Longitudinal change in physical functioning and dropout due to death among the oldest old: a comparison of three methods of analysis.
Longitudinal studies examining changes in physical functioning with advancing age among very old people are plagued by high death rates, which can lead to biased estimates. This study was conducted to analyse changes in physical functioning among the oldest old with three distinct methods which diff...
| Publicado en: | European Journal of Ageing Vol. 17; no. 2; pp. 207 - 217 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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Springer Nature
Jun2020
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=143738263&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 143738263 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 16139372 3RAL jtl: European Journal of Ageing issn: 16139372 maglogo: N pubinfo: dt: Jun2020 vid: 17 iid: 2 pid: 237 pub: Springer Nature artinfo: ui: 143738263 10.1007/s10433-019-00533-x ppf: 207 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.5MB tig: atl: Longitudinal change in physical functioning and dropout due to death among the oldest old: a comparison of three methods of analysis. aug: au: Raitanen, Jani Stenholm, Sari Tiainen, Kristina Jylhä, Marja Nevalainen, Jaakko affil: Faculty of Social Sciences (Health Sciences), Tampere University, PO Box 100, 33014, Tampere, Finland UKK Institute for Health Promotion Research, PO Box 30, 33501, Tampere, Finland Department of Public Health, University of Turku and Turku University Hospital, PO Box 52, 20521, Turku, Finland Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland Gerontology Research Center, Tampere University, PO Box 100, 33014, Tampere, Finland Science Center of Tampere University Hospital, PO Box 2000, 33521, Tampere, Finland su: Elder care Aging Life expectancy Life skills Mortality risk factors Geriatric assessment Comparative studies Functional assessment Longitudinal method Risk assessment Statistical models sug: subj: Elder care Aging Life expectancy Life skills Continuing Care Retirement Communities Mortality risk factors Geriatric assessment Comparative studies Functional assessment Longitudinal method Risk assessment Statistical models keyword: Attrition due to death Functioning Joint model Longitudinal study Model comparison Attrition due to death Functioning Joint model Longitudinal study Model comparison ab: Longitudinal studies examining changes in physical functioning with advancing age among very old people are plagued by high death rates, which can lead to biased estimates. This study was conducted to analyse changes in physical functioning among the oldest old with three distinct methods which differ in how they handle dropout due to death. The sample consisted of 3992 persons aged 90 or over in the Vitality 90+ Study who were followed up on average for 2.5 years (range 0–13 years). A generalized estimating equation (GEE) with independent 'working' correlation, a linear mixed-effects (LME) model and a joint model consisting of longitudinal and survival submodels were used to estimate the effect of age on physical functioning over 13 years of follow-up. We observed significant age-related decline in physical functioning, which furthermore accelerated significantly with age. The average rate of decline differed markedly between the models: the GEE-based estimate for linear decline among survivors was about one-third of the average individual decline in the joint model and half the decline indicated by the LME model. In conclusion, the three methods yield substantially different views on decline in physical functioning: the GEE model may be useful for considering the effect of intervention measures on the outcome among living people, whereas the LME model is biased regarding studying outcomes associated with death. The joint model may be valuable for predicting the future characteristics of the oldest old and planning elderly care as life expectancy continues gradually to rise. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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