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Projecting the Number of Elderly with Cognitive Impairment in China Using a Multi†State Dynamic Population Model

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  • John P. Ansah
  • Victoria Koh
  • Chi†Tsun Chiu
  • Choy†Lye Chei
  • Yi Zeng
  • Zhao†Xue Yin
  • Xiao†Ming Shi
  • David B. Matchar

Abstract

China is aging rapidly, and the number of Chinese elderly with dementia is expected to rise. This paper projects, up to year 2060, the number of Chinese elderly within four distinct cognitive states. A multi†state population model was developed using system dynamics and parametrized with age–gender†specific transition rates (between intact, mild, moderate and severe cognitive impairment and death) estimated from two waves (2012 and 2014) of a community†based cohort of elderly in China aged ≥65 years (N = 1824). Probabilistic sensitivity analysis and the bootstrap method was used to obtain the 95% confidence interval of the transition rates. The number of elderly with any degree of cognitive impairment increases; with severe cognitive impairment increasing the most, at 698%. Among elderly with cognitive impairment, the proportion of very old elderly (age ≥ 80) is expected to rise from 53% to 78% by 2060. This will affect the demand for social and health services China. Copyright © 2017 System Dynamics Society

Suggested Citation

  • John P. Ansah & Victoria Koh & Chi†Tsun Chiu & Choy†Lye Chei & Yi Zeng & Zhao†Xue Yin & Xiao†Ming Shi & David B. Matchar, 2017. "Projecting the Number of Elderly with Cognitive Impairment in China Using a Multi†State Dynamic Population Model," System Dynamics Review, System Dynamics Society, vol. 33(2), pages 89-111, April.
    • Handle: RePEc:bla:sysdyn:v:33:y:2017:i:2:p:89-111
    DOI: 10.1002/sdr.1581
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    Cited by:

    1. Negar Darabi & Niyousha Hosseinichimeh, 2020. "System dynamics modeling in health and medicine: a systematic literature review," System Dynamics Review, System Dynamics Society, vol. 36(1), pages 29-73, January.
    2. Jair Andrade & Jim Duggan, 2021. "A Bayesian approach to calibrate system dynamics models using Hamiltonian Monte Carlo," System Dynamics Review, System Dynamics Society, vol. 37(4), pages 283-309, October.
    3. John Pastor Ansah & Keith Low Sheng Hng & Salman Ahmad & Cheryl Goh, 2021. "Evaluating the impact of upstream and downstream interventions on chronic kidney disease and dialysis care: a simulation analysis," System Dynamics Review, System Dynamics Society, vol. 37(1), pages 32-58, January.
    4. John Pastor Ansah & Shawn Tan Yi Wei & Tessa Lui Shi Min, 2020. "An evaluation of the impact of aggressive diabetes and hypertension management on chronic kidney diseases at the population level: a simulation analysis," System Dynamics Review, System Dynamics Society, vol. 36(4), pages 497-522, October.
    5. Mohammad Reza Davahli & Waldemar Karwowski & Redha Taiar, 2020. "A System Dynamics Simulation Applied to Healthcare: A Systematic Review," IJERPH, MDPI, vol. 17(16), pages 1-27, August.

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