Disease Mapping and Inequalities in Health Services in a Welfare State

Hintergrund: Since the 1930s Denmark has developed a special version of the welfare state to support elaborate public systems of income redistribution and services. However, health inequalities persist. With geographic information systems (GIS), spatial differences in health can be examined, offering new opportunities for description and analysis of health status. Ziel: This study examines inequalities in hospital utilisation in Denmark. This is done by examining differences by location and social status as well as by sex and age. The use of GIS can help to identify where and for whom inequalities in health status and health services exist. Methoden: Data come from public use files of Statistics Denmark. Hospitalisation is measured as the average number of bed days from 1999–2001. Direct and indirect standardisation of hospitalisation rates and the Townsend index, a measure of deprivation, were calculated. At the aggregate level, regression was used to examine the relationship of the Townsend index to the hospitalisation rate. GIS was used to display both hospitalisation rates and Townsend values at the level of the kommune. Ergebnisse: Preliminary results point to geographic and social differences in hospital utilisation. In relation to national rates, hospital utilisation was highest in Copenhagen (SMR for men=1,14; SMR for women=1,17) and lowest in the rural areas in Jutland (SMR for men=0,92; SMR for women=0,90). The relationship of deprivation to hospital utilisation was strongest in Copenhagen with higher deprivation associated with longer hospital stays. (R²=0.66; p<0,005). Significant associations were also found for the islands, but not for Jutland. Diskussion: Inequalities in hospital utilisation in Denmark exist geographically and socially when data are analysed at the aggregate level. The ecological fallacy must be considered; however, recent discussions have recalled the advantages of aggregate level and geographic analyses for broad public health policy options. Schlussfolgerungen: GIS is a powerful tool for displaying and analysing aggregate data and should be incorporated in monitoring population health.