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Table 4 Univariate and multivariate linear regression models for the evaluation of factors related to serum creatinine

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)

0.173

 < 0.001

0.139

0.208

0.066

 < 0.001

0.037

0.096

Triglyceride (mg/dl)

0.200

 < 0.001

0.166

0.235

0.056

0.001

0.024

0.088

Total cholesterol (mg/dl)

0.033

0.068

-0.002

0.068

-

-

-

-

High-density lipoprotein (mg/dl)

-0.167

 < 0.001

-0.202

-0.132

0.053

0.001

0.021

0.085

Low-density lipoprotein (mg/dl)

0.038

0.033

0.003

0.074

-

-

-

-

Systolic blood pressure (mmHg)

0.261

 < 0.001

0.227

0.294

-0.037

0.094

-0.080

0.006

Diastolic blood pressure (mmHg)

0.278

 < 0.001

0.244

0.312

0.045

0.042

0.002

0.089

Height (cm)

0.435

 < 0.001

0.404

0.466

-

-

-

-

Weight (kg)

0.310

 < 0.001

0.277

0.343

0.075

 < 0.001

0.039

0.111

Waist circumference (cm)

0.158

 < 0.001

0.123

0.193

-

-

-

-

Hip circumference (cm)

0.043

0.018

0.007

0.078

-

-

-

-

Body mass index (kg/m2)

0.049

0.007

0.014

0.084

-

-

-

-

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

-0.007

0.703

-0.042

0.028

-0.027

0.067

-0.055

0.002

Abdominal volume index (m 2 )

0.156

 < 0.001

0.122

0.191

-

-

-

-

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

0.005

0.784

-0.030

0.040

-

-

-

-

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

0.366

 < 0.001

0.334

0.398

0.084

 < 0.001

0.044

0.123

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

0.075

 < 0.001

0.040

0.111

-

-

-

-

Dietary inflammatory index

0.155

 < 0.001

0.120

0.190

-

-

-

-

Age (year)

0.003

0.321

-0.003

0.009

-

-

-

-

Sex

 Male

Ref

-

-

-

Ref

-

-

-

 Female

-1.179

 < 0.001

-1.243

-1.115

-0.954

 < 0.001

-1.061

-0.846

  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