Evidence mapPaperPMID 41775648Full record

ArticleAmerican journal of epidemiology2026

Methodological considerations for investigating the impact of abortion restrictions on outcomes using aggregate panel data.

Alison Gemmill, Alexander Franks, Avi Feller, Elizabeth A Stuart, Eli Ben-Michael, Suzanne O Bell

Abstract read
In one paragraph

Article in American journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alison GemmillDepartment of Epidemiology, University of California Los Angeles Fielding School of Public Health, Los Angeles, CA, United States.ORCID 0000-0001-5879-9730
Alexander FranksDepartment of Statistics and Applied Probability, University of California, Santa Barbara, Santa Barbara, CA, United States.ORCID 0000-0002-9329-206X
Avi FellerDepartment of Statistics, Goldman School of Public Policy, University of California, Berkeley, Berkeley, CA, United States.ORCID 0000-0001-7319-5468
Elizabeth A StuartDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-9042-8611
Eli Ben-MichaelDepartment of Statistics and Data Science, Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA, United States.ORCID 0000-0002-1175-4129
Suzanne O BellDepartment of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-7650-5940

Funding

The fertility, maternal health, and infant health consequences of reproductive policy changeR01HD114292 · JOHNS HOPKINS UNIVERSITY · 2025 to 2025
$550k
The Hopkins Population CenterP2CHD042854 · JOHNS HOPKINS UNIVERSITY · 2025 to 2025
$423k
Human Development of the National Institutes of Health P2CHD042854Human Development of the National Institutes of Health R01HD114292National Institute of Child HealthNICHD NIH HHS L60 HD103256NICHD NIH HHS P2C HD042854NICHD NIH HHS R01 HD114292
6 · The paper itself

Abstract

Dramatic changes in the US abortion policy landscape have led to growing interest in studying the health and social impacts of abortion bans. Many studies of population-level impacts necessarily rely on panel designs using aggregate state-level data to strengthen causal inference, yet such analyses risk pitfalls if they apply generic evaluation frameworks that overlook the complexity of the US abortion context and relevant outcomes. This commentary provides practical guidance for researchers engaged in panel studies of abortion policy, as well as for peer reviewers who may be less familiar with the methodological and substantive considerations in this area. Drawing from recent work, we highlight abortion-specific challenges that require attention, including time-varying confounding and violation of parallel trends, COVID-era disruptions, data suppression, spillover effects, and subgroup heterogeneity. We further recommend assessing sensitivity to including Texas, given its earlier implementation of abortion restrictions and potential outsized influence on results. Ultimately, we emphasize that rigorous evaluation of abortion policies requires thoughtful study design, context-specific considerations, and collaboration between methodologists and subject-matter experts.

Indexed as

Abortion, InducedCOVID-19FemaleHumansPregnancyResearch DesignUnited Statesabortion policycausal inference methodspanel data

Identifiers

PMID41775648
PMCPMC13464492

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.