Evidence Hub

Global birth prevalence of congenital heart defects 1970–2017: updated systematic review and meta-analysis of 260 studies

Yingjuan Liu, Sen Chen, L. Zühlke, G. Black, M. Choy, Ning-Xiu Li, B. Keavney

International Journal of Epidemiology, 2019

1,216 citations

Abstract

Abstract Background Globally, access to healthcare and diagnostic technologies are known to substantially impact the reported birth prevalence of congenital heart disease (CHD). Previous studies have shown marked heterogeneity between different regions, with a suggestion that CHD prevalence is rising globally, but the degree to which this reflects differences due to environmental or genetic risk factors, as opposed to improved detection, is uncertain. We performed an updated systematic review to address these issues. Methods Studies reporting the birth prevalence of CHD between the years 1970–2017 were identified from searches of PubMed, EMBASE, Web of Science and Google Scholar. Data on the prevalence of total CHD and 27 anatomical subtypes of CHD were collected. Data were combined using random-effect models. Subgroup and meta-regression analyses were conducted, focused on geographical regions and levels of national income. Results Two hundred and sixty studies met the inclusion criteria, encompassing 130 758 851 live births. The birth prevalence of CHD from 1970–2017 progressively increased to a maximum in the period 2010–17 of 9.410/1000 [95% CI (confidence interval) 8.602–10.253]. This represented a significant increase over the fifteen prior years (P = 0.031). The change in prevalence of mild CHD lesions (ventricular septal defect, atrial septal defect and patent ductus arteriosus) together explained 93.4% of the increased overall prevalence, consistent with a major…

How strong is the evidence?

Evidence Hub reads this as a meta-analysis. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free