Maternal Diabetes during Pregnancy and Early Childhood Obesity—A Population-Level Analysis
Bibliographic record
Abstract
We examined the association between maternal diabetes status (preexisting diabetes mellitus (pre-DM), gestational diabetes mellitus (GDM), and no DM) during pregnancy and overweight or obesity status of the offspring in early childhood (4-6 years). Immunization records, containing height and weight at the time of preschool vaccination for children born between Jan 2005-Aug 2013 in Alberta, Canada were linked with the following: 1) maternal hospitalization and outpatient records prior to delivery; and 2) registry data containing birth weight, parity, and gestational age. World Health Organization (WHO) criteria were used to categorize children as overweight or obese. Our cohort had 91,382 live births from 68,457 mothers. Rates of pre-DM, GDM and no-DM were 0.8%, 6.2%, and 93.0%, respectively (Table). Childhood overweight/obesity rates were significantly higher among women with pre-DM or GDM, than with no-DM. After adjustment, both GDM and pre-DM were associated with a higher likelihood of having an overweight/obese child. Breast feeding data were available for 63,374 children. A higher proportion of GDM and pre-DM babies were not breast fed, which was also associated with a higher risk of childhood obesity. The impact of maternal diabetes on offspring weight continues beyond birth to early childhood. This association may be further exacerbated by breast feeding challenges in women with diabetes. Disclosure S.L. Bowker: None. A. Savu: None. R.O. Yeung: Consultant; Self; Sanofi. Research Support; Self; AstraZeneca. Consultant; Self; Novo Nordisk Inc.. E.A. Ryan: None. P. Kaul: None.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".