Childhood dyslexia risk elevated by heavy metal mixtures from e-waste: A machine learning–driven mixture modeling study

Key Points

• Elevated risk for dyslexia occurs in children exposed to heavy metal mixtures from e-waste.
• Key evidence shows a significant correlation between heavy metal exposure and dyslexia risk in the studied population.
• The analysis utilized machine learning-driven mixture modeling to assess the impact of heavy metals on dyslexia risk.
• These findings highlight the importance of regulatory measures regarding e-waste to protect children's health.