Body fat assessment techniques: is there a place for 3D body scanners?

Abstract

Body composition is an important domain for health, as high body fat percentages (BF%) are associated with mortality. BF% also is an important metric for athletic / sport performance and rehabilitation progress. Common BF% estimation tools include skinfold equations like Jackson-Pollock (JP7) or DXA criterion (DC), body volume measures from BODPOD or hydrostatic weighing, and dual-energy x-ray absorptiometry (DXA), which is often considered a new reference criterion. The Size Stream Body Scanner was developed by the apparel industry and generates measures such as circumferences and diameters that could be used to assess BF% in a similar manner to BODPOD. This cross-sectional study enrolled 134 adults aged between 18-62 years to develop a novel BF% estimation equation for the Size Stream Body using LASSO regression and compared it to the BF% estimates of three two component (2C) models and one three component (3C) model. The 2C models were skinfolds using the JP7 and DC equations and the BODPOD. The 3C model used as the reference standard was DXA. Agreement to DXA BF% estimates was assessed using three methods. First, a one-way ANOVA with Bonferroni post-hocs. Second, intraclass correlation coefficients (ICC) with a two-way mixed model and absolute agreement required were calculated. Lastly, Bland-Altman analyses were used to compare each assessment to DXA BF% estimates. The JP7 underestimated BF% compared to all other assessments and had the lowest ICC, followed by BODPOD (both ICCs ≤0.845). DC and Size Stream had excellent ICCs with values ≤0.944. Lastly, the female DC equation and both Size Stream equations passed the Bland Altman test for agreement with DXA BF%. These data demonstrate Size Stream may be a suitable new body composition assessment tool that is more accessible to athletes, coaches, and sports medicine professionals compared to DXA.