Trends in adolescents’ material and occupational social class-based inequalities in health
Bibliographic record
Abstract
Background: Studies have shown increasing trends in adolescent health inequalities but explanations for this evolution are currently lacking. This study aimed to provide a better understanding by examining trends in material and occupational social class-based inequalities in adolescent health and health behaviours over a 12-year period and to assess whether this evolution differs depending on the SES-indicator. Methods: Repeated cross-sectional data from the Health Behaviour in School-aged Children survey (HBSC) collected across 23 countries in 2002, 2006, 2010, and 2014 was used. Multilevel regression analyses were conducted on a sample from 11 to 15-year old adolescents (n = 480386). Trends in material (family affluence scale) and occupational social class-based inequalities were assessed for adolescent health and health behaviours. Findings: Between 2002 to 2014 material inequalities in adolescent health and health behaviours decreased (life satisfaction: 0·81 to 0·68 (scale 0-10), screen time: 0·53 to 0·34 hours/day, fruit: OR 1·89 to 1·72 and soft drinks: OR 1·36 to 1·13 (consumption of at least once daily); p < 0·05). Material inequalities in all other variables remained stable (p > 0·05). Occupational social class-based inequalities increased between 2002 to 2014 in almost all health behaviours (physical activity: 0·16 to 0·24 hours/day, breakfast: 0·31 to 0·51 days/week, vegetable and fruit: OR range 1·23 to 1·74, screen time and use of soft drinks, alcohol and tobacco: OR range 0·99 to 0·43; p < 0·05) but remained stable in health outcomes (p > 0·05). Conclusions: Adolescents from higher occupational social classes systematically performed healthier behaviours over time compared to those from lower occupational social classes, whereas material inequalities in adolescent health and health behaviours remained stable or decreased. Therefore, effective interventions focusing on intangible resources are key in reducing future health inequalities. Key messages: Occupational class-based Inequalities in adolescent health increased for several health behaviours. Actions to reduce health inequalities should not only focus on a redistribution of material factors but also address intangible resources as they became important drivers of health inequalities.
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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 | 0.001 |
| 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 | 0.001 | 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".