ABSTRACT
Severe maternal morbidity (SMM), which encompasses conditions that put pregnant people most at risk
of dying (e.g., hemorrhage, sepsis, organ failure), doubled in the last two decades. The most common
precursors to SMM – anemia, hypertensive disorders of pregnancy (HDP), and cesarean birth – are also
increasing. People of color, especially Black and Native American people, are at increased risk for all
these outcomes. This Renewal proposal builds on our prior work to address inequities in maternal
outcomes. Via the Parent Grant, our team enhanced current understanding of the contribution of social
context (focusing on neighborhood social disadvantage) and maternal pre-pregnancy health (focusing on body
mass index) to SMM risk, using a unique data resource we built of California (CA) births. This Renewal uses
theoretically grounded approaches to address several remaining gaps in our understanding of maternal health
in the U.S. that were illuminated by the Parent Grant. We will build a unique resource of 16 million births in
three states from 1997-2021. The dataset longitudinally links vital records (live birth and fetal death certificates)
with hospital discharge data for mother and baby; includes residential address; and links data for repeat
pregnancies to the same person over time, thus providing the type of large-scale data with high-quality
information on maternal health and social context that the field needs to advance population-level research on
maternal health. All phases of the research will be guided by a community advisory board (CAB). Using an
intersectionality framework, Aim 1 will examine joint impacts of multiple forms of marginalization on SMM, its
subtypes (i.e., hypertension-, hemorrhage-, and sepsis-related SMM), and its precursors (i.e., HDP, anemia,
mode of birth). Indicators of marginalization include race-ethnicity, education, health care payer, nativity, and
census tract-level markers of social disadvantage and structural inequality (e.g., poverty, segregation). Using a
reproductive life-course framework, Aim 2 will determine the cumulative impact of social and medical risk
factors across successive pregnancies on maternal health (i.e., SMM, SMM subtypes, SMM precursors). We
will examine how factors related to social context (e.g., persistent census tract poverty), morbidity (e.g.,
persistent HDP), and mode of birth (primary cesarean birth) affect subsequent occurrence and recurrence of
the study outcomes. Aim 3 will use findings from Aims 1 and 2 to identify and prioritize strategies to improve
maternal health and equity. We will use a) causal inference methods (mediation and g-computation) to
understand mechanisms and compare the potential impact of selected hypothetical interventions on study
outcomes and disparities, and b) community-engaged prioritization methods to synthesize our findings and
prioritize next steps. By understanding risks across multiple forms of marginalization and successive
pregnancies, and guided by rigorous analytics and community-grounded knowledge, our work will contribute to
advancing the next generation of actionable population-level SMM equity research.
