Department of Human Nutrition and Hospitality Management

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Browsing Department of Human Nutrition and Hospitality Management by Subject "ABSORPTIOMETRY"

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    Validity of a 3-compartment body composition model using body volume derived from a novel 2-dimensional image analysis program
    (Springer Nature, 2022) Sullivan, Katherine; Hornikel, Bjoern; Holmes, Clifton J.; Esco, Michael R.; Fedewa, Michael V.; University of Alabama Tuscaloosa; Washington University (WUSTL)
    Background/Objectives The purpose of this study was: (1) to compare body volume (BV) estimated from a 2-dimensional (2D) image analysis program (BVIMAGE), and a dual-energy x-ray absorptiometry (DXA) equation (BVDXA-Smith-Ryan) to an underwater weighing (UWW) criterion (BVUWW); (2) to compare relative adiposity (%Fat) derived from a 3-compartment (3C) model using BVIMAGE (%Fat(3C-IMAGE)), and a 4-compartment (4C) model using BVDXA-Smith-Ryan (%Fat(4C-DXA-Smith-Ryan)) to a 4C criterion model using BVUWW (%Fat(4C-UWW)). Subject/Methods Forty-eight participants were included (60% male, 22.9 +/- 5.0 years, 24.2 +/- 2.6 kg/m(2)). BVIMAGE was derived using a single digital image of each participant taken from the rear/posterior view. DXA-derived BV was calculated according to Smith-Ryan et al. Bioimpedance spectroscopy and DXA were used to measure total body water and bone mineral content, respectively, in the 3C and 4C models. A standardized mean effect size (ES) assessed the magnitude of differences between models with values of 0.2, 0.5, and 0.8 for small, moderate, and large differences, respectively. Data are presented as mean +/- standard deviation. Results Near-perfect correlation (r = 0.998, p < 0.001) and no mean differences (p = 0.267) were observed between BVIMAGE (69.6 +/- 11.5 L) and BVUWW (69.5 +/- 11.4 L). No mean differences were observed between %Fat(4C-DXA-Smith-Ryan) and the %Fat(4C-UWW) criterion (p = 0.988). Small mean differences were observed between %Fat(3C-IMAGE) and %Fat(4C-UWW) (ES = 0.2, p < 0.001). %Fat(3C-IMAGE) exhibited smaller SEE and TE, and tighter limits of agreement than %Fat(4C-DXA-Smith-Ryan). Conclusions The 2D image analysis program provided an accurate and non-invasive estimate of BV, and subsequently %Fat within a 3C model in generally healthy, young adults.