Prevalence and severity of menopausal symptoms among menopausal women, Babol, Iran
Bibliographic record
Abstract
Background: Understanding prevalence of various menopausal symptoms and symptom severity in Iran will enhance reproductive health care. The aim of the study was to determine the prevalence and severity of menopausal symptoms among menopausal women in Babol, Iran. Methods: A cross sectional study was conducted on the 150 healthy postmenopausal women aged between 45–65 years in Babol city (located in Northern Iran), and cluster sampling was used as a method of sampling. The questionnaires used in this study include: symptom score card for measuring the frequency and severity of menopausal symptoms and socio demographic data. Results: The mean ± SD age at natural menopause was 48.5 ± 4.1 years. The most prevalent symptoms were back pain and joint pain (48.7%), anxiety and unusual tiredness (48.0%), irritability (46.7%), muscle pains (44.0%) and hot flashes (42.7%). The average overall symptom score card in the study for menopausal symptoms was 22.1 ± 9.8. The severity of symptoms was in the range of mild to moderate in 42% of samples, and 58% of samples had moderate to severe symptoms. Conclusion: This study showed that more than half of the women had moderate to severe menopausal symptoms and an earlier mean age of menopause (48.5 y) for women in Babol, Iran.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".