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Decomposing Inequality in Long-Term Care Need Among Older Adults with Chronic Diseases in China: A Life Course Perspective

Author

Listed:
  • Han Hu

    (School of Public Policy and Administration, Xi’an Jiaotong University, No. 28 Xianning West Road, Xi’an 710049, Shaanxi, China)

  • Yafei Si

    (ARC Centre of Excellence in Population Ageing Research (CEPAR), The University of New South Wales, Sydney, NSW 2052, Australia)

  • Bingqin Li

    (Social Policy Research Centre, The University of New South Wales, Sydney, NSW 2052, Australia
    Centre for Social Development in Africa, University of Johannesburg, Johannesburg, Auckland Park 2006, South Africa)

Abstract

Background : China has the largest number of aging people in need of long-term care, among whom 70% have chronic diseases. For policy planners, it is necessary to understand the different levels of needs of long-term care and provide long-term care insurance to ensure the long-term care needs of all people can be met. Methods : This study combines the 2013 wave of CHARLS survey and the Life Course Survey of 2014. The combination allows us to factor in both childhood and adulthood data to provide life-course analysis. We identified 7,734 older adults with chronic diseases for analysis. The need for long-term care is defined by the presence of functional limitations based on the performance of basic activities of daily living (ADLs) and of instrumental activities of daily living (IADLs). Two dummy variables, ADLs disability and IADLs disability, and two count variables, ADLs score and IADLs score, were defined to measure incidence and severity of long-term care need, respectively. The concentration index was used to capture the inequality in long-term care need, and a decomposition method based on Probit Regression and Negative Binomial Regression was exploited to identify the contribution of each determination. Results : At least a little difficulty was reported in ADLs and IADLs in 20.44% and 19.25% of respondents, respectively. The concentration index of ADLs disability, ADLs score, IADLs disability, IADLs score were −0.085, −0.109, −0.095 and −0.120, respectively, all of which were statistically significant, indicating the pro-poor inequality in the incidence and severity of long-term care need. Decomposition analyses revealed that family income, education attainment, aging, and childhood experience played a significant role in explaining the inequalities. Conclusions : The long-term care need among older adults with chronic disease is high in China and low socioeconomic groups had a higher probability of needing long-term care or need more long-term care. It is urgent to implement long-term care insurance, especially for the individuals from lower socioeconomic groups.

Suggested Citation

  • Han Hu & Yafei Si & Bingqin Li, 2020. "Decomposing Inequality in Long-Term Care Need Among Older Adults with Chronic Diseases in China: A Life Course Perspective," IJERPH, MDPI, vol. 17(7), pages 1-14, April.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:7:p:2559-:d:342999
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    References listed on IDEAS

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    1. Yafei Si & Zhongliang Zhou & Min Su & Xiao Wang & Dan Li & Dan Wang & Shuyi He & Zihan Hong & Xi Chen, 2018. "Socio-Economic Inequalities in Tobacco Consumption of the Older Adults in China: A Decomposition Method," IJERPH, MDPI, vol. 15(7), pages 1-13, July.
    2. repec:wbk:wbpubs:6896 is not listed on IDEAS
    3. Lei, Xiaoyan & Sun, Xiaoting & Strauss, John & Zhao, Yaohui & Yang, Gonghuan & Hu, Perry & Hu, Yisong & Yin, Xiangjun, 2014. "Health outcomes and socio-economic status among the mid-aged and elderly in China: Evidence from the CHARLS national baseline data," The Journal of the Economics of Ageing, Elsevier, vol. 3(C), pages 29-43.
    4. Heckley, Gawain & Gerdtham, Ulf-G. & Kjellsson, Gustav, 2016. "A general method for decomposing the causes of socioeconomic inequality in health," Journal of Health Economics, Elsevier, vol. 48(C), pages 89-106.
    5. Carmen B Franse & Amy van Grieken & Li Qin & René J F Melis & Judith A C Rietjens & Hein Raat, 2017. "Socioeconomic inequalities in frailty and frailty components among community-dwelling older citizens," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-15, November.
    6. repec:wbk:wbpubs:29807 is not listed on IDEAS
    7. Li, Yaxi & Xue, Qian-Li & Odden, Michelle C. & Chen, Xi & Wu, Chenkai, 2019. "Early Life Environments and Frailty in Old Age among Chinese Older Adults," IZA Discussion Papers 12764, IZA Network @ LISER.
    8. Ming Wen & Danan Gu, 2011. "The Effects of Childhood, Adult, and Community Socioeconomic Conditions on Health and Mortality among Older Adults in China," Demography, Springer;Population Association of America (PAA), vol. 48(1), pages 153-181, February.
    9. Lei, Xiaoyan & Sun, Xiaoting & Strauss, John & Zhao, Yaohui & Yang, Gonghuan & Hu, Perry & Hu, Yisong & Yin, Xiangjun, 2014. "Reprint of: Health outcomes and socio-economic status among the mid-aged and elderly in China: Evidence from the CHARLS national baseline data," The Journal of the Economics of Ageing, Elsevier, vol. 4(C), pages 59-73.
    10. Hu, Bo, 2019. "Projecting future demand for informal care among older people in China: the road towards a sustainable long-term care system," Health Economics, Policy and Law, Cambridge University Press, vol. 14(1), pages 61-81, January.
    11. Adam Wagstaff, 2005. "The bounds of the concentration index when the variable of interest is binary, with an application to immunization inequality," Health Economics, John Wiley & Sons, Ltd., vol. 14(4), pages 429-432, April.
    12. Koike, Soichi & Furui, Yuji, 2013. "Long-term care-service use and increases in care-need level among home-based elderly people in a Japanese urban area," Health Policy, Elsevier, vol. 110(1), pages 94-100.
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    Cited by:

    1. World Bank, 2024. "China Economic Update, June 2024," World Bank Publications - Reports 41709, The World Bank Group.
    2. Javier Lera & Marta Pascual-Sáez & David Cantarero-Prieto, 2020. "Socioeconomic Inequality in the Use of Long-Term Care among European Older Adults: An Empirical Approach Using the SHARE Survey," IJERPH, MDPI, vol. 18(1), pages 1-14, December.
    3. Chen Li & Jiaji Wu & Yi Huang, 2023. "Spatial–Temporal Patterns and Coupling Characteristics of Rural Elderly Care Institutions in China: Sustainable Human Settlements Perspective," Sustainability, MDPI, vol. 15(4), pages 1-27, February.

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