Breast-feeding, rapid growth in the first year of life and excess weight at the age of 2 years: the 3D Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To assess relationships between breast-feeding, rapid growth in the first year of life and overweight/obesity status at the age of 2 years. DESIGN: As part of an observational, longitudinal study beginning in early pregnancy, multivariable logistic regressions were used to assess associations between breast-feeding duration (total and exclusive) and rapid weight gain (RWG) between birth and 1 year of age, and to determine predictors of overweight/obesity status at the age of 2 years. SETTING: Nine hospitals located in the province of Quebec, Canada. PARTICIPANTS: A sample of 1599 term infants who participated in the 3D Cohort Study. RESULTS: Children having RWG in the first year and those having excess weight at the age of 2 years accounted for 28 % and < 10 %, respectively. In multivariable models, children breastfed < 6 months and from 6 months to < 1 year were, respectively, 2·5 times (OR 2·45; 95 % CI 1·76, 3·41) and 1·8 times (OR 1·78; 95 % CI 1·29, 2·45) more likely to show RWG up to 1 year of age compared to children breastfed ≥ 1 year. Children exclusively breastfed < 3 months had significantly greater odds of RWG in the first year (OR 1·94; 95 % CI 1·25, 3·04) compared to children exclusively breastfed for ≥ 6 months. Associations between breast-feeding duration (total or exclusive) and excess weight at the age of 2 years were not detected. RWG in the first year was found to be the main predictor of excess weight at the age of 2 years (OR 6·98; 95 % CI 4·35, 11·47). CONCLUSIONS: The potential beneficial effects of breast-feeding on rate of growth in the first year of life suggest that interventions promoting breast-feeding are relevant for obesity prevention early in life.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".