Sex-specific prevalence and correlates of possible undiagnosed obstructive sleep apnea in rural Canada
Bibliographic record
Abstract
Abstract Background Obstructive Sleep Apnea (OSA) has been under-investigated in rural communities, particularly through a sex/gender lens. The purpose of this study was to examine the prevalence and correlates of OSA risk among rural-dwelling women and men in Saskatchewan, Canada. Methods Participants for this cross-sectional study were 2340 women and 2030 men living in rural Saskatchewan, Canada and were without a prior diagnosis of OSA. The dependent variable, OSA risk, was estimated from self-reported symptoms of OSA and percentage body fat. Independent variables included socio-demographic characteristics, health behaviors, comorbidities, and quality of life indicators. Multivariable logistic regression was the primary statistical technique employed, conducted separately for women and men. Results A greater proportion of men (30.1%) than women (19.4%) were at high risk of OSA. While many of the correlates of OSA risk were similar for women and men, sex differences emerged for marital status, educational attainment, financial strain, depression, asthma, and perceptions of community support. Conclusion A sizable minority of rural women and men may have possible undiagnosed OSA, which in turn, is associated with substantial comorbidity and reduced quality of life. Additional research with enhanced measurement and a longitudinal design is required to test the veracity of these findings and further clarify the role of sex/gender in relation to OSA risk in rural adults.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".