3DBODY.TECH 2018 - Paper 18.195

R. Varte et al., "Prediction of Fat Mass and Validation Using 3D-Whole Body Scanner in Healthy Indian Males", in Proc. of 3DBODY.TECH 2018 - 9th Int. Conf. and Exh. on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 16-17 Oct. 2018, pp. 195-200, doi:10.15221/18.195.


Prediction of Fat Mass and Validation Using 3D-Whole Body Scanner in Healthy Indian Males


Robert VARTE, Shweta RAWAT, Inderjeet SINGH, Shilpa CHOUDHARY, Suchitra SINGH, Deepika KAKKAR, Yashmita CHAUDHARY, Usha PANJWANI, Bhuvnesh KUMAR

Defence Inst. of Physiology and Allied Sciences (DIPAS), Defence Research and Development Organisation (DRDO), Delhi, India


Background: BMI generally overestimates adiposity (i.e. body fat tissue) and underestimates excess body fat on those with less lean body mass. Aim: We wanted to assess the hypothesis that Fat Mass (FM) measured by bio impedance analysis (BIA) is comparable to the predicted Body Fat Mass (BFM) using 3D scanned anthropometric dimensions. Methods: The present paper investigates whether anthropometric measurements using 3D whole body scanner can provide clinically reliable prediction equation to assess adiposity. 3D whole body scanner provides a fast and precise alternative where the scanner gives upto 140 measurements within a few seconds. Intra-and inter-individual error margins in traditional anthropometric measurements frequently arises for large sample studies, besides, manually taking measurements are time-consuming and challenging to perform within acceptable limits. Six hundred and eight (608) healthy adults were scanned using a 3D whole body scanner and their body composition was measured using the Tanita Bipodal bioelectrical impedance analysis (BIA). 486 formed the development group (for the prediction equation) and 20% of the total (i.e. 122 formed the validation group) based on alphabetical order of participant's name. Linear regressions were performed to predict an equation wherein the body circumferential measurements like Waist Girth, Hip Girth and Chest Girth were predictors and Fat Mass was the dependent variable.
Results: Predictive body composition equation based on volumetric body circumference (girth) proposed for healthy Indian males is FM = 0.420 (Waist Girth) + 0.241 (Chest Girth) + 0.051 (Hip Girth) - 51.817. The predicted fat mass value was used for the validated population and we did not see much of a difference between the predicted and measured fat mass. The mean age among the 608 volunteers was 32.54 +- 6.3 years, weight was 71.26 kg +-7.8 kg and BMI was 24.1 +- 2.57 kg/mt2. Average difference between body fat measured by BIA - predicted body fat mass was 0.13 kg, median 0.50 kg, IQR: 0.80 to 0.20 kg, adjusted R2 0.74.
Conclusions: 3D whole body scanner technology offer defined and accurate automated anthropometric dimensions and measurements of body shape. Further studies are warranted to reveal important relationships between body shape, body composition and metabolic health across sex, age, BMI and ethnicity groups.


Full paper: 18195varte.pdf
Proceedings: 3DBODY.TECH 2018, 16-17 Oct. 2018, Lugano, Switzerland
Pages: 195-200
DOI: 10.15221/18.195

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