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Table 3 Logistics regression model of diet quality scores and obesity indicators

From: Association between diet quality and obesity indicators among the working-age adults in Inner Mongolia, Northern China: a cross-sectional study

  T1 T2 T3 P Ptrend
OR (95% CI) OR (95% CI)
DASH
 WC Model1 1.00 0.95(0.72,1.26) 0.78(0.60,1.02) 0.07 0.13
Model2 1.00 0.95(0.70,1.27) 0.71(0.53,0.96) 0.03 0.03
 BMI Model1 1.00 1.01(0.77,1.34) 0.86(0.66,1.12) 0.27 0.27
Model2 1.00 0.99(0.74,1.33) 0.76(0.57,1.02) 0.07 0.07
 WC-BMI Model1 1.00 1.08(0.81,1.43) 0.89(0.68,1.16) 0.39 0.38
Model2 1.00 1.06(0.79,1.43) 0.82(0.61,1.09) 0.17 0.12
aMed
 WC Model1 1.00 1.15(0.88,1.50) 0.76(0.57,1.00) 0.05 0.04
Model2 1.00 1.10(0.83,1.46) 0.64(0.47,0.87) 0.004 0.005
 BMI Model1 1.00 0.81(0.62,1.06) 0.70(0.53,0.92) 0.01 0.19
Model2 1.00 0.76(0.57,1.02) 0.57(0.41,0.77) < 0.001 0.02
 WC-BMI Model1 1.00 0.83(0.63,1.10) 0.70(0.53,0.93) 0.01 0.10
Model2 1.00 0.79(0.59,1.06) 0.60(0.44,0.81) 0.001 0.02
  1. Model 1: crude data;
  2. Model 2: Adjusted for gender, age, place of residence, ethnicity, education level, smoking status, drinking status, physical activity, meals eaten outside the home, family history of chronic diseases, hypertension, diabetes and energy intake.