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Table 4 Clustered logistic regression models explaining hospitalization in the last year by socio-demographic characteristics, lifestyle and health-related factors, and FIM domains among patients with multimorbidity (n=1173)

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

Variablea

OR b

95% CI

P value

Nagelkerke R2c

Independent contribution d (%)

Model 1

 Gender (male)

1.59

1.16–2.17

0.004

  

 Total

   

0.012

18.46

Model 2

 Gender (male)

1.60

1.16–2.20

0.004

  

 Number of chronic diseases

1.52

1.30–1.78

< 0.001

  

 Total

   

0.049

56.92

Model 3

 Gender (male)

1.63

1.18–2.24

0.003

  

 Number of chronic diseases

1.45

1.24–1.71

< 0.001

  

 Walk

0.80

0.70–0.91

0.001

  

 Total

   

0.065

24.62

  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%