Tribby Calvin P, Miller Harvey J, Brown Barbara B, Smith Ken R, Werner Carol M
Department of Geography, The Ohio State University, 1036 Derby Hall/154 North Oval Mall, Columbus, OH 43210, USA; Center for Urban and Regional Analysis, The Ohio State University, United States.
Department of Family and Consumer Studies, University of Utah, United States.
Health Place. 2017 May;45:1-9. doi: 10.1016/j.healthplace.2017.02.004. Epub 2017 Feb 24.
There is growing international evidence that supportive built environments encourage active travel such as walking. An unsettled question is the role of geographic regions for analyzing the relationship between the built environment and active travel. This paper examines the geographic region question by assessing walking trip models that use two different regions: walking activity spaces and self-defined neighborhoods. We also use two types of built environment metrics, perceived and audit data, and two types of study design, cross-sectional and longitudinal, to assess these regions. We find that the built environment associations with walking are dependent on the type of metric and the type of model. Audit measures summarized within walking activity spaces better explain walking trips compared to audit measures within self-defined neighborhoods. Perceived measures summarized within self-defined neighborhoods have mixed results. Finally, results differ based on study design. This suggests that results may not be comparable among different regions, metrics and designs; researchers need to consider carefully these choices when assessing active travel correlates.
越来越多的国际证据表明,有利的建成环境会鼓励诸如步行之类的主动出行。一个尚未解决的问题是地理区域在分析建成环境与主动出行之间关系时所起的作用。本文通过评估使用两种不同区域的步行出行模型来探讨地理区域问题:步行活动空间和自我定义的社区。我们还使用两种类型的建成环境指标(感知数据和实地调查数据)以及两种研究设计(横断面研究和纵向研究)来评估这些区域。我们发现,建成环境与步行之间的关联取决于指标类型和模型类型。与自我定义社区内的实地调查指标相比,步行活动空间内汇总的实地调查指标能更好地解释步行出行情况。自我定义社区内汇总的感知指标结果不一。最后,结果因研究设计而异。这表明不同区域、指标和设计之间的结果可能不可比;研究人员在评估主动出行的相关因素时需要仔细考虑这些选择。