Plasma Carotenoids and Premenstrual Symptoms in a Multi-Ethnic Population of Young Women
Bibliographic record
Abstract
Premenstrual symptoms are experienced by most women of reproductive age, but effective therapies are limited. Carotenoids may have an attenuating effect on premenstrual symptoms; however, studies to date are equivocal. The objective of the present study was to examine the association between plasma concentrations of seven carotenoids and premenstrual symptom severity in 553 women from the Toronto Nutrigenomics and Health study. Participants provided information on fifteen common premenstrual symptoms and severities. Each participant completed a General Health and Lifestyle Questionnaire and provided a fasting blood sample from which plasma carotenoid concentrations were measured. Multinomial logistic regressions were used to determine associations between plasma carotenoid concentrations and premenstrual symptom severity. Beta-cryptoxanthin was associated with moderate/severe increased appetite for women in the highest compared to the lowest tertile (OR: 2.33; 95% CI: 1.39, 3.89). This association remained significant after adjusting for multiple comparisons. There were no observed associations between other plasma carotenoids and any premenstrual symptoms. In summary, higher concentrations of beta-cryptoxanthin were associated with an increased appetite as a premenstrual symptom, but no associations were observed for any other carotenoid and for any other symptom.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".