Sleep Quality and Nocturnal Sleep Duration in Pregnancy and Risk of Gestational Diabetes Mellitus
Bibliographic record
Abstract
Study Objectives: To examine the influence of maternal sleep quality and nocturnal sleep duration on risk of gestational diabetes mellitus (GDM) in a multiethnic Asian population. Methods: A cohort of 686 women (376 Chinese, 186 Malay, and 124 Indian) with a singleton pregnancy attended a clinic visit at 26-28 weeks of gestation as part of the Growing Up in Singapore Towards healthy Outcomes mother-offspring cohort study. Self-reported sleep quality and sleep duration were assessed using the Pittsburgh Sleep Quality Index (PSQI). GDM was diagnosed based on a 75-g oral glucose tolerance test administered after an overnight fast (1999 WHO criteria). Multiple logistic regression was used to model separately the associations of poor sleep quality (PSQI score > 5) and short nocturnal sleep duration (<6 h) with GDM, adjusting for age, ethnicity, maternal education, body mass index, previous history of GDM, and anxiety (State-Trait Anxiety Inventory score). Results: In the cohort 296 women (43.1%) had poor sleep quality and 77 women (11.2%) were categorized as short sleepers; 131 women (19.1%) were diagnosed with GDM. Poor sleep quality and short nocturnal sleep duration were independently associated with increased risk of GDM (poor sleep, adjusted odds ratio [OR] = 1.75, 95% confidence interval [CI] 1.11 to 2.76; short sleep, adjusted OR = 1.96, 95% CI 1.05 to 3.66). Conclusions: During pregnancy, Asian women with poor sleep quality or short nocturnal sleep duration exhibited abnormal glucose regulation. Treating sleep problems and improving sleep behavior in pregnancy could potentially reduce the risk and burden of GDM.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".