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Body composition by DXA

Published on Nov 1, 2017in Bone4.36
· DOI :10.1016/j.bone.2017.06.010
John A. Shepherd49
Estimated H-index: 49
(UCSF: University of California, San Francisco),
Bennett K. Ng6
Estimated H-index: 6
(UCSF: University of California, San Francisco)
+ 1 AuthorsSteven B. Heymsfield111
Estimated H-index: 111
(UCSF: University of California, San Francisco)
Sources
Abstract
Abstract Body composition measurements from DXA have been available since DXA technology was developed 30 years ago, but are historically underutilized. Recently, there have been rapid developments in body composition assessment including the analysis and publication of representative data for the US, official usage guidance from the International Society for Clinical Densitometry, and development of regional body composition measures with clinical utility. DXA body composition is much more than whole body percent fat. In this paper celebrating 30 years of DXA for body composition, we will review the principles of DXA soft tissue analysis, practical clinical and research applications, and what to look for in the future.
  • References (39)
  • Citations (23)
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References39
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#1John A. Shepherd (University of California, Berkeley)H-Index: 49
#2Bennett K. Ng (University of California, Berkeley)H-Index: 6
Last. Timothy F. Cootes (University of Manchester)H-Index: 64
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There is growing evidence that body shape and regional body composition are strong indicators of metabolic health. The purpose of this study was to develop statistical models that accurately describe holistic body shape, thickness, and leanness. We hypothesized that there are unique body shape features that are predictive of mortality beyond standard clinical measures. We developed algorithms to process whole-body dual-energy X-ray absorptiometry (DXA) scans into body thickness and leanness imag...
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#1Benjamin Hinton (UCSF: University of California, San Francisco)H-Index: 2
#2Bo Fan (UCSF: University of California, San Francisco)H-Index: 29
Last. John A. Shepherd (UCSF: University of California, San Francisco)H-Index: 49
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Body Mass Index has traditionally been used as a measure of health, but Fat Mass Index (FMI) and Lean Mass Index (LMI) have been shown to be more predictive of mortality and health risk. Total body FMI and LMI reference curves have particularly been useful in quantifying sarcopenia and sarcopenic obesity. Research has shown regional composition has significant associations to health outcomes. We derived FMI and LMI reference curves of the regions of the body (leg, arm, and trunk) for 15,908 indi...
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#1John A. Shepherd (UCSF: University of California, San Francisco)H-Index: 49
#2Markus J. Sommer (UCSF: University of California, San Francisco)H-Index: 4
Last. George K. Siberry (NIH: National Institutes of Health)H-Index: 22
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Objective To evaluate a novel technique designed to reduce the negative impact of motion artifacts in infant dual-energy X-ray absorptiometry (DXA) scans. Study design Using cross-sectional data from a large multicenter study, we developed and tested advanced methods for infant scan analysis. Newborns (n = 750) received spine and whole-body DXA scans with up to 3 attempts to acquire a motion free scan. Precision of infant DXA was estimated from visits with multiple valid scans. Accuracy of regio...
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There are four body composition phenotypes widely used to describe older adults: normal, sarcopenic, obese, and sarcopenic obese. In this paper, we will discuss how DXA can be used to quantify body composition and how DXA can identify patients with sarcopenia and sarcopenic obesity.
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