Evidence map›Paper›PMID 38064212›Full record

ArticleJAMA network open2023

US County-Level Variation in Preterm Birth Rates, 2007-2019.

Sadiya S Khan, Adam S Vaughan, Katharine Harrington, Laura Seegmiller, Xiaoning Huang, Lindsay R Pool, Matthew M Davis, Norrina B Allen, Simon Capewell, Martin O'Flaherty and 6 more

Open 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. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.6field-weighted citation impact, top 6% 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

12 citing papers in PubMed, 17 citations in OpenAlex.

  1. The Influence of County Contexts on Preterm Births Among Latina Mothers in the US.Journal of racial and ethnic health disparities · 2026
    Article
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  7. Towards a new taxonomy of preterm birth.Journal of perinatology : official journal of the California Perinatal Association · 2025
    Review
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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

16 authors at 5 institutions in 2 countries.

Sadiya S KhanDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Adam S VaughanDivision for Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia.
Katharine HarringtonDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Laura SeegmillerDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Xiaoning HuangDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Lindsay R PoolDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Matthew M DavisDepartment of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Norrina B AllenDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Simon CapewellInstitute of Population Health, University of Liverpool, Liverpool, United Kingdom.
Martin O'FlahertyInstitute of Population Health, University of Liverpool, Liverpool, United Kingdom.
Gregory E MillerInstitute for Policy Research, Northwestern University, Evanston, Illinois.
Roxana MehranDepartment of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.
Birgit VogelDepartment of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.
Kiarri N KershawDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Donald M Lloyd-JonesDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
William A GrobmanDepartment of Obstetrics and Gynecology, The Ohio State University School of Medicine, Columbus.
Northwestern University · USIcahn School of Medicine at Mount Sinai · USUniversity of Liverpool · GBCenters for Disease Control and Prevention · USThe Ohio State University · US

Funding

PRegnancy OuTcomEs and subclinical Cardiovascular disease sTudy: (PROTECT)R01HL161514 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Sadiya Sana Khan · 2022 to 2026
$3.3M
NHLBI NIH HHS R01 HL161514
6 · The paper itself

Abstract

Importance: Preterm birth is a leading cause of preventable neonatal morbidity and mortality. Preterm birth rates at the national level may mask important geographic variation in rates and trends at the county level. Objective: To estimate age-standardized preterm birth rates by US county from 2007 to 2019. Design, Setting, and Participants: This serial cross-sectional study used data from the National Center for Health Statistics composed of all live births in the US between 2007 and 2019. Data analyses were performed between March 22, 2022, and September 29, 2022. Main Outcomes and Measures: Age-standardized preterm birth (<37 weeks' gestation) and secondarily early preterm birth (<34 weeks' gestation) rates by county and year calculated with a validated small area estimation model (hierarchical bayesian spatiotemporal model) and percent change in preterm birth rates using log-linear regression models. Results: Between 2007 and 2019, there were 51 044 482 live births in 2383 counties. In 2007, the national age-standardized preterm birth rate was 12.6 (95% CI, 12.6-12.7) per 100 live births. Preterm birth rates varied significantly among counties, with an absolute difference between the 90th and 10th percentile counties of 6.4 (95% CI, 6.2-6.7). The gap between the highest and lowest counties for preterm births was 20.7 per 100 live births in 2007. Several counties in the Southeast consistently had the highest preterm birth rates compared with counties in California and New England, which had the lowest preterm birth rates. Although there was no statistically significant change in preterm birth rates between 2007 and 2019 at the national level (percent change, -5.0%; 95% CI, -10.7% to 0.9%), increases occurred in 15.4% (95% CI, 14.1%-16.9%) of counties. The absolute and relative geographic inequalities were similar across all maternal age groups. Higher quartile of the Social Vulnerability Index was associated with higher preterm birth rates (quartile 4 vs quartile 1 risk ratio, 1.34; 95% CI, 1.31-1.36), which persisted across the study period. Similar patterns were observed for early preterm birth rates. Conclusions and Relevance: In this serial cross-sectional study of county-level preterm and early preterm birth rates, substantial geographic disparities were observed, which were associated with place-based social disadvantage. Stability in aggregated rates of preterm birth at the national level masked increases in nearly 1 in 6 counties between 2007 and 2019.

Indexed as

Premature BirthBayes TheoremCross-Sectional StudiesFemaleHumansInfantInfant, NewbornNew England

Identifiers

PMID38064212
PMCPMC10709777
OpenAlexW4389490467

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.