Maternal Factors During Pregnancy and Pubertal Timing in Offspring: A Systematic Review of the Literature
Bibliographic record
Abstract
PURPOSE: This systematic review aims to identify, assess the quality of, and synthesize evidence on nongenetic maternal factors, such as psychological factors, lifestyle, nutrition, and endocrine conditions that may be associated with pubertal timing in male and female offspring. METHODS: The search was conducted in Medline, Embase, PsycInfo and Web of Science. The reference lists of retrieved articles were checked to avoid missing relevant studies. There were no restrictions on publication year or language. The quality of the studies was assessed using the Newcastle-Ottawa Scale. This review has been registered on PROSPERO (CRD42023394102). A best-evidence approach was applied to qualitatively summarize the findings and draw conclusions on the level of evidence. RESULTS: The search yielded 4199 studies, of which 73 were included in this systematic review. In both boys and girls, there is strong evidence of a positive association between maternal gestational weight gain and an earlier pubertal timing, while no association was found with maternal substance use, thyroid dysfunction, or gestational hypertension. In addition, there is insufficient evidence of an association with maternal psychological factors, smoking, diet, physical activity, prepregnancy weight/body mass index, diabetes, menstruation-related disorders, and steroid medication use. CONCLUSION: This review provides a comprehensive overview of the quality and consistency of existing evidence regarding maternal factors during pregnancy that may be associated with the pubertal timing in their offspring. This review may serve as an orientation for future research initiatives, with a particular focus on exploring these associations among male offspring and in low- and middle-income countries.
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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 | 0.008 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".