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2012-08-28Zeitschriftenartikel DOI: 10.1186/1476-072X-11-37
Ecological analysis of social risk factors for Rotavirus infections in Berlin, Germany, 2007–2009
dc.contributor.authorWilking, Hendrik
dc.contributor.authorHöhle, Michael
dc.contributor.authorVelasco, Edward
dc.contributor.authorSuckau, Marlen
dc.contributor.authorEckmanns, Tim
dc.date.accessioned2018-05-07T16:12:05Z
dc.date.available2018-05-07T16:12:05Z
dc.date.created2013-01-09
dc.date.issued2012-08-28none
dc.identifier.otherhttp://edoc.rki.de/oa/articles/reuWPkm5RzGu2/PDF/28QpBf2LrkTb2.pdf
dc.identifier.urihttp://edoc.rki.de/176904/1396
dc.description.abstractBackground: Socioeconomic factors are increasingly recognised as related to health inequalities in Germany and are also identified as important contributing factors for an increased risk of acquiring infections. The aim of the present study was to describe in an ecological analysis the impact of different social factors on the risk of acquiring infectious diseases in an urban setting. The specific outcome of interest was the distribution of Rotavirus infections, which are a leading cause of acute gastroenteritis among infants and also a burden in the elderly in Germany. The results may help to generate more specific hypothesis for infectious disease transmission. Methods: We analysed the spatial distribution of hospitalized patients with Rotavirus infections in Berlin, Germany. The association between the small area incidence and different socio-demographic and economic variables was investigated in order to identify spatial relations and risk factors. Our spatial analysis included 447 neighbourhood areas of similar population size in the city of Berlin. We included all laboratory-confirmed cases of patients hospitalized due to Rotavirus infections and notified between 01/01/2007 and 31/12/2009. We excluded travel-associated and nosocomial infections. A spatial Bayesian Poisson regression model was used for the statistical analysis of incidences at neighbourhood level in relation to socio-demographic variables. Results: Altogether, 2,370 patients fulfilled the case definition. The disease mapping indicates a number of urban quarters to be highly affected by the disease. In the multivariable spatial regression model, two risk factors were identified for infants (eng
dc.language.isoeng
dc.publisherRobert Koch-Institut, Infektionsepidemiologie
dc.subjectRisk factorseng
dc.subjectRotavirus infectioneng
dc.subjectUrban healtheng
dc.subjectDisease clusteringeng
dc.subjectSocial environmenteng
dc.subjectBayesian inferenceeng
dc.subject.ddc610 Medizin
dc.titleEcological analysis of social risk factors for Rotavirus infections in Berlin, Germany, 2007–2009
dc.typeperiodicalPart
dc.identifier.urnurn:nbn:de:0257-10029115
dc.identifier.doi10.1186/1476-072X-11-37
dc.identifier.doihttp://dx.doi.org/10.25646/1321
local.edoc.container-titleInternational Journal of Health Geographics
local.edoc.fp-subtypeArtikel
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttp://www.ij-healthgeographics.com/content/11/1/37/
local.edoc.container-publisher-nameBioMedCentral
local.edoc.container-volume11
local.edoc.container-issue37
local.edoc.container-year2012

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