Maternal pre-pregnancy obesity and offspring hyperactivity-inattention symptoms at 5 years in preterm and term children: a multi-cohort analysis
Bibliographic record
Abstract
Abstract The objective of this study was to determine the relationship between maternal pre-pregnancy body mass index (BMI) and child hyperactivity-inattention symptoms (HIS) at 5 years, including preterm and term-born children, and to determine whether this association varied with gestational age. Maternal pre-pregnancy BMI and offspring HIS were assessed in 10,898 participants born ≥ 33 weeks of gestation from the ELFE cohort and 2646 children born between 23 and 34 weeks from the EPIPAGE 2 cohort. Reported pre-pregnancy weight (kg) and measured height (m) were collected from mothers at inclusion and used to classify BMI (kg/m2). Child HIS were evaluated using the Strengths and Difficulties Questionnaire around 5 years of age. Logistic regression estimated odds ratios (OR) of a high HIS score (≥ 90th percentile) in the ELFE cohort and generalized estimated equations were used in EPIPAGE 2 to account for non-independence of multiple births. As a negative control, paternal BMI was also considered as an exposure of interest in sensitivity analyses. Maternal pre-pregnancy obesity and overweight were associated with child HIS at 5 years in ELFE (adjusted OR [aOR] for obesity 1.27 [1.06, 1.53]; overweight aOR 1.16 [1.00, 1.36]) and pre-pregnancy obesity was associated with high HIS scores in preterm infants of EPIPAGE 2 (aOR 1.48 [1.06, 2.08]). In ELFE, the magnitude of the association increased with decreasing gestational age (interaction p = 0.02). High maternal pre-pregnancy BMI is associated with greater likelihood of high HIS scores in both at-term and preterm children at 5 years of age.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".