Abstract
Hyperuricemia and its complications are severe risks to human health. Dietary intervention is considered an essential part of the management of hyperuricemia. Studies have reported that the intake of antioxidants has a positive effect on hyperuricemia. Here, we collected data from 8761 participants of the National Health and Nutrition Examination Survey for this analysis. Daily intakes of vitamins A, C, and E; manganese; selenium; and zinc were calculated as the composite dietary antioxidant index (CDAI). The participants were divided into four groups (Q1, Q2, Q3, and Q4) according to the CDAI. Univariate analysis was used to assess the association of covariates with hyperuricemia. The association between the CDAI and hyperuricemia was evaluated using multinomial logistic regression, and its stability was determined by stratified analysis. Our results revealed that the CDAI has a significant negative association with hyperuricemia (Q2: 0.81 (0.69, 0.95); Q3: 0.75 (0.62, 0.90); Q4: 0.65 (0.51, 0.82); ). The results of stratified analysis emphasize that this association between CDAI and hyperuricemia is stable. In conclusion, this study suggested a negative association between the CDAI and hyperuricemia.
1. Introduction
Hyperuricemia (HUA) is clinically defined as high levels of serum uric acid in the body (>7 mg/dL for men and >6 mg/dL for women). Excess uric acid is often deposited in the joint, causing gout [1]. In addition, numerous complications associated with hyperuricemia have been reported, such as chronic kidney disease, cardiovascular disease, type 2 diabetes, and hypertension, and are considered critical burdens on human health [2–5]. Research data have shown that the prevalence of HUA among adults in the US is 20.2% for men and 20% for women [6]. Even worse, there is no curative treatment available [7]. In general, dietary intervention is considered to play a critical role in the management of HUA.
Recent studies have shown that excess uric acid in HUA patients can locally activate oxidative stress [8]. Oxidative stress produces oxidants, and the accumulation of oxidants leads to DNA oxidation, causing abnormal apoptosis and organ dysfunction and consequently leading to the abovementioned complications [8, 9]. Thus, there may be an interaction mechanism between uric acid and antioxidants, and antioxidants may mitigate the damage caused by uric acid.
Vitamin (vit) C, a common antioxidant, has been shown to have a negative association with HUA. Sun et al. also reported that supplementation with vit C might delay the development of hyperuricemic nephropathy [10, 11]. In addition, vit A, vit E, and zinc (Zn) have been shown to reduce the level of serum uric acid [12–16]. Although numerous studies have reported the effect of a single antioxidant on HUA, a study evaluating the association between comprehensive antioxidants and HUA still needs to be completed.
According to previous studies, we proposed a hypothesis that the intake of antioxidants and the risk of hyperacidity are inversely associated. We constructed a composite dietary antioxidant index (CDAI) consisting of food parameters for vit A, C, and E; manganese (Mn); selenium (Se); and Zn to represent an individual’s antioxidant intake status and to enhance the credibility of disease risk assessment [17]. A cross-sectional study including 8761 participants was conducted based on the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018 to investigate the association between the CDAI and HUA.
2. Methods and Materials
2.1. Data Sources and Study Design
Subject data for this study were obtained from the NHANES 2007–2018. NHANES is a representative cross-sectional survey of the American population designed to collect nutrition and health information from noninstitutionalized people. The NHANES website provides comprehensive and detailed information on study design, demographics, dietary assessments, health interviews, physical examinations, and laboratory data. Demographic and health-related information was obtained through questionnaires. Health interviews were conducted in the participants’ homes. Dietary assessments were obtained through 24-hour dietary memories. The Mobile Examination Centre was responsible for the physical examination and the collection of blood samples, which were then sent to the laboratory for testing.
Data marked as missing, refused, and did not know were considered missing data and manually excluded by the researcher. Only participants over 20 years of age were considered for inclusion in the study. After excluding missing data for uric acid levels, CDAI scores and covariates, a total of 8761 participants were included in the final study. The flow graph for inclusion and exclusion is shown in Figure 1. All participants provided written informed consent, and the NCHS Research Ethics Review Committee approved the study (https://wwwn.cdc.gov/nchs/nhanes/default.aspx).
2.2. Hyperuricemia and CDAI
HUA was diagnosed as uric acid levels ≥420 μmol/l (7 mg/dL) in males and ≥360 μmol/l (6 mg/dL) in females.
The CDAI proposed by Wright et al. was obtained by a composite calculation of the intake of multiple dietary antioxidants [17–20]. For all participants included in this study, the CDAI contained six dietary antioxidants: vit A, C, and E; Mn; Se; and Zn. The formula for CDAI is [21]. In the formula, Xi is the daily intake of antioxidants, μi is the mean of antioxidants in the study population, and Si is the standard deviation of μi. In brief, the CDAI is a scoring algorithm based on 24-hour dietary recall data designed to assess the level of antioxidant intake of participants. We averaged participants into four groups based on CDAI, Q1 (−7.177 to −1.178), Q2 (−1.177 to −0.796), Q3 (0.799 to 3.202), and Q4 (3.203 to 88.502).
2.3. Covariates
To exclude other factors interfering with the results, age, sex, race, education, household income to poverty ratio, BMI, dietary capacity and protein intake, hypertension status, diabetes status, smoking status, alcohol consumption status, physical activity, and biochemical indicators, including gamma glutamyl transferase, triglycerides, total cholesterol, HDL cholesterol, and creatinine, were selected as covariates for the analysis. Race was categorized as Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, and Other race—including multiracial. Educational attainment included three levels: below high school, high school, and above high school. Household income and poverty rates were used to measure participants’ household economic status and were categorized into three levels: less than 1, between 1 and 3, and more than 3. Hypertension was defined as participants taking medication for hypertension or having a past/current diagnosis of hypertension. Diabetes was classified into four categories: no, impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and yes. Smoking status was categorized as never, former, and now. Participants who consumed at least 12 alcoholic beverages in a year were considered to have drinking behavior. Physical activity included two categories, work activity status and recreational activity status, with four ratings of no, vigorous, moderate, and both. In addition, specific data for biochemical indicators were provided by the NHANES laboratory. All covariate data for this study can be viewed in detail on the NHANES website (https://www.cdc.gov/nchs/nhanes/index.htm).
2.4. Statistical Analyses
The statistical packages R (The R Foundation; https://www.r-project.org; version 3.6.3) and Empower Stats (https://www.empowerstats.net, X&Y solutions, Inc., Boston, Massachusetts) were used to process the data. In the analysis of participant characteristics, continuous variables were expressed as the “mean ± standard deviation,” and categorical variables were expressed as weighted percentages (%). χ2 tests and Kruskal‒Wallis tests were used to assess the significance of categorical and continuous variables, respectively. Univariate analysis of variance was used to assess the relation between each covariate and HUA. Multinomial logistic regression analysis with five adjusted models was used to investigate the association between CDAI and HUA, and the stability of the association was assessed by stratified analysis. The 95% confidence intervals were calculated. was considered statistically significant in this study.
3. Result
3.1. Baseline Characteristics of Participants
A total of 8761 participants were included in the analysis (1904 with HUA vs. 6857 with non-HUA). Participants’ CDAI ranged from −7.177 to 88.502. Patients with HUA had lower CDAI scores (0.98 ± 3.47 vs. 1.45 ± 3.88, ). In addition, patients with HUA are more likely to be older, to have a high BMI, and to have hypertension and glucose-related disorders. Table 1 describes the participants’ characteristics in detail.
3.2. Analysis of Factors Associated with HUA
In the univariate analysis, several covariates were selected as independent exposure variables in this study to determine the factors that interfered with the association between CDAI and HUA. The results of the univariate analysis indicated that age, sex, race, household income to poverty ratio, marital status, BMI, gamma glutamyl transferase, triglycerides, total cholesterol, HDL cholesterol, creatinine, dietary energy intake, hypertensive status, diabetes status, smoking status, and leisure activity status were statistically significant (), demonstrating that they may be potential confounding factors. The results of the univariate analysis are described in detail in Table 2.
3.3. Association between CDAI and HUA
Figure 2 describes the association between the CDAI and HUA. Participants in the study were equally allocated into four groups according to the CDAI. The multinomial logistic regression included one crude and five adjusted models. A negative and statistically significant association of CDAI with HUA was observed in all six models. In model 5, which adjusted for all confounders, participants in the CDAI Q4 group (highest) had a 35% lower risk of suffering from HUA than those in the Q1 group (lowest) (OR = 0.65, 95% CI 0.51, 0.82, ). To visualize the association between the CDAI and HUA, smoothed curve fits were plotted according to adjusted model 5. The results are shown in Figure 3, where the CDAI is negatively associated with HUA.
3.4. Stratification Analysis
Statistically significant covariates from the univariate analysis were included in the stratified analysis to assess the stability of the association between CDAI and HUA in different populations. All covariates in the stratified analysis except for the stratified variables were adjusted. CDAI shows a negative association with HUA in the vast majority of subgroups, except in the few subgroups where a positive association is observed. In addition, no statistically significant results are observed for any subgroups with positive associations. The results suggest that the CDAI has stability in its negative association with HUA and may be a valid protective factor for HUA. Table 3 describes the detailed results of the stratified analysis.
4. Discussion
This research analysed the most representative US population data (4244 males and 4571 females) and found a negative association between CDAI and the incidence of HUA in the population, which confirmed our hypothesis. These results suggest that appropriate modifications in the level and proportion of antioxidants in the diet may facilitate the prevention and treatment of HUA.
This is the first large-scale study to consider the association between a composite of dietary antioxidants and HUA. Although previous studies have researched the effects of dietary antioxidants such as vit C, vit E, and Zn on HUA, they have not been considered in combination. In the average person’s daily diet, it is clear that a single antioxidant intake is difficult to achieve, and it is more likely that a variety of foods and multiple antioxidants are absorbed. In addition, there is no single antioxidant component in food, for example, tomatoes, are rich in vit A, vit E, vit C, Mn, and many other antioxidants [22, 23]. Therefore, a comprehensive study on the effects of dietary antioxidants on HUA is necessary.
The composition of dietary antioxidants includes vit A, C, and E; Mn; Se; and Zn. There is a large amount of research in the field reporting the association, causality, and mechanism of the effect of individual nutrients on HUA. A study of 1387 males showed a negative association between vit C intake and HUA [24]. Studies by Huang et al. also showed that vit C intake can reduce serum uric acid levels and prevent the development of gout [25, 26]. Current reports in the field of vit C reducing serum uric acid focus on the renal excretion mechanism. Two vit C transport proteins, SLC23A1 and SLC23A2, existing in proximal renal tubular epithelial cells, can alter the activity of URAT1 in renal tubular cells, thus promoting uric acid excretion and reducing serum uric acid levels [27–31]. The mechanism of xanthine oxidase (XO) inhibition is also of concern. An in vitro study reported that vit C and vit E could inhibit XO activity. Studies have also suggested a negative association between vit E and HUA [12, 13, 32]. Similar associations and mechanisms have also been reported for dietary Zn [14, 33–35]. The role of Se in HUA is currently controversial, with some studies claiming a negative association between serum selenium and uric acid levels [15, 36]. However, other studies have suggested the opposite. The difference may be related to the source of Se [37]. This suggests that we consider the role of other substances in food while increasing the dietary intake of antioxidants. Ma et al. showed a negative association between Mn and uric acid levels [16].
There is a near consensus that XO plays a crucial role in uric acid metabolism. Uric acid is generated during the XO-catalyzed conversion of hypoxanthine and xanthine and is accompanied by the production of reactive oxygen species (ROS) [38]. Furthermore, uric acid increases the production of inflammatory factors and reduces the amount of free radical nitric oxide (NO) in cells, which can lead to an increase in ROS levels and oxidative stress, with the contribution of XO [39, 40]. This process can activate osteoclasts and inhibit osteoblasts, resulting in increased bone loss and triggering osteoporosis and bone destruction [39, 41–43]. Several antioxidants have been reported to function as XO inhibitors, reducing serum uric acid levels and scavenging intracellular oxygen radicals, thereby ameliorating the impairment of hyperuricemia. Zeng et al. showed that baicalein and baicalein, two antioxidants widely present in plants, could bind to the FAD center of XO and inhibit XO activity, suppressing uric acid production and oxidative stress levels [38]. Ellagic acid, another natural antioxidant, has also been found to inhibit XO and scavenge superoxide anions (O2−), ameliorating hyperuricemia [44]. Moreover, the inhibition of XO also contributes to increased bone formation by promoting osteoblast differentiation, which may be associated with the inhibition of ROS [39, 45–47]. We hypothesize that the association of a high CDAI with a low risk of hyperuricemia may be attributable to the inhibition of dietary antioxidants on XO. In fact, Li et al. showed that vit C supplementation reduced XO activity in hyperuricemic rats and decreased ROS levels by inhibiting TGF-beta [11]. Similar findings have also been reported in other studies [12, 44, 48, 49]. However, studies exploring the inhibitory capacity of these antioxidants against XO and their mechanisms are still insufficient. Our findings may provide valuable insights for further research.
In this study, the association between the CDAI and hyperuricemia was explored through a cross-sectional study that included 8761 participants. Different models were constructed to exclude the effect of confounding factors on the results. The results showed that the negative association between CDAI and hyperuricemia was stable across the different models. In the final adjusted model 5, the Q4 group (highest) had a 35% lower risk of suffering from HUA than the Q1 group (lowest) (OR = 0.65, 95% CI 0.51, 0.82, ). This suggests that the treatment of hyperuricemia may be facilitated by adjusting the ratio of antioxidants in the diet.
To summarize, the CDAI is negatively associated with HUA. However, there are still some limitations to our study. First, we cannot determine the causal relation between the CDAI and HUA, which is limited because our research is a cross-sectional study. Although a large number of studies have shown that dietary antioxidants reduce serum uric acid levels, further cohort studies and clinical trials are needed to determine the causal relationship between CDAI and HUA and the therapeutic value of CDAI. Second, although a large number of participants were included in this study, it was limited to US residents only. Considering the differences between a variety of factors, such as body composition, lifestyle, and dietary habits of residents in different countries and regions, multicenter controlled trials are needed to validate our findings.
5. Conclusion
Our study suggests that there is a significant and stable negative association between CDAI and HUA in the population. This suggests that the CDAI may be an effective protective factor for HUA and holds promise as a preventive and therapeutic tool for HUA.
Abbreviations
BMI: | Body mass index |
CDAI: | Composite dietary antioxidant index |
HUA: | Hyperuricemia |
IFG: | Impaired fasting glucose |
IGT: | Impaired glucose tolerance |
NHANES: | National Health and Nutrition Examination Survey |
Mn: | Manganese |
Se: | Selenium |
Vit: | Vitamin |
Zn: | Zinc. |
Data Availability
The datasets generated and/or analysed during the current study are available in the NHANES repository (https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2007, https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2009, https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2011, https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2013, https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2015, and https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2017).
Ethical Approval
All procedures performed in studies involving human participants followed the ethical standards of the Institutional and National Research Committee and the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Consent
Informed consent was obtained from all participants included in the study.
Disclosure
Zhenzong Lin and Haokai Chen should be regarded as co-first authors.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Authors’ Contributions
Zhenzong Lin and Haokai Chen contributed equally to this work.