Spatial inequalities in health of ethnic German immigrants in the Federal Republic of Germany: a comparative analysis of contextual effects on regional morbidity differences

Daniel Kreft, Rostock Center for the Study of Demographic Change
Gabriele Doblhammer-Reiter, University of Rostock

Since Ethnic German Immigrants are the largest immigrant group in Germany, the investigation of health inequalities in the population of Ethnic German Immigrants is important for public health researchers as well as for policymakers. In this study, binary logistic regression models are conducted to examine regional inequalities in health. Correlation analyses are used to evaluate morbidity patterns, especially in comparison to Native Germans. Based on the data of the Microcensus 2005 and the INKAR-Database, contextual effects on health are analysed and compared among the two subgroups to find potential explanations for health disparities. By controlling for individual characteristics, effects of settlement structure and economic performance are testified in subgroup- and sex-specific models. A major result is the detection of spatial divergence in health, but with different morbidity patterns among the subgroups measured by a non-significant correlation of (sex-specific) regional prevalence rates between the subgroups. A high regional morbidity prevalence of Native Germans is not implicitly linked to a high prevalence of Ethnic German Immigrants in the same region. When interpreting contextual-effects models, only the GDP per head and the indicators of the settlement structure exposed a notable relationship with the morbidity risk. Whereas the settlement structure of a region has a less pronounced effect on individual health of Ethnic German Immigrants, a high population density has a negative impact on the individual health of Native Germans (both sexes). The GDP per head as an indicator of economic performance is correlated with the individual health of both subgroups. People living in a region with a high GDP have a lower risk of being sick than people in regions with a low GDP, even if it is controlled for the individual socioeconomic status. In future analysis, additional indicators and cross-level interactions are going to be tested in multilevel regression models.