Assessing urban and rural neighborhood characteristics using audit and GIS data: derivation and reliability of constructs
Assessing urban and rural neighborhood characteristics using audit and GIS data: derivation and reliability of constructs
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DOI：
10.1186/1479-5868-6-44
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发表时间：
2009-07-20
影响因子：
8.7
通讯作者：
Rodriguez, Daniel A.
中科院分区：
文献类型：
--
作者：
Evenson, Kelly R.;Sotres-Alvarez, Daniela;Rodriguez, Daniel A.
背景：需要采取措施评估社区环境，以更好地了解可能增加户外体育活动的显著特征，例如步行和骑自行车作为交通或休闲方式。本研究的目的是利用主要（邻里审计）和次要（地理信息系统）数据推导出描述邻里的结构。方法：利用审计和二次数据收集了10770个路段的详细信息。道路段样本随机分为探索性样本（60%）和验证性样本（40%）进行交叉验证。使用探索性样本（n = 6,388），使用多组验证性因子分析（CFA），通过城市化分别评估了七个先验结构（功能，安全，美学，目的地，不文明，地域性，社会空间）。此外，利用探索性因子分析（EFA）导出了新的后验结构。为了交叉验证（n = 4,382），我们测试了两个子样本之间的因素负荷、阈值、相关误差和后验结构之间的相关性。采用Spearman相关系数对采用路段子样本（n = 464）的最终结构进行两周测试-重测信度检验。结果：CFA表明，除了身体不文明行为外，先验构念在该地理区域不成立。因此，我们使用EFA对探索性样本得出了一个四因素解决方案：动脉或大道、可步行社区、物理不文明和装饰。在验证样本上使用CFA，这些后验结构的内部效度很高（范围为0.43至0.73），拟合是可以接受的。Spearman相关性表明，在城市和农村路段，动脉或通道因素显示出接近完美的可靠性（r = 0.96）。物理不文明因素和可步行社区因素在城市和农村部分都具有相当的接近完美的可靠性（r分别= 0.77至0.78和r = 0.79至0.82）。装饰因素在城市地区表现出中等信度（r = 0.50; 95% CI: 0.38-0.60），在农村地区表现出较低的信度（r = 0.39; 95% CI: 0.25-0.52）。结论：我们的分析结果产生了四个可靠和客观的测量结构，这些结构将用于探索北卡罗来纳州城市和农村体力活动的关联。这些结构应该在其他地理区域进行探索，以确认它们在其他地方的有用性。
Background: Measures to assess neighborhood environments are needed to better understand the salient features that may enhance outdoor physical activities, such as walking and bicycling for transport or leisure. The purpose of this study was to derive constructs to describe neighborhoods using both primary (neighborhood audit) and secondary (geographic information systems) data.Methods: We collected detailed information on 10,770 road segments using an audit and secondary data. The road segment sample was randomly split into an exploratory (60%) and validation sample (40%) for cross-validation. Using the exploratory sample (n = 6,388), seven a priori constructs were assessed separately (functionality, safety, aesthetics, destinations, incivilities, territorality, social spaces) by urbanicity using multi-group confirmatory factor analysis (CFA). Additionally, new a posteriori constructs were derived using exploratory factor analysis (EFA). For cross-validation (n = 4,382), we tested factor loadings, thresholds, correlated errors, and correlations among a posteriori constructs between the two subsamples. Two-week test-retest reliability of the final constructs using a subsample of road segments (n = 464) was examined using Spearman correlation coefficients.Results: CFA indicated the a priori constructs did not hold in this geographic area, with the exception of physical incivilities. Therefore, we used EFA to derive a four-factor solution on the exploratory sample: arterial or thoroughfare, walkable neighborhood, physical incivilities, and decoration. Using CFA on the validation sample, the internal validity for these a posteriori constructs was high (range 0.43 to 0.73) and the fit was acceptable. Spearman correlations indicated the arterial or thoroughfare factor displayed near perfect reliability in both urban and rural segments (r = 0.96). Both the physical incivilities factor and the walkable neighborhood factor had substantial to near perfect reliability in both urban and rural segments (r = 0.77 to 0.78 and r = 0.79 to 0.82, respectively). The decoration factor displayed moderate reliability in urban segments (r = 0.50; 95% CI: 0.38-0.60) and lower reliability in rural segments (r = 0.39; 95% CI: 0.25-0.52).Conclusion: The results of our analyses yielded four reliably and objectively measured constructs that will be used to explore associations with physical activity in urban and rural North Carolina. These constructs should be explored in other geographic areas to confirm their usefulness elsewhere.