Urban and Rural Areas in Malaysia: The Mediating Role of Social Capital," IJERPH, MDPI, vol. 19(11), pages 1-16, May.
    2. Chongxian Chen & Weijing Luo & Ning Kang & Haiwei Li & Xiaohao Yang & Yu Xia, 2020. "Study on the Impact of Residential Outdoor Environments on Mood in the Elderly in Guangzhou, China," Sustainability, MDPI, vol. 12(9), pages 1-18, May.
    3. Huan Wu & Yaqing Liu, 2023. "Association Between Living Arrangements and Psychological Well-Being Among Older Adults in Rural China: Activities of Daily Living Disability as a Moderator," SAGE Open, , vol. 13(4), pages 21582440231, December.
    4. Jianjian Liu & Wei Yu & Jiayi Zhou & Yifan Yang & Shuoni Chen & Shaotang Wu, 2020. "Relationship between the Number of Noncommunicable Diseases and Health-Related Quality of Life in Chinese Older Adults: A Cross-Sectional Survey," IJERPH, MDPI, vol. 17(14), pages 1-11, July.
    5. Mingna Li & Bo Zhou & Bingbin Hu, 2022. "Relationship between Income and Mental Health during the COVID-19 Pandemic in China," IJERPH, MDPI, vol. 19(15), pages 1-14, July.

    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. Kazuma Sato, 2020. "Does marriage improve subjective health in Japan?," The Japanese Economic Review, Springer, vol. 71(2), pages 247-286, April.
    2. Kwon-Soo Kim, 2019. "The Influence of Hotels High-Commitment HRM on Job Engagement of Employees: Mediating Effects of Workplace Happiness and Mental Health," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 14(2), pages 507-525, April.
    3. Rong Fu & Haruko Noguchi, 2018. "Does the positive relationship between health and marriage reflect protection or selection? Evidence from middle-aged and elderly Japanese," Review of Economics of the Household, Springer, vol. 16(4), pages 1003-1016, December.
    4. Fu, Rong & Noguchi, Harkuo & Tachikawa, Hirokazu & Aiba, Miyuki & Nakamine, Shin & Kawamura, Akira & Takahashi, Hideto & Tamiya, Nanako, 2017. "Relation between social network and psychological distress among middle-aged adults in Japan: Evidence from a national longitudinal survey," Social Science & Medicine, Elsevier, vol. 175(C), pages 58-65.
    5. Yang, Liyuan & Zikos, Vasileios, 2022. "Healthy mind in healthy body: Identifying the causal effect of mental health on physical health," Economics Letters, Elsevier, vol. 213(C).
    6. Ana Margarida Alves & Alexandre Rodrigues & Pedro Sa-Couto & João Lindo Simões, 2021. "Effect of an Educational Nursing Intervention on the Mental Adjustment of Patients with Chronic Arterial Hypertension: An Interventional Study," IJERPH, MDPI, vol. 19(1), pages 1-22, December.
    7. Sung-Joo Yoon, 2019. "What Can We Obtain from Mental Health Care? The Dynamics of Physical and Mental Health," IJERPH, MDPI, vol. 16(17), pages 1-18, August.
    8. Takahashi, Shuko & Jang, Soong-nang & Kino, Shiho & Kawachi, Ichiro, 2020. "Gender inequalities in poor self-rated health: Cross-national comparison of South Korea and Japan," Social Science & Medicine, Elsevier, vol. 252(C).
    9. Chris Muris & Pedro Raposo & Sotiris Vandoros, 2020. "A Dynamic Ordered Logit Model with Fixed Effects," Department of Economics Working Papers 2020-14, McMaster University.
    10. Xiuhai Xiong & Lingbo Liu & Zhenghong Peng & Hao Wu, 2021. "Physical Activities in Public Squares: The Impact of Companionship on Chinese Residents’ Health," Land, MDPI, vol. 10(7), pages 1-14, July.
    11. Guolei Chen & Jing Luo & Chunyan Zhang & Liang Jiang & Lingling Tian & Guangping Chen, 2018. "Characteristics and Influencing Factors of Spatial Differentiation of Urban Black and Odorous Waters in China," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    12. Yue Li & Chengmeng Zhang & Yan Tong & Yalu Zhang & Gong Chen, 2022. "Prediction of the Old-Age Dependency Ratio in Chinese Cities Using DMSP/OLS Nighttime Light Data," IJERPH, MDPI, vol. 19(12), pages 1-23, June.
    13. Yuanyuan Wu & Yuxiang Song & Tingting Yu, 2019. "Spatial Differences in China’s Population Aging and Influencing Factors: The Perspectives of Spatial Dependence and Spatial Heterogeneity," Sustainability, MDPI, vol. 11(21), pages 1-20, October.
    14. Andrea Čajková & Peter Čajka, 2021. "Challenges and Sustainability of China’s Socio-Economic Stability in the Context of Its Demographic Development," Societies, MDPI, vol. 11(1), pages 1-20, March.
    15. Sunitha Singh & Sowmya Kshtriya & Reimara Valk, 2023. "Health, Hope, and Harmony: A Systematic Review of the Determinants of Happiness across Cultures and Countries," IJERPH, MDPI, vol. 20(4), pages 1-68, February.
    16. Shangmei Zhao & Jiang He & Haijun Yang, 2018. "Population Ageing, Financial Deepening and Economic Growth: Evidence from China," Sustainability, MDPI, vol. 10(12), pages 1-15, December.
    17. Sijia Wu & Hongyan Ren & Wenhui Chen & Tiegang Li, 2019. "Neglected Urban Villages in Current Vector Surveillance System: Evidences in Guangzhou, China," IJERPH, MDPI, vol. 17(1), pages 1-15, December.
    18. Sheng Liu & Ming Bai & Min Yao & Ke Huang, 2021. "Identifying the natural and anthropogenic factors influencing the spatial disparity of population hollowing in traditional villages within a prefecture-level city," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-21, April.
    19. Xinxin Wang & Jingjing Hong & Pengpeng Fan & Shidan Xu & Zhixian Chai & Yubo Zhuo, 2021. "Is China’s urban–rural difference in population aging rational? An international comparison with key indicators," Growth and Change, Wiley Blackwell, vol. 52(3), pages 1866-1891, September.
    20. Chan Chen & Jie Li & Jian Huang, 2022. "Spatial–Temporal Patterns of Population Aging in Rural China," IJERPH, MDPI, vol. 19(23), pages 1-18, November.

    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:jsusta:v:11:y:2019:i:24:p:7114-:d:297012. 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.