1030 py may influence metabolic factors, patients who were on chronic steroid therapy (defined as more than a month of any steroid dosage) were also excluded. Due to the cross-section- al nature of this study, missing data occurred in some cases pertaining to the classification criteria (nine cases), and these cases were negatively coded (they were regarded as not fulfill- ing the criteria). The prevalence of metabolic syndrome obtained from this study was age-adjusted with using the male population from the year 2000 Population Projection for Korea (9). The preva- lence of metabolic syndrome in this study was compared with that from the previous studies done in Korea with the gen- eral population, which prevalence was also age-adjusted by using epidemiologic methods. Among the reports, we used the prevalence reported by Lee et al. (10) (5.2%: male sex only, total prevalence: 6.8%) as the prevalence of the general pop- ulation since it was based on the largest sample size (40,698 persons). There has been a study derived from a national health survey (11) and it reported a 22.1% prevalence among males, but that study used the modified ATP III criteria, in which the waist circumference criteria is adjusted to males ≥90 cm and females ≥80 cm according to the WHO Asia-Pacific obesity criteria (APC) (12), and so our results were compared separately to that study. Historical controls were used for the reason that such data would be more representative of the general population than using clinical data from institutions and so this should make a more objective comparison. As hyperuricemia and hypertriglyceridemia are associated with alcohol consumption and this may confound the results, the amount of alcohol consumption was checked in a categorized fashion. We classified the patients by the average daily alco- hol consumption into three groups; non-drinkers, moderate drinkers (≤30 g/day), or heavy drinkers (>30 g/day). A case-only analysis for comparing gout patients with or without metabolic syndrome by multiple logistic regression analysis was conducted to determine the strongest factors Table 1. Descriptive data of the patients with gout Mean±Standard deviation Factors Age (yr) Height (cm) Weight (kg) Body mass index (BMI, kg/m2) Waist (cm) Systolic blood pressure (SBP, mmHg) Diastolic blood pressure (DBP, mmHg) Fasting blood glucose (FBS, mg/dL) Total cholesterol (mg/dL) Triglyceride (TG, mg/dL) HDL (mg/dL) LDL (mg/dL) Serum uric acid (mg/dL) Serum creatinine (mg/dL) Hypertension Diabetes 53.0±11.9 168.6±5.3 74.0±10.3 25.97±2.96 92.8±7.8 132.7±17.9 83.9±11.1 102.9±22.7 201.6±43.6 230.3±202.8 45.2±10.8 115.7±35.6 7.3±2.4 1.2±0.29 47.6% 10.7% Y.H. Rho, S.J. Choi, Y.H. Lee, et al. associated with the occurrence of metabolic syndrome with gout. Statistical analysis was done with SPSS for Windows 10.0 (SPSS Inc. Chicago, U.S.A.). Comparisons between the continuous or categorical variables were done by t-tests or chi-square tests, respectively. To compare variables among the different alcohol consumption groups, we used one-way analysis of variance (ANOVA). The prevalence, expressed as rates, was compared using chi-square tests of homogeneity. Multiple logistic regression analysis was applied for the multi- variate analysis as described above, and the results are given in odds ratios (OR) with 95% confidence intervals (95% CI). Variables with p values of <0.05 were considered significant. RESULTS Descriptive analysis A total of 168 patients with gout were recruited from the four hospitals. Table 1 shows the descriptive data of these patients. All the patients were males, and the mean age was 53±11.9 yr. Almost half (47.6%) were hypertensive and 10.7% were diabetic, and this is similar to previous data from patients with gout (13). Forty-two percent (42.9%) drank in moderation (≤30 g/day) and 28.6% drank heavily (>30 g/day) (Table 2). Differences in the variables among the alco- hol consumption groups could be seen for the triglyceride and glucose levels. The triglyceride levels increased linearly in proportion to the alcohol consumption levels, while the glucose levels were lowest among the moderate drinkers. The urate levels were not significantly different among the groups (Table 2). Prevalence of the metabolic syndrome in patients with gout The age-adjusted prevalence of metabolic syndrome with gout was 43.6%, which is significantly higher than that of the control population (10) (p<0.001) (Table 3). When using the modified ATP III criteria where the waist criteria is lowered to ≥90 cm in males and ≥80 cm in females, the prevalence jumped up to 57.2%, and this is also significantly higher Table 2. Metabolic factors according to alcohol consumption Average daily alcohol consumption Non-drinker ≤30 g/day > 30 g/day p Prevalence of MS* 19 (11.3%) 26 (15.5%) 18 (10.7%) 0.929 FBS (mg/dL) 109.1±26.7‖ 98.4±17.7‖ 103.9±24.0 0.04 TG (mg/dL) 175.1±97.7¶ 234.3±161.5 279.6±302.7¶ 0.04 Uric acid (mg/dL) 7.8±2.2 6.9±2.4 7.4±2.6 0.97 Total 48 (28.6%) 72 (42.9%) 48 (28.6%) - *Metabolic syndrome, chi-square test of homogeneity, One-way ANOVA, Mean±SD, ‖p=0.036, ¶p=0.034, Bonferroni test. The other factors are not significant.