Season of birth is associated with increased risk of atopic dermatitis in Japanese infants: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Several epidemiological studies have examined the possibility of a relationship between season of birth and atopic dermatitis (AD) and food allergy (FA), yet their results are contradictory. We investigated the association between season of birth and risk of AD and FA in Japanese infants. METHODS: Study subjects were 612 newborn infants born at a single obstetric/pediatric clinic without perinatal diseases. Season of birth was classified as spring (March-May), summer (June-August), autumn (September-November) or winter (December-February). AD was diagnosed according to the United Kingdom Working Party's criteria. FA was defined as present if there was a history of immediate allergic symptoms within 2 h after ingestion of a food. Specific IgE to the corresponding food was also assessed to support the diagnosis. We assessed the association between season of birth and risk of AD and FA using Cox proportional hazard models. RESULTS: We identified a total of 365 cases of AD occurring during 3659 person-months of follow-up. Compared with summer birth, autumn, winter, and spring birth were significantly positively associated with the risk of AD: adjusted HRs (95% CIs) were 2.67 (1.96-3.63), 1.42 (1.03-1.95), and 1.43 (1.04-1.98), respectively. We identified a total of 23 cases of physician-diagnosed FA occurring during 6815 person-months of follow-up. CONCLUSIONS: Being born in the summer is associated with a lower risk of AD compared to other seasons of birth. The low incidence of FA in our cohort group made it difficult to establish a valid association between FA and season of birth as the statistical power was low.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".