Social inequalities in mental disorders and substance misuse in young adults. A birth cohort study in Southern Brazil
Bibliographic record
Abstract
Purpose To investigate the association between mental disorders and substance misuse at 30 years of age with gender, socioeconomic position at birth, and family income trajectories. Methods The 1982 Pelotas Birth Cohort was used; all 5914 children born alive at hospital were originally enrolled (99.2% of all city births). In 2012, 3701 subjects were located and interviewed (68% retention rate). Mental disorders and substance misuse were assessed, and their prevalence analysed according to gender, socioeconomic status at birth, and four different income trajectories: always poor, never poor, poor at birth/non-poor at age 30, and non-poor at birth/poor at age 30. Results While women presented higher prevalence of mental disorders, substance misuse was much more frequent among men. Individuals in the lowest income quintile at birth presented 2–5 times more mental disorders and substance misuse than those in the highest quintile. Young adults who were always poor or were not poor at birth but were poor at 30 years of age had a higher prevalence of mental disorders than the other groups. Conclusions The high rates of mental disorders and lifetime suicide attempts in young adults, especially those who were always poor or became poor after childhood, suggest that recent socioeconomic-related stressful situations may have a higher impact on the current mental health than events earlier in life. However, we could not identify at what specific ages socioeconomic changes were more important.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".