Effects of single and multiple endocrine-disrupting chemical exposures on hyperactivity trajectories among preschoolers: A cohort study
Year: 2025
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: To evaluate the association of individual and mixed exposure to endocrine-disrupting chemicals (EDCs) with hyperactivity trajectories in preschoolers. METHOD: ). Latent class growth analysis (LCGA) was used to assess children's hyperactivity trajectories. We investigated the individual and joint effects of EDCs using binary logistic regression, quantile-based g-computation (Q-gcomp) model, and Bayesian kernel machine regression (BKMR) model, respectively. RESULTS: We identified two hyperactivity trajectories: the "high hyperactivity trajectory" and the "low hyperactivity trajectory". The binary logistic regression results showed that nine chemicals were significantly associated with hyperactivity trajectories (OR = 0.57 ∼ 2.37, 95 % CI: 0.33-4.03). The Q-gcomp model showed a positive association between mixed EDC exposures and the hyperactivity trajectories (OR = 2.13, 95 % CI: 1.70-2.66). The BKMR model found a significant positive relationship between the EDC mixtures and hyperactivity trajectories when all chemical concentrations were at or above their 55th percentile compared with the median. After stratification by gender, we found that exposure to EDC mixtures was more strongly associated with hyperactivity trajectories in girls. CONCLUSION: The current study indicates the adverse health effects of exposure to mixtures of EDCs among preschoolers, and suggests gender specificity in these effects. This highlights the importance of focusing on multi-pollutant exposure in early childhood and taking targeted interventions.
Source: Environment International
Authors: Ruo-yu Li, Shu-qin Li, Yang Zhou, Wan Xiao, Hui-qiong Xu, Xing-yong Tao, Ji-an Xie, Yu-hui Wan
Language: English
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $4,750
Awards: G3197559858, G3274976677
OpenAlex ID: W4414780522
