Creating ‘obesogenic realities’; do our methodological choices make a difference when measuring the food environment?

International Journal of Health Geographics

Amelia A Lake³  Seraphim Alvanides¹  Thomas Burgoine² 

[1] Geography and the Built Environment, Ellison Building, Northumbria University, Newcastle upon Tyne NE1 8ST, UK;UKCRC Centre for Diet and Activity Research (CEDAR), Box 296, Institute of Public Health, Forvie Site, Robinson Way, University of Cambridge, Cambridge CB2 0SR, UK;Centre for Public Policy and Health, School of Medicine, Pharmacy and Health, Wolfson Research Institute, Queen’s Campus, Thornaby, Durham University, Stockton-on-Tees TS17 6BH, UK

关键词: Proximity;    Density;    Exposure;    Methods;    Foodscape;    Obesogenic Environments;   

Others  :  810096
DOI  :  10.1186/1476-072X-12-33

 received in 2013-04-23, accepted in 2013-06-23,  发布年份 2013

【 摘 要 】

Background

The use of Geographical Information Systems (GIS) to objectively measure ‘obesogenic’ food environment (foodscape) exposure has become common-place. This increase in usage has coincided with the development of a methodologically heterogeneous evidence-base, with subsequent perceived difficulties for inter-study comparability. However, when used together in previous work, different types of food environment metric have often demonstrated some degree of covariance. Differences and similarities between density and proximity metrics, and within methodologically different conceptions of density and proximity metrics need to be better understood.

Methods

Frequently used measures of food access were calculated for North East England, UK. Using food outlet data from local councils, densities of food outlets per 1000 population and per km² were calculated for small administrative areas. Densities (counts) were also calculated based on population-weighted centroids of administrative areas buffered at 400/800/1000m street network and Euclidean distances. Proximity (street network and Euclidean distances) from these centroids to the nearest food outlet were also calculated. Metrics were compared using Spearman’s rank correlations.

Results

Measures of foodscape density and proximity were highly correlated. Densities per km² and per 1000 population were highly correlated (r_s = 0.831). Euclidean and street network based measures of proximity (r_s = 0.865) and density (r_s = 0.667-0.764, depending on neighbourhood size) were also highly correlated. Density metrics based on administrative areas and buffered centroids of administrative areas were less strongly correlated (r_s = 0.299-0.658).

Conclusions

Density and proximity metrics were largely comparable, with some exceptions. Whilst results suggested a substantial degree of comparability across existing studies, future comparability could be ensured by moving towards a more standardised set of environmental metrics, where appropriate, lessening the potential pitfalls of methodological variation between studies. The researchers’ role in creating their own obesogenic ‘reality’ should be better understood and acknowledged.

【 授权许可】

   
2013 Burgoine et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

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