Mañana, JUEVES, 24 DE ABRIL, el sistema se apagará debido a tareas habituales de mantenimiento a partir de las 9 de la mañana. Lamentamos las molestias.

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dc.contributor.authorLlorente, José María
dc.contributor.authorOliván-Blázquez, Bárbara
dc.contributor.authorZuñiga-Antón, María
dc.contributor.authorMasluk, Bárbara
dc.contributor.authorAndrés, Eva
dc.contributor.authorGarcía-Campayo, Javier
dc.contributor.authorMagallón-Botaya, Rosa
dc.contributor.otherUAM. Departamento de Economía Aplicadaes_ES
dc.date.accessioned2019-02-26T17:36:29Z
dc.date.available2019-02-26T17:36:29Z
dc.date.issued2018-11-12
dc.identifier.citationFrontiers in Psychology 9.November (2018): Article 2182en_US
dc.identifier.issn1664-1078es_ES
dc.identifier.urihttp://hdl.handle.net/10486/686741
dc.description.abstractMajor depression etiopathogenesis is related to a wide variety of genetics, demographic and psychosocial factors, as well as to environmental factors. The objective of this study is to analyze sociodemographic and environmental variables that are related to the prevalence of depression through correlation analysis and to develop a regression model that explains the behavior of this disease from an ecological perspective. This is an ecological, retrospective, cross-sectional study. The target population was 1,148,430 individuals over the age of 16 who were registered in Aragon (Spain) during 2010, with electronic medical records in the community's primary health care centers. The spatial unit was the Basic Health Area (BHA). The dependent variable was the diagnosis of Depression and the ecological independent variables were: Demographic variables (gender and age), population distribution, typology of the entity, population structure by sex and age, by nationality, by education, by work, by salary, by marital status, structure of the household by number of members, and state of the buildings. The results show moderate and positive correlations with higher rates of depression in areas having a higher femininity index, higher population density, areas with a higher unemployment rate and higher average salary. The results of the linear regression show that aging +75 and rural entities act as protective factors for depression, while urban areas and deficient buildings act as risk factors. In conclusion, the ecological methodology may be a useful tool which, together with the statistical epidemiological analysis, can help in the political decision making process.en_US
dc.description.sponsorshipThis work was supported by the Health Institute Carlos III (grant number Medical research Council (grant number PS09/01378); Research Group B21_R17 of the Department of Research, Innovation and University of the Government of Aragon (Spain); and Feder Funds “Another way to make Europe”.en_US
dc.format.extent10 pag.es_ES
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherFrontiers Media S.A.en_US
dc.relation.ispartofFrontiers in Psychologyen_US
dc.rights© 2018 Llorente, Oliván-Blázquez, Zuñiga-Antón, Masluk, Andrés, Garcia-Campayo and Magallón-Botaya.es_ES
dc.subject.otherDepressionen_US
dc.subject.otherEnvironmental factorsen_US
dc.subject.otherPrevalenceen_US
dc.subject.otherSociodemographic factorsen_US
dc.subject.otherVariabilityen_US
dc.titleVariability of the prevalence of depression in function of sociodemographic and environmental factors: Ecological modelen_US
dc.typearticleen
dc.subject.ecienciaCiencias Socialeses_ES
dc.relation.publisherversionhttps://doi.org/10.3389/fpsyg.2018.02182es_ES
dc.identifier.doi10.3389/fpsyg.2018.02182es_ES
dc.identifier.publicationfirstpage2182-1es_ES
dc.identifier.publicationissueNovemberes_ES
dc.identifier.publicationlastpage2182-10es_ES
dc.identifier.publicationvolume9es_ES
dc.relation.projectIDGobierno de España. PS09/01378es_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.rights.ccReconocimientoes_ES
dc.rights.accessRightsopenAccessen
dc.facultadUAMFacultad de Ciencias Económicas y Empresariales


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