Prediction of body cell mass, fat-free mass, and total body water with bioelectrical impedance analysis: effects of race, sex, and disease

Am J Clin Nutr. 1996 Sep;64(3 Suppl):489S-497S. doi: 10.1093/ajcn/64.3.489S.


The inability to precisely estimate body composition with simple, inexpensive, and easily applied techniques is an impediment to clinical investigations in nutrition. In this study, predictive equations for body cell mass (BCM), fat-free mass (FFM), and total body water (TBW) were derived from direct measurements through use of single-frequency bioelectrical impedance analysis (BIA) in 332 subjects, including white, black, and Hispanic men and women, who were both healthy control subjects and patients infected with the human immunodeficiency virus (HIV). Preliminary studies showed more accurate predictions of BCM when parallel-transformed values of reactance were used rather than the values reported by the bioelectrical impedance analyzer. Modeling equations derived after logarithmic transformation of height, reactance, and impedance were more accurate predictors than equations using height2/resistance, and the use of sex-specific equations further improved accuracy. The effect of adding weight to the modeling equation was less important than the BIA measurements. The resulting equations were validated internally, and race and disease (HIV infection) were shown not to affect the predictions. The equation for FFM was validated externally against results derived from hydrodensitometry in 440 healthy individuals; the SEE was < 5%. These results indicate that body composition can be estimated with simple and easily applied techniques, and that the estimates are sufficiently precise for use in clinical investigation and practice.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Body Composition*
  • Body Water / metabolism*
  • Continental Population Groups*
  • Electric Impedance*
  • Female
  • Forecasting
  • HIV Infections / ethnology
  • HIV Infections / pathology
  • HIV Infections / physiopathology*
  • Humans
  • Male
  • Models, Biological
  • Sex Characteristics*