The Relationship Between Body Mass Index and Dysmenorrhea in the General Female Population
Bibliographic record
Abstract
Background: There may be an etiological association between obesity and dysmenorrheal traits. This study aimed to observe the relationship between body mass index (BMI) and dysmenorrhea in a general female population. Methods: Premenopausal adult females (n = 2,805) undergoing health checkups were assessed for data such as the BMI and self-reported severity of dysmenorrhea. The BMI levels were compared according to the severity of dysmenorrhea with adjustment for age, smoking habit, exercise habit, serum lipids, and plasma glucose. Results: The mean BMI level in females with severe dysmenorrhea (n = 278; 23.3 ± 4.5 (standard deviation) kg/m 2 ) was high relative to those with mild (n = 1,451; 22.3 ± 3.9 kg/m 2 ) and moderate (n = 1,076; 22.6 ± 4.4 kg/m 2 ) dysmenorrhea. Even after adjustment for covariables, the difference in BMI remained significant. Conclusions: The high-normal BMI level may be seen in severe dysmenorrhea in the general female population. Further research is needed to confirm the findings. J Clin Med Res. 2023;15(4):239-242 doi: https://doi.org/10.14740/jocmr4893
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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) | 0.002 | 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".