{"title":"儿童和年轻人","authors":"O. Robison, G. Inglis, J. Egan","doi":"10.7765/9781526147448.00007","DOIUrl":null,"url":null,"abstract":"Background The environment in which we live, travel and socialise has a profound influence on health. Existing literature typically uses a fixed ‘ neighbourhood ’ as the unit of analysis – assuming often that people conduct their lives within that spatially defined unit. The aim of this study is to describe urban mobility and environmental exposure across an entire urban landscape. Methods Using the ‘ Studying Physical Activity in Children ’ s Environments across Scotland ’ (SPACES) study, we developed a novel concept to construct a model of the entire urban landscape within the Central Belt of Scotland. The model used a 25 m 2 grid system (~3 million GRID squares). For each cell, there was detailed built-environment information, including characteristics of the road network, retail outlets, greenspace, and walkability measures. SPACES used GPS to collect individual-level mobility information for 100 10-year-old children over the course of one week. Each child ’ s location was recorded every 10 seconds during waking hours and that data was joined to the urban landscape model. The result was a comprehensive dataset describing of whether and when each child visited each grid cell, how long they spent there, and what the location comprised. Using negative binomial regression, we explored which features of the built environment were associated with the child visiting that space at all, and with time spent there, and examined whether this differed by the sociodemographic characteristics of the child. Results We found land-uses across the urban landscape that were predictive of children spending time, such as: libraries ((coef) 2.0, 95% CI 1.0 to 3.0) and places of worship (1.8, 95% CI 1.2 to 2.5), and a linear relationship between increased walkability of a cell and a greater time spent there. Cells containing playing fields, public parks and play parks were","PeriodicalId":193734,"journal":{"name":"Organising care around patients","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Children and young people\",\"authors\":\"O. Robison, G. Inglis, J. Egan\",\"doi\":\"10.7765/9781526147448.00007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background The environment in which we live, travel and socialise has a profound influence on health. Existing literature typically uses a fixed ‘ neighbourhood ’ as the unit of analysis – assuming often that people conduct their lives within that spatially defined unit. The aim of this study is to describe urban mobility and environmental exposure across an entire urban landscape. Methods Using the ‘ Studying Physical Activity in Children ’ s Environments across Scotland ’ (SPACES) study, we developed a novel concept to construct a model of the entire urban landscape within the Central Belt of Scotland. The model used a 25 m 2 grid system (~3 million GRID squares). For each cell, there was detailed built-environment information, including characteristics of the road network, retail outlets, greenspace, and walkability measures. SPACES used GPS to collect individual-level mobility information for 100 10-year-old children over the course of one week. Each child ’ s location was recorded every 10 seconds during waking hours and that data was joined to the urban landscape model. The result was a comprehensive dataset describing of whether and when each child visited each grid cell, how long they spent there, and what the location comprised. Using negative binomial regression, we explored which features of the built environment were associated with the child visiting that space at all, and with time spent there, and examined whether this differed by the sociodemographic characteristics of the child. Results We found land-uses across the urban landscape that were predictive of children spending time, such as: libraries ((coef) 2.0, 95% CI 1.0 to 3.0) and places of worship (1.8, 95% CI 1.2 to 2.5), and a linear relationship between increased walkability of a cell and a greater time spent there. 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引用次数: 0
摘要
我们生活、旅行和社交的环境对健康有着深远的影响。现有文献通常使用固定的“社区”作为分析单位——通常假设人们在这个空间定义的单位中生活。本研究的目的是描述整个城市景观的城市流动性和环境暴露。方法利用“研究苏格兰儿童环境中的体育活动”(空间)研究,我们提出了一个新的概念来构建苏格兰中央地带的整个城市景观模型。该模型使用了一个25平方米的网格系统(约300万个grid方格)。对于每个单元,都有详细的建筑环境信息,包括道路网络、零售网点、绿地和步行措施的特征。空间使用GPS在一周的时间里收集了100名10岁儿童的个人移动信息。在醒着的时候,每个孩子的位置每10秒被记录一次,这些数据被加入到城市景观模型中。结果是一个全面的数据集,描述了每个孩子是否以及何时访问每个网格单元,他们在那里呆了多长时间,以及位置组成。使用负二项回归,我们探索了建筑环境的哪些特征与儿童访问该空间有关,以及与在那里度过的时间有关,并检查了这是否因儿童的社会人口特征而有所不同。我们发现,整个城市景观的土地利用都可以预测儿童的消费时间,例如:图书馆((coef) 2.0, 95% CI 1.0至3.0)和宗教场所(1.8,95% CI 1.2至2.5),并且一个细胞的步行性增加与在那里度过的时间增加之间存在线性关系。含有运动场、公共公园和游戏场的细胞
Background The environment in which we live, travel and socialise has a profound influence on health. Existing literature typically uses a fixed ‘ neighbourhood ’ as the unit of analysis – assuming often that people conduct their lives within that spatially defined unit. The aim of this study is to describe urban mobility and environmental exposure across an entire urban landscape. Methods Using the ‘ Studying Physical Activity in Children ’ s Environments across Scotland ’ (SPACES) study, we developed a novel concept to construct a model of the entire urban landscape within the Central Belt of Scotland. The model used a 25 m 2 grid system (~3 million GRID squares). For each cell, there was detailed built-environment information, including characteristics of the road network, retail outlets, greenspace, and walkability measures. SPACES used GPS to collect individual-level mobility information for 100 10-year-old children over the course of one week. Each child ’ s location was recorded every 10 seconds during waking hours and that data was joined to the urban landscape model. The result was a comprehensive dataset describing of whether and when each child visited each grid cell, how long they spent there, and what the location comprised. Using negative binomial regression, we explored which features of the built environment were associated with the child visiting that space at all, and with time spent there, and examined whether this differed by the sociodemographic characteristics of the child. Results We found land-uses across the urban landscape that were predictive of children spending time, such as: libraries ((coef) 2.0, 95% CI 1.0 to 3.0) and places of worship (1.8, 95% CI 1.2 to 2.5), and a linear relationship between increased walkability of a cell and a greater time spent there. Cells containing playing fields, public parks and play parks were