Smoking in Young Adults: A Study of 4-Year Smoking Behavior Patterns and Residential Presence of Features Facilitating Smoking Using Data From the Interdisciplinary Study of Inequalities in Smoking Cohort
Bibliographic record
Abstract
INTRODUCTION: Young adults have the highest prevalence of smoking among all age groups in most industrialized countries and exhibit great variability in smoking behavior. Differences in associations between features in residential environments and smoking initiation, prevalence, and cessation have been extensively examined in the literature. Nonetheless, in many cases, findings remain inconsistent. This paper proposes that a potential driver of these inconsistencies is an almost exclusive focus on point-specific smoking outcomes, without consideration for the different behavior patterns that this age group may experience over time. AIMS AND METHODS: Based on data from the Interdisciplinary Study of Inequalities in Smoking cohort of 18- to 25-year-old Montreal residents (n = 1025), we examined associations between 4-year smoking patterns measured at three timepoints and proximal presence/density of tobacco retail outlets and presence of smoker accommodation facilities in Montreal, Canada. Associations were tested using two-level multinomial and logistic models. RESULTS: In fully adjusted models, compared to never-smokers, residents of areas with a higher density of tobacco retail were more likely to (1) be characterized as established smokers, (2) have experienced repeated changes in smoking status (being "switchers") during the 4-year study period, and (3) be former smokers. CONCLUSIONS: From a conceptual standpoint, these findings highlight the importance of acknowledging and examining smoking behavior patterns among young adults. Furthermore, specific pattern-feature associations may point to unique mechanisms by which features could influence smoking behavior patterns. These findings require replication and extension, including testing hypotheses regarding tobacco retail density's role in sustaining smoking and in influencing changes in smoking status. IMPLICATIONS: Results from this study highlight the importance of describing and examining different young adult smoking behavior patterns and how they may be influenced by residential environment features such as the density of tobacco retail. Findings suggest that young adults residing in areas with a higher density of tobacco retailers are more likely to have experienced repeated changes in smoking status and to be established smokers. Further research in this area is needed to advance knowledge of the putative mechanisms by which residential features may influence smoking behavior patterns and to ultimately orient policy and interventions seeking to curb smoking at the local level.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".