- Data, Statistics and AI for Well-Being of People and Organisations
- A cura di Luigi Fabbris, Alberto Franci, Pietro Renzi
Estimating disability prevalence and incidence in Italy using a multistate model: Merging information from different sources
- Enrico Roma
- Rossella Miglio
- © 2026 Author(s) |
- CC BY 4.0
- DOI: 10.36253/979-12-215-1062-1.63
Disability is a key determinant of social exclusion, poor health, and premature mortality. Understanding its progression and monitoring its prevalence are essential for policy planning in ageing societies. In Italy, two complementary data sources are available: the AVQ survey, conducted annually from 2013 to 2023, provides regionally representative prevalence estimates but no longitudinal follow-up; the SHARE study, collected biennially between 2004 and 2022, follows individuals over time and enables estimation of transition dynamics. However, SHARE data are interval-censored, meaning that transitions between health states are only known to occur between interviews, except for deaths, which are dated exactly. This study integrates both datasets to estimate disability prevalence and transitions across age. A continuous-time Markov model describes transitions among three states: healthy, with limitation, and dead, allowing for recovery. Transition intensities are modeled as smooth, age-dependent functions under a proportional hazards assumption, including the effects of two covariates: gender and education. Semiparametric estimation is performed using penalized B-splines. The estimated intensities are used to compute transition probabilities and, subsequently, age-specific model-based disability prevalences. These prevalences are then used as parameters in a binomial model for GALI responses in the AVQ sample. Parameters are estimated by maximizing a joint penalized likelihood combining both sources. Preliminary findings show that transition rates from healthy to disabled and from disabled to dead increase sharply with age. Transition patterns differ by gender and education: women experience more disability transitions, while men face higher mortality. Lower education is associated with greater disability risk, reduced recovery, and higher mortality. The model supports improved projections and planning in ageing populations.
- Keywords:
- synthetic data,
- telecommunication,
- call detail records,
Alma Mater Studiorum University of Bologna, Italy - ORCID: 0000-0003-3957-3087
Alma Mater Studiorum University of Bologna, Italy - ORCID: 0000-0001-7968-0368
- Bergmann, M., Kneip, T., De Luca, G., Scherpenzeel, A. (2019). Survey participation in the Survey of Health, Ageing and Retirement in Europe (SHARE), Wave 1–7. Based on Release 7.0.0. SHARE Working Paper Series, 41-2019. MEA, Max Planck Institute for Social Law and Social Policy, Munich, (DE). DOI: 10.1332/175795919x15694136530293
- Börsch-Supan, A., Brandt, M., Hunkler, C., Kneip, T., Korbmacher, J., Malter, F., Schaan, B., Stuck, S., Zuber, S. (2013). Data resource profile: The survey of health, ageing and retirement in Europe (SHARE). International Journal of Epidemiology, 42(4), pp. 992-1001. DOI: 10.1093/ije/dyt088
- Cox, D.R., Miller, H.D. (1965). The Theory of Stochastic Processes. Chapman & Hall, London, (UK). DOI: 10.2307/1266653
- Eurostat (2020). Ageing Europe – Statistics on Population Developments. Eurostat Statistics Explained. Available at: https://ec.europa.eu/eurostat/statisticsexplained/index.php?title= Ageing_Europe_-_statistics_on_population_developments. Accessed: 28 January 2025.
- Istat (2015). Aspetti della vita quotidiana. Data: 2013–2022. Available at: https://www.istat.it/microdati/aspetti-della-vita-quotidiana/. Accessed: 1 September 2025.
- Kuper, H., Rotenberg, S., Azizatunnisa, L., Morgon Banks, L., Smythe, T. (2024). The association between disability and mortality: a mixed-methods study. The Lancet Public Health, 9(5), pp. e306-e315. DOI: 10.1016/s2468-2667(24)00054-9
- Machado, R.J., van den Hout, A., Marra, G. (2021). Penalised maximum likelihood estimation in multi-state models for interval-censored data. Computational Statistics & Data Analysis, 153, pp. 107057. DOI: 10.1016/j.csda.2020.107057
- Officer, A., Posarac, A. (2011). World Report on Disability. World Health Organization, Geneva, (CH). DOI: 10.5195/ijt.2011.6076
- Robine, J., Jagger, C., Euro-REVES Group. (2003). Creating a coherent set of indicators to monitor health across Europe: The EuroREVES 2 project. European Journal of Public Health, 13(Suppl 3), pp. 6-14. DOI: 10.1093/eurpub/13.suppl_3.6
- Roma, E., Miglio, R. (2025). Disability trends in selected European countries: An age-period-cohort analysis. Rivista Italiana di Economia Demografia e Statistica, pp. 199-210. DOI: 10.71014/sieds.v79i4.354
- SHARE-ERIC. (2024). Survey of Health, Ageing and Retirement in Europe (SHARE), Waves 1–9. Release version: 9.0.0. DOIs: 10.6103/SHARE.w1.900; w2.900; w4.900; w5.900; w6.900; w7.900; w8.900; w9.900. DOI: 10.6103/SHARE.w1.900
- Smythe, T., Kuper, H. (2024). The association between disability and all-cause mortality in low-income and middle-income countries: a systematic review and meta-analysis. The Lancet Global Health, 12(5), pp. e756-e770. DOI: 10.1016/s2214-109x(24)00042-1
- Van der Gaag, N., Bijwaard, G., de Beer, J., Bonneux, L. (2015). A multistate model to project elderly disability in case of limited data. Demographic Research, 32, pp. 75-106. DOI: 10.4054/demres.2015.32.3
- Van Imhoff, E. (1990). The exponential multidimensional demographic projection model. Mathematical Population Studies, 2(3), pp. 171-182. DOI: 10.1080/08898489009525305
Informazioni sul capitolo
Titolo del capitolo
Estimating disability prevalence and incidence in Italy using a multistate model: Merging information from different sources
Autori
Enrico Roma, Rossella Miglio
Lingua
Inglese
DOI
10.36253/979-12-215-1062-1.63
Opera sottoposta a peer review
Anno di pubblicazione
2026
Copyright
© 2026 Author(s)
Licenza d'uso
Licenza dei metadati
Informazioni bibliografiche
Titolo del libro
Data, Statistics and AI for Well-Being of People and Organisations
Curatori
Luigi Fabbris, Alberto Franci, Pietro Renzi
Opera sottoposta a peer review
Numero di pagine
420
Anno di pubblicazione
2026
Copyright
© 2026 Author(s)
Licenza d'uso
Licenza dei metadati
Editore
Firenze University Press
DOI
10.36253/979-12-215-1062-1
ISBN Print
979-12-215-1061-4
eISBN (pdf)
979-12-215-1062-1
eISBN (xml)
979-12-215-1063-8
Collana
Applied Statistics Series