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Background This study aims to examine temporal trends in frailty state transitions, and years spent frail, in older Swedish adults. Methods We followed the Swedish National Study on Aging and Care in Kungsholmen participants from baseline (2001–2004) for 15 (median: 9.6) years. A 40-deficit frailty index (FI) was constructed to identify 3 frailty states: robust (FI ≤ 0.125), mild frailty (0.125 < FI ≤   0.25), and moderate and severe frailty (FI  > 0.25). Multistate survival analyses were implemented to obtain hazard ratios (HRs) for frailty state transitions, with birth year and sex as predictors. To examine temporal trends, frailty state-specific life expectancies at age 60 were forecasted for robust persons born in different years (1900, 1910, 1920, 1930, and 1940), also by sex. Results At baseline, the 2 941 participants' mean age was 75 years and 65% were women. Predicted life expectancy and time spent frail from age 60 followed an increasing trend by birth year. Hazards of transitioning from mild frailty to death (HR: 0.89; 95% confidence interval [CI]: 0.83–0.97) and moderate and severe frailty to death (HR: 0.98; 95% CI: 0.97–1.00) were lower for those born later. Women were less likely to transition from robust to mild frailty (HR: 0.81; 95% CI: 0.70–0.93), mild frailty to moderate and severe frailty (HR: 0.80; 95% CI: 0.68–0.93), and moderate and severe frailty to death (HR: 0.68; 95% CI: 0.59–0.78), but spent more time frail. Conclusions Our results point to an expansion of time spent frail among older Swedish adults over time. [ABSTRACT FROM AUTHOR]

Background There is a growing interest in generating precise predictions of survival to improve the assessment of health and life-improving interventions. We aimed to (a) test if observable characteristics may provide a survival prediction independent of chronological age; (b) identify the most relevant predictors of survival; and (c) build a metric of multidimensional age. Methods Data from 3 095 individuals aged ≥60 from the Swedish National Study on Aging and Care in Kungsholmen. Eighty-three variables covering 5 domains (diseases, risk factors, sociodemographics, functional status, and blood tests) were tested in penalized Cox regressions to predict 18-year mortality. Results The best prediction of mortality at different follow-ups (area under the receiver operating characteristic curves [AUROCs] 0.878–0.909) was obtained when 15 variables from all 5 domains were tested simultaneously in a penalized Cox regression. Significant prediction improvements were observed when chronological age was included as a covariate for 15- but not for 5- and 10-year survival. When comparing individual domains, we find that a combination of functional characteristics (ie, gait speed, cognition) gave the most accurate prediction, with estimates similar to chronological age for 5- (AUROC 0.836) and 10-year (AUROC 0.830) survival. Finally, we built a multidimensional measure of age by regressing the predicted mortality risk on chronological age, which displayed a stronger correlation with time to death (R = −0.760) than chronological age (R = −0.660) and predicted mortality better than widely used geriatric indices. Conclusions Combining easily accessible characteristics can help in building highly accurate survival models and multidimensional age metrics with potentially broad geriatric and biomedical applications. [ABSTRACT FROM AUTHOR]