Evidence map›Paper›PMID 38122847›Full record

ArticleThe Journal of nutrition2024

Periconceptional Dietary Patterns and Adverse Pregnancy and Birth Outcomes.

Lisa M Bodnar, Sharon I Kirkpatrick, Sara M Parisi, Qianhui Jin, Ashley I Naimi

Open access · greenAbstract read
In one paragraph

Article in The Journal of nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
4.1field-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

8 citing papers in PubMed, 7 citations in OpenAlex.

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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

5 authors at 3 institutions in 2 countries.

Lisa M BodnarDepartment of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States; Department of Obstetrics, Gynecology, and Reproductive Sciences, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States. Electronic address: lbodnar@pitt.edu.
Sharon I KirkpatrickSchool of Public Health Sciences, University of Waterloo, Waterloo, Ontario, Canada.
Sara M ParisiDepartment of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
Qianhui JinDepartment of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
Ashley I NaimiDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States.
University of Pittsburgh · USEmory University · USUniversity of Waterloo · CA

Funding

Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
Preterm Birth in Nulliparous Women: An Understudied Population at Great RiskU10HD063036 · NICHD · RESEARCH TRIANGLE INSTITUTE · PI PARKER, CORETTE BREEDEN · 2010 to 2015
$19.5M
Institute for Clinical and Translational ScienceUL1TR000153 · NCATS · UNIVERSITY OF CALIFORNIA-IRVINE · PI COOPER, DAN M · 2012 to 2015
$12.1M
Informing national guidelines on diet patterns that promote healthy pregnancy outcomesR01HD102313 · NICHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BODNAR, LISA M, NAIMI, ASHLEY ISAAC · 2020 to 2024
$3.0M
Prevention of Preterm Birth in high Risk Nulliparous PatientsU10HD063047 · NICHD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI WAPNER, RONALD · 2010 to 2014
$1.9M
Preterm Birth in Nulliparous Women: An Understudied Population at Great RiskU10HD063053 · NICHD · UNIVERSITY OF UTAH · PI SILVER, ROBERT M. · 2010 to 2014
$1.7M
Preterm Birth in Nulliparous Women: An Understudied Population at Great Risk U10HD063020 · NICHD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI GROBMAN, WILLIAM ADAM · 2010 to 2014
$1.6M
Preterm Birth in Nulliparous Women: An Understudied Population at Great RiskU10HD063046 · NICHD · UNIVERSITY OF CALIFORNIA-IRVINE · PI WING, DEBORAH A · 2010 to 2014
$1.6M
Preterm Birth in Nulliparous Women: An Understudied Population at Great RiskU10HD063041 · NICHD · MAGEE-WOMEN'S RES INST AND FOUNDATION · PI SIMHAN, HYAGRIV N · 2010 to 2014
$1.5M
Preterm Birth in Nulliparous Women: An Understudied Population at Great RiskU10HD063048 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI PARRY, SAMUEL I. · 2010 to 2014
$1.5M
Dissecting the Genetic Etiology of Preterm Birth in Nulliparous WomenU10HD063037 · NICHD · INDIANA UNIVERSITY INDIANAPOLIS · PI HAAS, DAVID M. · 2010 to 2014
$1.2M
Adverse Outcomes in Nulliparous Pregnancies: The Ohio CollaborativeU10HD063072 · NICHD · CASE WESTERN RESERVE UNIVERSITY · PI MERCER, BRIAN M. · 2010 to 2014
$1.2M
NCATS NIH HHS UL1 TR000153NCATS NIH HHS UL1 TR001108NICHD NIH HHS R01 HD102313NICHD NIH HHS U10 HD063020NICHD NIH HHS U10 HD063036NICHD NIH HHS U10 HD063037NICHD NIH HHS U10 HD063041NICHD NIH HHS U10 HD063046NICHD NIH HHS U10 HD063047NICHD NIH HHS U10 HD063048NICHD NIH HHS U10 HD063053NICHD NIH HHS U10 HD063072
6 · The paper itself

Abstract

backgroundThe periconceptional period is a critical window for the origins of adverse pregnancy and birth outcomes, yet little is known about the dietary patterns that promote perinatal health.

objectiveWe used machine learning methods to determine the effect of periconceptional dietary patterns on risk of preeclampsia, gestational diabetes, preterm birth, small-for-gestational-age (SGA) birth, and a composite of these outcomes.

methodsWe used data from 8259 participants in the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (8 US medical centers, 2010‒2013). Usual daily periconceptional intake of 82 food groups was estimated from a food frequency questionnaire. We used k-means clustering with a Euclidean distance metric to identify dietary patterns. We estimated the effect of dietary patterns on each perinatal outcome using targeted maximum likelihood estimation and an ensemble of machine learning algorithms, adjusting for confounders including health behaviors and psychological, neighborhood, and sociodemographic factors.

resultsThe 4 dietary patterns that emerged from our data were identified as "Sandwiches and snacks" (34% of the sample); "High fat, sugar, and sodium" (29%); "Beverages, refined grains, and mixed dishes" (21%); and "High fruits, vegetables, whole grains, and plant proteins" (16%). One-quarter of pregnancies had preeclampsia (8% incidence), gestational diabetes (5%), preterm birth (8%), or SGA birth (8%). Compared with the "High fat, sugar, and sodium" pattern, there were 3.3 to 4.3 fewer cases of the composite adverse outcome per 100 pregnancies among participants following the "Beverages, refined grains and mixed dishes" pattern (risk difference -0.043; 95% confidence interval -0.078, -0.009), "High fruits, vegetables, whole grains and plant proteins" pattern (-0.041; 95% confidence interval -0.078, -0.004), and "Sandwiches and snacks" pattern (-0.033; 95% confidence interval -0.065, -0.002).

conclusionsOur results highlight that there are a variety of periconceptional dietary patterns that are associated with perinatal health and reinforce the negative health implications of diets high in fat, sugars, and sodium.

Indexed as

Diabetes, GestationalPre-EclampsiaPremature BirthDietFemaleFetal Growth RetardationHumansInfant, NewbornPlant ProteinsPregnancyPregnancy OutcomeSodiumSugarsVegetablesPlant ProteinsSodiumSugarsdietary patternsgestational diabetesmachine learningpreeclampsiapregnancypreterm birth

Identifiers

PMID38122847
PMCPMC10900249
OpenAlexW4389953762

What OpenQuestion holds

Textmetadata
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.