Comparison of alternate scoring of variables on the performance of the frailty index

Abstract

BackgroundThe frailty index (FI) is used to measure the health status of ageing individuals. An FI is constructed as the proportion of deficits present in an individual out of the total number of age-related health variables considered. The purpose of this study was to systematically assess whether dichotomizing deficits included in an FI affects the information value of the whole index.MethodsSecondary analysis of three population-based longitudinal studies of community dwelling individuals: Nova Scotia Health Survey (NSHS, n = 3227 aged 18+), Survey of Health, Ageing and Retirement in Europe (SHARE, n = 37546 aged 50+), and Yale Precipitating Events Project (Yale-PEP, n = 754 aged 70+). For each dataset, we constructed two FIs from baseline data using the deficit accumulation approach. In each dataset, both FIs included the same variables (23 in NSHS, 70 in SHARE, 33 in Yale-PEP). One FI was constructed with only dichotomous values (marking presence or absence of a deficit); in the other FI, as many variables as possible were coded as ordinal (graded severity of a deficit). Participants in each study were followed for different durations (NSHS: 10 years, SHARE: 5 years, Yale PEP: 12 years).ResultsWithin each dataset, the difference in mean scores between the ordinal and dichotomous-only FIs ranged from 0 to 1.5 deficits. Their ability to predict mortality was identical; their absolute difference in area under the ROC curve ranged from 0.00 to 0.02, and their absolute difference between Cox Hazard Ratios ranged from 0.001 to 0.009.ConclusionsAnalyses from three diverse datasets suggest that variables included in an FI can be coded either as dichotomous or ordinal, with negligible impact on the performance of the index in predicting mortality.

Prevalence of and factors associated with frailty and disability in older adults from China, Ghana, India, Mexico, Russia and South Africa

“…Yet, the frailty index and WHODAS remain robust screening tools for complex and multidimensional conditions [33][34][35]. The frailty index, with mean frailty levels in SAGE are similar to those found in other studies in Chinese populations [36][37][38], and in Mexico [9].…”

Hypoglycemia in Older People - A Less Well Recognized Risk Factor for Frailty

“…Its definition was previously based on the presence of three or more phenotypes (weight loss, weakness, decreased physical activity, exhaustion and slow gait speed) [41] although it can be measured indirectly by a Frailty Index using the cumulative effects of multiple health deficits to quantify the underlying health status of the individual [42]. Measuring frailty by using the Frailty Index substantially classifies older people as frail than using the phenotypic definition approach (22.7% vs 8.7%) [43].…”

Ageing well: a review of sarcopenia and frailty

“…Frailty is then quantified according to the proportion of deficits present and, although designed to be used as a continuous scale, an index value of about 0·20-0·25 (regardless of age) is usually accepted as the threshold above which frailty is present (14) . The deficit approach to frailty measurement was pioneered by Kenneth Rockwood and Arnold Mitnitski in the Canadian Study of Health and Ageing (16) but has since been applied in other cohorts (15,(17)(18)(19) . The components of one FI are exemplified in Fig.…”