基于外周定量计算机断层扫描的脂肪和肌肉面积、密度与基于双能X线吸收法的健康女性和男性全身及腿部软组织质量之间的关联。
Associations between pQCT-based fat and muscle area and density and DXA-based total and leg soft tissue mass in healthy women and men.
作者信息
Sherk V D, Thiebaud R S, Chen Z, Karabulut M, Kim S J, Bemben D A
机构信息
University of Colorado Anschutz Medical Campus, Division of Geriatric Medicine.
出版信息
J Musculoskelet Neuronal Interact. 2014 Dec;14(4):411-7.
UNLABELLED
Peripheral Quantitative Computed Tomography (pQCT) can be used for muscle and fat area and density assessments. These may independently influence muscle and fat mass measurements from Dual Energy X-ray Absorptiometry (DXA).
OBJECTIVE
To determine associations between pQCT-derived soft tissue density and area measures and DXA-derived soft tissue mass.
METHODS
Linear regression models were developed based on BMI and calf fat and muscle cross-sectional area (FCSA and MCSA) and density measured by pQCT in healthy women (n=76) and men (n=82) aged 20-59 years. Independent variables for these models were leg and total bone-free lean mass (BFLM) and fat mass (FM) measured by DXA.
RESULTS
Sex differences (p<0.01) were found in both muscle (Mean±SE: Women: 78.6±0.4; Men: 79.9±0.2 mg/cm(3)) and fat (Women: 0.8±0.4 Men: 9.1±0.6 mg/cm(3)) density. BMI, fat density, and age (R(2)=0.86, p<0.01) best accounted for the variability in total FM. FCSA, BMI, and fat density explained the variance in leg FM (R(2)=0.87, p<0.01). MCSA and muscle density explained the variance in total (R(2)=0.65, p<0.01) and leg BFLM (R(2)=0.70, p<0.01).
CONCLUSION
Calf muscle and fat area and density independently predict lean and fat tissue mass.
未标注
外周定量计算机断层扫描（pQCT）可用于肌肉和脂肪面积及密度评估。这些因素可能独立影响双能X线吸收法（DXA）测量的肌肉和脂肪量。
目的
确定pQCT衍生的软组织密度和面积测量值与DXA衍生的软组织量之间的关联。
方法
基于20 - 59岁健康女性（n = 76）和男性（n = 82）的BMI、小腿脂肪和肌肉横截面积（FCSA和MCSA）以及通过pQCT测量的密度，建立线性回归模型。这些模型的自变量是通过DXA测量的腿部和全身无骨瘦体重（BFLM）以及脂肪量（FM）。
结果
在肌肉（平均值±标准误：女性：78.6±0.4；男性：79.9±0.2 mg/cm³）和脂肪（女性：0.8±0.4；男性：9.1±0.6 mg/cm³）密度方面均发现了性别差异（p < 0.01）。BMI、脂肪密度和年龄（R² = 0.86，p < 0.01）最能解释总FM的变异性。FCSA、BMI和脂肪密度解释了腿部FM的方差（R² = 0.87，p < 0.01）。MCSA和肌肉密度解释了总BFLM（R² = 0.65，p < 0.01）和腿部BFLM（R² = 0.70，p < 0.01）的方差。
结论
小腿肌肉和脂肪面积及密度可独立预测瘦组织和脂肪组织量。
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