Breastfeeding is associated with positive maternal-child health outcomes that includes reducing transmission of non-HIV infection such as COVID-19 from mother to baby 1. In the United States, rates of breastfeeding differ significantly depending on race and income status of mother 2. Mothers with lower rates of breastfeeding tend to be young, low-income, African American, unmarried, less educated, enrolled in the Supplemental Nutrition Program for Women, Infants, and Children (WIC), overweight or obese before pregnancy, and more likely to report their pregnancy was unintended 3. Given the complexity in breastfeeding disparities, there is an urgent need to develop breastfeeding interventions that include vulnerable and hard-to-reach populations. Electronic health records (EHRs) represent a unique data source that contains longitudinal clinical data that is linked to non-clinical data sources such as residential location, race, socio-economic status and other social determinants of health (SDoH)4. The goal of this proposal is to leverage mom-baby linked EHR and biomedical informatics to estimate geospatial patterns in breastfeeding and characterize the SDoH that impact breastfeeding outcomes in vulnerable and hard-to-reach populations.
