Methyl Paraben May Increase Risk of Pruritus in African Americans Whereas Triclosan Is Inversely Associated With Pruritus and Eczema
Bibliographic record
Abstract
BACKGROUND: Phenols and parabens (P&Ps) are commonly found in skin care products. However, P&Ps' role in pruritus and eczema has not been studied. OBJECTIVE: The aim of the study was to investigate the association between P&Ps, and pruritus and eczema. METHODS: This is a cross-sectional population-based study of 2202 participants. We examined the association between urinary phenols (triclosan, bisphenol A, benzophenone-3) and parabens (methyl and propyl parabens) and itchy rash/eczema using the 2005-2006 National Health and Nutrition Examination Survey database. Phenols and parabens were divided into quartiles (Qs) with the first Q as the reference. We calculated odds ratios and 95% confidence intervals, adjusting for multiple variables. RESULTS: Urinary triclosan was inversely associated with itchy rash (P trend = 0.048). In a subpopulation analysis by race/ethnicity, urinary methyl paraben was positively associated with itchy rash in African Americans (fourth Q vs first Q: odds ratio, 12.60; 95% confidence interval, 1.03-154.06; P trend = 0.02). Triclosan was inversely associated with eczema in whites (P trend = 0.04). CONCLUSIONS: Methyl paraben exposure may increase the risk of itchy rash in African Americans, whereas triclosan may decrease the risk of itchy rash and eczema. The potential effect of triclosan and methyl paraben in pruritus and eczema warrants further study.
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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) | 0.003 | 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".