ESPE2021 ePoster Category 1 Fat, Metabolism and Obesity B (10 abstracts)
Evaluation of the BigO behavioral indicators in overweight and obese children and adolescents
Penio Kassari 1,2 , Athanasia Tragomalou 1,2 , Aikaterini Vourdoumpa 1,2 , Diamanto Koutaki 1,2 , Marina Papadopoulou 1,2 , Maria Manou 1,2 , Ioannis Ioakeimidis 3 , Konstantinos Filis 4 , Eleni Theodoropoulou 4 , Giorgos Lymperopoulos 4 , Daniel Ferri 5 , Youla Karavidopoulou 6 , Leandros Stefanopoulos 6 , Ioannis Sarafis 7 , Christos Diou 7 , Eirini Lekka 6 , Nicos Maglaveras 6 , Anastasios Delopoulos 7 & Evangelia Charmandari 1,2
1Division of Endocrinology and Metabolism, Center of Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece; 2Out-patient Clinic for the Prevention and Management of Overweight and Obesity, Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, National and Kapodistrian University of Athens Medical School, “Aghia Sophia” Children’s Hospital, Athens, Greece; 3Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden; 4Cosmote Mobile Telecommunications SA, Athens, Greece; 5MySphera, Valencia, Spain; 6Department of Medicine, Lab of Computing Medical Informatics and Biomedical Imaging Technologies, Aristotle University of Thessaloniki Medical School, Thessaloniki, Greece; 7Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Thessaloniki, Greece
Background: Obesity represents one of the most challenging public health problems of our century. According to the World Health Organization, there is a need to create reliable monitoring and behavioral systems, and to investigate their effectiveness in preventing childhood obesity.
Objective: To evaluate the BigO behavioral indicators in a pediatric population in Greece.
Methodology: The study was carried out as part of the four-year European BigO project (http://bigoprogram.eu, Horizon2020, No. 727688). Overweight and obese children and adolescents aged 9-18 years participated in the study following approval by the local Committee on the Ethics of Human Research. Written informed consent was obtained by parents/guardians in all cases. The data collection system included the BigO technology platform, which interfaces with a Smartphone and Smartwatch, and records data objectively (using inertial sensors and GPS) for each patient. Participants used the BigO system for at least 4 weeks. Data were then transmitted to BigO servers to extract behavioral indicators, including: (a) physical activity/exercise and (b) dietary habits. Behavioral indicators included: average steps per hour daily, average activity counts per hour daily, average food visits daily, average public park visits daily, average fast food (take away) visits daily, average supermarket (grocery stores) visits daily, average athletic sports visits daily, average food outlets visits daily, average cafe visits daily, average bars visits daily and average food cafe bar visits daily. For the correlation analysis, data with zero values have been omitted.
Results: The study population consisted of 867 children and adolescents (448 males, 419 females; mean age ± SD: 12.645 ± 2.445). Subjects were classified as having obesity (n = 644, 74.3%), overweight (n = 203, 23.4%) or normal BMI (n = 20, 2.3%) according to WHO cut-off points. In subjects with obesity, BMI correlated positively with average steps per hour daily (rho = 0.102, P = 0.010), average activity counts per hour daily (rho = 0.117, P = 0.003), average food visits daily (rho = 0.221, P = 0.001), as well as average daily visits to fast food (take away) places (rho = 0.262, P = 0.001), food outlets (rho = 0.274, P < 0.001), café shops (rho = 0.288, P < 0.001), and food cafe bars (rho = 0.154, P = 0.007). In overweight subjects, BMI correlated positively with average athletic sports visits daily (rho = 0.287, P = 0.041).
Conclusions: These novel methodologies will enable scientists and public health authorities to collect and analyze objective daily behavioral data in children and adolescents with overweight and obesity, and implement appropriate public health policies and/or strategies at a local level.
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