Impact of Maternal Prenatal Mineral Intake on Pubertal Onset in Mexican Children
Bibliographic record
Abstract
Prenatal intake of minerals that affect sex hormone levels may be related to initiation of maturity in children. We examined the effects of maternal intakes of selenium (Se), vitamin B2, calcium (Ca) and iron (Fe) during pregnancy on the pubertal onset at ages 8‐14 among 118 boys and 103 girls. Maternal dietary intake was assessed using a validated food frequency questionnaire. Tanner stages for genitalia (G) and pubic hair (MP) in boys; breast (B) and pubic hair (FP) in girls were obtained by clinical observation. Girls self‐reported age at menarche (M). Multivariable logistic models the association between Se, B2, Ca or Fe and pubertal onset, adjusting for child age, maternal energy intake and socio‐economic status. Mean (±SD) maternal prenatal intake during pregnancy was 46.73±17.11µg Se, 2.12±0.75 mg B2, 1198.30±411.17mg Ca, and 13.24±4.42mg Fe. With 1 standard deviation (SD) increase in Se, odds of M increased by 7.90 (95%CI: 1.13‐55.12) whereas 1 SD increase in Fe decreased odds of M by 0.18 (95%CI: 0.03‐0.97). With 1 SD increase in B2, odds of G decreased by 0.19 (95%CI: 0.05‐0.72); 1 SD increase in Ca decreased odds of G by 0.20 (95%CI: 0.06‐0.65) Findings suggest prenatal selenium consumption may be positively associated with menarche. By contrast, iron, vitamin B2, and calcium intake during pregnancy may be related to delayed pubertal onset. Future research will focus on examining the relationships between these micronutrients and sex hormones in order to understand underlying mechanisms. NIEHS 1R01ES021446‐01, P20 ES018171‐01/RD834800, P01 ES02284401/RD 83543601
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".