Exposure to Secondhand Smoke Among Students Aged 13-15 Years—Worldwide, 2000-2007
Bibliographic record
Abstract
Breathing secondhand smoke (SHS) causes heart disease and lung cancer in adults and increased risks for sudden infant death syndrome, acute respiratory infections, middle-ear disease, worsened asthma, respiratory symptoms, and slowed lung growth in children. No risk-free level of exposure to SHS exists. The Global Youth Tobacco Survey (GYTS), initiated in 1999 by the World Health Organization (WHO), the Canadian Public Health Association, and CDC includes questions related to tobacco use, including exposure to SHS. This report examines data collected from 137 jurisdictions (i.e., countries and territories) during 2000-2007, presents estimates of exposure to SHS at home and in places other than the home among students aged 13-15 years who had never smoked, and examines the association between exposure to SHS and susceptibility to initiating smoking. GYTS data indicated that nearly half of never smokers were exposed to SHS at home (46.8%), and a similar percentage were exposed in places other than the home (47.8%). Never smokers exposed to SHS at home were 1.4-2.1 times more likely to be susceptible to initiating smoking than those not exposed. Students exposed to SHS in places other than the home were 1.3-1.8 times more likely to be susceptible to initiating smoking than those not exposed. As part of their comprehensive tobacco-control programs, countries should take measures to create smoke-free environments in all indoor public places and workplaces.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".