Infant feeding modifies the relationship between rapid weight gain in infancy and childhood obesity
Bibliographic record
Abstract
Rapid weight gain in infancy has been consistently associated with obesity later in life. Breastfed infants gain weight more slowly than formula‐fed infants and have a lower risk of later obesity in most studies. We used data from the PROBIT trial in the Republic of Belarus, for children followed from birth until 6–7 y of age (n=13,888), to examine whether infant feeding modifies the relationship between rapid weight gain in infancy and child obesity. Rapid weight gain (defined as a rate of gain greater than the 95 th percentile on the new WHO growth velocity standards) occurred in 3.2% of infants at 0–3 mo and 8.7% of infants at 0–6 mo of age. Rapid weight gain was strongly related to child obesity (defined as BMI‐for‐age greater than the 95 th percentile using the CDC growth reference) with AOR= 2.63, (95% CI 1.95–3.55) for 0–3 mo and AOR=3.09, (95% CI 2.48–3.85) for 0–6 mo, controlling for breastfeeding intensity (# breastfeeds/total # milk feeds), birth weight, maternal BMI, education, sex and sex by breastfeeding intensity interaction. The relationship of rapid weight gain at 0–3 mo to subsequent child obesity was significantly stronger in infants who had been exclusively formula‐fed since 1 mo of age (AOR=7.67, 95% CI 3.19–18.41) compared to other infants (AOR=2.34, 95% CI 1.70–3.23). It is important to consider feeding mode when examining the association between rapid weight gain in infancy and obesity later in life. Grant Funding Source : N/A
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".