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Three-compartment model: critical evaluation based on neutron activation analysis.

Analiza M Silva1, Wei Shen, ZiMian Wang

  • 1Exercise and Health Laboratory, Faculty of Human Movement, Technical University of Lisbon, 1495-688 Lisbon, Portugal.

American Journal of Physiology. Endocrinology and Metabolism
|June 10, 2004
PubMed
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The classic three-compartment body composition model

Area of Science:

  • Human physiology
  • Body composition analysis
  • Biomedical engineering

Background:

  • The three-compartment (3C) body composition model is regaining interest for estimating body volume (BV) and total body water (TBW).
  • Existing methods like DEXA and IVNA have limitations for severely obese individuals.
  • The model's accuracy relies on assumptions about mineral to protein ratios (alpha) and residual mass density (D(RES)), potentially varying across demographics.

Purpose of the Study:

  • To derive new in vivo coefficients for the 3C body composition model.
  • To compare these new coefficients with Siri's classic model values.
  • To evaluate potential errors in body fat estimation, especially in obese populations.

Main Methods:

  • Utilized in vivo neutron activation (IVNA) and dual-energy X-ray absorptiometry (DEXA) in 323 healthy adults to measure body components.

Related Experiment Videos

  • Derived alpha and D(RES) values from measured components.
  • Evaluated model performance and potential errors in a second group of 264 adults using hydrodensitometry and (2)H(2)O dilution for BV and TBW measurements.

    • Main Results:

    • Overall alpha and D(RES) values were similar to Siri's proposed constants.
    • Significant variations in alpha and D(RES) were observed based on sex, race, weight, and age.
    • Application of Siri's model in morbidly obese subjects showed potential for significant errors in percent body fat estimation.

    Conclusions:

    • The classic 3C body composition model's assumptions may not hold true across diverse populations.
    • New coefficients derived in this study offer improved accuracy for specific demographic groups.
    • This research provides critical insights into the limitations of Siri's model and offers updated formulas for more precise body composition analysis, particularly in obese individuals.