Sex‐specific white matter alterations in children exposed to high pregestational <scp>BMI</scp>
Bibliographic record
Abstract
Abstract Objective This study investigated whether exposure to high pregestational BMI (≥ 25 kg/m 2 ) is associated with alterations in white matter microstructure in early childhood, explored sex‐specific effects, and examined associations with cognitive performance. Methods A total of 90 children from the Alberta Pregnancy Outcomes and Nutrition (APrON) cohort underwent diffusion tensor imaging between ages 2 and 7 years. Data were processed using ExploreDTI to obtain mean fractional anisotropy (FA) and mean diffusivity (MD). Pregestational weight was self‐reported by pregnant individuals, height was measured at enrollment, and child cognitive outcomes were assessed at ages 3 to 4 years using the Wechsler Preschool and Primary Scale of Intelligence. Results Children exposed to high pregestational BMI had lower FA, but not higher MD, in the superior longitudinal fasciculus and in the body and splenium of the corpus callosum compared with unexposed children (BMI 18.5–24.9 kg/m 2 ). This association persisted when analyzing pregestational obesity and overweight categories separately. Altered FA in splenium of the corpus callosum was associated with poorer cognitive outcomes in exposed children. Exposed male children had higher FA in the fornix, whereas female children had lower FA in the body and splenium of the corpus callosum compared with unexposed peers. Conclusions High pregestational BMI was associated with alterations in white matter microstructure during early childhood in a sex‐specific manner. Promoting healthy lifestyles and weight management among individuals of childbearing age is crucial.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".