Prevalence and risk factors of asthma in urban Canadian aboriginal children
Bibliographic record
Abstract
Several studies have investigated the prevalence and risk factors of asthma in school-age children, adolescents and adults in Canadian Aboriginal population. However, only a few studies have investigated asthma morbidity in young Aboriginal children. The objective of the study was to determine the prevalence and risk factors of asthma in urban Aboriginal children aged 0 to 6 years. The data from 14,170 children who participated in the 2006 Canadian Aboriginal Children Survey were considered for this study. Children living in the First Nations reserves were excluded from the survey. Designed weights were used to adjust for overlap with other surveys, non-response and post-stratification. Asthma prevalence for children with North American Indian, Métis, Inuit and Multiple ancestries were 10.0%, 8.5%, 6.6% and 9.7%, respectively. Asthma prevalence was greater in boys than girls (11.4% vs. 7.3%). In the multivariate analysis, low birth weight, respiratory allergy, ear infection and daycare attendance were risk factors for asthma. Breastfeeding, having more healthcare access and playing more frequently outside were protective factors for asthma. The influence of respiratory allergy on asthma was modified by ear infection and parental education. Relationship between daycare attendance and asthma varied with parental education levels. The relationship of frequently playing outside with asthma varied between children living in houses and other dwellings. In conclusion, Inuit children who live mainly in the Northern Canadian Territories had the lowest prevalence of asthma and risk factors of asthma for young Aboriginal children living off-reserve were similar to those reported for non-Aboriginal Canadian children.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".