Table 4.

Multiple Logistic regression between CHD with FBG, PBG and HbA1c.

CHD		P value.	Exp(B)	95% C.I.for EXP(B)
				Lower	Upper
Model 1 (FBG)	Age	<0.001	1.029	1.015	1.043
	Gender	<0.001	2.813	2.083	3.799
	SBP	0.032	1.011	1.001	1.021
	histrory of Af	0.028	0.515	0.284	0.932
	HDL	0.035	0.634	0.415	0.968
	Lp(a)	<0.001	1.001	1.000	1.001
	FBG	0.008	1.155	1.039	1.284
Model 2 (PBG)	age	0.001	1.025	1.010	1.039
	Gender	<0.001	3.179	2.357	4.287
	Lp(a)	0.003	1.001	1.000	1.001
	PBG	<0.001	1.098	1.051	1.147
Model 3 (HbA1c)	Age	<0.001	1.028	1.014	1.042
	Gender	<0.001	2.809	2.079	3.795
	SBP	0.033	1.011	1.001	1.021
	histrory of Af	0.025	0.507	0.280	0.918
	HDL	0.045	0.647	0.423	0.990
	Lp(a)	<0.001	1.001	1.000	1.001
	HbA1c	0.002	1.239	1.078	1.424
Model 4 (FBG, PBG, HbA1c)	Age	0.001	1.024	1.010	1.039
	Gender	<0.001	3.139	2.326	4.236
	Lp(a)	0.002	1.001	1.000	1.001
	PBG	<0.001	1.096	1.050	1.145

Multiple logistic regression was performed to identify risk factors associated with the CHD. In model 1, only fasting plasma glucose (FPG) was taken into account as glycemic parameter with other variables. In model 2, only postprandial blood glucose (PBG) was taken into account as glycemic parameter with other variables.In model 3, only HbA1c was taken into account as glycemic parameter with other variables. In model 4, FPG, PBG and HbA1c were all taken into account as glycemic parameters with other variables. Exp, exponential; B, coefficient; CI, confidence interval.