Investigation of seasonal patterns of congenital anomalies (CAs) can help identify environmental risk factors. Smaller datasets and spatiotemporal variation in previous studies have lead to conflicting evidence. The aim of our study was to investigate previously described associations and to generate new hypotheses on the role of seasonal factors in the etiology of CAs using a large high quality European dataset.
The European Surveillance for Congenital Anomalies (EUROCAT) is a European network of standardized population-based registries for the surveillance of CAs. A 2000–2009 dataset involving 19 EUROCAT registries and over 63,000 CAs was utilized to investigate seasonal patterns. Analysis of EUROCAT defined CAs was performed in two steps; first on CAs previously associated with seasonal factors and second on all remaining CAs. CAs and monthly births were calculated back to month of last menstrual period after which trigonometric regression analysis was performed to explore seasonal trends in CA prevalence.
Our dataset confirmed seasonality for Ebstein’s anomaly (p<0.05), triscuspid atresia and stenosis (p<0.05), congenital hydronephrosis (p<0.001) and hip dislocation (p<0.001) and a new signal was generated for seasonality of situs inversus (p<0.001). We detected non-significant seasonal peaks for neural tube defects (p=0.0683) and spina bifida (p=0.0507) coinciding with influenza season. We were not able to detect seasonality for any other CAs. We were unable to confirm the associations between neural tube defects, some other anomalies and influenza.
The associations detected and the negative results provided can help future studies unravelling the etiology of CAs.
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