Abstract:
Background: The plasticity of human body in terms of surface area and composition is a challenge for health care units to address obesity. What they need is a cost-effective, easy to use tool to manage the daily clinical settings. For that reason, Dahlmann created a model that refers to a reference population. Based on several regression equations including the parameters height, weight and hand circumference, the model offered for the first time the possibility to develop weight-height-frame tables (1) and to calculate a reference weight (RefWt) for each individual regardless of age. The waist circumference (WC) was integrated into the model as a proxy for central obesity. Processed by a network of algorithms, it was now possible to distinguish the difference between the actual weight (ActWt) and the reference weight (RefWt) into fat mass (FM, kg) and muscle mass (SMM, kg). Fat mass derived by the DBA revealed a strong agreement with BIA measurements (2).
Methods: A data set of 61 severely obese women were analysed. All subjects had a BMI >30 kg/m². Anthropometric data are statistically compared with systolic blood pressure (SBP) and the MetS risk factors triglyceride (TG), HDL cholesterol (HDL-C), fasting plasma glucose (FPG) and the parameters C-reactive protein (CRP) and low-density lipoprotein (LDL-C) using receiver operating curves (ROC) based on sensitivity and specificity, area under curve (AUC), correlation coefficients and regression analysis.
Results: The average %FM was about 50%, meaning that 44% of subjects suffered from MetS. Associations between body fat mass and the systolic blood pressure and seven metabolic risk factors showed a significantly rising linear relationship for the parameters Insulin, HOMA-IR, HDL-C and CRP.
Conclusions: To our knowledge, it is the first time that inflammatory parameters are associated in a linear manner with increasing amounts of fat mass supporting the suspicion that obesity is toxic.