Gallagher D, Belmonte D, Deurenberg P, Wang Z, Krasnow N, Pi-Sunyer F X, Heymsfield S B
Obesity Research Center, St. Luke's-Roosevelt Hospital, Columbia University College of Physicians and Surgeons, New York, New York 10025, USA.
Am J Physiol. 1998 Aug;275(2):E249-58. doi: 10.1152/ajpendo.1998.275.2.E249.
Investigators have expressed interest in the associations between resting energy expenditure (REE) and body mass for over a century. Traditionally, descriptive models using regression analysis are applied, linking REE with metabolically active compartments such as body cell mass (BCM) and fat-free body mass (FFM). Recently developed whole body magnetic resonance imaging (MRI) and echocardiography methods now allow estimation of all major organs and tissue volumes in vivo. Because measured values are available for REE, BCM, and FFM content of individual organs and tissues, it should now be possible to develop energy expenditure-body composition estimation models based on MRI-measured organ-tissue volumes. Specifically, the present investigation tested the hypothesis that in vivo estimation of whole body REE, BCM, and FFM is possible using MRI- and echocardiography-derived organ volumes combined with previously reported organ-tissue metabolic rates and chemical composition. Thirteen subjects (5 females, 8 males) had REE, BCM, and FFM measured by indirect calorimetry, whole body 40K counting, and dual-energy X-ray absorptiometry, respectively. Models developed from estimated and measured variables were highly correlated, with no significant differences between those estimated and measured [e.g., calculated vs. measured REE: r = 0.92, P < 0. 001; (mean +/- SD) 6,962 +/- 1,455 and 7,045 +/- 1,450 kJ/day, respectively (P = not significant)]. Strong associations were observed between REE, individual or combined organ weights, BCM, and FFM that provide new insights into earlier observed metabolic phenomona. The present approach, the first to establish an energy expenditure-body composition link with a mechanistic model in vivo, has the potential to greatly expand our knowledge of energy expenditure-body size relationships in humans.
一个多世纪以来，研究人员一直对静息能量消耗（REE）与体重之间的关联很感兴趣。传统上，采用回归分析的描述性模型被用于将REE与诸如体细胞质量（BCM）和去脂体重（FFM）等代谢活跃部分联系起来。最近开发的全身磁共振成像（MRI）和超声心动图方法现在能够在体内估计所有主要器官和组织的体积。由于可以获得REE、BCM以及各个器官和组织的FFM含量的测量值，现在应该能够基于MRI测量的器官组织体积来开发能量消耗-身体成分估计模型。具体而言，本研究检验了这样一个假设，即利用MRI和超声心动图得出的器官体积，结合先前报道的器官组织代谢率和化学成分，在体内估计全身REE、BCM和FFM是可行的。13名受试者（5名女性，8名男性）分别通过间接量热法、全身40K计数法和双能X线吸收法测量了REE、BCM和FFM。根据估计变量和测量变量建立的模型高度相关，估计值和测量值之间没有显著差异[例如，计算得出的REE与测量得出的REE：r = 0.92，P < 0.001；（均值±标准差）分别为6,962 ± 1,455和7,045 ± 1,45０kJ/天（P = 不显著）]。在REE、单个或组合器官重量、BCM和FFM之间观察到了很强的关联，这为早期观察到的代谢现象提供了新的见解。本方法是首次在体内通过机械模型建立能量消耗-身体成分联系，有潜力极大地扩展我们对人类能量消耗与身体大小关系的认识。
