A new anthropometric model for body composition estimation in the assessment of metabolic risk factors of obese women

Abstract

Abstract Background Excessive body fat is associated with disorders defined as Metabolic Syndrome (MetS). The study sets out to uncover the underlying mechanisms of MetS pathogenesis comparing metabolic and inflammatory variables with increasing amounts of fat mass (FM). Aiming to solve this issue, the study refers to an anthropometric model named Dahlmann-Body-Analysis (DBA) to define the percentage of fat mass (%FM). Methods A data set of 61 severely obese women were analysed. All subjects had a BMI > 30 kg/m². Body weight (W), body height (Ht), hand circumference (HdC) and the circumference of the abdomen (AC) were measured and processed by the DBA model. The result is the percentage of fat mass (%FM), which is compared to data, produced by a bioelectrical impedance analysis (BIA) device. 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. The overall pattern of correlation coefficients revealed that none of the adiposity indices like BMI, AC, AC/Ht and %FM (BIA or DBA) is of crucial advantage to detect metabolic risk factors. AUC values of the different obesity indices detecting MetS reached values between 0.63 and 0.75 representing a low discrimination power in the diagnose of MetS. Associations between body fat mass measured by the DBA system (%FM-DBA) 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. The corresponding correlation coefficients are r > 0.30. The parameters Glucose, TG, LDL-C and SBP had correlation coefficients r < 0.12. Conclusions To our knowledge, it is the first time that biochemical parameters and blood pressure are associated with increasing amounts of fat mass in human adults. The waist circumference (WC) as part of the MetS definition should be replaced by direct or indirect measurements of body fat estimation to give reliable information on individuals.