1069-P: How Does Exposure to Overnutrition In Utero Lead to Childhood Adiposity? A Longitudinal Study in the Exploring Perinatal Outcomes among Children (EPOCH) Cohort
Bibliographic record
Abstract
We explored the longitudinal sequence of metabolic changes linking overnutrition in utero to development of adiposity among initially normal weight children in the EPOCH cohort. This study includes 312 normal weight youth (body mass index [BMI] z <1 SD per the World Health Organization growth reference) that were exposed (n=144) or unexposed (n=168) to overnutrition in utero (maternal BMI ≥25 kg/m2 or gestational diabetes). Fasting insulin, glucose and adiposity were obtained at research visits during childhood (age 10 y) and adolescence (age 16 y). We examined associations of overnutrition in utero with natural log transformed fasting insulin at baseline, followed by associations of baseline fasting insulin with adiposity (BMI z, subcutaneous [SAT] and visceral fat depots [VAT]), insulin resistance (HOMA-IR), and fasting glucose during follow-up using linear mixed models that accounted for child age, sex, and race/ethnicity; maternal education and prenatal smoking. Baseline BMI z, fasting glucose, HOMA-IR, and adiposity markers (except for slightly higher SAT in exposed youth [+10 mm2]) were not different by exposure status. Overnutrition in utero corresponded with 14% (1%, 29%) higher baseline fasting insulin, even after controlling for child VAT, SAT, or VAT:SAT. Higher baseline fasting insulin was, in turn, associated with greater adiposity (0.41 [0.26, 0.55] SD BMI z; 13.9 [2.4, 25.4] mm2 SAT; 2.0 [0.1, 3.8] mm2 VAT) and HOMA-IR (0.88 [0.69, 1.07]) across follow-up, but not with fasting glucose. These results suggest that overnutrition in utero may result in hyperinsulinemia during childhood and precede accrual of adiposity. However, since our study started at age 10 y, studies in normal weight youth starting earlier, and with repeated assessments of insulin sensitivity, β cell function and glycemia, are needed to clarify the sequence of metabolic changes resulting from early exposures. Disclosure W. Perng: None. M. M. Kelsey: Other Relationship; Self; Boehringer Ingelheim (Canada) Ltd., Daiichi Sankyo, Janssen Pharmaceuticals, Inc., Merck Sharp & Dohme Corp. K. A. Sauder: None. D. Dabelea: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R01DK068001); Colorado Clinical and Translational Sciences Institute (KL2-TR002534 to W.P.)
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".