Associations of maternal insulin sensitivity during pregnancy with childhood central adiposity in the Genetics of Glucose regulation in Gestation and Growth (Gen3G) cohort
Bibliographic record
Abstract
BACKGROUND: Childhood obesity has been associated with prenatal exposure to maternal hyperglycaemia, but we lack understanding about maternal insulin physiologic components that contribute to this association. OBJECTIVES: Evaluate the association between maternal insulin sensitivity during pregnancy and adiposity measures in childhood. METHODS: In 422 mother-child pairs, we tested associations between maternal insulin sensitivity measures at ~26 weeks of pregnancy and child adiposity measures, including dual-energy X-ray absorptiometry body composition and anthropometry (body mass index and waist circumference) at ~5 years. We used linear regression analyses to adjust for maternal age, ethnicity, gravidity, first-trimester body mass index, and child sex and age at mid-childhood. RESULTS: . Lower maternal insulin sensitivity indices were correlated with greater child adiposity based on anthropometry measures and on dual-energy X-ray absorptiometry total and trunk % fat in univariate associations (r = -0.122 to -0.159). Lower maternal insulin sensitivity was specifically associated with higher dual-energy X-ray absorptiometry trunk % fat (n = 359 for Matsuda; β = -0.034 ± 0.013; p = 0.01) after adjustment for covariates, including maternal body mass index. CONCLUSIONS: Maternal insulin sensitivity during pregnancy may contribute to increased risk for higher offspring central adiposity in middle childhood.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".