[Neighbourhood deprivation and type 2 diabetes: results from the Dortmund Health Study (DHS)]

Gesundheitswesen. 2013 Dec;75(12):797-802. doi: 10.1055/s-0033-1333737. Epub 2013 Mar 13.
[Article in German]

Abstract

Objective: The association between deprivation in the residential environment and the prevalence of type 2 diabetes has been evaluated by applying two approaches to measure neighbourhood deprivation.

Methods: Individual data were extracted from the Dortmund Health Study (n=1 312) and combined with administrative data on 62 neighbourhoods in the city of Dortmund. Deprivation indices were constructed by applying principal component analysis with a set of 8 demographic and socio-economic context variables on the low city level. 2-level cross-sectional logistic regression analyses were conducted, adjusted for age, sex, social class and employment status.

Results: The study population had a type 2 diabetes prevalence of 7.2%. The principal component analysis provided a 2-factor solution of which one factor was given in the multivariable analysis. Individuals, residing in neighbourhoods with a very high level of unemployment rate or socio-economic deprivation, showed a higher chance to have type 2 diabetes [OR: 4.44 (95% CI: 1.29-15.33) or, respectively, OR: 2.79 (95% CI: 1.10-7.07)], independent of individual characteristics.

Conclusion: Beyond individual characteristics, the residential environment contributes to the chance of type 2 diabetes. The unemployment rate operated as a strong predictor of the chance of type 2 diabetes.

Publication types

  • English Abstract

MeSH terms

  • Adult
  • Age Distribution
  • Aged
  • Cultural Deprivation*
  • Diabetes Mellitus, Type 2 / epidemiology*
  • Female
  • Germany / epidemiology
  • Health Status Disparities*
  • Humans
  • Male
  • Middle Aged
  • Poverty / statistics & numerical data*
  • Prevalence
  • Residence Characteristics / statistics & numerical data*
  • Risk Factors
  • Sex Distribution
  • Social Class
  • Socioeconomic Factors
  • Unemployment / statistics & numerical data*