Factors associated with changing cigarette consumption patterns among low-intensity smokers: Longitudinal findings across four waves (2008–2012) of ITC Mexico Survey
Bibliographic record
Abstract
Light and intermittent smoking has become increasingly prevalent as smokers shift to lower consumption in response to tobacco control policies. We examined changes in cigarette consumption patterns over a four-year period and determined which factors were associated with smoking transitions. We used data from a cohort of smokers from the 2008–2012 ITC Mexico Survey administrations to investigate transitions from non-daily (ND; n = 669), daily light (DL; ≤5 cigarettes per day (cpd); n = 643), and daily heavy (DH; >5 cpd; n = 761) smoking patterns. To identify which factors (i.e., sociodemographic measures, perceived addiction, quit behavior, social norms) were associated with smoking transitions, we stratified on smoking status at time t (ND, DL, DH) and used multinomial (ND, DL) and binomial (DH) logistic regression to examine transitions (quitting/reducing or increasing versus same level for ND and DL, quitting/reducing versus same level for DH). ND smokers were more likely to quit at follow-up than DL or DH smokers. DH smokers who reduced their consumption to ND were more likely to quit eventually compared to those who continued as DH. Smokers who perceived themselves as addicted had lower odds of quitting/reducing smoking consumption at follow-up compared to smokers who did not, regardless of smoking status at the prior survey. Quit attempts and quit intentions were also associated with quitting/reducing consumption. Reducing consumption may eventually lead to cessation, even for heavier smokers. The findings that perceived addiction and quit behavior were important predictors of changing consumption for all groups may offer insights into potential interventions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".