• Medicina · Feb 2022

    Which Clusters of Metabolic Syndrome Are the Most Associated with Serum Uric Acid?

    • Jurgita Mikolaitytė, Jolita Badarienė, Roma Puronaitė, Alma Čypienė, Irma Rutkauskienė, Jolanta Dadonienė, and Aleksandras Laucevičius.
    • State Research Institute Centre for Innovative Medicine, LT-08406 Vilnius, Lithuania.
    • Medicina (Kaunas). 2022 Feb 16; 58 (2).

    AbstractBackground and Objectives: Metabolic syndrome is defined as three or more of five components; therefore, there are 16 possible different clusters of metabolic risk factors that are under one diagnosis of metabolic syndrome. In this study, we evaluated the different clusters of metabolic syndrome (MetS) across serum uric acid (SUA) quartiles and analyzed the association of these clusters with SUA levels, respectively, in both men and women. Materials and Methods: A total of 606 subjects were recruited to a cross-sectional study from the ongoing Lithuanian High Cardiovascular Risk primary prevention program (LitHiR). All of the study subjects were diagnosed with MetS (according to the 2005 National Cholesterol Education Program Adult Treatment Panel III MetS definition). Results: In the middle-aged population of patients with MetS living in Lithuania, a high proportion of hyperuricaemia was detected-35.5% (95% Cl 31.7% to 39.4%). For women possessing all five MetS components, the chances of having hyperuricaemia are 2.807 higher than for women with three risk factors (p < 0.001). However, men do not have a statistically significantly higher chance of having hyperuricaemia, depending on the number of MetS components in our population. Using multivariable models, the statistically significant chance of having hyperuricaemia was observed only in women possessing all five MetS components (OR = 2.386, p < 0.0001), compared to any other of 15 MetS clusters. After adjustment for age and sex, the chance of having hyperuricaemia for individuals with the cluster of all five MetS components, compared to any other of 15 MetS clusters, remained (OR = 1.982, p = 0.001). Also, a lower probability (OR = 0.653, p = 0.039) of having hyperuricaemia was observed for individuals having the combination of abnormal plasma glucose, blood pressure, and waist circumference. Conclusions: Patients with the clustering of all five metabolic syndrome components are at higher risk for having hyperuricaemia than patients with any other combination of MetS clusters. This risk is even higher for women. It could be beneficial for patients presented with all five MetS components to be screened for SUA concentration in the primary CVD prevention program.

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