Bosy-Westphal A, Reinecke U, Schlörke T, Illner K, Kutzner D, Heller M, Müller M J
Institut für Humanernährung und Lebensmittelkunde, Kiel, Germany.
Int J Obes Relat Metab Disord. 2004 Jan;28(1):72-9. doi: 10.1038/sj.ijo.0802526.
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).
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).
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.).
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.
在体重正常的受试者中，静息能量消耗（REE）可通过应用恒定的器官特异性代谢率，根据器官和组织质量准确计算得出。这种方法能够精确校正因身体成分导致的受试者间REE差异。由于从包括人体研究在内的种间比较中推断出器官代谢率会随器官质量增加而降低，因此在更广泛的去脂体重（FFM）范围内，器官和组织特异性REE计算方法的有效性仍有待验证。
在一项针对57名健康成年人（35名女性和22名男性，年龄19 - 43岁；14名体重过轻、25名体重正常和18名肥胖）的横断面研究中，使用磁共振成像（MRI）和双能X线吸收法（DXA）评估脑、内脏器官、骨骼肌（MM）、骨骼和脂肪组织的质量。通过间接测热法测量REE（REEm），并根据MRI和DXA详细测定的器官大小计算REE（REEc1），或者采用仅基于DXA的简化方法计算REE（REEc2）。
我们发现在整个FFM范围（28 - 86千克）内，REEm与REEc1高度一致。体重正常、体重过轻和肥胖受试者的REE预测误差分别为 - 17 ± 505、 - 145 ± 514和 - 141 ± 1058千焦/天（无显著差异）。将REEm对FFM进行回归分析，得到显著的正截距为每天1.6兆焦，通过根据MM/器官质量比例调整FFM，可将其降至每天0.5兆焦。在多元回归分析中，MM和肝脏质量解释了REEm变异的81%。DXA得出的REE预测值与测量值显示出良好的一致性（REEm和REEc2的平均值分别为5.72 ± 1.87和5.82 ± 1.51兆焦/天；差异无统计学意义）。
对FFM的代谢活跃成分进行详细分析，能够在广泛的FFM范围内预测REE。这些数据为以下观点提供了间接证据：就人体实际情况而言，特定代谢率随器官质量增加而保持恒定。FFM组成部分在一定程度上解释了REE与FFM之间的非线性关系。未来研究中必须对基于局部DXA测量的简化REE预测算法进行验证。
