Patterns, Variability, and Predictors of Urinary Triclosan Concentrations during Pregnancy and Childhood
Bibliographic record
Abstract
Exposure to triclosan, an antimicrobial used in many consumer products, is ubiquitous in the United States, yet only limited data are available on the predictors and variability of exposure, particularly in children. We examined the patterns, variability, and predictors of urinary triclosan concentrations in 389 mother-child pairs enrolled in the Health Outcomes and Measures of the Environment Study from 2003 to 2006. We quantified triclosan in 3 urine samples collected from women between 16 weeks of pregnancy and birth and 6 urine samples collected from children between the ages of 1-8 years. For maternal and child samples, we calculated intraclass correlation coefficients (ICCs) to assess triclosan reproducibility and identified sociodemographic predictors of triclosan. Among 8 year old children, we examined associations between triclosan and personal-care product use. We detected triclosan in >70% of urine samples. Median maternal triclosan varied across pregnancy from 17 to 11 ng/mL, while in children, median concentrations increased from 3.6 to 17 ng/mL over the first 4 years of life, declining slightly at later ages. Triclosan reproducibility was fair to good during pregnancy and for child samples taken weeks apart (ICCs = 0.4-0.6) but poor for annual child samples (ICCs = 0.2-0.4). Triclosan was 66% (95% CI: 29-113) higher in 8 year olds using hand soap compared to nonusers and increased monotonically with hand-washing frequency. Toothpaste use in children was also positively associated with triclosan. Our results suggest that urinary triclosan concentrations have modest stability over weeks to months; children are exposed to triclosan through the use of some personal-care products.
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 | 0.001 | 0.004 |
| 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) | 0.000 | 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".