Author Identifier
Marc Sim: https://orcid.org/0000-0001-5166-0605
Document Type
Journal Article
Publication Title
Advances in Nutrition
Volume
16
Issue
2
Publisher
Elsevier
School
Nutrition and Health Innovation Research Institute / School of Medical and Health Sciences
Funders
Curtin University / Dementia Centre of Excellence / Curtin enAble Institute Seed Funding / Italian Ministry of University and Research (PE00000003) / Canada Research Chairs Program / Future Health Research and Innovation Fund, Department of Health, Western Australia
Abstract
The adaptive and independent interrelationships between different body composition components have been identified as crucial determinants of disease risk. On the basis of this concept, the load-capacity model of body composition, which utilizes measurements obtained through nonanthropometric techniques such as dual-energy X-ray absorptiometry, was proposed. This model is typically operationalized as the ratio of metabolic load (adipose mass) to metabolic capacity (lean mass). In recent years, a series of load-capacity indices (LCIs) have been utilized to identify abnormal body composition phenotypes such as sarcopenic obesity (SO) and to predict the risk of metabolic, cardiovascular, and cognitive disorders. In this review, we comprehensively review the characteristics of different LCIs used in previous studies, with a specific focus on their applications, especially in identifying SO and predicting cardiometabolic outcomes. A systematic literature search was performed using PubMed, MEDLINE, PsycINFO, Embase, and the Cochrane Library. Two meta-analyses were conducted to 1) estimate the overall prevalence of SO mapped by LCIs, and 2) assess the association of LCIs with cardiometabolic outcomes. A total of 48 studies (all observational) were included, comprising 22 different LCIs. Ten studies were included in the meta-analysis of SO prevalence, yielding a pooled prevalence of 14.5% [95% confidence interval (CI): 9.4%, 21.6%]. Seventeen studies were included in the meta-analysis of the association between LCIs and adverse cardiometabolic outcomes, which showed a significant association between higher LCI values and increased risk (odds ratio = 2.22; 95% CI: 1.81, 2.72) of cardiometabolic diseases (e.g. diabetes and metabolic syndrome). These findings suggest that the load-capacity model of body composition could be particularly useful in the identification of SO cases and prediction of cardiometabolic risk. Future longitudinal studies are needed to validate the association of LCIs with chronic cardiometabolic and neurodegenerative diseases. This systematic review and meta-analysis has been registered with PROSPERO (CRD42024457750).
DOI
10.1016/j.advnut.2024.100364
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Guan, Z., Minnetti, M., Heymsfield, S. B., Poggiogalle, E., Prado, C. M., Sim, M., ... & Siervo, M. (2025). Beyond traditional body composition metrics: Load-capacity indices emerge as predictors of cardiometabolic outcomes–A systematic review and meta-analysis. Advances in Nutrition, 16(2). https://doi.org/10.1016/j.advnut.2024.100364