Subclinical Cardiovascular System Changes in Obese Patients with Juvenile Idiopathic Arthritis

Table 6

Multiple linear regression analyses for IMT, FMD, and LVMi as dependent variables.

	Model 1			Model 2
Dependent variable	Independent variable	𝛽	𝑃	Independent variable	𝛽	𝑃
	Age	0.09	0.460	Age	0.20	0.17
	SDS-BMI	0.25	0.010	SDS-BMI	0.21	0.10
	HOMA	0.18	0.050	HOMA	0.17	0.12
IMT	HDL	−0.16	0.070	HDL	−0.11	0.25
	SBP	0.42	0.001	SBP	0.37	0.02
	DBP	0.27	0.020	DBP	0.26	0.05
				Il-6	0.04	0.65
				TNF𝛼	0.20	0.04
				hsCRP	0.02	0.79
	𝑅^2=0.42, 𝑃<0.001			𝑅^2=0.47, 𝑃<0.001
	Age	−0.04	0.75	Age	−0.20	0.21
	SDS-BMI	−0.22	0.06	SDS-BMI	−0.29	0.04
	HOMA	−0.26	0.01	HOMA	−0.19	0.13
	HDL	0.08	0.39	HDL	−0.03	0.75
FMD	SBP	−0.01	0.80	SBP	0.1	0.54
				Il-6	−0.16	0.16
				TNF𝛼	−0.24	0.04
				hsCRP	−0.04	0.71
	𝑅^2=0.22, 𝑃<0.001			𝑅^2=0.30, 𝑃<0.001
	Age	−0.01	0.880	Age	0.02	0.890
	SDS-BMI	0.43	0.003	SDS-BMI	0.53	0.004
	HOMA	0.14	0.270	HOMA	0.07	0.620
LVMi	HDL	−0.09	0.400	HDL	−0.01	0.880
	SBP	0.05	0.720	SBP	0.02	0.860
				TNF𝛼	0.20	0.100
				hsCRP	−0.03	0.980
	𝑅^2=0.36, 𝑃<0.001			𝑅^2=0.41, 𝑃<0.001

Multiple linear regression analyses for IMT, FMD, and LVMi as dependent variables in models of traditional atherosclerosis risk factors (Model 1) and extended model with the conjunction with the inflammatory markers (Model 2), SBP: systolic blood pressure, DBP: diastolic blood pressure, and HOMA: insulin resistance index.