Abstract
The quantification of biological age in humans is an important scientific endeavor in the face of ageing populations. The frailty index (FI) methodology is based on the accumulation of health deficits and captures variations in health status within individuals of the same age. The aims of this study were to assess whether the addition of age to an FI improves its mortality prediction and whether the associations of the individual FI items differ in strength. We utilized data from The Irish Longitudinal Study on Ageing to conduct, by sex, machine learning analyses of the ability of a 32-item FI to predict 8-year mortality in 8174 wave 1 participants aged 50 or more years. By wave 5, 559 men and 492 women had died. In the absence of age, the FI was an acceptable predictor of mortality with AUCs of 0.7. When age was included, AUCs improved to 0.8 in men and 0.9 in women. After age, deficits related to physical function and self-rated health tended to have higher importance scores. Not all FI variables seemed equally relevant to predict mortality, and age was by far the most relevant feature. Chronological age should remain an important consideration when interpreting the prognostic significance of an FI.
Highlights
As populations get older, the association between chronological age and health status becomes increasingly heterogeneous [1]
Our study revealed that in the absence of age, the frailty index (FI) was an acceptable predictor of mortality with area under the curve (AUC) of 0.7
Our results suggest that the addition of chronological age significantly enhanced the ability of the FI to classify mortality events
Summary
The association between chronological age and health status becomes increasingly heterogeneous [1]. The frailty index (FI) methodology was introduced by Rockwood and colleagues [4,5] to quantify the accumulation of people’s health ‘deficits’ (i.e., symptoms, clinical signs, medical conditions and disabilities) at a given chronological age. This method has allowed for the establishment of potentially useful population norms [6] and the study of influences of wider determinants of health on the variation in health status within people of a similar chronological age [7]. It has been suggested that given the age-related nature of its constituent deficits, the FI should be interpreted jointly with age [12]
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