Socioeconomic and Psychosocial Exposures across the Life Course and Binge Drinking in Adulthood: Population-based Study
Bibliographic record
Abstract
Despite recognition of the health risks of binge drinking, its life-course precursors have not been widely examined. Data from the Kuopio Ischemic Heart Disease Risk Factor Study (1984-1989) were used to investigate the association between socioeconomic and psychosocial exposures across the life course and binge drinking in a population-based sample of 2,316 middle-aged men. Binge drinking was defined as drinking at least four bottles of beer, one bottle of wine, one bottle of strong wine, or six servings of spirits on a single occasion. A composite indicator of childhood socioeconomic position was based on parental education, occupation, and number of rooms and divided into tertiles. Low childhood socioeconomic position increased the odds of binge drinking (odds ratio = 1.70, 95% confidence interval: 1.26, 2.31) when other early life exposures were adjusted. Additional adjustment of adult socioeconomic and psychosocial factors attenuated the odds of bingeing associated with low childhood socioeconomic position (odds ratio = 1.29, 95% confidence interval: 0.93, 1.79). Adult socioeconomic conditions, marital status, hostility, and organizational membership were independently associated with bingeing. This study shows that both early and later life characteristics including socioeconomic conditions and adult psychosocial factors contribute to adult binge drinking in this population, but the effects of adult characteristics are stronger.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".