Do changes in frailty, physical functioning, and cognitive functioning predict mortality in old age? Results from the Longitudinal Aging Study Amsterdam.

BACKGROUND

The ability to accurately predict survival in older adults is crucial as it guides clinical decision making. The added value of using various health indicators as well as changes in these indicators for predicting mortality remains unclear. The aim of this study was to investigate whether changes in health indicators such as frailty and physical performance improve mortality predictions in old age.

METHODS

This is a population based prospective cohort study on 995 community-dwelling people aged 68-92 years from the Longitudinal Aging Study Amsterdam. Two measurements at a three-year interval (1995/1996 and 1998/1999) were available for the frailty index, frailty phenotype, grip strength, walking speed, and Mini-Mental State Examination (MMSE). Cox regression was used to analyze mortality risks associated with the current health status and changes in health, with mortality data up to 2017. The extent to which these health indicators improved mortality predictions compared to models with age and sex only was assessed by the area under the receiver operating characteristic curve (AUC).

RESULTS

The AUC of age and sex for five-year mortality was 72.8% (95% CI 69.0 - 76.5) and was the lowest in the oldest old (age > 80.5 years). The added AUC of the current status of health indicators ranged from 0.7 to 3.3%. The added AUC of the three-year change was lower, ranging from -0.0 to 1.1%, whereas the added AUC of three-year change and current status combined was similar to current status alone, ranging from 0.6 to 3.2%. Across age, the added AUC of current status was highest in the oldest old, however there was no such pattern using three-year change. Overall, the frailty index appeared to improve mortality predictions the most, followed by the frailty phenotype, MMSE, grip strength, and walking speed.

CONCLUSIONS

Current health status improved mortality predictions better than changes in health. Its contribution was highest in the oldest old, but the added value to models with age and sex only was limited.