Background/Objectives There is a concern that measures aiming to limit a further spread of COVID-19, e.g., school closures and social distancing, cause an aggravation of the childhood obesity epidemic. Therefore, we compared BMI trends during the 15 years before and during the COVID-19 pandemic. Subjects/Methods To assess the change in weight dynamics during the first months of COVID-19, we compared the trends of 3-month change in BMI-SDS (ΔBMI-SDS) and the proportions of children showing a high positive (HPC) or high negative (HNC) weight change between 2005 and 2019 and the respective changes from 2019 (pre-pandemic) to 2020 (after the onset of anti-pandemic measures) in more than 150,000 children (9689 during the pandemic period). The period of 3 months corresponds approximately to the first lockdown period in Germany. Results During the COVID-19 pandemic, we found a substantial weight gain across all weight and age groups, reflected by an increase in the 3-month change in BMI-SDS (β = 0.05, p < 0.001), an increase in the proportion of children showing HPC (OR = 1.4, p < 0.001), and a decrease in the proportion of children showing HNC (OR = 0.7, p < 0.001). Besides, we found the same trends since 2005 on a low but stable level with a yearly increase of ΔBMI-SDS by β = 0.001 (p < 0.001), the odds of HPC increased by ORhigh_pos = 1.01 (p < 0.001), and the odds of HNC decreased by ORhigh_neg = 0.99 (p < 0.001). These rather small effects accumulated to β = 0.02, ORhigh_pos = 1.14, and ORhigh_pos = 0.85 over the whole period 2005–2019. Alarmingly, both the long-term and the short-term effects were most pronounced in the obese subgroup. Conclusions There are positive dynamics in different measures of weight change, indicating a positive trend in weight gain patterns, especially within the group of children with obesity. These dynamics are likely to be escalated by COVID-19-related measures. Thus, they may lead to a significant further aggravation of the childhood obesity pandemic.

Early diagnosed, treated, and continuously monitored patients with PKU showed reduced height from birth onward. During the last 2 decades, this phenomenon attenuated, probably because of advances in PKU therapy related to protein supplements and special low-protein foods.

We observed a further stabilization of overweight and obesity prevalence rates for all age groups and even a decrease in the rates for the younger ages (4-7·99 years, 8-11·99 years). As other industrialized countries have also reported similar trends, it seems that the epidemic of childhood overweight and obesity is reaching a turning point in the industrial part of the world.

Objective The COVID-19 pandemic and the measures implemented to stop the pandemic had a broad impact on our daily lives. Besides work and social life, health care is affected on many levels. In particular, there is concern that attendance in health care programs will drop or hospital admissions will be delayed due to COVID-19-related anxieties, especially in children. Therefore, we compared the number of weekly visits to 78 German pediatric institutions between 2019 and 2020. Results We found no significant differences during the first 10 weeks of the year. However, and importantly, from April, the weekly number of visits was more than 35% lower in 2020 than in 2019 (p = 0.005). In conclusion, the COVID-19 pandemic seems to relate to families´ utilization of outpatient well-child clinics and pediatric practice attendance in Germany.

Sharing data is of great importance for research in medical sciences. It is the basis for reproducibility and reuse of already generated outcomes in new projects and in new contexts. FAIR data principles are the basics for sharing data. The Leipzig Health Atlas (LHA) platform follows these principles and provides data, describing metadata, and models that have been implemented in novel software tools and are available as demonstrators. LHA reuses and extends three different major components that have been previously developed by other projects. The SEEK management platform is the foundation providing a repository for archiving, presenting and secure sharing a wide range of publication results, such as published reports, (bio)medical data as well as interactive models and tools. The LHA Data Portal manages study metadata and data allowing to search for data of interest. Finally, PhenoMan is an ontological framework for phenotype modelling. This paper describes the interrelation of these three components. In particular, we use the PhenoMan to, firstly, model and represent phenotypes within the LHA platform. Then, secondly, the ontological phenotype representation can be used to generate search queries that are executed by the LHA Data Portal. The PhenoMan generates the queries in a novel domain specific query language (SDQL), which is specific for data management systems based on CDISC ODM standard, such as the LHA Data Portal. Our approach was successfully applied to represent phenotypes in the Leipzig Health Atlas with the possibility to execute corresponding queries within the LHA Data Portal.