Depressive symptoms and sleep problems as risk factors for heart disease: a prospective community study
Bibliographic record
Abstract
AIMS: The goals of the present study were to examine the associations between depressive symptoms, sleep problems and the risk of developing heart disease in a Canadian community sample. METHODS: Baseline data were from the CARTaGENE study, a community health survey of adults aged 40-69 years in Quebec, Canada. Incidence of heart disease was examined in N = 33 455 participants by linking survey data with administrative health insurance data. Incident heart disease was identified using the World Health Organization's International Classification of Diseases, 9th or 10th edition (ICD-9 and ICD-10) diagnostic codes for heart disease. Sleep problems were assessed with diagnostic codes for sleep disorders within the 2 years preceding the baseline assessment. Average sleep duration was assessed by self-report. Depressive symptoms were assessed with the nine-item Patient Health Questionnaire. RESULTS: In total, 2448 (7.3%) participants developed heart disease over an average follow-up period of 4.6 years. Compared to those without depressive symptoms and with no sleep disorders, those with elevated depressive symptoms and a sleep disorder (HR = 2.60, 95% CI 1.83-3.69), those with depressive symptoms alone (HR = 1.40, 95% CI 1.25-1.57) and those with sleep disorders alone (HR = 1.33, 95% CI 1.03-1.73) were more likely to develop heart disease. Test of additive interaction suggested a synergistic interaction between depressive symptoms and sleep disorders (synergy index = 2.17 [95% CI 1.01-4.64]). When sleep duration was considered, those with long sleep duration and elevated depressive symptoms were more likely to develop heart disease than those with long sleep alone (HR = 1.77, 95% CI 1.37-2.28; and HR = 1.16, 95% CI 0.99-1.36, respectively). CONCLUSIONS: Depression and diagnosed sleep disorders or long sleep duration are independent risk factors for heart disease and are associated with a stronger risk of heart disease when occurring together.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".