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一种评估健康心血管城市环境的多组分方法:健康城区心脏指数。

A multicomponent method assessing healthy cardiovascular urban environments: The Heart Healthy Hoods Index.

机构信息

Social and Cardiovascular Epidemiology Research Group, School of Medicine, University of Alcalá, Alcalá de Henares, Madrid, Spain; Department of Geology, Geography and Environmental Sciences, University of Alcalá, Alcalá de Henares, Madrid, Spain.

Department of Epidemiology and Biostatistics, City University of New York, New York, United States.

出版信息

Health Place. 2019 Jan;55:111-119. doi: 10.1016/j.healthplace.2018.11.010. Epub 2018 Dec 11.

Abstract

Previous studies have examined the built environment mostly focusing on a single exposure construct (e.g. walkability) to examine its association with health outcomes. This study developed a multicomponent Heart Healthy Hoods Index to characterize heart-healthy urban environments and examined its relationship with the prevalence of cardiovascular disease (CVD) in Madrid, Spain. Using spatial methods, we generated two index models (model 0 unweighted and model 1 weighted) using the percentage of deaths for the main behavioral risk factors for CVD (diet, physical activity, alcohol, and tobacco environments). We performed global (Ordinal Least Square) and local (Geographically Weighed Regression) regression analyses to assess the relationship between both index models and CVD prevalence, and to identify the best index model. In the global analysis, both models showed a significant negative relationship with CVD prevalence. In the local analysis, Model 1 removed the spatial autocorrelation of residuals and showed the lowest values for the Akaike information criterion. This study provides evidence of a non-stationary relationship between the heart-healthy urban environment and CVD prevalence. The HHH index may be an effective tool to identify and prioritize geographical areas for CVD prevention.

摘要

先前的研究主要集中在单一暴露结构(例如可步行性)上,以研究其与健康结果的关联。本研究开发了一个多成分的“心脏健康街区指数”来描述心脏健康的城市环境,并研究了其与西班牙马德里心血管疾病(CVD)患病率的关系。我们使用空间方法,使用 CVD 的主要行为风险因素(饮食、身体活动、酒精和烟草环境)的死亡率百分比,生成了两个指数模型(模型 0 未加权和模型 1 加权)。我们进行了全局(有序最小二乘法)和局部(地理加权回归)回归分析,以评估两个指数模型与 CVD 患病率之间的关系,并确定最佳指数模型。在全局分析中,两个模型都显示出与 CVD 患病率呈显著负相关。在局部分析中,模型 1 消除了残差的空间自相关,并显示出最低的 Akaike 信息准则值。本研究提供了心脏健康城市环境与 CVD 患病率之间存在非平稳关系的证据。HHH 指数可能是识别和优先考虑 CVD 预防的地理区域的有效工具。

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