Accuracy of a Mobile 2D Imaging System for Body Volume and Subsequent Composition Estimates in a Three-Compartment Model

Abstract

Purpose: The purpose of the study was to compare a single two-dimensional image processing system (IMAGE) to underwater weighing (UWW) for measuring body volume (BV) and subsequently estimating body fat percentage (%Fat), fat mass (FM), and fat-free mass (FFM) via a 3-compartment (3C) model. Methods: A sample of participants age 18-39 yr was recruited for this study (n = 67, 47.8% female). BV was measured with UWW and predicted via the IMAGE software. The BV estimates from UWW (3C UWW ) and IMAGE (3C IMAGE ) were separately combined with constant total body water and body mass values for 3C model calculation of %Fat, FM, and FFM. Results: BV obtained from the IMAGE was 67.76 ± 12.19 and 67.72 ± 12.04 L from UWW, which was not significantly different (P = 0.578) and very largely correlated (r = 0.99, P < 0.001). When converted to %Fat (3C UWW = 21.01% ± 7.30%, 3C IMAGE = 21.08% ± 7.04%, P = 0.775), FM (3C UWW = 14.68 ± 5.15 kg, 3C IMAGE = 14.78 ± 5.08 kg, P = 0.578), and FFM (3C UWW = 57.00 ± 13.20 kg, 3C IMAGE = 56.90 ± 12.84 kg, P = 0.578) with the 3C model, no significant mean differences and very large correlations (r values ranged from 0.96 to 0.99) were observed. In addition, the standard error of estimate, total error, and 95% limits of agreement for all three metrics were small and considered acceptable. Conclusions: An IMAGE system provides valid estimates of BV that accurately estimates body composition in a 3C model.

Utilizing a Novel 2D Image Processing System for Relating Body Composition Metrics to Performance in Collegiate Female Rowers

“…The research regarding the validity of this new approach has begun to emerge. For instance, Fedewa et al recently demonstrated that body volume estimates from the same 2D method of the current study displayed an r of 0.99 when compared to the underwater weighing technique in a sample of healthy adults [ 10 ]. In addition, when the body volume estimates were combined with total body water measures from bioimpedance spectroscopy for a “field-based” three-compartment model, there were very large correlations (r = 0.96 to 0.99) with the laboratory method for FM and FFM [ 10 ].…”

“…For instance, Fedewa et al recently demonstrated that body volume estimates from the same 2D method of the current study displayed an r of 0.99 when compared to the underwater weighing technique in a sample of healthy adults [ 10 ]. In addition, when the body volume estimates were combined with total body water measures from bioimpedance spectroscopy for a “field-based” three-compartment model, there were very large correlations (r = 0.96 to 0.99) with the laboratory method for FM and FFM [ 10 ]. Moreover, Farina et al [ 26 ] showed no significant differences, strong relationships (R 2 = 0.91 to 0.95), and a small standard error of estimate values (±2.71 to 2.83 kg) when comparing FM estimates from a different 2D body composition program to dual-energy X-ray absorptiometry.…”

“…Recently, a method of measuring body composition from a single 2-dimensional (2D) image was proposed for use within field settings [ 10 ]. The proprietary automated process predicts body volume by measuring the widths and lengths of various anatomical landmarks within a picture.…”

“…The system is available commerically as a smartphone application referred to as “made health and fitness”. Previous investigation compared this novel method to underwater weighing in a large sample from the general, healthy population [ 10 ]. The findings demonstrated a 0.99 correlation coefficient and no significant mean differences in estimates of body volume [ 10 ], in which the smartphone application converts to estimates of FM and FFM.…”

“…Previous investigation compared this novel method to underwater weighing in a large sample from the general, healthy population [ 10 ]. The findings demonstrated a 0.99 correlation coefficient and no significant mean differences in estimates of body volume [ 10 ], in which the smartphone application converts to estimates of FM and FFM. Because of the simplicity of assessment, the new method has potential to be commonly used among practitioners for assessing body composition in athletes.…”