Predictors of urinary antibiotics in children of Shanghai and health risk assessment

• Main Authors: Hexing Wang, Chuanxi Tang, Jiaqi Yang, Na Wang, Feng Jiang, Qinghua Xia, Gengsheng He, Yue Chen, Qingwu Jiang
• Format: Article
• Language: English
• Published: Elsevier 2018-12-01
• Series: Environment International
• Online Access: http://www.sciencedirect.com/science/article/pii/S0160412018312790

Background: An extensive exposure to antibiotics has been confirmed in children, but the predictors and potential health risk remain unclear. Objective: To investigate the predictors of antibiotics in urine and potential health risk in children of Shanghai. Methods: We selected 284 school children aged 8–11 years from a central area of Shanghai, China, in 2017. Ultra-performance liquid chromatography coupled with high-resolution mass spectrometry was used to measure 20 antibiotics, including four human antibiotics (HAs), six veterinary antibiotics (VAs), 10 human/veterinary antibiotics (H/VAs), and three metabolites in first morning urine. Logistic regression model was used to examine the associations of 17 variables related to demographic and socioeconomic factors, recent antibiotic use, drinking water intake, food consumption, and anthropometric measurements with the detection frequency of HAs, VAs, or H/VAs in urine. After daily intake was estimated, health risk was assessed for VAs and H/VAs by using hazard quotient (HQ) and hazard index (HI) based on microbiological or toxicological effects. Results: The detection frequencies of 20 antibiotics and three metabolites ranged from 0 to 27.8% with an overall detection frequency being 56.0%. The detection frequency of HAs increased with age and screen time at weekend. Sex, age, family income and screen time were positively associated with the detection frequencies of VAs and H/VAs. Children reporting antibiotic use in the past three months had a higher detection frequency of HAs. Children with a higher consumption frequency of dairy products had a higher detection frequency of VAs + H/VAs, but a lower detection frequency of HAs. An increased overall detection frequency of all antibiotics was seen in children with higher consumption frequencies of aquatic products, livestock and poultry meat, or milk and dairy products. HQ >1 was only found for ciprofloxacin (5.6%) and ofloxacin (0.4%) based on microbiological effect. HI >1 was found in 6.0% of children for microbiological effect and none was found for toxicological effect. Conclusions: Predictors for antibiotics in urine for children included sex, age, family income, screen time, clinical use, and animal-derived food consumption. There was potential health risk for children with exposure to antibiotics. Keywords: Antibiotic, Urine, Predictor, Health risk, Chinese children, Shanghai