Non-genetic risk factors for early and late age at menarche in Eastern Ukrainian females
Bibliographic record
Abstract
ABSTRACT: BACKGROUND: Age at menarche is a reproductive trait, which is largely influenced by environmental factors. Each population has a set of lifestyle factors that may shift age at menarche in different direction. Populations of Eastern Slavs, particularly Ukrainians, are underrepresented in studies of reproductive health. The objective of the present research was to determine important non-genetic risk factors, which may contribute to menarcheal onset in Eastern Ukrainians. METHODS: In total 620 females aged 17-25 years participated in the cross-sectional survey. The questionnaire included lifestyle factors previously reported in other populations as those, which might affect age at menarche. The risk factors for early and late age at menarche were determined using logistic regression models. The models were validated by receiver operating curves. RESULTS: Body composition in the prepubertal stage as presented by responders seems to have the strongest association with age at menarche. Those who were shorter and thinner as compared to their peers at age six had significantly more chance to start menstruating later (OR = 1.66, 95% CI [1.01-2.73]) and reduced chance to have menarche before 12 years old (OR = 0.32, 95% CI [0.14-0.73]). Maternal smoking during pregnancy and low protein intake reported during childhood may decrease a probability of late age at menarche. CONCLUSIONS: Although overall body composition at age of six was a main trait, which was associated with menarcheal timing, more information on body measurements (e.g. waist-hip ratio) in prepubertal stage would help to establish a greater degree of accuracy on this matter.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".