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Multimorbidity patterns in older adults: An approach to the complex interrelationships among chronic diseases

dc.rights.licensehttp://creativecommons.org/licenses/by/4.0es_MX
dc.creatorDOLORES MINO LEONes_MX
dc.creatorHORTENSIA REYES MORALESes_MX
dc.creatorSVETLANA VLADISLAVOVNA DOUBOVAes_MX
dc.creatorRicardo Perez-Cuevases_MX
dc.creatorMARTHA LILIANA GIRALDO RODRIGUEZes_MX
dc.creatorMarcela Agudelo Boteroes_MX
dc.date2017
dc.date.accessioned2021-12-15T20:33:55Z
dc.date.available2021-12-15T20:33:55Z
dc.identifier.urihttps://hdl.handle.net/20.500.12100/17348
dc.descriptionBackground and aims: There is a growing need for evidence based answers to multimorbidity, especially in primary care settings. The aim was estimate the prevalence and patterns of multimorbidity in a Mexican population of public health institution users ≥60 years old. Methods: Observational and multicenter study was carried out in four family medicine units in Mexico City; included older men and women who attended at least one consultation with their family doctor during 2013. The most common diseases were grouped into 11 domains. The observed and expected rates, as well as the prevalence ratios, were calculated for the pairs of the more common domains. Logistic regression models were developed to estimate the magnitude of the association. Cluster and principal components analyses were performed to identify multimorbidity patterns. Results: Half of all of the patients who were ≥60 years old and treated by a family doctor had multimorbidity. The most common disease domains were hypertensive and endocrine diseases. The highest prevalence of multimorbidity concerned the renal domain. The domain pairs with the strongest associations were endocrine + renal and hypertension + cardiac. The cluster and principal components analyses revealed five consistent patterns of multimorbidity. Conclusions: The domains grouped into five patterns could establish the framework for developing treatment guides, deepen the knowledge of multimorbidity, develop strategies to prevent it, decrease its burden, and align health services to the care needs that doctors face in daily practice.es_MX
dc.formatAdobe PDFes_MX
dc.languageenges_MX
dc.publisherElsevier and IMSSes_MX
dc.relationhttps://www.sciencedirect.com/science/article/abs/pii/S0188440917300528?via%3Dihubes_MX
dc.relation.requiresSies_MX
dc.rightsAcceso Abiertoes_MX
dc.sourceArchives of Medical Research (0188-4409) Vol. 48 (2017)es_MX
dc.subjectMEDICINA Y CIENCIAS DE LA SALUDes_MX
dc.subjectCiencias médicases_MX
dc.subjectCiencias clínicases_MX
dc.subjectGeriatríaes_MX
dc.subjectSalud públicaes_MX
dc.subjectPublic healthes_MX
dc.subjectFactores epidemiológicoses_MX
dc.subjectEpidemiologic factorses_MX
dc.subjectMultimorbilidades_MX
dc.subjectMultimorbidityes_MX
dc.subjectEnfermedades crónicases_MX
dc.subjectChronic diseaseses_MX
dc.subjectAtención primariaes_MX
dc.subjectPrimary health carees_MX
dc.subjectPersonas mayoreses_MX
dc.subjectOlder adultses_MX
dc.titleMultimorbidity patterns in older adults: An approach to the complex interrelationships among chronic diseaseses_MX
dc.typeArtículoes_MX
dc.audienceResearcherses_MX
dc.creator.idMILD650803MDFNNL06es_MX
dc.creator.idREMH510406MDFYRR02es_MX
dc.creator.idDOXS690510MNEBXV08es_MX
dc.creator.idCA1217102es_MX
dc.creator.idGIRM750612MNERDR04es_MX
dc.creator.idAUBM810307MNEGTR01es_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercaes_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercurpes_MX


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