Disparities in Temporal and Geographic Patterns of Myocardial Infarction Hospitalization Risks in Florida

Bibliographic Data

ID15469874
AuthorsEvah W Odoi (0000-0002-6730-3642, University of Tennessee at Knoxville), Nicholas N Nagle (0000-0002-3721-8148, University of Tennessee at Knoxville), Chris DuClos (Florida Department of Health), Kristina W Kintziger (0000-0003-3555-7805, University of Tennessee at Knoxville, corresponding author)
Year2019
Volume16
Issue23
Pages4734-4734
Publication date2019-11-27
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph16234734
PMID31783516
OpenAlexW2991063996
LanguageEN
Citations received1
References cited93

Knowledge of geographical disparities in myocardial infarction (MI) is critical for guiding health planning and resource allocation. The objectives of this study were to identify geographic disparities in MI hospitalization risks in Florida and assess temporal changes in these disparities between 2005 and 2014. This study used retrospective data on MI hospitalizations that occurred among Florida residents between 2005 and 2014. We identified spatial clusters of hospitalization risks using Kulldorff's circular and Tango's flexible spatial scan statistics. Counties with persistently high or low MI hospitalization risks were identified. There was a 20% decline in hospitalization risks during the study period. However, we found persistent clustering of high risks in the Big Bend region, South Central and southeast Florida, and persistent clustering of low risks primarily in the South. Risks decreased by 7%-21% in high-risk clusters and by 9%-28% in low-risk clusters. The risk decreased in the high-risk cluster in the southeast but increased in the Big Bend area during the last four years of the study. Overall, risks in low-risk clusters were ahead those for high-risk clusters by at least 10 years. Despite MI risk declining over the study period, disparities in MI risks persist. Eliminating/reducing those disparities will require prioritizing high-risk clusters for interventions

Cluster (spacecraft · Environmental health · Geography · Myocardial infarction · Psychological intervention · Risk assessment · Demography · Health disparities and outcomes · Health Systems, Economic Evaluations, Quality of Life · Healthcare Policy and Management · Medicine · Internal Medicine

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