Urban Health Collaborative, Dornsife School of Public Health, Drexel University, 3600 Market St. 7th Floor, Philadelphia, PA, 19104, USA.
Urban Health Collaborative, Dornsife School of Public Health, Drexel University, 3600 Market St. 7th Floor, Philadelphia, PA, 19104, USA; Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Nesbitt Hall, 3215 Market St., Philadelphia, PA, 19104, USA.
Health Place. 2022 Jan;73:102722. doi: 10.1016/j.healthplace.2021.102722. Epub 2021 Dec 3.
We employed a longitudinal distributed lag modeling approach to systematically estimate how associations between built environment features and transport walking decayed with the increase of distance from home to built environment destinations. Data came from a cohort recruited from six U.S. cities (follow-up 2000-2010, N = 3913, baseline mean age 60). Built environment features included all walkable destinations, consisting of common and popular destinations for daily life. We also included two subsets frequent social destinations and food stores to examine if the spatial scale effects differed by varying density for different types of built environment destinations. Adjusted results found that increases in transport walking diminished when built environment destinations were farther, although distance thresholds varied across different types of built environment destinations. Higher availability of walking destinations within 2-km and frequent social destinations within 1.6-km were associated with transport walking. Food stores were not associated with transport walking. This new information will help policymakers and urban designers understand at what distances each type of built environment destinations influences transport walking, in turn informing the development of interventions and/or the placement of amenities within neighborhoods to promote transport walking. The findings that spatial scales depend on specific built environment features also highlight the need for methods that can more flexibly estimate associations between outcomes and different built environment features across varying contexts, in order to improve our understanding of the spatial mechanisms involved in said associations.
我们采用纵向分布滞后模型方法,系统地估计了居住环境特征与交通步行之间的关联随距离的增加而衰减的情况,其中距离是指从家到居住环境目的地的距离。数据来自于在美国六个城市招募的一个队列研究(随访期 2000-2010 年,N=3913,基线平均年龄 60 岁)。居住环境特征包括所有可步行的目的地,包括日常生活中常见和受欢迎的目的地。我们还包括了两个经常光顾的社交目的地和食品店子集,以检验不同类型的居住环境目的地的密度不同是否会导致空间尺度效应的差异。调整后的结果发现,随着居住环境目的地越来越远,交通步行的增加量减少,尽管不同类型的居住环境目的地的距离阈值有所不同。在 2 公里范围内有更多的步行目的地和在 1.6 公里范围内有更多的经常光顾的社交目的地与交通步行有关。而食品店与交通步行无关。这些新信息将帮助政策制定者和城市设计师了解每种类型的居住环境目的地在多远的距离上影响交通步行,从而为促进交通步行的干预措施的制定和/或社区内设施的安置提供信息。空间尺度取决于特定的居住环境特征这一发现也强调了需要采用更灵活的方法来估计不同空间尺度的居住环境特征与结果之间的关联,以便更好地理解这些关联中涉及的空间机制。