P2-102 Developmental trajectories of body mass index in childhood: is maternal smoking during pregnancy a critical exposure?
Bibliographic record
Abstract
Introduction Intrauterine life has been identified as a critical period for the development of obesity. Research has consistently shown that prenatal exposure to maternal cigarette smoke (PEMCS) is associated with a number of adverse fetal, obstetrical and developmental outcomes. While PEMCS has emerged as an important risk factor for overweight in offspring, no consensus exists on the pattern or duration of impact. This study seeks to further examine the role of PEMCS on developmental body mass index (BMI) trajectories in children up to 10 years of age. Methods Data on mother–child pairs (n=1291) was obtained from the Quebec Longitudinal Study of Child Development, which includes a range of social and biological information on child development. Developmental BMI trajectories were established empirically, with a group based modelling strategy, using repeated measurements of height of weight up to age 10. This approach (TRAJ) complements both hierarchical and latent growth curve modelling for analysing developmental trajectories. Results Four distinct BMI trajectories were identified: early onset overweight (4.4%), increasing to overweight (2.7%), stable overweight (26.1%) and never overweight (66.8%). PEMCS was associated with increased risk of overweight at age 10 (OR: 3.3, 95% CI 1.96 to 5.57) and with trajectory membership (p<0.003). Conclusions The elevated risk of excess weight among the offspring of smoking mothers supports the paradigm of in utero and early life obesity prevention. Our approach to longitudinal childhood weight analysis, which allows for heterogeneous population trajectories, may help to improve our understanding of the different pathways leading to obesity in adulthood.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".