Assessing skeletal muscle mass and lean body mass: an analysis of the agreement among dual X-ray absorptiometry, anthropometry, and bioelectrical impedance - Baglietto, Nicolás; Vaquero-Cristóbal, Raquel; Albaladejo-Saura, Mario; Mecherques-Carini, Malek; Esparza-Ros, Francisco (Frontiers in Nutrition, 2024)
Introduction: Methods of body composition estimation such as dual-energy X-ray absorptiometry (DXA), anthropometry, and bioimpedance (BIA) are used for the estimation of skeletal muscle mass (SMM) and lean body mass (LBM). No previous studies have examined whether these methods generate comparable results, or whether they are valid by using DXA as the reference. The aims of the present investigation were: a) to assess the differences between DXA, anthropometry, and BIA in the estimation of SMM and LBM, taking into consideration the impact of sex and hydration status; and b) to examine the agreement of anthropometry and BIA as compared to DXA for the estimation of SMM and LBM. Methods: A descriptive cross-sectional design was followed with 262 healthy young adults (159 males and 103 females). LBM and SMM were assessed by anthropometry with the formulas from Lee et al. and Kulkarni et al. for LBM; and Kerr (opt a), Kerr (opt b), Lee et al., Poortmans, Matiegka, Martin et al., Drinkwater and Ross, and Heymsfield et al. for SMM; by BIA with the formula reported by the TANITA MC-780-MA software for LBM and SMM; and DXA with the formula reported by the Hologic Horizon software for LBM, and the conversion by Kim et al. for SMM. Results: Significant differences were found for both SMM and LBM in kg, and percentages between most methods and formulas for the overall sample (p<0.001-0.003) and divided by sex (p<0.001-0.035). Hydration status did not have a significant effect on the differences between methods and formulas (p=0.058-0.870). Lin’s coefficient revealed limited agreement among the majority of formulas and methods (CCC= 0.007-0.880). The Bland-Altman analysis showed significant differences in most methods and formulas, both in the overall sample and divided by sex, when using SMM and LBM with DXA as the reference (p<0.001-0.030). Conclusion: There is a lack of agreement between methods and formulas for assessing SMM and LBM. Sex was found to be a significant factor in this analysis. Furthermore, significant differences were observed between most formulas and methods as compared to DXA, except for the equations to estimate SMM with anthropometry by Poortmans.