seca gmbh & co. kg, Hamburg, Germany.
Institut für Humanernährung und Lebensmittelkunde, Christian-Albrechts-Universität Kiel, Kiel, Germany.
Obes Facts. 2019;12(3):307-315. doi: 10.1159/000499607. Epub 2019 May 27.
A high amount of adipose tissue limits the accuracy of methods for body composition analysis in obesity.
The aim was to quantify and explain differences in fat-free mass (FFM) (as an index of skeletal muscle mass, SMM) measured with bioelectrical impedance analysis (BIA), dual energy X-ray absorptiometry (DXA), air displacement plethysmography (ADP), and deuterium dilution in comparison to multicompartment models, and to improve the results of BIA for obese subjects.
In 175 healthy subjects (87 men and 88 women, BMI 20-43.3 kg/m2, 18-65 years), FFM measured by these methods was compared with results from a 3- (3C) and a 4-compartment (4C) model. FFM4C was compared with SMM measured by magnetic resonance imaging.
BIA and DXA overestimated and ADP underestimated FFM in comparison to 3C and 4C models with increasing BMI (all p < 0.001). -Differences were largest for DXA. In obesity, BIA results were improved: valuecorrected = -valueuncorrected - a(BMI - 30 kg/m2), a = 0.256 for FFM and a = 0.298 for SMM. SMM accounts for 45% of FFM in women and 49% in men.
In obesity, the use of FFM is limited by a systematic error of reference methods. In addition, SMM accounts for about 50% of FFM only. Corrected measurement of SMM by BIA can overcome these drawbacks.
大量脂肪组织会限制肥胖人群体成分分析方法的准确性。
旨在定量和解释生物电阻抗分析(BIA)、双能 X 射线吸收法(DXA)、空气置换体描记法(ADP)和氘稀释法测量的去脂体重(FFM)(作为骨骼肌质量的指标,SMM)与多 compartment 模型相比的差异,并改善 BIA 在肥胖人群中的结果。
在 175 名健康受试者(87 名男性和 88 名女性,BMI 为 20-43.3 kg/m2,年龄 18-65 岁)中,这些方法测量的 FFM 与 3 compartment(3C)和 4-compartment(4C)模型的结果进行比较。FFM4C 与磁共振成像测量的 SMM 进行比较。
BIA 和 DXA 与 3C 和 4C 模型相比,高估了 FFM,而 ADP 随着 BMI 的增加而低估了 FFM(均 p < 0.001)。与 DXA 相比,差异最大。在肥胖中,BIA 结果得到了改善:值修正= -值未修正 - a(BMI - 30 kg/m2),a 为 FFM 的 0.256,SMM 的 0.298。女性 FFM 中 SMM 占 45%,男性 FFM 中 SMM 占 49%。
在肥胖中,参考方法的系统误差限制了 FFM 的使用。此外,SMM 仅占 FFM 的约 50%。通过 BIA 对 SMM 的修正测量可以克服这些缺点。