Association between Small Fetuses and Puberty Timing: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Epidemiological studies reporting the effect of small fetuses (SF) on puberty development have shown inconsistent results. Objective: To examine current study evidence and determine the strength and direction of the association between SF and puberty timing. Methods: PubMed, OVID, Web of Science, EBSCO, and four Chinese databases were searched from their date of inception to February 2016. All cohort studies that examined the association between SF and puberty timing in children were identified. Two reviewers independently screened the studies, assessed the quality of included studies, and extracted the data. The quality of the included cohort studies was assessed by the Newcastle–Ottawa Scale. Risk ratio (RR), Weighted Mean Difference (WMD), and 95% confidence intervals (CIs) were calculated and pooled by RevMan5.3 (Cochrane Collaboration, London, UK). Results: A total of 10 cohort studies involving 2366 subjects was included in the final analysis. The pooled estimates showed that SF did not significantly increase the number of pubertal children in boys (RR: 0.97; 95% CI: 0.82 to 1.15), or in girls (RR: 0.91; 95% CI: 0.79 to 1.04). Compared with the control group, the SF group had an earlier onset of puberty in girls (WMD: −0.64; 95% CI: −1.21 to −0.06), and in precocious pubarche (PP) girls (WMD: −0.10; 95% CI: −0.13 to −0.07). There was no difference in the onset of puberty in boys (WMD: −0.48; 95% CI: −1.45 to 0.50) between SF and control groups. The pooled result indicated an earlier age at menarche in girls born small for gestational age (WMD: −0.30; 95% CI: −0.58 to −0.03), but no difference in the age at menarche in the SF group of PP girls. Conclusions: SF may be associated with an earlier age of onset of puberty, especially among girls, as well as earlier age at menarche for girls. Well-designed studies with larger sample sizes and long-term follow-up among different countries and ethnicities are needed.
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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 | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.029 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".