Who purchases cigarettes from cheaper sources in China? Findings from the ITC China Survey
Bibliographic record
Abstract
OBJECTIVE: The availability of cigarettes from cheaper sources constitutes a major challenge to public health throughout the world, including China, because it may counteract price-based tobacco control policies. The goal of this study was to identify factors associated with purchasing cigarettes from cheaper sources among adult smokers in China. METHODS: Data were analysed from Waves 1 to 3 of the International Tobacco Control China Survey conducted in 2006-2009 among adult smokers in six cities in China (N=7980). One survey question asked, "In the last 6 months, have you purchased cheaper cigarettes than you can get from local stores for economic reasons?" We examined whether sociodemographic factors and smoking intensity were associated with purchasing cigarettes from cheaper sources using the general estimating equations model. Sociodemographic factors considered were gender, age, marital status, monthly household income, education, employment status and city of residence. RESULTS: 15.6% of smokers reported purchasing cigarettes from cheaper sources. After controlling for other covariates, the associations of the behaviour of purchasing cigarettes from cheaper sources with age (adjusted OR (AOR)=1.49, 95% CI 1.17 to 3.92 for age 18-24 compared with age 55+) and with income (AOR=2.93, 95% CI 2.27 to 3.79 for low income compared with high income) were statistically significant, but there was no statistically significant relationship with smoking intensity. CONCLUSIONS: Our findings indicate that young and low-income smokers are more likely than older and high-income smokers to purchase cigarettes from cheaper sources in China. Tobacco control policies that reduce the availability of cigarettes from cheaper sources could have an impact on reducing cigarette consumption among young and low-income smokers in China.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.003 | 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 teacher head, 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".