Do social inequalities in smoking differ by immigration status in young adults?
Bibliographic record
Abstract
Abstract Background Tobacco use accounts for half the difference in life expectancy across groups of low and high socioeconomic status. The objective was to assess whether social inequalities in smoking in Canada-born young adults are also apparent among same-age immigrants, a group often viewed as disadvantaged and vulnerable to multiple health issues. Methods Data were drawn from the Interdisciplinary Study of Inequalities in Smoking, a longitudinal investigation of social inequalities in smoking in Montreal, Canada. The sample included 2,077 young adults age 18-25 (56.6% female; 18.9% immigrants). Immigrants had been in Canada 11.6 (SD 6.4) years on average. The association between level of education and current smoking was examined separately in immigrants and non-immigrants in multivariate logistic regression analyses controlling for covariates. Results Twenty percent of immigrants were current smokers compared to 24% of non-immigrants. In immigrants, relative to those who were university-educated, the adjusted odds ratio (OR) (95% confidence interval) for current smoking was 1.2 (0.6, 2.3) among those with pre-university or vocational training, and 1.5 (0.7, 2.9) among those with high school education only. In non-immigrants, the adjusted ORs were 1.9 (1.4, 2.5) among those with pre-university or vocational training and 4.0 (2.9, 5.5) among those with high school education. Conclusions Despite a mean of over 10 years in Canada, young adults who immigrated to Canada did not manifest the strong social gradient in smoking apparent in non-immigrants. Identification of factors that protect immigrants from manifesting marked social inequalities in smoking could inform the development of smoking preventive intervention sensitive to social inequalities in smoking. Key messages A social gradient in smoking apparent in Canada-born young adults was not observed in same-age immigrants. Factors that protect immigrants against social inequalities in smoking should be identified.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".