Salamat Mohammad Reza, Shanei Ahmad, Salamat Amir Hossein, Khoshhali Mehri, Asgari Mahdi
Department of Medical Physics and Medical Engineering, Medical School, Isfahan University of Medical Sciences, Isfahan, Iran.
Department of Research and Development, Isfahan Osteoporosis Diagnosis and Body Composition Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Adv Biomed Res. 2015 Jan 30;4:34. doi: 10.4103/2277-9175.150429. eCollection 2015.
Precise and accurate measurements of body composition are useful in achieving a greater understanding of human energy metabolism in physiology and in different clinical conditions, such as, cardiovascular disease and overall mortality. Dual-energy x-ray absorptiometry (DXA) can be used to measure body composition, but the easiest method to assess body composition is the use of anthropometric indices. This study has been designed to evaluate the accuracy and precision of body composition prediction equations by various anthropometric measures instead of a whole body DXA scan.
We identified 143 adult patients underwent DXA evaluation of the whole body. The anthropometric indices were also measured. Datasets were split randomly into two parts. Multiple regression analysis with a backward stepwise elimination procedure was used as the derivation set and then the estimates were compared with the actual measurements from the whole-body scans for a validation set. The SPSS version 20 for Windows software was used in multiple regression and data analysis.
Using multiple linear regression analyses, the best equation for predicting the whole-body fat mass (R(2) = 0.808) included the body mass index (BMI) and gender; the best equation for predicting whole-body lean mass (R(2) = 0.780) included BMI, WC, gender, and age; and the best equation for predicting trunk fat mass (R(2) = 0.759) included BMI, WC, and gender.
Combinations of anthropometric measurements predict whole-body lean mass and trunk fat mass better than any of these single anthropometric indices. Therefore, the findings of the present study may be used to verify the results in patients with various diseases or diets.
准确精确地测量身体成分有助于更深入地了解生理学以及不同临床状况（如心血管疾病和全因死亡率）下的人体能量代谢。双能X线吸收法（DXA）可用于测量身体成分，但评估身体成分最简单的方法是使用人体测量指标。本研究旨在通过各种人体测量方法而非全身DXA扫描来评估身体成分预测方程的准确性和精确性。
我们纳入了143例接受了全身DXA评估的成年患者。同时测量了人体测量指标。数据集被随机分为两部分。采用向后逐步淘汰程序的多元回归分析作为推导集，然后将估计值与验证集全身扫描的实际测量值进行比较。使用Windows版SPSS 20软件进行多元回归和数据分析。
通过多元线性回归分析，预测全身脂肪量的最佳方程（R² = 0.808）包括体重指数（BMI）和性别；预测全身瘦体重的最佳方程（R² = 0.780）包括BMI、腰围（WC）、性别和年龄；预测躯干脂肪量的最佳方程（R² = 0.759）包括BMI、WC和性别。
人体测量指标的组合预测全身瘦体重和躯干脂肪量的效果优于任何单一人体测量指标。因此，本研究结果可用于验证患有各种疾病或遵循不同饮食的患者的结果。
