Table 5.

Clustered logistic regression models explaining hospitalization in the last year by socio-demographic characteristics, lifestyle and health-related factors, and FIM domains among patients without multimorbidity (n = 1430)

Variablea	ORb	95% CI	P value	Nagelkerke R2c	Independent contributiond (%)
Model 1
Age	1.47	1.20–1.79	< 0.001
Total				0.048	54.55
Model 2
Age	1.51	1.23–1.85	< 0.001
Diabetes mellitus	2.61	1.27–5.35	0.009
Peripheral vascular disease	8.75	2.22–34.47	0.002
Heart disease	3.93	1.42–10.92	0.009
Total				0.088	45.45
Model 3
Age	1.51	1.23–1.85	< 0.001
Diabetes mellitus	2.61	1.27–5.35	0.009
Peripheral vascular disease	8.75	2.22–34.47	0.002
Heart disease	3.93	1.42–10.92	0.009
Total				0.088	0

^aOnly variables with P < 0.05 were included in the model

^bFor age, body mass index, number of chronic diseases, and functional independence domains scores, the odd ratios per SD increase are shown

^cNagelkerke R² is the variance of the dependent variable (hospitalization in the last year) explained by all independent variables included in the regression model

^dThe independent contribution of each cluster of predictors to the variation in hospitalization in the last year calculated as individual corresponding R² change/total R² change in the final model × 100%