How to construct a frailty index from an existing dataset in 10 steps.

TitleHow to construct a frailty index from an existing dataset in 10 steps.
Publication TypeJournal Article
Year of Publication2023
AuthorsTheou, O, Haviva, C, Wallace, L, Searle, SD, Rockwood, K
JournalAge and Ageing
Volume52
Issue12
ISSN Number1468-2834
KeywordsAged, Aging, Frail Elderly, Frailty, Geriatric Assessment, Humans, Retrospective Studies
Abstract

BACKGROUND: The frailty index is commonly used in research and clinical practice to quantify health. Using a health deficit accumulation model, a frailty index can be calculated retrospectively from data collected via survey, interview, performance test, laboratory report, clinical or administrative medical record, or any combination of these. Here, we offer a detailed 10-step approach to frailty index creation, with a worked example.

METHODS: We identified 10 steps to guide the creation of a valid and reliable frailty index. We then used data from waves 5 to 12 of the Health and Retirement Study (HRS) to illustrate the steps.

RESULTS: The 10 steps are as follows: (1) select every variable that measures a health problem; (2) exclude variables with more than 5% missing values; (3) recode the responses to 0 (no deficit) through 1 (deficit); (4) exclude variables when coded deficits are too rare (< 1%) or too common (> 80%); (5) screen the variables for association with age; (6) screen the variables for correlation with each other; (7) count the variables retained; (8) calculate the frailty index scores; (9) test the characteristics of the frailty index; (10) use the frailty index in analyses. In our worked example, we created a 61-item frailty index following these 10 steps.

CONCLUSIONS: This 10-step procedure can be used as a template to create one continuous health variable. The resulting high-information variable is suitable for use as an exposure, predictor or control variable, or an outcome measure of overall health and ageing.

DOI10.1093/ageing/afad221
Citation Key13788
PubMed ID38124255
PubMed Central IDPMC10733590
Grant ListR03 AG043052 / AG / NIA NIH HHS / United States
NIA U01AG009740 / AG / NIA NIH HHS / United States