Department of Epidemiology, Biostatistics and Occupational Health, McGill University Health Centre, McGill University, Montréal, Quebec, Canada.
Am J Prev Med. 2013 Jun;44(6):e51-5. doi: 10.1016/j.amepre.2013.01.033.
Given the health benefits of walking, there is interest in understanding how physical environments favor walking. Although GIS-derived measures of land-use mix, street connectivity, and residential density are commonly combined into indices to assess how conducive neighborhoods are to walking, field validation of these measures is limited.
To assess the relationship between audit- and GIS-derived measures of overall neighborhood walkability and between objective (audit- and GIS-derived) and participant-reported measures of walkability.
Walkability assessments were conducted in 2009. Street-level audits were conducted using a modified version of the Pedestrian Environmental Data Scan. GIS analyses were used to derive land-use mix, street connectivity, and residential density. Participant perceptions were assessed using a self-administered questionnaire. Audit, GIS, and participant-reported indices of walkability were calculated. Spearman correlation coefficients were used to assess the relationships between measures. All analyses were conducted in 2012.
The correlation between audit- and GIS-derived measures of overall walkability was high (R=0.7 [95% CI=0.6, 0.8]); the correlations between objective (audit and GIS-derived) and participant-reported measures were low (R=0.2 [95% CI=0.06, 0.3]; R=0.2 [95% CI=0.04, 0.3], respectively). For comparable audit and participant-reported items, correlations were higher for items that appeared more objective (e.g., sidewalk presence, R=0.4 [95% CI=0.3, 0.5], versus safety, R=0.1 [95% CI=0.003, 0.3]).
The GIS-derived measure of walkability correlated well with the in-field audit, suggesting that it is reasonable to use GIS-derived measures in place of more labor-intensive audits. Interestingly, neither audit- nor GIS-derived measures correlated well with participants' perceptions of walkability.
鉴于步行对健康有益,人们有兴趣了解物理环境如何有利于步行。尽管 GIS 衍生的土地利用混合、街道连通性和居住密度等指标通常被组合成一个指数来评估社区对步行的便利性,但这些指标的现场验证是有限的。
评估审计和 GIS 衍生的整体邻里步行能力指标之间的关系,以及客观(审计和 GIS 衍生)和参与者报告的步行能力指标之间的关系。
2009 年进行了步行能力评估。街道层面的审计采用了行人环境数据扫描的修改版本。GIS 分析用于衍生土地利用混合、街道连通性和居住密度。参与者的看法是通过自我管理的问卷来评估的。计算了审计、GIS 和参与者报告的步行能力指数。使用 Spearman 相关系数评估了这些指标之间的关系。所有分析均于 2012 年进行。
审计和 GIS 衍生的整体步行能力指标之间的相关性很高(R=0.7 [95%CI=0.6, 0.8]);客观(审计和 GIS 衍生)和参与者报告的指标之间的相关性较低(R=0.2 [95%CI=0.06, 0.3];R=0.2 [95%CI=0.04, 0.3],分别)。对于类似的审计和参与者报告的项目,对于看起来更客观的项目,相关性更高(例如,人行道的存在,R=0.4 [95%CI=0.3, 0.5],而安全性,R=0.1 [95%CI=0.003, 0.3])。
GIS 衍生的步行能力指标与现场审计相关性良好,表明使用 GIS 衍生的指标替代更耗时的审计是合理的。有趣的是,审计和 GIS 衍生的指标都与参与者对步行能力的看法相关性不高。