Title

Upper extremity soft and rigid tissue mass prediction using segment anthropometric measures and DXA

Date of Award

2007

Degree Type

Thesis

Department

Kinesiology

Rights

CC BY-NC-ND 4.0

Abstract

Multiple linear stepwise regression was used to generate equations to predict bone mineral content (BMC), fat mass (FM), lean mass (LM), and wobbling mass (WM) of three segments of the upper extremities including the arm, forearm, and forearm + hand segments using simple anthropometrics. Full body scans using Dual Energy X-ray Absorptiometry (DXA) were used as the reference method. 100 (50 M, 50 F) young adults, ranging in age from 17 to 30 years, volunteered where data from 76 participants was used to generate the equations while data from the remaining 24 was used for equation validation. Prediction equations exhibited high adjusted R2 values (range from 0.854 to 0.968). Scatter plots of the actual versus predicted masses of the validation group revealed a close relationship (R2 range from 0.681 to 0.951). This indicates that accurate estimates of in-vivo tissue masses for upper extremity segments can be predicted by anthropometrics.