Regional and neighborhood disparities in the odds of type 2 diabetes: results from 5 population-based studies in Germany (DIAB-CORE consortium)

Am J Epidemiol. 2013 Jul 15;178(2):221-30. doi: 10.1093/aje/kws466. Epub 2013 May 5.


The objective of this study was to investigate the association between residential environment and type 2 diabetes. We pooled cross-sectional data from 5 population-based German studies (1997-2006): the Cardiovascular Disease, Living and Ageing in Halle Study, the Dortmund Health Study, the Heinz Nixdorf Recall Study, the Cooperative Health Research in the Region of Augsburg Study, and the Study of Health in Pomerania. The outcome of interest was the presence of self-reported type 2 diabetes. We conducted mixed logistic regression models in a hierarchical data set with 8,879 individuals aged 45-74 years on level 1; 226 neighborhoods on level 2; and 5 study regions on level 3. The analyses were adjusted for age, sex, social class, and employment status. The odds ratio for type 2 diabetes was highest in eastern Germany (odds ratio = 1.98, 95% confidence interval: 1.81, 2.14) and northeastern Germany (odds ratio = 1.58, 95% confidence interval: 1.40, 1.77) and lowest in southern Germany (reference) after adjustment for individual variables. Neighborhood unemployment rates explained a large proportion of regional differences. Individuals residing in neighborhoods with high unemployment rates had elevated odds of type 2 diabetes (odds ratio = 1.62, 95% confidence interval: 1.25, 2.09). The diverging levels of unemployment in neighborhoods and regions are an independent source of disparities in type 2 diabetes.

Keywords: diabetes mellitus; lifestyle; multilevel analysis; residence characteristics; socioeconomic factors; type 2 diabetes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Cross-Sectional Studies
  • Diabetes Mellitus, Type 2 / epidemiology
  • Diabetes Mellitus, Type 2 / etiology*
  • Female
  • Germany / epidemiology
  • Health Status Disparities*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Odds Ratio
  • Residence Characteristics* / statistics & numerical data
  • Risk Factors
  • Self Report
  • Unemployment* / statistics & numerical data