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去脂体重作为脂肪量和日常活动水平的函数。

Fat-free mass as a function of fat mass and habitual activity level.

作者信息

Westerterp K R, Meijer G A, Kester A D, Wouters L, ten Hoor F

机构信息

Department of Human Biology, University of Limburg, Maastricht, The Netherlands.

出版信息

Int J Sports Med. 1992 Feb;13(2):163-6. doi: 10.1055/s-2007-1021249.

Abstract

The best predictor of energy expenditure in man is the fat-free mass of the body. Fat-free mass explains most of the variation in resting metabolic rate and even in total metabolic rate under sedentary conditions. We studied possible determinants of fat-free mass as routes to influence energy metabolism. Existing data sets were analysed with observations on height, fat mass (FM), fat-free mass (FFM), and habitual level of physical activity (PA). PA was calculated from average daily metabolic rate (ADMR) as measured over 1-4-week intervals with 2H2(18)O and basal metabolic rate (BMR): PA = ADMR/BMR. Ninety-six subjects, 66 females and 30 males, from 7 different studies were included. FFM and FM were adjusted for height by taking its ratio to the square of height, in analogy with the body mass index. Subsequently, all analyses were corrected for origin of the data. In a regression analysis FM explained 53 and 40% of the variation in FFM in females and males, respectively. Adding PA to the model raised the explained variation in FFM in females to 62%. In contrast with females (r = 0.10, n.s.), there was an independent relationship between PA and FM in males (r = -0.41, p less than or equal to 0.05), such that a higher PA was related to a lower FM. In conclusion, FFM is a function of FM and PA. The absence of an effect of exercise training on FFM, i.e. additional exercise in weight-reduction programmes, is discussed.

摘要

人体能量消耗的最佳预测指标是身体的去脂体重。去脂体重解释了静息代谢率甚至久坐条件下总代谢率的大部分变化。我们研究了去脂体重的可能决定因素,将其作为影响能量代谢的途径。利用身高、脂肪量(FM)、去脂体重(FFM)和习惯性身体活动水平(PA)的观测数据对现有数据集进行了分析。PA通过使用2H2(18)O和基础代谢率(BMR)在1 - 4周间隔内测量的平均每日代谢率(ADMR)计算得出:PA = ADMR/BMR。纳入了来自7项不同研究的96名受试者,其中66名女性和30名男性。FFM和FM通过将其与身高平方的比值进行调整,类似于体重指数。随后,所有分析都对数据来源进行了校正。在回归分析中,FM分别解释了女性和男性FFM变化的53%和40%。将PA加入模型后,女性FFM的解释变异增加到62%。与女性相反(r = 0.10,无统计学意义),男性的PA与FM之间存在独立关系(r = -0.41,p≤0.05),即较高的PA与较低的FM相关。总之,FFM是FM和PA的函数。讨论了运动训练对FFM无影响,即在减肥计划中额外运动的情况。

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