Segmental fat-free mass and lean soft mass: a comparative study with dual X-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA) and anthropometry and development of anthropometric prediction models.

Abstract

Background: Although dual X-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA), and anthropometry (ANT) are commonly used to evaluate body composition, evidence on their agreement at the segmental level remains limited. This study aimed to compare intra-subject differences in DXA, BIA, and ANT for estimating segmental weight (SW), fat-free mass (FFM), and lean soft mass (LSM) and to examines sex-related influences, and to develop anthropometric prediction equations using DXA as the reference.

Methods: A cross-sectional study was conducted on 258 young adults (157 males, 101 females). Participants were assessed using DXA, BIA, and ANT. SW, FFM, and LSM were estimated in kilograms and percentages for the upper limbs, trunk, and lower limbs using DXA and BIA. FFM was also estimated using anthropometry (ANT).

Results: Significant intra-subject differences were observed between methods across most body segments (p ≤ 0.049), except for SW in the right upper limb (p = 0.328) and LSM in the trunk (p = 0.186) for females. Sex covariable showed a significant influence on the differences found in these comparisons (p ≤ 0.032). Females exhibited lower values of SW, FFM, and LSM in the upper limbs, while males showed higher values of FFM and LSM specifically in the trunk and lower limbs. Bland - Altman analysis revealed a general lack of agreement between DXA and both BIA and ANT, except for BIA when estimating SW in the right upper limb in females (p = 0.167). The new anthropometric equations demonstrated high predictive accuracy (R² > 0.750), with slightly lower values in the upper limbs of females for FFM and LSM (R²  = 0.688-0.723). Key predictors included body mass, corrected girths, and segmental lengths.

Conclusions: DXA, BIA, and ANT showed significant differences in estimating SW, FFM, and LSM, highlighting their lack of interchangeability. Sex was a significant factor, indicating its importance in body composition estimation. The new anthropometric equations showed good comparability with DXA, although their predictive performance was slightly lower in the upper limbs of females for FFM and LSM.