Display Settings:

Format

Send to:

Choose Destination
See comment in PubMed Commons below
J Biomech. 2009 Feb 9;42(3):389-94. doi: 10.1016/j.jbiomech.2008.11.021. Epub 2009 Jan 14.

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

Author information

  • 1Ergonomics Department, Schukra of North America, Lakeshore, Ontario, Canada N8N 4Y3.

Abstract

Regression equations for predicting bone mineral content (BMC), fat mass (FM), lean mass (LM), and wobbling mass (WM) of living people from simple anthropometric measures (segment lengths, circumferences, breadths, and skin folds) have been reported in the literature for the lower extremities, but are lacking for the upper extremities. Multiple linear stepwise regression was used to generate such equations for the arm, forearm, and forearm and hand segments of healthy university aged people (38 males, 38 females). Actual tissue masses were obtained from full body Dual-energy X-ray Absorptiometry (DXA) scans and were used to validate the developed equations with an independent sample of 24 participants (12 male, 12 female). Prediction equations exhibited very high adjusted R(2) values (range from 0.854 to 0.968), with more explained variance for LM and WM than for BMC and FM. Scatter plots of actual versus predicted tissue masses revealed a close relationship (R(2) range from 0.681 to 0.951). Relative errors between the predicted and actual tissue masses for the validation group ranged from -2.2% to 15.5%, and the root-mean-squared error (RMS(error)) ranged from 7.92 to 180.26g, for BMC of the forearm and LM of the arm, respectively. These results suggest that accurate estimates of in-vivo tissue masses for the upper extremities can be predicted from simple anthropometric measurements in young adults. Access to tissue masses such as these will enable the development of more accurate models for predicting dynamic in-vivo response of the body to activities involving impact.

PMID:
19147145
[PubMed - indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Icon for Elsevier Science
    Loading ...
    Write to the Help Desk