Hayes Matthew, Chustek Michael, Wang ZiMian, Gallagher Dympna, Heshka Stanley, Spungen Ann, Bauman William, Heymsfield Steven B
Department of Medicine, Obesity Research Center, St. Luke's/Roosevelt Hospital, Columbia University, College of Physicians and Surgeons, New York, New York 10025, USA.
Obes Res. 2002 Oct;10(10):969-77. doi: 10.1038/oby.2002.132.
This study tested the hypothesis that tissue-organ components can be derived from DXA measurements, and in turn, resting energy expenditure (REE) can be calculated from the summed heat productions of DXA-estimated brain, skeletal muscle mass (SM), adipose tissue, bone, and residual mass (RM).
Subjects were divided into five groups of adults <50 years of age. The specific metabolic rate of RM was developed in 13 Group I healthy subjects and a DXA-brain mass prediction formula in 52 Group II subjects. SM, adipose tissue, and bone models were developed based on earlier reports. The composite REE prediction model (REEp) was tested in 154 Group III subjects in whom REEp was compared with measured REE (REEm). Features of the developed model were determined in 94 normal-weight men and women (Group IV) and seven spinal cord injury patients and healthy matched controls (Group V).
REEp and REEm in Group III were highly correlated (y = 0.85x + 233; r = 0.82, p < 0.001), and no bias was detected. Both REEm (mean +/- SD, 1,579 +/- 324 kcal/d) and REEp (1,585 +/- 316 kcal/d) were also highly correlated (r values = 0.85 to 0.98; p values < 0.001) and provided similar group values to REE estimated by the Harris-Benedict equations (1,597 +/- 279 kcal/d) and Wang's composite fat-free mass-based REE equation (1,547 +/- 248 kcal/d). New insights into the sources and distribution of REE were provided by analysis of the demonstration groups.
This approach offers a new practical and educational opportunity to examine REE in subject groups using modeling strategies that reveal the magnitude and distribution of fundamental somatic heat-producing units.
本研究检验了以下假设，即组织器官成分可从双能X线吸收法（DXA）测量值得出，进而静息能量消耗（REE）可根据DXA估计的脑、骨骼肌质量（SM）、脂肪组织、骨骼和剩余质量（RM）的总产热来计算。
将受试者分为五组年龄小于50岁的成年人。在13名I组健康受试者中得出RM的特定代谢率，在52名II组受试者中得出DXA脑质量预测公式。基于早期报告建立SM、脂肪组织和骨骼模型。在154名III组受试者中测试复合REE预测模型（REEp），并将REEp与测量的REE（REEm）进行比较。在94名正常体重男性和女性（IV组）以及7名脊髓损伤患者和健康匹配对照（V组）中确定所建立模型的特征。
III组中的REEp和REEm高度相关（y = 0.85x + 233；r = 0.82，p < 0.001），未检测到偏差。REEm（均值±标准差，1579±324千卡/天）和REEp（1585±316千卡/天）也高度相关（r值 = 0.85至0.98；p值 < 0.001），并提供了与通过哈里斯-本尼迪克特方程估计的REE（1597±279千卡/天）和基于无脂肪质量的王复合REE方程（1547±248千卡/天）相似的组值。对示范组的分析提供了有关REE来源和分布的新见解。
这种方法提供了一个新的实践和教育机会，可使用建模策略来检查受试者组中的REE，这些策略揭示了基本产热体细胞单位的大小和分布。
