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AB153. The relationship between serum uric acid (SUA) and metabolic syndrome (MetS) in a Chinese male population survey
BACKGROUND: The relationship between serum uric acid (SUA) and metabolic syndrome (MetS) has been reported in some epidemiology studies. Nonetheless, it is still controversial whether SUA is a risk predictor for the prevalence of MetS. The current study was designed to highlight the association of S...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4708528/ http://dx.doi.org/10.3978/j.issn.2223-4683.2014.s153 |
Sumario: | BACKGROUND: The relationship between serum uric acid (SUA) and metabolic syndrome (MetS) has been reported in some epidemiology studies. Nonetheless, it is still controversial whether SUA is a risk predictor for the prevalence of MetS. The current study was designed to highlight the association of SUA and MetS and its components. METHODS: Serum samples from 3,675 healthy male subjects, aged 17-88 years, were collected from the Fangchenggang Area Male Health and Examination Survey (FAMHES) for cross-sectional studies. A representative sample of 2,575 individuals who did not suffer from MetS at baseline was recruited in the cohort study. The association between SUA quartiles and MetS was estimated using multivariable logistic regression. To further evaluate causality, we evolved a cox regression with data from 2- and 4-year large scale longitudinal study. MetS was defined based upon the updated National Cholesterol Education Program Adult Treatment Panel III for Asian American. RESULTS: In the cross-sectional analysis, men with MetS had a higher level of SUA than those without MetS (P<0.001). SUA showed a statistically significant negative correlation with high-density lipoprotein cholesterol and a positive correlation with blood pressure, triglycerides, waist circumference, and BMI (all P<0.001) while no significant relationship with glucose after adjusted for age (P=0.495). The strongest correlation was proven to be between SUA and waist circumference (r=0.318). In the multivariate analysis, increased odds ratios (ORs) for the MetS and its components were observed from the lowest to the highest SUA concentration. After adjustment for BMI, statistically significant difference maintained in MetS [OR =2.077; 95% confidence interval (CI), 1.470-2.936], hypertriglyceridemia (OR =3.048; 95% CI, 2.216-4.192), hyperglycemia (OR =1.363, 95% CI, 1.071-1.734). In longitudinal analysis, examining the risk of developing MetS, SUA levels (hazard ratios comparing fourth quartile to the first quartile of 1.746; 95% CI, 1.265-2.411) were positively associated with incident MetS after adjusted for other confounders. CONCLUSIONS: SUA was independently positively correlated with the prevalence of MetS. SUA may be a risk predictor for MetS. Further studies are needed to figure out the mechanisms behind the relationship. |
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