Child Growth Trajectories From Birth To Three Years: The Impact Of Prenatal Physical Activity
Bibliographic record
Abstract
Pregnant individuals who are physically activity are 37% less likely to have a baby >4000 g and no increased risk of having a small baby. There is limited information on the long-term impact of prenatal physical activity on child growth. PURPOSE: To examine the impact of maternal prenatal physical activity on child growth from birth to three years. METHODS: Data were obtained from a subset of the Alberta Pregnancy Outcomes and Nutrition (APrON) cohort (N = 1,654). Prenatal physical activity was assessed (Baecke) at three timepoints. Singleton infant weight and length were collected at birth, 3, 6, 12, 24, and 36 months of age and converted to z-scores (WHO Anthro Survey Analyser). We created separate trajectories of latent clusters of work, leisure, and sports scores across pregnancy. Multi-trajectory modeling identified four latent clusters of offspring based on z-score length, weight, and body mass index (kg/m2) (Figure 1). Multinomial logistic regression was used to assess the associations (relative risk; RR) between pregnancy physical activity and child growth trajectories. RESULTS: Mothers were 31 ± 4.5 (mean ± SD) y of age, mostly Caucasian (81%), and well-educated (88% - some post-secondary); infant birthweight was 3.4 ± 0.4 kg. In crude analyses, maternal work, sport, and leisure trajectories were associated with infant growth (p = 0.04). Lower levels of work activity and higher levels of leisure activity were both associated with decreased odds of membership in Group 1 vs Group 2 (reference) (RR: 0.7; p = 0.03) and (RR: 0.6; p = 0.04), respectively. Maternal physical activity was no longer associated with child growth following adjustment for relevant covariates. CONCLUSION: Maternal prenatal physical activity does not impact child growth trajectories in the first three years postpartum. Supported by WCHRI, CIHR, Christenson Professorship in Active Healthy Living, Fundamental Research Funds - Central Universities, Young Scientists Fund of the NSFC.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".