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Record W2150585529 · doi:10.1093/aje/kwq496

Impact of Breastfeeding Duration on Age at Menarche

2011· article· en· W2150585529 on OpenAlexaff
Ban Al‐Sahab, Linda S. Adair, Mazen J. Hamadeh, Chris I. Ardern, Hala Tamim

Bibliographic record

VenueAmerican Journal of Epidemiology · 2011
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsYork University
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsBreastfeedingMenarcheDuration (music)MedicineDemographyBreast feedingPediatricsObstetricsInternal medicinePhysics

Abstract

fetched live from OpenAlex

The study aims to assess the relation between breastfeeding duration and age at menarche. Analysis was based on a cohort of 994 Filipino girls born in 1983-1984 and followed up from infancy to adulthood by the Cebu Longitudinal Health and Nutrition Survey. The main outcome was self-reported age at menarche. Cox regression was used to investigate the relation between duration of exclusive and any breastfeeding with age at menarche with adjustment sequentially for specific sets of known socioeconomic, maternal, genetic, and prenatal confounders. The estimated median of age at menarche was 13.08 years. After adjustment for potential confounders of the association of breastfeeding with age at menarche, exclusive breastfeeding duration retained an independent and significant association with age at menarche. An increase in 1 month of exclusive breastfeeding decreases the hazard of attaining earlier menarche by 6% (hazard ratio = 0.94, 95% confidence interval: 0.90, 0.98). Any breastfeeding duration was not associated with age at menarche. Although this is the first longitudinal study that reveals a negative association between exclusive breastfeeding and early menarche, the relation is still elusive. Further longitudinal studies within different contexts are warranted to assess the generalizability of these findings.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.035
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.000
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 head0.123
GPT teacher head0.400
Teacher spread0.278 · 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

Citations39
Published2011
Admission routes1
Has abstractyes

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