PROJECT SUMMARY The Dobbs v. Jackson Women’s Health Organization Supreme Court decision, which eliminated federal protections for abortion rights, is an unprecedented policy change with implications for fertility, maternal health, and infant health in the US. Abortion is currently banned in 12 states and severely restricted in 14 others. Approximately one in three people who can become pregnant in the US reside in a state with little or no access to safe abortion services since the ruling, predominantly in the South and Midwest, where a disproportionate share of the population is Black or Hispanic. Restricting safe abortion services may differentially impact fertility rates of disadvantaged groups, with long term implications for population health and persisting disparities. Populations with the highest abortion rates are also at greater risk of poor pregnancy and birth outcomes, including late entry into prenatal care, preterm birth, low birthweight, and severe maternal morbidity. Abortion restrictions imposed following Dobbs may increase rates of negative pregnancy outcomes and widen disparities simply because more people who reside in those states, especially disadvantaged populations, are exposed to the risks associated with carrying a pregnancy to term. Post-Dobbs abortion restrictions may also directly impact risks of these outcomes via changes in clinical practice, accessibility of timely maternal care, and increases in stress. The proposed research will estimate the impact of the Supreme Court’s Dobbs decision on fertility and maternal and infant health outcomes over time and by subgroups in states that recently banned or restricted abortion services. We will use high-quality, state-specific monthly data from 2016 through 2024 from several sources, including state birth certificate data compiled nationally by the CDC, Census Bureau data, and administrative hospitalization data from State Inpatient Databases. For each Aim, we will estimate the impact of Dobbs on outcomes using a comparative interrupted time series design with control locations, establishing a strong counterfactual to support causal inference while also accounting for recent trends (e.g., declining fertility) and perturbations (e.g., COVID-19). For Aims 2 and 3, we will use a difference- in-difference decomposition approach to determine how much of the observed change in outcomes post- Dobbs is attributable to shifts in the composition of the birthing population versus changing risks, comparing restrictive and non-restrictive states. We propose the following specific aims: 1) Evaluate the impact of the Dobbs decision on fertility; 2) Determine the impact of the Dobbs decision on severe maternal morbidity; 3) Assess the impact of the Dobbs decision on infant birth outcomes, including preterm birth, low birthweight, and small for gestational age. This work will address major gaps in the literature regarding the causal impact of abortion restrictions on population health, in p...