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OBJECTIVE: This study aimed to assess the association between neonatal antibiotic exposure and the risk of childhood obesity. STUDY DESIGN: This retrospective cohort study enrolled neonates born between 2011 and 2015 and followed up until 5 years. The incidence of obesity at 5 years old, and other characteristics were compared between the antibiotic-exposed and unexposed groups. 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 1,447 subjects, 749 (51.8%) received ampicillin and gentamicin, and 333 (23%) were obese. Neonates exposed to antibiotics were more likely to be obese compared with those unexposed (26 vs. 20%, p = 0.01). In the adjusted model, this association persisted (adjusted odds ratio: 1.37, p = 0.02). CONCLUSION: Neonatal antibiotic exposure is associated with early childhood obesity and may play a significant role in the weight trajectories of these children. Hence, antibiotic stewardship in this period cannot be overemphasized. KEY POINTS: · Findings from our study showed that neonatal antibiotic exposure is associated with early childhood obesity.. · The prevalence of childhood obesity at 5 years is high (23%).. · Further exploration of the role of antibiotics on the gut microbiome and its effect on weight trajectories is needed..
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Colombia announced the first case of severe acute respiratory syndrome coronavirus 2 on March 6, 2020. Since then, the country has reported a total of 5,002,387 cases and 127,258 deaths as of October 31, 2021. The aggressive transmission dynamics of SARS-CoV-2 motivate an investigation of COVID-19 at the national and regional levels in Colombia. We utilize the case incidence and mortality data to estimate the transmission potential and generate short-term forecasts of the COVID-19 pandemic to inform the public health policies using previously validated mathematical models. The analysis is augmented by the examination of geographic heterogeneity of COVID-19 at the departmental level along with the investigation of mobility and social media trends. Overall, the national and regional reproduction numbers show sustained disease transmission during the early phase of the pandemic, exhibiting sub-exponential growth dynamics. Whereas the most recent estimates of reproduction number indicate disease containment, with Rt<1.0 as of October 31, 2021. On the forecasting front, the sub-epidemic model performs best at capturing the 30-day ahead COVID-19 trajectory compared to the Richards and generalized logistic growth model. Nevertheless, the spatial variability in the incidence rate patterns across different departments can be grouped into four distinct clusters. As the case incidence surged in July 2020, an increase in mobility patterns was also observed. On the contrary, a spike in the number of tweets indicating the stay-at-home orders was observed in November 2020 when the case incidence had already plateaued, indicating the pandemic fatigue in the country.