Reliability of dual-energy X-ray absorptiometry (DXA) in assessing body composition in elite athletes

Nana, A 2013, Reliability of dual-energy X-ray absorptiometry (DXA) in assessing body composition in elite athletes, Doctor of Philosophy (PhD), Medical Sciences, RMIT University.

Document type: Thesis
Collection: Theses

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Title Reliability of dual-energy X-ray absorptiometry (DXA) in assessing body composition in elite athletes
Author(s) Nana, A
Year 2013
Abstract Dual energy X-ray absorptiometry (DXA) is rapidly becoming more accessible and popular as a technique to monitor body composition, especially in athletic population as the measurement is rapid and non-intrusive, whilst provides detailed body composition information. Although studies in sedentary populations have investigated the validity of DXA assessment of body composition, the issues of reliability have not been systematically examined, especially in athletic populations. A literature review noted the surprising lack of information on scanning protocols in study reports. As a result of consideration of the various sources of error and variability in the measurement of body composition by DXA, a theoretical model of Best Practice was developed to standardise the conduct and analysis of a DXA scan. Components of this protocol included standardisation of subject presentation (subjects rested, overnight-fasted and in minimal clothing) and positioning on the scanning bed (centrally aligned in a standard position using custom-made positioning aids) as well as manipulation of the automatic segmentation of regional areas of the scan results. The implications of the standardised protocol were that scans can only be undertaken in the morning, limiting the use of the DXA machine and focussing on a small window of opportunity in an athlete’s daily timetable. Therefore it was important to measure the reliability of the protocol and the magnitude of the additional error involved in introducing variations that could make it more practical.

The first study found daily activities and consumption of breakfast generally produced substantial increase in the typical error and mean of DXA estimates of total and regional lean mass, and associated body mass. The second study found exercise and its related practices of fluid and food intake are associated with changes in the mean estimates of total and regional body composition that range from trivial to small but substantial. A practical problem in undertaking whole body composition assessment with DXA in athletes who are taller and/or broader than the active scanning area of the Lunar Prodigy DXA machine was investigated in the third study. Summing of partial DXA scans provides accurate body composition estimates for broad subjects, but other strategies are needed to accommodate tall subjects. The final study investigated the implications of undertaking DXA scans using the Best Practice Protocol or a less precise but more practical protocol in assessing training- and cold water immersion therapy-induced changes in body composition. The standard deviations of change scores for total and lean mass from afternoon scans were approximately double those observed in the morning, and led to a different interpretation of the changes in body composition arising from the exposure to cold water immersion therapy.

In summary, the research demonstrate the importance of undertaking DXA scans according to the Best Practice Protocol, which consisted of meticulous standardised techniques throughout the entire scanning process. Body composition assessment implemented with such protocol ensures high level of precision so that any small changes in body composition are confidently detected and correctly interpreted. It is also envisaged that the Best Practice Protocol will assist future research in the determination of functionally-based smallest worthwhile effects, which are highly warranted information.
Degree Doctor of Philosophy (PhD)
Institution RMIT University
School, Department or Centre Medical Sciences
Keyword(s) DXA
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Created: Mon, 15 Jul 2013, 09:53:13 EST by Brett Fenton
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