Age of menarche: the role of some psychosocial factors
Bibliographic record
Abstract
BACKGROUND: The goal of this study was to determine associations between the age of first menstrual period (menarche) and adverse childhood experiences in a random community sample of New Zealand women. Previous reports have linked early menarche to absence of a live-in father figure and to family conflict, as well as genetic determination of early puberty and adiposity. METHOD: Two groups of women randomly selected from the community on their responses to a mailed screening questionnaire on childhood sexual abuse (CSA) were interviewed in detail. Data about their childhood experiences, including age of menarche, were collected on two occasions, 6 years apart. Early menarche was defined as first menstruation occurring before the age of 12 years. RESULTS: Univariate analyses identified a number of adverse childhood experiences preceded early menarche, which was reported by 20.3% of this sample. These included low family socio-economic status, absence of father, a number of variables showing family conflict, poor relationships between the girl and either/both parents, a self-rated childhood personality style as a loner, childhood physical and sexual abuse. Sequential modelling showed parental rows, being a loner and the duration of CSA to be most important, although lack of a father and any CSA were each also independently associated with early menarche. No variables survived the modelling exercise as predictors of early menarche for those women who did not report childhood sexual abuse. CONCLUSIONS: The identified variables statistically interacted with each other in a highly complex manner. The attempt to rank their importance was only partially successful, for methodological reasons (half the sample reporting CSA). Chronic or protracted CSA needs to be added to the list of factors associated with early menarche in future studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".