Prevalence and impact of vasomotor symptoms due to menopause among women in Brazil, Canada, Mexico, and Nordic Europe: a cross-sectional survey
Bibliographic record
Abstract
OBJECTIVE: This study investigated the prevalence and impact of moderate to severe vasomotor symptoms (VMS), related treatment patterns, and experiences in women. METHODS: The primary objective was to assess the prevalence of moderate to severe menopause-related VMS among postmenopausal women aged 40 to 65 years in Brazil, Canada, Mexico, and four Nordic European countries (Denmark, Finland, Norway, and Sweden) using an online survey. Secondary objectives assessed impact of VMS among perimenopausal and postmenopausal women with moderate to severe VMS using the Menopause-Specific Quality of Life questionnaire, Work Productivity and Activity Impairment questionnaire, Patient-Reported Outcomes Measurement Information System sleep disturbances assessment, and questions regarding treatment patterns and attitudes toward symptoms and available treatments. RESULTS: Among 12,268 postmenopausal women, the prevalence of moderate to severe VMS was about 15.6% and was highest in Brazil (36.2%) and lowest in Nordic Europe (11.6%). Secondary analyses, conducted among 2,176 perimenopausal and postmenopausal women, showed that VMS affected quality of life across all domains measured and impaired work activities by as much as 30%. Greater symptom severity negatively affected sleep. Many women sought medical advice, but most (1,238 [56.9%]) were not receiving treatment for their VMS. The majority (>70%) considered menopause to be a natural part of aging. Those treated with prescription hormone therapy and nonhormone medications reported some safety/efficacy concerns. CONCLUSIONS: Among women from seven countries, moderate to severe menopause-related VMS were widespread, varied by region, and largely impaired quality of life, productivity, and/or sleep.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".