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Table 3 Univariate and multivariate linear regression models for the evaluation of factors related to blood urea nitrogen

From: The relationship between kidney function and cardiometabolic risk factors, anthropometric indices, and dietary inflammatory index in the Iranian general population: a cross-sectional study

 

Univariate model

Multivariate model

Independent variables (Q1-Q4)

ß

P1

95% CI

ß

P2

95% CI

Lower

Upper

Lower

Upper

Fasting blood sugar (mg/dl)

0.079

 < 0.001

0.044

0.114

-

-

-

-

Triglyceride (mg/dl)

0.030

0.091

-0.005

0.066

0.056

0.011

0.013

0.098

Total cholesterol (mg/dl)

0.033

0.068

-0.002

0.068

0.041

0.051

0.000

0.083

High-density lipoprotein (mg/dl)

-0.029

0.110

-0.064

0.006

0.047

0.027

0.005

0.089

Low-density lipoprotein (mg/dl)

0.027

0.140

-0.009

0.062

-

-

-

-

Systolic blood pressure (mmHg)

0.125

 < 0.001

0.091

0.160

-

-

-

-

Diastolic blood pressure (mmHg)

0.106

 < 0.001

0.071

0.141

-0.036

0.071

-0.075

0.003

Height (cm)

0.209

 < 0.001

0.174

0.243

-

-

-

-

Weight (kg)

0.128

 < 0.001

0.094

0.163

0.037

0.083

-0.005

0.079

Waist circumference (cm)

0.057

0.002

0.021

0.092

-

-

-

-

Hip circumference (cm)

-0.012

0.519

-0.047

0.024

-

-

-

-

Body mass index (kg/m2)

-0.014

0.435

-0.049

0.021

-

-

-

-

A body shape index \({(\mathbf{m}/\mathbf{k}\mathbf{g})}^{2/3}\)

0.027

0.128

-0.008

0.063

-

-

-

-

Abdominal volume index (m 2 )

0.057

0.002

0.022

0.092

-

-

-

-

Conicity index \({(\mathbf{m}/\mathbf{k}\mathbf{g})}^{1/2}\)

0.008

0.664

-0.027

0.043

-

-

-

-

Body adiposity index (1/ \({\mathbf{m}}^{1/2}\) ) %

0.203

 < 0.001

0.168

0.237

0.064

0.008

0.016

0.111

Visceral adiposity index ( \({\mathbf{m}}^{3}\) /kg)

0.043

0.017

0.008

0.078

-

-

-

-

Dietary inflammatory index

0.098

 < 0.001

0.063

0.133

-

-

-

-

Age (year)

0.015

 < 0.001

0.009

0.021

0.015

 < 0.001

0.009

0.021

Sex

 Male

Ref

-

-

-

Ref

-

-

-

 Female

-0.622

 < 0.001

-0.697

-0.547

-0.603

 < 0.001

-0.729

-0.477

  1. P1: P-value based on univariate linear regression
  2. P2: P-value based on multivariate linear regression (backward) method
  3. P-value > 0.05 was considered significant
  4. In order to remove the confounding effect of independent variables, multivariate linear regression model (backward) method was used
  5. In order to remove the high variance inflation factor (VIF) of independent variables, quartiles were used in multivariate linear regression
  6. Q1-Q4: Quartile 1 to quartile 4