Factors associated with quit attempts and smoking cessation in Brazil: findings from the International Tobacco Control Brazil Survey
Bibliographic record
Abstract
Background In Brazil, the treatment of tobacco dependence is available at no cost. This study aimed to identify factors associated with attempting to quit and of successful smoking cessation in a population-based sample of Brazilian smokers. Methods Data came from the first two waves of the International Tobacco Control (ITC) Brazil Survey, conducted in 2009 and 2012/2013 in three cities: Rio de Janeiro, São Paulo, and Porto Alegre. Prospective cohort data were collected from 488 adults (≥18 years) who smoked at Wave 1 who were resurveyed at Wave 2. Crude and adjusted relative risks (RR) for two outcomes (making a quit attempt between Wave 1 and Wave 2 and successfully quitting by Wave 2) were estimated. Multivariable multilevel logistic regression models were used, whereby variables were added to the models in a series of blocks. Results Nearly two-thirds (65.6%) of smokers attempted to quit between waves, and 23.4% had quit at Wave 2. Intention to quit smoking at Wave 1 was the only variable associated with attempt to quit by Wave 2 (OR=2.85; 95%CI 1.64-4.94; p< 0.001). Smokers of higher socioeconomic status (OR high versus low =1.80; 95%CI 1.05-3.10; p=0.03) and lower nicotine dependence (OR low HSI versus high HSI =1.94; 95%CI 1.10-3.43; p=0.02) were more likely to successfully quit. The presence of another adult smoker at home was negatively related to successful quitting (OR=0.50; 95%CI 0.26-0.94; p= 0.03). Conclusions These results are generally consistent with prior research and have potential to inform governmental interventions to promote tobacco cessation, particularly among disadvantaged groups.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".