A longitudinal cohort based association study between uric acid level and metabolic syndrome in Chinese Han urban male population
- Equal contributors
1 Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, PO Box 100, Jinan, 250012, China
2 Health Management Center, Shandong Provincial QianFoShan Hospital, Jinan, 250014, China
3 Center for Health Management, Provincial Hospital affiliated to Shandong University, Jinan, China
4 Department of Epidemiology and Biostatistics, Drexel University School of Public Health, Philadelphia, PA, USA
5 Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, CA, 95616, USA
BMC Public Health 2012, 12:419 doi:10.1186/1471-2458-12-419Published: 8 June 2012
It has been recently demonstrated that serum uric acid (UA) is associated with metabolic syndrome (MetS) or its related clinical indications based on cross-sectional or prospective cohort studies. Nonetheless, due to the fact that UA level constantly fluctuates from time to time even for the person, using a single measure of UA level at baseline of those studies may not be sufficient for estimating the UA-Mets association.
To further estimate this time-dependent association, we fitted a generalized estimating equation (GEE) regression model with data from a large-scale 6-year longitudinal study, which included 2222 participants aged > =25 years with an average of 3.5 repeated measures of UA per person in the Health Management Center of Shandong Provincial Hospital, Shandong, China.
After adjusting for other potential confounding factors (i.e., total cholesterol, low-density lipoprotein), it was verified that time-dependent UA level was an independent risk factor for MetS (OR = 1.6920, p < 0.0001). It was found that UA level was positively associated with obesity, hypertension, and dyslipidemia, but was inversely associated with hyperglycemia.
Serum UA level may serve as an important risk factor of MetS. Additionally, our study suggested that UA level be an independent risk factor to obesity, hypertension and dyslipidemia, but a protective factor to hyperglycemia. These findings are concordant with results from other studies on Asian populations, and jointly provide a basis to further develop a risk assessment model for predicting MetS using UA levels and other factors in China.