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Behaviour Profiles for Evidence-based Policies Against Obesity | IEEE Conference Publication | IEEE Xplore

Behaviour Profiles for Evidence-based Policies Against Obesity


Abstract:

Obesity is a preventable disease that affects the health of a significant population percentage, reduces the life expectancy and encumbers the health care systems. The ob...Show More

Abstract:

Obesity is a preventable disease that affects the health of a significant population percentage, reduces the life expectancy and encumbers the health care systems. The obesity epidemic is not caused by isolated factors, but it is the result of multiple behavioural patterns and complex interactions with the living environment. Therefore, in-depth understanding of the population behaviour is essential in order to create successful policies against obesity prevalence. To this end, the BigO system facilitates the collection, processing and modelling of behavioural data at population level to provide evidence for effective policy and interventions design. In this paper, we introduce the behaviour profiles mechanism of BigO that produces comprehensive models for the behavioural patterns of individuals, while maintaining high levels of privacy protection. We give examples for the proposed mechanism from real world data and we discuss usages for supporting various types of evidence-based policy design.
Date of Conference: 23-27 July 2019
Date Added to IEEE Xplore: 07 October 2019
ISBN Information:

ISSN Information:

PubMed ID: 31946655
Conference Location: Berlin, Germany

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