Skip to main content

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)

From: Functional status and annual hospitalization in multimorbid and non-multimorbid older adults: a cross-sectional study in Southern China

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

  1. aOnly variables with P < 0.05 were included in the model
  2. bFor age, body mass index, number of chronic diseases, and functional independence domains scores, the odd ratios per SD increase are shown
  3. cNagelkerke R2 is the variance of the dependent variable (hospitalization in the last year) explained by all independent variables included in the regression model
  4. 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%