Impact of maternal pre‐pregnancy overweight on infant overweight at 1 year of age: associations and sex‐specific differences
Bibliographic record
Abstract
BACKGROUND: Maternal overweight or obesity (OWOB) is linked to gestational diabetes, fetal macrosomia and higher rates of caesarean delivery. OBJECTIVES: The study aims to assess whether maternal pre-pregnancy OWOB is associated with infant overweight in a sex-dependent manner, independent of microbiota-altering variables. METHODS: Weight and length measurements of 955 mother-infant pairs were obtained from the Canadian Healthy Infant Longitudinal Development cohort. Maternal pre-pregnancy weight was defined as follows: normal, overweight (25 ≤ body mass index < 30) and obese (body mass index ≥ 30). Age and sex-adjusted weight-for-length z-scores >97th percentile were classified as infant overweight at age 1 year. Associations between pre-pregnancy and infant overweight were determined by linear and logistic regression, adjusting for covariates. RESULTS: Maternal pre-pregnancy OWOB were associated with infant weight-for-length and overweight risk at 1 year. Except for pre-pregnancy obesity, these associations were not attenuated appreciably after adjustment for birth mode, exclusivity of breastfeeding, exposure to antibiotics and infant sex. Yet only boys born to mothers with obesity were three times more likely to become overweight at age 1 independent of microbiota-altering variables. Pre-pregnancy obesity was associated with weight-for-length in male and female infants. CONCLUSIONS: Maternal pre-pregnancy OWOB increases the risk of infant overweight, and this association is more evident in male infants.
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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 | 0.000 | 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) | 0.002 | 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".