巴西非正式社区街道层面因素的基于手机的邻里审计:非正式城市环境的局部视角。

A Local View of Informal Urban Environments: a Mobile Phone-Based Neighborhood Audit of Street-Level Factors in a Brazilian Informal Community.

机构信息

Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.

Maryland Institute for Applied Environmental Health, School of Public Health, University of Maryland-College Park, College Park, MD, USA.

出版信息

J Urban Health. 2019 Aug;96(4):537-548. doi: 10.1007/s11524-019-00351-7.

Abstract

Street-level environment characteristics influence the health behaviors and safety of urban residents, and may particularly threaten health within informal communities. However, available data on how such characteristics vary within and among informal communities is limited. We sought to adapt street audit strategies designed to characterize the physical environment for use in a large informal community, Rio das Pedras (RdP) located in Rio de Janeiro, Brazil. A smartphone-based systematic observation protocol was used to gather street-level information for a high-density convenience sample of street segments (N = 630, estimated as 86% of all street segments in the community). We adapted items related to physical disorder and physical deterioration. Measures selected to illustrate the approach include the presence of the following: (1) low-hanging or tangled wires, (2) litter, (3) structural evidence of sinking, and (4) an unpleasant odor. Intercept-only spatial generalized additive models (GAM) were used to evaluate and visualize spatial variation within the RdP community. We also examined how our estimates and conclusions about spatial variation might have been affected by lower-density sampling from random subsets street observations. Random subsets were selected to determine the robustness of study results in scenarios with sparser street sampling. Selected characteristics were estimated to be present for between 18% (unpleasant odor) to 59% (low-hanging or tangled wires) of the street segments in RdP; estimates remain similar (± 6%) when relying on a random subset created to simulate lower-density spatial sampling. Spatial patterns of variation based on predicted probabilities across RdP differed by indicator. Structural sinking and low-hanging or tangled wires demonstrated relatively consistent spatial distribution patterns across full and random subset sample sizes. Smartphone-based systematic observations represent an efficient and potentially feasible approach to systematically studying neighborhood environments within informal communities. Future deployment of such tools will benefit from incorporating data collection across multiple time points to explore reliability and quantify neighborhood change. These tools can prove useful means to assess street-level exposures that can be modifiable health determinants across a wide range of informal urban settings. Findings can contribute to improved urban planning and provide useful information for identifying potential locations for neighborhood-scaled interventions that can improve living conditions for residents in Rio das Pedras.

摘要

街道环境特征会影响城市居民的健康行为和安全,特别是在非正式社区内可能会对健康造成威胁。然而,目前可用的数据有限,无法充分了解这些特征在非正式社区内和之间的差异。本研究旨在将专门用于描述物理环境的街道评估策略进行改编,以应用于巴西里约热内卢的 Rio das Pedras(RdP)这个大型非正式社区。本研究使用基于智能手机的系统观测方案,对高密度便利抽样的街道段(N=630,估计为社区内所有街道段的 86%)进行街道层面的信息收集。我们改编了与物理无序和物理恶化相关的项目。选择用来举例说明该方法的措施包括以下内容:(1)低垂或纠结的电线,(2)垃圾,(3)下沉的结构证据,和(4)令人不快的气味。仅拦截空间广义加性模型(GAM)用于评估和可视化 RdP 社区内的空间变化。我们还研究了,如果仅从随机子集的街道观察中进行低密度抽样,我们对空间变化的估计和结论可能会受到何种影响。随机子集用于确定在街道抽样密度较稀疏的情况下研究结果的稳健性。在 RdP 中,约有 18%(令人不快的气味)到 59%(低垂或纠结的电线)的街道段估计存在选定特征;当依赖于创建来模拟低密度空间抽样的随机子集时,估计值保持相似(±6%)。基于 RdP 中预测概率的变化的空间模式因指标而异。结构下沉和低垂或纠结的电线在全样本和随机子集样本大小下表现出相对一致的空间分布模式。基于智能手机的系统观测代表了一种高效且具有潜在可行性的方法,可以在非正式社区内系统地研究邻里环境。未来部署此类工具将受益于结合多个时间点的数据收集,以探索可靠性并量化邻里变化。这些工具可以成为评估街头暴露的有用手段,街头暴露是广泛的非正式城市环境中可改变的健康决定因素。研究结果可以有助于改善城市规划,并为识别可以改善 Rio das Pedras 居民生活条件的邻里尺度干预的潜在地点提供有用信息。

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