Comparison of field body composition techniques in elite female heptathletes

L. Houtkooper, J. Ricketts, S. Going, N. Ayan, T. Robertson

Research output: Contribution to journalReview articlepeer-review


Criterion methods of measuring body composition are often limited to a laboratory setting. An alternative to criterion methods are the more mobile field methods, which are simple techniques for measuring body composition. Cross-validation of prediction equations for specific athletic populations can be used to determine prediction accuracy for estimates of percent body fat (%BF). This study compares two field methods [skinfolds (SKF), bioelectrical impedance analysis (BIA)] to two criterion methods [dual energy x-ray absorptiometry (DXA) and a multi-component model (MULTI-Lohman, 1986)]. Prediction equations used for both field methods were developed for young athletic women. The subjects were 18 elite female heptathletes participating in a USA Track and Field Development Project. Standard protocols and tetrapolar placement for whole body BIA were used and the prediction equations include: A) Lohman, 1992, B) Lohman, active women 1992, and C) Valhalla, model 1990b. Standard procedures were used for skinfold measurement and the prediction equations include: A) Jackson & Pollock, 1985 (3 site), and B) Jackson & Pollock, 1985 (4 site). Correlation analysis between criterion methods and field methods were significant (p<0.001) for DXA vs SKF-A (r O 70) and SKF-B (r 0.72); MULTI vs SKF-A (r 0.78) and SKF-B (r 0.75), (p<0.000); and MULTI vs BIA-C (r 0.48), (p<0.04). These data suggest that the use of skinfold measurement for the estimation of %BF using prediction equations A and B will more accurately estimate %BF relative to the criterion methods DXA and MULTI within this population than estimates of %BF from BIA equations.

Original languageEnglish (US)
Pages (from-to)A1038
JournalFASEB Journal
Issue number5
StatePublished - Mar 20 1998

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Genetics


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