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Exploring Associations Between Children’s Obesogenic Behaviors and the Local Environment Using Big Data: Development and Evaluation of the Obesity Prevention Dashboard

Exploring Associations Between Children’s Obesogenic Behaviors and the Local Environment Using Big Data: Development and Evaluation of the Obesity Prevention Dashboard

Per Diou et al [20], personal sensory data, such as GPS and accelerometry, were used to extract individual indicators. The aggregated behaviors were calculated either based on the unique individuals visiting a geohash, or based on all values across the visits, even if they are visits from the same individual, while various geohash sizes are supported through the OPdashboard. Furthermore, aggregations are also performed based on the individuals living in a geohash.

Dimitris Filos, Irini Lekka, Vasileios Kilintzis, Leandros Stefanopoulos, Youla Karavidopoulou, Christos Maramis, Christos Diou, Ioannis Sarafis, Vasileios Papapanagiotou, Leonidas Alagialoglou, Ioannis Ioakeimidis, Maria Hassapidou, Evangelia Charmandari, Rachel Heimeier, Grace O'Malley, Shane O’Donnell, Gerardine Doyle, Anastasios Delopoulos, Nicos Maglaveras

JMIR Mhealth Uhealth 2021;9(7):e26290