Astrup A, Thorbek G, Lind J, Isaksson B
Research Department of Human Nutrition, Royal Veterinary and Agricultural University, Copenhagen, Denmark.
Am J Clin Nutr. 1990 Nov;52(5):777-83. doi: 10.1093/ajcn/52.5.777.
The applicability of body composition as estimated by the bioimpedance method to predict energy expenditure (EE) was studied. Ten healthy subjects underwent measurement of body composition and 24-h energy expenditure (24-h EE) twice in a respiration chamber on a fixed program. The 24-h EE and its components, sleeping EE (SEE), basal EE (BEE), and daytime EE, for an individual were very reproducible (coefficient of variation 2.3%, 1.4%, 5.0%, & 3.1%, respectively). The variability of 24-h EE among subjects was 11.4% but only 4.1% when adjusted for differences in lean body mass (LBM). LBM was the best determinant of 24-h EE, BEE, and SEE and accounted for 91-93% of the interindividual variance of EE. The prediction equations were 24EE (kcal/d) = 390 + 33.3 LBM (r2 = 0.93, P = 0.000001), SEE (kcal/h) = 9.8 + 1.1 LBM (r2 = 0.92, P = 0.000001), and BEE (kcal/h) = -3.1 + 1.35 LBM (r2 = 0.91, P = 0.000002). In conclusion, 24EE, BEE, and SEE can be predicted with a high degree of precision from LBM as estimated by bioimpedance in normal-weight subjects.
研究了通过生物电阻抗法估算的身体成分在预测能量消耗（EE）方面的适用性。10名健康受试者按照固定方案在呼吸室内进行了两次身体成分测量和24小时能量消耗（24-h EE）测量。个体的24小时EE及其组成部分，即睡眠EE（SEE）、基础EE（BEE）和白天EE，具有很高的可重复性（变异系数分别为2.3%、1.4%、5.0%和3.1%）。受试者之间24小时EE的变异性为11.4%，但在根据瘦体重（LBM）差异进行调整后仅为4.1%。LBM是24小时EE、BEE和SEE的最佳决定因素，占EE个体间差异的91 - 93%。预测方程为24EE（千卡/天）= 390 + 33.3LBM（r2 = 0.93，P = 0.000001），SEE（千卡/小时）= 9.8 + 1.1LBM（r2 = 0.92，P = 0.000001），BEE（千卡/小时）= -3.1 + 1.35LBM（r2 = 0.91，P = 0.000002）。总之，在正常体重受试者中，通过生物电阻抗估算的LBM可以高精度预测24EE、BEE和SEE。
