Family Size, Day-Care Attendance, and Breastfeeding in Relation to the Incidence of Childhood Asthma
Bibliographic record
Abstract
A hypothesis has been suggested stating that children exposed early to infections are less likely to develop atopy or asthma. The authors investigated the relation between risk of childhood asthma and number of siblings as well as day-care attendance, as factors possibly increasing the likelihood of early infections, and breastfeeding as a factor reducing them. A case-control study was carried out in Montréal, Canada, between 1988 and 1995 that included 457 children diagnosed with asthma at 3--4 years of age and 457 healthy controls. Cases followed for 6 years were later classified as persistent or transient by the symptoms and use of medication after diagnosis. Among cases diagnosed at 3--4 years of age, the adjusted odds ratio for asthma was 0.54 (95% confidence interval (CI): 0.36, 0.80) for one sibling and 0.49 (95% CI: 0.30, 0.81) for two or more. The adjusted odds ratio for day-care attendance before 1 year of age was 0.59 (95% CI: 0.40, 0.87). Results were similar with persistent cases. Among transient cases (who possibly had an infection with wheezing at 3--4 years of age), day-care attendance and a short duration of breastfeeding resulted in increased risk. The results support the hypothesis that opportunity for early infections reduces the risk of asthma.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".