How Parental Predictors Jointly Affect the Risk of Offspring Congenital Heart Disease: A Nationwide Multicenter Study Based on the China Birth Cohort

ObjectiveCongenital heart disease (CHD) is complex in its etiology. Its genetic causes have been investigated, whereas the non-genetic factor related studies are still limited. We aimed to identify dominant parental predictors and develop a predictive model and nomogram for the risk of offspring CHD. MethodsThis was a retrospective study from November 2017 to December 2021 covering 44,578 participants, of which those from 4 hospitals in eastern China were assigned to the development cohort and those from 5 hospitals in central and western China were used as the external validation cohort. Univariable and multivariable analyses were used to select the dominant predictors of CHD among demographic characteristics, lifestyle behaviors, environmental pollution, maternal disease history, and the current pregnancy information. Multivariable logistic regression analysis was used to construct the model and nomogram using the selected predictors. The predictive model and the nomogram were both validated internally and externally. A web-based nomogram was developed to predict patient-specific probability for CHD. ResultsDominant risk factors for offspring CHD included increased maternal age [odds ratio (OR): 1.14, 95% CI: 1.10-1.19], increased paternal age (1.05, 95% CI: 1.02-1.09), maternal secondhand smoke exposure (2.89, 95% CI: 2.22-3.76), paternal drinking (1.41, 95% CI: 1.08-1.84), maternal pre-pregnancy diabetes (3.39, 95% CI: 1.95-5.87), maternal fever (3.35, 95% CI: 2.49-4.50), assisted reproductive technology (2.89, 95% CI: 2.13-3.94), and environmental pollution (1.61, 95% CI: 1.18-2.20). A higher household annual income (100,000-400,000 CNY: 0.47, 95% CI: 0.34-0.63; > 400,000 CNY: 0.23, 95% CI: 0.15-0.36), higher maternal education level (13-16 years: 0.68, 95% CI: 0.50-0.93; >= 17 years: 0.87, 95% CI: 0.55-1.37), maternal folic acid (0.21, 95% CI: 0.16-0.27), and multivitamin supplementation (0.33, 95% CI: 0.26-0.42) were protective factors. The nomogram showed good discrimination in both internal [area under the receiver-operating-characteristic curve (AUC): 0.843] and external validations (development cohort AUC: 0.849, external validation cohort AUC: 0.837). The calibration curves showed good agreement between the nomogram-predicted probability and actual presence of CHD. ConclusionWe revealed dominant parental predictors and presented a web-based nomogram for the risk of offspring CHD, which could be utilized as an effective tool for quantifying the individual risk of CHD and promptly identifying high-risk population.