A multidimensional biomarker model of vitality and its associations with intrinsic capacity and frailty

BACKGROUND: The World Health Organisation has identified intrinsic capacity (IC) as a key determinant of healthy ageing. Within the IC framework, vitality reflects physiological reserve arising from neuromuscular, metabolic and inflammatory/stress-response systems. However, this multidomain physiological construct has not been empirically validated, and vitality is often operationalised using nutritional assessments alone. OBJECTIVES: We evaluated a biomarker-derived vitality construct and examined its associations with IC domains and frailty, compared to nutritional measures. METHODS: Cross-sectional analysis of 300 community-dwelling, functionally-independent older adults (mean (SD) age 67.4 (7.1) years; 69% female) was conducted using exploratory (EFA) and confirmatory factor analyses (CFA) to characterise the latent structure of biomarker-defined vitality. Factor scores were examined for associations with IC domains, composite IC and frailty using linear regression, compared with the Mini Nutritional Assessment-Short Form (MNA-SF). RESULTS: EFA supported a multidimensional structure with biomarkers clustering into neuromuscular, metabolic and inflammatory domains. CFA supported a correlated three-factor model for vitality; while a bifactor model showed superior global fit, general factor dominance was limited (ECV = 0.28; ωH = 0.26), with most variance at the domain level. Higher neuromuscular vitality was associated with greater composite IC (β = 1.39, 95% CI 0.25-2.54) and cognitive capacity (β = 1.74, 95% CI 0.52-2.95). A better metabolic vitality profile was associated with higher locomotor capacity (β = 1.74, 95% CI 0.58-2.91), while a more favourable inflammatory vitality profile was associated with higher locomotor capacity (β = 1.33, 95% CI 0.09-2.57) and reduced frailty (β = -0.11, 95% CI - 0.22 to -0.022). In contrast, MNA-SF scores were associated only with lower frailty (β = -0.09, 95% CI - 0.17 to -0.004), and not with IC. CONCLUSIONS: Vitality is better represented as a multidimensional, physiological construct than by nutrition-based measures alone. Distinct biomarker-derived vitality domains were associated with IC and frailty, supporting its role in characterising physiological determinants of healthy ageing. Longitudinal research is required to establish its prognostic value.

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Publication Details

Journal
The journal of nutrition health & aging
Published
2026-06-09
DOI
https://doi.org/10.1016/j.jnha.2026.100894
Primary Topic
Frailty in Older Adults
Type
article
Field-Weighted Citation Impact
0.00

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article

A multidimensional biomarker model of vitality and its associations with intrinsic capacity and frailty

C. N. Tan, W.S. Lim, J.P. Lim, J. Chew et al.
The journal of nutrition health & aging
Frailty in Older Adults
article

A multidimensional biomarker model of vitality and its associations with intrinsic capacity and frailty

C. N. Tan, W.S. Lim, J.P. Lim, J. Chew, C.L. Lim, J.Q. Chia, S.P. Chan, A. Yeo
article en

Abstract

BACKGROUND: The World Health Organisation has identified intrinsic capacity (IC) as a key determinant of healthy ageing. Within the IC framework, vitality reflects physiological reserve arising from neuromuscular, metabolic and inflammatory/stress-response systems. However, this multidomain physiological construct has not been empirically validated, and vitality is often operationalised using nutritional assessments alone. OBJECTIVES: We evaluated a biomarker-derived vitality construct and examined its associations with IC domains and frailty, compared to nutritional measures. METHODS: Cross-sectional analysis of 300 community-dwelling, functionally-independent older adults (mean (SD) age 67.4 (7.1) years; 69% female) was conducted using exploratory (EFA) and confirmatory factor analyses (CFA) to characterise the latent structure of biomarker-defined vitality. Factor scores were examined for associations with IC domains, composite IC and frailty using linear regression, compared with the Mini Nutritional Assessment-Short Form (MNA-SF). RESULTS: EFA supported a multidimensional structure with biomarkers clustering into neuromuscular, metabolic and inflammatory domains. CFA supported a correlated three-factor model for vitality; while a bifactor model showed superior global fit, general factor dominance was limited (ECV = 0.28; ωH = 0.26), with most variance at the domain level. Higher neuromuscular vitality was associated with greater composite IC (β = 1.39, 95% CI 0.25-2.54) and cognitive capacity (β = 1.74, 95% CI 0.52-2.95). A better metabolic vitality profile was associated with higher locomotor capacity (β = 1.74, 95% CI 0.58-2.91), while a more favourable inflammatory vitality profile was associated with higher locomotor capacity (β = 1.33, 95% CI 0.09-2.57) and reduced frailty (β = -0.11, 95% CI - 0.22 to -0.022). In contrast, MNA-SF scores were associated only with lower frailty (β = -0.09, 95% CI - 0.17 to -0.004), and not with IC. CONCLUSIONS: Vitality is better represented as a multidimensional, physiological construct than by nutrition-based measures alone. Distinct biomarker-derived vitality domains were associated with IC and frailty, supporting its role in characterising physiological determinants of healthy ageing. Longitudinal research is required to establish its prognostic value.

The journal of nutrition health & agingVol. 30(8)
Nanyang Technological University (SG), Tan Tock Seng Hospital (SG), VinUniversity (VN)
Lee Foundation
Zero hunger
Openalex Percentile: Top 9%
Frailty in Older Adults
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