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 (3CUWW) and IMAGE (3CIMAGE) 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 (3CUWW = 21.01% ± 7.30%, 3CIMAGE = 21.08% ± 7.04%, P = 0.775), FM (3CUWW = 14.68 ± 5.15 kg, 3CIMAGE = 14.78 ± 5.08 kg, P = 0.578), and FFM (3CUWW = 57.00 ± 13.20 kg, 3CIMAGE = 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.
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 (3CUWW) and IMAGE (3CIMAGE) 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 (3CUWW = 21.01% ± 7.30%, 3CIMAGE = 21.08% ± 7.04%, P = 0.775), FM (3CUWW = 14.68 ± 5.15 kg, 3CIMAGE = 14.78 ± 5.08 kg, P = 0.578), and FFM (3CUWW = 57.00 ± 13.20 kg, 3CIMAGE = 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.
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