Exercise Physiology Laboratory, Department of Kinesiology, The University of Alabama, Tuscaloosa, AL, USA.
Program in Physical Therapy, School of Medicine, Washington University, St. Louis, MO, USA.
Eur J Clin Nutr. 2022 Jan;76(1):111-118. doi: 10.1038/s41430-021-00899-1. Epub 2021 Mar 26.
BACKGROUND/OBJECTIVES: The purpose of this study was: (1) to compare body volume (BV) estimated from a 2-dimensional (2D) image analysis program (BV), and a dual-energy x-ray absorptiometry (DXA) equation (BV) to an underwater weighing (UWW) criterion (BV); (2) to compare relative adiposity (%Fat) derived from a 3-compartment (3C) model using BV (%Fat), and a 4-compartment (4C) model using BV (%Fat) to a 4C criterion model using BV (%Fat).
SUBJECT/METHODS: Forty-eight participants were included (60% male, 22.9 ± 5.0 years, 24.2 ± 2.6 kg/m). BV 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.
Near-perfect correlation (r = 0.998, p < 0.001) and no mean differences (p = 0.267) were observed between BV (69.6 ± 11.5 L) and BV (69.5 ± 11.4 L). No mean differences were observed between %Fat and the %Fat criterion (p = 0.988). Small mean differences were observed between %Fat and %Fat (ES = 0.2, p < 0.001). %Fat exhibited smaller SEE and TE, and tighter limits of agreement than %Fat.
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.
背景/目的：本研究的目的是：（1）比较二维（2D）图像分析程序（BV）和双能 X 射线吸收法（DXA）方程（BV）估计的体体积（BV）与水下称重（UWW）标准（BV）；（2）比较使用 BV 的 3 compartment（3C）模型计算的相对肥胖度（%Fat）和使用 BV 的 4 compartment（4C）模型计算的相对肥胖度（%Fat）与使用 BV 的 4C 标准模型（%Fat）。
纳入 48 名参与者（60%男性，22.9±5.0 岁，24.2±2.6kg/m）。使用从后/后视图拍摄的每个参与者的单个数字图像来获取 BV。根据 Smith-Ryan 等人的方法计算 DXA 衍生的 BV。生物阻抗谱和 DXA 分别用于测量 3C 和 4C 模型中的总体体水和骨矿物质含量。标准化均数效应量（ES）评估了模型之间差异的大小，0.2、0.5 和 0.8 分别表示差异小、中大和大。数据表示为均值±标准差。
BV（69.6±11.5L）与 BV（69.5±11.4L）之间存在近乎完美的相关性（r=0.998，p<0.001），且无均值差异（p=0.267）。%Fat 与%Fat 标准之间无均值差异（p=0.988）。%Fat 与%Fat 之间存在较小的均值差异（ES=0.2，p<0.001）。%Fat 表现出较小的 SEE 和 TE，以及更紧的一致性界限。
2D 图像分析程序在一般健康的年轻成年人中，为 BV 以及随后的 3C 模型中的%Fat 提供了准确且非侵入性的估计。
