Exploring environmental obesogenous effects of organic ultraviolet filters on children from a case-control study

Chemosphere(2023)

引用 0|浏览7
暂无评分
摘要
It has been globally recognized that obesity has become a major public health concern, especially childhood obesity. There is limited information, however, regarding the exposure risk of organic ultraviolet (UV) filters, a kind of emerging contaminant, on childhood obesity. This study would be made on 284 obese and 220 non-obese Chinese children with eight organic UV filters at urinary levels. The eight organic UV filters, including 2-Ethylhexyl 4-aminobenzoate (PABA-E), octisalate (EHS), homosalate (HMS), 2-Ethylhexyl-p-methoxycinnamate (EHMC), benzophenone-3 (BP-3), amiloxate (IAMC), octocrylene (OC) and 4-Methylbenzylidene camphor (4-MBC) were identified in urine samples with detection rates ranged from 35.32% to 100%, among which PABA-E, HMS, IAMC and OC were firstly detected in children’ s urine. And the urinary UV filters concentration was associated with genders, living sites, guardian education levels, household income, and dietary factors. Urinary EHMC concentrations and childhood obesity were positively associated for girls [Adjusted OR = 2.642 (95% CI: 1.019, 6.853)], while OC concentrations and childhood obesity were negatively associated for girls [Adjusted OR = 0.022 (95% CI: 0.001, 0.817)]. The results suggest that EHMC exposure may be an environmental obesogen for girls. Moreover, two statistical models were used separately to evaluate the impact of UV filter mixtures on childhood obesity, including the Bayesian kernel machine regression (BKMR) model and the quantile g-computation (qgcomp) model. The negative association between UV filter mixtures and childhood obesity was proposed from both BKMR and qgcomp models. Further experimental and epidemiological studies are called upon to discern the individual and mixture impacts of organic UV filters on childhood obesity.
更多
查看译文
关键词
Childhood obesity,Organic UV filters,Urinary concentration,Case-control study,Co-exposure
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要