Associations of Coffee, Diet Drinks, and Non-Nutritive Sweetener Use with Depression among Populations in Eastern Canada
Bibliographic record
Abstract
Consumption of coffee and diet drinks and the use of non-nutritive sweeteners is commonplace worldwide. We conducted a cross-sectional analysis to investigate the associations between coffee consumption and non-nutritive sweetener use and depression among populations in Atlantic Canada. During 2009 to 2013, we recruited 18838 participants aged 35-69 years (5854 men and 12984 women) for the baseline survey of the Atlantic Partnership for Tomorrow's Health cohort study. Coffee consumption, sweetener use, and major depression were assessed using a set of standardized questionnaires. We utilized multiple logistic regression models to assess the associations of coffee drinking and non-nutritive sweetener use with major depression. Compared with non-coffee drinkers, female participants who drank coffee ≥4 cups/day had an odds ratio of 1.38 (95% confidence interval, 1.15-1.64) for major depression with adjustment for sociodemographic and behavioral factors, chronic disease status, and body mass index. We found a significant association between depression and consumption of sweeteners and diet drinks, which was more apparent among women than men. We conclude that heavy coffee drinking and non-nutritive sweetener use were associated with depression among populations in Atlantic Canada. Further studies are warranted to investigate the underlying biological mechanisms.
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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 | 0.001 |
| 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".