Abstract
Introduction: Obesity is defined as an increase in body fat composition.
Aim: The purpose of our study was to evaluate metabolic risk factors and diseases in different patterns of abdominal fat distribution.
Materials and methods: This is a cross-sectional study. Among patients aged 15 to 65 years who have had no significant weight loss in the past year and were referred to the Radiology Department to perform an abdominal CT-scan, the visceral and subcutaneous fat area (VFA and SFA) with Hounsfield units -30 to -190 (±2 SD) was calculated at the umbilical level. Based on the VFA and SFA, patients were stratified into four groups, group 1: V(+)S(+); group 2: V(+)S(-); group 3: V(−)S(+); group 4: V(−)S(−). The following parameters were assessed in the groups: anthropometric parameters including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), waist to hip ratio (WH); laboratory parameters, including fasting blood glucose (FBG), lipids profile (TG, LDH, LDL, and total cholesterol), creatinine, and liver enzymes (AST, ALT). Additionally, sensitivity, specificity, positive predictive value (PPV), and negative predictive value of study variables were assessed in predicting group 1.
Results: The study included 180 individuals (mean age 50±14 years, range 15-65 years). Group 1 was the most, and group 2 was the least prevalent pattern of abdominal fat distribution. Most females (75%) had high percentage of subcutaneous fat tissue. There was a significant association between the abdominal fat distribution pattern and BMI, WC, WHtR, TG, LDL, HDL, total cholesterol, FBG, diabetes, and metabolic syndrome (p<0.05).
Conclusions: Most of the metabolic factors, including BMI, WC, lipid profile, and FBG, as well as metabolic syndrome, diabetes, and impaired glucose tolerance, were highly correlated with group 1. However, most of the individuals in group 1 were normal according to the factors mentioned above. Therefore, there is a gap between the main definition of obesity (increasing body fat mass) and parameters that calculated obesity and metabolic disorders.