Investigation of relationship of visceral body fat and inflammatory markers with metabolic syndrome and its components among apparently healthy individuals

Autor: Yasemin, Turker, Davut, Baltaci, Yasin, Turker, Serkan, Ozturk, Cemil Isik, Sonmez, Mehmet Harun, Deler, Yunus Cem, Sariguzel, Feyza, Sariguzel, Handan, Ankarali
Rok vydání: 2015
Předmět:
Zdroj: International journal of clinical and experimental medicine. 8(8)
ISSN: 1940-5901
Popis: Metabolic syndrome is a cluster of disorders and great risk for cardiovascular diseases. We aimed to investigate association between severity of metabolic syndrome (MetS) and anthropometric measurements, and to evaluate correlation of MetS and its components with metabolic deterioration and inflammatory indexes. The cross-sectional study enrolled 1474 patients with obesity and overweight. The patients were grouped as MetS and Non-MetS, and were sub-grouped as group 1 (three criteria), 2 (four criteria) and 3 (≥ five criteria) according to NCEP ATP III. Mean age was 38.7 ± 11.9 years and BMI was 35.1 ± 6.3 kg/m(2). Lipid profile, anthropometric and blood pressure measurements, liver function tests, bioelectric impedance body fat compositions, insulin resistance and HbA1c, and spot urinary albumin-creatinine ratio were significantly different between groups of MetS and Non-MetS. Age, lipid profile, bioelectric impedance fat analyses, BMI, blood pressure values, glucose, insulin resistance, uric acid and hs-CRP levels were significantly different between groups of MetS component groups. ROC analysis revealed that hs-CRP was found to be more predictive for severity of metabolic syndrome components 3 and 4 (P=0.030); uric acid and visceral fat were more actual to predict severity of metabolic syndrome between 3 and 5 MetS components, (P=0.006) and uric acid was detected as more actual to predict severity of MetS between 4 and 5 components (P=0.023). In conclusion, uric acid, hs-CRP and visceral body fat composition were useful to predict to severity of MetS in primary care.
Databáze: OpenAIRE