Factors associated with sleep duration across life stages: results from the Canadian Health Measures Survey
Bibliographic record
Abstract
INTRODUCTION: Sleep is essential for both physical and mental well-being. This study investigated sociodemographic, lifestyle/behavioural, environmental, psychosocial and health factors associated with sleep duration among Canadians at different life stages. METHODS: We analyzed nationally representative data from 12 174 Canadians aged 3-79 years in the Canadian Health Measures Survey (2009-2013). Respondents were grouped into five life stages by age in years: preschoolers (3-4), children (5-13), youth (14-17), adults (18-64) and older adults (65-79). Sleep duration was classified into three categories (recommended, short and long) according to established guidelines. Logistic regression models were used to identify life stage-specific correlates of short and long sleep. RESULTS: The proportion of Canadians getting the recommended amount of sleep decreased with age, from 81% of preschoolers to 53% of older adults. Statistically significant factors associated with short sleep included being non-White and having low household income among preschoolers; being non-White and living in a lone-parent household among children; and second-hand smoke exposure among youth. Boys with a learning disability or an attention-deficit/hyperactivity disorder and sedentary male youth had significantly higher odds of short sleep. Among adults and older adults, both chronic stress and arthritis were associated with short sleep. Conversely, mood disorder and poor/fair self-perceived general health in adults and weak sense of community belonging in adults and older men were associated with long sleep. CONCLUSION: Our population-based study identified a wide range of factors associated with short and long sleep at different life stages. This may have implications for interventions aimed at promoting healthy sleep duration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 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".