Development and validation of an intrinsic capacity score in the UK Biobank study.

Autor: Beyene MB; Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia; Adelaide Geriatrics Training and Research with Aged Care Centre (GTRAC), Faculty of Health and Medical Sciences, University of Adelaide, Woodville, SA, 5011, Australia., Visvanathan R; Adelaide Geriatrics Training and Research with Aged Care Centre (GTRAC), Faculty of Health and Medical Sciences, University of Adelaide, Woodville, SA, 5011, Australia; Aged and Extended Care Services, The Queen Elizabeth Hospital, Central Adelaide Local Health Network, Adelaide, SA, Australia., Ahmed M; Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia., Benyamin B; Australian Centre for Precision Health, Allied Health and Human Performance, University of South Australia, Adelaide 5000, Australia; South Australian Health and Medical Research Institute, Adelaide 5000, Australia., Beard JR; International Longevity Centre USA, Columbia University Mailman School of Public Health, NY, USA., Amare AT; Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia; Adelaide Geriatrics Training and Research with Aged Care Centre (GTRAC), Faculty of Health and Medical Sciences, University of Adelaide, Woodville, SA, 5011, Australia. Electronic address: azmeraw.amare@adelaide.edu.au.
Jazyk: angličtina
Zdroj: Maturitas [Maturitas] 2024 Jul; Vol. 185, pp. 107976. Date of Electronic Publication: 2024 Mar 17.
DOI: 10.1016/j.maturitas.2024.107976
Abstrakt: Background: In 2015, the World Health Organization introduced the concept of intrinsic capacity (IC) to define the individual-level characteristics that enable an older person to be and do the things they value. This study developed an intrinsic capacity score for UK Biobank study participants and validated its use as a tool for health outcome prediction, understanding healthy aging trajectories, and genetic research.
Methods: Our analysis included data from 45,208 UK biobank participants who had a complete record of the ten variables included in the analysis. Factor adequacy was tested using Kaiser-Meyer-Olkin, Barthelt's, and the determinant of matrix tests, and the number of factors was determined by the parallel analysis method. Exploratory and confirmatory factor analyses were employed to determine the structure and dimensionality of indicators. Finally, the intrinsic capacity score was generated, and its construct and predictive validities as well as reliability were assessed.
Results: The factor analysis identified a multidimensional construct comprising one general factor (intrinsic capacity) and five specific factors (locomotor, vitality, cognitive, psychological, and sensory). The bifactor structure showed a better fit (comparative fit index = 0.995, Tucker Lewis index = 0.976, root mean square error of approximation = 0.025, root mean square residual = 0.009) than the conventional five-factor structure. The intrinsic capacity score generated using the bifactor confirmatory factor analysis has good construct validity, as demonstrated by an inverse association with age (lower intrinsic capacity in older age; (β) =-0.035 (95%CI: -0.036, -0.034)), frailty (lower intrinsic capacity score in prefrail participants, β = -0.104 (95%CI: (-0.114, -0.094)) and frail participants, β = -0.227 (95%CI: -0.267, -0.186) than robust participants), and comorbidity (a lower intrinsic capacity score associated with increased Charlson's comorbidity index, β =-0.019 (95%CI: -0.022, -0.015)). The intrinsic capacity score also predicted comorbidity (a one-unit increase in baseline intrinsic capacity score led to a lower Charlson's comorbidity index, β = 0.147 (95%CI: -0.173, -0.121)) and mortality (a one-unit increase in baseline intrinsic capacity score led to 25 % lower risk of death, odds ratio = 0.75(95%CI: 0.663, 0.848)).
Conclusion: The bifactor structure showed a better fit in all goodness of fit tests. The intrinsic capacity construct has strong structural, construct, and predictive validities and is a promising tool for monitoring aging trajectories.
Competing Interests: Declaration of competing interest Professor Renuka Visvanathan and Professor John Beard are members of WHO Clinical Consortium in Healthy Aging; the views expressed in this article are those of the authors and do not necessarily reflect the views of WHO.
(Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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