Multicomponent density models for body composition: Review of the dual energy X‐ray absorptiometry volume approach

Summary Accurate and precise body composition estimates, notably of total body adiposity, are a vital component of in vivo physiology and metabolic studies. The reference against which other body composition approaches are usually validated or calibrated is the family of methods referred to as multi...

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Published in:Obesity reviews Vol. 22; no. 8; pp. e13274 - n/a
Main Authors: Heymsfield, Steven B., Smith, Brooke, Wong, Michael, Bennett, Jonathan, Ebbeling, Cara, Wong, Julia M. W., Strauss, Boyd J. G., Shepherd, John
Format: Journal Article
Language:English
Published: England Wiley Subscription Services, Inc 01-08-2021
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Summary:Summary Accurate and precise body composition estimates, notably of total body adiposity, are a vital component of in vivo physiology and metabolic studies. The reference against which other body composition approaches are usually validated or calibrated is the family of methods referred to as multicomponent “body density” models. These models quantify three to six components by combining measurements of body mass, body volume, total body water, and osseous mineral mass. Body mass is measured with calibrated scales, volume with underwater weighing or air‐displacement plethysmography, total body water with isotope dilution, and osseous mineral mass by dual‐energy X‐ray absorptiometry. Body density is then calculated for use in model as body mass/volume. Studies over the past decade introduced a new approach to quantifying body volume that relies on dual‐energy X‐ray absorptiometry measurements, an advance that simplifies multicomponent density model development by eliminating the need for underwater weighing or air‐displacement plethysmography systems when these technologies are unavailable and makes these methods more accessible to research and clinical programs. This review critically examines these new dual‐energy X‐ray approaches for quantifying body volume and density, explores their shortcomings, suggests alternative derivation approaches, and introduces ideas for potential future research studies.
Bibliography:Funding information
Names for PubMed Indexing: Ebbeling, Heymsfield, Shepherd, Smith, Strauss, Wong, Wong.
Office of Extramural Research, National Institutes of Health, Grant/Award Numbers: P30DK040561, P30DK072476, R01DK109008
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ISSN:1467-7881
1467-789X
1467-789X
DOI:10.1111/obr.13274