Clinical nutrition ESPEN · 2026
Development and Validation of Ultrasound-based Prediction Equations for Fat and Lean Mass in Adults With Obesity.
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Sizoo Dionne, Beumeler Lise F E, de Heide Loek J M, van Zutphen Tim, Tan-Phan Ha, Emous Marloes, van Beek André P
Аннотация
BACKGROUND & AIMS: Obesity treatment is measured by total weight loss or BMI loss, neither of which accurately reflects fat mass. Ultrasound (US) offers a non-invasive, portable alternative for measuring subcutaneous adipose tissue (SAT) thickness. The aim of this study was to (1) assess the reliability of US-derived SAT measurements, and (2) develop and validate prediction equations for fat mass (FM) and lean mass (LM) based on SAT thickness at multiple sites.
METHODS: Two separate observational studies were performed. To investigate reliability, the intra- and interrater reliability of the SAT measurements was assessed. For the development and validation of prediction equations, linear regression was used to generate a seven- and three-point model for the estimation of both lean and fat mass. Validity was assessed in the validation cohort using Bland-Altman plots, intraclass correlation coefficients (ICC), and linear regression to detect proportional bias.
RESULTS: US measurements showed high intra- and good interrater reliability (resp. ICC = 0.948; ICC = 0.859). All models demonstrated a high predictive accuracy for DXA-based body composition (R2>0.71 for fat mass assessment, R2>0.90 for lean mass assessment). There was a strong agreement with DXA across all models (ICC > 0.846).
CONCLUSION: Ultrasonography-based measurement of SAT provides a cheap, easy-to-use, and reliable tool to assess fat and lean mass in a population with class II/III obesity.
METHODS: Two separate observational studies were performed. To investigate reliability, the intra- and interrater reliability of the SAT measurements was assessed. For the development and validation of prediction equations, linear regression was used to generate a seven- and three-point model for the estimation of both lean and fat mass. Validity was assessed in the validation cohort using Bland-Altman plots, intraclass correlation coefficients (ICC), and linear regression to detect proportional bias.
RESULTS: US measurements showed high intra- and good interrater reliability (resp. ICC = 0.948; ICC = 0.859). All models demonstrated a high predictive accuracy for DXA-based body composition (R2>0.71 for fat mass assessment, R2>0.90 for lean mass assessment). There was a strong agreement with DXA across all models (ICC > 0.846).
CONCLUSION: Ultrasonography-based measurement of SAT provides a cheap, easy-to-use, and reliable tool to assess fat and lean mass in a population with class II/III obesity.