Childhood obesity constitutes a major risk factor for future adverse health conditions. Multicomponent parent–child interventions are considered effective in controlling weight. Τhe ENDORSE platform utilizes m-health technologies, Artificial Intelligence (AI), and serious games (SG) toward the creation of an innovative software ecosystem connecting healthcare professionals, children, and their parents in order to deliver coordinated services to combat childhood obesity. It consists of activity trackers, a mobile SG for children, and mobile apps for parents and healthcare professionals. The heterogeneous dataset gathered through the interaction of the end-users with the platform composes the unique user profile. Part of it feeds an AI-based model that enables personalized messages. A feasibility pilot trial was conducted involving 50 overweight and obese children (mean age 10.5 years, 52% girls, 58% pubertal, median baseline BMI z-score 2.85) in a 3-month intervention. Adherence was measured by means of frequency of usage based on the data records. Overall, a clinically and statistically significant BMI z-score reduction was achieved (mean BMI z-score reduction −0.21 ± 0.26, p-value < 0.001). A statistically significant correlation was revealed between the level of activity tracker usage and the improvement of BMI z-score (−0.355, p = 0.017), highlighting the potential of the ENDORSE platform.

Childhood obesity is a serious public health problem worldwide. The ENDORSE platform is an innovative software ecosystem based on Artificial Intelligence which consists of mobile applications for parents and health professionals, activity trackers, and mobile games for children. This study explores the impact of the ENDORSE platform on metabolic parameters associated with pediatric obesity and on the food parenting practices of the participating mothers. Therefore, the metabolic parameters of the 45 children (mean age: 10.42 years, 53% girls, 58% pubertal, mean baseline BMI z-score 2.83) who completed the ENDORSE study were evaluated. The Comprehensive Feeding Practices Questionnaire was used for the assessment of food parenting practices. Furthermore, regression analysis was used to investigate possible associations between BMI z-score changes and changes in metabolic parameters and food parenting practices. Overall, there was a statistically significant reduction in glycated hemoglobin (mean change = −0.10, p = 0.013), SGOT (mean change = −1.84, p = 0.011), and SGPT (mean change = −2.95, p = 0.022). Emotional feeding/food as reward decreased (mean change −0.21, p = 0.007) and healthy eating guidance increased (mean change = 0.11, p = 0.051). Linear regression analysis revealed that BMI z-score change had a robust and significant correlation with important metabolic parameters: HOMA-IR change (beta coefficient = 3.60, p-value = 0.046), SGPT change (beta coefficient = 11.90, p-value = 0.037), and cortisol change (beta coefficient = 9.96, p-value = 0.008). Furthermore, healthy eating guidance change had a robust negative relationship with BMI z-score change (beta coefficient = −0.29, p-value = 0.007). Conclusions: The Endorse digital weight management program improved several metabolic parameters and food parenting practices.

Childhood obesity has been linked to physical and psychological comorbidities that can be carried into adulthood. A bidirectional link between body weight and the stress system appears to exist, as cortisol may affect the regulation of appetite, while adiposity can affect cortisol secretion. Among the biological tissues used to evaluate cortisol concentrations, scalp hair can provide retrospective measures. The aim of this systematic review was to investigate the difference in hair cortisol concentrations between obese and non-obese minors ≤ 19 years of age. Children and adolescents with genetic, somatic or psychiatric comorbidities were excluded. The work was conducted following the PRISMA guidelines, using prespecified search terms in the Pubmed database. The initial search yielded 56 studies, while the last step of the screening procedure concluded in 9 observational studies. Among them, the results could be characterized as inconclusive. Five of them demonstrated significantly higher hair cortisol concentrations in obese children and adolescents than normal weight subjects. On the contrary, the remaining four found no statistically significant differences in hair cortisol concentrations between obese and non-obese subjects. Different methodologies applied, and confounding factors could explain the inconsistency in the findings. Further research is needed to provide more solid results.

The aim of the current study was to investigate the tear proteome in children and adolescents with type 1 diabetes (T1D) compared to healthy controls, and to identify differences in the tear proteome of children with T1D depending on different characteristics of the disease. Fifty-six children with T1D at least one year after diagnosis, aged 6–17 years old, and fifty-six healthy age- and sex-matched controls were enrolled in this cross-sectional study. The proteomic analysis was based on liquid chromatography tandem mass spectrometry (LC-MS/MS) enabling the identification and quantification of the protein content via Data-Independent Acquisition by Neural Networks (DIA-NN). Data are available via ProteomeXchange with the identifier PXD052994. In total, 3302 proteins were identified from tear samples. Two hundred thirty-nine tear proteins were differentially expressed in children with T1D compared to healthy controls. Most of them were involved in the immune response, tissue homeostasis and inflammation. The presence of diabetic ketoacidosis at diagnosis and the level of glycemic control of children with T1D influenced the tear proteome. Tear proteomics analysis revealed a different proteome pattern in children with T1D compared to healthy controls offering insights on deregulated biological processes underlying the pathogenesis of T1D. Differences within the T1D group could unravel biomarkers for early detection of long-term complications of T1D.

Childhood obesity is a complex disease with multiple biological and psychosocial risk factors. Recently, novel digital programs were developed with growing evidence for their effectiveness in pediatric weight management studies. The ENDORSE platform consists of mobile applications, wearables, and serious games for the remote management of childhood obesity. The pilot studies included 50 mothers and their children aged 6–14 years and resulted in a clinically significant BMI z-score reduction over 4 to 5 months. This secondary analysis of the ENDORSE study focuses on parenting styles and psychosocial factors. Methodology: Semi-structured clinical interviews were conducted with all participating mothers pre-and post-intervention. The Parenting Styles and Dimensions Questionnaire (PSDQ) evaluated the mothers’ parenting styles. The psychosocial functioning of the participating children was assessed with the parental version of the Strengths and Difficulties Questionnaire (SDQ). The relationship between parenting styles, psychosocial parameters, and weight outcomes was investigated using a linear regression analysis. Results: Weight-related stigma at school (56%), body image concerns (66%), and difficulties in family relationships (48%) were the main concerns documented during the initial psychological interviews. According to the SDQ, there was a significant decrease in children’s conduct problems during the study’s initial phase (pre-pilot group). A decrease in maternal demandingness (i.e., strict parenting style) was associated with a decrease in BMI z-score (beta coefficient = 0.314, p-value = 0.003). Conclusion: Decreasing parental demandingness was associated with better weight outcomes, highlighting the importance of assessing parenting factors in pediatric weight management programs.