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Table 3 Multivariable linear and non-linear relationship between sUA and BMI stratified by gender, β (95% CI) of BMI (kg/m2)

From: Nonlinear relationship between serum uric acid and body mass index: a cross-sectional study of a general population in coastal China

ModelsMenP-valueWomenP-valueTotalP-value
Linear regression model, Per SD increase in BMI
 Crude model6.11 (5.56, 6.66)< 0.00015.03 (4.66, 5.40)< 0.00015.47 (5.15, 5.78)< 0.0001
 Model I6.16 (5.60, 6.71)< 0.00014.09 (3.71, 4.48)< 0.00015.29 (4.97, 5.61)< 0.0001
 Model II4.71 (4.08, 5.35)< 0.00013.03 (2.60, 3.46)< 0.00013.80 (3.44, 4.17)< 0.0001
Non-linear model, regression coefficients (β)
 Break point of BMI, kg/m2 (K)19.1 21.3 19.2 
  < K− 7.74 (− 14.7, − 0.75)0.0301− 2.70 (− 4.47, − 0.94)0.0027− 8.72 (− 12.4, − 5.06)< 0.0001
  ≥ K5.10 (4.44, 5.77)< 0.00013.93 (3.42, 4.43)< 0.00014.26 (3.87, 4.65)< 0.0001
Difference of β-value between strata12.8 (5.66, 20.0)0.00056.63 (4.65, 8.61)< 0.000113.0 (9.21, 16.8)< 0.0001
 Predicted value of sUA at break point308 (304, 312) 243 (240, 245) 267 (264, 270) 
 P-value for likelihood ratio test< 0.001 < 0.001 < 0.001 
  1. Model I: Adjusted for age
  2. Model II: Adjusted for age, current smoking status, current drinking status, occupational types, SBP, DBP, fasting blood sugar (log10 transformed), eGFR, LDL, triglyceride (log10 transformed), and total cholesterol
  3. Non-linear model: Adjusted for age, current drinking status, current smoking status, occupational types, SBP, DBP, fasting blood sugar (log10 transformed), eGFR, LDL, triglyceride (log10 transformed), and total cholesterol