Abstract 4369666: Prediction of Cyanotic Congenital Heart Disease Risk Reveals Maternal Age and Ethnicity, but Not Education, as Significant Factors in U.S. Births from 2022–2023

Background: Cyanotic congenital heart disease (CCHD) accounts for nearly one-third of infant mortality from congenital anomalies, yet the role of social determinants in its development remains poorly understood. This study examined how maternal factors - age, education, and race - are associated with CCHD prevalence across births in a large national cohort. Methods: We analyzed 718,920 birth records from the CDC’s 2022–2023 National Vital Statistics System. The outcome variable, identified using birth certificate documentation, was the presence or absence of CCHD and was coded as a binary variable (1 = present, 0 = not present). The maternal demographic and social factors collected were age (18–55 years), education (less than high school, high school, some college, college completion), and race (White [ref], Black, Latina, Asian, American Indian). Regression analyses were conducted to predict CCHD using these factors. Linear regression examined general associations between maternal characteristics and CCHD while logistic regression accounted for the non-linear nature of CCHD as a rare binary outcome. All analyses were performed in Stata with statistical significance set at p<0.05. Results: CCHD was a rare outcome across the study period (0.06%), with a prevalence of 0.0677% in 2022 and 0.0523% in 2023, reflecting an approximate 22% relative decrease (p = 0.01). Each additional year of maternal age was associated with a 2.5% increase in odds of CCHD (OR=1.025, 95% CI: 1.0068–1.0434, p=0.007). Latina mothers had 36% lower odds of having a child with CCHD compared to White mothers (p<0.01). The other racial categories showed no statistical significance. Education level had no statistically significant association with CCHD risk. Conclusions: The findings suggest that maternal age and Latina ethnicity are significantly associated with CCHD outcomes whereas maternal education shows an inconsistent relationship. This suggests that ascribed characteristics or factors that are beyond the control of the mother are larger predictors of CCHD than factors that are in the mother’s control. Focusing on economic factors (e.g., income level and housing security) may yield different results. The study underscores the complex role of social factors in pediatric cardiac outcomes, the need for targeted prenatal screening to detect CCHD early in older mothers, and the importance of further investigation into structural determinants not captured in standard birth records.