Breastfeeding and the Developmental Origins of Asthma: Current Evidence, Possible Mechanisms, and Future Research Priorities
Bibliographic record
Abstract
Breastfeeding has many established health benefits, but its impact on asthma development is uncertain. Breastfeeding appears to have a positive and dose-dependent impact on respiratory health, particularly during early childhood and in high-risk populations; however, the strength and causality of these associations are unclear. It is challenging to compare results across studies due to methodological differences and biological variation. Resolving these inconsistencies will require well-designed, prospective studies that accurately capture asthma diagnoses and infant feeding exposures (including breastfeeding duration, exclusivity, and method of feeding), account for key confounders, evaluate dose effects, and consider effect modification and reverse causality. Mechanistic studies examining human milk bioactives and their impact on lung health and asthma development are beginning to emerge, and these will be important in establishing the causality and mechanistic basis of the observed associations between breastfeeding and asthma. In this review, we summarize current evidence on this topic, identify possible reasons for disagreement across studies, discuss potential mechanisms for a causal association, and provide recommendations for future research.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".