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Abstract. Impact of breastfeeding on the intelligence quotient of eight-year-old children1

2015· article· en· W624907855 on OpenAlexaff
Fonseca A.L., Albernaz Elaine P., Kaufmann C.C., N. H., de Figueiredo V.L.

Bibliographic record

VenueRevista chilena de pediatría · 2015
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsImpact
Fundersnot available
KeywordsBreastfeedingMedicineRaven's Progressive MatricesConfoundingPediatricsCohortDemographyCohort studyProspective cohort studyIntelligence quotientInternal medicine

Abstract

fetched live from OpenAlex

This study aimed to determine the influence of breastfeeding on the intellectual capacity of children from a cohort in a developing country, with a control for the main confounding factors. A prospective cohort study was performed including all infants born in the hospitals of a medium-size city, and a random sample of these newborns was monitored at 30, 90, and 180 days of life, and at age 8 years. Several aspects of breastfeeding were assessed in the follow-up and, at 8 years, general intellectual capacity was assessed through the Raven's Colored Progressive Matrices test. The statistical analyses used Student's t-test, -ANOVA, and linear regression and logistics, considering p-values less than 0.05 as statistically significant associations. At age 8 years, 560 children were assessed with Raven's Colored Progressive Matrices test. The average score was 22.56 points, with a standard deviation of 5.93. The difference in the averages found between the breastfed and non-breastfed groups at six months of age was 1.33 (p = 0.008). Mother's and child's skin color, social and economic class, maternal education and smoking, and breastfeeding at six months of age (p = 0.007) were still associated with the outcome. Children that were breastfed for six months or more had better performance in the general -intellectual assessment, even after adjusting for the main confounding factors.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.324
Teacher spread0.277 · 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.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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