Modeling elite male athletes' peripheral bone mass, assessed using regional dual x-ray absorptiometry.
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AbstractThere is still considerable debate as to whether bone mineral content (BMC) increases in proportion to the projected bone area, A(p), or an estimate of the skeletal bone volume, (A(p))(3/2), being assessed. The results from this study suggest that the bone mass acquisition of elite athletes' arms and legs increases in proportion to the projected bone area, A(p), having simultaneously controlled/removed the effect of the confounding variables of body mass and body fat. Although this supports the use of the traditional bone mineral density ratio (BMD=BMC/A(p)), it also highlights the dangers of overlooking the effect of known confounding variables. Ignoring the effect of such confounding variables, athletic groups whose activities involve upper body strength (rugby, rock climbing, kayaking, weight lifting) had the highest arm BMD, while runners were observed to have the lowest arm BMD (lower than that of the controls). Similarly, leg BMD was highest in rugby players, whose activities included both running and strength training. However, the rugby players were also observed to have the greatest body mass. When the important determinants of body mass, body fat, as well as projected bone area, A(p), were incorporated as covariates into a proportional allometric ANCOVA model for BMC, different conclusions were obtained. The introduction of these covariates had the effect of reducing the sporting differences on adjusted arm BMC, although the "sport" by "side" interaction still identified racket players as the only group with a greater dominant arm BMC (P < 0.05). In contrast, sporting differences in adjusted leg BMC remained highly significant, but with a rearranged hierarchy. The runners replaced the rugby players as having the greatest adjusted leg BMC. The results confirm the benefits of activity on peripheral bone mass as being site-specific but reinforce the dangers of making generalizations about the relative benefits of different exercises ignoring the effects of known confounding variables, such as body size, body composition, and age.
CitationBone, 32(1): 62-68
PublisherElsevier Science Direct
CollectionsSport, Exercise and Health Research Group
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