Department of Clinical Medicine and Surgery, University Federico II, Naples, Italy.
Department of Clinical Medicine and Surgery, University Federico II, Naples, Italy.
Clin Nutr. 2018 Oct;37(5):1670-1674. doi: 10.1016/j.clnu.2017.07.016. Epub 2017 Jul 27.
BACKGROUND & AIMS: The assessment of body composition is crucial in evaluating nutritional status in female subjects with anorexia nervosa (AN) and improving their clinical management. The aim of this retrospective study was to assess the accuracy of selected BIA (bioimpedance analysis) equations for fat-free mass (FFM) in female AN subjects and to formulate a specific equation for these subjects.
Eighty-two restrictive female AN subjects (age 20.5 ± 3.7 yrs, BMI 15.7 ± 1.7 kg/m) were studied. Body composition was determined with dual-energy X-ray absorptiometry (DXA) and estimated by BIA using five different equations. Linear correlation analysis was carried out to evaluate the association of FFM with selected variables. Multiple regression analysis was used to formulate specific equations to predict FFM in AN.
All predictive equations underestimated FFM at the population level with a bias from -5.6 to -11.7%, while the percentage of accurate predictions varied from 12.2% to 35.4%. More interestingly, multiple regression analysis clearly indicates that, in addition to weight, ZI or RI also emerged as independent predictors of DXA-derived FFM, increasing the prediction power of the equation well above that observed with anthropometric characteristics only.
This study shows that the selected predictive BIA equations considered exhibit an insufficient accuracy at the population and the individual level. Predictive formulas based on body weight plus BIA parameters such as RI and ZI offer a rather accurate prediction of FFM (with high R squared).
评估人体成分对于评估厌食症(AN)女性患者的营养状况以及改善其临床管理至关重要。本回顾性研究旨在评估特定 BIA(生物电阻抗分析)公式在评估女性 AN 患者的去脂体重(FFM)方面的准确性,并为这些患者制定特定的公式。
共纳入 82 名限制型 AN 女性患者(年龄 20.5±3.7 岁,BMI 15.7±1.7 kg/m)。通过双能 X 射线吸收法(DXA)和 5 种不同的 BIA 公式来测定人体成分。采用线性相关分析评估 FFM 与选定变量的相关性。采用多元回归分析制定特定的公式来预测 AN 患者的 FFM。
所有预测公式在人群水平上均低估了 FFM,偏差范围为-5.6%至-11.7%,而准确预测的百分比从 12.2%到 35.4%不等。更有趣的是,多元回归分析清楚地表明,除了体重之外,ZI 或 RI 也成为 DXA 测定的 FFM 的独立预测因子,使方程的预测能力明显高于仅使用人体测量特征时的预测能力。
本研究表明,所选预测性 BIA 公式在人群和个体水平上的准确性均不足。基于体重加 BIA 参数(如 RI 和 ZI)的预测公式可以对 FFM 进行相当准确的预测(R 平方值较高)。