Abstract
Objective
To evaluate the associations between serum uric acid (SUA) levels and cardiovascular disease (CVD) 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, outheastern China.
Participants
6119 participants aged 40 years and above who underwent at least three times of physical examinations were enrolled.
Methods
Participants were categorised into four groups (Q1–Q4) based on baseline SUA quartiles within the normal range, with hyperuricaemia (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 generalised estimating equation. Additionally, the associations of elevated SUA levels and HUA with hypertension, hyperglycaemia and dyslipidaemia 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 dyslipidaemia risk in both sexes, and increased hyperglycaemia risk only in women, with HRs (95% CI) of 1.64 (1.05 to 2.55) and 2.37 (1.47 to 3.81) in the Q4 and HUA group, respectively. Women with HUA had higher hypertension risk (HR=1.45, 95% CI 1.21 to 1.73), while no such association was observed in men. Stratified analyses revealed significant associations between elevated SUA levels and CVD risk factors in postmenopausal and non-obese women.
Conclusions
Elevated SUA levels increase the risk of dyslipidaemia in both sexes. SUA levels within normal range and HUA are positively associated with hyperglycaemia and hypertension in postmenopausal women, but not in men.
Keywords: Hypertension; DIABETES & ENDOCRINOLOGY; General diabetes; Lipid disorders; Factor Analysis, Statistical
STRENGTHS AND LIMITATIONS OF THIS STUDY.
The strength of this study was the utilisation of a large-scale dynamic retrospective cohort in the southeastern community of China.
The menopausal status in women was considered when we investigated the effect of elevated serum uric acid on cardiovascular disease risk factors.
Data collected in this retrospective survey did not include sufficient information on possible confounding factors, such as alcoholic consumption, physical activity and dietary habits.
Introduction
Cardiovascular diseases (CVDs) have a high incidence and disability rate that have worsened the quality of life for middle-aged and elderly individuals.1 Given the increasing disease burden of CVDs,2 early monitoring and intervention for the CVD-associated risk factors are imperative in preventing the onset of CVDs.
Uric acid is the end-product of purine metabolism. Hyperuricaemia (HUA) caused by high levels of uric acids increases the risk of developing gout.3 Numerous epidemiological studies have suggested strong associations between serum uric acid (SUA) and CVD risk factors,4–7 including hypertension, obesity, diabetes and dyslipidaemia.8–11 In animal-based studies, elevated SUA levels have been found to affect cardiovascular and metabolic functions via multiple pathways, such as oxidative stress and endothelial dysfunction, and insulin resistance.6 12–15 However, ambiguity remains regarding the associations between SUA and CVD risk factors. First, conflicting results from previous studies have made it unclear whether SUA levels were associated with systolic blood pressure (SBP), diastolic blood pressure (DBP) or both.16–21 Second, gender disparities were reported in the relationship between SUA and fasting blood glucose (FBG), with some studies suggesting a stronger association between SUA and FBG in women than in men,22–24 while other studies found no correlation between SUA and diabetes in men.25 26 Third, the investigation into the relationship between SUA within normal range and blood lipids has been relatively limited, most of them focused on studying the association between disease outcomes (HUA or gout) and dyslipidaemia. Therefore, it is necessary to explore the connections between elevated SUA within the normal range and dyslipidaemia. Examining the potential associations can enhance our understanding of the pathophysiology underlying dyslipidaemia.27–29
In this study, using a retrospective cohort study conducted in southeastern China, we aimed to investigate the associations of SUA levels and HUA with blood pressure (BP), hyperglycaemia and dyslipidaemia in adults over 40 years old.
Methods
Study design
A dynamic retrospective cohort study was conducted, based on the ‘Public Basic Health Services Project’ of China, which aims to understand the health status of residents, monitor and manage patients with chronic disease, and improve overall health awareness and disease prevention. In this national project, participants with local household registration and who live in the community for more than 6 months were eligible for a free health check-up every 2 years. The primary study participants included 12 498 adults aged 40 years or older who finished physical examinations in the Zhanongkou community health service centre, Hangzhou, Zhejiang Province from May 2010 to December 2018. In this current study, participants who had undergone fewer than three physical examinations (n=2618), and those with incomplete SUA data (n=252), missing BP, FBG and total cholesterol (TC) information (n=384), and having a history of hypertension, hyperglycaemia, or dyslipidaemia at baseline (n=3125) were excluded. Ultimately, a total of 6119 eligible participants (2041 men and 4078 women) were included in this study (figure 1).
Figure 1.
Flow chart of the participant inclusion. BP, blood pressure; FBG, fasting blood glucose; TC, total cholesterol.
Data measurement
Each participant was required to complete an in-person interview by a trained nurse using a standardised questionnaire, which included information related to demographic characteristics (age and sex) and the medical history (disease and drug history of hypertension, diabetes, dyslipidaemia). 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 8 hours. Serum creatinine, SUA, FBG and TC for each participant were measured using standard clinical laboratory methods.
Diagnostic criteria
The primary endpoints in this study included hypertension, hyperglycaemia and dyslipidaemia. Hypertension was defined as either SBP ≥140 mm Hg or DBP ≥90 mm Hg, or having been previously diagnosed with hypertension and currently receiving anti-hypertensive treatment. Hyperglycaemia was defined as FBG ≥7.0 mmol/L or self-reported diabetes. Dyslipidaemia was defined as TC ≥6.22 mmol/L.30 HUA was defined as SUA ≥416 µmol/L (70 mg/L) in men and SUA ≥357 µmol/L (60 mg/L) in women. According to Chinese body mass index (BMI) classification criteria,31 obesity was defined as BMI ≥28 kg/m2.
Patient and public involvement
There was no patient and/or public involvement in the design of this study.
Statistical analysis
The normality of continuous variables’ distribution was assessed using the Shapiro-Wilk tests. Continuous variables with normal distribution are presented as the mean±SD, and with non-normal distribution are presented as the median (IQR). Categorical variables are expressed as numbers (percentages). The group differences for continuous variables were compared using analysis of variance and the Kruskal-Wallis test. The Χ2 test was used for categorical variables. Given the gender differences in SUA levels, all analyses were stratified by gender. SUA levels within the normal range were divided into four groups based on their SUA levels (Q1–Q4). The HUA was grouped as the fifth group. For women, the detailed grouping information was: Q1 (SUA <227 µmol/L), Q2 (227≤SUA<262 µmol/L), Q3 (262≤SUA<300 µmol/L), Q4 (300≤SUA<357 µmol/L) and HUA (SUA ≥357 µmol/L). For men, the detailed grouping information was: Q1 (SUA <284 µmol/L), Q2 (284≤SUA<327 µmol/L), Q3 (327≤SUA<367 µmol/L), Q4 (367≤SUA<416 µmol/L) and HUA (SUA ≥416 µmol/L). The first quartile (Q1) was used as the reference group. Linear models of generalised estimating equations (GEE) were used to calculate the HRs of SUA levels on SBP, DBP, FBG and TC. The model investigating the relationship between SUA levels and SBP/DBP was adjusted for age, BMI, FBG, TC, serum creatinine and estimated glomerular filtration rate (eGFR). Similarly, the model examining the association between SUA levels and FBG was adjusted for age, BMI, SBP, DBP, TC, serum creatinine and eGFR. Additionally, the model exploring the relationship between SUA levels and TC was adjusted for age, BMI, SBP, DBP, FBG, serum creatinine and eGFR. Multivariate logistic regression models were used to evaluate the risk of hypertension, hyperglycaemia and dyslipidaemia for different SUA levels or HUA, adjusting for the same confounding factors as above. Furthermore, stratified analyses were conducted by women’s menopausal status, age and obesity status.
All analyses were performed using SPSS V.26.0 and R software V.4.2.1. We applied the Bonferroni correction method to account for multiple comparisons. Therefore, only two-sided p values of <0.05/3 (0.0167) were considered to be statistically significant.
Results
The baseline characteristics of the study participants by sexes are presented in online supplemental table 1. A total of 6119 participants (2041 men and 4078 women) were included, with an average age of 65.4±9.3 years. The prevalence of HUA was significantly higher in men than in women (20.0% vs 13.4%, respectively, p<0.001). Moreover, men had significantly higher values of age, BMI, SBP, DBP, FBG, creatinine and SUA than women (p<0.001). Conversely, women had significantly higher eGFR and TC levels than men (p<0.001). From May 2010 to December 2018, with a median follow-up time of 6.18 years, 2561 participants were newly diagnosed with hypertension, 605 with hyperglycaemia and 1081 with dyslipidaemia.
bmjopen-2023-073930supp001.pdf (80.7KB, pdf)
The baseline clinical characteristics of participants with different SUA levels are presented in tables 1 and 2. As the SUA levels increased, DBP in women and SBP, FBG, TC and creatinine in both sexes increased, while eGFR decreased in both sexes. Moreover, in both sexes, those with higher SUA levels or HUA were more likely to be older and obese.
Table 1.
Baseline characteristics of the male participants according to different SUA levels
| Characteristics | SUA level | P value | ||||
| Q1 (n=409) | Q2 (n=414) | Q3 (n=401) | Q4 (n=408) | HUA (n=409) | ||
| Age (years) | 67.32±8.52 | 68.90±8.84 | 69.73±8.21 | 70.24±8.83 | 71.22±9.18 | <0.001 |
| Body mass index (%) | <0.001 | |||||
| <18.5 (kg/m2) | 29 (7.1) | 20 (4.8) | 20 (4.9) | 18 (4.4) | 9 (2.2) | |
| 18.5~24 (kg/m2) | 248 (61.1) | 236 (56.9) | 235 (58.2) | 181 (44.5) | 174 (42.5) | |
| 24~28 (kg/m2) | 107 (26.4) | 141 (34.0) | 126 (31.2) | 170 (41.8) | 183 (44.8) | |
| ≥28 (kg/m2) | 22 (5.4) | 18 (4.3) | 23 (5.7) | 38 (9.3) | 43 (10.5) | |
| SBP (mm Hg) | 123.25±10.76 | 124.24±9.76 | 125.88±9.77 | 126.22±8.97 | 126.82±9.11 | <0.001 |
| DBP (mm Hg) | 76.63±7.16 | 77.20±6.80 | 76.86±6.67 | 77.45±6.39 | 77.13±6.70 | 0.464 |
| FBG (mmol/L) | 5.33±0.63 | 5.36±0.61 | 5.41±0.61 | 5.45±0.64 | 5.52±0.62 | <0.001 |
| TC (mmol/L) | 4.43±0.72 | 4.51±0.75 | 4.53±0.75 | 4.56±0.74 | 4.67±0.74 | <0.001 |
| Creatine (μmol/L) | 89.00±19.86 | 89.08±17.86 | 90.66±18.67 | 92.14±19.28 | 101.78±24.76 | <0.001 |
| eGFR (mL/min/1.73 m2) | 87.78±24.92 | 86.57±24.14 | 84.70±23.68 | 83.00±23.17 | 74.21±23.40 | <0.001 |
DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; FBG, fasting blood glucose; HUA, hyperuricaemia group; SBP, systolic blood pressure; SUA, serum uric acid; TC, total cholesterol.
Table 2.
Baseline characteristics of the female participants according to different SUA levels
| Characteristics | SUA level | P value | ||||
| Q1 (n=891) | Q2 (n=878) | Q3 (n=901) | Q4 (n=863) | HUA (n=545) | ||
| Age (years) | 59.73±8.68 | 62.41±8.00 | 63.73±8.43 | 65.09±8.50 | 67.81±9.26 | <0.001 |
| Body mass index (%) | <0.001 | |||||
| <18.5 (kg/m2) | 61 (6.9) | 45 (5.1) | 45 (5.0) | 29 (3.4) | 9 (1.6) | |
| 18.5~24 (kg/m2) | 617 (69.4) | 603 (68.6) | 539 (59.7) | 460 (53.4) | 244 (44.7) | |
| 24~28 (kg/m2) | 185 (20.8) | 195 (22.2) | 267 (29.6) | 303 (35.2) | 227 (41.6) | |
| ≥28 (kg/m2) | 26 (2.9) | 36 (4.1) | 52 (5.7) | 69 (8.0) | 66 (12.1) | |
| SBP (mm Hg) | 120.05±11.42 | 121.89±10.56 | 122.66±11.01 | 125.21±9.82 | 127.06±9.23 | <0.001 |
| DBP (mm Hg) | 73.72±7.47 | 74.23±6.91 | 74.28±7.29 | 74.99±7.12 | 75.27±6.82 | <0.001 |
| FBG (mmol/L) | 5.16±0.55 | 5.18±0.54 | 5.29±0.57 | 5.32±0.56 | 5.50±0.62 | <0.001 |
| TC (mmol/L) | 4.62±0.73 | 4.75±0.74 | 4.86±0.72 | 4.92±0.71 | 4.96±0.75 | <0.001 |
| Creatine (μmol/L) | 69.26±15.17 | 71.06±15.38 | 73.04±17.06 | 75.52±17.24 | 81.15±19.48 | <0.001 |
| eGFR (mL/min/1.73 m2) | 96.91±29.01 | 92.95±27.30 | 90.31±27.75 | 86.43±27.38 | 78.73±25.04 | <0.001 |
DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; FBG, fasting blood glucose; HUA, hyperuricaemia group; SBP, systolic blood pressure; SUA, serum uric acid; TC, total cholesterol.
Linear regression models with GEE were used to evaluate the association between SUA and CVD risk factors (table 3). After adjustment of the confounding factors, we found that men in the Q3 group displayed a positive association with SBP (beta=1.63 (95% CI 0.31 to 2.94)). Among women, participants in Q4 and the HUA groups had positive associations with SBP (beta=2.02 (95% CI 1.06 to 2.97) for Q4; beta=2.31 (95% CI 1.22 to 3.39) for HUA) and DBP (beta=1.17 (95% CI 0.47 to 1.86) for Q4; beta=1.27 (95% CI 0.49 to 2.06) for HUA). Furthermore, we found a positive association between SUA and FBG in women with beta of 0.11 (95% CI 0.05 to 0.17) in Q3 group, 0.13 (95% CI 0.07 to 0.19) in Q4 group and 0.28 (95% CI 0.19 to 0.36) in HUA group, respectively. However, no significant associations were observed between SUA and SBP, DBP or FBG in men. Notably, there was a linear increase in TC with increasing quartiles of SUA in both sexes. The beta (95% CI) in the HUA group of SUA was 0.16 (95% CI 0.06 to 0.25) in men and 0.15 (95% CI 0.06 to 0.24) in women.
Table 3.
Linear regression analysis of baseline SUA levels and BP, FBG and TC
| SUA (μmol/L) | Characteristics, beta (95% CI) | |||
| SBP | DBP | FBG | TC | |
| Men | ||||
| Q1 | Ref | Ref | Ref | Ref |
| Q2 | 0.50 (−0.78, 1.77) | 0.74 (−0.12, 1.60) | 0.04 (−0.14, 0.06) | 0.08 (−0.01, 0.17) |
| Q3 | 1.63 (0.31, 2.94)** | 0.73 (−0.16, 1.63) | 0.01 (−0.12, 0.11) | 0.11 (0.01, 0.20)* |
| Q4 | 1.00 (−0.26, 2.26) | 1.01 (0.16, 1.87)* | 0.02 (−0.09, 0.12) | 0.10 (0.01, 0.20)* |
| HUA | 1.30 (0.04, 2.56)* | 0.89 (−0.02, 1.80) | 0.03 (−0.08, 0.14) | 0.16 (0.06, 0.25)** |
| Women | ||||
| Q1 | Ref | Ref | Ref | Ref |
| Q2 | 0.54 (−0.40, 1.48) | 0.64 (−0.03, 1.32) | 0.01 (−0.05, 0.07) | 0.07 (0.01, 0.14) |
| Q3 | 0.27 (−0.68, 1.23) | 0.42 (−0.26, 1.10) | 0.11 (0.05, 0.17)** | 0.12 (0.05, 0.19)** |
| Q4 | 2.02 (1.06, 2.97)** | 1.17 (0.47, 1.86)** | 0.13 (0.07, 0.19)** | 0.13 (0.06, 0.20)** |
| HUA | 2.31 (1.22, 3.39)** | 1.27 (0.49, 2.06)** | 0.28 (0.19, 0.36)** | 0.15 (0.06, 0.24)** |
Model on SBP or DBP was adjusted for age, BMI, FBG, TC, creatine and eGFR. Model on FBG was adjusted for age, BMI, SBP, DBP, TC, creatine and eGFR. Model on TC was adjusted for age, BMI, SBP, DBP, FBG, creatine and eGFR.
*0.0167≤p<0.05, **p<0.0167.
BMI, body mass index; BP, blood pressure; DBP, diastolic BP; eGFR, estimated glomerular filtration rate; FBG, fasting blood glucose; HUA, hyperuricaemia group; SBP, systolic BP; SUA, serum uric acid; TC, total cholesterol.
The HRs of hypertension, hyperglycaemia and dyslipidaemia were calculated using multiple logistic regression analyses in the GEE across different SUA levels. After adjustment of the covariates, we found that elevated SUA levels were significantly associated with an increased incidence of hypertension, hyperglycaemia and dyslipidaemia in women. Compared with the lowest SUA quartile, women in the HUA group showed a significantly higher risk of hypertension (HR: 1.45, 95% CI: 1.21 to 1.73, p<0.001). For hyperglycaemia, the HRs were 2.37 (1.47 to 3.81) in HUA group. Similarly, for dyslipidaemia, the HRs were 1.55 (1.16 to 2.06) in HUA group. In men, elevated SUA levels were associated with a higher incidence of dyslipidaemia with HRs of 1.65 (1.28 to 2.12) in HUA; however, no significant associations were observed between SUA levels and hypertension or hyperglycaemia (figure 2).
Figure 2.
HRs of hypertension, hyperglycaemia and dyslipidaemia according to the SUA levels. Model on hypertension was adjusted for age, BMI, FBG, TC, creatine and eGFR. Model on hyperglycaemia was adjusted for age, BMI, SBP, DBP, TC, creatine and eGFR. Model on dyslipidaemia was adjusted for age, BMI, SBP, DBP, FBG, creatine and eGFR. Q1–Q4 were quartiles of normal SUA. *0.0167≤p<0.05, **p<0.0167. BMI, body mass index; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; FBG, fasting blood glucose; HUA, hyperuricaemia group; SBP, systolic blood pressure; SUA, serum uric acid; TC, total cholesterol.
We stratified participants by age using 65 years as a cut-off point. Among men, elevated SUA levels were significantly associated with dyslipidaemia. In women aged 40–65 years, elevated SUA levels were linked to hyperglycaemia and dyslipidaemia; women aged ≥65 years showed significant associations between elevated SUA levels and hypertension. Furthermore, women were stratified by menopausal status, using 51 years as the cut-off point. Participants younger than 51 years had no significant association between SUA and hypertension or hyperglycaemia, but a significant association was observed between SUA and dyslipidaemia. For participants aged 51 years and above, we observed a significant association between SUA levels and hypertension, hyperglycaemia and dyslipidaemia. In the obesity-stratified analysis, we found similar associations of SUA with hypertension, hyperglycaemia and dyslipidaemia in the non-obese group. However, none of these associations were statistically significant in the obese population (see online supplemental tables 2–6).
Discussion
Our study investigated the associations between SUA levels, HUA and CVD risk factors, including hypertension, hyperglycaemia and dyslipidaemia, and revealed the gender-specific relationships between SUA levels and these outcomes on continuous and categorical scales. Higher SUA levels increased the risk of dyslipidaemia in both sexes and increased the risk of hypertension and hyperglycaemia in women on a categorical scale.
Previous studies have reported inconsistent relationships between SBP or DBP and SUA.16–21 32 Our study showed a positive correlation between SUA levels and elevated SBP and DBP, which is in line with the majority of previous research.8 33 Additionally, numerous earlier studies and meta-analyses have highlighted that HUA and elevated SUA levels are associated with a higher risk of developing hypertension.34 35 This may be explained by the effect of elevated SUA levels on the renin–angiotensin system, which is closely related to BP regulation.36 Furthermore, elevated SUA levels may trigger oxidative stress and inflammatory responses, leading to vascular endothelial cell damage and the formation of atherosclerotic plaque, which is one of the leading causes of CVDs. Elevated SUA levels could also inhibit the release of nitric oxide, resulting in endothelial dysfunction. This dysfunction increases BP and promotes cardiovascular pathological damage. In conclusion, the mechanisms of SUA on the development of CVDs are complex and interactive; future studies are required to explain the role of high uric acid in CVDs and its factors.37
Higher SUA levels and HUA prevalence are observed in men than in women, possibly due to differences in body metabolism and sex hormone secretion in middle-aged and older women. Oestrogen facilitates SUA excretion, resulting in lower average SUA levels in women than in men.38 Our study found a significant association between HUA and hypertension in women but not in men, consistent with a cross-sectional study of over 11 000 participants investigating the association between SUA and cardiovascular risk factors.8 Gender differences were also observed in the association between SUA and hyperglycaemia, with significant association only found in women but not in men. A study in a rural population in northeastern China consistently found that HUA was associated with hyperglycaemia only in women.39 Furthermore, HUA and diabetes have been demonstrated to have shared common genetic predispositions, and several genes have been shown to be strongly associated with the development and progression of both diseases.40 41 A genome-wide association study in India revealed that single nucleotide polymorphisms (SNPs) in genes such as SLC2A9, SLC22A11 and ABCG2 were involved in the interaction between HUA and type 2 diabetes.42 Similarly, several studies in Chinese populations have indicated that SNPs in SLC2A9 are associated with an increased risk of type 2 diabetes, as well as with glucose metabolism and insulin secretion.43 These genetic correlations between uric acid and diabetes indirectly support our findings.
Dyslipidaemia is a significant risk factor for CVD. In a meta-analysis involving 17 studies, the combined OR for the highest SUA level compared with the lowest SUA level was 1.84 (1.49 to 2.28) for the risk of dyslipidaemia.27 Our study found a significant positive correlation between SUA and TC, as well as an elevated risk of dyslipidaemia with both HUA and higher SUA levels within the normal range, which was consistent with earlier studies.44–47 Notably, previous studies did not find a connection between SUA and dyslipidaemia in females.48 However, our study found significant associations between both men and women, with a stronger trend observed in men when the analysis was stratified by gender. These findings were also consistent with those of a cross-sectional study conducted in Korea.29 Furthermore, given the high incidence of HUA among middle-aged women,49 we stratified women by menopausal status. Our study confirmed a significant association between SUA levels and hypertension, hyperglycaemia and dyslipidaemia for women after menopause, suggesting that SUA is an independent risk factor for CVD in postmenopausal women. These findings are consistent with previous reports.50 Importantly, our study underlines the necessity of considering the impact of menopausal status on the association between SUA and CVD.
There are several limitations in our study. First, data in relation to potential confounding factors had not been collected, such as smoking, alcohol consumption, physical activity and dietary habits, which may cause overestimations on the associations between uric acid and cardiovascular risk factors in this study. Second, our study was based on a single-centre investigation and included only adults aged 40 years and older residing in the community, which should be cautious when extrapolating our findings to other populations. Third, because of the retrospective study design, our results may be subject to self-reporting bias, such as the disease and drug histories. However, most of the information in this study was based on blood measurements, which suggested that the self-reporting bias might be small. Our study has several strengths, such as a large sample size, a long follow-up period and a prospective design. Analyses using both continuous and categorical scales of the endpoints can provide more reliable and robust findings. Our study provides valuable insights into the association between SUA levels and CVD risk factors in a specific population. Further investigation in this area could improve our understanding of the pathogenesis of CVD and inform the development of preventive and therapeutic interventions.
Conclusion
This study highlights the detrimental impact of elevated SUA levels on dyslipidaemia risk in both sexes. Furthermore, it reveals that SUA levels within the normal range and HUA status are positively associated with hyperglycaemia and hypertension in postmenopausal women, but no such associations were observed in men.
Supplementary Material
Acknowledgments
The authors would like to thank all community residents for participating in the present study, as well as the corresponding medical staff at the community health centre for their assistance in this study.
Footnotes
Contributors: YL and HM conducted the conception and design of the research protocol. YL, CJ, MH and YW acquired and analysed the data, YL and QW were responsible for writing and revising the article, and FL and RM provided guidance on the research methodology. HM is the guarantor responsible for the overall content. All authors reviewed the manuscript and agreed to submit the paper.
Funding: This study was supported by a grant from the Preventive Medicine Discipline Construction Project of Hangzhou Normal University.
Competing interests: None declared.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review: Not commissioned; externally peer reviewed.
Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Data availability statement
Data are available upon reasonable request. Data may be obtained from a third party and are not publicly available.
Ethics statements
Patient consent for publication
Obtained.
Ethics approval
This study involves human participants and was approved by the Ethics Committee of Hangzhou Normal University School of Public Health (20220009). Participants gave informed consent to participate in the study before taking part.
References
- 1.Zhao D, Liu J, Wang M, et al. Epidemiology of cardiovascular disease in China: Current features and implications. Nat Rev Cardiol 2019;16:203–12. 10.1038/s41569-018-0119-4 [DOI] [PubMed] [Google Scholar]
- 2.Liu S, Li Y, Zeng X, et al. Burden of cardiovascular diseases in China, 1990-2016: findings from the 2016 global burden of disease study. JAMA Cardiol 2019;4:342–52. 10.1001/jamacardio.2019.0295 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.He H, Guo P, He J, et al. Prevalence of hyperuricemia and the population attributable fraction of Modifiable risk factors: evidence from a general population cohort in China. Front Public Health 2022;10:936717. 10.3389/fpubh.2022.936717 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Kleber ME, Delgado G, Grammer TB, et al. Uric acid and cardiovascular events: A Mendelian randomization study. J Am Soc Nephrol 2015;26:2831–8. 10.1681/ASN.2014070660 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Sung K-C, Byrne CD, Ryu S, et al. Baseline and change in uric acid concentration over time are associated with incident hypertension in large Korean cohort. Am J Hypertens 2017;30:42–50. 10.1093/ajh/hpw091 [DOI] [PubMed] [Google Scholar]
- 6.Copur S, Demiray A, Kanbay M. Uric acid in metabolic syndrome: does uric acid have a definitive role? Eur J Intern Med 2022;103:4–12. 10.1016/j.ejim.2022.04.022 [DOI] [PubMed] [Google Scholar]
- 7.Park JS, Kim Y, Kang J. Genome-wide meta-analysis revealed several genetic Loci associated with serum uric acid levels in Korean population: an analysis of Korea Biobank data. J Hum Genet 2022;67:231–7. 10.1038/s10038-021-00991-1 [DOI] [PubMed] [Google Scholar]
- 8.Shi Q, Wang R, Zhang H, et al. Association between serum uric acid and cardiovascular disease risk factors in adolescents in America: 2001-2018. PLoS One 2021;16:e0254590. 10.1371/journal.pone.0254590 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Singh SK, Singh R, Singh SK, et al. Prevalence of hyperuricemia and the relationship between serum uric acid and hypertension in New onset diabetic patients: A cross-sectional Indian study. Diabetes Metab Syndr Obes 2022;15:1809–17. 10.2147/DMSO.S363311 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Son Y-B, Yang JH, Kim M-G, et al. The effect of baseline serum uric acid on chronic kidney disease in normotensive, Normoglycemic, and non-obese individuals: A health checkup cohort study. PLoS One 2021;16:e0244106. 10.1371/journal.pone.0244106 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Tian T, Wang Y, Xie W, et al. Associations of serum uric acid with clustering of cardiovascular risk factors and a 10-year Atherosclerotic cardiovascular disease risk score in Jiangsu adults, China. Diabetes Metab Syndr Obes 2021;14:3447–60. 10.2147/DMSO.S323917 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Gherghina M-E, Peride I, Tiglis M, et al. Uric acid and oxidative stress-relationship with cardiovascular, metabolic, and renal impairment. Int J Mol Sci 2022;23:3188. 10.3390/ijms23063188 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Li P, Zhang L, Zhang M, et al. Uric acid enhances PKC-dependent eNOS Phosphorylation and mediates cellular ER stress: A mechanism for uric acid-induced endothelial dysfunction. Int J Mol Med 2016;37:989–97. 10.3892/ijmm.2016.2491 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Borghi C, Agnoletti D, Cicero AFG, et al. Uric acid and hypertension: a review of evidence and future perspectives for the management of cardiovascular risk. Hypertension 2022;79:1927–36. 10.1161/HYPERTENSIONAHA.122.17956 [DOI] [PubMed] [Google Scholar]
- 15.Ghasemi A. Uric acid-induced Pancreatic Β-cell dysfunction. BMC Endocr Disord 2021;21:24. 10.1186/s12902-021-00698-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Liu C-W, Ke S-R, Tseng G-S, et al. Elevated serum uric acid is associated with incident hypertension in the health according to various contemporary blood pressure guidelines. Nutrition, Metabolism and Cardiovascular Diseases 2021;31:1209–18. 10.1016/j.numecd.2021.01.003 [DOI] [PubMed] [Google Scholar]
- 17.Zhang L, Li J-L, Guo L-L, et al. The interaction between serum uric acid and triglycerides level on blood pressure in middle-aged and elderly individuals in China: result from a large national cohort study. BMC Cardiovasc Disord 2020;20:174. 10.1186/s12872-020-01468-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Lee SW, Kim HC, Nam C, et al. Age-differential association between serum uric acid and incident hypertension. Hypertens Res 2019;42:428–37. 10.1038/s41440-018-0168-4 [DOI] [PubMed] [Google Scholar]
- 19.Zhu L, Zhang X, Fang Z, et al. Association between serum uric acid and pre-hypertension and hypertension among Chinese adults. Arq Bras Cardiol 2021;116:1072–8. 10.36660/abc.20200098 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Wu Y, Li J, Xu Y, et al. Predictive value of serum uric acid on cardiovascular disease and all-cause mortality in urban Chinese patients. Chin Med J (Engl) 2010;123:1387–91. [PubMed] [Google Scholar]
- 21.Puddu PE, Bilancio G, Terradura Vagnarelli O, et al. Serum uric acid and Egfr_Ckdepi differently predict long-term cardiovascular events and all causes of deaths in a residential cohort. Int J Cardiol 2014;171:361–7. 10.1016/j.ijcard.2013.12.029 [DOI] [PubMed] [Google Scholar]
- 22.Kawamoto R, Tabara Y, Kohara K, et al. Serum uric acid is more strongly associated with impaired fasting glucose in women than in men from a community-dwelling population. PLoS One 2013;8:e65886. 10.1371/journal.pone.0065886 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Kivity S, Kopel E, Steinlauf S, et al. The association between serum uric acid and diabetes mellitus is stronger in women. J Womens Health (Larchmt) 2013;22:782–9. 10.1089/jwh.2012.4043 [DOI] [PubMed] [Google Scholar]
- 24.Li H, Zha X, Zhu Y, et al. An invert U-shaped curve: relationship between fasting plasma glucose and serum uric acid concentration in a large health check-up population in China. Medicine (Baltimore) 2016;95:e3456. 10.1097/MD.0000000000003456 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Lou Y, Qin P, Wang C, et al. Sex-specific Association of serum uric acid level and change in hyperuricemia status with risk of type 2 diabetes mellitus: A large cohort study in China. J Diabetes Res 2020;2020:9637365. 10.1155/2020/9637365 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Cheng D, Hu C, Du R, et al. Serum uric acid and risk of incident diabetes in middle-aged and elderly Chinese adults: prospective cohort study. Front Med 2020;14:802–10. 10.1007/s11684-019-0723-7 [DOI] [PubMed] [Google Scholar]
- 27.Chen S, Yang H, Chen Y, et al. Association between serum uric acid levels and Dyslipidemia in Chinese adults: A cross-sectional study and further meta-analysis. Medicine (Baltimore) 2020;99:e19088. 10.1097/MD.0000000000019088 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Pang S, Jiang Q, Sun P, et al. Hyperuricemia prevalence and its association with metabolic disorders: a multicenter retrospective real-world study in China. Ann Transl Med 2021;9:1550. 10.21037/atm-21-5052 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Son M, Seo J, Yang S, et al. Association between Dyslipidemia and serum uric acid levels in Korean adults: Korea national health and nutrition examination survey 2016-2017. PLoS ONE 2020;15:e0228684. 10.1371/journal.pone.0228684 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Shan R, Ning Y, Ma Y, et al. Incidence and risk factors of hyperuricemia among 2.5 million Chinese adults during the years 2017-2018. IJERPH 2021;18:2360. 10.3390/ijerph18052360 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Weng J, Ji L, Jia W, et al. Standards of care for type 2 diabetes in China. Diabetes Metab Res Rev 2016;32:442–58. 10.1002/dmrr.2827 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Zhang L, Li J-L, Zhang L-L, et al. Body mass index and serum uric acid level: individual and combined effects on blood pressure in middle-aged and older individuals in China. Medicine (Baltimore) 2020;99:e19418. 10.1097/MD.0000000000019418 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Ding N, He L, Li C, et al. Uric acid and blood pressure in NHANES dated from 2009 to 2018: A cross-sectional research. Nutr Metab Cardiovasc Dis 2022;32:2568–78. 10.1016/j.numecd.2022.08.017 [DOI] [PubMed] [Google Scholar]
- 34.Grayson PC, Kim SY, LaValley M, et al. Hyperuricemia and incident hypertension: a systematic review and meta-analysis. Arthritis Care Res 2011;63:102–10. 10.1002/acr.20344 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Wang J, Qin T, Chen J, et al. Hyperuricemia and risk of incident hypertension: a systematic review and meta-analysis of observational studies. PLoS ONE 2014;9:e114259. 10.1371/journal.pone.0114259 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Sanchez-Lozada LG, Rodriguez-Iturbe B, Kelley EE, et al. Uric acid and hypertension: an update with recommendations. Am J Hypertens 2020;33:583–94. 10.1093/ajh/hpaa044 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Saito Y, Tanaka A, Node K, et al. Uric acid and cardiovascular disease: A clinical review. J Cardiol 2021;78:51–7. 10.1016/j.jjcc.2020.12.013 [DOI] [PubMed] [Google Scholar]
- 38.Yahyaoui R, Esteva I, Haro-Mora JJ, et al. Effect of long-term administration of cross-sex hormone therapy on serum and urinary uric acid in Transsexual persons. J Clin Endocrinol Metab 2008;93:2230–3. 10.1210/jc.2007-2467 [DOI] [PubMed] [Google Scholar]
- 39.Yu S, Yang H, Guo X, et al. Prevalence of hyperuricemia and its correlates in rural northeast Chinese population: from lifestyle risk factors to metabolic Comorbidities. Clin Rheumatol 2016;35:1207–15. 10.1007/s10067-015-3051-6 [DOI] [PubMed] [Google Scholar]
- 40.Szabó E, Kulin A, Mózner O, et al. Potential role of the Abcg2-Q141K polymorphism in type 2 diabetes. PLoS ONE 2021;16:e0260957. 10.1371/journal.pone.0260957 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Zhao SS, Rajasundaram S, Karhunen V, et al. Sodium-glucose cotransporter 1 inhibition and gout: Mendelian Randomisation study. Semin Arthritis Rheum 2022;56:152058. 10.1016/j.semarthrit.2022.152058 [DOI] [PubMed] [Google Scholar]
- 42.Giri AK, Banerjee P, Chakraborty S, et al. Genome wide Association study of uric acid in Indian population and interaction of identified variants with type 2 diabetes. Sci Rep 2016;6:21440. 10.1038/srep21440 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Sun X, Zhang R, Jiang F, et al. Common variants related to serum uric acid concentrations are associated with glucose metabolism and insulin secretion in a Chinese population. PLoS ONE 2015;10:e0116714. 10.1371/journal.pone.0116714 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Ali N, Rahman S, Islam S, et al. The relationship between serum uric acid and lipid profile in Bangladeshi adults. BMC Cardiovasc Disord 2019;19:42. 10.1186/s12872-019-1026-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Kuwabara M, Borghi C, Cicero AFG, et al. Elevated serum uric acid increases risks for developing high LDL cholesterol and Hypertriglyceridemia: A five-year cohort study in Japan. Int J Cardiol 2018;261:183–8. 10.1016/j.ijcard.2018.03.045 [DOI] [PubMed] [Google Scholar]
- 46.Peng T-C, Wang C-C, Kao T-W, et al. Relationship between hyperuricemia and lipid profiles in US adults. Biomed Res Int 2015;2015:127596. 10.1155/2015/127596 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Liu F, Du G-L, Song N, et al. Hyperuricemia and its association with Adiposity and Dyslipidemia in Northwest China: results from cardiovascular risk survey in Xinjiang (CRS 2008-2012). Lipids Health Dis 2020;19:58. 10.1186/s12944-020-01211-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Kuwabara M, Niwa K, Hisatome I, et al. Asymptomatic hyperuricemia without Comorbidities predicts Cardiometabolic diseases: five-year Japanese cohort study. Hypertension 2017;69:1036–44. 10.1161/HYPERTENSIONAHA.116.08998 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Cho SK, Winkler CA, Lee S-J, et al. The prevalence of hyperuricemia sharply increases from the late menopausal transition stage in middle-aged women. J Clin Med 2019;8:296. 10.3390/jcm8030296 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Yuan Q, Karmacharya U, Liu F, et al. Uric acid and its correlation with hypertension in postmenopausal women: A multi-ethnic study (observational study). Clinical and Experimental Hypertension 2020;42:559–64. 10.1080/10641963.2020.1739697 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
bmjopen-2023-073930supp001.pdf (80.7KB, pdf)
Data Availability Statement
Data are available upon reasonable request. Data may be obtained from a third party and are not publicly available.