BACKGROUND: Active transport can contribute to physical activity accumulation and improved health in adults. The built environment is an established associate of active transport behaviours; however, assessment of environmental features encountered during journeys remains challenging. The purpose of this study was to examine the utility of wearable cameras to objectively audit and quantify environmental features along work-related walking and cycling routes. METHODS: A convenience sample of employed adults was recruited in New Zealand, in June 2011. Participants wore a SenseCam for all journeys over three weekdays and completed travel diaries and demographic questionnaires. SenseCam images for work-related active transport journeys were coded for presence of environmental features hypothesised to be related to active transport. Differences in presence of features by transport mode and in participant-reported and SenseCam-derived journey duration were determined using two-sample tests of proportion and an independent samples t-test, respectively. RESULTS: Fifteen adults participated in the study, yielding 1749 SenseCam images from 30 work-related active transport journeys for coding. Significant differences in presence of features were found between walking and cycling journeys. Almost a quarter of images were uncodeable due to being too dark to determine features. There was a non-significant tendency for respondents to under-report their journey duration. CONCLUSION: This study provides proof of concept for the use of the SenseCam to capture built environment data in real time that may be related to active transportation. Further work is required to test and refine coding methodologies across a range of settings, travel behaviours, and demographic groups.
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