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Table 2 Multiple logistic regression analysis demonstrating relationship between hyperuricemia and metabolic syndrome * in four models

From: The Relevance of Hyperuricemia and Metabolic Syndrome and the Effect of Blood Lead Level on Uric Acid Concentration in Steelmaking Workers

Variables Odds ratio (95% confidence interval)
Model 1 Model 2 Model 3 Model 4
Hyperuricemia (≥7 mg/dL)     
No 1.000 1.000 1.000 1.000
Yes 1.533 (1.014 ~ 2.317) 2.016 (1.296 ~ 3.135) 1.939 (1.242 ~ 3.026) 1.787 (1.125 ~ 2.839)
Age (years)   1.057 (1.037 ~ 1.077) 1.055 (1.032 ~ 1.077) 1.049 (1.026 ~ 1.073)
log transformed blood lead (μg/dL)   0.855 (0.414 ~ 1.768) 0.822 (0.394 ~ 1.715) 0.789 (0.370 ~ 1.681)
Smoking (pack-year)    1.007 (0.991 ~ 1.024) 1.005 (0.988 ~ 1.022)
Drinking (days/week)    1.035 (0.906 ~ 1.183) 0.948 (0.820 ~ 1.097)
Exercise (days/week)    0.941 (0.837 ~ 1.057) 0.969 (0.861 ~ 1.091)
LDL-cholesterol (mg/dL)     1.002 (0.996 ~ 1.008)
γ-GTP (IU/L)     1.008 (1.005 ~ 1.012)
Serum creatinine (mg/dL)     0.433 (0.077 ~ 2.442)
  1. *: Defined as the presence of at least three of the following components : waist circumference ≥90 cm, triglycerides ≥150 mg/dL or on drug treatment, HDL-cholesterol < 40 mg/dL or on drug treatment, SBP ≥130 or DBP ≥85 mmHg or on drug treatment, and fasting glucose ≥100 mg/dL or on drug treatment.
  2. Model 1: not adjusted.
  3. Model 2: adjusted by age, log transformed blood lead.
  4. Model 3: adjusted for model 2 plus smoking, drinking, exercise.
  5. Model 4: adjusted for model 3 plus LDL-cholesterol, γ-GTP, serum creatinine.