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Record W2946950316 · doi:10.1093/pch/pxz066.058

59 Age of introduction to cow milk and childhood growth

2019· article· en· W2946950316 on OpenAlexaffabout
Izabela Soczynska, Jonathon L. Maguire, Catherine S. Birken, Deborah L. O’Connor, David Dai, Mary Aglipay, Charles Keown‐Stoneman

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsHospital for Sick ChildrenSt. Michael's HospitalPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsSick childLibrary scienceResearch centreMedicineSociologyMedia studiesPediatrics

Abstract

fetched live from OpenAlex

Considerable debate exists around what age children should start consuming cow milk. The Canadian Paediatric Society recommends that cow milk be introduced between 9 and 12 months of age while American, Australian and UK guidelines recommend waiting until 12 months. Children who consume cow milk tend to be taller than those who do not, so earlier introduction may positively impact child height. However, later introduction may decrease weight gain and lower the risk of child obesity. The objectives of the study were to evaluate the association between the age of introduction to cow milk and child height (primary objective) and adiposity (secondary objective). A prospective cohort study was conducted through a large practice-based research network. The primary exposure was child age at introduction to cow milk measured using a parent-completed standardized questionnaire. The primary outcome was height-for-age z-score and the secondary outcome was body mass index z-score (BMIz) measured between 3 and 5 years of age. Multiple linear regression was used to evaluate the associations. A total of 1864 children were included in the study (54% male). On average, cow milk was introduced at 11.8 months (SD = 2.2) and almost all children (94.2%) had been introduced to cow milk by 2 years of age. Mean age at follow-up was 46.9 months (SD = 7.5). In the primary analysis, earlier introduction to cow milk was associated with taller children (p< 0.001). Each month earlier that cow milk was introduced was associated with 0.04 higher height-for-age z-score (95% CI: 0.02–0.06). For example, the height difference between a 4-year-old child introduced to cow milk at 12 months relative to 18 months was 0.25 height-for-age z-score units (95% CI: 013-0.36) or 1.05 cm (95% CI: 0.55–1.54 cm). Exploration of non-linearity using linear splines revealed the association between earlier introduction to cow milk and child height was statistically significant after 10 months of age but not before. In the secondary analysis, there was no association between age of introduction to cow milk and BMIz (p= 0.27). Earlier introduction to cow milk was associated with taller children by 3 to 5 years of age without increasing child adiposity. Canadian Paediatric Society recommendations for cow milk introduction as early as 9 months of age appear to be appropriate for optimizing childhood height. Future research is needed to understand the causal relationship between starting cow milk earlier and taller height.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.007
GPT teacher head0.253
Teacher spread0.246 · 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

Citations0
Published2019
Admission routes2
Has abstractyes

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