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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".