Study on the influencing factors of primary dysmenorrhea in female college students: Systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The influencing factors of primary dysmenorrhea in female college students were analyzed through meta-analysis to provide the corresponding basis for its prevention and treatment. METHODS: The databases, including China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform, VIP database, China Biology Medicine Disc, Pubmed, Embase, Cochrane library, and Web of science were searched for the literature on the influencing factors of primary dysmenorrhea in female college students was retrieved from the science database from the establishment of the database to July 17, 2023. The Newcastle-Ottawa Quality Scale was used to score the quality of cohort and case-control studies included in the study. The cross-sectional studies were scored by the Agency for Healthcare Research and Quality. Two researchers independently screened the literature, and if there was no consensus, the third party would make a judgment on whether to include the literature. The extracted content included the first author, publication year, country, study type, sample size, and influencing factors. Stata17.0 software was used for meta-analysis. RESULTS: A total of 23 studies were included, with a total sample size of 18,080 cases. Current evidence shows that the prevalence of primary dysmenorrhea in female college students is 70.3% (95%CI: 62.7-77.9%), and the combined odd ratio values (95%CI) of the main influencing factors are: family history of dysmenorrhea 2.116 (1.613-2.776), early age at menarche 2.200 (1.392-3.477), irregular menstrual cycle 1.662 (1.166-2.367), drinking cold drinks 1.717 (1.220-2.417), high caffeine intake 2.082 (1.379-3.144), stress 1.895 (1.515-2.282), medical specialty 1.827 (1.365-2.445), and adequate sleep 0.328 (0.232-0.463). CONCLUSION: The prevalence of primary dysmenorrhea is high in female college students, and adequate sleep is a protective factor for primary dysmenorrhea. Family history of dysmenorrhea, early age at menarche, irregular menstrual cycle, drinking cold drinks, high caffeine intake, stress, and medical specialty were all risk factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".