Abstract Although infant mortality in the USA has trended downward since the 1930s, large racial disparities persist. Administrative data on maternal-infant health are shaped by the contexts in which they are collected, including systemic racial inequities. Analyzing these data requires integrating experiential knowledge to advance health equity. Guided by a Public Interest Technology framework – FAIR2 – we integrated experiential knowledge in the analysis of birth certificate data for participants in a community-based initiative aimed at improving infant health outcomes. Insights of mothers on what influenced their birth outcomes were drawn through a thematic literature review to help inform modeling assumptions and interpretation of results. The analysis sample included 1,535 infants born in 2017–2024 to 635 program participants enrolled during 2022–2024. We examined key birth outcomes across multiple pregnancies using mother fixed-effects models to control for unobserved characteristics, including the impact of discrimination. Results showed that gains in maternal education and enrollment in Women, Infants, and Children (WIC) program were positively associated with improved prenatal care, with WIC also impacting infant vitality. The onset of pre-pregnancy hypertension and diabetes was associated with an increased risk of admission to the NICU. Women’s insights suggest that the positive impact of education advancement is mediated by access to better jobs and maternity leave. Additionally, they underscore the link between hypertension and discrimination, pointing to the need for equity-focused education in the healthcare system. This study highlights the value of incorporating experiential knowledge into data analytics to advance the public interest via community- and policy-driven action for infant health equity.
Richter et al. (Thu,) studied this question.