Factors associated with smoking in immigrants from non-western to western countries – what role does acculturation play? A systematic review
Bibliographic record
Abstract
INTRODUCTION: We aimed to identify factors associated with smoking among immigrants. In particular, we investigated the relationship between acculturation and smoking, taking into consideration the stage of the 'smoking epidemic' in the countries of origin and host countries of the immigrants. METHODS: We searched PubMed for peer-reviewed quantitative studies. Studies were included if they focused on smoking among adult immigrants (foreign-born) from non-western countries now residing in the USA, Canada, Ireland, Germany, the Netherlands, Norway, the UK, and Australia. Studies were excluded if, among others, a distinction between immigrants and their (native-born) offspring was not made. RESULTS: We retrieved 27 studies published between 1998 and 2013. 21 of the 27 studies focused on acculturation (using bidimensional multi-item scales particularly designed for the immigrant group under study and/or proxy measures such as language proficiency or length of stay in host country) and 16 of those found clear differences between men and women: whereas more acculturated women were more likely to smoke than less acculturated women, the contrary was observed among men. CONCLUSION: Immigrants' countries of origin and host countries have reached different stages of the 'smoking epidemic' where, in addition, smoking among women lags behind that in men. Immigrants might 'move' between the stages as (I) the (non-western) countries of origin tend to be in the early phase, (II) the (western) host countries more in the advanced phase of the epidemic and (III) the arrival in the host countries initiates the acculturation process. This could explain the 'imported' high (men)/low (women) prevalence among less acculturated immigrants. The low (men)/high (women) prevalence among more acculturated immigrants indicates an adaptation towards the social norms of the host countries with ongoing acculturation.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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 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".