Higher Pro-Inflammatory Dietary Score is Associated with Higher Hyperuricemia Risk: Results from the Case-Controlled Korean Genome and Epidemiology Study_Cardiovascular Disease Association Study

In previous studies, the elevated dietary inflammatory index (DII®) scores have been consistently associated with several chronic diseases. However, the relationship with hyperuricemia remains unknown. The aim of this study was to determine if the DII is associated with hyperuricemia risk. The study included 13,701 participants (men 5102; women 8599) in a large-scale cross-sectional study in South Korea. A validated semi-quantitative food frequency questionnaire (SQFFQ) was used to measure dietary intake, and blood samples were obtained to determine hyperuricemia. As the DII score increased, the hyperuricemia risk increased among women (OR 1.35, 95% CI 1.03–1.77, p trend = 0.02). However, no significant results were found for men. Women with lower BMI scores had higher risks of hyperuricemia with higher DII scores (OR 1.62, 95% CI 1.05–2.52, p trend = 0.03). As the DII increased, however, only women who consumed alcohol (“past or current drinkers”) had higher risks of hyperuricemia (OR 1.92, 1.22–3.02, p trend = 0.004). Among the DII components, intake of flavonoids showed a significant association with the hyperuricemia risk in women (OR 0.75, 0.59–0.96, p trend = 0.03). Our results suggest that higher intake of pro-inflammatory diet is significantly associated with higher risk of hyperuricemia among women. These results reinforce the importance of less pro-inflammatory habitual dietary patterns in lowering the risk of hyperuricemia and secondary afflictions such as cardiovascular diseases.


Introduction
Uric acid is the final product of purine metabolism in the human body. Hyperuricemia is the state of excessive uric acid retention. As hyperuricemia can be linked to major disease such as gout, chronic kidney disease and cardiovascular disease, strategies for its prevention are crucial for improved public health [1][2][3][4]. For example, it was found that 18.8% of hyperuricemic patients experienced gout within a follow-up period of five years [1], and that hyperuricemia was highly prevalent among those with renal failure [2]. Additionally, hyperuricemia was found to be strongly associated with cardiovascular disease [3].

Data Collection
All of the study participants provided biomarkers according to standard procedures. The body height and weight of the participants were measured with subjects wearing light indoor clothing and without shoes. The body-mass index (BMI) was calculated as: weight (kg)/height (m) 2 . Blood pressure was measured on the right arm after resting in a quiet room for 5 min using a standard mercury sphygmomanometer (Baumanometer, W.A. Baum Co. Inc., Copiague, NY, USA). With each subject seated, a properly sized cuff placed along the mid-arm circumference at the heart level. The arm circumference was measured twice at 5 min intervals and the average of the two measurements was used.
Blood samples were collected from all of the study participants after at least 10 h of fasting. For long-term storage, the serum and plasma were separated and aliquoted in 6-10 vials (300-500 μL per vial), after which all of the samples were transported to the National Biobank of Korea [26]. Laboratory evaluations were performed in the same core clinical laboratory that is accredited and participates annually in inspections and surveys by the Korean Association of Quality Assurance for Clinical Laboratories. Blood concentrations of glucose, TC, HDL-cholesterol, and TG were measured using the enzyme method (ADVIA 1650 and ADVIA 1800; Siemens Healthineers, Deerfield, IL, USA). Serum concentrations of HDL-cholesterol and TG were determined using enzymatic methods (ADVIA 1650 Chemistry System, Bayer, Leverkusen, Germany). Hs-CRP was measured using a turbidimetric assay method (ADVIA 1650 and ADVIA 1800; Siemens Healthineers).
During the examination, sociodemographic information, family and personal medical history, nutrition intake, and physical activity consistency were obtained. Marital status was stratified into those who are married and those who are single/divorced/widowed/separated. Education status was divided into three categories: education up to elementary school, middle school to high school, and college education or above. Household income levels were divided into four categories: less than 1,000,000 won, between 1,000,000 and 2,000,000 won, between 2,000,000 and 3,000,000 won, and more than 4,000,000 won. With regard to smoking status, those who had smoked more than about 400 cigarettes and were continuing to smoke at the time of the survey were classified as "current" smokers; those who had smoked more than about 400 cigarettes but had stopped smoking by the time of the survey were designated as "past" smokers, and those who had not smoked more than 400 cigarettes were classified as "never" smokers. Drinking status was divided into three groups: Those who had consumed alcohol and were still drinkers at the time of the survey were deemed "current" drinkers; those who had consumed alcohol but were abstaining from drinking at the time of the survey were designated "past" drinkers, and those who had never consumed alcohol were classified as "never" drinkers. Regularity of physical activity was determined according to whether or not subjects

Data Collection
All of the study participants provided biomarkers according to standard procedures. The body height and weight of the participants were measured with subjects wearing light indoor clothing and without shoes. The body-mass index (BMI) was calculated as: weight (kg)/height (m) 2 . Blood pressure was measured on the right arm after resting in a quiet room for 5 min using a standard mercury sphygmomanometer (Baumanometer, W.A. Baum Co. Inc., Copiague, NY, USA). With each subject seated, a properly sized cuff placed along the mid-arm circumference at the heart level. The arm circumference was measured twice at 5 min intervals and the average of the two measurements was used.
Blood samples were collected from all of the study participants after at least 10 h of fasting. For long-term storage, the serum and plasma were separated and aliquoted in 6-10 vials (300-500 µL per vial), after which all of the samples were transported to the National Biobank of Korea [26]. Laboratory evaluations were performed in the same core clinical laboratory that is accredited and participates annually in inspections and surveys by the Korean Association of Quality Assurance for Clinical Laboratories. Blood concentrations of glucose, TC, HDL-cholesterol, and TG were measured using the enzyme method (ADVIA 1650 and ADVIA 1800; Siemens Healthineers, Deerfield, IL, USA). Serum concentrations of HDL-cholesterol and TG were determined using enzymatic methods (ADVIA 1650 Chemistry System, Bayer, Leverkusen, Germany). Hs-CRP was measured using a turbidimetric assay method (ADVIA 1650 and ADVIA 1800; Siemens Healthineers).
During the examination, sociodemographic information, family and personal medical history, nutrition intake, and physical activity consistency were obtained. Marital status was stratified into those who are married and those who are single/divorced/widowed/separated. Education status was divided into three categories: education up to elementary school, middle school to high school, and college education or above. Household income levels were divided into four categories: less than 1,000,000 won, between 1,000,000 and 2,000,000 won, between 2,000,000 and 3,000,000 won, and more than 4,000,000 won. With regard to smoking status, those who had smoked more than about 400 cigarettes and were continuing to smoke at the time of the survey were classified as "current" smokers; those who had smoked more than about 400 cigarettes but had stopped smoking by the time of the survey were designated as "past" smokers, and those who had not smoked more than 400 cigarettes were classified as "never" smokers. Drinking status was divided into three groups: Those who had consumed alcohol and were still drinkers at the time of the survey were deemed "current" drinkers; those who had consumed alcohol but were abstaining from drinking at the time of the survey were designated "past" drinkers, and those who had never consumed alcohol were classified as "never" drinkers. Regularity of physical activity was determined according to whether or not subjects participated regularly in any sports to the point of sweating. The history of diabetes and hypertension were indicated as "Yes" if diagnosed.

Diagnostic Criteria
Hyperuricemia was defined as a serum uric acid level of >7 mg/dL for men and >6 mg/dL for women, which are similar to the diagnostic criteria used in other studies, including in China [27][28][29]. A total of 1515 incident hyperuricemia cases were identified.

Dietary Assessment Using SQ-FFQ and Calculation of DII
To gather information on the subjects' dietary intakes, they were asked to complete a validated semi-quantitative food frequency questionnaire (SQFFQ). Detailed information on the SQFFQ is available elsewhere [30,31]. Based on the SQFFQ, consumption frequencies and average amounts of 106 food items were determined. The frequencies were measured according to nine response categories ranging from "almost never" to "more than three per day." Portion size was measured based on three responses including 1/2 serving, 1 serving, and 3/2 servings. Daily nutrient intake was estimated by combining obtained information on serving frequency per day, portion per unit for each food item, and average serving number. The food composition table of the Korean Health and Industry of Development was used in the calculation of nutrient intake and total energy [32].
These pro-inflammatory parameters were included: total calories, cholesterol, carbohydrate, protein, total fat, saturated fatty acids, and vitamin B-12. These anti-inflammatory parameters were included: vitamin A, vitamin B-6, vitamin C, vitamin D, vitamin E, niacin, magnesium, riboflavin, beta-carotene, isoflavones, flavan-3-ol, flavanols, flavones, folic acid, fiber, alcohol, ginger, garlic, pepper, MUFAs, PUFAs, and tea. The present study utilized nutritional content data from the Functional Ingredients Table (Rural Development Administration), Computer Aided Nutritional Analysis (The Korean Nutrition Society), and the U.S. Department of Agriculture. From our SQFFQ 37 of the 45 parameters were available and these were as follows: carbohydrate, protein, fat, fiber, cholesterol, carotene, caffeine, energy, n-3 fatty acids, n-6 fatty acids, trans fat, saturated fat, mono-unsaturated fat, poly-unsaturated fat, niacin, thiamin, riboflavin, falvan-3-ol, flavones, flavonols, flavonones, anthocyanidins, isoflavones, vitamin B12, vitamin B6, iron, magnesium, zinc, selenium, vitamin A, vitamin C, vitamin D, vitamin E, folic acid, onion, garlic and tea. As a comparative standard for those parameters, a world database consisting of diet surveys from 11 countries was used [33]. The DII scores were calculated based on the database's intake values, the details on which are available elsewhere [33]. In brief, a standard mean for each parameter from the database was subtracted from the actual individual exposure. The results were then divided by their standard deviation to generate Z scores. Those were converted to proportions to minimize the effects of outliers. The proportions were multiplied by two and then one was subtracted to achieve symmetrical distributions with values centered around 0. The results were then multiplied by the complementary inflammation score for each food parameter, which were all summed to obtain the overall DII score. In the DII score calculation, intakes from both foods and supplements were included. Several studies have found and validated the association between DII score and inflammatory markers in various populations [14][15][16][17][20][21][22][23][24].

Statistical Analysis
All of the statistical analyses were performed with SAS ® 9.3 (SAS Institute, Cary, NC, USA). For continuous variables such as age (years), energy intake (kcal), BMI, and hs-CRP levels, the results were expressed as medians (25%, 75%). Also, the following categorical variables were expressed as n (%). The chi-square test and t-test were used to compare categorical and continuous variables according to the case-control status of hyperuricemia. The DII score of the control group was divided into quartiles according to gender, and the range was applied to the group with hyperuricemia. The odds ratios and the corresponding 95% confidence intervals (ORs; 95% CIs) were estimated using logistic regression models, adjusting for age and additionally for smoking status, drinking status, education, BMI, daily caloric intake, hs-CRP, and region. Tests for trends were performed using DII as a continuous variable. Stratified analyses were carried out according to BMI and drinking status. The p value for interaction was calculated by contrasting the coefficients of the cross-product of BMI or drinking status and DII quartile in the multivariable logistic regression model. Flavonoid intake level of the DII component was divided into four levels in the control group in women. p values <0.05 were considered statistically significant.

Results
In the present study, 12,186 controls and 1515 hyperuricemia cases were included ( Table 1). The DII scores were higher in female hyperuricemia cases than in controls. Compared with the controls, the cases were older, heavier (higher BMI), consumed fewer calories, had larger waist circumferences, and higher hs-CRP, homeostatic model assessment of insulin resistance (HOMA-IR), glucose and triglyceride. The percentages of past or current smokers and drinkers were higher in men with hyperuricemia than in women, while the hypertension-history rate was higher in women with hyperuricemia than in men.
The results of the multivariate logistic analysis suggested that people with hyperuricemia were more likely to be those in the highest quartile of the DII (Q4) (OR 1.23, 95% CI 1.03-1.46, p for trend = 0.02). The results also are reported by gender in Table 2. Among women, participants who had higher DII scores (Q4) had a significantly higher hyperuricemia risk (OR 1.35, 95% CI 1.03-1.77, p for trend = 0.02). No statistically significant association between DII and hyperuricemia risk was observed among the men (OR 1.10, 95% CI 0.87-1.39, p for trend = 0.49).
The association between hyperuricemia risk and DII score, as stratified by BMI and drinking status, was investigated (Table 3). Women with low BMI had higher risk of hyperuricemia for the DII quartiles (OR 1.62, 95% CI 1.05-2.52, p for trend = 0.03), while no association was found among those with high BMI scores (OR 1.19, 95% CI 0.84-1.68, p for trend = 0.34). However, a contrasting result was found among men, for whom there was no statistically significant association between hyperuricemia risk and DII score (OR 1.02, 95% CI 0.73-1.42, p for trend = 0.96; OR 1.18, 95% CI 0.85-1.67, p for trend = 0.27) in men with either a low or a high BMI score. Women drinkers showed a significant increase in hyperuricemia risk (OR 1.92, 95% CI 1.22-3.02, p for trend = 0.004), while no association was found among non-drinkers (OR 1.12, 95% CI 0.80-1.57, p for trend = 0.48). Among the men, both drinkers and non-drinkers showed only an insignificant increase in hyperuricemia risk according to their DII scores (OR 1.05, 95% CI 0.56-1.98, p for trend = 0.83; OR 1.12, 95% CI 0.86-1.42, p for trend = 0.49).
The association between flavonoids intake and hyperuricemia risk in women is shown in Table 4. High scores for flavan-3-ol, flavones, flavonols and flavonones were found to be significantly associated with decreased ORs for hyperuricemia risk in the women. Increased flavonoids, which represented the sum of those four components, were correlated with decreased risk of hyperuricemia (OR 0.75, 95% CI 0.59-0.96, p trend = 0.03).

Discussion
The present cross-sectional study based on data from the KoGES_CAVAS cohort aimed to explore the association between DII score, which represents diet-based inflammatory state, and hyperuricemia risk. The study found that higher DII scores (more pro-inflammatory diets) were associated with higher risk of hyperuricemia among women. Women in the highest DII score quartile (=Q4) had a 22% higher risk of hyperuricemia than those in the lowest DII score quartile (=Q1) after adjusting for potential confounders. The results of the current study were consistent with our hypothesis, which is that diet's inflammatory potential can influence hyperuricemia risk. We assumed that in a state of inflammation, the body makes more uric acid or cannot excrete uric acid properly, which leads to hyperuricemia. In turn, hyperuricemia may worsen the state of inflammation, which condition can lead to gout or other autoimmune diseases. As the physiological mechanism of inflammation's causative role with respect to hyperuricemia is not yet clearly known, future studies should be designed to address this issue.
The present study also found a statistically significant association between the DII and increased hyperuricemia risk among women with a BMI lower than 25 kg/m 2 ; a finding which does not coincide with the results of previous studies that found a positive correlation between uric acid level and obesity [34][35][36][37]. However, other studies found that being either overweight or underweight was associated with higher inflammation in various populations, which might explain why women with low BMI scores had a significantly positive result for the relation of DII with hyperuricemia risk [38,39]. In any case, further research that can confirm the present results is called for.
Additionally, the present study found a statistically significant association between the DII and hyperuricemia risk among women drinkers. Previous studies had found that ethanol intake increases serum uric acid level via both decreased urate excretion and increased production [40][41][42][43]. Additionally, beer and serum uric acid are positively related due to beer's high purine contents [42], which might explain the enhanced risk of hyperuricemia among those who consumed alcohol. Alcohol gets an anti-inflammatory score on the DII. Across all of the papers that were reviewed, alcohol, on average, exerted an anti-inflammatory effect. It is important to note that these effects are seen within the normal physiologic range. Of course, severe abuse of alcohol, which exerts a pro-inflammatory effect, is ill-advised. Additionally, when considering diet's inflammatory potential, overall diet is key, and if people are consuming high amounts of alcohol, then it could mean that they are also consuming high amounts of carbohydrates and energy, which have pro-inflammatory scores on the DII.
The present study also found that hyperuricemia risk decreased as the quartile of flavonoids, which are DII components, increased. Flavonoids are products of the secondary metabolism of many edible plants. Flavonoids intake is inversely associated with cardiovascular disease, type 2 diabetes mellitus, hypertension, stoke risk, myocardial infarction, coronary heart disease, nonalcoholic fatty liver disease, dementia, and colorectal cancer [44][45][46][47][48][49][50][51][52][53]. Various studies on flavonoids suggest that they are antioxidants that are able to reduce free radical formation as well as the number of free radicals [54,55]. Oxidative stress is known to activate a variety of transcription factors, such as inflammatory cytokines, that can lead to the expression of various genes [56]. It is associated with activation of reactive oxygen species, which are supplemented by antioxidants such as flavonoids to reduce cellular oxidants, which, in turn, can prevent hyperuricemia. One study reported that flavonoids are related to ã-aminobutyric acid type A (GABA A ) receptor for preventing alcohol use disorders [57]. We also performed a joint analysis of alcohol consumption and flavonoid intake for the risk of hyperuricemia. The results showed that the interaction of alcohol consumption and flavonoid intake was not significant (p = 0.23, data not shown), and the combined effect was significant, but it was similar to these factors' respective single effects.
In the present study, the association between the DII and hyperuricemia risk differed by gender. While statistically significant results were shown among the women participants, no such results were observed among the men. Also in the subgroup analyses, statistically significant results were shown only among the women participants. Whereas there are no available studies on the association between the DII and the hyperuricemia risk that could be used for comparison, there has been some research stressing the importance of estrogen in promoting excretion of uric acid [58][59][60]. Estrogen, in fact, has been hypothesized to have a protective anti-inflammatory effect [61,62]. As the mean age of the present study's women participants was older than the mean age at menopause among Korean women (49.2 years), the number of postmenopausal women in this study might have been the majority; if so, the results on hyperuricemia risk well might have been skewed higher [63]. Another important factor to consider is the role of tobacco smoke as a pro-inflammatory agent. It may be that the effect of tobacco swamps the effect of dietary sources of inflammation [64]. The fact that men smoked at about 10 times the rate of women in this study (75% of men were past or present smokers vs. only about 7% of women) may help to explain the sex differences observed in our study. More research on the issue of whether DII affects the risk of hyperuricemia only in women is needed.
Underlying our observations and understanding from all of the many studies that have been conducted to date using the DII are two countervailing effects [33,65,66]. The first is a tendency to eat more of everything as one increases caloric intake; this results in a positive correlation between caloric intake and nutrient intake. The other is the "healthy eater" effect (e.g., due to the intention of careful, health-conscious people to choose nutrient-dense, energy-sparse foods in preference to calorie-dense, nutrient-sparse foods). This type of eater produces data that results in negative correlations between caloric density and nutrient density. In this study, we anticipated the former to be happening; hence, we saw higher DII scores among women with hyperuricemia but lower values of not only pro-inflammatory components like energy and macronutrients but also fruits that contain vital micronutrients and other bio active compounds considered to be anti-inflammatory. In the DII calculation, there is no differentiation between complex and simple carbohydrates, and there is no overall inflammatory effect score for it, because when the literature search was done for carbohydrates, we did not find many articles demarcating them. A similar approach was used for proteins, as there was not enough research demarcating protein from animal proteins. However, these demarcations will again be considered in the next iteration of the DII, which will be developed sometime in the future.
There are three limitations to the present study, which should be duly considered in considering its results. First, the research participants were recruited in 11 rural areas of the National Health Examination Registry, but only those willing to participate were enrolled; consequently, more women enrolled than men; their proportion in this study does not represent the general population. This sort of screening bias occurs in many prospective cohort studies [67]. Second, possible confounding variables existed and could have affected the outcome. The present study adjusted for sex, smoking status, drinking status, education, BMI, age, daily caloric intake, CRP and region, which are potential confounding, as they affect both exposure and outcome. However, there may be variables that can affect hyperuricemia, such adiposity (expressed as a sum of skinfold thickness measurements) or creatinine levels [68]. Third, the questionnaire-derived data utilized in this study might not accurately reflect the subjects' usual dietary intakes. The questionnaire contains a list of limited food items, and individuals cannot accurately report food intake retrospectively over a long period of time. Even with these limitations, the present study highlights the potential harmful effects of pro-inflammatory dietary patterns with respect to hyperuricemia risk. The results underline the importance of consuming a more anti-inflammatory diet as a strategy to lower the risk of hyperuricemia. intervention in clinical settings. NS is an employee of CHI. The remaining authors declare that they have no conflicts of interest.