Gender Differences in Tobacco Smoking: Higher Relative Exposure to Smoke Than Nicotine in Women
Bibliographic record
Abstract
INTRODUCTION: Men and women are thought to regulate their smoking differently and to differ in their susceptibility to nicotine addiction. METHODS AND MATERIALS: Various measures of smoke exposure were compared between 400 current regular tobacco-dependent (DSM-IV) male and female light (1-15 cigarettes per day) and heavy (>15 cigarettes per day) smokers. Between 2 and 8 PM, blood was collected for nicotine and cotinine analysis, and breath carbon monoxide (CO) was measured. Individuals with genetic variants of the CYP2A6 gene were removed from analysis (n = 25). RESULTS: No significant difference was found in the number of cigarettes per day or CO levels between the sexes. However, females had significantly lower nicotine levels than males (16.9 +/- 0.6 vs. 21.1 +/- 0.07, p < 0.01). This is only partly explained by the fact that females smoked lower nicotine-containing cigarettes. Female heavy smokers demonstrated higher -log nicotine/CO values (a representation of cost of smoking) compared with male heavy smokers (0.1 +/- 0.02 vs. 0.02 +/- 0.01 mg/L ppm, p < 0.05). CONCLUSIONS: Thus, gender differences appear to exist in smoking behaviors, nicotine sensitivity, and nicotine requirements. These differences are expected to contribute to gender differences in health risks and cancers associated with smoking.
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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 | 0.000 | 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) | 0.006 | 0.001 |
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".