Effect of organ and tissue masses on resting energy expenditure in underweight, normal weight and obese adults
- PMID: 14647174
- DOI: 10.1038/sj.ijo.0802526
Effect of organ and tissue masses on resting energy expenditure in underweight, normal weight and obese adults
Abstract
Background: In normal-weight subjects, resting energy expenditure (REE) can be accurately calculated from organ and tissue masses applying constant organ-specific metabolic rates. This approach allows a precise correction for between-subjects variation in REE, explained by body composition. Since a decrease in organ metabolic rate with increasing organ mass has been deduced from interspecies comparison including human studies, the validity of the organ- and tissue-specific REE calculation remains to be proved over a wider range of fat-free mass (FFM).
Design: In a cross-sectional study on 57 healthy adults (35 females and 22 males, 19-43 y; 14 underweight, 25 intermediate weight and 18 obese), magnetic resonance imaging (MRI) and dual-energy X-ray absorptiometry (DXA) were used to assess the masses of brain, internal organs, skeletal muscle (MM), bone and adipose tissue. REE was measured by indirect calorimetry (REEm) and calculated from detailed organ size determination by MRI and DXA (REEc1), or in a simplified approach exclusively from DXA (REEc2).
Results: We found a high agreement between REEm and REEc1 over the whole range of FFM (28-86 kg). REE prediction errors were -17 +/- 505, -145 +/- 514 and -141 +/- 1058 kJ/day in intermediate weight, underweight and obese subjects, respectively (n.s.). Regressing REEm on FFM resulted in a significant positive intercept of 1.6 MJ/day that could be reduced to 0.5 MJ/day by adjusting FFM for the proportion of MM/organ mass. In a multiple regression analysis, MM and liver mass explained 81% of the variance in REEm. DXA-derived REE prediction showed a good agreement with measured values (mean values for REEm and REEc2 were 5.72 +/- 1.87 and 5.82 +/- 1.51 MJ/day; difference n.s.).
Conclusion: Detailed analysis of metabolically active components of FFM allows REE prediction over a wide range of FFM. The data provide indirect evidence for a view that, for practical purposes within humans, the specific metabolic rate is constant with increasing organ mass. Nonlinearity of REE on FFM was partly explained by FFM composition. A simplified REE prediction algorithm from regional DXA measurements has to be validated in future studies.
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