Associations between Major Health Behaviors and Sleep Problems: Results from the 2015, 2016, 2017 Canadian Community Health Survey
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Key health behaviors including cigarette smoking, alcohol consumption, fruit and vegetable (FV) consumption, and physical activity have been associated with sleep-related problems. This cross-sectional study describes sleep quality and duration by gender in a large adult population and examines whether health behavioral factors are associated with short/long sleep duration and sleep problems (difficulty initiating/maintaining sleep [DIMS], daytime sleepiness, and finding sleep refreshing). METHODS: Using Canadian Community Health Survey data from cycles 2015, 2016, and 2017, binary and multinomial logistic regression models were computed. RESULTS: Of the 44,911 respondents included, only half of respondents met the recommended sleep duration. Fifty-five percent of females and forty-one percent of males reported DIMS. Binge drinking was associated with increased DIMS, with the strongest relationship being among females reporting weekly binge drinking (odds ratio (OR) 2.03 [1.59,2.60]). Binge drinking was also associated with decreased odds of finding sleep refreshing among females only (OR 0.73 [0.56,0.96] in weekly binge drinkers). Compared to respondents who had never smoked, daily smokers had higher odds of short sleep (OR 1.50 [1.30,1.74] and OR 1.39 [1.21,1.60]; females and males, respectively). Similarly, former smokers had higher odds of DIMS (OR 1.18 [1.06,1.31]) and not finding sleep refreshing (OR 0.85 [0.77,0.95]), among females; similar OR among males. Increased FV consumption was associated with increased odds of finding sleep refreshing (OR 1.05 [1.03,1.07] and OR 1.06 [1.04,1.08] in females and males, respectively). CONCLUSION: There is a high prevalence of sleep problems among Canadians. Potential gender differences in the relationships between health behaviors and sleep problems warrant further research.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".