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Table 3 Logistic GEE-regression on multimorbidity prevalence risks by SES, age, and year, stratified for gender

From: Widening inequalities in multimorbidity? Time trends among the working population between 2005 and 2015 based on German health insurance data

 

Men

Women

OR

95%-CI

p

OR

95%-CI

p

Educational level

low

1

  

1

  

high

0.68

0.63–0.74

< 0.001

0.62

0.57–0.67

< 0.001

missing

0.87

0.84–0.90

< 0.001

0.94

0.91–0.98

0.002

Income

low

1

  

1

  

middle

0.83

0.79–0.86

< 0.001

0.92

0.89–0.94

< 0.001

high

0.72

0.69–0.75

< 0.001

0.91

0.88–0.95

0.001

missing

0.83

0.80–0.87

< 0.001

1.05

1.02–1.09

< 0.001

Occupational group

unskilled

1

  

1

  

skilled

0.88

0.86–0.91

< 0.001

0.91

0.88–0.94

< 0.001

specialists

1.04

0.99–1.08

0.116

0.81

0.78–0.83

< 0.001

highly qualified

0.83

0.77–0.88

< 0.001

0.79

0.73–0.86

< 0.001

missing

0.78

0.75–0.82

< 0.001

0.63

0.58–0.68

< 0.001

Year

 

1.09

1.09–1.10

< 0.001

1.06

1.06–1.06

< 0.001

Age

 

1.15

1.14–1.15

< 0.001

1.13

1.12–1.13

< 0.001

Number of subjects

 

407,274

293,570

Number of observations

 

2,835,451

1,973,699

Wald Chi2 (p)

 

29,912.71 (df = 11) (< 0.001)

18,181.09 (df = 11)(< 0.001)

  1. OR odds ratio,95%-CI 95%-confidence interval, p p-value, df degrees of freedom
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International Journal for Equity in Health

ISSN: 1475-9276

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