Systems Science Approaches to Understand Neighborhood Opportunity and Racial/Ethnic Disparities in Maternal Morbidity

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Rising maternal mortality rates, and the significant racial/ethnic disparities that characterize them, result in black women dying from pregnancy-related causes at three to four times the rate of their white counterparts. Considering that for every maternal death, over 100 women experience severe maternal morbidity —a life- threatening diagnosis or condition occurring as a direct result of pregnancy and childbirth—the implications of reducing maternal morbidity for black maternal health are profound. Morbidity during the postpartum period, as represented by postpartum hospital readmissions, is also 30% more likely to impact black women. Effective interventions developed from a comprehensive, multilevel evidence base are needed to successfully eliminate these disparities. However, many of these multilevel factors remain understudied, and translation of evidence into action remains challenging due to complex inter-relationships across factors that produce unanticipated outcomes. The objectives of this study are to address this twofold gap by 1) investigating neighborhood opportunity access as an understudied multilevel factor in relation to racial/ethnic disparities in maternal morbidity and 2) using systems science methodologies, such as system dynamics, in a participatory framework to develop a causal system map that contextualizes the role of neighborhood opportunity access within the complex, inter-related system shaping racial/ethnic disparities in maternal morbidity. Using Philadelphia, PA as a base case, I will partner with the Maternal, Child, and Family Health Division in the Philadelphia Department of Public Health to leverage linked hospital discharge, birth record, and neighborhood indicator data to accomplish the following aims: (1) To estimate associations between neighborhood opportunity access and severe maternal morbidity, using a composite measure that includes indicators from the social, physical, and built environment, and assess whether it explains racial/ethnic disparities; (2) To estimate associations between neighborhood opportunity access and postpartum hospital readmissions, and assess whether it explains racial/ethnic disparities; (3) To develop a qualitative system map detailing the causal feedback structure driving associations between neighborhood opportunity access and racial/ethnic disparities peripartum maternal morbidity, contextualized within an ecosystem of other multilevel factors, using participatory system dynamics methodologies. The K01 will allow me to gain integral training in the use of administrative data for population health, advanced spatial statistics to geospatially contextualize health disparities, and participatory systems science methodologies to support the translation of evidence into action to eliminate health disparities. This will help me achieve my long-term goal of successfully building a rigorous research agenda that uses applied methodologies to understand the sociostructural determinants of racial/ethnic disparities in maternal and infant health and informs the development of sustainable policies and programs to eliminate them.