Contextualising the association of socioeconomic deprivation with hospitalisation rates of myocardial infarction in a rural area in eastern Germany

Abstract

Introduction: Evidence on the association of socioeconomic deprivation with occurrence of acute myocardial infarction (AMI) is available from international studies and urban settings in western Germany. This study aimed to assess this association based on small geographical areas in a rural setting in eastern Germany. Methods: This study used routine data of all patients with AMI who were treated in the Hospital Brandenburg in the city of Brandenburg, Germany, between May 2019 and May 2020. Hospitalisation rates of AMI were calculated for postal code regions that were located within the catchment area of the Hospital Brandenburg. Poisson regression was used to compare hospitalisation rates in areas with medium socioeconomic deprivation to areas with high deprivation, controlling for age group, sex and period (before or during COVID-19 pandemic). Publicly available social, infrastructure and healthcare-related features were mapped to characterise the study region. Results: In total, 265 cases of AMI were registered in the study area, which comprised 116,126 inhabitants. The city of Brandenburg was characterised by the highest level of socioeconomic deprivation, while neighbouring areas showed a rural settlement structure and medium levels of deprivation. The number of general practitioners per 10 000 inhabitants did not differ between both areas. The adjusted rate ratio comparing hospitalisations due to AMI in areas with medium socioeconomic deprivation to areas with high socioeconomic deprivation was 0.71 (95%CI 0.56-0.91, p=0.01). Conclusion: This study adds evidence about the association of socioeconomic deprivation and AMI occurrence from a rural area in eastern Germany. Further research about the relationship of socioeconomic deprivation and cardiovascular health is needed from heterogeneous contexts.

Keywords

• acute myocardial infarction
• Germany
• hospitalisation rate
• regional health disparities
• rurality
• social inequalities