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Early-life antibiotic exposure linked to modest increased risk of childhood type 1 diabetes

Early-life antibiotic exposure linked to modest increased risk of childhood type 1 diabetes
Photo by National Institute of Allergy and Infectious Diseases / Unsplash
Key Takeaway
Consider the modest association between early-life antibiotics and type 1 diabetes risk when prescribing.

This is a meta-analysis examining the association between early-life antibiotic exposure and childhood type 1 diabetes risk. The authors synthesized data from studies involving over 1.5 million participants for prenatal exposure and over 4 million for postnatal exposure.

For prenatal antibiotic exposure, the pooled effect size was 1.05 (95% CI 0.98-1.11). For postnatal exposure, the pooled effect size was 1.07 (95% CI 1.01-1.14). The risk appeared higher with more courses: for postnatal exposure of at least 2 courses, the pooled effect size was 1.11 (95% CI 1.02-1.20), and for at least 5 courses, it was 1.14 (95% CI 1.00-1.30). Postnatal broad-spectrum antibiotics had a pooled effect size of 1.13 (95% CI 1.03-1.23), while narrow-spectrum antibiotics were not significant (pooled effect size 1.08, 95% CI 0.93-1.26).

The authors acknowledge limitations including variability in study design and exposure definitions, potential confounding by indication, and a small number of studies for subgroup analyses by antibiotic spectrum. They note the high quality of evidence but emphasize that associations are modest and causality needs clarification, with effects of antibiotics needing to be disentangled from those of underlying infections.

Practice relevance focuses on judicious antibiotic prescribing in early life, but the findings do not establish a causal relationship.

Study Details

Study typeMeta analysis
EvidenceLevel 1
PublishedJun 2026
View Original Abstract ↓
BACKGROUND: Early-life antibiotic use may increase the risk of childhood type 1 diabetes (T1D), potentially through gut microbiota dysbiosis and associated effects on immune development. This meta-analysis evaluated associations between early-life antibiotic use and T1D. METHODS: A systematic search of PubMed, MEDLINE, Scopus and Web of Science was conducted up to June 2025, which focused on studies reporting associations between antibiotic use in the pre- and postnatal periods and childhood T1D. Pooled effect sizes were assessed using random effects models separately for prenatal and postnatal antibiotic exposure, with subgroup analyses by antibiotic course, class and spectrum. Study quality was assessed using the Newcastle-Ottawa Quality Assessment Scale (NOS). RESULTS: The analysis included 20 studies (11 cohort, 9 case-control), encompassing > 1.5 million participants for prenatal and over 4 million for postnatal antibiotic exposure. A pooled effect size of 1.05 (95% CI 0.98-1.11) for prenatal exposure was found. Further analysis by antibiotic spectrum yielded no significant associations, likely due to the small number of studies. For postnatal antibiotic exposure, a pooled effect size of 1.07 (95% CI 1.01-1.14) was found, with estimates increasing with increased number of antibiotic courses: ≥ 2 courses, 1.11, 95% CI 1.02-1.20; and ≥ 5 courses, 1.14, 95% CI 1.00-1.30. Associations were stronger for broad-spectrum (1.13, 95% CI 1.03-1.23) than for narrow-spectrum antibiotics (1.08, 95% CI 0.93-1.26) but no significant associations were observed by antibiotic class. The impact of mode of obstetric delivery remained inconclusive across studies. The quality of the evidence was high. CONCLUSION: This meta-analysis suggests that early-life antibiotic use is associated with an increased risk of T1D, particularly with repeated courses and broad-spectrum agents. However, confidence in these findings is constrained by variability in study design and exposure definitions, as well as the potential for confounding by indication. While the observed associations are modest, they highlight the importance of judicious antibiotic prescribing in early life. Further large, well-designed prospective cohort studies are needed to clarify causality and better disentangle the effects of antibiotics from those of underlying infections.
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