Air Quality and Respiratory Health among Adolescents from the United Arab Emirates
Bibliographic record
Abstract
PURPOSE: To examine the role of air quality in relation to chronic bronchitis, emphysema, asthma, wheeze, and dry cough among adolescents from the United Arab Emirates (UAE). METHODS: A survey was administered on 6,363 adolescents from 9 UAE regions. Data consists of demographic, socioeconomic, residential, and behavioural variables, such as location of residence, residing near industry/gas stations/dumpsites/construction sites, residing near overhead power line/plants, exposure to tobacco, residential exposure, ethnicity, concern over air pollution, smoking, and purposely smelling gasoline fumes/glue/correctors/car exhaust/burning black ants. Logistic regression modeling was used to determine significant predictors of respiratory health. RESULTS: Asthma prevalence was 12.3%, followed by chronic bronchitis (1.8%) and emphysema (0.5%). Overall 12.2% reported wheeze and 34.8% reported a dry nocturnal cough in the past year. Multivariate analyses suggest that sex is a significant predictor of asthma and dry cough. Exposure to tobacco and arts/crafts/ceramics/stain is significant predictor of respiratory health. Tobacco smoking and purposely smelling gasoline fumes/glue/correctors/car exhaust/burning black ants are significant predictors of wheeze and dry cough. CONCLUSIONS: This study suggests that exposure to air quality and behavioral factors such as smoking and purposely smelling gasoline fumes, glue, correctors, car exhaust, or burning black ants are significant predictors of respiratory health among UAE adolescents.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".