Sleep Duration, Lifestyle Intervention, and Incidence of Type 2 Diabetes in Impaired Glucose Tolerance
Bibliographic record
Abstract
OBJECTIVE: Both short and long sleep duration have frequently been found to be associated with an increased risk for diabetes. The aim of the present exploratory analysis was to examine the association between sleep duration and type 2 diabetes after lifestyle intervention in overweight individuals with impaired glucose tolerance in a 7-year prospective follow-up. RESEARCH DESIGN AND METHODS: A total of 522 individuals (aged 40-64 years) were randomly allocated either to an intensive diet-exercise counseling group or to a control group. Diabetes incidence during follow-up was calculated according to sleep duration at baseline. Sleep duration was obtained for a 24-h period. Physical activity, dietary intakes, body weight, and immune mediators (C-reactive protein and interleukin-6) were measured. RESULTS: Interaction between sleep duration and treatment group was statistically significant (P = 0.003). In the control group, the adjusted hazard ratios (HRs) (95% CI) for diabetes were 2.29 (1.38-3.80) and 2.74 (1.67-4.50) in the sleep duration groups 9-9.5 h and >or=10 h, respectively, compared with for that of the 7-8.5 h group. In contrast, sleep duration did not influence the incidence of diabetes in the intervention group; for sleep duration groups 9-9.5 h and >or=10 h, the adjusted HRs (95% CI) were 1.10 (0.60-2.01) and 0.73 (0.34-1.56), respectively, compared with that in the reference group (7-8.5 h sleep). Lifestyle intervention resulted in similar improvement in body weight, insulin sensitivity, and immune mediator levels regardless of sleep duration. CONCLUSIONS: Long sleep duration is associated with increased type 2 diabetes risk. Lifestyle intervention with the aim of weight reduction, healthy diet, and increased physical activity may ameliorate some of this excess risk.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".