Early age at menarche and metabolic cardiovascular risk factors: mediation by body composition in adulthood
Bibliographic record
Abstract
Evidence suggests that early menarche increases cardiometabolic risk, and adiposity would be a possible mediator of this association. We assessed the association between age at menarche and metabolic cardiovascular risk factors and estimated the indirect effect of body composition in adulthood. In 1982, all hospital births in the city of Pelotas/Brazil, were identified and live births were examined and have been prospectively followed. At 30 years, information on age at menarche and metabolic cardiovascular risk factors was available for 1680 women. Mediation analysis was performed using G-computation to estimate the direct effect of age at menarche and the indirect effect of body composition. The prevalence of age at menarche < 12 years was 24.5% and was associated with higher mean diastolic blood pressure [β: 1.98; 95% CI: 0.56, 3.40], total cholesterol (β: 8.28; 95% CI: 2.67, 13.88), LDL-cholesterol (β: 6.53; 95% CI: 2.00, 11.07), triglycerides (β: 0.11; 95% CI: 0.03, 0.19). For diastolic blood pressure, total cholesterol, LDL-cholesterol, triglycerides, body composition assessed by fat mass index captured from 43.8 to 98.9% of the effect of early menarche, except to systolic blood pressure, HDL-cholesterol, C-reactive-protein. Suggesting that the effect of menarche age < 12 years on some metabolic cardiovascular risk factors is mediated partially by body composition in adulthood.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".