Sleep Apnea and Type 2 Diabetes in Two Saskatchewan First Nations Communities
Bibliographic record
Abstract
Title: Sleep Apnea and Type 2 Diabetes in Two Saskatchewan First Nations Communities\nBackground: There has been a sharp increase in type 2 diabetes mellitus (T2DM) in Saskatchewan. Recent research shows that obstructive sleep apnea (OSA) and diabetes are interlinked. Information regarding risk factors associated with T2DM among the First Nations communities is scarce.\nPurpose: The objective was to estimate the current prevalence of T2DM and determine the associations between OSA, established risk factors, and T2DM in two Saskatchewan First Nations communities.\nMethods: This cross-sectional study is based on the First Nations Sleep Health Project baseline survey data, including 588 participants aged ≥ 18 years in two Saskatchewan First Nations communities. The primary outcome of interest for analysis was T2DM. Independent variables included questions on established risk factors for diabetes, the STOP-BANG questionnaire as a measure of OSA as the primary predictor of T2DM, and other sleep-related variables. Statistical analysis was conducted using SPSS 28.\nResults: The majority of the participants were female (55.8%), the mean (±SD) age was 40.03 (±15.3) years, and 18.9% reported having T2DM. Multivariable logistic regression results indicated that those having an intermediate risk of OSA (OR=2.26 (1.22-4.18)) and a high risk of OSA (OR=3.70 (1.67-8.18)) compared to low risk were associated significantly with a higher prevalence of T2DM. In addition, the age group 35-50 years (OR=3.56 (1.67-7.59)) and >50 years (OR=3.40 (1.51-7.66)) compared to <35 years, and regular prescription medication use (OR=3.83 (2.02-6.7.29)) for any health condition compared to non-use, increased the risk of T2DM.\nConclusion: In two First Nations communities in Saskatchewan, Canada, a significant association was observed between OSA and T2DM. This result suggests the need for intervention by screening for OSA routinely to combat the diabetes burden in these communities. The study recommends further studies to establish the causal relationship between OSA and T2DM.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".