Public health interventions targeting violence among young adolescents should be developed in combination with alcohol education programs.

Objective: To examine risk of neonatal respiratory morbidity associated with gestational and pregestational diabetes, accounting for the prematurity-associated risk using a propensity score analysis. Study design: In a retrospective study including 222,978 singleton pregnancies, delivering at 24 0/7–41 6/7 weeks (2002–2008), we calculated a probability to deliver at term (≥ 37 weeks’ gestation). Outcomes were stratified by the probability to deliver at term (>0.8 and ≤0.8). Adjusted odds ratios (aOR) with 95% confidence intervals (95%CI) were calculated. Results: Gestational and pregestational diabetes complicated 5.1% and 1.5% of pregnancies, respectively and were associated with increased risks of neonatal respiratory morbidity compared to women without diabetes regardless of probability to deliver at term, although the risks tended to be higher with a higher probability to deliver at term: respiratory distress syndrome: aOR 1.5; 95%CI 1.3–1.7 and aOR 3.1; 95%CI 2.6–3.7; transient tachypnea of newborn aOR 1.5; 95%CI 1.3–1.6, and aOR 2.2; 95%CI 1.9–2.6; and apnea aOR 1.5; 95%CI 1.2–1.7 and aOR 3.2; 95%CI 2.6–3.9, for gestational and pregestational at term, respectively. Conclusion: Diabetes was associated with increased risk of neonatal respiratory morbidity beyond what can be attributed to prematurity. Neonatal respiratory morbidities were increased with pregestational compared with gestational diabetes.

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We read with great interest the recent article by Yeoh et al, demonstrating an altered stool microbiome composition in patients with COVID-19 compared with controls, with greater dysbiosis correlating with elevated inflammatory markers. 1 Additionally, dysbiosis was seen after disease resolution. 1 To our knowledge, gut microbiome studies in young children with COVID-19 have not been reported. Critically, the developing gut microbiome of very young children differs from adults and establishes immune and inflammatory pathways. 2 3 Moreover, children with COVID-19 can subsequently develop autoimmune and autoinflammatory diseases including Multisystem Inflammatory Syndrome in Children (MIS-C) 4 5 , which may in part be microbiome mediated, given recent findings by Yeoh et al. 1 It is difficult to study this in young children, as many with SARS-CoV-2 infection are asymptomatic and rarely tested. 6 To address this, knowing that SARS-CoV-2 can be detected in stool, 7 we used an established study collecting longitudinal stool samples from before and throughout the pandemic to investigate the prevalence and associated microbiome changes of SARS-CoV-2 in very young children. We ran the CDC 2019-Novel Coronavirus Real-Time RT-PCR Diagnostic Panel assay on 769 serial stool samples from 595 children aged 0-24 months collected from February 2020 to February 2021. The prevalence of SARS-CoV-2 in faeces was 1.7% (13 samples from 13 separate children) with prevalence at <2 days and 2, 6, 12 and 24 months of 0% (0/1), 0% (0/21), 2.6% (4/156), 2.0% (7/357) and 0.9%,(2/234), respectively. Prevalence by month is shown in online supplemental figure 1A, with the first positive sample detected 31 days before the first reported case of COVID-19 regionally. No samples were positive in controls collected prior to the pandemic in 2019 (n=97 samples from 66 individuals). Of 13 positive children, 12 were asymptomatic with no personal or family history of SARS-CoV-2 (table 1A). Of 13 children, 1 was symptomatic with COVID-19 diagnosed 21 days before stool was collected. Hispanic ethnicity

BackgroundChildhood obesity studies rely on parentally reported anthropometrics. However, the accuracy of such data has not been evaluated for 12-month-old children. Moreover, methods to improve the accuracy of reported data have not been assessed in prior studies.MethodsA total of 185 children enrolled in a northern Virginia childhood longitudinal cohort genomic study had parentally completed surveys at 12 months. Measured weights and lengths were recorded for the same children from their 12-month paediatrician visit. Weight for length percentiles were calculated using World Health Organization gender-specific growth charts. The agreement between reported and measured values was examined using Pearson's correlation, paired t-test and κ statistics. The interquartile outlier rule was used to detect and remove outliers.ResultsParentally reported weight was strongly associated with measured weight at 12 months (r=0.90). There was only a moderate correlation between parentally reported and measured lengths (r=0.52) and calculated weight for length percentiles (r=0.65). After removing outliers from parentally reported data, there was an increase in correlation between parentally reported and measured data for weight (r=0.93), length (r=0.69) and weight for length percentiles (r=0.76). Outliers removed compared to all children included were more likely to have maternal education less than a bachelor's degree (p=0.007).ConclusionsAfter removal of outliers from reported data, there is a strong correlation between calculated reported and measured weight for length percentiles suggesting that this may be an effective method to increase accuracy when conducting large-scale obesity studies in young children where study costs benefit from using parentally reported data.