Abstract
BackgroundGPS tracking is increasingly used in health and aging research to objectively and unobtrusively assess individuals’ daily-life mobility. However, mobility is a complex concept and its thorough description based on GPS-derived mobility indicators remains challenging.MethodsWith the aim of reflecting the breadth of aspects incorporated in daily mobility, we propose a conceptual framework to classify GPS-derived mobility indicators based on their characteristic and analytical properties for application in health and aging research. In order to demonstrate how the classification framework can be applied, existing mobility indicators as used in existing studies are classified according to the proposed framework. Then, we propose and compute a set of selected mobility indicators based on real-life GPS data of 95 older adults that reflects diverse aspects of individuals’ daily mobility. To explore latent dimensions that underlie the mobility indicators, we conduct a factor analysis.ResultsThe proposed framework enables a conceptual classification of mobility indicators based on the characteristic and analytical aspects they reflect. Characteristic aspects inform about the content of the mobility indicator and comprise categories related to space, time, movement scope, and attribute. Analytical aspects inform how a mobility indicator is aggregated with respect to temporal scale and statistical property. The proposed categories complement existing studies that often underrepresent mobility indicators involving timing, temporal distributions, and stop-move segmentations of movements. The factor analysis uncovers the following six dimensions required to obtain a comprehensive view of an older adult’s daily mobility: extent of life space, quantity of out-of-home activities, time spent in active transport modes, stability of life space, elongation of life space, and timing of mobility.ConclusionThis research advocates incorporating GPS-based mobility indicators that reflect the multi-dimensional nature of individuals’ daily mobility in future health- and aging-related research. This will foster a better understanding of what aspects of mobility are key to healthy aging.
Highlights
Promoting healthy aging has become a key research endeavor by reason of increasingly aging societies around the world [1]
This paper presents a framework that allows the classification of Global Positioning System (GPS)-based mobility indicators commonly used in literature based on several characteristic and analytical aspects of mobility
The classification scheme aims to demonstrate the breadth of aspects that can be derived from GPS data and to make explicit which aspects are assessed by mobility indicators involved in health and aging studies
Summary
Promoting healthy aging has become a key research endeavor by reason of increasingly aging societies around the world [1]. Mobility has been found to be an important predictor for individuals’ health and well-being, especially for older adults [2,3,4,5,6]. Key components of healthy aging such as well-being, social participation and active living are associated with different aspects of an individual’s daily mobility [7, 8]. The number of visited locations has been shown to be associated with social network size [13]. GPS tracking is increasingly used in health and aging research to objectively and unobtrusively assess individuals’ daily-life mobility. Mobility is a complex concept and its thorough description based on GPSderived mobility indicators remains challenging
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