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Record W4213102564 · doi:10.1002/lipd.12338

Docosahexaenoic acid and arachidonic acid levels are correlated in human milk: Implications for new European infant formula regulations

2022· article· en· W4213102564 on OpenAlexafffund
Kathryn E. Hopperton, Michael A. Pitino, Kathryn Walton, Alex Kiss, Sharon Unger, Deborah L. O’Connor, Richard P. Bazinet

Bibliographic record

VenueLipids · 2022
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsInstitute for Clinical Evaluative SciencesSunnybrook Health Science CentreUniversity of TorontoSinai Health SystemHospital for Sick Children
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsDocosahexaenoic acidLipidologyColostrumInfant formulaArachidonic acidClinical chemistryFatty acidBreast milkEuropean unionFood scienceLactationChemistryBiochemistryBiologyPolyunsaturated fatty acidPregnancyImmunology

Abstract

fetched live from OpenAlex

From February 2022, all infant formula sold in the European Union must contain docosahexaenoic acid (DHA) at ~0.33%-1.14% of total fat with no minimum requirement for arachidonic acid (ARA). This work examines the association between DHA and ARA levels in human milk, the gold standard for infant feeding. Human milk (n = 470) was collected over 12-weeks postpartum from lactating mothers (n = 100) of infants born weighing <1250 g (NCT02137473). Fatty acids were analyzed by gas chromatography. ARA and DHA concentrations were associated in human milk (β = 0.47 [95% confidence interval 0.38-0.56] mol%), including transitional and mature milk, but not colostrum. This remained significant upon adjustment for percentages of other saturated, monounsaturated, n-3, or n-6 fatty acids, day of sample collection, or maternal characteristics (body mass index, ethnicity, education, and income). Infant formulas containing relatively high concentrations of DHA without ARA, as permitted by the new regulations, would not reflect the balance of these fatty acids in human milk.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.335
Teacher spread0.284 · 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 teacher head, 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

Citations6
Published2022
Admission routes2
Has abstractyes

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