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

First scientific paper from citizen science project @school

8 January 2020

Students from IEGS helped researchers to identify food advertisements in neighborhoods in Stockholm as citizen scientists. All advertisements in two areas of Stockholm (Skärholmen and Östermalm) were captured by the use of the BigO mobile phone technology. The data collection was done together with students and teachers from Internationella Engelska Gymnasieskolan Södermalm (IEGS). Petter Fagerberg, who is doing his Ph.D. work in the context of the BigO project explains his work that is now published in a highly ranked scientific journal. This is the first scientific paper that is based on data collected in a citizen scientist project at a participating @school.

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BigO presented at MobiHealth 2019

10 December 2019

Leandros Stefanopoulos from the Aristotle University of Thessaloniki presented his newest paper about BigO at the MobiHealth Coference. This International Conference on Wireless Mobile Communication and Healthcare took place on November 14 and 15 in Dublin.

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Greek primary school students wear smartwatches for BigO

6 December 2019

4th grade primary school students from the Ellinogermaniki Agogi school in Athens participate in the BigO project. The students wear smartwatches that record their physical activity and sleep duration. At the same time students record their meals for two weeks on specially formatted log sheets and take pictures of them. After collecting all the data, they are discussed in class.

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