Prediction of Android and Gynoid Body Adiposity via a Three-dimensional Stereovision Body Imaging System and Dual-Energy X-ray Absorptiometry.
Current methods for measuring regional body fat are expensive and inconvenient compared to the relative cost-effectiveness and ease of use of a stereovision body imaging (SBI) system. The primary goal of this research is to develop prediction models for android and gynoid fat by body measurements assessed via SBI and dual-energy x-ray absorptiometry (DXA). Subsequently, mathematical equations for prediction of total and regional (trunk, leg) body adiposity were established via parameters measured by SBI and DXA.



A total of 121 participants were randomly assigned into primary and cross-validation groups. Body measurements were obtained via traditional anthropometrics, SBI, and DXA. Multiple regression analysis was conducted to develop mathematical equations by demographics and SBI assessed body measurements as independent variables and body adiposity (fat mass and percentage fat) as dependent variables. The validity of the prediction models was evaluated by a split sample method and Bland-Altman analysis.



The R(2) of the prediction equations for fat mass and percentage body fat were 93.2% and 76.4% for android and 91.4% and 66.5% for gynoid, respectively. The limits of agreement for the fat mass and percentage fat were -0.06 ± 0.87 kg and -0.11% ± 1.97% for android and -0.04 ± 1.58 kg and -0.19% ± 4.27% for gynoid. Prediction values for fat mass and percentage fat were 94.6% and 88.9% for total body, 93.9% and 71.0% for trunk, and 92.4% and 64.1% for leg, respectively.



The three-dimensional (3D) SBI produces reliable parameters that can predict android and gynoid as well as total and regional (trunk, leg) fat mass.
a Department of Nutritional Sciences, School of Human Ecology, The University of Texas at Austin , Austin , Texas.
Jane J
JJ
Lee
a Department of Nutritional Sciences, School of Human Ecology, The University of Texas at Austin , Austin , Texas.
Jeanne H
JH
Freeland-Graves
a Department of Nutritional Sciences, School of Human Ecology, The University of Texas at Austin , Austin , Texas.
M Reese
MR
Pepper
b Department of Kinesiology and Healthy Education , Austin , Texas.
Philip R
PR
Stanforth
c School of Human Ecology, The University of Texas at Austin , Austin , Texas.
Bugao
B
Xu
D015502:Absorptiometry, Photon / Q000379:methods*; D000273:Adipose Tissue; D050154:Adiposity; D000328:Adult; D000368:Aged; D001823:Body Composition; D015992:Body Mass Index; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016014:Linear Models; D008297:Male; D008777:Methyltestosterone / Q000378:metabolism*; D008875:Middle Aged; D055815:Young Adult
D008777:Methyltestosterone
android fat; body composition; gynoid fat; obesity; prediction equations; stereovision body imaging