Insulin levels early in perimenopause inform vasomotor symptom incidence across the menopausal transition
Bibliographic record
Abstract
Context: Metabolic health and body mass index (BMI) has been implicated in influencing menopause-related changes, but the role of elevated insulin, an early marker of metabolic dysfunction, remains understudied. Objective: To determine whether midlife fasting insulin is associated with menopausal changes such as vasomotor symptom incidence and reproductive hormone trajectories. Methods: This study consisted of longitudinal analyses of 704 community-based participants from the Study of Women's Health Across the Nation (SWAN). It included data from baseline to the 10th annual visit, restricted to women who had age-47 fasting insulin measurements. Main outcome measures included timing and duration of hot flashes, night sweats, cold sweats, and vaginal dryness, and trajectories of estradiol, follicle-stimulating hormone, and testosterone from 6 years before to 6 years after the final menstrual period. Results: Higher fasting insulin levels during early perimenopause predicted earlier onset of hot flashes and night sweats, longer duration of hot flashes and cold sweats, and greater increases in testosterone. In Cox proportional hazards models, elevated age-47 insulin was associated with a higher hazard of hot flashes and cold sweats; the association between insulin and hot flash likelihood remained significant when BMI was incorporated as a covariate. BMI associations with vasomotor symptoms paralleled those of insulin levels, but BMI appeared to be more closely associated with slower estradiol decline and blunted FSH rise. Conclusions: Perimenopausal fasting insulin and BMI show complementary but distinct associations with menopausal changes. Elevated insulin predicts earlier and prolonged vasomotor symptoms, and is also associated with higher testosterone levels.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| 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".