Evidence mapPaperPMID 41808561Full record

SynthesisDiabetes, obesity & metabolism2026

Antibiotic Exposure in Early Life and Risk of Type 1 Diabetes: A Meta-Analysis.

Sharan Ram, Marine Corbin, Andrea 't Mannetje, Jeroen Douwes, Amanda Kvalsvig, Amanda Eng

Abstract readMeta-Analysis
In one paragraph

Synthesis in Diabetes, obesity & metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Sharan RamCentre for Public Health Research, Massey University, Wellington, New Zealand.ORCID https://orcid.org/0000-0003-1903-8677
Marine CorbinCentre for Public Health Research, Massey University, Wellington, New Zealand.
Andrea 't MannetjeCentre for Public Health Research, Massey University, Wellington, New Zealand.
Jeroen DouwesCentre for Public Health Research, Massey University, Wellington, New Zealand.
Amanda KvalsvigDepartment of Public Health, University of Otago, Wellington, New Zealand.
Amanda EngCentre for Public Health Research, Massey University, Wellington, New Zealand.

Funding

Health Research Council of New Zealand HD21/053
6 · The paper itself

Abstract

backgroundEarly-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.

methodsA 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).

resultsThe 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.

conclusionThis 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.

Indexed as

Anti-Bacterial AgentsDiabetes Mellitus, Type 1Prenatal Exposure Delayed EffectsChildChild, PreschoolDysbiosisFemaleGastrointestinal MicrobiomeHumansInfantInfant, NewbornPregnancyRisk FactorsAnti-Bacterial Agentsantibiotic‐usechildhood type 1 diabetesearly lifemeta‐analysismicrobiome dysbiosis

Identifiers

PMID41808561
PMCPMC13146189

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.