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
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:5864-5867. 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.
肥胖是一种复杂的疾病，其患病率取决于与个体当地社会经济、文化和城市环境相关的多个因素。然而，许多肥胖预防策略和政策都是横向措施，并不依赖于针对具体情况的证据。在本文中，我们概述了BigO（http://bigoprogram.eu），这是一个旨在收集儿童和青少年人群及其环境的客观行为数据的系统，以支持公共卫生当局制定有效、针对具体情况的政策和干预措施来解决儿童肥胖问题。我们概述了BigO系统的数据采集、指标提取、数据探索和分析组件，并介绍了其在四个欧洲国家的33所学校和2家诊所的初步试点应用情况，参与人数超过4200人。
