High-sensitivity C-reactive protein to detect metabolic syndrome in a centrally obese population: a cross-sectional analysis

Background: People with central obesity have an increased risk for developing the metabolic syndrome, type 2 diabetes and cardiovascular disease. However, a substantial part of obese individuals have no other cardiovascular risk factors, besides their obesity. High sensitivity C-reactive protein (hs-CRP), a marker of systemic inflammation and a predictor of type 2 diabetes and cardiovascular disease, is associated with the metabolic syndrome and its separate components. We evaluated the use of hs-CRP to discriminate between centrally obese people with and without the metabolic syndrome. Methods: 1165 people with central obesity but without any previous diagnosis of hypertension, dyslipidemia, diabetes or cardiovascular disease, aged 20-70 years, underwent a physical examination and laboratory assays to determine the presence of the metabolic syndrome (NCEP ATP III criteria). Multivariable linear regression analyses were performed to assess which metabolic syndrome components were independently associated with hs-CRP. A ROC curve was drawn and the area under the curve was calculated to evaluate whether hs-CRP was capable to predict the presence of the metabolic syndrome. Results: Median hs-CRP levels were significantly higher in individuals with central obesity with the metabolic syndrome (n = 417; 35.8%) compared to individuals with central obesity without the metabolic syndrome (2.2 mg/L (IQR 1.2-4.0) versus 1.7 mg/L (IQR 1.0-3.4); p < 0.001). Median hs-CRP levels increased with an increasing number of metabolic syndrome components present. In multivariable linear regression analyses, waist circumference and triglycerides were the only components that were independently associated with hs-CRP after adjusting for smoking, gender, alcohol consumption and the other metabolic syndrome components. The area under the ROC curve was 0.57 (95%-CI 0.53-0.60). Conclusions: Hs-CRP has limited capacity to predict the presence of the metabolic syndrome in a population with central obesity.