Alcohol Consumption and Major Depression: Findings from a Follow-up Study
Bibliographic record
Abstract
OBJECTIVE: To investigate whether alcohol consumption predicts major depressive disorder episodes (MDEs) in the general population. METHOD: The respondents without depression (n = 12,290) in the longitudinal cohort of the Canadian National Population Health Survey (NPHS) were classified into cohorts based on any drinking, frequency of drinking, maximum number of drinks on a maximal drinking occasion, and average daily alcohol consumption, based on data collected in the 1994-1995 survey. Major depression frequency 2 years later, in 1996-1997, was evaluated and compared across drinking categories. RESULTS: The respondents who reported any drinking, drinking daily, having more than 5 drinks on a maximal drinking occasion, and having more than 1 drink daily on average, did not have an elevated risk of major depression. A trend in the data suggested that women who reported having more than 5 drinks on a maximal drinking occasion might be at a higher risk of major depression. No evidence of confounding or effect modification by demographic, psychological, and clinical variables was found. CONCLUSION: In a general population sample, alcohol consumption levels were not associated with major depression. Having more than 5 drinks on a maximal drinking occasion, however, may be associated with an increased risk of major depression among women. Extreme patterns of alcohol consumption, which tend to characterize clinical samples, are associated with depression. These patterns of drinking, however, are relatively uncommon in the general population, and the current analysis may have lacked power to detect these associations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".