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dc.contributor.authorBest, Kate E.
dc.contributor.authorRankin, Judith
dc.contributor.authorDolk, Helen
dc.contributor.authorLoane, Maria
dc.contributor.authorHaeusler, Martin
dc.contributor.authorNelen, Vera
dc.contributor.authorVerellen-Dumoulin, Christine
dc.contributor.authorGarne, Ester
dc.contributor.authorSayers, Gerardine
dc.contributor.authorMullaney, Carmel
dc.contributor.authorO'Mahony, Mary
dc.contributor.authorGatt, Miriam
dc.contributor.authorde Walle, Hermien
dc.contributor.authorKlungsøyr, Kari
dc.contributor.authorMokoroa, Olatz
dc.contributor.authorCavero-Carbonell, Clara
dc.contributor.authorKurinczuk, Jennifer J.
dc.contributor.authorDraper, Elizabeth S.
dc.contributor.authorTucker, David
dc.contributor.authorWellesley, Diana
dc.contributor.authorZymak-Zakutnia, Natalya
dc.contributor.authorLelong, Nathalie
dc.contributor.authorKhoshnood, Babak
dc.date.accessioned2021-08-02T10:55:58Z
dc.date.available2021-08-02T10:55:58Z
dc.date.created2020-11-10T11:39:26Z
dc.date.issued2020
dc.identifier.issn0269-5022
dc.identifier.urihttps://hdl.handle.net/11250/2765821
dc.description.abstractBackground Public health organisations use public health indicators to guide health policy. Joint analysis of multiple public health indicators can provide a more comprehensive understanding of what they are intended to evaluate. Objective To analyse variaitons in the prevalence of congenital anomaly-related perinatal mortality attributable to termination of pregnancy for foetal anomaly (TOPFA) and prenatal diagnosis of congenital anomaly prevalence. Methods We included 55 363 cases of congenital anomalies notified to 18 EUROCAT registers in 10 countries during 2008-12. Incidence rate ratios (IRR) representing the risk of congenital anomaly-related perinatal mortality according to TOPFA and prenatal diagnosis prevalence were estimated using multilevel Poisson regression with country as a random effect. Between-country variation in congenital anomaly-related perinatal mortality was measured using random effects and compared between the null and adjusted models to estimate the percentage of variation in congenital anomaly-related perinatal mortality accounted for by TOPFA and prenatal diagnosis. Results The risk of congenital anomaly-related perinatal mortality decreased as TOPFA and prenatal diagnosis prevalence increased (IRR 0.79, 95% confidence interval [CI] 0.72, 0.86; and IRR 0.88, 95% CI 0.79, 0.97). Modelling TOPFA and prenatal diagnosis together, the association between congenital anomaly-related perinatal mortality and TOPFA prevalence became stronger (RR 0.70, 95% CI 0.61, 0.81). The prevalence of TOPFA and prenatal diagnosis accounted for 75.5% and 37.7% of the between-country variation in perinatal mortality, respectively. Conclusion We demonstrated an approach for analysing inter-linked public health indicators. In this example, as TOPFA and prenatal diagnosis of congenital anomaly prevalence decreased, the risk of congenital anomaly-related perinatal mortality increased. Much of the between-country variation in congenital anomaly-related perinatal mortality was accounted for by TOPFA, with a smaller proportion accounted for by prenatal diagnosis.en_US
dc.language.isoengen_US
dc.publisherWileyen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleMultilevel analyses of related public health indicators: The European Surveillance of Congenital Anomalies (EUROCAT) Public Health Indicatorsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2020 The Authorsen_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.doi10.1111/ppe.12655
dc.identifier.cristin1846498
dc.source.journalPaediatric and Perinatal Epidemiologyen_US
dc.source.pagenumber122-129en_US
dc.identifier.citationPaediatric and Perinatal Epidemiology. 2020, 34 (2), 122-129.en_US
dc.source.volume34en_US
dc.source.issue2en_US


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