South-East Asia Regional Conference on Epidemiology

<strong>South</strong>-<strong>East</strong> <strong>Asia</strong> <strong>Regional</strong> <strong>Conference</strong> on Epidemiology | 205
one can assess the nature of the food that is available and the nature of the food that is affordable.
The social environmental is relevant in terms of culture and norms regarding in-home or out-of-home
consumption patterns, types and quality of foods consumed, serving quantities, preferred locations for
obtaining food, and perceptions of food availability and pricing which may differ from the directly
measured reality. Social factors like these and culture, more generally, are spatially distributed as
are built environmental factors relating to food. Such geographical data are not generally captured
by government data sets but can be prepared using spatially organized inventories of services or
resources, residents perceptions and direct observations by researchers.
Spatial data can be characterized in different ways; for example, by using predefined administrative
boundaries (e.g. census tracts) or using buffers of defined radii to scale spatial representations for
each survey participant according to where they live, work or travel between residence and work,
or all three (18). It is often feasible and straightforward to perform multilevel modelling that
considers food outlets and people as nested within census tracts or similar administrative units. But
this approach has been criticized, in that administrative boundaries are artificial and typically lack
a theoretical justification for use in representing meaningful social spaces. Buffer zones suffer this
same limitation in the arbitrary specification of radii; however, buffer size can be allowed to vary
according to some relevant environmental factor (e.g. population density) and buffers have the benefit
of being centred on the location of individual residents. Given the data, GIS can be used to represent
a broad spectrum of key dimensions of environments. Considering again the food environment, the
spectrum of dimensions given in Fig. 4 can be captured by GIS where the use of indirect measures
from administrative and commercial services data on the left end of the continuum (food availability
and accessibility) transitions to more-or-less direct measures obtained from field research, on the right
end of the continuum (nature of food products and marketing). A complete spatial representation of
the food environment will thus involve a combination of indirect and direct measures.
Fig. 4: GIS can represent different dimensions of the food environment