Diabetes prevalence based on health insurance claims: large differences between companies

Diabet Med. 2011 Aug;28(8):919-23. doi: 10.1111/j.1464-5491.2011.03305.x.

Abstract

Aims: We investigated if there are substantial differences in the prevalence of diabetes between members of different health insurance funds in Germany and, if so, which variables might explain these differences.

Methods: Ten representative surveys (conducted between 2004 and 2008) of the Bertelsmann Healthcare Monitor, comprising 15 089 participants aged 18-79 years, were analysed. Our main independent variable was membership in one of eight health insurance funds. We first estimated the crude prevalence of diabetes stratified by these funds. We further fitted logistic regression models and stepwise adjusted for age and sex, further co-morbidities and anthropometric measures and factors influencing health awareness and lifestyle.

Results: The overall prevalence of diabetes was 6.9%. Stratified by health insurance funds, prevalences ranged between 3.9% within the Innungskrankenkassen to 11.4% within the Allgemeine Ortskrankenkassen. Adjusting for age and sex only led to minor changes. After controlling for all mentioned variables, these differences remained. Compared with those who were privately insured, persons within the Allgemeine Ortskrankenkassen (OR 1.73; 95% CI 1.30-2.29), the Betriebskrankenkassen (OR 1.54; 95% CI 1.15-2.07) and the Barmer (OR 1.39; 95% CI 1.01-1.91) had a higher prevalence.

Conclusions: We found considerable differences in diabetes prevalence between German health insurance funds that remained after controlling for several relevant variables.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Diabetes Mellitus / economics
  • Diabetes Mellitus / epidemiology*
  • Female
  • Germany / epidemiology
  • Humans
  • Insurance Claim Reporting / economics
  • Insurance Claim Reporting / statistics & numerical data*
  • Insurance, Health / economics
  • Insurance, Health / statistics & numerical data*
  • Logistic Models
  • Male
  • Middle Aged
  • Prevalence
  • Young Adult