Association of serum uric acid levels with cardiovascular and all-cause mortality in hypertensive patients in China: a cohort study

Abstract

Purpose

The present study aimed to assess the association of elevated serum uric acid (SUA) and hypouricemia with all-cause mortality and cardiovascular mortality in Chinese hypertensive patients.

Methods

In the present prospective cohort, 9325 hypertensive patients from Dongguan, China were enrolled from 2014 to 2018 for analysis. Participants were categorised by quintiles of SUA. The HRs and 95% CIs for the association between SUA, all-cause and cardiovascular mortality were evaluated using the multivariate Cox regression model. After adjusting for multiple confounders, restricted cubic spline analysis was conducted to demonstrate the shape of relationship.

Results

After a median follow-up of 4.18 years for 9325 participants, there were 409 (4.4%) and 151 (1.6%) reported cases of all-cause and cardiovascular mortality, respectively. By using the third quintile of SUA (6.68 mg/dL to <7.55 mg/dL for men, 5.63 mg/dL to <6.42 mg/dL for women) as reference, the highest quintiles of SUA were associated with an elevated risk of all cause (HR: 1.34, 95% CI 1.00 to 1.80) in the crude model, but the association was not significant after adjusting for multiple comparisons. The association between low SUA and mortality and the dose–response analysis on the non-linearity of SUA–mortality relationship were not statistically significant.

Conclusions

Although the association between SUA levels, all-cause and cardiovascular disease mortality did not appear to be significant among Chinese hypertensive patients, the findings might be confounded by their medical conditions. Further studies are needed to verify the optimal SUA levels for hypertensive patients.

Introduction

Elevated blood pressure (BP) is one of the major risk factors for global disease burden [1], it can cause severe target organ damage, and a higher risk for mortality. Moreover, serum uric acid (SUA), as the end product of purine metabolism [2], has been related to hypertension, diabetes, dyslipidaemia and obesity [3, 4]. SUA is also being regarded as an independent risk factor for cardiovascular disease (CVD) [5], including heart failure [6, 7]. Some studies demonstrated a positive association between hyperuricemia and cardiovascular mortality [8–11]. However, the influence of a low uric acid level on mortality and clinical outcomes has not been established, since only several studies have been performed. A Korean study has demonstrated low uric acid level to be associated with higher all-cause mortality in patients undergoing dialysis [12]. A cohort study in Japan reported that low uric acid level (<4.6 mg/dL in men and <3.3 mg/dL in women) can increase the risk of CVD mortality [13]. Despite the aforementioned studies, the prospective impact of hyperuricemia and hypouricemia in the risk of mortality has not been investigated adequately, including people with hypertension. To address this research gap, we aimed to assess the association of elevated SUA and hypouricemia with all-cause mortality and cardiovascular mortality in Chinese hypertensive patients.

Methods

Study population

All participants were essential hypertensive patients aged 18 years or above, who lived in Liaobu community in Dongguan, Guangdong Province of China. Patients were enrolled during January and December 2014 and being followed until 31 December 2018. Participants with missing baseline data on SUA levels or BP or patients who took diuretic and other uric acid-lowering drugs were excluded (Figure 1). Finally, 9325 participants were included in this analysis. This study was following the principles outlineWHd in the Declaration of Helsinki.

Data collection

To measure the level of SUA, fasting blood samples were drawn after 8 hours to 10 hours of overnight fasting. After that, the samples were centrifuged at 3500 rounds per minute for 15 min to obtain a serum layer for analysis. The concentration of SUA was measured using an automatic biochemical analyser (Hitachi 7170A) [14]. Demographic data from participants were obtained using a standardised questionnaire, including age, sex, lifestyle habits such as smoking (yes or no), alcohol intake (yes or no), history of coronary artery diseases (CAD) (yes or no), diabetes (yes or no), stroke (yes or no) and antihypertensive medication use (antihypertensive drugs: β-receptor blockers (beta), calcium channel blockers (CCB), angiotensin converting enzyme inhibitors (ACEI)/angiotensin (ARB)). Height and weight were measured using an automatic scale, and body mass index (BMI) was calculated using these measurements as follow: BMI=body weight/height [2]. Diabetes mellitus (DM) was defined as fasting blood glucose (FBG) ≥126 mg/dL, the use of hypoglycaemic agents or self-reported history of diabetes [14]. Blood samples drawn from the antecubital vein were obtained after overnight fasting. Serum levels of uric acid, FBG, total cholesterol (CHOL), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG) were measured by standard method in core clinical laboratory. BP and heart rate (HR) were measured by the Omron HBP-1100u professional portable BP monitor (Japan) placed on the right arm, while the individual was in a sitting position more than 5 min. The average measurement values of systolic BP (SBP) and diastolic BP (DBP) were used. Hypertension was defined as SBP ≥140 mm Hg and/or DBP ≥90 mm Hg or self-reported use of antihypertensive drug in the last 2 weeks [14].

Outcome assessment and follow-up

All-cause and cardiovascular mortality were the outcomes of the present study, which were assessed according to the International Classification of Diseases, 10th Edition (ICD-10) [15]. All-cause mortality included deaths from all causes. Cardiovascular mortality was defined by ICD-10, Clinical Modification System codes (ICD-10) (I00-I09, I11, I13 and I20-I51) derived from death-certificate data. From the time of enrolment until 31 December 2018, data on mortality were obtained from the local medical insurance administration of Dongguan City, which were investigated by clinic visit or phone call during follow-up.

Statistical methods

Continuous variables were reported as means and SD, and categorical variables were reported as frequencies with percentages. By using predefined normal values (3.5 mg/dL to 7.2 mg/dL for men, 2.6 mg/dL to 6.0 mg/dL for women) of SUA, [16] only very few patients from the present study sample were low in SUA (0.6% for men and 0.3% for women). Therefore, participants were categorised by sex-specific quintiles in the study population for all analyses instead. For men, the range of quintiles was <5.76 mg/dL, 5.76 mg/dL to <6.68 mg/dL, 6.68 mg/dL to <7.55 mg/dL, 7.55 mg/dL to <8.68 mg/dL and ≥8.68 mg/dL, respectively. For women, the range of quintiles was <4.83 mg/dL, 4.83 mg/dL to <5.63 mg/dL, 5.63 mg/dL to <6.42 mg/dL, 6.42 mg/dL to <7.46 mg/dL and ≥7.46 mg/dL, respectively. These categories were used to explore the non-linear associations and better delineate the effects of low and high SUA levels on mortality risk. With the use of Cox proportional hazard models (the third quintile as referent), HRs and 95% CIs were estimated to demonstrate the association between SUA, all-cause and cardiovascular mortality. Two regression models were built. Model 1 only included SUA, while model 2 was additionally adjusted for age, sex, BMI, SBP, DBP, smoking, alcohol intake, TG, HDL-C, CHOL, FBG comorbidities (stroke, DM, CAD) and medication use (beta, CCB, ACEI/ARB). Trend analysis was performed by assigning median values of each SUA quintile and treating it as a continuous variable in the regression model [17]. We performed restricted cubic spline analysis with three knots (25th, 50th and 75th percentiles) to detect the shape of dose–response relationships of SUA and mortality, using the median of SUA as the reference point, adjusted by all covariates in model 2 [18]. We used Wald-type statistics testing that a beta coefficient for second spline is not equal to zero [19]. For the subgroup analyses, we stratified participants by age (<80 or ≥80 years), sex (male or female), antihypertensive medication use (yes or no) and BMI (<25 kg/m² or ≥25 kg/m²) to investigate potential sources of effect modification. All p values were two sided, and p values <0.05 were considered statistically significant. To avoid false-positive findings due to multiple comparisons, the significance level of all statistical analyses has been adjusted using Bonferroni correction. All analyses were performed with R V.3.6.3 (R Foundation for Statistical Computing, Vienna, Austria).

Results

Baseline characteristics

The baseline characteristics of all the participants according to SUA levels are summarised in Table 1. A total of 9325 (48.5% male) participants with an average age of 62.22±13.62 years were enrolled at baseline. The overall BMI of participants was 24.9 (SD=3.93), demonstrating that half of the study population tended to be overweight. There were significant differences in age, SUA, SBP, alcohol intake, BMI, the use of antihypertensive drugs, CHOL, HDLC and TG across the quintiles of SUA (all p<0.05). In general, all aforementioned variables increased across quintiles except for HDLC that decreased across quintiles.

Exploring the non-linear association between SUA and mortality

There were 409 deaths documented during the follow-up period (average=4.18 years). Among the total cases of deaths, 151 (36.9%) events were attributed by CVD. Univariate and multivariate Cox regression analyses were performed to study the association of SUA level with cardiovascular and all-cause mortality (Table 2). When compared with the third quintile, the highest quintile of SUA was associated with the elevated risk of all-cause (HR: 1.34, 95% CI 1.00 to 1.80) in the crude model (model 1), but the association was not statistically significant after adjusting for multiple comparisons (p=0.48). Furthermore, the strength of association of the highest quintile of SUA with all-cause mortality attenuated after being fully adjusted in model 2 (HR: 0.87, 95% CI 0.64 to 1.18). In the trend analysis, SUA was associated with the elevated risk of all-cause (HR: 1.10, 95% CI 1.05 to 1.16) in the crude model after adjusting for multiple comparisons (model 1), but the association (HR: 0.98, 95% CI 0.92 to 1.04) was not significant after being fully adjusted in model 2. For the dose–response analysis (Figure 2), the p value for non-linearity was not significant for both all-cause (p=0.29) and CVD mortality (p=0.45).

Subgroup analyses

As shown in Table 3, after multivariate adjustment for confounders, subgroup analyses were performed in age (≥80 years vs <80 years), sex (male vs female), the use of antihypertensive drug (yes vs no) and BMI (≥25 kg/m² vs<25 kg/m²), respectively. The only significant interaction was found between age and SUA in the relationship between SUA and all-cause mortality, but the association between SUA in quintiles, all-cause and cardiovascular mortality was not significant regardless of subgroups.

Discussion

In a cohort of 9325 patients with hypertension in China, the present study has examined the association between both higher and low SUA levels and the risk of all-cause and cardiovascular mortality. Although SUA at the highest quintile might associate with an elevated risk of all-cause mortality in the crude model, the magnitude of association was insignificant after adjusting for multiple comparisons. The dose–response analysis on the non-linearity of SUA–mortality relationship was also insignificant.

The association of elevated SUA levels with all-cause and cardiovascular mortality was examined in several studies [20–24]. For example, one study categorised SUA into quartiles, [14] and they found that hyperuricemia was an independent risk factor of mortality from all causes and total CVD in Taiwanese population. Moreover, few studies have explored the role of both high and low uric acid level in mortality risk. Kuo et al found that individuals with either high (>11.4 mg/dL) or low (<2.9 mg/dL) SUA levels were at high risk for all-cause and cardiovascular mortality by setting the reference group as 5–6 mg/dL [22]. However, the study quality of Kuo et al might be affected by not adjusting for smoking, alcohol intake and BMI, which were the key cardiovascular risk factors.

To date, the underlying pathophysiologic mechanism of the association between low SUA levels and mortality is still unclear. Uric acid is known for two important opposing properties, namely, the antioxidant properties and its role in endothelial dysfunction. Several experimental investigations have demonstrated the free radical-scavenging capacity of SUA, while it can induce endothelial dysfunction [25–27]. A Taiwanese study showed that low uric acid level can also be a marker of malnutrition, and further pointed out that low SUA level was only predictive of increased mortality in older people who were malnourished (as defined by Geriatric Nutritional Risk Index, albumin and BMI) [28].

While previous studies have explored the influence of elevated and low SUA levels on the risk of death, inconsistent results were observed for different patient groups. For example, a study on people with diabetes showed that SUA has no independent role on cardiovascular mortality [29]. In another study of 15 366 participants in the Atherosclerosis Risk in Communities, there was a significant association between hyperuricemia and mortality (HR 1.18, 95% CI 1.04 to 1.33) in a non-CKD population, while the association in the CKD population was not significant [30]. The connection between hypertension and hyperuricemia also attracts people’s attention. Zhang et al reported that SUA level was positively associated with DBP and SBP in both men and women in general population [31]. In a study conducted among Chinese hypertensive patients, hyperuricemia was associated with higher risk for all-cause and cardiovascular mortality [32]. Uric acid is the final oxidation product of purine metabolism, [33] which approximately two-thirds of SUA is excreted by the kidneys, and its excretion level is affected by renal function [20]. In hypertensive patients, increased SUA levels may reflect early renal vascular alterations, with reduction in cortical blood flow and depressed tubular secretion of urate as caused by its reduced delivery to the tubular secretory sites [34]. Besides this, the increased activity of the sympathetic nervous system and hyperinsulinemia have been proved to be associated with reduced renal excretion of uric acid [35, 36].

In order words, the insignificant association between SUA and mortality in our study population might be attributed by several reasons. First, when compared with other studies conducted among general population, all participants in the present study were with essential hypertension. Although we have performed multivariable Cox regression analysis to minimise the interference of other potential risk factors and comorbidities, one also must consider the possibility that hypertension itself may be a risk factor for mortality, and, consequently, the presence of hypertension may attenuate the association of SUA with mortality. Second, only very few patients (0.6% for men and 0.3% for women) from the present study sample were low in SUA (<3.5 mg/dL for men and <2.6 mg/dL for women) [16]. In other words, patient in the present study might not reach the threshold level of exposure to elevate the mortality risk. Third, when compared with the study conducted among Chinese hypertensive patients, [32] the present study has lower all-cause mortality rate (27.4% vs 4.4%) and a shorter follow-up period (5.75 years vs 4.18 years on average). The relatively fewer cases of death and shorter follow-up duration for the present study might limit the statistical power to detect associations between SUA and the risk of mortality. To explore the influence of SUA on mortality risk across a wider range of exposure, more studies among hypertensive from diverse population should be conducted. In long term, optimal SUA levels for hypertensive patients can be established.

Some potential limitations of the present study should be considered. First, we determined uric acid level at a single time point and might not account for the changes in SUA with time. Second, information such as smoking status, alcohol use and medical history was self-reported through a questionnaire and could have resulted in recall bias. Third, some cardiovascular risk factors (eg, diet and mental health) were not adjusted in the present study and might result in residual confounding effect. Fourth, this study was conducted solely the Chinese population, so, therefore the conclusions of the study cannot be extrapolated to other ethnic population.

Conclusion

In summary, this study indicated that SUA levels did not have significant association with all-cause and CVD mortality among Chinese hypertensive patients, which might be confounded by their medical conditions. Further studies are needed to verify the optimal SUA levels for hypertensive patients.

Contributors

Conceptualisation: SXZ, KL, YQF and JYC. Methodology: SXZ, YLY, KL, YQF and JYC. Formal analysis: SXZ and KL. Data curation: SXZ, YLY, STT, KL, YQF and JYC. Writing—original draft preparation: SXZ and KL. Writing—review and editing: SXZ and KL. Supervision: KL, YQF and JYC. All authors drafted the manuscript. KL, YQF and JYC are the guarantors of the paper.

Funding

This research was supported by Science and Technology Plan Program of Guangzhou (Number 201803040012), The Key Area R&D Program of Guangdong Province (Number 2019B020227005), Guangdong Provincial People's Hospital Clinical Research Fund (Y012018085), The Fundamental and Applied Basic Research Foundation Project of Guangdong Province (2020A1515010738), and The Climbing Plan of Guangdong Provincial People's Hospital (DFJH2020022).

Competing interests

None declared.

Provenance and peer review

Not commissioned; externally peer reviewed.

Data availability statement

Data are available upon reasonable request. Raw data were generated at the Guangdong Provincial People’s Hospital. Derived data supporting the findings of this study are available from the corresponding author on request.

Ethics statements

Patient consent for publication

Not applicable.

Ethics approval

This study involves human participants and was approved by The Institutional Medical Ethical Committee of the Guangdong Provincial People’s Hospital, Guangzhou, China (reference number: 2012143H). Participants gave informed consent to participate in the study before taking part.

References