Digital three-dimensional anthropometry detection of exercise-induced fat mass reduction in obese women

Purpose This work aimed at investigating the ability of a new automatic tool estimating geometrical parameters from photonic 3D scans of human subjects to detect and predict changes in Dual-energy X-ray absorptiometry (DXA) measured absolute and relative (%) total body (TB) and trunk fat mass (FM) in obese women after exercise training. Methods Twenty-five otherwise healthy obese females (age range, 20–60 years; body mass index range, 30–40 kg/m2) who participated in a whole-body vibration exercise programme had DXA and whole-body photonic 3D scanning before and after 10-week training. The 3D automatic digital anthropometric measurements (3D_AM) were: whole-body volume and surface area, maximal average trunk section radius, maximal anterior–posterior distance at the trunk, maximal trunk width and maximal trunk section area. The post–pre difference (Δ) was calculated for each variable and used for correlation (Pearson’s r) and linear regression analysis. Results Significant r values were found between Δ of all 3D_AM and Δ TB FM (r > 0.5 for all) as well as four out of six 3D_AM and Δ trunk FM. Percent TB FM and % trunk FM only correlated with trunk digital anthropometric automatic measurements. Linear regression analysis showed that several 3D_AM are able to predict to a significant extent changes in FM and % FM of obese women explaining 12.0–39.9 % of variance in the dependent variable (p 0.050 to <0.001). Conclusions The results showed that automatic digital anthropometry is a promising tool for detecting and predicting fat changes in obese subjects.