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Table 5 Univariate and multivariate linear regression models for the evaluation of factors related to estimated glomerular filtration rate

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)

-0.033

0.069

-0.068

0.003

-0.033

0.075

-0.069

0.003

Triglyceride (mg/dl)

0.026

0.149

-0.009

0.061

-

-

-

-

Total cholesterol (mg/dl)

-0.006

0.728

-0.042

0.029

-

-

-

-

High-density lipoprotein (mg/dl)

0.040

0.026

0.005

0.075

-

-

-

-

Low-density lipoprotein (mg/dl)

0.008

0.660

-0.027

0.043

-

-

-

-

Systolic blood pressure (mmHg)

-0.040

0.027

-0.075

-0.004

-0.052

0.013

-0.092

-0.011

Diastolic blood pressure (mmHg)

-0.040

0.028

-0.075

-0.004

-

-

-

-

Height (cm)

-0.003

0.878

-0.038

0.033

0.062

0.095

-0.011

0.134

Weight (kg)

-0.017

0.347

-0.052

0.018

-0.062

0.024

-0.117

-0.008

Waist circumference (cm)

0.002

0.924

-0.034

0.037

-

-

-

-

Hip circumference (cm)

0.006

0.759

-0.030

0.041

-

-

-

-

Body mass index (kg/m2)

-0.005

0.789

-0.040

0.030

-

-

-

-

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

0.001

0.992

-0.035

0.035

-

-

-

-

Abdominal volume index (m 2 )

0.002

0.924

-0.034

0.037

-

-

-

-

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

0.007

0.682

-0.028

0.043

-

-

-

-

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

0.020

0.266

-0.015

0.055

-0.083

0.009

-0.146

-0.021

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

0.041

0.024

0.005

0.076

-0.056

0.003

-0.093

-0.020

Dietary inflammatory index

0.010

0.580

-0.025

0.045

-

-

-

-

Age (year)

0.000

0.924

-0.006

0.006

-

-

-

-

Sex

 Male

Ref

-

-

-

Ref

-

-

-

 Female

0.000

0.099

-0.079

0.079

0.145

0.037

0.009

0.281

  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