Evidence map›Paper›PMID 37600935›Full record

ArticleCurrent developments in nutrition2023

Examining Prenatal Dietary Factors in Association with Child Autism-Related Traits Using a Bayesian Mixture Approach: Results from 2 United States Cohorts.

Kristen Lyall, Juliette Rando, Siwen Wang, Ghassan B Hamra, Jorge Chavarro, Marc G Weisskopf, Lisa A Croen, M Daniele Fallin, Irva Hertz-Picciotto, Heather E Volk and 2 more

Open access · goldAbstract read
In one paragraph

Article in Current developments in nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 25% 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

5 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

12 authors at 7 institutions in 1 country.

Kristen LyallAJ Drexel Autism Institute, Drexel University, Philadelphia, PA, United States.
Juliette RandoAJ Drexel Autism Institute, Drexel University, Philadelphia, PA, United States.
Siwen WangDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
Ghassan B HamraDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Jorge ChavarroDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
Marc G WeisskopfDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
Lisa A CroenDivision of Research, Kaiser Permanente Northern California, Oakland, CA, United States.
M Daniele FallinDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States.
Irva Hertz-PicciottoDepartment of Public Health Sciences, University of California, Davis, Davis, CA, United States.
Heather E VolkDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Rebecca J SchmidtDepartment of Public Health Sciences, University of California, Davis, Davis, CA, United States.
Craig J NewschafferCollege of Health and Human Development, Penn State University, State College, PA, United States.
Harvard University · USDrexel University · USJohns Hopkins University · USUniversity of California, Davis · USEmory University · USKaiser Permanente · USPennsylvania State University · US

Funding

BUILDS MARBLES: Biorepository Upkeep and Infrastructure for Longitudinal Data Sharing for MARBLESR24ES028533 · NIEHS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Brittany D. Chambers Butcher, Rebecca Jean Schmidt · 2017 to 2026
$2.3M
BUILDS MARBLES: Biorepository Upkeep and Infrastructure for Longitudinal Data Sharing for MARBLESU24ES028533 · NIEHS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CHAMBERS BUTCHER, BRITTANY D., SCHMIDT, REBECCA JEAN · 2023 to 2025
$1.2M
NIEHS NIH HHS R24 ES028533NIEHS NIH HHS U24 ES028533
6 · The paper itself

Abstract

Background: Prior work has suggested relationships between prenatal intake of certain nutrients and autism. Objectives: We examined a broad set of prenatal nutrients and foods using a Bayesian modeling approach. Methods: Participants were drawn from the Early Autism Risks Longitudinal Investigation ( Results: In adjusted analyses, the overall mixture effects of nutrients in Early Autism Risks Longitudinal Investigation and foods in both cohorts on SRS scores were not observed, though there was some suggestion of decreasing SRS scores with increasing overall nutrient mixture in NHSII. No associations were observed with folate within the context of this mixture, but holding other nutrients fixed, n-6 PUFAs were associated with lower SRS scores in NHSII. In both cohorts, lower SRS scores were observed with higher intake of some groupings of vegetables, though for differing types of vegetables across cohorts, and some vegetable groups were associated with higher SRS scores in NHSII. Conclusions: Our work extends prior research and suggests the need to further consider prenatal dietary factors from a combined effects perspective. In addition, findings here point to potential differences in nutrient associations based on a family history of autism, which suggests the need to consider gene interactions in future work.

Indexed as

autismBayesian mixture modelingdietEARLINHSIISocial Responsiveness Scale

Identifiers

PMID37600935
PMCPMC10432916
OpenAlexW4385233699

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.