Article Text
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 m2 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 predictive of children spending time, independently of proximity to their home. For most land-uses there were no differences by gender, except for leisure centres where girls spent more time than boys (4.0, 95% CI 1.0 to 7.0).
Conclusion We created ‘personalised activity spaces’ which simultaneously assessed all the types of environment children could and did visit. The study found features of the urban landscape that, regardless of distance from home, children were more or less likely to spend time in. The ability to consider how children use their urban area, and the multiple environments they are exposed to, is a significant step towards understanding the urban environment as a complex system.