Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.
University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Andreasstrasse 15, 8050, Zurich, Switzerland.
Int J Health Geogr. 2019 Jul 24;18(1):17. doi: 10.1186/s12942-019-0181-0.
GPS 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.
With 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.
The 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.
This 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.
全球定位系统（GPS）追踪技术在健康和老龄化研究中越来越多地被用于客观、非侵入性地评估个体的日常生活活动。然而，移动性是一个复杂的概念，基于 GPS 衍生的移动性指标来全面描述它仍然具有挑战性。
为了反映日常生活移动性所包含的各个方面的广度，我们提出了一个概念框架，根据其特征和分析属性对基于 GPS 的移动性指标进行分类，以便将其应用于健康和老龄化研究。为了展示分类框架的应用方式，我们根据提出的框架对现有研究中使用的现有移动性指标进行了分类。然后，我们基于 95 名老年人的真实生活 GPS 数据提出并计算了一组选定的移动性指标，这些指标反映了个体日常移动性的各个方面。为了探索移动性指标背后的潜在维度，我们进行了因子分析。
所提出的框架能够根据其反映的特征和分析方面对移动性指标进行概念分类。特征方面提供了移动性指标的内容信息，包含与空间、时间、运动范围和属性相关的类别。分析方面提供了关于如何根据时间尺度和统计属性对移动性指标进行聚合的信息。所提出的类别补充了现有研究，后者往往会低估涉及运动时间、时间分布和运动停止-移动分段的移动性指标。因子分析揭示了获得老年人日常生活移动性全貌所需的六个维度：生活空间范围、户外活动量、积极交通模式所花费的时间、生活空间稳定性、生活空间延伸和移动性时间。
本研究提倡在未来的健康和老龄化相关研究中纳入反映个体日常生活移动性多维性质的基于 GPS 的移动性指标。这将促进对移动性的哪些方面对健康老龄化至关重要的更好理解。
