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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.