Hypotheses concerning adverse effects of changes in microbiota have received much recent attention, but unobserved confounding makes them difficult to test. We investigated whether surrogate markers for potential adverse microbiota change in infancy affected autism risk, addressing unobserved confounding using a sibling study design.
This is a population-based, prospective cohort study including all singleton live births in Denmark from 1997 to 2010. The exposure variables were cesarean delivery and antibiotic use in the first 2 years of life. The outcome was a subsequent autism diagnosis. We used the between- and within-sibling model and compared it with sibling-stratified Cox models and simpler standard Cox models that ignored sibship.
Of our study population including 671,606 children, who were followed for up to 15 years (7,341,133 person-years), 72% received antibiotics, 17.5% were delivered by cesarean, and 1.2% (8,267) developed autism. The standard Cox models predicted that both cesarean (compared with vaginal) delivery and antibiotics increased the risk of autism. In the sibling-stratified Cox model, only broader spectrum antibiotics were associated with increased risk of autism: hazard ratio (HR) = 1.16 (95% confidence interval = 1.01, 1.36). The between–within model estimated no exposure effects: intrapartum cesarean HR = 1.06 (0.89, 1.26); prelabor cesarean HR = 0.97 (0.83, 1.15); exclusively penicillin HR = 1.05 (0.93, 1.18); and broader spectrum antibiotics HR = 1.05 (0.95, 1.16).
The between–within model rendered more precise estimates than sibling-stratified Cox models, and we believe that it also provided more valid estimates. Results from these preferred models do not support a causal relation between antibiotic treatment during infancy, cesarean delivery, and autism. See video abstract at, http://links.lww.com/EDE/B432.
From the aDepartment of Gynaecology and Obstetrics, Nordsjaellands Hospital, University of Copenhagen, Hillerød, Denmark
bSection of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
cPsychiatric Center Copenhagen, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
dDepartment of Obstetrics and Gynaecology, Copenhagen University Hospital, Hvidovre Hospital, Hvidovre, Denmark
eDepartment of Obstetrics, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
fDepartment of Clinical Microbiology, Hvidovre Hospital, Hvidovre, Denmark.
Submitted March 14, 2018; accepted September 24, 2018.
The study was supported by grants from the Capital Region Denmark Research Fund, the Capital Region Denmark PhD-start Fund, the Nordsjælland Hospital Hillerød Research Fund, the Jascha Fund, the Tvergaard Fund, and the Gangsted Fund. The funders had no role in the design and conduct of the study, analysis, interpretation of results, writing of the manuscript, approval of the manuscript, and decision to submit the manuscript for publication. The authors are fully independent from influence by the funders.
All authors have completed the International Comittee of Medical Journal Editors (ICMJE) uniform disclosure form and declare L.V.K. has within the preceding 3 years been a consultant for Sunovion. No other financial relations with any organizations that might have an interest in the submitted work in the previous 3 years. No other relations or activities that could appear to have influenced the submitted work. The other authors have no conflicts to report.
Data and computing code: By Danish law, the authors are not permitted to share person-level data. Anyone can request access to the data, by first acquiring permission from the Danish Data Protection agency and afterward the Danish Health Authority. However, these government instances have strict requirements to be allowed access to medicinal information that most foreign identities do not live up to, and therefore, cooperation with researchers from a Danish University or a Hospital is recommended if this particular dataset is of interest. The data are located at the Statistics Denmark servers and require an application defining the persons to be in the cohort and which variables to be extracted from the national registries. Data can only be accessed through the Statistics Denmark servers. The statistical program R is available at the Statistics Denmark servers. The code is available as an Appendix; links.lww.com/EDE/B418 to this publication.
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Correspondence: Paul Bryde Axelsson, Nordsjællands Hospital, Hillerød c/o Gynækologisk-Obstetrisk Afdeling, Dr Paul Axelsson Dyrehavevej 29, 3400 Hillerød Denmark. E-mail: email@example.com.