Risk of gestational diabetes mellitus: which lifestyle parameters should be changed?
Bibliographic record
Abstract
Background. Gestational diabetes mellitus (GDM) is a common complication of pregnancy. It can cause significant problems for the mother and offspring, such as caesarean delivery, birth trauma and the development of type 2 diabetes mellitus (T2DM) in the future. The identification and correction of modifiable risk factors for GDM will provide a possibility to prevent these complications. Aim. This study aimed to identify the most significant lifestyle parameters affecting the risk of developing GDM. Methods. The study included 680 pregnant women who underwent oral glucose tolerance test at 2432 weeks of pregnancy and responded to a questionnaire comprising the following sections stratified in a semi-quantitative manner: the consumption of major food groups and drinks and the amount of physical activity and smoking before and during pregnancy. A logistic regression analysis was performed to identify lifestyle parameters that influence GDM development. GDM was diagnosed according to the IADPSG criteria. Results. GDM was diagnosed in 266 women; the other 414 women formed the control group. The most significant dietary risk factor for developing GDM was the consumption of sausage(s), dried fruits and fresh fruits. Eating sausage(s) more than thrice a week during pregnancy increased the risk of developing GDM by 2.4 times [95% confidence interval (CI), 1.53.8; p 0.001] and so did the consumption of dried fruits more than thrice a week during pregnancy [odds ratio (OR), 6.5; 95% CI, 2.516.8; p 0.001)] compared with the risk of GDM by less consumption of these food groups. A regular consumption of fresh fruits more than 12 times a week during pregnancy reduced the risk of GDM (OR, 0.5; 95% CI, 0.30.8; p = 0.015). The habit of climbing at least four floors per day during pregnancy also reduced the risk of GDM (OR, 0.7; 95% CI, 0.51.0; p = 0.069). Conclusions. The recommendations for GDM prevention should include limiting the consumption of sausage(s) and dried fruits, increasing the consumption of fresh fruits and introducing regular physical activities, such as climbing stairs.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".