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Background Overweight and obesity during childhood consist two of the most important public health issues in the 21st century. Consumption of high-fat processed food has been increased alarmingly. Objective To examine the association between parental ultra-processed, high-fat products’ consumption and childhood overweight/obesity. Methods A cross-sectional survey, conducted among 422 children, aged 10–12 years, and their parents, during school years 2014–16. Parental and child data were collected through self-administered, anonymous and validated questionnaires. Among others, high-fat ultra-processed food consumption was also recorded. Children’s weight status was based on gender- and age-specific tables derived from the International Obesity Task Force body mass index (BMI) cut-offs. Results The prevalence of obesity in the reference population was 2.9%, whereas the prevalence of overweight was 19.3%. A strong correlation was observed between children’s and their parents’ BMI status (P < 0.001). Multi-adjusted data analysis revealed no association between parental intake of ultra-processed, high-fat products and children overweight/obesity. Similarly, when the data analysis accounted for family income and physical activity status of the children, the aforementioned results remained insignificant. Conclusion Despite the fact that parents’ specific dietary habits seem not to affect their children’s weight status, public health programs should consider parental nutrition education and mobilization as a preventive measure for childhood overweight/obesity.

Increasing user engagement is one of the biggest challenges when a new application is developed. An engaged user is one who finds a product valuable; highly engaged users generate profit. This study focuses on increasing user engagement in a transport application, via a user reputation score feature. The score is to reward application users and activity organisers, as well as to motivate beginners by offering a high reputation score in the first days of use. The algorithms are based on exponential and logarithmic functions, and were first tested on synthetic data. Real-world tests have shown that the algorithms behave as expected, but the COVID-19 pandemic created a disturbance which prevented any user from achieving the maximum score and many users from registering altogether. Data show positive results, although the real number of users is not sufficient to certify a correct behaviour. Further tests will be carried out when transport activities return to normal.