Implications of Restrictive Abortion Laws on Unintended Births in the U.S.: A Cross-Sectional Multilevel Analysis

Sara Redd, MSPH1, Whitney Rice, DrPH2 and Kelli Hall, PhD, MS2, (1)Emory University, Atlanta, GA, (2)Rollins School of Public Health, Emory University, Atlanta, GA

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Objective: This cross-sectional analysis examined associations between restrictive abortion policies and risk of unintended birth (UIB) among a cohort of U.S. women.

Methods: Individual-level data on UIBs were drawn from 75,207 women from 34 states who participated in the 2014 or 2015 Pregnancy Risk Assessment Monitoring System. State-level data on eleven abortion restrictions (ARs) were derived from the Guttmacher Institute and Temple University’s Policy Surveillance Program. Multilevel models estimated the relationship between our exposure (count of ARs in each state in 2014) and a woman’s risk of UIB. Adjusted models controlled for individual- and state-level covariates and cross-level interactions for individual factors hypothesized to vary by state context.

Results: Half of women (49%) reported an UIB. On average, states had 4 ARs implemented, the most common being gestational limits (76%) and public funding bans (62%). In adjusted models, for each additional AR present in a state, the odds of a woman reporting an UIB increased by 4% ([aOR]: 1.04, [95% CI]: 1.01, 1.07). Women had higher odds of reporting UIB if they were teenagers ([aOR]: 2.26, [95% CI]: 2.06, 2.47), Black ([aOR]: 1.72, [95% CI]: 1.63, 1.81), had Medicaid coverage pre-pregnancy ([aOR]: 1.32, [95% CI]: 1.20, 1.45), and resided in states with higher poverty levels ([aOR]: 1.03, [95% CI]: 1.01, 1.05).

Conclusion: Greater exposure to ARs was associated with increased risk of UIB, which varied by demographic and social context. Our ongoing research further examines the health effects of ARs over time and place using quasi-experimental designs and difference-in-difference modeling.

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