Home Environmental Factors Associated With Poor Asthma Control in Montreal Children: A Population-Based Study
Bibliographic record
Abstract
BACKGROUND: Home environmental exposures may aggravate asthma. Few population-based studies have investigated the relationship between asthma control in children and home environmental exposures. OBJECTIVE: Identify home environmental exposures associated with poor control of asthma among asthmatic children less than 12 years of age in Montreal (Quebec, Canada). METHODS: This cross-sectional population-based study used data from a respiratory health survey of Montreal children aged 6 months to 12 years conducted in 2006 (n = 7980). Asthma control was assessed (n = 980) using an adaptation of the Canadian asthma consensus report clinical parameters. Using log-binomial regression models, prevalence ratios (PRs) with 95% confidence intervals (95% CIs) were estimated to explore the relationship between inadequate control of asthma and environmental home exposures, including allergens, irritants, mold, and dampness indicators. Subjects with acceptable asthma control were compared with those with inadequate disease control. RESULTS: Of 980 children with active asthma in the year prior to the survey, 36% met at least one of the five criteria as to poor control of their disease. The population's characteristics found to be related with a lack of asthma control were younger age, history of parental atopy, low maternal education level, foreign-born mothers, and tenant occupancy. After adjustments, children living along high-traffic density streets (PR, 1.35; 95% CI, 1.00-1.81) and those with their bedroom or residence at the basement level (PR, 1.30; 95% CI, 1.01-1.66) were found to be at increased risk of poor asthma control. CONCLUSIONS: Suboptimal asthma control appears to be mostly associated with traffic, along with mold and moisture conditions, the latter being a more frequent exposure and therefore having a greater public health impact.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".