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1.
Metabolism ; 58(11): 1663-8, 2009 Nov.
Article in English | MEDLINE | ID: mdl-19632696

ABSTRACT

Repeated dual-energy x-ray absorptiometry (DEXA) measurements are often performed both in clinical work and in research studies. The aims of the present study were to investigate the repeatability of DEXA total body measurements, to clarify the effect of the scanning positioning of the subject, and to compare the reliability of DEXA measurements of the extremities between automatically and manually defined regions of interest (ROIs). Three DEXA measurements of the total body composition, that is, fat tissue mass, lean tissue mass (LM), and bone mineral content, were performed on 30 male volunteers (mean age, 45.2 years) in addition to measurements of bone mineral density. Using a narrow fan-beam Lunar Prodigy densitometer (GE Lunar, Madison, WI), 3 DEXA scans (2 supine and 1 prone) of the total body were performed. For regional measurements of the right arm and leg, ROIs were set automatically and manually in the supine-supine and supine-prone positions. Repeatability of total body DEXA measurements was excellent for bone mineral content (r = 0.99), LM (r = 0.99), fat tissue mass (r = 1.00), and bone mineral density (r = 0.98) in supine scanning. Change of position from supine to prone slightly decreased the reproducibility of total body measurements. Reproducibility of regional measurements was inferior to total body results; especially in the upper extremity, the repeated automatic LM measurements in supine-supine positions produced r values as low as 0.74 but increased to 0.93 after manual adjustment of the ROIs. To obtain maximal reliability of the composition measurements, we recommend manual checking of machine-made ROIs and, if needed, manual adjustment to avoid measurement errors.


Subject(s)
Absorptiometry, Photon/methods , Body Composition/physiology , Adipose Tissue/physiology , Adult , Body Weight/physiology , Bone Density , Humans , Male , Middle Aged , Prone Position , Reproducibility of Results , Supine Position , Young Adult
2.
Med Sci Sports Exerc ; 39(12): 2242-7, 2007 Dec.
Article in English | MEDLINE | ID: mdl-18046197

ABSTRACT

PURPOSE: The aim of the study was to determine the body composition of healthy young men and to investigate whether there exists an association between body composition and physical fitness. MATERIALS AND METHODS: A prospective cohort study of 140 healthy male conscripts (mean age 19.8yr, SD 1.0 yr) was conducted. We examined subject characteristics, aerobic performance, and muscle strength, and we assessed body composition using dual-energy x-ray absorptiometry (DEXA). The association between total body composition and lower-limb composition and physical performance was investigated by linear regression. RESULTS: The mean body mass index (BMI) of the subjects was 24.6 kg.m (SD 4.7). Their mean bone mineral density (BMD) was 1.3 g.cm (SD 0.1), fat percentage (fat%) 22.6 (SD 9.7), lean mass 57.6 kg (SD 7.0), and bone mass 3.2 kg (SD 0.4) at the beginning of the military service. Fat percentage was significantly associated with 12-min running performance (P < 0.001), and a significant relationship was found between muscle strength and fat% (P< 0.001), and increasing BMD (P < 0.001), in multivariate analysis. Lean mass was not associated with physical performance. CONCLUSIONS: DEXA measurement of the proportion of body fat is a useful tool to indirectly assess running performance and muscle strength in Finnish male conscripts. Increased fat mass and fat percentage were strong predictors of poorer physical fitness. Moreover, the relationship between muscle strength and BMD was confirmed. However, muscle mass did not predict muscle strength in our sample.


Subject(s)
Absorptiometry, Photon , Body Composition , Military Personnel/statistics & numerical data , Physical Fitness/physiology , Adolescent , Adult , Athletic Performance/statistics & numerical data , Exercise Test/statistics & numerical data , Humans , Male , Prospective Studies , Running/physiology , Running/statistics & numerical data
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