Total-body skeletal muscle mass: estimation by a new dual-energy X-ray absorptiometry method
Total-body skeletal muscle mass: estimation by a new dual-energy X-ray absorptiometry method
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DOI：
10.1093/ajcn/76.2.378
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发表时间：
2002-08-01
影响因子：
7.1
通讯作者：
Gallagher, D
中科院分区：
文献类型：
--
作者：
Kim, J;Wang, ZM;Gallagher, D
背景资料：骨骼肌（SM）是一个重要的身体组成部分，仍然很难和不切实际的量化大多数研究人员以外的专业研究中心。全身SM的大部分存在于四肢，并且四肢瘦软组织的大部分是SM。因此，在无脂肪瘦软组织（ALST）质量和全身SM质量之间应该存在强有力的联系。目的：目的是建立预测模型，将双能X射线吸收测定法（DXA）估计的ALST与健康成年人多层磁共振成像量化的全身SM联系起来。设计：ALST和全身SM采用横断面设计在成人[体重指数（kg/m2）< 35]，分别在模型开发组和模型验证组中开发和验证SM预测模型。模型开发组和模型验证组分别包括321名和93名不同种族的成年人。结果：单独的ALST与全身SM高度相关（模型1：R-2 = 0.96，SEE = 1.63 kg，P < 0.001），尽管多元回归分析显示2个额外的预测变量：年龄（模型2：2-变量组合R-2 = 0.96，SEE = 1.58 kg，P < 0.001）和性别（模型3：3-变量组合R-2 = 0.96，SEE = 1.58 kg，P < 0.001）。所有3个模型在验证组中表现良好。一个SM预测模型的SM-ALST比率的基础上，也开发了，虽然这个模型有局限性，当它被应用于所有subjects.Conclusion：全身SM可以准确地预测从DXA估计ALST，从而提供了一个实用的手段量化的大型和临床上重要的SM室。
Background: Skeletal muscle (SM) is an important body-composition component that remains difficult and impractical to quantify by most investigators outside of specialized research centers. A large proportion of total-body SM is found in the extremities, and a large proportion of extremity lean soft tissue is SM. A strong link should thus exist between appendicular lean soft tissue (ALST) mass and total-body SM mass.Objective: The objective was to develop prediction models linking ALST estimated by dual-energy X-ray absorptiometry (DXA) with total-body SM quantified by multislice magnetic resonance imaging in healthy adults.Design: ALST and total-body SM were evaluated with a cross-sectional design in adults [body mass index (in kg/m(2)) < 35] with an SM-prediction model developed and validated in model-development and model-validation groups, respectively. The model-development and model-validation groups included 321 and 93 ethnically diverse adults, respectively.Results: ALST alone was highly correlated with total-body SM (model 1 : R-2 = 0.96, SEE = 1.63 kg, P < 0.001), although multiple regression analyses showed 2 additional predictor variables: age (model 2: 2-variable combined R-2 = 0.96, SEE = 1.58 kg, P < 0.001) and sex (model 3: 3-variable combined R-2 - 0.96, SEE = 1.58 kg, P < 0.001). All 3 models performed well in the validation group. An SM-prediction model based on the SM-ALST ratio was also developed, although this model had limitations when it was applied across all subjects.Conclusion: Total-body SM can be accurately predicted from DXA-estimated ALST, thus affording a practical means of quantifying the large and clinically important SM compartment.