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Published on: July 10, 2017
Evaluation of a Rapid Four-Compartment Model and Stand-Alone Methods in Hispanic Adults
Brett S Nickerson1, Grant M Tinsley2, Kyung-Shin Park3
1School 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.
Background:
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.
Objectives:
This study aimed to determine the added benefit of a rapid 4C model over stand-alone DXA and MFBIA when estimating body composition.
Methods:
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.
Results:
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.
Conclusions:
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).
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