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Bayesian Modeling and Estimation of Spatial Risk for Hospitalization and Mortality from Ischemic Heart Disease in Paraná, Brazil

dc.contributor.authorde Carvalho Dutra, Amanda
dc.contributor.authorBorba, Isadora Martins
dc.contributor.authorSilva, Lincoln Luis
dc.contributor.authorde Campos, Edvaldo Vieira
dc.contributor.authorDos Santos, Amanda Gubert Alves
dc.contributor.authorStaton, Catherine Ann
dc.contributor.authorDo Lago Franco, Rogério
dc.contributor.authorMarquezoni, Diogo Pinetti [UNESP]
dc.contributor.authorForato, Giane Aparecida Chaves
dc.contributor.authorNihei, Oscar Kenji
dc.contributor.authorBergamini, Marcela
dc.contributor.authorVissoci, João Ricardo Nickenig
dc.contributor.authorde Andrade, Luciano
dc.contributor.institutionState University of Maringa
dc.contributor.institutionDuke University School of Medicine
dc.contributor.institutionCentro Universitário Integrado
dc.contributor.institutionDuke Global Health Institute
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionState University of the West of Paraná
dc.date.accessioned2025-04-29T18:07:26Z
dc.date.issued2024-01-01
dc.description.abstractObjective: Despite significant advancements in understanding risk factors and treatment strategies, ischemic heart disease (IHD) remains the leading cause of mortality worldwide, particularly within specific regions in Brazil, where the disease is a burden. Therefore, the aim of this study was to estimate the risk of hospitalization and mortality from IHD in the state of Paraná (Brazil), using spatial analysis to identify areas with higher risk based on socioeconomic, demographic and health variables. Methods: This is an ecological study based on secondary and retrospective IHD hospitalization and mortality data obtained from the Brazilian Hospitalization and Mortality Information Systems during the 2010–2021 period. Data were analyzed for 399 municipalities and 22 health regions in the state of Paraná. To assess the spatial patterns of the disease and identify relative risk (RR) areas, we constructed a risk model by Bayesian inference using the R-INLA and SpatialEpi packages in R software. Results: A total of 333,229 hospitalizations and 73,221 deaths occurred in the analyzed period, and elevated RR of hospitalization (RR = 27.412, CI 21.801; 34.466) and mortality (RR = 15.673, CI 2.148; 114.319) from IHD occurred in small-sized municipalities. In addition, medium-sized municipalities also presented elevated RR of hospitalization (RR = 6.533, CI 1.748; 2.006) and mortality (RR = 6.092, CI 1.451; 2.163) from IHD. Hospitalization and mortality rates were higher in white men aged 40–59 years. A negative association was found between Municipal Performance Index (IPDM) and IHD hospitalization and mortality. Conclusion: Areas with increased risk of hospitalization and mortality from IHD were found in small and medium-sized municipalities in the state of Paraná, Brazil. These results suggest a deficit in health care attention for IHD cases in these areas, potentially due to a low distribution of health care resources.en
dc.description.affiliationPost-Graduation Program in Health Sciences State University of Maringa
dc.description.affiliationDepartment of Emergency Medicine Duke University School of Medicine
dc.description.affiliationCentro Universitário Integrado, Campo Mourao
dc.description.affiliationDepartment of Medicine State University of Maringa, Maringa
dc.description.affiliationRegional University Hospital of Maringa State University of Maringa
dc.description.affiliationDuke Global Health Institute
dc.description.affiliationHospital das Clinicas of the Medical School of Botucatu UNESP
dc.description.affiliationEducation Letters and Health Center State University of the West of Paraná, Paraná
dc.description.affiliationUnespHospital das Clinicas of the Medical School of Botucatu UNESP
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipIdCAPES: 001
dc.identifierhttp://dx.doi.org/10.5334/gh.1347
dc.identifier.citationGlobal Heart, v. 19, n. 1, 2024.
dc.identifier.doi10.5334/gh.1347
dc.identifier.issn2211-8179
dc.identifier.issn2211-8160
dc.identifier.scopus2-s2.0-85201245438
dc.identifier.urihttps://hdl.handle.net/11449/297684
dc.language.isoeng
dc.relation.ispartofGlobal Heart
dc.sourceScopus
dc.subjectBayesian analysis
dc.subjectepidemiology
dc.subjectischemic heart disease
dc.subjectspatiotemporal analysis
dc.titleBayesian Modeling and Estimation of Spatial Risk for Hospitalization and Mortality from Ischemic Heart Disease in Paraná, Brazilen
dc.typeArtigopt
dspace.entity.typePublication
relation.isOrgUnitOfPublicationa3cdb24b-db92-40d9-b3af-2eacecf9f2ba
relation.isOrgUnitOfPublication.latestForDiscoverya3cdb24b-db92-40d9-b3af-2eacecf9f2ba
unesp.author.orcid0000-0002-2372-7275[1]
unesp.author.orcid0000-0003-4637-3286[2]
unesp.author.orcid0000-0001-8445-0743[3]
unesp.author.orcid0000-0002-7343-4526[4]
unesp.author.orcid0000-0001-7330-2905[5]
unesp.author.orcid0000-0001-7061-5762 0000-0001-7061-5762[6]
unesp.author.orcid0000-0002-5926-6941[7]
unesp.author.orcid0000-0001-6460-8486[8]
unesp.author.orcid0000-0001-8508-700X[9]
unesp.author.orcid0000-0002-9156-7787[10]
unesp.author.orcid0000-0002-8517-0660[11]
unesp.author.orcid0000-0001-7276-0402[12]
unesp.author.orcid0000-0003-2077-1518 0000-0003-2077-1518[13]
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Medicina, Botucatupt

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