School of Health and Rehabilitation Sciences, College of Medicine, The Ohio State University, Columbus, OH, United States; College of Nursing and Health Sciences, Texas A & M International University, Laredo, TX, United States.
Department of Kinesiology and Sport Management, Texas Tech University, Lubbock, TX, United States.
J Nutr. 2023 Aug;153(8):2154-2162. doi: 10.1016/j.tjnut.2023.06.041. Epub 2023 Jul 5.
A rapid 4-compartment (4C) model integrates dual-energy x-ray absorptiometry (DXA) and multi-frequency bioimpedance analysis (MFBIA), which may be useful for clinical and research settings seeking to employ a multi-compartment model.
This study aimed to determine the added benefit of a rapid 4C model over stand-alone DXA and MFBIA when estimating body composition.
One hundred and thirty participants (n = 60 male; n = 70 female) of Hispanic descent were included in the present analysis. A criterion 4C model that employed air displacement plethysmography (body volume), deuterium oxide (total body water), and DXA (bone mineral) was used to measure fat mass (FM), fat-free mass (FFM), and body fat percent (%BF). A rapid 4C model (DXA-derived body volume and bone mineral; MFBIA-derived total body water) and stand-alone DXA (GE Lunar Prodigy) and MFBIA (InBody 570) assessments were compared against the criterion 4C model.
Lin's concordance correlation coefficient values were >0.90 for all comparisons. The standard error of the estimates ranged from 1.3 to 2.0 kg, 1.6 to 2.2 kg, and 2.1 to 2.7% for FM, FFM, and %BF, respectively. The 95% limits of agreement ranged from ±3.0 to 4.2 kg, ±3.1 to 4.2 kg, and ±4.9 to 5.2% for FM, FFM, and %BF, respectively.
Results revealed that all 3 methods provided acceptable body composition results. The MFBIA device used in the current study may be a more economically friendly option than DXA or when there is a need to minimize radiation exposure. Nonetheless, clinics and laboratories that already have a DXA device in place or that value having the lowest individual error when conducting a test may consider continuing to use the machine. Lastly, a rapid 4C model may be useful for assessing body composition measures observed in the current study and those provided by a multi-compartment model (e.g., protein).
快速 4 compartment(4C)模型集成了双能 X 射线吸收法(DXA)和多频生物阻抗分析(MFBIA),这对于寻求使用多 compartment 模型的临床和研究环境可能很有用。
本研究旨在确定快速 4C 模型在估计身体成分方面相对于独立的 DXA 和 MFBIA 的额外益处。
本分析纳入了 130 名西班牙裔参与者(n=60 名男性;n=70 名女性)。使用空气置换体积描记法(体容积)、重水(总体水)和 DXA(骨矿物质)的标准 4C 模型来测量脂肪量(FM)、去脂体重(FFM)和体脂百分比(%BF)。将快速 4C 模型(DXA 衍生的体容积和骨矿物质;MFBIA 衍生的总体水)和独立的 DXA(GE Lunar Prodigy)和 MFBIA(InBody 570)评估与标准 4C 模型进行比较。
所有比较的林氏一致性相关系数值均大于 0.90。估计的标准误差范围分别为 FM、FFM 和 %BF 的 1.3 至 2.0 千克、1.6 至 2.2 千克和 2.1 至 2.7%。95%的一致性界限范围分别为 FM、FFM 和 %BF 的±3.0 至 4.2 千克、±3.1 至 4.2 千克和±4.9 至 5.2%。
结果表明,所有 3 种方法均提供了可接受的身体成分结果。本研究中使用的 MFBIA 设备可能比 DXA 或需要最小化辐射暴露时更具经济吸引力。然而,已经在使用 DXA 设备的诊所和实验室,或者在进行测试时希望将个体误差降到最低的诊所和实验室,可能会考虑继续使用该设备。最后,快速 4C 模型可能对评估当前研究中观察到的身体成分测量值以及多 compartment 模型(例如蛋白质)提供的身体成分测量值有用。