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Serum uric acid and appropriate cutoff value for prediction of metabolic syndrome among Chinese adults

The relation between serum uric acid and metabolic syndrome is observed not only with frank hyperuricemia but also with serum uric acid levels within the normal range. The current “normal” range set for hyperuricemia often fails to identify patients with potential metabolic disorders. We investigate...

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Detalles Bibliográficos
Autores principales: Zhang, Mei-lin, Gao, Yu-xia, Wang, Xuan, Chang, Hong, Huang, Guo-wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: the Society for Free Radical Research Japan 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3541417/
https://www.ncbi.nlm.nih.gov/pubmed/23341696
http://dx.doi.org/10.3164/jcbn.12-65
Descripción
Sumario:The relation between serum uric acid and metabolic syndrome is observed not only with frank hyperuricemia but also with serum uric acid levels within the normal range. The current “normal” range set for hyperuricemia often fails to identify patients with potential metabolic disorders. We investigate the association between serum uric acid within the normal range and incident metabolic syndrome risk, and further to determine the optimal cut-off value of serum uric acid for the diagnosis or prediction of metabolic syndrome. A total of 7399 Chinese adults (2957 men and 4442 women; ≥20 years) free of metabolic syndrome were followed for 3 years. During the 3-year follow-up, 1190 normouricemic individuals developed metabolic syndrome (16.1%). After adjusting the associated variables, the top quartile of serum uric acid levels was associated with higher metabolic syndrome development compared with the bottom quartile in men (hazard ratio (HR), 1.29; p<0.05) and women (HR, 1.62; p<0.05). ROC curve analysis indicated that the optimal cut-off values for serum uric acid to identify metabolic syndrome were 6.3 mg/dl in men and 4.9 mg/dl in women. Our results suggested that high baseline serum uric acid levels within the normal range predict future development of metabolic syndrome after 3 y of follow-up.