Abstract

The optical device LIPOMETER allows for non-invasive, quick, precise and safe determination of subcutaneous fat distribution, so-called subcutaneous adipose tissue topography (SAT-Top).

Previously we showed how the high-dimensional SAT-Top information of women with type-2 diabetes mellitus (NIDDM) and a healthy control group can be analysed and represented in low-dimensional plots by applying special artificial neural networks (ANNs). Three top-down sorted subcutaneous adipose tissue compartments were determined (upper trunk, lower trunk, legs). NIDDM women provided significantly higher upper trunk obesity and significantly lower leg obesity ('apple' type), as compared with their healthy control group.

Now we apply these ANN results on SAT-Top measurements of young and healthy women, comparing their individual subcutaneous fat pattern to the body fat distribution of NIDDM women and to the „normal fat development" of healthy women. Some of these young and healthy women provide a subcutaneous fat distribution very similar to the SAT-Top results of NIDDM women, which might increase their risk for this disease later in life.

© 2001 OSA/SPIE