Area characteristics and admission rates of people with schizophrenia and affective disorders in a German rural catchment area

Epidemiol Psychiatr Sci. 2012 Dec;21(4):371-9. doi: 10.1017/S2045796012000157. Epub 2012 Apr 11.

Abstract

Background: Studies in urban areas identified environmental risk factors for mental illness, but little research on this topic has been performed in rural areas.

Methods: Hospital admission rates were computed for 174 rural municipalities in the catchment area of the state psychiatric hospital in Günzburg in years 2006 to 2009 and combined with structural and socio-economic data. Relationships of overall and diagnosis-specific admission rates with municipality characteristics were analysed by means of negative binomial regression models.

Results: Admission rates of patients with a diagnosis of schizophrenia and affective disorder combined decrease with increasing population growth, population density, average income and green areas, while admission rates are positively correlated with commuter balance, income inequality, unemployment rates and traffic areas. Admission rates for schizophrenia are negatively related to population growth, average income and agricultural areas, but positively related to mobility index, income inequality and unemployment rate. Admission rates for affective disorders are negatively related to population growth, population density, average income and green areas, while higher admission rates are correlated with commuter balance, high income inequality, unemployment rate and traffic-related areas.

Conclusions: Effects of wealth, economic inequality, population density and structural area characteristics influence psychiatric admission rates also in rural areas.

MeSH terms

  • Catchment Area, Health / statistics & numerical data
  • Germany / epidemiology
  • Hospitals, Psychiatric / statistics & numerical data*
  • Humans
  • Income / statistics & numerical data
  • Mood Disorders / epidemiology*
  • Patient Admission / statistics & numerical data*
  • Population Density*
  • Population Growth*
  • Poverty
  • Rural Population / statistics & numerical data
  • Schizophrenia / epidemiology*
  • Socioeconomic Factors
  • Unemployment / statistics & numerical data