Department of Physical Therapy, School of Health Sciences, Japan University of Health Sciences, Saitama 340-0145, Japan.
Division of Physical Therapy, Department of Rehabilitation, Faculty of Health Sciences, Nagano University of Health and Medicine, Nagano 381-2227, Japan.
Int J Environ Res Public Health. 2022 Mar 29;19(7):4042. doi: 10.3390/ijerph19074042.
Non-invasive and easy alternative methods to indicate skeletal muscle mass index (SMI) have not been established when dual energy X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA) cannot be performed. This study aims to construct a prediction model including gastrocnemius thickness using ultrasonography for skeletal muscle mass index (SMI). Total of 193 Japanese aged ≥65 years participated. SMI was measured by BIA, and subcutaneous fat thickness and gastrocnemius thickness in the medial gastrocnemius were measured by using ultrasonography, and age, gender and body mass index (BMI), grip strength, and gait speed were collected. The stepwise multiple regression analysis was conducted, which incorporated SMI as a dependent variable and age, gender, BMI, gastrocnemius thickness, and other factors as independent variables. Gender, BMI, and gastrocnemius thickness were included as significant factors, and the formula: SMI = 1.27 × gender (men: 1, women: 0) + 0.18 × BMI + 0.09 × gastrocnemius thickness (mm) + 1.3 was shown as the prediction model for SMI (R = 0.89, R2 = 0.8, adjusted R2 = 0.8, p < 0.001). The prediction model for SMI had high accuracy and could be a non-invasive and easy alternative method to predict SMI in Japanese older adults.
当无法进行双能 X 射线吸收法(DXA)或生物电阻抗分析(BIA)时,尚未建立非侵入性且易于替代的方法来指示骨骼肌质量指数(SMI)。本研究旨在构建一种使用超声测量腓肠肌厚度的预测模型,用于预测骨骼肌质量指数(SMI)。共有 193 名年龄≥65 岁的日本老年人参与了该研究。使用 BIA 测量 SMI,使用超声测量皮下脂肪厚度和内侧腓肠肌的腓肠肌厚度,并收集年龄、性别和体重指数(BMI)、握力和步速等数据。进行逐步多元回归分析,将 SMI 作为因变量,年龄、性别、BMI、腓肠肌厚度和其他因素作为自变量。性别、BMI 和腓肠肌厚度被纳入为显著因素,公式为:SMI=1.27×性别(男性:1,女性:0)+0.18×BMI+0.09×腓肠肌厚度(mm)+1.3,这是 SMI 的预测模型(R=0.89,R²=0.8,调整后的 R²=0.8,p<0.001)。该 SMI 预测模型具有较高的准确性,可能是一种非侵入性且易于替代的方法,可用于预测日本老年人的 SMI。