Relationship between community characteristics and admission rates in rural communities in South Germany during the years 2006 to 2009

Background/Objectives: Studies in urban areas show a relationship between socio-economic and structural characteristics of the living environment and the development and course of psychiatric disorders. It was examined whether socio-economic and structural characteristics of the living environment known from the situation in urban areas also influence psychiatric admissions rates in rural communities.

Methods: For the years 2006 to 2009, psychiatric hospital admission rates for 174 communities were computed from the admission records of the state mental hospital which provides the psychiatric inpatient service for the region. Socio-economic and structural community characteristics were obtained from the Bavarian State Office for Statistics and Data Processing and from the Federal Employment Office. Relationships between diagnosis-specific admission rates and community characteristics were analysed by means of negative binomial regression models.

Results: Admissions of all patients with a diagnosis either of F2 (schizophrenia, schizotypal and delusional disorders) or F3 (affective disorders) combined decrease with the increase of population density, population growth, and average income, while high income inequality and a high unemployment rate are associated with increasing admissions. A high percentage of green areas in a community is connected with a reduction of admission rates, while a high percentage of traffic related areas seems to increase admission rates. Admission rates for F2 are negatively related to an increase in population density, population growth, and average income, but positively related to income inequality. Admission rates for F3 are negatively related to population density, population growth and average income as well as to a high percentage of green areas. High income inequality and high percentage of traffic related areas are related to higher admission rates for F3.

Discussion/Conclusions: Effects of wealth and economic inequality on psychiatric admission rates previously reported for urban areas also seem to apply to rural areas. This indicates that underlying socio-economic risk factors found in previous studies for urban areas do influence mental health independently from geographical circumstances. In contrast to findings in urban areas though, the present study suggests that population density and population growth have a positive effect on mental health. A low population density may lead to a lack of social networks and social support which both have been identified as protective factors against mental illness. Another possible reason could be that mentally ill people in sparsely populated areas may face stigmatisation. Findings from urban areas about land use could also be replicated. This shows that certain environmental factors may influence human well-being, especially if they have a particular restorative effect (like green areas) or a particular stressing effect (like roads). It can only be hypothesised that in urban areas certain factors do have a larger impact because of missing buffer effects or amplifying circumstances; another explanation may be the drift of diseased people towards larger cities with better health care services.

Funding: None declared.

Keywords: Burden of illness, environmental risk factors, socio-economic risk factors.