The study aimed to investigate the correlations between some anthropometric and lipid profile parameters, as well the glycated hemoglobin (HbA1c) values of Bulgarian females with type 2 Diabetes mellitus (T2DM). 212 women of Bulgarian ethnicity with T2DM of the age groups 40-60 and 61-80 years were included in the research. The anthropometric parameters: waist and hip circumferences were measured, and body mass index (BMI) and waist/hip ratio (WHR) were calculated. We also studied the lipid profile parameters: total cholesterol, triglycerides, high density lipoprotein (HDL), low density lipoprotein (LDL) and very low density lipoprotein (VLDL). A comparative study of the lipid profile criteria revealed significant differences in the levels of triglycerides, HDL-cholesterol and VLDL between the two age groups. Differences were found with regard to the values of glycated hemoglobin too. Correlations between the above anthropometric parameters and the lipid profile of patients with T2DM were examined. In patients of the age group 40-60 years a moderate strength correlation in opposite direction (negative or inverse correlation) was found between HbA1c and BMI p<0.05). In the age group 61-80 years a low strength negative correlation was found between BMI and total cholesterol, as well as between BMI and LDL.

The purpose of the study was to examine certain limb and body circumferences in Bulgarians with type 1 Diabetes Mellitus and to compare them with healthy subjects. The study included 120 patients aged 20-40 years and 80 healthy Bulgarians at the same age. Measured circumferences: neck, arm, forearm, waist, hip, thigh, and calf. Calculated indices: Waist-to-hip ratio (WHR), Waist-to-thigh ratio (WTR). The circumferences of neck, arm, forearm, hip, thigh, and calf in the healthy men were significantly greater than in male patients. The circumferences of neck, arm, forearm waist and calf in the female patients were significantly greater than in the healthy controls. The value of WHR was significantly greater in the patients of both sexes than in healthy people. Reduction of subcutaneous, but not of visceral adipose tissue in the male patients was detected. The amount of both subcutaneous and visceral adipose tissue was greater in female patients than in healthy women.

The aim of the present study was to provide information about the type of face in young Bulgarian adults. The three-dimensional coordinates of several soft-tissue landmarks on the face were obtained using hand-held laser scanner in 95 healthy individuals (46 males and 49 females) of Bulgarian origin aged 21-30 years. From the landmarks bizygomatic breadth and morphological face height were calculated and averaged for sex. The face was classified into five different types based on the values of facial index, according to the categories of Garson. For morphological facial index most of the males fell in the categories mesoprosop -30.43 % and leptoprosop -26.09 % and females in the category leptoprosop -38.78%. Equal percentages of the females fell in the categories mesoprosop and hyperleptoprosop -26.53%. The data obtained in the present study can be used in aesthetic and maxillofacial surgery, forensic anthropology.

This study is focused on an innovative approach to the numerical assessment of gluteal tuberosity through 3D visualization and its use as sex discriminant. The study was based on an aggregate of 40 right femora, male and female in equal proportion. The surface of tuberositas glutea femoris is captured in a 3D image, using a Hand-held Laser Scanner (FastSCAN). Afterwards, the assessment contains two ways. Firstly, the result is a 3D shape comprising two tetrahedrons with common base. Therefore, the volume of the roughness is approximately equal to the total of the volumes of these two tetrahedrons (volume). Secondly, several points (markers) are placed on the surface of the roughness of the 3D image. After that we create two-dimensional shape which is a function of the three-dimensional one. The area of the formed shape is measured (area) as well as its greatest elevation (elevation). The results were processed with SPSS 17.0 using Discriminant Function Analysis. If the predictors (volume, area and elevation) are included in the model, the percentage of cases classified correctly is 92.5%. This score coincides with world results based on various anthropometric indices of the femur.