Prevalence of Gestational Diabetes Mellitus and Its Risk Factors in Chinese Pregnant Women: A Prospective Population-Based Study in Tianjin, China
Bibliographic record
Abstract
OBJECTIVE: We compared the increases in the prevalence of gestational diabetes mellitus (GDM) based on the 1999 World Health Organization (WHO) criteria and its risk factors in Tianjin, China, over a 12-year period. We also examined the changes in the prevalence using the criteria of International Association of Diabetes and Pregnancy Study Group (IADPSG). METHODS: In 2010-2012, 18589 women who registered within 12 weeks of gestation underwent a glucose challenge test (GCT) at 24-28 gestational weeks. Amongst them, 2953 women with 1-hour plasma glucose ≥ 7.8 mmol/L underwent a 75-gram 2-hour oral glucose tolerance test (OGTT) and 781 women had a positive GCT but absented from the standard OGTT. An adjusted prevalence of GDM was calculated for the whole cohort of women by including an estimate of the proportion of women with positive GCTs who did not have OGTTs but would have been expected to have GDM. Logistic regression was used to obtain odds ratios and 95% confidence intervals using the IADPSG criteria. The prevalence of GDM risk factors was compared to the 1999 survey. RESULTS: The adjusted prevalence of GDM by the 1999 WHO criteria was 8.1%, a 3.5-fold increase as in 1999. Using the IADPSG criteria increased the adjusted prevalence further to 9.3%. Advanced age, higher pre-pregnancy body mass index, Han-nationality, higher systolic blood pressure (BP), a family history of diabetes, weight gain during pregnancy and habitual smoking were risk factors for GDM. Compared to the 1999 survey, the prevalence of overweight plus obesity had increased by 1.8 folds, age ≥ 30 years by 2.3 folds, systolic BP by 2.3 mmHg over the 12-year period. CONCLUSIONS: Increasing prevalence of overweight/obesity and older age at pregnancy were accompanied by increasing prevalence of GDM, further increased by change in diagnostic criteria.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".