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Accuracy of aggregate 2-and 3-component models of body composition relative to 4-component for the measurement of changes in fat mass during weight loss in overweight and obese subjects

Lookup NU author(s): Dr Jose Lara-Gallegos, Dr Mario Siervo

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Abstract

The 4-component (4-C) model is the reference method to measure fat mass (FM). Simpler 2-component (2-C) models are widely used to assess FM. We hypothesised that an aggregate 2-C model may improve accuracy of FM assessment during weight loss (WL). One hundred and six overweight and obese men and women were enrolled in different WL programs (fasting, very low energy diet, low energy diet). Body density, bone mineral content, and total body water were measured. FM was calculated using 2-C, 3-C, and 4-C models. Aggregate equations for 2-C, 3-C, and 4-C models were calculated, with the aggregate 4-C model assumed as the reference method. The aggregate approach postulates that the average of the individual estimates obtained from each model is more accurate than the best single measurement. The average WL was -7.5 kg. The agreement between 3-C and 4-C models for FM change was excellent (R-2 = 0.99). The aggregate 2-C equation was more accurate than individual 2-C estimates in measuring changes in FM. The aggregate model was characterised by a lower measurement error at baseline and post-WL. The relationship between the aggregate 3-C and 4-C component models was highly linear (R-2 = 0.99), whereas a lower linearity was found for the aggregate 2-C and 4-C model (R-2 = 0.72). The aggregate 2-C model is characterised by a greater accuracy than commonly applied 2-C equations for the measurement of FM during WL in overweight and obese men and women.


Publication metadata

Author(s): Lara J, Johnstone AM, Wells J, Jebb S, Siervo M

Publication type: Article

Publication status: Published

Journal: Applied Physiology, Nutrition, and Metabolism

Year: 2014

Volume: 39

Issue: 8

Pages: 871-879

Print publication date: 01/08/2014

Online publication date: 20/02/2014

Acceptance date: 12/02/2014

ISSN (print): 1715-5312

ISSN (electronic): 1715-5320

Publisher: NRC Research Press

URL: http://dx.doi.org/10.1139/apnm-2013-0424

DOI: 10.1139/apnm-2013-0424


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