Breastfeeding and risk of childhood asthma: a systematic review and meta-analysis
Bibliographic record
Abstract
Objective To investigate the relationship between breastfeeding and the development of paediatric asthma. Methods A systematic review and meta-analysis was conducted with MEDLINE, Embase, CINAHL and ProQuest Nursing and Allied Health source databases. Retrospective/prospective cohorts in children aged <18 years with breastfeeding exposure reported were included. The primary outcome was a diagnosis of asthma by a physician or using a guideline-based criterion. A secondary outcome was asthma severity. Results 42 studies met inclusion criteria. 37 studies reported the primary outcome of physician-/guideline-diagnosed asthma, and five studies reported effects on asthma severity. Children with longer duration/more breastfeeding compared to shorter duration/less breastfeeding have a lower risk of asthma (OR 0.84, 95% CI 0.75–0.93; I 2 = 62.4%). Similarly, a lower risk of asthma was found in children who had more exclusive breastfeeding versus less exclusive breastfeeding (OR 0.81, 95% CI 0.72–0.91; I 2 =44%). Further stratified analysis of different age groups demonstrated a lower risk of asthma in the 0–2-years age group (OR 0.73, 95% CI 0.63–0.83) and the 3–6-years age group (OR 0.69, 95% CI 0.55–0.87); there was no statistically significant effect on the ≥7-years age group. Conclusion The findings suggest that the duration and exclusivity of breastfeeding are associated with a lower risk of asthma in children aged <7 years.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.037 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".