MétaCan
Menu
Back to cohort
Record W2114462161 · doi:10.1136/jech.2010.111955

Are dietary patterns in childhood associated with IQ at 8 years of age? A population-based cohort study

2011· article· en· W2114462161 on OpenAlexaff
Kate Northstone, Carol Joinson, Pauline Emmett, Andy Ness, Tomáš Paus

Bibliographic record

VenueJournal of Epidemiology & Community Health · 2011
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsMcGill UniversityUniversity of TorontoMontreal Neurological Institute and Hospital
FundersMedical Research CouncilUniversity of BristolWellcome Trust
KeywordsMedicineIntelligence quotientConfoundingCohortEarly childhoodCohort studyGeneration RPediatricsPopulationDemographyEnvironmental healthCognitionDevelopmental psychologyInternal medicinePsychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Little is known about the effects of overall diet in childhood and intelligence later in life. METHODS: The current study, based on the Avon Longitudinal Study of Parents and Children, uses data on children's diet reported by parents in food-frequency questionnaires at 3, 4, 7 and 8.5 years of age. Dietary patterns were identified using principal-components analysis and scores computed at each age. IQ was assessed using the Wechsler Intelligence Scale for Children at 8.5 years. Data on a number of confounders were collected, and complete data were available for 3966 children. RESULTS: After adjustment, the 'processed' (high fat and sugar content) pattern of diet at 3 years of age was negatively associated with IQ assessed at 8.5 years of age-a 1 SD increase in dietary pattern score was associated with a 1.67 point decrease in IQ (95% CI -2.34 to -1.00; p<0.0001). The 'health-conscious' (salad, rice, pasta, fish, fruit) pattern at 8.5 years was positively associated with IQ: a 1 SD increase in pattern score led to a 1.20 point increase in IQ (95% CI 0.52 to 1.88; p=0.001). CONCLUSION: There is evidence that a poor diet associated with high fat, sugar and processed food content in early childhood may be associated with small reductions in IQ in later childhood, while a healthy diet, associated with high intakes of nutrient rich foods described at about the time of IQ assessment may be associated with small increases in IQ.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.026
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.141
GPT teacher head0.378
Teacher spread0.236 · 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

Citations106
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Epidemiology & Community HealthSame topicNutritional Studies and DietFrench-language works237,207