Washington [US], April 3 (ANI): Findings from a recent study suggest a correlation between gestational exposure to selected environmental toxicants, including metals, pesticides, polychlorinated biphenyls (PCBs), phthalates, and bisphenol-A (BPA), and increased expression of autistic behaviors in preschool children. age.
The study, led by researchers at the Faculty of Health Sciences at Simon Fraser University, was published today in the American Journal of Epidemiology.
This population-based study measured the level of 25 chemicals in blood and urine samples collected from 1,861 Canadian women during the first trimester of pregnancy. A study was conducted with 478 participants, using the Social Response Scale (SRS) tool to assess autistic behavior of preschool children.
The researchers found that higher concentrations of cadmium, lead and some phthalates in mothers in blood or urine samples were associated with increased SRS scores, and these associations were particularly strong among children with a higher degree of autistic behavior. Interestingly, the study also noted that increased maternal concentrations of manganese, trans-nonachlor, many metabolites of organophosphate pesticides, and mono-ethyl phthalate (MEP) were most strongly associated with lower SRS scores.
Lead author of the study Josh Alampi notes that this study primarily “emphasizes the relationship between selected environmental toxicants and increased SRS results. Further studies are needed to fully assess the links and effects of these environmental chemicals on brain development during pregnancy.” they were achieved using a statistical analysis tool, called Bayesian quantile regression, which allowed researchers to determine which individual toxicants were associated with increased SRS scores in a more nuanced way than conventional methods.
“The relationships we found between these toxicants and SRS results would not be detected using a means-based statistical analysis method (such as linear regression),” Alampi noted. “Although researchers do not use quantile regression often, it can be a powerful way to analyze complex population-based data.” (ANI)