A Field-based Three-Compartment Model Derived from Ultrasonography and Bioimpedance for Estimating Body Composition Changes

Abstract

Purpose The purpose of this study was to assess the agreement between a field-based three-compartment (3CFIELD) model and a laboratory-based three-compartment (3CLAB) model for tracking body composition changes over time. Methods Resistance-trained males completed a supervised nutrition and resistance training intervention. Before and after the intervention, assessments were performed via air displacement plethysmography (ADP), bioimpedance spectroscopy (BIS), portable ultrasonography (US), and bioelectrical impedance analysis (BIA). ADP body density and BIS body water were used within the reference 3CLAB model, whereas US-derived body density and BIA body water were used within the 3CFIELD model. Two-compartment model body composition estimates provided by US and BIA were also examined. Changes in fat-free mass and fat mass were analyzed using repeated-measures ANOVA, equivalence testing, Bland–Altman analysis, linear regression, and related validity analyses. Results Significant increases in fat-free mass (3CLAB, 4.0 ± 4.5 kg; 3CFIELD, 3.9 ± 4.2 kg; US, 3.2 ± 4.3 kg; BIA, 3.9 ± 4.2 kg) and fat mass (3CLAB, 1.3 ± 2.2 kg; 3CFIELD, 1.4 ± 2.2 kg; US, 2.1 ± 2.6 kg; BIA, 1.4 ± 2.9 kg) were detected by all methods. However, only the 3CFIELD model demonstrated equivalence with the 3CLAB model. In addition, the 3CFIELD model exhibited superior performance to US and BIA individually, as indicated by the total error (3CFIELD, 1.0 kg; US, 1.8 kg; BIA, 1.6 kg), 95% limits of agreement (3CFIELD, ±2.1 kg; US, ±3.3 kg; BIA, ±3.1 kg), correlation coefficients (3CFIELD, 0.79–0.82; US, 0.49–0.55; BIA, 0.61–0.72), and additional metrics. Conclusions The present study demonstrated the potential usefulness of a 3CFIELD model incorporating US and BIA data for tracking body composition changes over time, as well as its superiority to US or BIA individually. As such, this accessible multicompartment model may be suitable for implementation in field or limited-resource settings.

Tracking changes in body composition: comparison of methods and influence of pre-assessment standardisation

“…All participants completed 6 weeks of 3 d/week supervised RT while consuming a hyperenergetic diet as previously described (7)(8)(9) . Briefly, the RT programme was designed by a Certified Strength and Conditioning Specialist and included a lower body session, upper body session and full body session weekly.…”

Cross‐sectional and longitudinal associations between subcutaneous adipose tissue thickness and dual‐energy X‐ray absorptiometry fat mass

“…This comparison bridges two levels of body composition assessment, as DXA FM is considered a molecular‐level entity (i.e. an estimation of the molecular fat content of the body) while subcutaneous adipose tissue thickness more closely resembles an organ/tissue‐level assessment (Tinsley, Moore, et al, 2020; Tinsley, Rodriguez, et al, 2020; Wang et al, 1992). Previously, researchers have entered the sum of skinfolds into body density predictions, most frequently those developed by Jackson and Pollock (1978), with the body density value subsequently entered into a separate equation, such as the Siri equation (Siri, 1961) to yield a 2C FM estimate.…”

“…A trained researcher manually adjusted region of interest lines within the enCORE software to designate body segments (i.e. arms, trunk and legs; Tinsley, Moore, et al, 2020; Tinsley, Rodriguez, et al, 2020). In our laboratory, these procedures have produced intraclass correlation coefficient (ICC) values from 0.974 to 0.996 and root‐mean‐square coefficient of variation (RMS‐CV) from 2.6 to 5.4% for total and segmental FM estimates.…”

“…The molecular level is employed when the sum of skinfolds estimated by US is utilized in a body density equation [e.g. Jackson and Pollock's equation (Jackson & Pollock, 1978)], with the subsequent body density value inserted into a two‐ or three‐component model equation to ultimately yield estimates of FM and FFM (Tinsley, Moore, et al, 2020; Tinsley, Rodriguez, et al, 2020). In contrast, US‐derived raw skinfold thicknesses can be directly interpreted as an estimate of subcutaneous adipose tissue thickness, which is more closely related to regional tissue‐level assessments.…”

Oversimplification of the Relationship between Ultrasound and Skinfold Measurements of Subcutaneous Fat Thickness

“…In the March 2021 issue of Medicine & Science in Sports & Exercise , two separate studies (1,2) from different research laboratories both used ultrasound to estimate body fat percentage (%BF). Both Chandler et al (1) and Tinsley et al (2) reported using a modification of the Jackson–Pollock (3) seven-site skinfold formula to convert their ultrasound fat thicknesses into estimates of body density and subsequently converted body density to %BF with the Siri (4) formula. Close inspection of their methods reveals that the only “modification” to the Jackson–Pollock equation was a doubling of the ultrasound fat thicknesses.…”