Abstract

Researchers broadly represented the built environment (BE) using geographic and topological indicators. Despite studies have shown that the geographic BE affects children independent mobility (CIM), little is known about the effects of topological BE on CIM. Less so, how the effects vary between discretionary and nondiscretionary CIM trips. The study addresses these gaps using self-reported two-day mobility data of 151 children aged 10–14 years from Dhaka, Bangladesh. Geographic BE data (e.g. land uses, street width, building height) were collected through a virtual BE audit following each route. Topological BE data (e.g. step-depth, integration, choice) were derived in Depthmap X. CIM was measured in a binary scale by checking whether the reported trips were taken independently or not. Three binary logistic regression models (an overall model, a discretionary trip model, and a nondiscretionary trip model) were estimated to determine the effects of geographic and topological BE on CIM, controlling for other confounding effects. The findings demonstrate that both geographic and topological BE affect CIM. However, they affect discretionary and non-discretionary CIM differently – e.g. step-depth, angular connectivity and presence of institutional land use affect only non-discretionary CIM, whereas integration, recreational land use and traffic composition affect only discretionary CIM. The findings highlight that geographical features need to be considered in tandem with topological features of the BE, stratified by destination types, to maximise CIM.

Full Text
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