Workplace second-hand smoke exposure and its association with respiratory symptoms: Findings from cross-sectional surveys 2015–2020
Bibliographic record
Abstract
OBJECTIVES: We investigated the prevalence and associated factors of exposure to secondhand smoke (SHS) at workplaces from 2015 to 2020, 8+ years after the expansion of smoke-free areas, including all indoor workplaces in Hong Kong since 2007, and its association with respiratory symptoms in Chinese adults. STUDY DESIGN: Population-based survey. METHODS: 13,048 working respondents (aged 15+ years) from 6 waves of population-based random-digit telephone surveys (2015-2020) were included. Information on sociodemographic factors, smoking status, and SHS exposure at workplaces were collected. 4585 respondents were randomly selected to report their recent respiratory symptoms. Log-binomial regressions assessed factors associated with SHS exposure at workplaces and the association between SHS and respiratory symptoms, adjusting for sociodemographic factors. RESULTS: 24.8 % of respondents reported SHS exposure at workplaces in the 7 days preceding the survey. Male, older age, lower education level, work outdoors, work both outdoors and indoors, work in vehicles, work as service and sales workers, and work as manual laborers were associated with SHS exposure at workplaces (all P < 0.05). SHS exposure at workplaces was associated with respiratory symptoms in never smokers (Adjusted prevalence ratio (APR) 1.34, 95 %CI 1.00 to 1.81) and ex-smokers (APR 1.34, 95 %CI 1.02 to 1.77), with dose-response relationships. CONCLUSION: Eight to thirteen years after banning smoking at all indoor workplaces, SHS exposure at workplaces was prevalent in outdoor occupations. Exposure to SHS at workplaces was associated with self-reported respiratory symptoms in never and ex-smokers. Policymakers should consider continuously expanding smoke-free areas to more outdoor public places.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".