Purpose: The relationship between serum uric acid (SUA) and Chinese characteristic 10-year atherosclerotic cardiovascular disease (ASCVD) risk score has not been well evaluated in Chinese populations. Aims of this cross-sectional study were to describe the correlation between SUA level and clustering of prevalent cardiovascular risk factors (CRFs) including overweight, central obesity, hypertension, diabetes and dyslipidemia, as well as the Chinese 10-year ASCVD risk score in adults from Jiangsu Province located in Eastern China.
Patients and Methods: A total of 7700 adults from 12 cities in Jiangsu Province were selected through multi-stage stratified cluster random sampling method in 2015. Face-to-face interviews, physical examinations and laboratory examinations were carried out to collect the information of the participants. Multivariate logistic analysis was used to analyze the relationship between SUA quartiles and various CVD risk factors. The nonlinear analysis was conducted to evaluate the relationship between SUA levels and the China-PAR 10-year ASCVD risk scores.
Results: The prevalence of hyperuricemia was 13.3% in all of the participants. By adjusting potential confounders, significant correlations were found between the SUA level and the overweight, central obesity, hypertension and dyslipidemia in both males and females. The clustering of CRFs was different across SUA quantiles (χ ²=607.685, P < 0.001). After Gamma trend test (P < 0.001) and ordered logistic regression analysis, it was found out that with the increase of SUA quantiles, prevalent CRFs gradually gathered in both males and females. Furthermore, sex-specific difference was identified between SUA and 10-year ASCVD risk scores.
Conclusion: The accumulation of CRFs increased with elevated SUA levels, whereas it was different between genders in the relationship between SUA and 10-year ASCVD risk scores. Tailored strategies should be taken when it came to males and females in managing SUA.
Keywords: serum uric acid, cardiovascular risk factors, clustering, China-PAR risk score