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Updated: Mar 16, 2026

Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
Published on: September 27, 2024
Characteristics of Metabolic Syndrome in Morbidly Obese Subjects
Sasa Dusanov1, Eli Heggen1, Serena Tonstad1
1Section for Preventive Cardiology, Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital , Oslo, Norway .
Background:
Metabolic syndrome (MetSyn) magnifies risks of cardiovascular disease (CVD) and type 2 diabetes, but its expression varies within the obese population. We examined body mass index (BMI), metabolic traits, and fat distribution in morbidly obese individuals.
Methods:
Lipids and inflammatory, oxidative stress and hepatic biomarkers in 346 women and 203 men (BMI ≥35 kg/m2 and co-morbidity or ≥40 kg/m2) were stratified by MetSyn components (1-5, excluding diabetes). Age- and smoking-adjusted partial correlations were calculated. Dual-energy X-ray absorptiometry was measured in 206 participants.
Results:
Apolipoprotein B, ferritin, uric acid, and alanine aminotransferase (ALT) concentrations worsened with increasing MetSyn components (P ≤ 0.0001), while BMI and LDL-cholesterol showed no association. BMI correlated inversely with triglycerides (r = -0.16, P = 0.03) and positively with HDL-cholesterol in men (r = 0.16, P = 0.02), but not in women. BMI correlated with C-reactive protein (CRP) (r = 0.32, P < 0.0001; r = 0.24, P < 0.0001 in men and women, respectively) and white blood cell count (r = 0.24, P = 0.001 in men; r = 0.15, P = 0.008 in women). Truncal fat percentage correlated to CRP (r = 0.31, P = 0.03; r = 0.20, P = 0.02 in men and women, respectively). In women, number of MetSyn components was inversely related to truncal and peripheral fat (r = -0.20, P = 0.02; r = -0.42, P < 0.0001, respectively) as was ALT (r = -0.21, P = 0.009; r = -0.38, P < 0.0001, respectively) and triglycerides with peripheral fat (r = -0.38, P < 0.0001), while HDL cholesterol was positively associated with truncal and peripheral fat (r = 0.26; P = 0.001).
Conclusions:
BMI and fat distribution showed expected associations to inflammation biomarkers, but paradoxical relations between fat indices, and MetSyn components and biomarkers were seen. This suggests a need for better markers of CVD risk in morbid obesity.
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