Sleep duration and quality, and risk of gestational diabetes mellitus in pregnant Chinese women
Bibliographic record
Abstract
AIMS: To examine the association between sleep disturbances during pregnancy and risk of gestational diabetes mellitus. METHODS: From 2010 to 2012, 12 506 women in Tianjin, China, were screened using a 50-g 1-h glucose challenge test at 24-28 weeks' gestation. Those with glucose challenge test values of ≥ 7.8 mmol/l were invited to further undergo a 75-g 2-h oral glucose tolerance test. Gestational diabetes was determined according to the International Association of Diabetes and Pregnancy Study Group's definition. Self-reported sleep duration and sleep quality during pregnancy was documented using a modified questionnaire. Logistic regression was used to obtain odds ratios and 95% CIs. RESULTS: A total of 919 women (7.3%) had gestational diabetes. Sleep duration was found to have an approximate J-shaped association with gestational diabetes risk after adjusting for covariates. Compared with a sleep duration of 7-9 h/day (43% of 12 506 women), the adjusted odds ratios for sleep duration of ≥ 9 h/day (55%) and < 7 h/day (2%) for gestational diabetes were 1.21 (95% CI 1.03-1.42) and 1.36 (95% CI 0.87-2.14), respectively. Compared with good sleep quality (37.9% of 12 506 women), the adjusted odds ratios of moderate (59.9%) and poor sleep quality (2.2%) for gestational diabetes were 1.19 (95% CI 1.01-1.41) and 1.61 (95% CI 1.04-2.50), respectively. CONCLUSION: In pregnant Chinese women, poor sleep quality, and shorter and longer duration of sleep during pregnancy were independently associated with an increased risk of gestational diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".