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Dual-energy X-ray absorptiometry and body composition
1Department of Surgery, University of Auckland, New Zealand. l.planck@auckland.ac.nz
Current Opinion in Clinical Nutrition and Metabolic Care
|April 6, 2005
Summary
Dual-energy X-ray absorptiometry (DXA) shows variations between manufacturers and with older models, impacting body composition accuracy. Researchers must acknowledge these DXA limitations for reliable individual and multicenter study results.
Area of Science:
- Biomedical Engineering
- Human Physiology
- Medical Imaging
Background:
- Dual-energy X-ray absorptiometry (DXA) is a common method for assessing body composition, including fat, fat-free soft tissue, and bone mineral.
- Despite its widespread use, DXA technology has known limitations, particularly concerning inter-manufacturer and intra-manufacturer variability.
- Concerns regarding the validity and consistency of DXA measurements necessitate ongoing review and validation.
Purpose of the Study:
- To review recent literature on inter- and intra-manufacturer differences in DXA body composition measurements.
- To critically evaluate the validity of DXA measurements against established criterion methods.
- To highlight the implications of DXA limitations for researchers and clinical practice.
Main Methods:
- Systematic review of recent scientific literature.
- Analysis of studies comparing DXA machines from different manufacturers and generations.
- Evaluation of DXA validity against four-component models and other reference methods.
Main Results:
- Significant differences in body composition measurements exist between newer DXA machines and across manufacturers.
- These discrepancies can be unacceptable for multicenter studies and when upgrading equipment.
- DXA shows notable deviations from four-component models, with wide limits of agreement concerning for individual-level interpretation.
Conclusions:
- Investigators must recognize DXA technology's limitations when interpreting body composition data.
- Continued inter-machine comparisons and validation studies are crucial, especially with new software or hardware.
- DXA remains valuable for tracking compositional changes in longitudinal studies, but cross-calibration may be needed for cross-sectional research.