TY - JOUR
T1 - Who live longer than their age peers
T2 - individual predictors of longevity among older individuals
AU - Nosraty, Lily
AU - Deeg, Dorly
AU - Raitanen, Jani
AU - Jylhä, Marja
N1 - Funding Information: This study was supported by the Academy of Finland (projects 287372 and 312311), and the Competitive State Research Financing of the Expert Responsibility area of Tampere University Hospital to Jylhä M. and the Pirkanmaa and Central Cultural Funds to Nosraty L. ((grant numbers: 50191968 and 00200788). The work was partly done in the framework of the Centre of Excellence in Research on Aging and Care. The authors have no competing interests to declare that are relevant to the content of this article. Each author has participated in the research reported and has agreed to be an author on the manuscript. Publisher Copyright: © 2022, The Author(s).
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Absolute measure
KW - Individual-based measure of longevity
KW - Mortality
KW - Relative measure
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85145181896&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/36583848
UR - http://www.scopus.com/inward/record.url?scp=85145181896&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/s40520-022-02323-5
DO - https://doi.org/10.1007/s40520-022-02323-5
M3 - Article
C2 - 36583848
SN - 1594-0667
JO - Aging Clinical and Experimental Research
JF - Aging Clinical and Experimental Research
ER -