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Multilevel analyses of related public health indicators: The European Surveillance of Congenital Anomalies (EUROCAT) Public Health Indicators
Author(s) -
Best Kate E.,
Rankin Judith,
Dolk Helen,
Loane Maria,
Haeusler Martin,
Nelen Vera,
VerellenDumoulin Christine,
Garne Ester,
Sayers Gerardine,
Mullaney Carmel,
O'Mahony Mary T.,
Gatt Miriam,
De Walle Hermien,
Klungsoyr Kari,
Carolla Olatz Mokoroa,
CaveroCarbonell Clara,
Kurinczuk Jennifer J.,
Draper Elizabeth S.,
Tucker David,
Wellesley Diana,
ZymakZakutnia Nataliia,
Lelong Nathalie,
Khoshnood Babak
Publication year - 2020
Publication title -
paediatric and perinatal epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.667
H-Index - 88
eISSN - 1365-3016
pISSN - 0269-5022
DOI - 10.1111/ppe.12655
Subject(s) - medicine , poisson regression , public health , anomaly (physics) , pregnancy , pediatrics , confidence interval , prenatal diagnosis , rate ratio , prenatal care , demography , infant mortality , obstetrics , environmental health , fetus , population , physics , nursing , sociology , biology , genetics , condensed matter physics
Background 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.