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A multistate model to project elderly disability in case of limited data

Author

Listed:
  • Nicole L. Van Der Gaag

    (Nederlands Interdisciplinair Demografisch Instituut (NIDI))

  • Joop de Beer

    (Nederlands Interdisciplinair Demografisch Instituut (NIDI))

  • Govert Ewout Bijwaard

    (Nederlands Interdisciplinair Demografisch Instituut (NIDI))

  • Luc Bonneux

    (Groenhuysen)

Abstract

Background: Prevalence of disability depends on when a person becomes disabled (disability incidence) and when he or she dies (mortality). Multistate projection models can take into account both underlying processes of disability prevalence. The application of these models, however, is often hampered by high data requirements. Objective: This paper describes a generic estimation procedure for calculating disability incidence rates and mortality rates by disability status from data on disability prevalence and overall mortality. The procedure allows for the addition of risk factors. Methods: We estimate disability incidence rates from disability prevalence and mortality rates by disability status using prevalence data on disability from SHARE and mortality data from Eurostat and the Rotterdam Study of Health (ERGO). We use these rates to project future trends of ADL-disability prevalence among the elderly in the Netherlands for the period 2008-2040 using the multistate projection model LIPRO. Results: This paper shows that even in the case of limited data, multistate projection models can be applied to project trends in disability prevalence. In a scenario that assumes constant disability incidence rates, disability prevalence among the elderly will increase even though the mortality rates of disabled persons exceed those of non-disabled people. In a scenario that assumes declining incidence rates at the same pace as declining mortality rates, disability prevalence will be significantly lower. This latter scenario results in an almost similar decline in disability prevalence as the scenario assuming a strong reduction of age-specific obesity among the elderly. One conclusion, therefore, could be that the prevalence of obesity should be seriously reduced to reach a strong reduction of disability incidence. Conclusions: The strength of this method to calculate disability incidence-rates based on disability prevalence-rates is that the relationship between changes in mortality and changes in disability is taken into account, and that the effects of risk factors can be estimated. The improved transparency of the projections, the generic nature of the model and the applicability to all (European) countries with disability prevalence data make it a useful instrument for making plausible projections of future patterns of disability prevalence based on disability incidence.

Suggested Citation

  • Nicole L. Van Der Gaag & Joop de Beer & Govert Ewout Bijwaard & 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.
    • Handle: RePEc:dem:demres:v:32:y:2015:i:3
    DOI: 10.4054/DemRes.2015.32.3
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    References listed on IDEAS

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    1. Bartosz Przywara, 2010. "Projecting future health care expenditure at European level: drivers, methodology and main results," European Economy - Economic Papers 2008 - 2015 417, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    2. Roberto Impicciatore & Francesco Billari, 2011. "MAPLES: A general method for the estimation of age profiles from standard demographic surveys (with an application to fertility)," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 24(29), pages 719-748.
    3. Ehsan Khoman & James Mitchell & Martin Weale, 2008. "Incidence‐based estimates of life expectancy of the healthy for the UK: coherence between transition probabilities and aggregate life‐tables," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 203-222, January.
    4. Liming Cai & James Lubitz, 2007. "Was there compression of disability for older Americans from 1992 to 2003?," Demography, Springer;Population Association of America (PAA), vol. 44(3), pages 479-495, August.
    5. James W. Vaupel, 2010. "Biodemography of human ageing," Nature, Nature, vol. 464(7288), pages 536-542, March.
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    Cited by:

    1. William Lim & Gaurav Khemka & David Pitt & Bridget Browne, 2019. "A method for calculating the implied no-recovery three-state transition matrix using observable population mortality incidence and disability prevalence rates among the elderly," Journal of Population Research, Springer, vol. 36(3), pages 245-282, September.
    2. 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.

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    More about this item

    Keywords

    projections; long-term care; obesity; multistate models; disability;
    All these keywords.

    JEL classification:

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

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