Age at menarche in Canada: results from the National Longitudinal Survey of Children & Youth
Bibliographic record
Abstract
BACKGROUND: Given the downward trend in age at menarche and its implications for the reproductive health and wellbeing of women, little is known about menarcheal age in Canada. Most Canadian studies are only representative of specific populations. The present study, therefore, aims to assess the distribution of age at menarche for Canadian girls and explore its variation across socio-economic and demographic factors. METHODS: The analysis of the study was based on all female respondents aged 14 to 17 years during Cycle 4 (2000/2001) of the National Longitudinal Survey of Children & Youth (NLSCY). The main outcome was age at menarche assessed as the month and year of the occurrence of the first menstrual cycle. Kaplan Meier was used to estimate the mean and median of age at menarche. Chi-square test was used to assess the differences in early, average and later maturers across the different levels of socio-economic and demographic variables. Bootstrapping was performed to account for the complex sampling design. RESULTS: The total number of girls analyzed in this study was 1,403 weighted to represent 601,911 Canadian girls. The estimated mean and median of age at menarche was 12.72 years (standard deviation = 1.05) and 12.67 years, respectively. The proportions of early (< 11.53 years), average (≥ 11.53 years and ≤ 13.91 years) and late maturers (> 13.91 years) were 14.6% (95% confidence interval (CI): 11.92-17.35), 68.0% (95% CI: 63.82-72.17) and 17.4% (95% CI: 14.10-20.63), respectively. Variations across the menarcheal groups were statistically significant for the province of residence, household income and family type. CONCLUSION: The findings of the study pave the way for future Canadian research. More studies are warranted to understand menarcheal age in terms of its variation across the provinces, the secular trend over time and its potential predictors.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".