Evidence map›Paper›PMID 41175825›Full record

ArticleSocial science & medicine (1982)2026

The impact of state safety-net policies on perinatal birth outcomes by maternal race.

Alexandra Eastus, Alina Schnake-Mahl, M Pia Chaparro, Felice Lê-Scherban, Gabriel L Schwartz, Caroline Kravitz, Brent A Langellier

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Article in Social science & medicine (1982), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Alexandra EastusDepartment of Health Management and Policy, Dornsife School of Public Health, Drexel University, Nesbitt Hall, 3215 Market St., Philadelphia, PA, 19104, USA. Electronic address: ae466@drexel.edu.
Alina Schnake-MahlDepartment of Health Management and Policy, Dornsife School of Public Health, Drexel University, Nesbitt Hall, 3215 Market St., Philadelphia, PA, 19104, USA; Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.
M Pia ChaparroDepartment of Health Systems and Population Health, School of Public Health, University of Washington, 305J Raitt Hall, Box 353410, Seattle, WA, 98195, USA.
Felice Lê-ScherbanDepartment of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Nesbitt Hall, 3215 Market St., Philadelphia, PA, 19104, USA.
Gabriel L SchwartzDepartment of Health Management and Policy, Dornsife School of Public Health, Drexel University, Nesbitt Hall, 3215 Market St., Philadelphia, PA, 19104, USA; Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.
Caroline KravitzDepartment of Health Management and Policy, Dornsife School of Public Health, Drexel University, Nesbitt Hall, 3215 Market St., Philadelphia, PA, 19104, USA.
Brent A LangellierDepartment of Health Management and Policy, Dornsife School of Public Health, Drexel University, Nesbitt Hall, 3215 Market St., Philadelphia, PA, 19104, USA.

Funding

Complex systems approaches to identify policy levers to reduce racial/ethnic disparities in diet and obesity in citiesR01MD015107 · NIMHD · DREXEL UNIVERSITY · PI LANGELLIER, BRENT ALAN · 2021 to 2024
$2.2M
NIMHD NIH HHS R01 MD015107
6 · The paper itself

Abstract

objectiveTo examine the association between state safety-net policy robustness and rates of low birthweight and preterm births (2007-2018).

methodsWe created a state safety-net policy robustness index incorporating policies related to administrative burden, benefits, and eligibility for seven programs that provide health insurance, food, shelter, and cash assistance. Using quasi-Poisson regression models (state and year fixed effects, time-varying confounders), we assessed the association between policy robustness and low birthweight and preterm birth rates and examined differential associations by race/ethnicity via stratified models.

resultsOur sample consisted of 2922 state-year-race observations for preterm births and 2017 observations for low birthweight births. Our stratified findings suggest that more robust safety-net policies (e.g., more benefits, greater eligibility, and less administrative burden) are associated with declines in low birthweight and preterm birth among historically marginalized and racialized groups, including infants born to Asian and Pacific Islander, Black, and Hispanic birthing people.

conclusionsThe combination of state safety-net programs may imply important roles in reducing the prevalence of low birthweight and preterm birth.

Indexed as

Health PolicyPregnancy OutcomePremature BirthRacial GroupsSafety-net ProvidersAdultFemaleHumansInfant, Low Birth WeightInfant, NewbornPregnancyUnited StatesHealth disparitiesHealth policyInfant healthSafety net

Identifiers

PMID41175825
PMCPMC12718674

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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.