Völgyi Eszter, Tylavsky Frances A, Lyytikäinen Arja, Suominen Harri, Alén Markku, Cheng Sulin
Department of Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
Obesity (Silver Spring). 2008 Mar;16(3):700-5. doi: 10.1038/oby.2007.94. Epub 2008 Jan 17.
This study evaluated to what extent dual-energy X-ray absorptiometry (DXA) and two types of bioimpedance analysis (BIA) yield similar results for body fat mass (FM) in men and women with different levels of obesity and physical activity (PA).
The study population consisted of 37-81-year-old Finnish people (82 men and 86 women). FM% was estimated using DXA (GE Lunar Prodigy) and two BIA devices (InBody (720) and Tanita BC 418 MA). Subjects were divided into normal, overweight, and obese groups on the basis of clinical cutoff points of BMI, and into low PA (LPA) and high PA (HPA) groups. Agreement between the devices was calculated by using the Bland-Altman analysis.
Compared to DXA, both BIA devices provided on average 2-6% lower values for FM% in normal BMI men, in women in all BMI categories, and in both genders in both HPA and LPA groups. In obese men, the differences were smaller. The two BIA devices provided similar means for groups. Differences between the two BIA devices with increasing FM% were a result of the InBody (720) not including age in their algorithm for estimating body composition.
BIA methods provided systematically lower values for FM than DXA. However, the differences depend on gender and body weight status pointing out the importance of considering these when identifying people with excess FM.
本研究评估了双能X线吸收法(DXA)和两种生物电阻抗分析(BIA)方法在不同肥胖程度和身体活动(PA)水平的男性和女性中,测量体脂量(FM)时产生相似结果的程度。
研究对象为37至81岁的芬兰人(82名男性和86名女性)。使用DXA(GE Lunar Prodigy)和两种BIA设备(InBody(720)和Tanita BC 418 MA)估计FM%。根据BMI的临床切点将受试者分为正常、超重和肥胖组,并分为低PA(LPA)和高PA(HPA)组。使用Bland-Altman分析计算设备之间的一致性。
与DXA相比,在正常BMI男性、所有BMI类别的女性以及HPA和LPA组的男女中,两种BIA设备测得的FM%平均值均比DXA低2%-6%。在肥胖男性中,差异较小。两种BIA设备为各组提供的平均值相似。随着FM%增加,两种BIA设备之间的差异是由于InBody(720)在其身体成分估计算法中未纳入年龄。
BIA方法测得的FM值系统地低于DXA。然而,差异取决于性别和体重状况,这表明在识别FM过多的人群时考虑这些因素的重要性。