A team of AUB researchers, led by Dr. Hassan Dhaini, conducted a case control study that can set the basis for a novel birth defect risk prediction model.
The group analyzed data from the National Birth Defect Registry, a database maintained by the Lebanese Ministry of Public Health, the National Collaborative Perinatal Neonatal Network (NCPNN) records, a non-profit Lebanese network of 34 member hospitals in different Lebanese Governorates, and the National Air Quality Monitoring Network managed by the Lebanese Ministry of Environment.
Researchers examined medical records of 11,000 subjects including 553 birth defect cases across Lebanon and studied the association between maternal exposure to air pollutants during pregnancy and congenital anomalies, using both hypothesis-driven and machine learning approaches.
Main results show that maternal exposure to PM2.5 during the first trimester significantly increases the overall BD risk, and increases the risk of genitourinary and neural tube defects during specific gestational time windows.
The next step is to build on these findings to develop a novel birth defect risk prediction model.