Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
Kruschitz, R.
DETECTING BODY FAT – A WEIGHTY PROBLEM BMI versus SUBCUTANEOUSE FAT PATTERNS
Doktoratsstudium der Medizinischen Wissenschaft; Humanmedizin; [ Dissertation ] Medical University of Graz; 2014. pp. 95
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- Autor*innen der Med Uni Graz:
- Betreuer*innen:
- Holasek Sandra Johanna
- Moser Maximilian
- Tafeit Erwin
- Altmetrics:
- Abstract:
- Background Although the body mass index (BMI, kg/m2) is widely used as a surrogate measure of adiposity, it is a measure of excess weight, rather than excess body fat, relative to height. The BMI classification system is derived from cut points obtained from the general adult population and is not specific for subgroups such as athletes and young adults. The use of subcutaneous adipose tissue topography (SAT-Top) seems to be a more effective access for such cases. Objective We aimed to describe the relationship between BMI and the subcutaneous adipose tissue topography within young athletes and non-athletic controls, to comparatively evaluate the diagnostic powers of BMI and subcutaneous adipose tissue thicknesses at different body sites, and to explore appropriate subcutaneous adipose tissue measuring points and cutoffs to discriminate between athletes and non-athletic controls. Methods Measurements were determined in 64 males and 42 females, who were subsequently separated into two even groups (athletes and non-athletes). The optical device Lipometer was applied at standardised body sites to measure the thickness of subcutaneous adipose tissue layers. To calculate the power of the different body sites and the BMI to discriminate between athletes and non-athletes, receiver operating characteristic curve analysis was performed. Results In men, the neck (optimal cutoff value 2.3 mm) and trunk (optimal cutoff value 15.5 mm) provided the strongest discrimination power with 90.6% (58 of 64) of the subjects being correctly classified into athletes or non-athletes. Discrimination power of the BMI values was not significant. In women, the upper back (optimal cutoff value 3.3 mm) and arms (optimal cutoff value 15.9 mm) provided the strongest discrimination power with 88.1% (37 of 42) being correctly classified. When using BMI to discriminate between athletes and non-athletes only 52.4% (22 of 42) were correctly classified. Conclusion These results suggest that compared to BMI levels, subcutaneous fat patterns are a more accurate way of discriminating between athletes and non-athletes. In particular the neck and the trunk compartment in men and the upper back and arms compartment in women, were the best sites discriminate between young athletes and non-athletes on the basis of their fat patterns.