Sleep behaviours and associated habits and the progression of pre-diabetes to type 2 diabetes mellitus in adults: A systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Certain sleep behaviours increase risk of type 2 diabetes mellitus (T2DM) in the general population, but whether they contribute to the progression from pre-diabetes to T2DM is uncertain. We conducted a systematic review to assess this. Methods Structured searches were performed on bibliographic databases (MEDLINE, EMBASE and CINAHL) from inception to 26/04/2021 for longitudinal studies/trials consisting of adults⩾18 years with pre-diabetes and sleep behaviours (short or long sleep duration (SD), late chronotype, insomnia, obstructive sleep apnoea, daytime napping and/or night-shift employment) that reported on incident T2DM or glycaemic changes. The Newcastle-Ottawa Scale was used for quality assessment. Results Six studies were included. Meta-analysis of three studies ( n = 20,139) demonstrated that short SD was associated with greater risk of progression to T2DM, hazard ratio (HR) 1.59 (95% CI 1.29-1.97), I 2 heterogeneity score 0%, p < 0.0001, but not for long SD, HR 1.50 (0.86–2.62), I 2 heterogeneity 77%, p = 0.15. The systematic review showed insomnia and night-shift duty were associated with higher progression to T2DM. Studies were rated as moderate-to-high quality. Conclusions Progression from pre-diabetes to T2DM increases with short SD, but only limited data exists for insomnia and night-shift duty. Whether manipulating sleep could reduce progression from pre-diabetes to T2DM needs to be examined.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".