Breastfeeding and allergies: time for a change in paradigm?
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review examines recent studies of the relationships between breastfeeding and the epidemiology of allergic diseases, especially atopic dermatitis in infants and asthma in early and later childhood. RECENT FINDINGS: Results from observational birth cohort studies, case-control studies, and one cluster randomized intervention trial have generally failed to demonstrate a protective effect of breastfeeding on outcomes of atopic dermatitis, allergic sensitization, wheezing, or asthma. Difficulties in interpretation relate to the absence of nonbreastfed control or reference groups in some studies, meaning outcomes can only be compared between different durations of breastfeeding. Studies with a nonbreastfed control group suggest there is an increased risk for atopy and asthma associated with breastfeeding and that prolonged breastfeeding may eventually reduce this increased risk. The family history, sex of the child, and the presence of other risk factors for allergy and asthma also influence the outcome. SUMMARY: Although breastfeeding is strongly recommended for its multiple benefits on child health, most recent studies do not confirm the 'conventional wisdom' that breastfeeding is protective against allergy and asthma. Early reduction in childhood wheezing may reflect protection from viral infections, but allergies and asthma at later ages may be increased.
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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) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".