Obstructive Sleep Apnea Risk and Mental Health Conditions Among Older Canadian Adults in the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
Importance: Despite plausible mechanisms linking obstructive sleep apnea (OSA) and mental health conditions, prospective studies from representative samples are needed to estimate temporal associations between OSA and mental health conditions during aging. Objective: To evaluate whether high risk of OSA is associated with increased odds of concurrent and future mental health conditions among middle-aged and older adults. Design, Setting, and Participants: This cohort study is a secondary analysis of the Canadian Longitudinal Study on Aging (CLSA) and used data from respondents of the CLSA Baseline Comprehensive Cohort (2011-2015) and Follow-up 1 (2015-2018) who were aged 45 to 85 years at baseline. Statistical analysis was performed October 2024. The CLSA is a national community-based prospective cohort study collecting data on the biological, medical, cognitive, psychological, social, lifestyle, and economic aspects of aging. Exposure: Individuals with a score greater or equal to 2 on the STOP (snoring, daytime somnolence, witnessed apnea during sleep, or hypertension) questionnaire were considered at high risk of OSA. Main Outcome and Measures: A composite poor mental health outcome was computed as a binary variable, defined by the presence of any of the following: (1) Center for Epidemiologic Studies Short Depression Scale score of 10 or more, (2) Kessler Psychological Distress Scale score of 20 or more, (3) self-reported physician-diagnosed mental health condition, or (4) self-reported antidepressant use. Multivariate conventional and mixed logistic regressions were used to examine associations. Results: The study included 30 097 individuals at baseline (median age, 62 years [IQR, 54-71 years]; 50.9% women) and 27 765 individuals at follow-up (median age, 65 years [IQR, 57-73 years]; 50.9% women), with a median follow-up of 2.9 years (IQR, 2.8-3.1 years). A total of 7066 of 30 097 individuals (23.5%) at baseline and 7493 of 27 765 individuals (27.0%) at follow-up were at high risk of OSA. The composite mental health outcome was identified in 10 334 of 30 097 individuals (34.3%) at baseline and 8851 of 27 765 individuals (31.9%) at follow-up. In adjusted models, high risk of OSA was associated with an approximately 40% higher odds of the composite outcome concurrently at baseline (odds ratio [OR], 1.39; 95% CI, 1.28-1.50) and at follow-up (OR, 1.40; 95% CI, 1.30-1.50). In a repeated-measures analysis, OSA risk remained associated with a 44% higher odds (OR, 1.44; 95% CI, 1.34-1.53) of the composite outcome. Conclusions and Relevance: In this national longitudinal cohort study, middle-aged and older adults at high risk of OSA had consistently worse mental health outcomes. These findings bridge knowledge gaps on the association between OSA and mental health, highlighting the need for integrated screening and intervention strategies.
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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 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".