Abstract 2317: Historical trends in age of menarche and implications for breast cancer risk in the US population
Bibliographic record
Abstract
Abstract Background: Breast cancer incidence is increasing, especially among premenopausal women. Age of menarche is a critical marker of female pubertal development and a known risk factor for breast cancer. We, therefore, examined trends in the age of menarche among females born between 1910 and 2000 as well as the differences by race/ethnicity and country of birth. Methods: This serial, cross-sectional study analyzed the age of menarche from the nationally representative National Health and Nutrition Examination Survey (NHANES). Participants included noninstitutionalized US women from ten NHANES study cycles (1999-2000 to 2017-March 2020 pre-pandemic). Age of menarche was assessed as the age of first menstrual period by participants responding to the question “How old when you had your first menstrual period?” (range 0-22 years old). Participants who responded with an age of first menstrual period > 16 years were excluded from the current analysis. The year of birth was categorized into eight birth cohorts from 1910-1930, then every 10-year interval to 1990-2000. We calculated the weighted mean age and standard error of age of menarche overall and by birth cohort, race/ethnicity, and country of birth. We calculated weighted prevalences of the age of menarche by ages ≤ 10, 11, and 12 years, overall, and by birth cohort, race/ethnicity, and country of birth. Results: Data on 24, 391 US women were analyzed. For women born between 1910-1930 to those born between 1990-2000, the mean age of menarche declined from 12.9 (95% CI: 12.8 to 10.3) to 12.4 (95% CI: 12.3 to 12.6) years (difference=0.5, 95% CI: 0.3 to 0.7, p for trend<0.001). The significant decline in age of menarche was observed in women of all racial/ethnic groups (non-Hispanic White: 12.9 [95% CI: 12.8 to 13.0] to 12.6 [95% CI: 12.4 to 12.8], difference=0.3 [95% CI:0.01 to 0.5], non-Hispanic Black: 13.1 [95% CI: 12.8 to 13.3] to 12.2 [95% CI: 11.9 to 12.4], difference=0.9 [95% CI: 0.5 to 1.2]; Hispanic: 13.2 [95% CI: 12.7 to 13.8] to 12.1 [95% CI: 11.9 to 12.3], difference=1.1 [95% CI: 0.5 to 1.7]; Others: 13.0 [95% CI: 12.4 to 13.6] to 12.3 [95% CI: 11.9 to 12.6], difference=0.8 [95% CI: 0.03 to 1.5]). The decline in age of menarche was observed in both US (12.9 [95% CI: 12.8 to 13.0] to 12.4 [95% CI: 12.3 to 12.6]) and non-US born (13.3 [95% CI: 13.0 to 13.7] to 12.4 [95% CI: 12.1 to 12.8]) women. Among women in the 1990-2000 birth cohort, 11.1%, 27.9%, and 53.9% of women attained their age of menarche at ages younger than 10, 11, and 12 years, respectively. Conclusions: Women born in the 1990-2000 birth cohort experienced half a year younger age of menarche compared to those born between 1910-1930, with shaper declines in women of racial/ethnical minorities and those who were non-US born. These shifts suggest a growing proportion of women experiencing menarche earlier, likely contributing to the rising incidence of breast cancer. Citation Format: Lin Yang, Adetunji Torioa. Historical trends in age of menarche and implications for breast cancer risk in the US population [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2317.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".