The association between diabetes type, age of onset, and age at natural menopause: a retrospective cohort study using the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
OBJECTIVES: With growing incidence of type 1 diabetes (T1D), type 2 diabetes (T2D), and gestational diabetes, more women are expected to spend a larger proportion of their reproductive years living with a diabetes diagnosis. It is important to understand the long-term implications of premenopausal diabetes type on women's reproductive health including their age at natural menopause (ANM). METHODS: Baseline data from the Comprehensive Cohort of Canadian Longitudinal Study on Aging were used. Females who reported premenopausal diagnosis of diabetes were considered exposed. Kaplan-Meier cumulative survivorship estimates and multivariable Cox regression models were used to assess the association between diabetes types and ANM. Sociodemographic, lifestyle, and premenopausal clinical factors were adjusted in the final model as covariates. RESULTS: The sample comprised 11,436 participants, weighted to represent 1,474,412Canadian females aged 45 to 85 years. The median ANM was 52 years. After adjusting for ethnicity, education, smoking, and premenopausal clinical factors, early age of diagnosis of both T1D (<30 years) and T2D (30-39 years) were associated with earlier menopause (T1D, <30: hazard ratio [HR], 1.55; 95% confidence interval [CI], 1.05-2.28; T2D, 30-39: HR, 1.82; 95% CI, 1.12-2.94), as compared with nondiabetics. In addition, later age of diagnosis of T2D (≥40 years) was associated with later ANM (T2D: HR, 0.63; 95% CI, 0.50-0.80). No significant association between gestational diabetes and ANM was noted. CONCLUSIONS: Our results point to early menopause among young women living with a diabetes diagnosis. These findings should allow for more focused research geared toward understanding the long-term health implications of diabetes on women's reproductive health and aging.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| 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) | 0.001 | 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".