Association of diet quality and hormonal status in exercising women with menstrual disturbances
Bibliographic record
Abstract
Diet plays a role in the pathophysiology and treatment of women with hyperandrogenic menstrual disturbances; however, limited research exists examining components of dietary intake in women with subclinical menstrual disturbances. The aim of this investigation was to evaluate the relationship between diet quality and hormonal status in exercising women with menstrual disturbances. Eighty exercising women with ovulatory menstrual cycles (OV; n = 32), women with oligo/amenorrhea without evidence of hyperandrogenism (Oligo/Amen-LowFAI; n = 28), and women with oligo/amenorrhea and evidence of subclinical hyperandrogenism (Oligo/Amen-HighFAI; n = 32) participated in the cross-sectional observational study (Clinical Trial Number: NCT00392873). Self-reported menstrual history, resting energy expenditure, body composition, hormonal and metabolic hormone concentrations determined reproductive and metabolic status. Serum androgens and calculated free androgen index (FAI) determined androgen status. The Diet Quality Index International (DQI-I) and the Dietary Inflammatory Index (DII) evaluated quality of diet. Oligo/Amen-HighFAI group had the highest androgen concentrations ( P < 0.05) and lower DQI-I score compared to OV group and Oligo/Amen-LowFAI ( P < 0.05). The Oligo/Amen-HighFAI group consumed less of vitamin A, B2, B6, B12, magnesium, and potassium compared to the Oligo/Amen-LowFAI group (all P < 0.05). In the women with menstrual disturbances with subclinically elevated androgens, poor diet quality is related to altered hormonal parameters which may have implications for future nutritional treatment strategies.
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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 | 0.000 | 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".