Abstract 14105: Geographic Variation in Infant Mortality Due to Congenital Heart Disease

Abstract

Background: Geographic variation in ischemic heart disease and stroke mortality is well-known and likely mediated by health care access, environmental, and sociodemographic factors. Little is known, however, about geographic variation in infant mortality due to congenital heart disease (CHD-IM). This study examines county-level estimates of CHD-IM to understand geographic patterns and factors that may influence variation in mortality. Methods: In this cross-sectional population-based study, we used linked live birth-infant death cohort files from the National Center for Health Statistics containing live births from 2006 to 2015 with cause of death attributed to congenital heart disease. Hierarchical Bayesian models were used to estimate CHD-IM rate for all US counties (N=3,142). Model based estimates were mapped to explore geographic patterns. Covariates included sex, maternal race and ethnicity, percentage of the county population below the poverty level, and proximity of the county to a US News and World Report top 50 ranked pediatric cardiac center (PCC). Results: From 2006 to 2015, there were 13,987 infant deaths due to congenital heart disease and 40,847,089 live births, giving an unadjusted CHD-IM rate of 0.34/1,000 live births. In our model, decreased mortality risk correlated with close proximity to a top 50 PCC, while increased mortality risk correlated with higher level of poverty. The figure shows predicted CHD-IM rates by county. Kentucky and Mississippi had the greatest proportion of counties with a predicted CHD-IM rate > 95th percentile. All counties in Connecticut, Massachusetts, and Rhode Island had a predicted CHD-IM rate < 5th percentile. Conclusion: Analyzing county-level variation of CHD-IM reveals patterns that can help to identify health care disparities and inform local efforts to understand and address variation in outcomes of infants born with congenital heart disease.