Breastfeeding, maternal asthma and wheezing in the first year of life: a longitudinal birth cohort study
Bibliographic record
Abstract
The impact of breastfeeding on respiratory health is uncertain, particularly when the mother has asthma. We examined the association of breastfeeding and wheezing in the first year of life. We studied 2773 infants from the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort. Caregivers reported on infant feeding and wheezing episodes at 3, 6 and 12 months. Breastfeeding was classified as exclusive, partial (supplemented with formula or complementary foods) or none. Overall, 21% of mothers had asthma, 46% breastfed for at least 12 months and 21% of infants experienced wheezing. Among mothers with asthma, breastfeeding was inversely associated with infant wheezing, independent of maternal smoking, education and other risk factors (adjusted rate ratio (aRR) 0.52; 95% CI 0.35–0.77 for ≥12versus<6 months breastfeeding). Compared with no breastfeeding at 6 months, wheezing was reduced by 62% with exclusive breastfeeding (aRR 0.38; 95% CI 0.20–0.71) and by 37% with partial breastfeeding supplemented with complementary foods (aRR 0.63; 95% CI 0.43–0.93); however, breastfeeding was not significantly protective when supplemented with formula (aRR 0.89; 95% CI 0.61–1.30). Associations were not significant in the absence of maternal asthma (p-value for interaction <0.01). Breastfeeding appears to confer protection against wheezing in a dose-dependent manner among infants born to mothers with asthma.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".