In health research, like obesity studies, spatial technologies can add very valuable information. Combining remote sensing, geo-information and GPS will enable us to identify typical 'obesogenic' environments. Until now, only part of this type of information is used, while the combination - also called '3S' technology - has a large potential, according to researcher Peng Jia of the University of Twente, Faculty of Geoinformation Sciences and Earth Observation (ITC). He publishes about current and future applications of 3S-technologies in Trends in Endocrinology and Metabolism.
Obesity is a growing health problem we read about every day. We should exercise more, eat and drink healthy. Governments already plan 'lifestyle improvement programmes'. But what about the influence our daily environment has on obesity risk? Is it an inviting environment for doing exercises or going to work by bike? How about the availability of healthy food versus unhealthy food? And where do climate and temperature fit in? Obesity research is often done using questionnaires combined with activity tracking, sometimes adding aspects like income position and the social environment. But there is a lot more of information available from satellite images and geo-information systems, enabling us to identify regions with more or less obesity risk, according to Peng Jia. He is also director of a global research network 'International Initiative on Spatial Lifecourse Epidemiology'.
Mixed environments
Remote sensing, using satellites, provides many details about natural and built environments, including climate data. Geo-information systems add a lot of details to this, like the location of shops, restaurants, parks, and sports facilities. Is healthy food within reach, or is it tempting to go for a fast-food chain? What about the affordability? This may give rise to complicated questions: in the US, for example, a big supermarket offering a great choice of food, including healthy food, is often situated on a location that is typically made for going by car, with the fast-food chains present very nearby. This environment has obesogenic aspects, but also 'ingredients' for a more healthy lifestyle. Adding data coming from individuals, using GPS tracking for example, enables researchers to zoom in and find out which effects are predominant.
Local intervention
Using detailed knowledge of environment-related risk of obesity, interventions will be possible as well. Even on a city level, neighborhoods can be compared to see what works in obesity prevention. Spatial technologies have become increasingly accessible and affordable, according to Peng Jia, so it can be of great added value to health research. UT's ITC faculty has a lot of experience in collecting and interpreting these spatial data - and recently started a new Master's programme Spatial Engineering. The approach Peng Jia describes in his paper, is not limited to obesity: for certain diseases, information on the environment will add a lot of values as well.