Background/objectives: Previous research has compared 2- and 3-compartment (2C and 3C, respectively) models against criterion 4-compartment (4C) models while utilizing the same body density (Db) method for all measures. This design induces an inherent bias and obscures the added benefit of a 3C model over the simpler 2-compartment (2C) models.
Purpose: The purpose of this study was to determine the effect of total body water estimates via single-frequency (SF-BIA) and multi-frequency (MF-BIA) bioimpedance analysis on body fat estimates derived from air displacement plethysmography (ADP)-derived 3C models.
Subjects/methods: A sample of 95 females and 82 males (n = 177) participated in this study. Underwater weighing, dual energy X-ray absorptiometry, and bioimpedance spectroscopy were used to calculate percent fat (%Fat) via a criterion 4C model (4CCRITERION). %Fat was predicted via 3CMFBIA (ADP and MF-BIA), 3CSFBIA (ADP and SF-BIA), and a stand-alone 2-compartment (2C) model, based upon ADP, when using Siri and Brozek body density conversion formulas (2CSIRI and 2CBROZEK. respectively).
Results: The standard error of estimate (SEE) was lowest for 3CSFBIA when evaluated in females and males (2.72% and 2.31%, respectively) and highest for 2CSIRI (3.98% and 3.84%, respectively). Similarly, the total error (TE) for females and males was lowest for 3CSFBIA (3.21% and 2.67%, respectively) and highest for 2CSIRI (4.58% and 4.48%, respectively) and 2CBROZEK (4.65% and 4.33%, respectively).
Conclusions: Results suggest that SF-BIA and MF-BIA can improve the estimation of %Fat, beyond simpler 2C models, when integrated with ADP in a more advanced 3C model. Furthermore, the present study revealed that 3CSFBIA was the best overall prediction model based upon TE values. The current study results support the integration of ADP and bioimpedance technology as part of a 3C model for the improvement of %Fat estimates over simpler 2C models.
© 2021. The Author(s), under exclusive licence to Springer Nature Limited.