Pre-pregnancy body mass index, gestational diabetes mellitus, and gestational weight gain: individual and combined effects on fetal growth
Bibliographic record
Abstract
Background Pre-pregnancy body mass index (BMI), gestational diabetes mellitus (GDM), and gestational weight gain (GWG) are interlinked and may play a complex role in fetal growth. We aimed to examine the relationship between pre-pregnancy BMI, GDM, GWG, and fetal growth outcomes and explore the contribution of GDM and GWG to the relationship between Pre-pregnancy obesity/overweight and large-for-gestational-age (LGA) in a prospective cohort. Methods We prospectively recruited women in the first trimester and having one-step GDM screened with a 75-g oral glucose tolerance test between 24 and 28 weeks of gestation ( n = 802). Outcomes included LGA, small-for-gestational-age (SGA), and preterm birth. To assess the individual and cumulative associations between pre-pregnancy BMI, GDM, GWG, and these outcomes, we used multivariate logistic regression analysis. Furthermore, we employed structural equation modeling (SEM) to investigate the mediating role of GDM and excessive GWG in the correlation between pre-pregnancy overweight/obesity and LGA. Results Pre-pregnancy obesity, GDM, and excessive GWG were all independently associated with increased odds of LGA. Inadequate GWG was associated with higher odds of preterm birth. Compared with women unexposed to pre-pregnancy overweight/obesity, GDM, or excessive GWG, women exposed any two conditions had higher odds for LGA (AOR 3.18, 95% CI 1.25–8.11) and women with coexistence of all had the highest odds for LGA (AOR 8.09, 95% CI 2.18–29.97). The mediation analysis showed that GDM explained 18.60% ( p < 0.05) of the total effect of pre-pregnancy overweight/obesity on LGA, and GWG explained 17.44% ( p < 0.05) of the total effect. Conclusion Pre-pregnancy obesity/overweight, GDM, and excessive GWG are associated with higher odds of fetal growth disturbances as individual factors and when they co-exist. The effect of pre-pregnancy overweight/obesity on LGA is partially achieved through GDM and excessive GWG.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".