Visualising Combined Time Use Patterns of Children's Activities and Their Association with Weight Status and Neighbourhood Context.

Compositional data techniques are an emerging method in physical activity research. These techniques account for the complexities of, and interrelationships between, behaviours that occur throughout a day (e.g., physical activity, sitting, and sleep). The field of health geography research is also developing rapidly. Novel spatial techniques and data visualisation approaches are increasingly being recognised for their utility in understanding health from a socio-ecological perspective. Linking compositional data approaches with geospatial datasets can yield insights into the role of environments in promoting or hindering the health implications of the daily time-use composition of behaviours. The 7-day behaviour data used in this study were derived from accelerometer data for 882 Auckland school children and linked to weight status and neighbourhood deprivation. We developed novel geospatial visualisation techniques to explore activity composition over a day and generated new insights into links between environments and child health behaviours and outcomes. Visualisation strategies that integrate compositional activities, time of day, weight status, and neighbourhood deprivation information were devised. They include a ringmap overview, small-multiple ringmaps, and individual and aggregated time⁻activity diagrams. Simultaneous visualisation of geospatial and compositional behaviour data can be useful for triangulating data from diverse disciplines, making sense of complex issues, and for effective knowledge translation

Associations between Children's Physical Activity and Neighborhood Environments Using GIS: A Secondary Analysis from a Systematic Scoping Review.

Regular participation in physical activity is essential for children's physical, mental, and cognitive health. Neighborhood environments may be especially important for children who are more likely to spend time in the environment proximal to home. This article provides an update of evidence for associations between children's physical activity behaviors and objectively assessed environmental characteristics derived using geographical information system (GIS)-based approaches. A systematic scoping review yielded 36 relevant articles of varying study quality. Most studies were conducted in the USA. Findings highlight the need for neighborhoods that are well connected, have higher population densities, and have a variety of destinations in the proximal neighborhood to support children's physical activity behaviors. A shorter distance to school and safe traffic environments were significant factors in supporting children's active travel behaviors. Areas for improvement in the field include the consideration of neighborhood self-selection bias, including more diverse population groups, ground-truthing GIS databases, utilising data-driven approaches to derive environmental indices, and improving the temporal alignment of GIS datasets with behavioral outcomes

Associations between Children's Physical Activity and Neighborhood Environments Using GIS: A Secondary Analysis from a Systematic Scoping Review.

Regular participation in physical activity is essential for children's physical, mental, and cognitive health. Neighborhood environments may be especially important for children who are more likely to spend time in the environment proximal to home. This article provides an update of evidence for associations between children's physical activity behaviors and objectively assessed environmental characteristics derived using geographical information system (GIS)-based approaches. A systematic scoping review yielded 36 relevant articles of varying study quality. Most studies were conducted in the USA. Findings highlight the need for neighborhoods that are well connected, have higher population densities, and have a variety of destinations in the proximal neighborhood to support children's physical activity behaviors. A shorter distance to school and safe traffic environments were significant factors in supporting children's active travel behaviors. Areas for improvement in the field include the consideration of neighborhood self-selection bias, including more diverse population groups, ground-truthing GIS databases, utilising data-driven approaches to derive environmental indices, and improving the temporal alignment of GIS datasets with behavioral outcomes

A geospatial approach to measuring the built environment for active transport, physical activity and health outcomes.

Active transport and physical activity behaviours are recognised as important determinants of a number of health outcomes, including obesity. Over the last decade, there has been a significant amount of research focused on the need to quantify the ‘walkability’ of neighbourhoods or urban environments as a means of predicting physical activity behaviours. The most common methods used to create indices of walkability focus on a combination of land use mix, street connectivity and dwelling density, as developed by Frank et al., (2005). What is largely missing in this research, however, is a focus on other modes of active transport (such as cycling) and a related recognition of how different delineations (Euclidean and network) of neighbourhoods may affect results. This thesis investigates the influence of the built environment at a number of spatial levels and different neighbourhood delineations, using both standard and novel methods. This research advances and improves our current understandings of the built environment by being the first to use a novel method based on kernel density estimation, to measure associations between the built environment, active transport, physical activity, and health outcomes in a city in New Zealand (Wellington City). This novel method is used to create an Enhanced Walk Index, improving on standard walk indices by including measures of slope, street lights and footpaths and tracks. In addition, this research is the first to test and validate indices of bikeability and neighbourhood destination accessibility (NDAI), based on the novel method. Results of the study suggest that the novel Basic and Enhanced Walk Indices had strong significant positive associations with active transport and overweight/obesity. In comparison the standard method had weaker significant associations, potentially indicating previous research has underestimated the effect of the built environment on active behaviours and health outcomes. In addition, the novel indices of bikeability and NDAI also showed significant positive associations with active transport and overweight/obesity, however effect sizes were small. Furthermore, results varied depending on the type of neighbourhood delineation and spatial scale used. However, in general, the network buffer showed stronger associations between indices of the built environment and active transport, physical activity and overweight/obesity. This research thus strengthens current international and national evidence on how the built environment affects active transport, physical activity behaviours and health outcomes. It expands a preoccupation with walkability to encompass other modes of transport, such as bikeability. Furthermore it provides an alternative, and potentially more nuanced novel method to assess the relationships between the built environment, active transport, physical activity and health outcomes

Differences in child-drawn and GIS-modelled routes to school : Impact on space and exposure to the built environment in Auckland, New Zealand

Highlights • Use of online participatory mapping to measure children's travel routes to school. • About 50% of the child-drawn routes were spatially matched with GIS shortest routes. • The built environment differed between child-drawn routes and GIS shortest routes. • Active travel routes in pedestrian network were more similar to child-drawn routes

Improving spatial data in health geographics: a practical approach for testing data to measure children's physical activity and food environments using Google Street View

Background Geographic information systems (GIS) are often used to examine the association between both physical activity and nutrition environments, and children’s health. It is often assumed that geospatial datasets are accurate and complete. Furthermore, GIS datasets regularly lack metadata on the temporal specificity. Data is usually provided ‘as is’, and therefore may be unsuitable for retrospective or longitudinal studies of health outcomes. In this paper we outline a practical approach to both fill gaps in geospatial datasets, and to test their temporal validity. This approach is applied to both district council and open-source datasets in the Taranaki region of Aotearoa New Zealand. Methods We used the ‘streetview’ python script to download historic Google Street View (GSV) images taken between 2012 and 2016 across specific locations in the Taranaki region. Images were reviewed and relevant features were incorporated into GIS datasets. Results A total of 5166 coordinates with environmental features missing from council datasets were identified. The temporal validity of 402 (49%) environmental features was able to be confirmed from council dataset considered to be ‘complete’. A total of 664 (55%) food outlets were identified and temporally validated. Conclusions Our research indicates that geospatial datasets are not always complete or temporally valid. We have outlined an approach to test the sensitivity and specificity of GIS datasets using GSV images. A substantial number of features were identified, highlighting the limitations of many GIS datasets

Objective measurement of children's physical activity geographies: A systematic search and scoping review.

This study aimed to systematically identify, map out, and describe geographical information systems (GIS)-based approaches that have been employed to measure children's neighborhood geographies for physical activity behaviors. Forty studies were included, most were conducted in the USA. Heterogeneity in GIS methods and measures was found. The majority of studies estimated children's environments using Euclidean or network buffers ranging from 100 m to 5 km. No singular approach to measuring children's physical activity geographies was identified as optimal. Geographic diversity in studies as well as increased use of measures of actual neighborhood exposure are needed. Improved consistency and transparency in reporting research methods is urgently required

Viewing obesogenic advertising in children's neighbourhoods using Google Street View

The advertising of unhealthy food and beverages forms an important component of obesogenic environments. Such marketing to children is a key health determinant because of its impact on dietary preference and food purchasing behaviour. The location of outdoor advertising is important in exploring obesogenic environments and children's neighbourhoods. The aim of this study is to explore issues involved in the use of Google Street View to examine outdoor food and beverage advertising. The implications for using Google Street View in the context of neighbourhood built environment research and grass-roots advocacy are discussed. The study was conducted within walkable distances from 19 primary and intermediate schools in Auckland, New Zealand, where “walkable” was defined as limited by 800 m road network boundaries, which are equivalent to school buffer boundaries. Google Street View allows for centrality of data collection, coding, and storage. However, challenges exist with the method because 727 (29.4%) of a total of 2,474 outdoor advertisements that were identified were not able to be categorised because images were unclear, not in English, blocked, or at angles where detail cannot be deciphered. Specific to outdoor advertising for food and beverages, the results presented here show that children are exposed to a significantly greater number of unhealthy advertising than other advertising, P=0.001, eta-squared statistic (0.45) indicates a large effect size. Overall, the results show promise for the use of Google Street View in the study of obesogenic environments

Obtaining fruit and vegetables for the lowest prices: pricing survey of different outlets and geographical analysis of competition effects.

AIMS: Inadequate fruit and vegetable (F&V) consumption is an important dietary risk factor for disease internationally. High F&V prices can be a barrier to dietary intake and so to improve understanding of this topic we surveyed prices and potential competition between F&V outlet types. METHODS: Over a three week early autumn period in 2013, prices were collected bi-weekly for 18 commonly purchased F&Vs from farmers' markets (FM) selling local produce (n = 3), other F&V markets (OFVM) (n = 5), supermarkets that neighbored markets (n = 8), and more distant supermarkets (n = 8), (in urban Wellington and Christchurch areas of New Zealand). Prices from an online supermarket were also collected. RESULTS: A total of 3120 prices were collected. Most F&Vs (13/18) were significantly cheaper at OFVMs than supermarkets. Over half of the F&Vs (10/18) were significantly cheaper at nearby compared to distant supermarkets, providing evidence of a moderate 'halo effect' in price reductions in supermarkets that neighbored markets. Weekend (vs midweek) prices were also significantly cheaper at nearby (vs distant) supermarkets, supporting evidence for a 'halo effect'. Ideal weekly 'food basket' prices for a two adult, two child family were: OFVMs (NZ$76), online supermarket ($113), nearby supermarkets ($124), distant supermarkets ($127), and FMs ($138). This represents a savings of$49 per week (US$26) by using OFVMs relative to (non-online) supermarkets. Similarly, a shift from non-online supermarkets to the online supermarket would generate a$13 saving. CONCLUSIONS: In these locations general markets appear to be providing some substantially lower prices for fruit and vegetables than supermarkets. They also appear to be depressing prices in neighboring supermarkets. These results, when supplemented by other needed research, may help inform the case for interventions to improve access to fruit and vegetables, particularly for low-income populations