Using Geographic Information Systems (GIS) to assess the role of the built environment in influencing obesity: a glossary

Thornton, Lukar; Pearce, Jamie; Kavanagh, Anne

doi:10.1186/1479-5868-8-71

Cited by 199 publications

(179 citation statements)

References 74 publications

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“…An activity space is a representation of the actual area in which an individual roams or travels and may have limited overlap with arbitrary boundaries used to define 'neighbourhoods' [65]. Activity spaces can be generated using Global Positioning Systems (GPS) and may provide a more accurate reflection of exposure to environmental features [66]; however, causal inference with behaviour may be impacted by selective daily activity bias whereby access to a specific facility or resource is determined from locations specifically visited to use the resource [67]. To date, most use of GPS devices in physical activity research among children has utilized the devices in conjunction with accelerometry to identify where children engage in physical activity [e.g.…”

Section: Discussionmentioning

confidence: 99%

Playability: Built and Social Environment Features That Promote Physical Activity Within Children

2015

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The role of neighbourhood built and social environments in shaping children's physical activity has received increasing interest over the past 10 years. We reviewed recent evidence published between 2011 and 2014. Most of the recent evidence continues to be cross-sectional. Few macro-level neighbourhood attributes were consistently associated with physical activity in the expected direction. The strongest evidence for associations between neighbourhood attributes and physical activity with was for the transportation environment, particularly in relation to proximity to school and transport-related physical activity. There was intermediate evidence that neighbourhood walking/cycling infrastructure and pedestrian safety structures are associated with transport-related PA. Recent evidence on associations between the neighbourhood built and social environment and children's PA is modest. Stronger study designs and greater attention to conceptual-matching and specificity of measures are critical to advance the evidence base.

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Section: Discussionmentioning

confidence: 99%

Playability: Built and Social Environment Features That Promote Physical Activity Within Children

2015

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“…The number of different facilities within neighbourhoods and the proximity through the road network from participants' homes to the various facilities were calculated (Thornton et al, 2011). Data on store locations were obtained from a variety of sources including company websites and business directories and were cleaned to remove duplicates.…”

Section: Neighbourhood-level Variablesmentioning

confidence: 99%

Is neighbourhood obesogenicity associated with body mass index in women? Application of an obesogenicity index in socioeconomically disadvantaged neighbourhoods

Tseng¹,

Thornton²,

Lamb³

et al. 2014

Health & Place

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An aggregate index is potentially useful to represent neighbourhood obesogenicity. We created a conceptually-based obesogenicity index and examined its association with body mass index (BMI) among 3786 women (age 18-45y) in socio-economically disadvantaged neighbourhoods in Victoria, Australia. The index included 3 items from each of 3 domains: food resources (supermarkets, green grocers, fast food restaurants), recreational activity resources (gyms, pools, park space), and walkability (4+ leg intersections, neighbourhood walking environment, neighbourhood safety), with a possible range from 0 to 18 reflecting 0-2 for each of the 9 items. Using generalised estimating equations, neighbourhood obesogenicity was not associated with BMI in the overall sample. However, stratified analyses revealed generally positive associations with BMI in urban areas and inverse associations in rural areas (interaction p=0.02). These analyses are a first step towards combining neighbourhood characteristics into an aggregate obesogenicity index that is transparent enough to be adopted elsewhere and to allow examination of the relevance of its specific components in different settings.

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“…Using the geographic information system ArcGIS 9?3 (ESRI, Redlands, CA, USA), we undertook a count of fast-food restaurants within a 3-km road network distance (28) from each individual's household location. Three kilometres was chosen because this distance corresponds with prior evidence that the majority of food shopping is undertaken within this distance from home (29,30) .…”

Section: Fast-food Restaurant Exposurementioning

confidence: 99%

Barriers to avoiding fast-food consumption in an environment supportive of unhealthy eating

Thornton

Jeffery

Crawford

2012

Public Health Nutr.

Self Cite

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Objective: To investigate factors (ability, motivation and the environment) that act as barriers to limiting fast-food consumption in women who live in an environment that is supportive of poor eating habits. Design: Cross-sectional study using self-reports of individual-level data and objectively measured environmental data. Multilevel logistic regression was used to assess factors associated with frequency of fast-food consumption. Setting: Socio-economically disadvantaged areas in metropolitan Melbourne, Australia. Subjects: Women (n 932) from thirty-two socio-economically disadvantaged neighbourhoods living within 3 km of six or more fast-food restaurants. Women were randomly sampled in 2007-2008 as part of baseline data collection for the Resilience for Eating and Activity Despite Inequality (READI) study. Results: Consuming low amounts of fast food was less likely in women with lower perceived ability to shop for and cook healthy foods, lower frequency of family dining, lower family support for healthy eating, more women acquaintances who eat fast food regularly and who lived further from the nearest supermarket. When modelled with the other significant factors, a lower perceived shopping ability, mid levels of family support and living further from the nearest supermarket remained significant. Among those who did not perceive fruits and vegetables to be of high quality, less frequent fast-food consumption was further reduced for those with the lowest confidence in their shopping ability. Conclusions: Interventions designed to improve women's ability and opportunities to shop for healthy foods may be of value in making those who live in high-risk environments better able to eat healthily.

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Using Geographic Information Systems (GIS) to assess the role of the built environment in influencing obesity: a glossary

Cited by 199 publications

References 74 publications

Playability: Built and Social Environment Features That Promote Physical Activity Within Children

Playability: Built and Social Environment Features That Promote Physical Activity Within Children

Is neighbourhood obesogenicity associated with body mass index in women? Application of an obesogenicity index in socioeconomically disadvantaged neighbourhoods

Barriers to avoiding fast-food consumption in an environment supportive of unhealthy eating

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