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1 Exercise and Health Laboratory, Faculty of Human Movement-Technical University of Lisbon, Lisbon, Portugal
2 New York Obesity Research Center, St. Luke's-Roosevelt Hospital, Columbia University Institute of Human Nutrition, College of Physicians and Surgeons, New York, NY, USA
3 Department of Medicine, Winthrop-University Hospital, Mineola, NY, USA
4 John Hancock Center for Physical Activity and Nutrition, Friedman School of Nutrition Science and Policy at Tufts University, Boston, MA, USA
* To whom correspondence should be addressed. E-mail: SBH2{at}Columbia.edu.
There is renewed interest in Siri's classic three-compartment (3C) body
composition model, requiring body volume (BV) and total body water (TBW)
estimates, as dual-energy x-ray absorptiometry (DXA) and in vivo neutron activation
(IVNA) systems cannot accommodate subjects with severe obesity. However, the 3C
model assumption of a constant mineral (M) to total body protein (TBPro) ratio (
)
and related residual mass density (DRES) based on cadaver analyses might not be valid
across groups differing in sex, race, age, and weight. The aim of this study was to
derive new 3C model coefficients in vivo and to compare these estimates to those
derived by Siri. Healthy adults (n=323) were evaluated with IVNA and DXA and the
measured components used to derive
and DRES. For all subjects combined,
and
DRES (mean ± SD, 0.351 ± 0.043; 1.565 ± 0.023 kg/L) were similar to Siri's proposed
values of 0.35 and 1.565 kg/L, respectively. However,
and DRES varied significantly
as a function of sex, race, weight, and age. Expected errors in percent body fat arising
by application of Siri's model were illustrated in a second group of 264 adults,
including some whose size exceeded DXA limits, but whose BV and TBW had been
measured by hydrodensitometry and 2H2O dilution, respectively. Extrapolation of
predictions by newly developed models to very high weights allowed percent fat error
estimation when Siri's model is applied in morbidly obese subjects. The present study
results provide a critical evaluation of potential errors in the classic 3C model and
present new formulas for use in selected populations.
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