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GIS-modelled built-environment exposures reflecting daily mobility for applications in child health research.
International Journal of Health Geographics ( IF 4.9 ) Pub Date : 2020-04-10 , DOI: 10.1186/s12942-020-00208-2
Amy Mizen 1 , Richard Fry 1, 2 , Sarah Rodgers 3
Affiliation  

BACKGROUND Inaccurately modelled environmental exposures may have important implications for evidence-based policy targeting health promoting or hazardous facilities. Travel routes modelled using GIS generally use shortest network distances or Euclidean buffers to represent journeys with corresponding built-environment exposures calculated along these routes. These methods, however, are an unreliable proxy for calculating child built-environment exposures as child route choice is more complex than shortest network routes. METHODS We hypothesised that a GIS model informed by characteristics of the built-environment known to influence child route choice could be developed to more accurately model exposures. Using GPS-derived walking commutes to and from school we used logistic regression models to highlight built-environment features important in child route choice (e.g. road type, traffic light count). We then recalculated walking commute routes using a weighted network to incorporate built-environment features. Multilevel regression analyses were used to validate exposure predictions to the retail food environment along the different routing methods. RESULTS Children chose routes with more traffic lights and residential roads compared to the modelled shortest network routes. Compared to standard shortest network routes, the GPS-informed weighted network enabled GIS-based walking commutes to be derived with more than three times greater accuracy (38%) for the route to school and more than 12 times greater accuracy (92%) for the route home. CONCLUSIONS This research advocates using weighted GIS networks to accurately reflect child walking journeys to school. The improved accuracy in route modelling has in turn improved estimates of children's exposures to potentially hazardous features in the environment. Further research is needed to explore if the built-environment features are important internationally. Route and corresponding exposure estimates can be scaled to the population level which will contribute to a better understanding of built-environment exposures on child health and contribute to mobility-based child health policy.

中文翻译:

GIS建模的内置环境暴露量反映了在儿童健康研究中的日常活动。

背景技术不正确地建模的环境暴露可能对针对以健康促进或危险设施为基础的循证政策具有重要意义。使用GIS建模的旅行路线通常使用最短的网络距离或欧几里得缓冲区来表示带有沿这些路线计算的相应建筑环境暴露的旅程。但是,由于子路由选择比最短的网络路由更为复杂,因此这些方法对于计算子项内置环境的暴露量是不可靠的代理。方法我们假设可以开发一个以已知的影响孩子的路线选择的建筑环境为特征的GIS模型,以更准确地模拟暴露。通过使用GPS派送的上下班通勤路线,我们使用逻辑回归模型突出显示了在选择儿童路线时很重要的内置环境特征(例如,道路类型,交通信号灯数量)。然后,我们使用加权网络并入内置环境功能来重新计算步行通勤路线。使用多级回归分析来验证沿不同路由方法对零售食品环境的暴露预测。结果与模拟的最短网络路线相比,孩子们选择了具有更多交通信号灯和居民道路的路线。与标准的最短网络路线相比,具有GPS信息的加权网络使基于GIS的步行通勤的上班路线的准确性提高了三倍(38%),而上学路线的准确性提高了12倍(92%)。回家的路。结论本研究提倡使用加权GIS网络来准确反映儿童上学的步行路程。路线建模精度的提高反过来又提高了对儿童暴露于环境中潜在危险特征的估计。需要进行进一步的研究以探讨建筑环境功能在国际上是否重要。路线和相应的接触估计值可以按人口比例调整,这将有助于更好地了解建筑物环境对儿童健康的影响,并有助于基于流动性的儿童健康政策。暴露于环境中潜在危险的特征中。需要进行进一步的研究以探讨建筑环境功能在国际上是否重要。路线和相应的接触估计值可以按人口比例调整,这将有助于更好地了解建筑物环境对儿童健康的影响,并有助于基于流动性的儿童健康政策。暴露于环境中潜在危险的特征中。需要进行进一步的研究以探讨建筑环境功能在国际上是否重要。路线和相应的接触估计值可以按人口比例调整,这将有助于更好地了解建筑物环境对儿童健康的影响,并有助于基于流动性的儿童健康政策。
更新日期:2020-04-22
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