Evidence map›Paper›PMID 40293755›Full record

ArticleJAMA pediatrics2025

Trends in Maternal, Fetal, and Infant Mortality in the US, 2000-2023.

Robin Y Park, Alyssa Bilinski, Robbie M Parks, Seth Flaxman

Abstract read
In one paragraph

Article in JAMA pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Trends in maternal mortality rates by state, United States, 2018 to 2023.American journal of obstetrics and gynecology · 2026
    Article
  8. Article
  9. Article
  10. Review
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

4 authors.

Robin Y ParkDepartment of Engineering, University of Oxford, Oxford, United Kingdom.
Alyssa BilinskiDepartments of Health Services, Policy & Practice and Biostatistics, Brown University School of Public Health, Providence, Rhode Island.
Robbie M ParksDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York.
Seth FlaxmanDepartment of Computer Science, University of Oxford, Oxford, United Kingdom.

Funding

Observational causal inference with infectious disease outcomesR35GM155224 · NIGMS · BROWN UNIVERSITY · PI Alyssa Bilinski · 2024 to 2026
$1.1M
NIGMS NIH HHS R35 GM155224
6 · The paper itself

Abstract

Importance: Accurately measuring maternal mortality trends has been challenging due to changes in data collection. This work disambiguates trends from the effects of introducing the pregnancy checkbox on death certificates and also analyzes closely related fetal and infant mortality. Objective: To describe trends in maternal, fetal, and infant deaths since 2000, including the impact of the COVID-19 pandemic. Design, Setting, and Participants: A national, population-level, epidemiological, cross-sectional analysis during 2000 to 2023 was conducted as well as a staggered difference-in-differences analysis on the pregnancy checkbox, using the US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (WONDER) database on underlying causes of death in the US to identify maternal, infant, and fetal deaths. Study population was restricted to mothers aged 15 to 44 years for all definitions of maternal mortality. Exposures: Staggered introduction of the pregnancy checkbox on death certificates across different states. Main Outcomes and Measures: Longitudinal study (2000-2023) reporting crude rates per 100 000 population for adjusted maternal mortality and per 1000 population for fetal and infant mortality at the national level and by US Census Bureau-designated main census regions, age groups, and race and ethnicity. Staggered difference-in-differences counterfactuals (1999-2023) on impact of pregnancy checkbox. Results: The introduction of the pregnancy checkbox was associated with 6.78 (95% CI, 1.47-12.09) deaths per 100 000 live births increase in reported maternal mortality, 66% (95% CI, 14%-117%) of the total increase from 2000 to 2019, with a smaller impact on maternal mortality excluding cause unspecified (adjusted maternal death rates). Adjusted maternal death rates remained consistently between 6.75 (95% CI, 5.97-7.61) to 10.24 (95% CI, 9.22-11.34) per 100 000 live births from 2000 until 2021, when it peaked at 18.86 (95% CI, 17.48-20.32); the rate dropped to 10.23 (95% CI, 9.22-11.32) in 2022. The death rates of Native American or Alaska Native women increased the most during the COVID-19 period, almost tripling from 2011 to 2019 (10.70 per 100 000 live births; 95% CI, 7.64-14.57) to the 2020 to 2022 period (27.47 per 100 000 live births; 95% CI, 18.39-39.45). The death rates of non-Hispanic Black women were highest across time-approximately triple the rate of non-Hispanic White women in each time period. Infant death rates per 1000 live births dropped from 6.93 (95% CI, 6.85-7.01) in 2000 to 5.44 (95% CI, 5.36-5.51) in 2020, increasing slightly to 2018 levels in 2021 to 2023. Fetal death rates per 1000 live births decreased from 6.28 (95% CI, 6.16-6.31) in 2005 to 5.53 (95% CI, 5.45-5.60) in 2022. Conclusion and Relevance: Using difference-in-differences analyses, results of this study reveal that the pregnancy checkbox explained much of the observed increase in maternal mortality before the COVID-19 pandemic. Nevertheless, results of this cross-sectional study suggest that, even adjusting for pregnancy checkbox effects, most groups saw increases from 2011 to 2019 to the 2020 to 2022 period, indicating that the COVID-19 pandemic led to worse outcomes. The findings demonstrate the relevance of public health emergencies to maternal health outcomes.

Identifiers

PMID40293755
PMCPMC12038713

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.