Association between neighborhood socioeconomic position and risk of incident acute myocardial infarction in Denmark: a spatial analysis approach

INTRODUCTION: Acute myocardial infarction (AMI) constitutes a serious public health problem in Denmark and worldwide. AMI is associated with a range of individual risk factors, however, less is known about the interplay between different contextual factors and development of AMI. This study aimed at assessing the usefulness of spatial analysis to investigate neighborhood characteristics of areas with high risk of incident AMI by use of a unique combination of individual-level data sources.

METHODS: The study population consisted of 3,459,912 adult Danish residents (≥30 years). Data on AMI, SEP, current and historical addresses, and geographical coordinates were obtained from nationwide registers and linked at the individual level. Spatial scan statistics in SaTScan was applied to identify clusters with high risk of incident AMI (CHRIA) and logistic regression models were performed to investigate the association between neighborhood socioeconomic position (SEP) and CHRIA.   

RESULTS: Throughout the country 52 significant CHRIA with a median age below 75 years were identified (N=239,239 persons). The proportion of unemployed in the neighborhood was stronger associated with risk of living in CHRIA in rural (Odds Ratio(OR)=1.54, 95% confidence interval=[1.53;1.55]) and suburban (OR=1.42 [1.42;1.43]) than urban (OR=1.13 [1.13;1.14]) and metropolitan areas (OR=1.15 [1.14;1.15]), whereas the proportion of elderly people in the neighborhood was stronger associated with odds of living in CHRIA in metropolitan areas (OR=1.40 [1.40;1.41]) than less urban areas (OR=1.00 [1.00-1.00] to OR=1.06 [1.06;1.06]). An increasing proportion of immigrants and descendants as well as an increasing annual median disposable household income in the neighborhood decreased odds of living inside CHRIA across the four levels of urbanization.   

CONCLUSIONS: Areas with high risk of incident AMI are characterized by low neighborhood SEP. Spatial analysis may be an important analytic tool in epidemiologic research that enables public health professionals to make more efficient prevention strategies that target people most in need.