Construction of a risk prediction model for hypertension in type 2 diabetes: Independent risk factors and nomogram

Table 2 Multivariate logistic regression model analysis

Item	Coefficient (β)	SD	Z-statistic (Z)	P value	OR	95%CI
Constant	-10.25	0.56	-18.55	0.001	0.001	-
Age	0.08	0.008	15.56	0.001	1.09	1.07-1.10
LDL	0.23	0.05	4.32	0.001	1.04	1.02-1.06
BMI	0.25	0.012	16.03	0.001	1.28	1.24-1.31
Duration of diabetes	0.03	0.006	3.98	0.001	1.03	1.02-1.05
Urine Protein
+	0.72	0.25	2.71	0.001	2.03	1.25-3.48
++	1.38	0.34	4.11	0.001	4.00	2.12-8.02
+++	2.82	0.36	7.54	0.001	16.48	8.36-36.58

Coefficient (β) represents the regression coefficient in the multivariate logistic regression model, indicating the change in the log-odds of the outcome per unit change in the predictor variable. SD is the standard error of the coefficient estimate, reflecting its precision. Z-statistic (Z) is calculated by dividing the coefficient by its standard error for significance testing. All P values of 0.001 here imply strong statistical significance. OR is the exponentiated coefficient (β), showing the multiplicative change in the odds of the outcome. LDL: Low-density lipoprotein; BMI: Body mass index.