148 - Neonatal antibiotic exposure and the risk of early childhood obesity among South Bronx Pediatric population
Sunday, April 24, 2022
3:30 PM – 6:00 PM US MT
Poster Number: 148
Adeola O. Awujoola, Bronxcare Health System - - Bronx, NY, Bronx, NY, United States; Ana Patricia Torga, BronxCare Health System, New York, NY, United States; Mohamed Aashiq Abdul Ghayum, Bronxcare Health System, Bronx, NY, United States; Nadeem A. Mousa, BronxCare Health System, Bronx, NY, United States; Tolulope O. Olorunsogo, BronxCare Health System, Pediatrics Department, Bronx, NY, United States; Samantha DeSilva, BronxCare Health System, Thornhill, ON, Canada; Pratibha Ankola, BBronx Care Health System, Affiliated with Icahn School of Medicine at Mount Sinai, Scarsdale, NY, United States
Resident Bronxcare Health System - - Bronx, NY Bronx, New York, United States
Background: Currently, 1 in 3 children in the United States is diagnosed to be overweight or obese. The intestinal microbiome has been linked with the development of early-onset obesity. Alteration of gut microbiome through antibiotic exposure has been implicated in weight gain in animal models. Research of similar effects in humans remained inconclusive, and studies during the critical neonatal period are sparse.
Objective: To assess the association between neonatal antibiotic exposure and the risk of childhood obesity and to evaluate for the differences in effect based on the duration of exposure.
Design/Methods: This retrospective cohort study entailed chart review for neonates born between 2011 to 2015 and followed up until 5 years old in our hospital. Body Mass Index (BMI) percentile at 5 years, and other child and maternal characteristics were compared between the antibiotic-exposed and unexposed neonates. Premature infants ( < 33 weeks), and those with congenital syndromes affecting growth were excluded from the study. Chi-square test was conducted on categorical variables and student’s T-test for normally distributed continuous variable. Significant variables (p < 0.05) in bivariate analysis were modelled in a stepwise multivariate logistic regression analysis to ascertain independent predictors of obesity at 5 years.
Results: Of the 1447 subjects, 749 (52%) received ampicillin and gentamicin, and 333 (23%) were obese. Male-female distribution was similar. Neonates exposed to antibiotics were more likely to be obese compared to unexposed (26% versus 20%, p=0.0103) Table 1. Following adjustment for Early feeding practices, childhood atopy, birthweight, and maternal hypertension, diabetes, obesity, and ethnicity, this association persisted (aOR: 1.368, 95% C.I 1.055 - 1.775) (Table 2, Figure 1). There is no significant difference in weight outcome among children who received antibiotics for ≤48hours and >48hours (22.67% versus 25.28%, p=0.2389).Conclusion(s): Neonatal antibiotic exposure is independently associated with early childhood obesity. Antibiotic exposure may play a significant role in the weight trajectories of these children, hence antibiotic stewardship in this period cannot be over-emphasized, especially so in our vulnerable population in the Bronx. Given the high incidence of childhood obesity among our cohort (23%) compared to the national average of 13.4% among 2-5 years, augmenting current effort at reducing traditional obesity risk factors with judicious antibiotic use will reduce the prevalence of childhood obesity and the attendant cardiovascular comorbidity. My CVAwujoola Adeola CV-converted.pdf Factors independently associated with childhood obesity <img src=https://www.abstractscorecard.com/uploads/Tasks/upload/16020/FGOVBGGC-1176445-2-IMG.png width=440 hheight=245.490196078431 border=0 style=border-style: none;>Factors independently associated with childhood obesity. The multivariate analysis result is presented. aOR >1 denotes factors that are associated with increased risk of obesity at age 5, while aOR < 1 denotes factors that are associated with decreased risk of obesity at age 5. Hosmer Lemmeshow test (P= 0.7431), which indicates that our model fits the data. Statistical significance was set at (P < 0.05) with a 95% confidence interval that excludes null value of 1.