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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.