Body composition in dancers: the bioelectrical impedance method

Med Sci Sports Exerc. 2000 Jan;32(1):228-34. doi: 10.1097/00005768-200001000-00034.


Purpose: The aim of this study was to generate and validate a prediction equation for estimating the body composition in dancers using the bioelectrical impedance analysis (BIA) as a method of assessment.

Methods: The fat-free mass (FFM) of 42 young female professional dance students was estimated by four different methods: dual x-ray absorptiometry (DXA), BIA, simple anthropometry, and skinfold thickness; DXA was used as a criterion method.

Results: The dancers' FFM was 42.6 kg (SD: 3.3) and, on the average, body fat represented the 19.4% (SD: 4.3) of their body weight. Two dancer-specific BIA equations for the prediction of FFM (E(BIA)) were developed by multiple regression analysis using weight, height, resistance index, and triceps as predictor variables (E(BIA) and E(BIA-TRICEPS)). The validity of these equations as well as of those previously reported was assessed in two randomly selected subgroups of the initial study group, as described by the Bland-Altman analysis. The bias and the limits of agreement of the equations developed in the present study were lower than those resulting from the application of the previously used equations of Segal et al. and Hergenroeder et al. It was also found that, when validated against DXA, skinfolds measurements did not accurately predict body fatness in this group of young females.

Conclusion: The new equations allow for an accurate routine assessment of body composition in young female dancers by using the method of BIA. Further studies are needed for the cross-validation of the equations in various groups of dancers.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Absorptiometry, Photon
  • Adipose Tissue
  • Adolescent
  • Adult
  • Algorithms
  • Anthropometry
  • Bias
  • Body Composition / physiology*
  • Body Height
  • Body Weight
  • Dancing / physiology*
  • Electric Impedance*
  • Female
  • Forecasting
  • Humans
  • Muscle, Skeletal / anatomy & histology
  • Regression Analysis
  • Reproducibility of Results
  • Skinfold Thickness