The prevalence of menstrual pain and associated risk factors among Iranian women
Bibliographic record
Abstract
AIM: To estimate the prevalence of dysmenorrhea in Iranian women and investigate associated risk factors. MATERIAL & METHODS: In a cross-sectional study in Tehran, Iran in 2007, 381 women (81% response rate, age 16-56 years) were selected through a stratified random sample of 22 different districts and completed a questionnaire about dysmenorrhea. Descriptive statistics, spearman rank correlation statistic, and ordinal logistic regression models were used. Confounding and effect-modification were explored for each association. RESULTS: The prevalence of no, mild, moderate, and severe menstrual pain was 10%, 41%, 28%, and 22%, respectively. Older age and high intake of fruits and vegetables were protective factors for menstrual pain while women with family history of dysmenorrhea, higher stress and depression tended to have more severe pain. Body mass index, parity, smoking, and physical activity were not significantly associated with dysmenorrhea after controlling for potential confounding factors and effect modifiers. CONCLUSION: Menstrual pain is a common complaint in Iranian women. The inverse association between fruit and vegetable intake and dysmenorrhea, and reduction of stress and depression need to be further explored and considered in terms of recommendation to reduce dysmenorrhea.
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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 | 0.001 | 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".