Funded by the National Institute of Minority Health and Health Disparities, we are investigating how upstream systems across housing, education, labor, and local governance shape racial and ethnic disparities in maternal and child health (MCH) across U.S. counties. Our goal is to move beyond traditional measures of social determinants of health to identify the structural drivers—the policies, institutions, and power structures—that create and sustain inequities in health. To do this, we are compiling a national dataset of county-level indicators that capture economic, political, and social systems that influence opportunity and wellbeing. Using machine learning and spatial analytic methods, we will then identify typologies of structural environments and link them to MCH outcomes to examine how place-based conditions drive disparities in preconception and perinatal health. By integrating data science and population health frameworks, we aim to reveal how places shape inequities and to inform structural interventions and policies that advance health equity for women, children, and families.