Kuriyan Rebecca, Thomas Tinku, Kurpad A V
Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Bangalore, India.
Indian J Med Res. 2008 May;127(5):441-6.
BACKGROUND & OBJECTIVE: Skeletal muscle mass represents about 30-40 per cent of the total body weight, and has important roles in function and metabolism. Although newer methods of measuring muscle mass are accurate and sophisticated, there is a need for methods that can be used in low resource settings. Existing methods of predicting muscle mass are based on mid upper arm circumference (MUAC) measurements, sometimes corrected for triceps skinfold fat. The present study was undertaken to develop predictive equations for estimating muscle mass from simple and non-invasive methods such as bioelectrical impedance (BIA) and anthropometric measurements (circumferences and skinfold thickness) in Indian men.
BIA measurements and anthropometric measurements were carried out on 67 normal, healthy men between the ages of 18 and 45 yr. True muscle mass was measured from 24 h creatinine excretion. Multiple linear regression with step-wise forward selection was used to predict total muscle mass using measurements like height(2)/impedence, height and weight and using arm muscle area (AMA), thigh muscle area (TMA) and calf muscle area (CMA).
The prediction equation for muscle mass (kg) using height(2)/impedance and height was - 12.347+ (0.363 x height(2)/impedance) + (0.122 x height) [R(2) = 0.55; Standard error of estimate (SEE) = 2.58 kg], while the equation using appendicular muscle area was 10.122 + (0.23 x AMA)+ (0.049 x TMA) [R(2) 0.36; SEE 3.07 kg].
INTERPRETATION & CONCLUSION: This study provides prediction equations for estimating muscle mass in healthy Indian males from simple non invasive methods such as BIA and anthropometric measurements such as circumferences and skinfold thickness. Further studies need to be done on a larger sample size and using an external group to validate the equations.
骨骼肌质量约占总体重的30%-40%，在功能和代谢方面发挥着重要作用。尽管测量肌肉质量的新方法准确且精密，但仍需要适用于资源匮乏环境的方法。现有的预测肌肉质量的方法基于上臂中部周长（MUAC）测量，有时会根据肱三头肌皮褶厚度进行校正。本研究旨在通过生物电阻抗（BIA）和人体测量（周长和皮褶厚度）等简单且非侵入性的方法，为印度男性建立估算肌肉质量的预测方程。
对67名年龄在18至45岁之间的正常健康男性进行了BIA测量和人体测量。通过24小时肌酐排泄量测量真实肌肉质量。使用逐步向前选择的多元线性回归，利用身高(2)/阻抗、身高和体重等测量值以及臂肌面积（AMA）、大腿肌面积（TMA）和小腿肌面积（CMA）来预测总肌肉质量。
使用身高(2)/阻抗和身高预测肌肉质量（kg）的方程为 - 12.347 + (0.363 × 身高(2)/阻抗) + (0.122 × 身高) [R(2) = 0.55；估计标准误差（SEE） = 2.58 kg]，而使用附属肌肉面积的方程为10.122 + (0.23 × AMA) + (0.049 × TMA) [R(2) 0.36；SEE 3.07 kg]。
本研究通过BIA等简单非侵入性方法以及周长和皮褶厚度等人体测量方法，为健康印度男性估算肌肉质量提供了预测方程。需要对更大样本量进行进一步研究，并使用外部群体来验证这些方程。
