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.

Latest News

Final version review paper published

25 October 2022

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.

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Paper accepted: Towards Systems Models for Obesity Prevention: A Big Role for Big Data

24 August 2022

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.

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BigO presented in course at Adolescent Health/Medicine Course

1 October 2021

The BigO project will be presented at the 14th State of the Art Adolescent Health/Medicine Course by the team from Prof.Charmandari (BRFAA).

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The BigO project on Twitter

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