Prevalence of insomnia and use of sleep aids among adults in Canada
Bibliographic record
Abstract
OBJECTIVES: To estimate the prevalence of insomnia and the use of sleep aids among Canadian adults. METHODS: Data were derived from a phone interview conducted (April to October 2023) with a stratified, population-based sample of 4037 adults (57.6 % females; mean age 50.6 ± 18.4; range 18-102 years old) living in Canada. Post-stratified survey weights were included in the analysis to ensure the representativity of the adult Canadian population. RESULTS: The prevalence estimate of insomnia disorder was 16.3 % (95 % CI 15.1-17.6), with higher rates in females (risk ratio [RR] 1.24, 95 % CI 1.06-1.45), Indigenous peoples (RR 1.77, 95 % CI 1.27-2.47), and individuals with poorer mental or physical health. Overall, 14.7 % of respondents reported having used prescribed sleep medications in the previous 12 months, 28.7 % used natural products or over-the-counter (OTC) sleep aids, 15.6 % used cannabis-derived products and 9.7 % used alcohol for sleep in the last 12 months. Higher proportions of females used prescribed medication (RR 1.79, 95 % CI 1.31-2.43) and natural products or OTC medication (RR 1.41, 95 % CI 1.16-1.71), while more males used cannabis (RR 1.33, 95 % CI 1.03-1.72) and alcohol (RR 1.67, 95 % CI 1.16-2.33) for sleep. Higher proportions of older adults (≥65 years) were taking prescribed medications, while more young adults (18-35 years) used natural products or OTC medications, cannabis, and alcohol as sleep aids. CONCLUSIONS: Insomnia is a highly prevalent condition in Canada and there is widespread and increasing use of various medications and substances to cope with this health issue. These findings highlight the need for public health interventions to promote healthy sleep and for wider dissemination of evidence-based treatments for insomnia, such as cognitive behavioral therapy which is the first-line treatment for insomnia in practice guidelines, to reduce sleep health disparities.
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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) | 0.001 | 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".