Abstract
BackgroundThe existing smartphones’ technology allows for the objective measurement of a person’s movements at a fine-grained level of geographic and temporal detail, and in doing so, it mitigates the issues associated with self-report biases and lack of spatial details. This study proposes and evaluates the advantages of using a smartphone app for collecting accurate, fine-grained, and objective data on people’s transport-related walking.MethodsA sample of 142 participants (mostly young adults) was recruited in a large Australian university, for whom the app recorded all their travel activities over two weekdays during August–September 2014. We identified eight main activity nodes which operate as transport-related walking generators. We explored the participants’ transport-related walking patterns around and between these activity nodes through the use of di-graphs to better understand patterns of incidental physical activity and opportunities for intervention to increase incidental walking.ResultsWe found that the educational node — in other samples may be represented by the workplace — is as important as the residential node for generating walking trips. We also found that the likelihood of transport-related walking trips is larger during the daytime, whereas at night time walking trips tend to be longer. We also showed that patterns of transport-related walking relate to the presence of ‘chaining’ trips in the afternoon period.ConclusionsThe findings of this study show how the proposed data collection and analytic approach can inform urban design to enhance walkability at locations that are likely to generate walking trips. This study’s insights can help to shape public education and awareness campaigns that aim to encourage walking trips throughout the day by suggesting locations and times of the day when engaging in these forms of exercise is easiest and least intrusive.
Highlights
The existing smartphones’ technology allows for the objective measurement of a person’s movements at a fine-grained level of geographic and temporal detail, and in doing so, it mitigates the issues associated with self-report biases and lack of spatial details
Incidental physical activity — PA accumulated through normal daily activities un-associated with exercise goals, such as Assemi et al BMC Public Health (2020) 20:244 walking for transport purposes — is attracting the attention of researchers and policy makers as a means to improve the overall health status in communities [15, 16]
We study transport-related walking trips between these activity nodes at five different time-slots throughout the day, using di-graphs, to reveal potential time-specific patterns
Summary
The existing smartphones’ technology allows for the objective measurement of a person’s movements at a fine-grained level of geographic and temporal detail, and in doing so, it mitigates the issues associated with self-report biases and lack of spatial details. This study proposes and evaluates the advantages of using a smartphone app for collecting accurate, fine-grained, and objective data on people’s transport-related walking. The literature suggests that even small increases in PA can improve people’s health status [13, 14]. Incidental physical activity — PA accumulated through normal daily activities un-associated with exercise goals, such as Assemi et al BMC Public Health (2020) 20:244 walking for transport purposes — is attracting the attention of researchers and policy makers as a means to improve the overall health status in communities [15, 16]. Research has shown that increasing PA for transport (i.e., active travel), positively contributes to people’s health and happiness [14, 15, 17, 18]. Active travel constitutes any kind of travel between places through walking, cycling or other non-motorised modes of transport [15]
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