Bibliographic record
Abstract
OBJECTIVE: To evaluate the association between breastfeeding and asthma in young Canadian children. METHODS: Baseline data from the National Longitudinal Survey of Children and Youth (a population-based study of child health and well-being) were used. A weighted sample of 331 100 (unweighted n = 2184) children between the ages of 12 and 24 months, whose biological mother reported data on breastfeeding and asthma, were included. Outcomes included parental report of physician-diagnosed asthma and wheeze in the previous year. Breastfeeding was categorized by duration as follows: less than 2 months, 2 to 6 months, 7 to 9 months, and longer than 9 months. Logistic regression analyses were conducted with breastfeeding duration dichotomized at various cutoffs. Important potential confounders were considered in the adjusted analyses. Published statistical methods appropriate for the sampling strategy were used. RESULTS: The prevalence of asthma was 6.3%; and wheeze, 23.9%. Almost half of the children (44.0%) were breastfed for less than 2 months. After adjustment for smoking, low birth weight, low maternal education, and sex, a duration of breastfeeding for 9 months or less was found to be a risk factor for asthma (odds ratio, 2.39; 99% confidence interval, 0.95-6.03) and wheeze (odds ratio, 1.54; 99% confidence interval, 1.04-2.29). A dose-response effect was observed with breastfeeding duration. CONCLUSIONS: A longer duration of breastfeeding appears to be protective against the development of asthma and wheeze in young children. More public health efforts should be directed toward increasing the initiation and duration of breastfeeding.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".