Validation of rapid 4-component body composition assessment with the use of dual-energy X-ray absorptiometry and bioelectrical impedance analysis
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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.
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A personalized approach to obesity assessment considers factors such as muscle mass, visceral fat levels, and metabolic health markers, in addition to weight status.
“This personalized approach to obesity assessment considers factors such as muscle mass, visceral fat levels, and metabolic health markers, in addition to weight status [64].”
From Advantages and Limitations of the Body Mass Index (BMI) to Assess Adult Obesity (2024) · cites this paper as [64]
The Abstract Conclusions and Discussion (pages not provided) describe assessing fat, protein, and hydration for clinical uses that include obesity, supporting assessment beyond weight alone. The paper does not specify visceral fat levels or metabolic health markers as components of that assessment, and its protein or lean-mass measures are not direct muscle-mass measurements. (LLM, conf=0.86)
Experimental — accuracy not yet measuredAssessments for harmful adiposity encounter health system constraints of accessibility and affordability.
“Medical evaluations with greater predictive value need accurate measures and a definitive diagnosis of harmful adiposity, as well as functional assessments; such assessments encounter health system constraints of accessibility and affordability [64].”
From Advantages and Limitations of the Body Mass Index (BMI) to Assess Adult Obesity (2024) · cites this paper as [64]
The Introduction (page unavailable) says conventional four-component body-composition assessment is costly and time-consuming and therefore seldom used in clinics, supporting an affordability and accessibility constraint for that method. The paper does not establish the same constraint for functional assessments or definitive diagnosis of harmful adiposity more generally. (LLM, conf=0.82)
Experimental — accuracy not yet measured
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- Authors
- Ng, B. K., Liu, Y. E., Wang, W., Kelly, T. L., Wilson, K. E., Schoeller, D. A., Heymsfield, S. B., & Shepherd, J. A.
- Affiliations
- University of California, San Francisco (US)
- University of Hawaii Cancer Center (US)
- Hologic (United States) (US)
- University of Wisconsin–Madison (US)
- Pennington Biomedical Research Center (US)
- Corresponding author
- Shepherd, John A
- Venue
- The American Journal of Clinical Nutrition
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 108
- Issue
- 4
- Pages
- 708-715
- ISSN
- 0002-9165 (ISSN-L)
- PMC
- PMC7263310
- OpenAlex
- W2885594499
- Cited by
- 73
- References
- 18
- Citations by year
- 2026: 7 · 2025: 7 · 2024: 14 · 2023: 15 · 2022: 12 · 2021: 5 · 2020: 6 · 2019: 5 · 2018: 2
- FWCI
- 3.09
- Type
- journal article
- Language
- en
- Update notices
- erratum (2018-12-01)
- Open access
- hybrid
- doi.org
- Licence
- Locations
- American Journal of Clinical Nutrition (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Hologic Investigator-Initiated Study (P0515173)
- NIH
- Topics
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Health Sciences › Medicine › Orthopedics and Sports Medicine › Bone health and osteoporosis research
- Health Sciences › Medicine › Emergency Medicine › HIV-related health complications and treatments
- Keywords
- body composition assessment, dual-energy X-ray absorptiometry, bioelectrical impedance analysis, air displacement plethysmography, deuterium dilution, total body water, fat mass, protein mass, method validation, healthy adults
- MeSH terms
- Adipose Tissue, Adult, Body Composition, Body Water, Cross-Sectional Studies, Female, Humans, Indicator Dilution Techniques, Male, Middle Aged, Minerals, Nutritional Status, Plethysmography, Proteins, Reproducibility of Results, Absorptiometry, Photon, Linear Models, Electric Impedance, Young Adult
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