Objective: To evaluate the associations between serum uric acid (SUA) levels and cardiovascular disease (CVDs) risk factors, focusing on potential sex-specific differences.

Design: A retrospective cohort study.

Setting: A large community-based survey was conducted every two years from 2010 to 2018 in Hangzhou, Zhejiang Province, Southeastern China.

Participants: 6119 participants aged 40 years and above who underwent at least three times of physical examinations were enrolled.

Methods: Participants were categorized into four groups (Q1-Q4) based on baseline SUA quartiles within the normal range, with hyperuricemia (HUA) as the fifth group. The Q1 was the reference. By stratifying participants by gender, the relationships between SUA levels and systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood glucose (FBG), and total cholesterol (TC) were investigated using linear regression models in the generalized estimating equation (GEE). Additionally, the associations of elevated SUA levels and HUA with hypertension, hyperglycemia, and dyslipidemia were correspondingly examined using multivariate logistic regression models.

Results: After adjusting for confounding variables, we found positive associations between SUA levels and SBP, DBP, FBG, and TC in women, and with TC in men (P < 0.01). Likewise, Elevated SUA quartiles and HUA were linked to increased dyslipidemia risk in both sexes, and increased hyperglycemia risk only in women, with HRs (95%CI) of 1.64 (1.05-2.55) and 2.37 (1.47-3.81) in the Q4 and HUA group, respectively. Women with HUA had higher hypertension risk (HR=1.45, 95% CI 1.21-1.73), while no such association was observed in men. Stratified analyses revealed significant associations between elevated SUA levels and CVDs risk factors in postmenopausal and non-obese women.

Conclusions: Elevated SUA levels increase the risk of dyslipidemia in both sexes. SUA levels within normal-range and HUA are positively associated with hyperglycemia and hypertension in postmenopausal women, but not in men.

Each participant was required to complete an in-person interview by a trained nurse using a standardized questionnaire, which included information related to demographic characteristics (age and sex) and the medical history (disease and drug history of hypertension, diabetes, dyslipidemia). Values of weight and height were measured using a calibrated scale and a stadiometer. BP was measured using a calibrated mercury sphygmomanometer. Two consecutive measurements were taken and recorded, with a 2-minute break across the two measurements.  The final value was calculated as the average of the two readings. Prior to venous blood sample collection, all participants were required to fast for at least eight hours. Serum creatinine, SUA, FBG, and TC for each participant were measured using standard clinical laboratory methods. The normality of continuous variables’ distribution was assessed using the Shapiro-Wilk tests. Continuous variables with normal distribution are presented as the mean ± standard deviation, and those with non-normal distribution are presented as the median (interquartile range). Categorical variables are expressed as numbers (percentages). The group differences for continuous variables were compared using Analysis of Variance (ANOVA) and the Kruskal-Wallis test. The Chi-square test was used for categorical variables. Linear models of generalized estimating equations (GEE) were used to calculate the hazard ratios of SUA levels on SBP, DBP, FBG, and TC. Multivariate logistic regression models were used to evaluate the risk of hypertension, hyperglycemia, and dyslipidemia for different SUA levels or HUA.