Big data against childhood Obesity
Children and adolescents with obesity have a higher risk of developing various diseases later on, compared to children without obesity. The reasons why some children become obese are complex, and behaviour, the living environment, and public health policies all play a role. BigO collects and analyses anonymous data on children's behavioural patterns and their living environment. With advanced analytics BigO extracts data-driven evidence on which local factors are involved, and how these factors influence childhood obesity in Europe.
With this information BigO will be able to advice clinics and public health authorities on how to develop and plan effective programs and policies in an attempt to reduce childhood obesity.
Our last news item already described our newest paper: Toward Systems Models for Obesity Prevention: A Big Role for Big Data.
The final version of the review paper is now published in Current Developments in Nutrition.
Just before the summer holidays, we received the news that our opinion paper was accepted by the scientific journal “current developments in nutrition”. With this paper, we contribute to the academic discussion on system models and the use of Big Data in obesity prevention.Read more >
The BigO project will be presented at the 14th State of the Art Adolescent Health/Medicine Course by the team from Prof.Charmandari (BRFAA).Read more >