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Exposure to triclosan among pregnant women in northern China: urinary concentrations, sociodemographic predictors, and seasonal variability

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Abstract

Although triclosan (TCS) use is widespread in China, little is known about levels of exposure to TCS in pregnant women and its potential predictors, sources, and seasonal variability. We assessed urinary TCS levels of 466 pregnant women in a Chinese cohort. The estimated daily intake (EDI) and hazard quotient (HQ) were calculated. Potential predictors and sources were collected through a questionnaire and the seasonal variability was recorded based on the time of sampling. The geometric mean of urinary TCS concentration was 0.81 μg/g. The 95th EDI was 0.15 μg/kg BW per day and the corresponding HQ was 3.23 × 10−3. Women with a household monthly salary between RMB (¥) 1000 and 3000 and between RMB (¥) 3000 and 5000 had 0.52 μg/g (95% CI 0.08, 0.75) and 0.58 μg/g (95% CI 0.17, 0.79) lower urinary TCS levels than those with a household monthly salary of < RMB (¥) 1000, respectively. Urine samples collected in winter had lower TCS levels (geometric mean 0.72 μg/g) than in spring, summer, and autumn (geometric mean 0.82, 0.84, and 0.86 μg/g), although they were non-significant (P = 0.648). No association was found between drinking water and food consumed during pregnancy and TCS levels. The study population was ubiquitously exposed to a relatively low and safe dose of TCS. Women with lower household income tended to be exposed to higher levels of TCS.

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Funding

This study was financially supported by National Key Research and Development Program of China (2017YFC1600500, 2016YFC1000203) and National Natural Science Foundation of China (81872629; 81803247).

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Correspondence to Caifeng Wang or Ying Tian.

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The research was approved by the Medical Ethics Committee of Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine.

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Jin, C., Yao, Q., Zhou, Y. et al. Exposure to triclosan among pregnant women in northern China: urinary concentrations, sociodemographic predictors, and seasonal variability. Environ Sci Pollut Res 27, 4840–4848 (2020). https://doi.org/10.1007/s11356-019-07294-1

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