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首页> 外文期刊>Social science and medicine >Assessing patterns of spatial behavior in health studies: Their socio-demographic determinants and associations with transportation modes (the RECORD Cohort Study)
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Assessing patterns of spatial behavior in health studies: Their socio-demographic determinants and associations with transportation modes (the RECORD Cohort Study)

机译:评估健康研究中的空间行为模式:其社会人口统计学决定因素以及与交通方式的关联(RECORD队列研究)

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摘要

Prior epidemiological studies have mainly focused on local residential neighborhoods to assess environmental exposures. However, individual spatial behavior may modify residential neighborhood influences, with weaker health effects expected for mobile populations. By examining individual patterns of daily mobility and associated socio-demographic profiles and transportation modes, this article seeks to develop innovative methods to account for daily mobility in health studies. We used data from the RECORD Cohort Study collected in 2011-2012 in the Paris metropolitan area, France. A sample of 2062 individuals was investigated. Participants' perceived residential neighborhood boundaries and regular activity locations were geocoded using the VERUAS application. Twenty-four indicators were created to qualify individual space-time patterns, using spatial analysis methods and a geographic information system. Three domains of indicators were considered: lifestyle indicators, indicators related to the geometry of the activity space, and indicators related to the importance of the residential neighborhood in the overall activity space. Principal component analysis was used to identify main dimensions of spatial behavior. Multilevel linear regression was used to determine which individual characteristics were associated with each spatial behavior dimension. The factor analysis generated five dimensions of spatial behavior: importance of the residential neighborhood in the activity space, volume of activities, and size, eccentricity, and specialization of the activity space. Age, socioeconomic status, and location of the household in the region were the main predictors of daily mobility patterns. Activity spaces of small sizes centered on the residential neighborhood and implying a large volume of activities were associated with walking and/or biking as a transportation mode. Examination of patterns of spatial behavior by individual socio-demographic characteristics and in relation to transportation modes is useful to identify populations with specific mobility/accessibility needs and has implications for investigating transportation-related physical activity and assessing environmental exposures and their effects on health.
机译:先前的流行病学研究主要集中在当地居民区以评估环境暴露。但是,个人的空间行为可能会改变居民区的影响,对流动人口的健康影响较弱。通过研究日常出行的个人模式以及相关的社会人口统计资料和交通方式,本文力求开发出创新的方法来说明健康研究中的日常出行。我们使用了2011年至2012年在法国巴黎市区收集的RECORD队列研究的数据。调查了2062个人的样本。使用VERUAS应用程序对参与者的感知居民区边界和常规活动位置进行了地理编码。使用空间分析方法和地理信息系统,创建了二十四个指标来限定单个时空模式。考虑了三个指标领域:生活方式指标,与活动空间的几何形状有关的指标以及与居民区在整个活动空间中的重要性有关的指标。主成分分析用于确定空间行为的主要维度。使用多级线性回归来确定哪些个性特征与每个空间行为维度相关。因子分析产生了空间行为的五个维度:活动空间中居民区的重要性,活动量以及活动空间的大小,偏心率和专业化。年龄,社会经济地位以及该地区家庭的位置是日常出行方式的主要预测指标。小规模的活动空间以居民区为中心,意味着大量的活动与步行和/或骑自行车作为一种交通方式有关。通过个人社会人口学特征以及与运输方式有关的空间行为模式的检查,对于确定具有特殊机动性/可及性需求的人群非常有用,并且对调查与运输有关的体育活动,评估环境暴露及其对健康的影响具有影响。

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