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Bisher wurden r\u00e4umliche Cluster der Unterimmunisierung jedoch kaum beachtet und auf Basis kleinr\u00e4umiger Daten typisiert.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Ziel der Arbeit<\/jats:title>\n                <jats:p>Anhand des Beispiels der Impfung gegen Masern, Mumps und R\u00f6teln (MMR) bei Kindern sollen in der vorliegenden Studie 1.\u00a0die r\u00e4umliche Verteilung nicht ausreichender MMR-Impfungen in Westfalen-Lippe kleinr\u00e4umig identifiziert, 2.\u00a0spezifische, r\u00e4umliche Risikocluster mit nicht ausreichendem Impfschutz aufgezeigt und 3.\u00a0r\u00e4umlich-nachbarschaftliche Einflussfaktoren der unterschiedlichen Risikocluster als Ansatzpunkte f\u00fcr Public-Health-Interventionen beschrieben werden.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Material und Methoden<\/jats:title>\n                <jats:p>Grundlage waren Abrechnungsdaten der Kassen\u00e4rztlichen Vereinigung Westfalen-Lippe (KVWL). Es wurden Geburtsjahrgangskohorten 2013\u20132016 von gesetzlich versicherten Kindern gebildet und auf Postleitzahlenebene (<jats:italic>n<\/jats:italic>\u202f=\u2009410) aggregiert. Es wurden statistisch signifikante, r\u00e4umlich kompakte Cluster und relative Risiken (RR) der Unterimmunisierung identifiziert. Lokale Risikomodelle wurden in bin\u00e4r logistischen Regressionen auf Basis von r\u00e4umlich-nachbarschaftlichen Variablen gesch\u00e4tzt.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Ergebnisse und Diskussion<\/jats:title>\n                <jats:p>F\u00fcr die Impfquoten \u201emindestens eine MMR-Impfung\u201c und \u201ebeide MMR-Impfungen\u201c wurden jeweils 2 signifikante Cluster der Unterimmunisierung identifiziert. Signifikante Risikofaktoren f\u00fcr niedrige Impfquoten umfassten Altersstruktur, sozio\u00f6konomische Variablen, Einwohnerdichte, medizinische Versorgung und Werthaltung. Die vorgeschlagene Methodik ist geeignet, r\u00e4umliche Variationen des Impfverhaltens auf Basis der identifizierten Typologien f\u00fcr gezielte evidenzbasierte Interventionen zu beschreiben.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s00103-021-03318-9","type":"journal-article","created":{"date-parts":[[2021,4,24]],"date-time":"2021-04-24T01:46:47Z","timestamp":1619228807000},"page":"600-609","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Geografische Analysen f\u00fcr evidenzbasierte Public-Health-Interventionen: Das Beispiel Identifikation und Typisierung von Risikoclustern f\u00fcr Masern, Mumps und R\u00f6teln","Geographic analyses as a\u00a0foundation for evidence-based public health interventions: the example identification and typology of risk clusters for mumps, measles, and rubella"],"prefix":"10.1007","volume":"64","author":[{"given":"Sebastian","family":"V\u00f6lker","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reinhard","family":"Hammerschmidt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anke","family":"Spura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,4,23]]},"reference":[{"key":"3318_CR1","unstructured":"WHO \u2013 World Health Organization (2019) TIP tailoring immunization programmes. https:\/\/www.euro.who.int\/en\/health-topics\/disease-prevention\/vaccines-and-immunization\/publications\/2019\/tip-tailoring-immunization-programmes-2019. 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