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The Association between Prenatal Antibiotic Use and the Risk of Autism Spectrum Disorders among Children: An Updated
Azam Maleki1, Helen Behmanesh2, Ensiyeh Jenabi2
1Social Determinants of Health Research Center, Health and Metabolic Diseases Research Institute, Zanjan University of Medical Sciences, Zanjan, Iran.
Prenatal antibiotic exposure is linked to a higher risk of Autism Spectrum Disorder (ASD) in children. This association was consistent across all pregnancy trimesters, highlighting potential developmental impacts.
Area of Science:
- Perinatal health and developmental disorders
- Epidemiology of neurodevelopmental conditions
Background:
- Inconsistent findings exist regarding prenatal antibiotic use and Autism Spectrum Disorder (ASD) risk.
- Understanding this relationship is crucial for maternal and child health guidelines.
Purpose of the Study:
- To conduct a meta-analysis to resolve discrepancies in studies on prenatal antibiotic exposure and ASD risk.
- To provide a comprehensive assessment of the association between prenatal antibiotic use and ASD in children.
Main Methods:
- A systematic literature search was performed across PubMed, Scopus, and Web of Science databases.
- Random-effect models were used to calculate hazard ratios (HR) and odds ratios (OR), with publication bias assessed.
- Subgroup analyses examined trimester-specific effects, and study quality was evaluated using the Newcastle-Ottawa Scale.
Main Results:
- The meta-analysis included 12 studies with over 5 million participants.
- Prenatal antibiotic use was associated with an increased risk of ASD (HR: 1.08; 95% CI: 1.05, 1.12).
- Significant associations were found for each trimester of pregnancy, with no detected heterogeneity or publication bias.
Conclusions:
- A significant link exists between prenatal antibiotic use and elevated ASD risk, with a consistent, modest increase across all trimesters.
- Further research is needed to explore mechanisms, specific antibiotic classes, dosages, and timing.
- Longitudinal studies controlling for confounders are essential for causal inference and clinical recommendations.
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