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Healthy longevity from incidence-based models: More kinds of health than stars in the sky

Author

Listed:
  • Hal Caswell

    (Universiteit van Amsterdam)

  • Silke van Daalen

    (Universiteit van Amsterdam)

Abstract

Background: Healthy longevity (HL) is an important measure of the prospects for quality of life in ageing societies. Incidence-based (cf. prevalence-based) models describe transitions among age classes and health stages. Despite the probabilistic nature of those transitions, analyses of healthy longevity have focused persistently on means (``health expectancy''), neglecting variances and higher moments. Objective: Our goal is a comprehensive methodology to analyze HL in terms of any combination of health stages and age classes, or of transitions among health stages, or of values (e.g., quality of life) associated with health stages or transitions. Methods: We construct multistate Markov chains for individuals classified by age and health stage and use Markov chains with rewards to compute all moments of HL. Results: We present a new and straightforward algorithm to create the multistate reward matrices for occupancy, transitions, or values associated with occupancy or transitions. As an example, we analyze a published model for colorectal cancer. The possible definitions of HL in this simple model outnumber the stars in the visible universe. Our method can analyze any of them; we show four examples: longevity without abnormal cells, cancer-free longevity, and longevity with cancer before or after a critical age. Contribution: Our methods make it possible to analyze any incidence-based model,with any number of health stages, any pattern of transitions, and any kind of values assigned to stages. It is easily computable, requires no simulations, provides all the moments of healthy longevity, and solves the inhomogeneity problem.

Suggested Citation

  • Hal Caswell & Silke van Daalen, 2021. "Healthy longevity from incidence-based models: More kinds of health than stars in the sky," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(13), pages 397-452.
    • Handle: RePEc:dem:demres:v:45:y:2021:i:13
    DOI: 10.4054/DemRes.2021.45.13
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    References listed on IDEAS

    as
    1. Hal Caswell, 2014. "A matrix approach to the statistics of longevity in heterogeneous frailty models," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(19), pages 553-592.
    2. Nicole L. Van Der Gaag & Govert Ewout Bijwaard & Joop de Beer & Luc Bonneux, 2015. "A multistate model to project elderly disability in case of limited data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(3), pages 75-106.
    3. Michael D. Hurd & Pierre-Carl Michaud & Susann Rohwedder, 2014. "The Lifetime Risk of Nursing Home Use," NBER Chapters, in: Discoveries in the Economics of Aging, pages 81-109, National Bureau of Economic Research, Inc.
    4. Andrel Rogers & Jacques Ledent, 1976. "Increment-decrement life tables: A comment," Demography, Springer;Population Association of America (PAA), vol. 13(2), pages 287-290, May.
    5. Silke van Daalen & Hal Caswell, 2015. "Lifetime reproduction and the second demographic transition: Stochasticity and individual variation," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 33(20), pages 561-588.
    6. Frans Willekens & Hein Putter, 2014. "Software for multistate analysis," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(14), pages 381-420.
    7. Roth, Gregory & Caswell, Hal, 2018. "Occupancy time in sets of states for demographic models," Theoretical Population Biology, Elsevier, vol. 120(C), pages 62-77.
    8. Hartemink, Nienke & Missov, Trifon I. & Caswell, Hal, 2017. "Stochasticity, heterogeneity, and variance in longevity in human populations," Theoretical Population Biology, Elsevier, vol. 114(C), pages 107-116.
    9. Liming Cai & Mark D. Hayward & Yasuhiko Saito & James Lubitz & Aaron Hagedorn & Eileen Crimmins, 2010. "Estimation of multi-state life table functions and their variability from complex survey data using the SPACE Program," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 22(6), pages 129-158.
    10. David A. Wise, 2014. "Discoveries in the Economics of Aging," NBER Books, National Bureau of Economic Research, Inc, number wise13-1, June.
    11. Jackson, Christopher, 2011. "Multi-State Models for Panel Data: The msm Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 38(i08).
    12. James Vaupel & Vladimir Romo, 2003. "Decomposing change in life expectancy: A bouquet of formulas in honor of Nathan Keyfitz’s 90th birthday," Demography, Springer;Population Association of America (PAA), vol. 40(2), pages 201-216, May.
    13. Solveig Christiansen & Nico Keilman, 2013. "Probabilistic household forecasts based on register data- the case of Denmark and Finland," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(43), pages 1263-1302.
    14. Ryan D. Edwards & Shripad Tuljapurkar, 2005. "Inequality in Life Spans and a New Perspective on Mortality Convergence Across Industrialized Countries," Population and Development Review, The Population Council, Inc., vol. 31(4), pages 645-674, December.
    15. Marty Parker & Milica Bucknall & Carol Jagger & Ross Wilkie, 2020. "Extending Working Lives: A Systematic Review of Healthy Working Life Expectancy at Age 50," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 150(1), pages 337-350, July.
    16. Hal Caswell, 2011. "Beyond R0: Demographic Models for Variability of Lifetime Reproductive Output," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-21, June.
    17. van Daalen, Silke & Caswell, Hal, 2020. "Variance as a life history outcome: Sensitivity analysis of the contributions of stochasticity and heterogeneity," Ecological Modelling, Elsevier, vol. 417(C).
    18. Hal Caswell, 2020. "The formal demography of kinship II: Multistate models, parity, and sibship," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(38), pages 1097-1146.
    19. Hal Caswell & Fanny Annemarie Kluge, 2015. "Demography and the statistics of lifetime economic transfers under individual stochasticity," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(19), pages 563-588.
    20. Agnes Lievre & Nicolas Brouard & Christopher Heathcote, 2003. "The Estimation Of Health Expectancies From Cross-Longitudinal Surveys," Mathematical Population Studies, Taylor & Francis Journals, vol. 10(4), pages 211-248.
    21. Govert Ewout Bijwaard, 2014. "Multistate event history analysis with frailty," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(58), pages 1591-1620.
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    Cited by:

    1. Hal Caswell, 2023. "The contributions of stochastic demography and social inequality to lifespan variability," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 49(13), pages 309-354.
    2. Magdalena Muszyńska-Spielauer & Marc Luy, 2022. "Well-Being Adjusted Health Expectancy: A New Summary Measure of Population Health," European Journal of Population, Springer;European Association for Population Studies, vol. 38(5), pages 1009-1031, December.

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    More about this item

    Keywords

    cancer; Markov chains; health demography; incidence models; matrix methods; stochastic models; healthy longevity;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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