BigO: A public health decision support system for measuring obesogenic behaviors of children in relation to their local environment

• Published in: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) pp. 5864 - 5867
• Main Authors: Diou, Christos, Sarafis, Ioannis, Papapanagiotou, Vasileios, Alagialoglou, Leonidas, Lekka, Irini, Filos, Dimitrios, Stefanopoulos, Leandros, Kilintzis, Vasileios, Maramis, Christos, Karavidopoulou, Youla, Maglaveras, Nikos, Ioakimidis, Ioannis, Charmandari, Evangelia, Kassari, Penio, Tragomalou, Athanasia, Mars, Monica, Ngoc Nguyen, Thien-An, Kechadi, Tahar, O'Donnell, Shane, Doyle, Gerardine, Browne, Sarah, O'Malley, Grace, Heimeier, Rachel, Riviou, Katerina, Koukoula, Evangelia, Filis, Konstantinos, Hassapidou, Maria, Pagkalos, Ioannis, Ferri, Daniel, Perez, Isabel, Delopoulos, Anastasios
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2020
• ISSN: 1558-4615
• DOI: 10.1109/EMBC44109.2020.9175361

Obesity is a complex disease and its prevalence depends on multiple factors related to the local socioeconomic, cultural and urban context of individuals. Many obesity prevention strategies and policies, however, are horizontal measures that do not depend on context-specific evidence. In this paper we present an overview of BigO (http://bigoprogram.eu), a system designed to collect objective behavioral data from children and adolescent populations as well as their environment in order to support public health authorities in formulating effective, context-specific policies and interventions addressing childhood obesity. We present an overview of the data acquisition, indicator extraction, data exploration and analysis components of the BigO system, as well as an account of its preliminary pilot application in 33 schools and 2 clinics in four European countries, involving over 4,200 participants.