Using Big Data To Help Reduce Childhood Obesity

Recently the House of Commons released a report and action plan on tackling childhood obesity.  It’s estimated that nearly 1/3 of children aged between 2 and 15 are overweight or obese in the UK, with this trend getting worse. The challenge is greatest in the most deprived areas, but policies are generally blanket ones that fail to take account of the unique local circumstances.

“Children are becoming obese at an earlier age and staying obese for longer. Obesity rates are highest for children from the most disadvantaged communities and this unacceptable health inequality has widened every year since records began. The consequences for these children are appalling and this can no longer be ignored,” the authors say.

A recent European Commission project, called the BigO, aims to utilize big data to improve the ability of government’s to effectively monitor and evaluate interventions at a local level.  The project will consist of a big data platform that aims to allow the quantification of behavioral community patterns via data generated from a range of wearable and eHealth devices.

Community data

The project aims to work with over 25,000 obese children and adolescents, with models trained on the data to provide the team with a means of gauging the likely success of any policy interventions based upon the make up of the local community.  It will also allow real-time monitoring of the communities after each intervention, with powerful visualizations allowing for ease of understanding.

The team hope that the project will fundamentally change how obesity policies are designed and implemented across Europe by providing health authorities with a better way of evaluating their local communities based upon the obesity prevalence risk score.  This in turn will facilitate evidence-based policy making.

The project consists of a wide range of stakeholders, including research institutes, universities and industry experts from Greece, Ireland, The Netherlands, Spain and Sweden.

It’s a nice example of the possibilities when health data is collected on a population level, and it will be fascinating to watch the impact it has on policy making across Europe.

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