Joint Bone Spine 81 (2014) 513–519
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Original article
The effect of vitamin C intake on the risk of hyperuricemia and serum uric acid level in Korean Multi-Rural Communities Cohort Jisuk Bae a , Dong Hoon Shin b , Byung-Yeol Chun c , Bo Youl Choi d , Mi Kyung Kim d , Min-Ho Shin e , Young-Hoon Lee f , Pil Sook Park g,∗,1,2 , Seong-Kyu Kim h,∗,1 a
Department of Preventive Medicine, Catholic University of Daegu School of Medicine, Daegu, Republic of Korea Department of Preventive Medicine, School of Medicine Keimyung University, Daegu, Republic of Korea c Department of Preventive Medicine, School of Medicine, Health Promotion Research Center, Kyungpook National University, Daegu, Republic of Korea d Department of Preventive Medicine, Hanyang University, College of Medicine, Seoul, Republic of Korea e Department of Preventive Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea f Department of Preventive Medicine & Institute of Wonkwang Medical Science, Wonkwang University College of Medicine, Iksan, Jeonlabuk-do, Republic of Korea g Department of Food and Nutrition, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, Republic of Korea h Division of Rheumatology, Department of Internal Medicine, Arthritis and Autoimmunity Research Center, Catholic University of Daegu School of Medicine, 3056-6 Daemyung 4-Dong, Namgu, Daegu 705-718, Republic of Korea b
a r t i c l e
i n f o
Article history: Accepted 22 May 2014 Available online 3 July 2014 Keywords: Vitamin C Uric acid Hyperuricemia
a b s t r a c t Objective: The aim of this study was to determine the association between vitamin C intake and risk of hyperuricemia or serum uric acid levels in male and female subjects in the Korean Multi-Rural Communities Prospective Cohort. Methods: This cross-sectional analysis was conducted in 9400 subjects enrolled in the Korean Multi-Rural Communities Cohort Study. The risk of hyperuricemia was assessed in five quintiles (Q1 to Q5) according to dietary and total vitamin C intake using multivariate-adjusted logistic regression models. Relationships between serum uric acid levels and vitamin C intake were evaluated using linear regression analysis after adjustment for covariates. Information about dietary components was collected using validated food frequency questionnaires. Results: Dietary vitamin C intake, but not total vitamin C intake, was significantly different between hyperuricemic and non-hyperuricemic subjects in males (P = 0.01) and females (P = 0.02). The risk of hyperuricemia decreased with increased dietary vitamin C intake in male and female subjects after multivariate adjustment (P for trend = 0.002 in males and P for trend = 0.02 in females). An effect of total vitamin C intake on hyperuricemia risk was identified in females (P for trend = 0.04), but not males (P for trend = 0.06). Serum uric acid level was linearly associated with total vitamin C intake in females ( = −0.0001, P = 0.01), but not with dietary vitamin C intake in either gender. Conclusion: This study showed that vitamin C intake might be in part responsible for hyperuricemia or serum uric acid level in the Korean Multi-Rural Communities Cohort. © 2014 Société franc¸aise de rhumatologie. Published by Elsevier Masson SAS. All rights reserved.
1. Introduction Uric acid is produced through hepatic metabolism of purine, which comes from endogenous and exogenous sources [1,2]. In humans, serum uric acid levels are determined by the balance between urate production and excretion. Hyperuricemia can
∗ Corresponding authors. Tel.: +82 53 6503038; fax: +82 53 6298248. E-mail addresses:
[email protected] (P.S. Park),
[email protected] (S.-K. Kim). 1 Two corresponding authors contributed equally to this paper. 2 Tel: +82-53-9506236, Fax: +82-53-9506229.
occur from urate overproduction or impaired urate excretion through the kidney and gastrointestinal tract. Evidence about lifestyle or dietary factors that cause uric acid metabolism leading to changes of serum uric acid levels comes from epidemiologic observations and clinical trials [3]. Factors related to increased risk of hyperuricemia include intake of purine-rich foods, alcohol, and fructose-containing products. Intake of vitamin C and dairy products lowers serum uric acid levels. Several studies in humans suggest that vitamin C supplementation reduces serum uric acid level [4–6]. Although the uricosuric mechanism is not clearly defined, the uric acid-lowering effect of vitamin C is associated in clinical studies with enhanced urinary excretion of uric acid by
http://dx.doi.org/10.1016/j.jbspin.2014.05.007 1297-319X/© 2014 Société franc¸aise de rhumatologie. Published by Elsevier Masson SAS. All rights reserved.
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vitamin C [4,5]. A possible explanation is competitive interaction between vitamin C and urate-reabsorbing transporters, such as URAT1 and ABCG2, which are responsible for urate-anion exchange in proximal tubules [1]. However, different opinion that ascorbic acid could inhibit synthesis of urate was also reported [7]. Recently, an observational study using data from the Health Professional Follow-up Study (HPFS) demonstrated an inverse relationship between vitamin C intake and serum uric acid concentration in male subjects [8]. A prospective cohort study found that higher vitamin C intake independently reduced the risk of gout [9]. Meta-analysis of 13 randomized controlled trials found that vitamin C supplementation reduced serum uric acid levels in diverse and heterogeneous populations [10]. Vitamin C supplementation lowers serum uric acid levels in healthy nonsmokers [11]. However, vitamin C (500 mg/day) reduction of serum uric acid levels was not reproducible in established gout patients [12]. Inconsistencies in the reported relationship between vitamin C and serum uric acid level are likely to be the result of varying characteristics in study populations. Little information about the relationship between vitamin C intake and uric acid levels is available for Asian populations. The aim of this study was to determine the effect of dietary vitamin C on serum uric acid levels and the risk of hyperuricemia in the Korean Multi-Rural Communities Cohort study population. 2. Methods 2.1. Study population As a part of the Korean Genome Epidemiology Study, the Korean Multi-Rural Communities Cohort has been constructed since 2004. This multi-center prospective cohort was aimed to elucidate risk factors for cardiovascular diseases in the Korean population. The eligible subjects of the cohort were males and females who aged ≥ 40 years at enrollment in three geographically-defined rural areas nationwide. The study areas included Yangpyeong (located in the eastern part of Seoul, the capital of South Korea), Namwon (located in the southwestern part of South Korea), and Goryeong (located in the southeastern part of South Korea). As of August 2009, a total of 9697 study participants were recruited in the cohort. Of the eligible subjects, we excluded subjects with missing data on dependent (serum uric acid level) or independent variables (as an exception, subjects with missing data on supplemental vitamin C intake were included in the final dataset, but excluded from the analyses of total vitamin C intake as an independent variable), and subjects with implausible self-reports on dietary intake (total energy intake < 500 or > 4000 kcal/day; more than 10 missing food items; or missing data on rice, the staple food for most Koreans). As a result, the total number of eligible subjects was 9400 for the final analyses. This study was carried out in adherence with the guidelines of the Declaration of Helsinki and approved by the Institutional Review Boards of Hanyang University, Chonnam National University Hospital, and Keimyung University in Korea. 2.2. Data collection A standardized protocol for questionnaire survey and examination procedures was used to collect uniform data at each study center. All interviewers and examiners were trained at the coordinating center. A structured questionnaire, which provided information on demographic characteristics (i.e., age, gender, education, and marital status), medication history (i.e., anti-hypertensive medication), lifestyle factors such as cigarette smoking, alcohol consumption, and physical activity, was administered by trained interviewers. Various anthropometric indices such as height, weight, waist circumference, and systolic and diastolic pressures were directly measured based on the protocol. Body mass
index (BMI) was calculated as the weight in kilograms divided by the square of the height in meters. Clinical laboratory tests for baseline information were also applied to the study subjects. Each subject provided 20 mL of blood in the overnight fasting state (at least 8 hours of fasting) and 40 mL of mid-stream urine. Biochemical markers, such as serum uric acid, creatinine, triglyceride, HDL cholesterol, fasting serum glucose levels, were assessed the same day the blood sample was taken using the ADVIA1800 Auto Analyzer (Simens Medical Solutions USA, Inc., Malvern, PA, USA). Glomerular filtration rate (GFR) was calculated using the simplified equation of the Modification of Diet in Renal Disease Study [13]: GFR (mL/minute per 1.73 m2 ) = 186 × (serum creatinine level [mg/dL])−1.154 × (age)−0.203 × [0.742, if females]. 2.3. Dietary assessment Data on dietary intake were collected by trained interviewers using a semi-quantitative food frequency questionnaire, of which validation was assessed, and the results have been reported in detail elsewhere [14]. We estimated the average daily intakes of each food item (i.e., intakes of meat, seafood, dairy food, coffee, tea, and soft drink) using the weighted frequency per day and the portion size per unit of each food item. The seventh edition of the Food Composition Table [15], a nutrient database produced by the Korean Nutrition Society, was used to convert intakes of food items into nutrients (i.e., total energy and dietary vitamin C). Supplemental vitamin C intake was determined by the brand, frequency, amount, and duration of the use of multivitamin or vitamin C supplements over the past year. Total vitamin C intake was the sum of dietary and supplemental vitamin C intake. 2.4. Statistical analysis All descriptive data are presented as mean ± standard deviation (SD) for continuous variables and frequency and percentage for categorical variables. In order to compare the differences in means and proportions between two groups, Student’s t-tests or Chi2 tests were applied as appropriate. We carried out analyses separately according to gender. Hyperuricemia was defined as serum uric acid levels > 7.0 mg/dL in males and > 6.0 mg/dL in females [16]. Dietary vitamin C intake without supplement (< 42.5, 42.5–61.8, 61.9–84.7, 84.8–119.2, and ≥ 119.3 mg/day in males; < 39.4, 39.4–60.2, 60.3–85.2, 85.3–123.5, and ≥ 123.6 mg/day in females) and total vitamin C intake (< 43.8, 43.9–65.7, 65.8–94.3, 94.4–152.7, and ≥ 152.8 mg/day in males; < 41.2, 41.3–65.0, 65.1–95.5, 95.6–170.5, and ≥ 170.6 mg/day in females) were categorized into gender-specific quintiles. The differences in means across gender-specific quintiles were assessed by analysis of variance. We used multivariate logistic regression models to investigate the association between hyperuricemia and vitamin C intake. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated after adjusting for total energy (quintiles), age (< 50, 50–59, 60–69, 70–79, and ≥ 80 years), cigarette smoking (nonsmoker, former smoker, and current smoker), alcohol drinking (non-drinker, former drinker, and current drinker), regular exercise (yes or no), BMI (< 25.0 and ≥ 25.0 kg/m2 ), triglyceride (< 150 and ≥ 150 mg/dL), fasting serum glucose (< 100 and ≥ 100 mg/dL), anti-hypertensive medication (in the past 2 weeks; yes or no), GFR (< 60.0 and ≥ 60.0 mL/minute per 1.73 m2 ), meat intake, seafood intake, dairy food intake, coffee intake, and tea intake (all dietary factors as quintiles). The linear trend across categories of vitamin C intake was tested by incorporating vitamin C intake as a continuous variable into multivariate models. In order to investigate the association between serum uric acid level and vitamin C intake, we used multiple linear regression
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Table 1 Baseline characteristics of the study participants: the Korean Multi-Rural Communities Cohort study (n = 9400). Characteristics
Total (n = 9400)
Males (n = 3564)
Females (n = 5836)
P valuea
Age (year)
61.9 ± 9.7
62.5 ± 9.6
61.6 ± 9.8
< 0.0001
BMI (kg/m2 )
24.3 ± 3.2
23.9 ± 3.0
24.5 ± 3.2
< 0.0001
Waist circumference (cm) SBP (mmHg)
84.4 ± 8.9
85.6 ± 8.5
83.6 ± 9.1
< 0.0001
125.2 ± 17.8
126.3 ± 16.8
124.6 ± 18.3
< 0.0001
DBP (mmHg)
78.7 ± 10.3
79.9 ± 10.3
78.0 ± 10.3
< 0.0001
Uric acid (mg/dL)
4.9 ± 1.4
5.8 ± 1.5
4.4 ± 1.1
< 0.0001
Triglyceride (mg/dL)
152.4 ± 99.2
161.5 ± 116.0
146.8 ± 86.9
< 0.0001
HDL cholesterol (mg/dL) Fasting serum glucose (mg/dL) Cigarette smoking Nonsmoker Former smoker Current smoker
44.4 ± 10.7
43.5 ± 11.5
45.0 ± 10.2
< 0.0001
101.3 ± 24.9
104.5 ± 28.3
99.3 ± 22.3
< 0.0001 < 0.0001
6421 1573 1415
(68.2) (16.7) (15.1)
891 1456 1217
(25.0) (40.9) (34.2)
5521 117 198
(94.6) (2.0) (3.4)
Alcohol drinking Non-drinker Former drinker Current drinker
4684 683 4033
(49.8) (7.3) (42.9)
767 476 2321
(21.5) (13.4) (65.1)
3917 207 1712
(67.1) (3.6) (29.3)
Regular exercise No Yes
6643 2757
(70.7) (29.3)
2473 1091
(69.4) (30.6)
4170 1666
(71.5) (28.6)
Hypertension medication No Yes GFR (mL/minute per 1.73 m2 ) ≥ 60 < 60 Dietary intake Energy (kcal/day) Meat intake (g/day) Seafood intake (g/day) Dairy food intake (g/day) Coffee intake (g/day) Tea intake (mL/day) Soft drink intake (mL/day) Dietary vitamin C intake (mg/day) Total vitamin C intake (mg/day)b
< 0.0001
0.03
< 0.0001 7023 2377
(74.7) (25.3)
2777 787
(77.9) (22.1)
4246 1590
(72.8) (27.2) < 0.0001
8426 974
(89.6) (10.4)
3316 248
(93.0) (7.0)
5110 726
(87.6) (12.4)
1563.5 ± 471.4 24.6 ± 34.0 26.6 ± 31.1
1698.5 ± 494.1 36.4 ± 42.2 29.4 ± 33.8
1481.0 ± 437.0 17.4 ± 25.4 24.8 ± 29.3
< 0.0001 < 0.0001 < 0.0001
81.7 ± 113.4
75.3 ± 111.2
85.6 ± 114.6
< 0.0001
3.3 ± 3.5 39.2 ± 98.6 11.6 ± 49.9
4.1 ± 4.1 41.1 ± 96.7 16.2 ± 56.7
2.8 ± 3.0 38.1 ± 99.8 8.7 ± 45.0
< 0.0001 0.15 < 0.0001
85.3 ± 57.6
84.9 ± 55.7
85.5 ± 58.7
0.62
162.8 ± 264.8
156.2 ± 250.4
166.8 ± 273.2
0.06
BMI: body mass index; SBP: systolic blood pressure; DBP: diastolic blood pressure; HDL: high-density lipoprotein; GFR: glomerular filtration rate. Data were expressed as mean ± standard deviation for continuous variables and n (%) for categorical variables. a Calculated by Student’s t-tests for continuous variables and Chi2 tests for categorical variables between males and females. b Missing data were excluded from the analyses (n = 125).
models, after adjusting for the same covariates. Analysis of covariance, with adjustment for the same covariates, was used to assess the differences in serum uric acid level according to vitamin C intake. A two-sided significance level of 0.05 was used to evaluate statistical significance. All statistical analyses were carried out by the IBM SPSS Statistics 19.0 (IBM Corp., Armonk, NY, USA). 3. Results 3.1. Baseline characteristics From the 9697 participants recruited for the Korean MultiRural Communities Cohort from January 2005 through August 2009, we included 9400 (3564 males and 5836 females) in this
analysis. Baseline characteristics of the cohort are in Table 1, according to gender. Most characteristics were significantly different between males and females, except for intake of tea, dietary vitamin C, and total vitamin C. The prevalence of hyperuricemia in total, male, and female subjects was 10.9% (n = 1021), 17.2% (n = 614), and 7.0% (n = 407), respectively. In addition, the comparison of baseline characteristics between hyperuricemia and non-hyperuricemia was also illustrated (Table S1; see the supplementary material associated with this article online). In comparison of baseline characteristics of study participants according to dietary vitamin C intake, intakes of dietary components such as energy, meat, seafood, dairy food, coffee, tea, and soft drink, were gradually rose with increased dietary vitamin C intake in both males and females (Table 2).
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Table 2 Baseline characteristics of the study participants according to dietary vitamin C intake. P valuea
Dietary vitamin C intake (mg/d) Dietary components
Q1
Q2
Q3
Q4
Q5
Total participants (n = 9400) Energy (kcal/day) Meat intake (g/day) Seafood intake (g/day) Dairy food intake (g/day) Coffee intake (g/day) Tea intake (mL/day) Soft drink intake (mL/day)
1265.0 ± 352.7 11.9 ± 19.3 11.6 ± 15.3 43.0 ± 74.5 2.7 ± 3.3 6.4 ± 21.0 6.7 ± 28.6
1406.9 ± 356.1 18.2 ± 25.7 17.7 ± 16.6 63.4 ± 97.4 3.0 ± 3.4 13.7 ± 35.4 10.4 ± 45.8
1528.5 ± 380.3 23.6 ± 32.5 23.2 ± 20.7 75.0 ± 99.3 3.2 ± 3.3 26.9 ± 57.7 11.2 ± 41.3
1670.8 ± 418.2 29.2 ± 32.9 31.3 ± 27.2 99.1 ± 120.2 3.6 ± 3.5 48.2 ± 90.1 11.3 ± 40.6
1946.1 ± 517.8 40.0 ± 46.5 49.0 ± 48.3 127.9 ± 143.7 3.9 ± 3.9 101.0 ± 172.4 18.2 ± 78.3
< 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001
Males (n = 3564) Energy (kcal/day) Meat intake (g/day) Seafood intake (g/day) Dairy food intake (g/day) Coffee intake (g/day) Tea intake (mL/day) Soft drink intake (mL/day)
Q1 (< 42.5) 1368.4 ± 349.6 19.1 ± 24.9 12.7 ± 13.3 35.5 ± 65.0 3.6 ± 3.9 7.8 ± 23.3 8.5 ± 33.7
Q2 (42.5–61.8) 1540.1 ± 362.1 29.0 ± 33.7 20.1 ± 16.3 57.1 ± 93.2 3.6 ± 3.9 16.7 ± 39.6 15.0 ± 50.8
Q3 (61.9–84.7) 1648.5 ± 402.9 35.4 ± 43.1 25.2 ± 20.8 71.3 ± 94.3 3.9 ± 3.7 27.1 ± 56.9 15.2 ± 44.2
Q4 (84.8–119.2) 1811.5 ± 432.5 42.5 ± 40.4 34.7 ± 28.0 94.1 ± 121.4 4.4 ± 4.1 52.0 ± 86.9 14.1 ± 41.4
Q5 (≥ 119.3) 2123.3 ± 537.6 55.9 ± 53.6 54.5 ± 54.8 118.3 ± 145.5 4.7 ± 4.6 101.8 ± 167.8 28.3 ± 92.1
< 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001
Females (n = 5836) Energy (kcal/day) Meat intake (g/day) Seafood intake (g/day) Dairy food intake (g/day) Coffee intake (g/day) Tea intake (mL/day) Soft drink intake (mL/day)
Q1 (< 39.4) 1201.9 ± 339.6 7.5 ± 12.9 10.9 ± 16.3 47.6 ± 79.4 2.2 ± 2.8 5.6 ± 19.4 5.6 ± 25.0
Q2 (39.4–60.2) 1325.6 ± 326.9 11.7 ± 16.0 16.3 ± 16.6 67.2 ± 99.7 2.6 ± 3.0 11.8 ± 32.4 7.5 ± 42.2
Q3 (60.3–85.2) 1455.2 ± 346.1 16.4 ± 20.7 22.0 ± 20.5 77.3 ± 102.2 2.7 ± 2.9 26.7 ± 58.2 8.7 ± 39.2
Q4 (85.3–123.5) 1584.8 ± 384.9 21.1 ± 24.0 29.3 ± 26.5 102.1 ± 119.4 3.0 ± 3.0 45.8 ± 91.9 9.6 ± 40.0
Q5 (≥ 123.6) 1837.7 ± 474.0 30.3 ± 38.5 45.6 ± 43.5 133.7 ± 142.4 3.3 ± 3.3 100.5 ± 175.3 12.1 ± 67.7
< 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 0.009
BMI: body mass index; SBP: systolic blood pressure; DBP: diastolic blood pressure; HDL: high-density lipoprotein; GFR: glomerular filtration rate. Data were expressed as mean ± standard deviation. a Calculated by analysis of variance.
3.2. Comparison of vitamin C intake by presence of hyperuricemia In male subjects, absence of hyperuricemia was associated with higher levels of dietary vitamin C intake compared to male subjects with hyperuricemia (86.0 ± 56.0 mg/day vs. 79.7 ± 54.1 mg/day, P = 0.01) (Fig. 1A). Dietary vitamin C intake was also different between females with and without hyperuricemia (86.0 ± 58.5 mg/day vs. 79.2 ± 60.9 mg/day, P = 0.02). In total participants, dietary vitamin C intake between two groups is significantly different (P = 0.0007). However, total vitamin C intake was similar in males and females regardless of the presence of hyperuricemia (P = 0.38 for males; P = 0.25 for females) (Fig. 1B). The difference of total vitamin C intake between two groups is similar in total participants (P = 0.08). 3.3. Risk of hyperuricemia and vitamin C intake Because of differences in baseline characteristics (Table 1), analysis for effects of vitamin C intake on hyperuricemia risk was performed separately for males and females. Analysis was
performed after adjustment for various characteristics (Table 3). The risk of hyperuricemia in total participants was reduced with increasing dietary and total vitamin C intakes (P for trend < 0.001 and P for trend = 0.003, respectively). In male subjects, the risk of hyperuricemia was reduced with increased dietary vitamin C intake (P for trend = 0.002). However, the decreasing trends for the risk of hyperuricemia in males were observed without statistical significance in total vitamin C intake (P for trend = 0.06). In female subjects, dietary vitamin C intake showed a trend for decreased risk of hyperuricemia (P for trend = 0.02). Similarly, the risk of hyperuricemia in females was reduced with increased total vitamin C intake (P for trend = 0.04). 3.4. Correlation of serum uric acid level with vitamin C intake We conducted regression analysis to identify relationships between serum uric acid levels and vitamin C intake (Table 4). In total participants, total vitamin C intake was negatively associated with serum uric acid level ( = −0.0001, P = 0.01), but not in dietary vitamin C ( = −0.0004, P = 0.10). Serum uric acid levels were not linearly correlated with dietary or total vitamin C intake in male subjects. Total vitamin C intake in female subjects was negatively associated with serum uric acid level ( = −0.0001, P = 0.01), but not with dietary vitamin C intake ( = −0.0001, P = 0.81). In addition, serum uric acid levels were not significantly different among 5 categories of dietary and total vitamin C intake in males or females (Fig. 2). 4. Discussion
Fig. 1. Comparison of dietary vitamin C and total vitamin C intake between nonhyperuremic and hyperuremic subjects. A. Dietary vitamin C intake. B. Total vitamin C intake. Data were expressed as mean ± standard deviation for continuous variables. P values were calculated by Student’s t-tests for continuous variables. Missing data for total vitamin C intake were excluded from the analyses (n = 125). HUA: hyperuricemia.
The main aim of this study was to identify the effects of vitamin C on the risk of hyperuricemia in both males and females from the Korean Multi-Rural Communities Cohort. The facts that vitamin C reduced serum uric acid levels in an earlier population-based study from the HPFS prospective cohort [8] and a cross-sectional studies [17] have been demonstrated. However, whether this
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Table 3 Multivariate-adjusted ORs (95% CIs)a of hyperuricemia (serum uric acid level, > 7.0 mg/dL for males; > 6.0 mg/dL for females) according to categories of vitamin C intake. Variables
Males (n = 3564)
Total participants (n = 9400)
Females (n = 5836)
Dietary vitamin C intake (mg/day) Q1 1.00 Q2 0.98 0.86 Q3 0.69 Q4 0.58 Q5 c < 0.001 P for trend
(reference) (0.79–1.22) (0.68–1.08) (0.53–0.89) (0.44–0.78)
1.00 0.94 0.92 0.77 0.54
(reference) (0.70–1.27) (0.67–1.25) (0.55–1.08) (0.37–0.80) 0.002
1.00 1.01 0.80 0.61 0.68
(reference) (0.72–1.41) (0.56–1.16) (0.40–0.92) (0.43–1.07) 0.02
Total vitamin C intake (mg/day)b Q1 1.00 Q2 0.92 0.81 Q3 0.69 Q4 0.72 Q5 c P for trend 0.003
(reference) (0.74–1.15) (0.64–1.03) (0.53–0.89) (0.55–0.93)
1.00 0.86 0.83 0.74 0.73
(reference) (0.64–1.16) (0.60–1.13) (0.53–1.04) (0.52–1.03) 0.06
1.00 0.98 0.82 0.64 0.73
(reference) (0.70–1.38) (0.56–1.18) (0.43–0.97) (0.48–1.09) 0.04
OR: odds ratio; CI: confidence interval. a Logistic regression models were used to calculate ORs and 95% CIs, after the adjustment for total energy, age, cigarette smoking, alcohol drinking, regular exercise, body mass index, triglyceride, fasting serum glucose, hypertension medication, and glomerular filtration rate meat intake, seafood intake, dairy food intake, coffee intake, tea intake, soft drink intake, and/or gender, and/or supplemental vitamin C intake. b Missing data were excluded from the analyses (n = 125). c Likelihood ratio test for trend. Table 4 Linear regression coefficientsa between serum uric acid level and vitamin C intake. Males (n = 3564)
Total participants (n = 9400)
Females (n = 5836)
Variables

P value

P value

P value
Dietary vitamin C intake (mg/day) Total vitamin C intake (mg/day)b
−0.0004
0.10
−0.0008
0.14
−0.0001
0.81
−0.0001
0.01
−0.0001
0.22
−0.0001
0.01
a Adjusted for total energy, age, cigarette smoking, alcohol drinking, regular exercise, body mass index, triglyceride, fasting serum glucose, hypertension medication, and glomerular filtration rate meat intake, seafood intake, dairy food intake, coffee intake, tea intake, soft drink intake, and/or gender, and/or supplemental vitamin C intake. b Missing data were excluded from the analyses (n = 125).
relationship would be seen in both male and female subjects was unknown. Using the Korean Multi-Rural Communities Cohort, a large, population-based study, we found that dietary and total vitamin C intake showed a meaningful trend for lower risk of hyperuricemia in female subjects. Male subjects showed an association between reduced hyperuricemia risk and dietary vitamin C intake, but not total vitamin C intake. In addition, an inverse association between serum uric acid level and total vitamin C intake was observed for female participants after multivariate adjustment. Population-based evidence from the HPFS cohort study showed an association between vitamin C intake and serum uric acid
Fig. 2. Comparison of serum uric acid level according to quintiles of dietary and total vitamin C intake. A. Males. B. Females. Data were expressed as least-square (LS) mean ± 95% confidence intervals for continuous variables. P values were calculated by analysis of covariance after adjusted for total energy, age, cigarette smoking, alcohol drinking, regular exercise, body mass index, triglyceride, fasting serum glucose, hypertension medication, glomerular filtration rate, meat intake, seafood intake, dairy food intake, coffee intake, tea intake, soft drink intake, and/or gender, and/or supplemental vitamin C intake. Missing data for total vitamin C intake were excluded from the analyses (n = 125). SUA: serum uric acid.
in male subjects, reporting that males with higher vitamin C have lower serum uric acid levels [8]. In addition, some clinical investigations and meta-analyses show that vitamin C has a reducing effect on serum uric acid [4–6,10]. Gao et al. reported a difference of 0.6–0.7 mg/dL in serum uric acid level in participants taking between < 90 mg/day and ≥ 500 mg/day of vitamin C [8], which is in general agreement with other clinical trials using vitamin C supplementation of 500 mg/day [11]. In our study, serum uric acid levels in participants with the highest total vitamin C intake (Q5, ≥ 152.8 mg/day for males and ≥ 170.6 mg/day for females) were 0.09 mg/dL lower for males and 0.11 mg/dL lower for females than levels in participants with the lowest total vitamin C intake (Q1, < 43.8 mg/day for males and < 41.2 mg/day for females). We found a small difference of 0.1 mg/dL in serum uric acid levels corresponding to a difference of approximately 100 mg/day of vitamin C intake between the Q5 and Q1 study groups. For participants taking 500 mg of vitamin C daily, serum uric acid levels could be expected to drop to at least 0.5 mg. This estimate is consistent with data from an earlier study using 500 mg/day vitamin C [11]. Interestingly, the amount of calculated total vitamin C intake in participants in this study was significantly lower than in other Western populations [8,18] because of very low use of vitamin C supplementation in this cohort. The mean total intake of vitamin C in male subjects in the HPFS study exceeded the total intake amount in our study because about 50% of males in the US-based study took more than 250 mg/day of supplementary vitamin C and also had higher dietary vitamin C intake [8]. In the Nurses’ Health Study [18], the calculated amount of total vitamin C intake among US female subjects was higher than in our cohort. However, dietary analysis for 4073 people in the National Health and Nutrition Examination
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Survey 2001–2002 showed dietary vitamin C intake similar to our study [19]. Although small differences in the data of other studies [8,18,19] could not be clearly determined, differences might be related to changes in dietary patterns and timing for the data gathered for each study. In our study, the lower vitamin C intake might be related to the enrollment of rural rather than urban residents, because rural people in Korea have slightly lower use of nutritional supplements such as vitamins and minerals. In addition, patterns of nutritional supplementation in the general population could influence the differences between Korean and US populationbased studies [8,18]. Korean people prefer to use multinutritional supplements such as multivitamins rather than single-component supplements such as vitamin C and vitamin D. Hyperuricemia is generally considered to be associated with uric acid or urate deposition conditions such as gout and urate nephropathy [2] and noncrystal depositing conditions including hypertension, chronic renal disease, atherosclerosis, and metabolic syndrome [20,21], although debate about the association remains. Recently, the clinical importance of the association between hyperuricemia and gout has been highlighted. A relationship between comorbidities and serum uric acid levels suggests that lowering uric acid might be a strategy for reducing gout risk. A prospective study reported that higher vitamin C intake reduced the risk of developing gout after multivariate analyses (relative risk [RR] = 0.83 for total vitamin C intake 500–999 mg/day; RR = 0.66 for 1000–1499 mg/day; RR = 0.55 for 1500 mg/day or greater, compared to < 250 mg/day or less) [9]. However, a pilot randomized controlled trial for established gout patients receiving a moderate dose of vitamin C (500 mg/day) showed no significant uratelowering effect [12]. Our study observed trends for reduction in hyperuricemia risk in female subjects (P for trend = 0.02 for dietary vitamin C and P for trend = 0.04 for total vitamin C) and in male subjects (P for trend = 0.002 for dietary vitamin C and P for trend = 0.06 for total vitamin C intake). Although we did not identify the risk of developing gout, our evidence indicates the possibility of a preventive effect of vitamin C against gout. Unlike an earlier study [8], this study showed a trend for lowered hyperuricemia risk with increased total vitamin C intake in male subjects, although the result was not significant. The discrepancy in the association of vitamin C intake with hyperuricemia risk seen between male and female subjects in this study might be in part associated with less supplemental vitamin C intake in males than in females, resulting in an insufficient intake of total vitamin C. However, this result should be further determined in a study on a larger population. The mechanism for the uric acid-lowering effect by vitamin C has not been clearly identified. Some clinical studies in humans observed that vitamin C increases the excretion of uric acid in urine [4,5]. Another possible mechanism is suppression of uric acid synthesis by ascorbic acid [7]. Recently, molecular and experimental investigations identified uric acid transport molecules such as URAT1 and ABCG2 in renal epithelial cells in the proximal renal tubule [1,22,23]. The uricosuric effect of vitamin C is assumed to be related to interactions with a urate-anion exchanger transporter such as URAT1. A randomized placebo-controlled single-blind crossover study in renal transplant recipients demonstrated that antioxidant supplementation with vitamin C, vitamin E, and carotene improved GFR and serum creatinine [24]. Huang et al. reported that vitamin C increased GFR in subjects treated with vitamin C (500 mg/day) compared to placebo [11]. They suggested that antioxidant and osmotic effects led to increased GFR by vitamin C. A study using hyperuricemic rats demonstrated the harmful effects of uric acid on the kidney including renal hypertrophy, glomerulosclerosis, and interstitial fibrosis [25]. Similarly, high supplemental vitamin C intakes were noted to reduce the risk of major coronary artery disease [26]. These uric acid-related renal or vascular
damages were found to be related in part to oxidative stress and ischemic changes [25,27]. This evidence supports the possibility of increased GFR by vitamin C. Hyperuricemia is now established to increase the risk of cardiovascular diseases and chronic renal diseases, in addition to gout [2,20,21]. As shown in previous data, risk-benefit impact of pattern of diverse dietary consumption on hyperuricemia or increased serum uric acid level is tightly linked to uric acid-related systemic diseases [3]. From the lessons, diverse lifestyle and dietary modifications are needed to reduce risks of cardiovascular and metabolic disorders and their mortality. Prescription against hyperuricemia includes daily regular exercise, intake of low fat dairy products, and restriction of alcoholic and sugary beverages [3,28]. In addition, enhanced consumption of vitamin C may be a beneficial strategy for the risk of hyperuricemia if some medical issues such as crystalinduced arthropathy and renal stone was not existed. Strengths of current study include enrollment of large study population and participation of diverse confounding dietary variables including meat, seafood, or caffeine intakes in the assessment of effect of vitamin C intake on serum uric acid levels. Korean MultiRural Communities Cohort is multi-center community-based prospective cohort with the three rural areas evenly distributed in Korea. However, all participants restrict at mural communities. Therefore, they could not be representative sample of Korean, because this study did not recruit urban population. Another limitation is that our cohort study focuses on the effect of vitamin C intake on just serum uric acid levels, but not the risk of gout. The values of clinical significance for vitamin C intake rely on the assessment of the risk of incidental gout. Prospective study with follow-up data should be warranted to identify the role of vitamin C in uric acid levels. Our study analyzed the association between vitamin C intake and serum uric acid levels and hyperuricemia risk in both male and female subjects in an Asian population-based cohort. We found that vitamin C intake might contribute, in part, to reduced hyperuricemia risk in this population. Our findings provided evidence about the beneficial effects of vitamin C on uric acid-related health issues. The association between vitamin C intake and uric acid metabolism should further be analyzed in a prospective cohort study.
Author contributions All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be submitted for publication. Drs. P.S. Park, S.-K. Kim had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study conception and design: J. Bae, P.S. Park, S.-K. Kim. Acquisition of data: J. Bae, D.H. Shin, B.-Y. Chun, B.Y. Choi, M.K. Kim, M.-H. Shin, Y.-H. Lee, P.S. Park, S.-K. Kim. Analysis and interpretation of data: J. Bae, D.H. Shin, B.-Y. Chun, B.Y. Choi, M.K. Kim, M.-H. Shin, Y.-H. Lee, P.S. Park, S.-K. Kim.
Disclosure of interest The authors declare that they have no conflicts of interest concerning this article.
Acknowledgement This research was supported by a fund (2004-E71004-00, 2005E71011-00, 2006-E71009-00, 2007-E71002-00, 2008-E71004-00,
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