Associations between vaping and self-reported respiratory symptoms in young people in Canada, England and the US
Bibliographic record
Abstract
BACKGROUND: Prevalence of youth nicotine vaping has increased, heightening concerns around negative health effects. This study aimed to compare self-reported respiratory symptoms among youth by vaping behaviours. METHODS: Participants (n = 39,214) aged 16-19 from the 2020 and 2021 International Tobacco Control Policy Evaluation Project (ITC) Youth Tobacco and Vaping Surveys (Canada, England, US). Weighted multivariable logistic regression assessed associations between reporting any of five respiratory symptoms in the past week (shortness of breath, wheezing, chest pain, phlegm, cough) and: past 30-day smoking and/or vaping; lifetime/current vaping. Among past-30-day vapers (n = 4644), we assessed associations between symptoms and vaping frequency, use of nicotine salts, usual flavour and device type(s). RESULTS: Overall, 27.8% reported experiencing any of the five respiratory symptoms. Compared with youth who had only vaped, those who had only smoked had similar odds of symptoms [adjusted odds ratio, OR (95% confidence interval, CI): 0.97 (0.85-1.10)], those who both smoked and vaped had higher odds [1.26 (1.12-1.42)], and those who had done neither, lower odds [0.67 (0.61-0.72)]. Compared with those who had never vaped, past use, experimentation and current regular or occasional use were all associated with higher odds. Reporting usually using nicotine salts was associated with higher odds of symptoms [1.43 (1.22-1.68)] than non-salt but was often uncertain. Compared with tobacco flavour (including with menthol), menthol/mint and sweets flavours were associated with similar odds; fruit [1.44 (1.07-1.93)], multiple [1.76 (1.30-2.39)] and 'other' [2.14 (1.45-3.16)] flavours with higher odds. All device types were associated with similar odds. CONCLUSIONS: Among youth, vaping was associated with increased reporting of past-week respiratory symptoms. Among those who vaped, some flavour types and potentially nicotine salts were associated with respiratory symptoms.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".