Spatial and temporal analysis of myocardial infarction incidence in Zanjan province, Iran

Background Myocardial Infarction (MI) is a major important public health concern and has huge burden on health system across the world. This study aimed to explore the spatial and temporal analysis of the incidence of MI to identify potential clusters of the incidence of MI patterns across rural areas in Zanjan province, Iran. Materials & methods This was a retrospective and geospatial analysis study of the incidence of MI data from nine hospitals during 2014-2018. Three different spatial analysis methods (Spatial autocorrelation, hot spot analysis and cluster and outlier analysis) were used to identify potential clusters and high-risk areas of the incidence of MI at the study area. Results Three thousand eight hundred twenty patients were registered at Zanjan hospitals due to MI during 2014-2018. The overall age-adjusted incidence rate of MI was 343 cases per 100,000 person which was raised from 88 cases in 2014 to 114 cases in 2018 per 100,000 person-year (a 30% increase, P < 0.001). Golabar region had the highest age-adjusted incidence rate of MI (515 cases per 100,000 person). Five hot spots and one high-high cluster were detected using spatial analysis methods. Conclusion This study showed that there is a great deal of spatial variations in the pattern of the incidence of MI in Zanjan province. The high incidence rate of MI in the study area compared to the national average, is a warning to local health authorities to determine the possible causes of disease incidence and potential drivers of high-risk areas. The spatial cluster analysis provides new evidence for policy-makers to design tailored interventions to reduce the incidence of MI and allocate health resource to unmet need areas.

Automated summary

This study revealed significant spatial variations in the pattern of MI incidence in Zanjan province, with the study area showing a higher MI incidence rate compared to the national average. Spatial cluster analysis provides new evidence for policymakers to design tailored interventions to reduce MI incidence and allocate health resources to unmet need areas.