Bennett K Ng1, Yong E Liu2, Wei Wang3, Thomas L Kelly3, Kevin E Wilson3, Dale A Schoeller4, Steven B Heymsfield5, John A Shepherd2. 1. University of California, Berkeley and University of California, San Francisco Graduate Program in Bioengineering, CA. 2. Department of Epidemiology, University of Hawaii Cancer Center, Honolulu, HI. 3. Hologic Inc., Marlborough, MA. 4. Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI. 5. Department of Metabolism and Body Composition, Pennington Biomedical Research Center, Baton Rouge, LA.
Abstract
Background: The 4-component (4C) model is a criterion method for human body composition that separates the body into fat, water, mineral, and protein, but requires 4 measurements with significant cost and time requirements that preclude wide clinical use. A simplified model integrating only 2 measurements-dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA)-and 10 min of patient time has been proposed. Objective: We aimed to validate a rapid, simplified 4C DXA + BIA body composition model in a clinical population. Design: This was a cross-sectional observational study of 31 healthy adults. Participants underwent whole-body DXA, segmental BIA, air displacement plethysmography (ADP), and total body water (TBW) measurement by deuterium (D2O) dilution. 4C composition was calculated through the use of the Lohman model [DXA mineral mass, D2O TBW, ADP body volume (BV), scale weight] and the simplified model (DXA mineral mass and BV, BIA TBW, scale weight). Accuracy of percentage of fat (%Fat) and protein measurements was assessed via linear regression. Test-retest precision was calculated with the use of duplicate DXA and BIA measurements. Results: Of 31 participants, 23 were included in the analysis. TBWBIA showed good test-retest precision (%CV = 5.2 raw; 1.1 after outlier removal) and high accuracy to TBWD2O [TBWD2O = 0.956*TBWBIA, R2= 0.92, root mean squared error (RMSE) = 2.2 kg]. %Fat estimates from DXA, ADP, D2O, and BIA all showed high correlation with the Lohman model. However, only the 4C simplified model provides high accuracy for both %Fat (R2 = 0.96, RMSE = 2.33) and protein mass (R2= 0.76, RMSE = 1.8 kg). %Fat precision from 4C DXA + BIA was comparable with DXA (root mean square-SD = 0.8 and 0.6 percentage units, respectively). Conclusions: This work validates a simplified 4C method that measures fat, water, mineral, and protein in a 10-min clinic visit. This model has broad clinical application to monitor many conditions including over/dehydration, malnutrition, obesity, sarcopenia, and cachexia.
Background: The 4-component (4C) model is a criterion method for human body composition that separates the body into fat, water, mineral, and protein, but requires 4 measurements with significant cost and time requirements that preclude wide clinical use. A simplified model integrating only 2 measurements-dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA)-and 10 min of patient time has been proposed. Objective: We aimed to validate a rapid, simplified 4CDXA + BIA body composition model in a clinical population. Design: This was a cross-sectional observational study of 31 healthy adults. Participants underwent whole-body DXA, segmental BIA, air displacement plethysmography (ADP), and total body water (TBW) measurement by deuterium (D2O) dilution. 4C composition was calculated through the use of the Lohman model [DXA mineral mass, D2OTBW, ADP body volume (BV), scale weight] and the simplified model (DXA mineral mass and BV, BIATBW, scale weight). Accuracy of percentage of fat (%Fat) and protein measurements was assessed via linear regression. Test-retest precision was calculated with the use of duplicate DXA and BIA measurements. Results: Of 31 participants, 23 were included in the analysis. TBWBIA showed good test-retest precision (%CV = 5.2 raw; 1.1 after outlier removal) and high accuracy to TBWD2O [TBWD2O = 0.956*TBWBIA, R2= 0.92, root mean squared error (RMSE) = 2.2 kg]. %Fat estimates from DXA, ADP, D2O, and BIA all showed high correlation with the Lohman model. However, only the 4C simplified model provides high accuracy for both %Fat (R2 = 0.96, RMSE = 2.33) and protein mass (R2= 0.76, RMSE = 1.8 kg). %Fat precision from 4CDXA + BIA was comparable with DXA (root mean square-SD = 0.8 and 0.6 percentage units, respectively). Conclusions: This work validates a simplified 4C method that measures fat, water, mineral, and protein in a 10-min clinic visit. This model has broad clinical application to monitor many conditions including over/dehydration, malnutrition, obesity, sarcopenia, and cachexia.
Authors: S B Heymsfield; C B Ebbeling; J Zheng; A Pietrobelli; B J Strauss; A M Silva; D S Ludwig Journal: Obes Rev Date: 2015-02-03 Impact factor: 9.213
Authors: Anne B Newman; Varant Kupelian; Marjolein Visser; Eleanor M Simonsick; Bret H Goodpaster; Stephen B Kritchevsky; Frances A Tylavsky; Susan M Rubin; Tamara B Harris Journal: J Gerontol A Biol Sci Med Sci Date: 2006-01 Impact factor: 6.053
Authors: C Vaché; P Rousset; P Gachon; A M Gachon; B Morio; A Boulier; J Coudert; B Beaufrère; P Ritz Journal: Int J Obes Relat Metab Disord Date: 1998-06
Authors: Grant M Tinsley; M Lane Moore; Austin J Graybeal; Antonio Paoli; Youngdeok Kim; Joaquin U Gonzales; John R Harry; Trisha A VanDusseldorp; Devin N Kennedy; Megan R Cruz Journal: Am J Clin Nutr Date: 2019-09-01 Impact factor: 7.045
Authors: Grant M Tinsley; M Lane Moore; Jacob R Dellinger; Brian T Adamson; Marqui L Benavides Journal: Eur J Clin Nutr Date: 2019-11-04 Impact factor: 4.016
Authors: Matheus S Cerqueira; Paulo R S Amorim; Irismar G A Encarnação; Leonardo M T Rezende; Paulo H R F Almeida; Analiza M Silva; Manuel Sillero-Quintana; Diego A S Silva; Fernanda K Santos; João C B Marins Journal: Eat Weight Disord Date: 2022-06-14 Impact factor: 3.008
Authors: Jonathan P Bennett; Yong En Liu; Brandon K Quon; Nisa N Kelly; Michael C Wong; Samantha F Kennedy; Dominic C Chow; Andrea K Garber; Ethan J Weiss; Steven B Heymsfield; John A Shepherd Journal: Clin Nutr Date: 2021-12-07 Impact factor: 7.643
Authors: Kurt Z Long; Johanna Beckmann; Christin Lang; Harald Seelig; Siphesihle Nqweniso; Nicole Probst-Hensch; Ivan Müller; Uwe Pühse; Peter Steinmann; Rosa du Randt; Cheryl Walter; Jürg Utzinger; Markus Gerber Journal: BMC Med Date: 2022-01-27 Impact factor: 8.775
Authors: Zeke J McKinney; Ralph S Bovard; Maria N Starchook-Moore; Kevin Ronneberg; Min Xi; Dani M Bredeson; Erin C Schwartz; Sandra L Thelen; Trista L Nash; Mark Dickinson; Thomas McDonough; Kara Hirdman; Nicolaas P Pronk Journal: J Occup Environ Med Date: 2021-01-01 Impact factor: 2.306