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Record W4400194534 · doi:10.1016/j.ajcnut.2024.06.013

Association of maternal fish consumption and ω-3 supplement use during pregnancy with child autism-related outcomes: results from a cohort consortium analysis

2024· article· en· W4400194534 on OpenAlexfundno aff
Kristen Lyall, Matt Westlake, Rashelle J. Musci, Kennedy Gachigi, Emily S. Barrett, Theresa M. Bastain, Nicole R Bush, Claudia Buß, Carlos A. Camargo, Lisa Croen, Dana Dabelea, Anne L Dunlop, Amy J Elliott, Assiamira Ferrara, Akhgar Ghassabian, James E. Gern, Marion E. Hare, Irva Hertz‐Picciotto, Alison E. Hipwell, Christine W. Hockett, Margaret R Karagas, Claudia Lugo‐Candelas, Thomas G. O’Connor, Rebecca J. Schmidt, Joseph B Stanford, Jennifer K Straughen, Coral L. Shuster, Robert O Wright, Rosalind J. Wright, Qi Zhao, Emily Oken, P. Brian Smith, KL Newby, Lisa P. Jacobson, DJ Catellier, Richard Gershon, David Cella, AN Alshawabkeh, José F. Cordero, John D. Meeker, Judy L. Aschner, Steven L. Teitelbaum, Annemarie Stroustrup, J. Jonathan Mansbach, JM Spergel, ME Samuels-Kalow, MD Stevenson, CS Bauer, Daphne Koinis Mitchell, Sean Deoni, Viren D’Sa, CS Duarte, Catherine Monk, Jonathan Posner, Glorisa Canino, Christine M. Seroogy, Casper G. Bendixsen, Kate Keenan, Catherine J. Karr, Frances A. Tylavsky, A. Stuart Mason, Qi Zhao, Sheela Sathyanarayana, KZ LeWinn, B. Lester, B Carter, Steve Pastyrnak, Charles R. Neal, Laurie A. Smith, Jennifer Helderman, ST Weiss, Augusto A. Litonjua, George O'connor, Robert S. Zeiger, Leonard B. Bacharier, Heather E. Volk, Sally Ozonoff, Hyagriv N. Simhan, JM Kerver, Charles Barone, Christopher Fussman, Nigel Paneth, M Elliott, Douglas M. Ruden, Christina A. Porucznik, Angelo P. Giardino, Massimo Innocenti, Robert M. Silver, Elisabeth Conradt, Michelle Bosquet-Enlow, Kathi Huddleston, Ruby H.N. Nguyen, Leonardo Trasande, Shanna H. Swan

Bibliographic record

VenueAmerican Journal of Clinical Nutrition · 2024
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsnot available
FundersDuke Clinical Research InstituteNYU Grossman School of MedicineMichigan Department of Health and Human ServicesJohns Hopkins Bloomberg School of Public HealthJohns Hopkins UniversityCollege of Engineering, Michigan State UniversityChildren’s Hospital of Wisconsin Research InstituteOffice of Behavioral and Social Sciences ResearchYork UniversityNational Center for Advancing Translational SciencesSeattle Children's Research InstituteBrigham and Women's HospitalKaiser PermanenteMichigan State UniversityMedical Center, University of PittsburghUniversity of PittsburghNational Institute of Diabetes and Digestive and Kidney DiseasesWake Forest UniversityUtah State UniversityNational Institute of Environmental Health SciencesUniversity of MinnesotaGeorge Mason UniversityWayne State UniversityNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsAutismPregnancyOdds ratioMedicineAutism spectrum disorderCohortConfidence intervalCohort studyPediatricsPsychiatryInternal medicineBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Prenatal fish intake is a key source of omega-3 (ω-3) polyunsaturated fatty acids needed for brain development, yet intake is generally low, and studies addressing associations with autism spectrum disorder (ASD) and related traits are lacking. OBJECTIVE: This study aimed to examine associations of prenatal fish intake and ω-3 supplement use with both autism diagnosis and broader autism-related traits. METHODS: Participants were drawn from 32 cohorts in the Environmental influences on Child Health Outcomes Cohort Consortium. Children were born between 1999 and 2019 and part of ongoing follow-up with data available for analysis by August 2022. Exposures included self-reported maternal fish intake and ω-3/fish oil supplement use during pregnancy. Outcome measures included parent report of clinician-diagnosed ASD and parent-reported autism-related traits measured by the Social Responsiveness Scale (SRS)-second edition (n = 3939 and v3609 for fish intake analyses, respectively; n = 4537 and n = 3925 for supplement intake analyses, respectively). RESULTS: In adjusted regression models, relative to no fish intake, fish intake during pregnancy was associated with reduced odds of autism diagnosis (odds ratio: 0.84; 95% confidence interval [CI]: 0.77, 0.92), and a modest reduction in raw total SRS scores (β: -1.69; 95% CI: -3.3, -0.08). Estimates were similar across categories of fish consumption from "any" or "less than once per week" to "more than twice per week." For ω-3 supplement use, relative to no use, no significant associations with autism diagnosis were identified, whereas a modest relation with SRS score was suggested (β: 1.98; 95% CI: 0.33, 3.64). CONCLUSIONS: These results extend previous work by suggesting that prenatal fish intake, but not ω-3 supplement use, may be associated with lower likelihood of both autism diagnosis and related traits. Given the low-fish intake in the United States general population and the rising autism prevalence, these findings suggest the need for better public health messaging regarding guidelines on fish intake for pregnant individuals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.366
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2024
Admission routes1
Has abstractyes

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