Association of Breastfeeding with Asthma in Young Aboriginal Children in Canada
Bibliographic record
Abstract
BACKGROUND: Few studies have investigated the factors associated with asthma in young Aboriginal children. OBJECTIVE: To characterize the association of demographic, environmental and early life factors with asthma in young Aboriginal children in Canada. METHODS: The 2006 Aboriginal Children's Survey was conducted among off-reserve Aboriginal children zero to six years of age to obtain information on Aboriginal children's development and well-being. The prevalence of asthma in Aboriginal children was obtained from the parental report of asthma as diagnosed by a health care professional. RESULTS: The prevalence of reported asthma among off-reserve Aboriginal children zero to six years of age (n=14,170) was 9.4%. Asthma prevalence in both exclusively breastfed children (6.8%) and ever but not exclusively breastfed children (9.0%) was significantly lower than that in nonbreastfed children (11.0%). In the multiple logistic regression analysis, exclusive breastfeeding was protective of asthma compared with nonbreastfeeding (OR 0.59 [95% CI 0.44 to 0.78]). Older age groups, male sex, having two or more older siblings, low birth weight, day care attendance and ear infection were significant risk factors for asthma. CONCLUSIONS: The prevalence of asthma among young Aboriginal children zero to six years of age living off reserve was slightly lower than that reported for all other Canadian children. Breastfeeding, especially exclusively breastfeeding, was protective of asthma in Aboriginal children, which is consistent with what has been observed in non-Aboriginal children in Canada. Public health interventions intended for reducing asthma incidence in young Aboriginal children should include breastfeeding promotion programs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".