Effect of In-Utero Antibiotic Exposure on Childhood Outcomes: Methods and Baseline Data of the Fetal Antibiotic EXposure (FAX) Cohort Study.

Abstract

BackgroundThe widespread use of antepartum and intrapartum antibiotics has raised concerns about the possible disruption of the child’s gut microbiota and effects on the maturation from the infant to the adult microbiome. The Fetal Antibiotic EXposure (FAX) study provides a cohort to examine the association between in-utero exposure to antibiotics and adverse childhood outcomes including body weight, atopic diseases, and autism spectrum disorders and to investigate the role of other potential factors mitigating or moderating the risk for adverse outcomes.ObjectiveThe aim of this paper was to describe the methods, cohort characteristics, and retention of infants included in the study cohort.MethodsFor this retrospective cohort study, we included children born in Kaiser Permanente Southern California (KPSC) hospitals between January 1, 2007, and December 31, 2015, within 22 to 44 completed weeks of gestation with KPSC insurance coverage during the first year of life. Follow-up data collection was performed through electronic medical records.ResultsThe study cohort was comprised 223,431 children of which 65.7% (146,720/223,431) were exposed to antibiotics in-utero: 19.0% (42,511/223,431) were exposed during the antepartum period, 30.0% (66,896/223,431) during the intrapartum period, and 16.7% (37,313/223,431) exposed during both the antepartum and intrapartum periods.During their first year of life, children had a median of 5 weight and height measurements; the frequency of weight and height measurements declined to a median of 3 in their second year of life and 2 for 3 to 5 years of age. The 5-year retention of children in the health plan was over 80% with the highest retention for Hispanic children.ConclusionsThis cohort of children will provide a unique opportunity to address key questions regarding the long-term sequelae of in-utero exposure to antibiotics using real-world data. The high retention and multiple medical visits over time allow us to model the trajectories of body mass index over time.International Registered Report Identifier (IRRID)DERR1-10.2196/12065