Insulin Levels Early in Perimenopause Inform Vasomotor Symptom Incidence Across the Menopausal Transition
Bibliographic record
Abstract
CONTEXT: Metabolic health affects the menopausal transition. Metabolic characteristics like body mass index (BMI) affect vasomotor syndrome incidence, but the role of elevated insulin, an early marker of metabolic dysfunction, remains understudied. OBJECTIVE: This work aimed to determine whether midlife insulin levels are associated with vasomotor symptom incidence or reproductive hormone trajectories. METHODS: Longitudinal analyses of community-based data from the Study of Women's Health Across the Nation (SWAN) were conducted. We analyzed the 704 SWAN participants (of 3302) without oophorectomy or hysterectomy who had metabolic data for age 47 and did not take insulin/medications for hyperglycemia. Mean fasting insulin at age 47 was 10.117 µIU/mL (SD = 6.711), with 27.0 BMI (SD = 6.6); the mean age of the final menstrual period for these participants was 51.0 years (SD = 2.3). Main outcome measures included vasomotor symptom timings and durations, and trajectories of estradiol (E2), follicle-stimulating hormone (FSH), and testosterone (T) across the menopausal transition. RESULTS: Higher insulin at age 47 predicted younger onsets of hot flashes and night sweats, longer durations of hot flashes and cold sweats, and greater T rise. BMI associations with vasomotor symptoms paralleled those of insulin, but BMI appeared more closely linked to slower E2 decline and blunted FSH rise. In Cox proportional hazards models, elevated age-47 insulin was associated with increased likelihood of hot flashes; this remained statistically significant with BMI and glucose as covariates. CONCLUSION: Perimenopausal fasting insulin and BMI show complementary but distinct associations with menopausal changes. Elevated insulin predicts earlier and prolonged vasomotor symptoms, and is associated with higher T.
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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) | 0.000 | 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".