Kjærulff, Thora Majlund, Kristine Bihrmann, Ingelise Andersen, Gunnar Hilmar Gislason, Mogens Lytken Larsen, and Annette Kjær Ersbøll, Geographical Inequalities in Acute Myocardial Infarction beyond Neighbourhood-Level and Individual-Level Sociodemographic Characteristics: A Danish 10-Year Nationwide Population-Based Cohort Study, BMJ Open, 9.2 (2019).
Objective This study examined whether geographical patterns in incident acute myocardial infarction (AMI) were explained by neighbourhood-level and individual-level sociodemographic characteristics.
Design An open cohort study design of AMI-free adults (age ≥30 years) with a residential location in Denmark in 2005–2014 was used based on nationwide administrative population and health register data linked by the unique personal identification number. Poisson regression of AMI incidence rates (IRs) with a geographical random effect component was performed using a Bayesian approach. The analysis included neighbourhood-level variables on income, ethnic composition, population density and population turnover and accounted for individual-level age, sex, calendar year, cohabitation status, income and education. Setting Residents in Denmark (2005–2014).
Participants The study population included 4 128 079 persons (33 907 796 person-years at risk) out of whom 98 265 experienced an incident AMI. Outcome measure Incident AMI registered in the National Patient Register or the Register of Causes of Death. Results Including individual and neighbourhood sociodemographic characteristics in the model decreased the variation in IRs of AMI. However, living in certain areas was associated with up to 40% increased IRs of AMI in the adjusted model and accounting for sociodemographic characteristics only moderately changed the geographical disease patterns.
Conclusions Differences in sociodemographic characteristics of the neighbourhood and individuals explained part, but not all of the geographical inequalities in incident AMI. Prevention strategies should address the confirmed social inequalities in incident AMI, but also target the areas with a heavy disease burden to enable efficient allocation of prevention resources.