The association between family affluence and smoking among 15-year-old adolescents in 33 European countries, Israel and Canada: the role of national wealth
Bibliographic record
Abstract
AimsTo examine the role of national wealth in the association between family affluence and adolescent weekly smoking, early smoking behaviour and weekly smoking among former experimenters. Design and ParticipantsData were used from the Health Behaviour in School-aged Children (HBSC) study conducted in 2005/2006 in 35 countries from Europe and North America that comprises 60490 students aged 15 years. Multi-level logistic regression was conducted using Markov chain Monte Carlo methods (MCMC) to explore whether associations between family affluence and smoking outcomes were dependent upon national wealth. MeasurementFamily Affluence Scale (FAS) as an indicator for the socio-economic position of students. Current weekly smoking behaviour is defined as at least weekly smoking (dichotomous). Early smoking behaviour is measured by smoking more than a first puff before age 13years (dichotomous). Weekly smoking among former experimenters is restricted to those who had tried a first puff in the past. FindingsThe logistic multi-level models indicated an association of family affluence with current weekly smoking [odds ratio (OR)=1.088; 95% credible interval (CrI)=1.055-1.121, P<0.001], early smoking behaviour (OR=1.066; CrI=1.028-1.104, P<0.001) and smoking among former experimenters (OR=1.100; CrI=1.071-1.130; P<0.001). Gross domestic product (GDP) per capita was associated positively and significantly with the relationship between family affluence and current weekly smoking (OR=1.005; CrI=1.003-1.007; P<0.001), early smoking behaviour (OR=1.003; CrI=1.000-1.005; P=0.012) and smoking among former experimenters (OR=1.004; CrI=1.002-1.006; P<0.001). The association of family affluence and smoking outcomes was significantly stronger for girls. ConclusionsThe difference in smoking prevalence between rich and poor is greater in more affluent countries.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".