Unhealthy Behaviors Among Canadian Men Are Predictors of Comorbidities: Implications for Clinical Practice
Bibliographic record
Abstract
Men's poor health behaviors are an increasingly prevalent issue with long-term consequences. This study broadly samples Canadian men to obtain information regarding health behaviors as a predictor of downstream medical comorbidities. A survey of Canadian men included questions regarding demographics, comorbidities, and health behaviors (smoking and alcohol consumption, sleep and exercise behaviors, and dietary habits). Health behaviors were classified as either healthy or unhealthy based upon previous studies and questionnaire thresholds. Multivariate regression was performed to determine predictors for medical comorbidities. The 2,000 participants were aged 19-94 (median 48, interquartile range 34-60). Approximately half (47.4%) were regular smokers, 38.7% overused alcohol, 53.9% reported unhealthy sleep, 48.9% had low levels of exercise, and 61.8% had unhealthy diets. On multivariate analysis, regular smoking predicted heart disease (OR 2.08, p < .01), elevated cholesterol (OR 1.35, p = .02), type 2 diabetes (OR 1.57, p = .02), osteoarthritis (OR 1.43, p = .04), and depression (OR 1.62, p < .01). Alcohol overuse predicted hypertension (OR 1.40, p < .01) and protected against type 2 diabetes (OR 0.61, p < .01). Unhealthy sleep predicted hypertension (OR 1.46, p < .01), erectile dysfunction (OR 1.50, p = .04), and depression (OR 1.87, p < .01). Low levels of exercise predicted hypertension (OR 1.30, p = .03) and elevated cholesterol (OR 1.27, p = .05). Finally, unhealthy diet predicted depression (OR 1.65, p < .01). This study confirms the association of poor health behaviors and comorbidities common to middle-aged and older men. The results emphasize the potential scope of targeted gender-sensitized public awareness campaigns and interventions to reduce common male disease, morbidity, and mortality.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".