Evidence map›Paper›PMID 41121048›Full record

ArticleBMC pregnancy and childbirth2025

Geospatial analysis of preterm and small-for-gestational age births in Washington D.C.

Alina Peluso, Kate Michel, Kristin L Atkins, Shannon Gopaul-Balser, Tara Gibbons, Rachel K Scott

Abstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Alina PelusoOak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN, 37830, USA. pelusoa@ornl.gov.ORCID http://orcid.org/0000-0003-2895-0406
Kate MichelGeorgetown University, 3900 Reservoir Rd NW, Washington, D.C., 20007, USA.
Kristin L AtkinsUniversity of Virginia, 1340 Jefferson Park Ave, Charlottesville, VA, 22903, USA.
Shannon Gopaul-BalserHoward University, 2400 Sixth Street NW, Washington, D.C., 20059, USA.
Tara GibbonsGeorgetown University, 3900 Reservoir Rd NW, Washington, D.C., 20007, USA.
Rachel K ScottGeorgetown University, 3900 Reservoir Rd NW, Washington, D.C., 20007, USA.

Funding

Maternal Morbidity and Mortality: Risk Factors, Early Detection and Personalized InterventionUL1TR001409 · NCATS · GEORGETOWN UNIVERSITY · PI GONDRE-LEWIS, MARJORIE C, MELLMAN, THOMAS A · 2015 to 2024
$37.8M
NCATS NIH HHS UL1 TR001409NCATS NIH HHS UL1-TR001409
6 · The paper itself

Abstract

backgroundThis study is based on the recognition that adverse pregnancy outcomes significantly affect maternal and infant health, leading to increased morbidity and mortality. These outcomes are shaped by a complex interplay of individual-level factors—like maternal age and education—and community-level influences, including socio-economic status and access to healthcare. Understanding these determinants is crucial for developing effective public health strategies, especially for marginalized populations, by identifying high-risk areas and informing targeted interventions that address both individual and structural barriers.

methodsWe utilized geospatial analysis to explore the association between individual- and community-level factors and adverse pregnancy outcomes, specifically preterm birth (PTB) and small-for-gestational-age (SGA) birthweight in Washington, D.C. We used Empirical Bayes smoothing methods to calculate rates of adverse birth outcomes from 2010 to 2018 at the U.S. Census tract–level. Spatial scan statistics were used to investigate if adverse birth outcomes clustered in specific areas. ANOVA tests were conducted for individual- and community-level factors within identified clusters.

resultsSpatial analysis identified significant high-risk clusters for PTB and SGA infants primarily in southeastern Washington, D.C., particularly in Wards 7 and 8. Individuals residing within these clusters experienced a 47% increased risk of PTB (RR = 1.467) and a 56% increased risk of SGA (RR = 1.560) compared to those outside clusters. Space–time analysis revealed temporal variation, with PTB clusters persisting from 2011 to 2014 and SGA clusters extending through 2017. Compared to low-risk clusters, high-risk clusters had younger birthing individuals (mean age ~26.5 vs. ~33 years), lower maternal college degree attainment (~20% vs. ~80%), higher rates of late or no prenatal care (~16% vs. 11%), and increased prevalence of smoking and hypertension (all P < 0.001). Community-level indicators showed lower median household incomes ($40,000 vs. ~$105,000), greater poverty (~16% vs. ~7% below $10,000/year), higher public assistance use (~32% vs. ~5%), and reduced healthcare access (greater distances to emergency and specialty care) in high-risk areas (all P < 0.001). Neighborhood deprivation indices were significantly elevated, commutes were longer, and population density was lower in these clusters. These findings highlight that adverse birth outcomes cluster in neighborhoods with pronounced socioeconomic and health disparities.

conclusionHigh-risk birth clusters highlight intertwined factors: individual, socio-economic, and geographic. Addressing these requires comprehensive interventions focusing on social and structural determinants of health.

Indexed as

Infant, Small for Gestational AgePremature BirthAdultBayes TheoremDistrict of ColumbiaFemaleHumansInfant, NewbornPregnancyRisk FactorsSocioeconomic Disparities in HealthSocioeconomic FactorsSpatial AnalysisYoung AdultBirth outcomesCommunity-level factorsGeospatial analysisHealth disparitiesMaternal healthPregnancy risk factorsPreterm birthPublic healthSmall-for-gestational-age

Identifiers

PMID41121048
PMCPMC12542157

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.