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Who live longer than their age peers: individual predictors of longevity among older individuals.
Nosraty, Lily; Deeg, Dorly; Raitanen, Jani; Jylhä, Marja.
Afiliación
  • Nosraty L; Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), Tampere University, N33014, Tampere, Finland. Lily.Nosraty@tuni.fi.
  • Deeg D; Department of Epidemiology and Data Science, and Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, VU University, Amsterdam, The Netherlands.
  • Raitanen J; Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), The UKK Institute for Health Promotion Research, Tampere University, Tampere, Finland.
  • Jylhä M; Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), Tampere University, N33014, Tampere, Finland.
Aging Clin Exp Res ; 35(3): 677-688, 2023 Mar.
Article en En | MEDLINE | ID: mdl-36583848
ABSTRACT

BACKGROUND:

There are a very few studies focusing on the individual-based survival with a long follow-up time.

AIM:

To identify predictors and determine their joint predictive value for longevity using individual-based outcome measures.

METHODS:

Data were drawn from Tampere Longitudinal Study on Aging (TamELSA), a study of individuals' age 60-89 years (N = 1450) with a mortality follow-up of up to 35 years. Two measures of longevity were used the longevity difference (LD) and realized probability of dying (RPD), both of which compare each individual's longevity with their life expectancy as derived from population life tables. Independent variables were categorized into five domains sociodemographic, health and functioning, subjective experiences, social activities, and living conditions. Linear regression models were used in three

steps:

bivariate analysis for each variable, multivariate analysis based on backward elimination for each domain, and one final model.

RESULTS:

The most important predictors of both outcomes were marital status, years smoked regularly, mobility, self-rated health, endocrine and metabolic diseases, respiratory diseases, and unwillingness to do things or lack of energy. The explained variance in longevity was 13.8% for LD and 14.1% for RPD. This demonstrated a large proportion of unexplained error margins for the prediction of individual longevity, even though many known predictors were used. DISCUSSION AND

CONCLUSIONS:

Several predictors associated with longer life were found. Yet, on an individual level, it remains difficult to predict who will live longer than their age peers. The stochastic element in the process of aging and in death may affect this prediction.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Envejecimiento / Longevidad Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Aged80 / Humans Idioma: En Revista: Aging Clin Exp Res Asunto de la revista: GERIATRIA Año: 2023 Tipo del documento: Article País de afiliación: Finlandia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Envejecimiento / Longevidad Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Aged80 / Humans Idioma: En Revista: Aging Clin Exp Res Asunto de la revista: GERIATRIA Año: 2023 Tipo del documento: Article País de afiliación: Finlandia