Nicotine and tobacco-specific nitrosamine exposure among youth in England who smoke cigarettes and/or vape
Bibliographic record
Abstract
SIGNIFICANCE: Compared with adults who smoke cigarettes, adults who vape nicotine are exposed to similar levels of nicotine and significantly lower levels of tobacco-specific nitrosamines (TSNAs). Little research outside the USA has included youth who vape, particularly those using newer disposable vapes. We investigated exposure to nicotine and the TSNA NNK (4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol) among youth in England who vape, smoke, do both (dual) or do neither. METHODS: In 2023, youth aged 16-19 years from England completed a survey and provided a urine sample (n=201). Linear regressions examined associations of creatinine-normalised urinary concentrations of total nicotine equivalents (TNE-2) and NNAL (a metabolite of NNK) with past 7-day smoking/vaping status and self-reported recency of vaping. All analyses were adjusted for age, sex at birth, ethnicity and any past 7-day cannabis use. FINDINGS: Over three-quarters (77%) of those vaping were using the newer disposable vapes. Urinary TNE-2 concentrations among those who exclusively vaped in the past 7 days (n=83, geometric mean (GM)=5.09 nmol/mg creatinine (95% CI 3.19 to 8.12)) did not differ significantly from those who smoked (n=9, GM=1.74 nmol/mg creatinine (95% CI 0.64 to 4.72), p=0.426) or those who dual used (n=55, GM=5.60 nmol/mg creatinine (95% CI 3.32 to 9.43), p=0.953). Levels of NNAL among those who exclusively vaped (GM=1.87 pg/mg creatinine (95% CI 1.62 to 2.17)) were significantly lower than those who smoked (GM=4.87 pg/mg creatinine (95% CI 2.45 to 9.68), p=0.001) or those who dual used (GM=3.67 pg/mg creatinine (95% CI 2.76 to 4.86), p<0.001) and not significantly different from youth who neither vaped nor smoked (GM=1.84 pg/mg creatinine (95% CI 1.52 to 2.24), p=0.887). INTERPRETATION: Youth who vape are exposed to similar levels of nicotine as those who smoke or who dual use. NNAL exposure among youth who vape is much lower than among those who smoke and indistinguishable from youth who do not vape or smoke.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".