Evidence map›Paper›PMID 37535355›Full record

ArticleJAMA network open2023

Association of Pregnancy-Specific Alcohol Policies With Infant Morbidities and Maltreatment.

Sarah C M Roberts, Alex Schulte, Claudia Zaugg, Douglas L Leslie, Tammy E Corr, Guodong Liu

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
11.0field-weighted citation impact, top 1% of its field
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

21 citing papers in PubMed, 19 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Sarah C M RobertsDepartment of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, Oakland.
Alex SchulteDepartment of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, Oakland.
Claudia ZauggDepartment of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, Oakland.
Douglas L LeslieDepartment of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania.
Tammy E CorrDepartment of Pediatrics, Penn State College of Medicine, Hershey, Pennsylvania.
Guodong LiuDepartment of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania.
University of California, San Francisco · USPennsylvania State University · USPenn State Milton S. Hershey Medical Center · US

Funding

Alcohol and pregnancy: do state-level punitive and supportive policies matter?R01AA023267 · NIAAA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ROBERTS, SARAH C.M. · 2015 to 2025
$3.5M
NIAAA NIH HHS R01 AA023267
6 · The paper itself

Abstract

Importance: Research has found associations of pregnancy-specific alcohol policies with increased low birth weight and preterm birth, but associations with other infant outcomes are unknown. Objective: To examine the associations of pregnancy-specific alcohol policies with infant morbidities and maltreatment. Design, Setting, and Participants: This retrospective cohort study used outcome data from Merative MarketScan, a national database of private insurance claims. The study cohort included individuals aged 25 to 50 years who gave birth to a singleton between 2006 and 2019 in the US, had been enrolled 1 year before and 1 year after delivery, and could be matched with an infant. Data were analyzed from August 2021 to April 2023. Exposures: Nine state-level pregnancy-specific alcohol policies obtained from the National Institute on Alcohol Abuse and Alcoholism's Alcohol Policy Information System. Main Outcomes and Measures: The primary outcomes were 1 or more infant injuries associated with maltreatment and infant morbidities associated with maternal alcohol consumption within the first year. Logistic regression, adjusting for individual-level and state-level controls, and fixed effects for state, year, state-specific time trends, and SEs clustered by state were used. Results: A total of 1 432 979 birthing person-infant pairs were included (mean [SD] age of birthing people, 32.2 [4.2] years); 30 157 infants (2.1%) had injuries associated with maltreatment, and 44 461 (3.1%) infants had morbidities associated with alcohol use during pregnancy. The policies of Reporting Requirements for Assessment/Treatment (adjusted odds ratio [aOR], 1.28; 95% CI, 1.08-1.52) and Mandatory Warning Signs (aOR, 1.18; 95% CI, 1.10-1.27) were associated with increased odds of infant injuries but not morbidities. Priority Treatment for Pregnant Women Only was associated with decreased odds of infant injuries (aOR, 0.83; 95% CI, 0.76-0.90) but not infant morbidities. Civil Commitment was associated with increased odds of infant injuries (aOR, 1.26; 95% CI, 1.08-1.48) but decreased odds of infant morbidities (aOR, 0.57; 95% CI, 0.53-0.62). Priority Treatment for Pregnant Women and Women With Children was associated with increased odds of both infant injuries (aOR, 1.12; 95% CI, 1.00-1.25) and infant morbidities (aOR, 1.08; 95% CI, 1.03-1.13). Reporting Requirements for Child Protective Services, Reporting Requirements for Data, Child Abuse/Neglect, and Limits on Criminal Prosecution were not associated with infant injuries or morbidities. Conclusions and Relevance: In this cohort study, most pregnancy-specific alcohol policies were not associated with decreased odds of infant injuries or morbidities. Policy makers should not assume that pregnancy-specific alcohol policies improve infant health.

Indexed as

Premature BirthChildCohort StudiesFemaleHumansInfant, NewbornParturitionPregnancyPublic PolicyRetrospective Studies

Identifiers

PMID37535355
PMCPMC10401306
OpenAlexW4385515042

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.