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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