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Functional disability with systematic trends and uncertainty: a comparison between China and the US

Published online by Cambridge University Press:  02 December 2021

Yu Fu ,
Michael Sherris  and
Mengyi Xu Open the ORCID record for Mengyi Xu [Opens in a new window]
Yu Fu
Affiliation:
National School of Development, Institute for Global Health and Development, Peking University, Beijing, China
Michael Sherris
Affiliation:
ARC Centre of Excellence in Population Ageing Research, UNSW Sydney, Kensington, Australia School of Risk and Actuarial Studies, UNSW Business School, Sydney, Australia
Mengyi Xu*
Affiliation:
ARC Centre of Excellence in Population Ageing Research, UNSW Sydney, Kensington, Australia Department of Statistics and Department of Mathematics, Purdue University, West Lafayette, IN 47907, USA
*
*Corresponding author. E-mail: [email protected]
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Abstract

China and the US are two contrasting countries in terms of functional disability and long-term care. China is experiencing declining family support for long-term care and developing private long-term care insurance. The US has a more developed public aged care system and private long-term care insurance market than China. Changes in the demand for long-term care are driven by the levels, trends and uncertainty in mortality and functional disability. To understand the future potential demand for long-term care, we compare mortality and functional disability experiences in China and the US, using a multi-state latent factor intensity model with time trends and systematic uncertainty in transition rates. We estimate the model with the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and the US Health and Retirement Study (HRS) data. The estimation results show that if trends continue, both countries will experience longevity improvement with morbidity compression and a declining proportion of the older population with functional disability. Although the elderly Chinese have a shorter estimated life expectancy, they are expected to spend a smaller proportion of their future lifetime functionally disabled than the elderly Americans. Systematic uncertainty is shown to be significant in future trends in disability rates and our model estimates higher uncertainty in trends for the Chinese elderly, especially for urban residents.

Keywords

Functional disabilityLife expectancySystematic trend and uncertaintyMulti-state latent factor intensity model
Type
Original Research Paper
Information
Annals of Actuarial Science , Volume 16 , Issue 2 , July 2022 , pp. 289 - 318
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Institute and Faculty of Actuaries

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References

Administration for Community Living (2020). Receiving long-term care insurance benefits. Available online at the address https://acl.gov/ltc/costs-and-who-pays/what-is-long-term-care-insurance/receiving-long-term-care-insurance-benefits [accessed 26-May-2021].Google Scholar
Ameriks, J., Caplin, A., Laufer, S. & Van Nieuwerburgh, S. (2011). The joy of giving or assisted living? Using strategic surveys to separate public care aversion from bequest motives. Journal of Finance, 66(2), 519–561.CrossRefGoogle Scholar
Chan, K.W. & Wei, Y. (2019). Two systems in one country: the origin, functions, and mechanisms of the rural-urban dual system in China. Eurasian Geography and Economics, 60(4), 422–454.CrossRefGoogle Scholar
Cox, D.R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.Google Scholar
Feng, Z., Glinskaya, E., Chen, H., Gong, S., Qiu, Y., Xu, J. & Yip, W. (2020). Long-term care system for older adults in China: policy landscape, challenges, and future prospects. Lancet, 396(10259), 1362–1372.CrossRefGoogle Scholar
Feng, Z., Liu, C., Guan, X. & Mor, V. (2012). China’s rapidly aging population creates policy challenges in shaping a viable long-term care system. Health Affairs, 31(12), 2764–2773.CrossRefGoogle ScholarPubMed
Fong, J.H., Shao, A.W. & Sherris, M. (2015). Multistate actuarial models of functional disability. North American Actuarial Journal, 19(1), 41–59.CrossRefGoogle Scholar
Gong, P., Liang, S., Carlton, E.J., Jiang, Q., Wu, J., Wang, L. & Remais, J. V. (2012). Urbanisation and health in China. The Lancet, 379(9818), 843–852.CrossRefGoogle ScholarPubMed
Haberman, S. & Pitacco, E. (1998). Actuarial Models for Disability Insurance. Chapman & Hall, London, UK.Google Scholar
Hanewald, K., Li, H. & Shao, A.W. (2019). Modelling multi-state health transitions in China: a generalised linear model with time trends. Annals of Actuarial Science, 13(1), 145–165.CrossRefGoogle Scholar
Hao, L., Xu, X., Dupre, M. E., Guo, A., Zhang, X., Qiu, L., Zhao, Y. & Gu, D. (2020). Adequate access to healthcare and added life expectancy among older adults in China. BMC Geriatrics, 20, 1–15.CrossRefGoogle ScholarPubMed
Health and Retirement Study (2020). (RAND HRS Longitudinal File 2016 (V2)) public use dataset. Produced and distributed by the university of michigan with funding from the national institute on aging (grant number nia u01ag009740). ann arbor, mi.Google Scholar
Hougaard, J.L., østerdal, L.P. & Yu, Y. (2011). The Chinese healthcare system. Applied Health Economics and Health Policy, 9(1), 1–13.CrossRefGoogle ScholarPubMed
Jones, R.H. (1980). Maximum likelihood fitting of ARMA models to time series with missing observations. Technometrics, 22(3), 389–395.CrossRefGoogle Scholar
Koopman, S.J., Lucas, A. & Monteiro, A. (2008). The multi-state latent factor intensity model for credit rating transitions. Journal of Econometrics, 142(1), 399–424.CrossRefGoogle Scholar
Leveille, S.G., Penninx, B.W., Melzer, D., Izmirlian, G. & Guralnik, J.M. (2000). Sex differences in the prevalence of mobility disability in old age: the dynamics of incidence, recovery, and mortality. The Journals of Gerontology: Series B, 55(1), S41–S50.Google Scholar
Li, M., Zhang, Y., Zhang, Z., Zhang, Y., Zhou, L. & Chen, K. (2013). Rural-urban differences in the long-term care of the disabled elderly in China. PloS One, 8(11), 1–7.CrossRefGoogle Scholar
Li, Z., Shao, A.W. & Sherris, M. (2017). The impact of systematic trend and uncertainty on mortality and disability in a multistate latent factor model for transition rates. North American Actuarial Journal, 21(4), 594–610.CrossRefGoogle Scholar
Liu, J., Chen, G., Song, X., Chi, I. & Zheng, X. (2009). Trends in disability-free life expectancy among Chinese older adults. Journal of Aging and Health, 21(2), 266–285.Google ScholarPubMed
Liu, Z., Han, L., Feng, Q., Dupre, M.E., Gu, D., Allore, H.G., Gill, T.M. & Payne, C.F. (2019). Are China’s oldest-old living longer with less disability? A longitudinal modeling analysis of birth cohorts born 10 years apart. BMC Medicine, 17(1), 23.CrossRefGoogle ScholarPubMed
Møller, C.M. (1992). Numerical evaluation of Markov transition probabilities based on the discretized product integral. Scandinavian Actuarial Journal, 1992(1), 76–87.CrossRefGoogle Scholar
RAND HRS Longitudinal File 2016 (V2) (2020). Produced by the rand center for the study of aging, with funding from the national institute on aging and the social security administration. santa monica, ca (april 2020).Google Scholar
Sherris, M. & Wei, P. (2021). A multi-state model of functional disability and health status in the presence of systematic trend and uncertainty. North American Actuarial Journal, 25(1), 17–39.CrossRefGoogle Scholar
Wolthuis, H. (2003). Life Insurance Mathematics: (The Markovian Model), 2nd edition. Peeters Publishers, Herent, Belgium.Google Scholar
Yang, W. & Kanavos, P. (2012). The less healthy urban population: income-related health inequality in China. BMC Public Health, 12(1), 1–15.CrossRefGoogle ScholarPubMed
Yogo, M. (2016). Portfolio choice in retirement: health risk and the demand for annuities, housing, and risky assets. Journal of Monetary Economics, 80, 17–34.CrossRefGoogle ScholarPubMed
Zeng, Y. (2004). Chinese longitudinal healthy longevity survey and some research findings. Geriatrics & Gerontology International, 4, S49–S52.CrossRefGoogle Scholar
Zeng, Y., Gu, D., Purser, J., Hoenig, H. & Christakis, N. (2010). Associations of environmental factors with elderly health and mortality in China. American Journal of Public Health, 100(2), 298–305.CrossRefGoogle ScholarPubMed
Zeng, Y., Vaupel, J., Xiao, Z., Liu, Y. & Zhang, C. (2017). Chinese Longitudinal Healthy Longevity Survey (CLHLS), 1998-2014. Inter-university consortium for political and social research [distributor], 2017-04-11. Available online at the address https://doi.org/10.3886/ICPSR36692.v1.CrossRefGoogle Scholar
Zeng, Y. & Vaupel, J.W. (2002). Functional capacity and self-evaluation of health and life of oldest old in China. Journal of Social Issues, 58(4), 733–748.Google Scholar
Zimmer, Z., Wen, M. & Kaneda, T. (2010). A multi-level analysis of urban/rural and socioeconomic differences in functional health status transition among older Chinese. Social Science & Medicine, 71(3), 559–567.CrossRefGoogle ScholarPubMed
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