Frailty or Frailties: Exploring Frailty Index Subdimensions in the English Longitudinal Study of Ageing

TL;DR

This study identifies four distinct subdimensions of frailty in older adults using factor analysis, revealing that these subdimensions better predict quality of life than a single frailty score.

Contribution

It introduces a novel approach to decompose the frailty index into meaningful subdimensions, enhancing understanding of individual health variations.

Findings

Four frailty subdimensions identified: mobility, daily activities, mental health, disorientation.

Subdimensions predict quality of life better than overall frailty scores.

Decomposed frailty approach offers nuanced health assessment.

Abstract

Background: Frailty, a state of increased vulnerability to adverse health outcomes, has garnered significant attention in research and clinical practice. Existing constructs aggregate clinical features or health deficits into a single score. While simple and interpretable, this approach may overlook the complexity of frailty and not capture the full range of variation between individuals. Methods: Exploratory factor analysis was used to infer latent dimensions of a frailty index constructed using survey data from the English Longitudinal Study of Ageing (ELSA), wave 9. The dataset included 58 self-reported health deficits in a representative sample of community-dwelling adults aged 65+ (N = 4971). Deficits encompassed chronic disease, general health status, mobility, independence with activities of daily living, psychological wellbeing, memory and cognition. Multiple linear regression examined associations with CASP-19 quality of life scores. Results: Factor analysis revealed four frailty subdimensions. Based on the component deficits with the highest loading values, these factors were labelled "Mobility Impairment and Physical Morbidity", "Difficulties in Daily Activities", "Mental Health" and "Disorientation in Time". The four subdimensions were a better predictor of quality of life than frailty index scores. Conclusions: Distinct subdimensions of frailty can be identified from standard index scores. A decomposed approach to understanding frailty has potential to provide a more nuanced understanding of an individual's state of health across multiple deficits.