RESUMO
BACKGROUND: Most previous studies of frailty trajectories in older adults focus on the average trajectory and ignore death. Longitudinal quantile analysis of frailty trajectories permits the definition of reference curves, and the application of mortal cohort inference provides more realistic estimates than models that ignore death. METHODS: Using data from individuals aged 65 or older (nâ =â 25 446) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) from 2004 to 2020, we derived repeated values of the Frailty Index (FI) based on the accumulation of health deficits. We applied weighted Generalized Estimating Equations to estimate the quantiles of the FI trajectory, adjusting for sample attrition due to death, sex, education, and cohort. RESULTS: The FI quantiles increased with age and progressed faster for those with the highest level of frailty (ß^a0.9 = 0.0229, pâ <â .001; ß^a0.5 = 0.0067, pâ <â .001; H0: ßa0.5=ßa0.9, pâ <â .001). Education was consistently associated with a slower progression of the FI in all quantiles (ß^ae0.1 = -0.0001, pâ <â .001; ß^ae0.5 =-0.0004, pâ <â .001; ß^ae0.9 = -0.0003, pâ <â .001) but sex differences varied across the quantiles. Women with the highest level of frailty showed a slower progression of the FI than men when considering death. Finally, no cohort effects were observed for the FI progression. CONCLUSIONS: Quantile FI trajectories varied by age, sex, education, and cohort. These differences could inform the practice of interventions aimed at older adults with the highest level of frailty.
Assuntos
Fragilidade , Idoso , Humanos , Feminino , Masculino , Idoso Fragilizado , Avaliação Geriátrica , Estudos Longitudinais , EnvelhecimentoRESUMO
BACKGROUND: International comparisons of trajectories of depressive symptoms in older adults are scarce and longitudinal associations with co-morbid conditions not fully understood. OBJECTIVE: To compare trajectories of depressive symptoms from participants living in 10 European Countries and identify ages at which the associations of co-morbid conditions with these trajectories become more relevant. METHODS: Latent growth curve models were fitted to depressive symptoms scores from participants of the Survey of Health and Retirement in Europe (SHARE) initiative (combined n = 21,253) and co-morbid conditions modelled as time varying covariates. To identify the ages at which the association between co-morbid conditions and depressive symptoms was significant the Johnson-Neyman (JN) technique was used. RESULTS: The shape of depressive symptoms trajectories varied between countries, and was highly dependent on modelling decisions. The association between the average number of co-morbidities reported over time and depressive symptoms was consistent and positive across countries and ages. CONCLUSION: International differences in ageing-related trajectories of depressive symptoms emerged. The longitudinal association of co-morbid conditions with trajectories of depressive symptoms was found, but the results overall suggest that modelling decisions could greatly influence the outcomes, and should thus be interpreted with caution.