Does exposure to different menstrual products affect the vaginal environment?
Bibliographic record
Abstract
The vaginal ecosystem is a key component of women's health. It also represents an ideal system for ecologists to investigate the consequence of perturbations on species diversity and emerging properties between organizational levels. Here, we study how exposure to different types of menstrual products is linked to microbial, immunological, demographic, and behavioural measurements in a cohort of young adult women who reported using more often tampons (n = 107) or menstrual cups (n = 31). We first found that cup users were older and smoked less than tampon users. When analysing health indicators, we detected potential associations between cups use reporting and fungal genital infection. A multivariate analysis confirmed that in our cohort, reporting using cups over tampons was associated with the higher odds ratio to report a fungal genital infection diagnosis by a medical doctor within the last 3 months. We did not detect significant differences between groups in terms of their bacterial vaginal microbiota composition and found marginal differences in the level of expression of 20 cytokines. However, a multivariate analysis of these biological data identified some level of clustering based on the menstrual product type preferred (cups or tampons). These results suggest that exposure to different types of menstrual products could influence menstrual health. Larger studies and studies with a more powered setting are needed to assess the robustness of these associations and identify causal mechanisms.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".