Lifecourse SEP and tobacco and cannabis use
Bibliographic record
Abstract
BACKGROUND: Social inequalities in substance use have been well-documented; however, the impact of changes in socio-economic position from childhood to adulthood is unclear. We examined the relationship between intergenerational trajectories of social position and tobacco and cannabis use among young adults. METHODS: Data come from 1103 participants (mean age: 28.9 years) of the Trajectoires Epidémiologiques en Population (TEMPO) study and their parents, participants of the GAZEL study, France. Multinomial regression analyses were used to examine associations between lifecourse socio-economic position (SEP) assessed using the parent's reports of family income (1989 and 2002) and the participant's educational attainment, occupational grade and job stability in 2009, with self-reported tobacco and cannabis use in 2009. RESULTS: Compared with participants with stable intermediate/high SEP, those with stable low SEP and those with declining SEP were more likely to use tobacco (age- and sex-adjusted ORs = 2.03 and 2.26). Participants who experienced declining SEP were also disproportionately likely to use and abuse cannabis (adjusted ORs = 2.22 and 2.73). Associations remained significant after adjusting for family (parental smoking, alcohol use, ill health, unemployment, depression and divorce) and individual (early tobacco and cannabis use, academic difficulties, juvenile internalizing and externalizing problems) risk factors. CONCLUSIONS: Cross-sectional studies indicate social inequalities in substance use. Our longitudinal findings suggest that individuals who experienced declining SEP from childhood to adulthood may be twice as likely to use tobacco and cannabis compared with individuals with a stable/high trajectory. Interventions targeting substance abuse should take into account lifecourse determinants including the interplay between individuals' socio-economic origins and later attainment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".