Health risk assessment of exposure to triclosan in pregnant women using Monte Carlo simulation techniques: based on biomonitoring data .
Elham AttarianFarzaneh MohammadiKarim EbrahimMalihe MoazeniMohammadreza MaracyAfshin EbrahimiRoya KelishadiPublished in: Journal of environmental science and health. Part C, Toxicology and carcinogenesis (2023)
This study aimed to assess the triclosan (TCS) health risk in an Iranian pregnant women sample by Monte Carlo simulation (MCS). The urinary TCS of 99 women after the 28 th week of pregnancy was detected by gas chromatography/mass spectrometry detector (GC/MS), and the MCS model implemented a health risk assessment. The corresponding hazard quotient (HQ) and the sensitivity analysis were calculated. TCS was measured in 100% of the urine samples with a median concentration of 2.89 µg/L. The median of HQ was obtained at 1.93 × 10 -4 . The TCS exposure risk in the studied population was lower than the allowable limit. A comparison between HQ values in the two weight subgroups of pregnant women showed that the risk level is almost equal, and there was minimal health risk in pregnant women from exposure to TCS.
Keyphrases
- pregnant women
- health risk
- health risk assessment
- heavy metals
- monte carlo
- drinking water
- pregnancy outcomes
- gas chromatography mass spectrometry
- risk assessment
- physical activity
- computed tomography
- machine learning
- magnetic resonance imaging
- magnetic resonance
- type diabetes
- skeletal muscle
- big data
- clinical trial
- artificial intelligence
- data analysis
- simultaneous determination