Human Potential Centre, National Institute for Public Health and Mental Health Research, Auckland University of Technology, Auckland, New Zealand.
Int J Health Geogr. 2013 Apr 10;12:20. doi: 10.1186/1476-072X-12-20.
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.
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.
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.
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.
主动运输可以促进成年人的身体活动积累和健康改善。建成环境是积极运输行为的既定关联因素；然而，评估旅行中遇到的环境特征仍然具有挑战性。本研究的目的是检验可穿戴摄像机在客观审核和量化与工作相关的步行和自行车路线上的环境特征方面的效用。
2011 年 6 月，在新西兰招募了一批便利的成年在职人员作为研究对象。参与者在三个工作日的所有旅程中都佩戴了 SenseCam，并完成了旅行日记和人口统计调查问卷。对与工作相关的主动运输旅行的 SenseCam 图像进行编码，以确定与主动运输相关的环境特征。使用两样本比例检验和独立样本 t 检验分别确定了不同运输模式下环境特征的存在差异，以及参与者报告和 SenseCam 得出的旅行持续时间的差异。
15 名成年人参与了这项研究，从 30 次与工作相关的主动运输旅行中获得了 1749 张 SenseCam 图像进行编码。在步行和骑自行车旅行之间发现了环境特征的显著差异。由于太暗而无法确定特征，几乎四分之一的图像无法编码。受访者有低估旅行持续时间的趋势，但无统计学意义。
本研究提供了使用 SenseCam 实时捕获与积极交通相关的建筑环境数据的概念验证。需要进一步的工作来测试和完善在一系列环境、旅行行为和人群中进行编码方法。
