Childhood physical activity and pubertal timing: findings from the LEGACY girls study
Bibliographic record
Abstract
BACKGROUND: There is limited research on whether physical activity (PA) in early childhood is associated with the timing of pubertal events in girls. METHODS: We used data collected over 2011-16 from the LEGACY Girls Study (n = 984; primarily aged 6-13 years at study enrolment), a multicentre North American cohort enriched for girls with a breast cancer family history (BCFH), to evaluate if PA is associated with age at thelarche, pubarche and menarche. Maternal-reported questionnaire data measured puberty outcomes, PA in early childhood (ages 3-5 years) and total metabolic equivalents of organized PA in middle childhood (ages 7-9 years). We used interval-censored Weibull parametric survival regression models with age as the time scale and adjusted for sociodemographic factors, and we tested for effect modification by BCFH. We used inverse odds weighting to test for mediation by body mass index-for-age z-score (BMIZ) measured at study enrolment. RESULTS: Being highly active vs inactive in early childhood was associated with later thelarche in girls with a BCFH [adjusted hazard ratio (aHR) = 0.39, 95% CI = 0.26-0.59), but not in girls without a BCFH. In all girls, irrespective of BCFH, being in the highest vs lowest quartile of organized PA in middle childhood was associated with later menarche (aHR = 0.70, 95% CI = 0.50-0.97). These associations remained after accounting for potential mediation by BMIZ. CONCLUSION: This study provides new data that PA in early childhood may be associated with later thelarche in girls with a BCFH, also further supporting an overall association between PA in middle childhood and later menarche.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".