O5‐3: Traffic‐related air pollution and respiratory health: A cross‐sectional study among adolescents in Vietnam
Bibliographic record
Abstract
Traffic exposes children to the detrimental effects of air pollutants on respiratory health. This study determined the frequency of respiratory symptoms and its related factors among adolescents in Vietnam. Methods: This study had a cross-sectional design conducted in a total of 15,112 children aged 13 -14 years in Ho Chi Minh City, Vietnam. A questionnaire was used to inquire about socio-economic characteristics, traffic-related air polluted (TRAP) exposure, and respiratory symptoms of children. The relationship between our variables of interest and respiratory symptoms was determined by logistic regression analysis. Results: The results of the study show that the median time of TRAP exposure among of adolescents was 52 minutes per day (IQR 32-80). 78% of adolescents had a symptom of blocked nose, 68% had a symptom of runny nose and 55% had a dry cough during the last month. Also, over 80% of adolescents had experienced at least three respiratory symptoms, and 8.5% of those had asthma. There is a positive linear correlation between the time of TRAP exposure and the numbers of respiratory symptoms children had (p<0,001, r=0.05). The time of TRAP exposure of adolescents was not associated with a condition of asthma (OR = 1, 95% CI: 0.99 - 1.00). Conclusion: The respiratory symptoms observed among adolescents are associated with their exposure time to air pollutants from traffic.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".