The impact of local food environments on diet; Do neighbouring food retailers influence what you eat?

Organised by Laboratory of Geo-information Science and Remote Sensing

Tue 9 February 2016 11:00 to 11:30

Venue Atlas, gebouwnummer 104
Room 1

By Barbara Sienkiewicz (Poland)


Geographic Information Systems (GIS) have improved our understanding of the variations of food location availability and accessibility and its relation with diet and weight. However, studies on this topic are relatively new to Europe. Therefore, investigating how local food environments influence the diets of Europeans is of interest. To my knowledge, no studies investigating this problem in the Netherlands have been conducted. Consequently, this study is the first one investigating how the spatial distribution of food locations affects Dutch citizens. This investigation involved GIS methods to study the local food environment by calculating the density and proximity of food retailers. The methods used include: Euclidean distance, network distance, clustering to CBS neighbourhoods and kernel density. Three main variables of diet: DHD (Dutch Healthy Diet) index, calorie intake and BMI (Body Mass Index) - were investigated in relation to a food environment (density and proximity of a certain retailer).
Main findings indicate that there may be a relationship between BMI and the following retailers: restaurants, cafes, grocers and supermarkets, and takeaways. It was found that people with high and low BMI are clustered. High BMI clusters (obese people) lived closer to grocery stores and supermarkets than people from low BMI clusters (normal weight). Besides that, people from normal weight clusters lived in places with higher densities of restaurants and cafés than in places where obese people lived. It can be concluded, then, that the more restaurants and cafés there are in your neighbourhood, the less likely you are to be obese. It was also found that the further away your closest meal delivery, convenience store, takeaway, grocery store or supermarket is, the less likely you are to gain weight and become obese/overweight. The accuracy of these assumptions, however, can be discussed. Certainly, it has to be investigated further because there is a chance that restaurants and cafes are not responsible for healthier diets.
These results indicate that the spatial configuration of food retailers is influencing diet in the Netherlands. However, the strength of this relation is unknown. Therefore, it is suggested to investigate this problem further, using larger groups of people and new techniques like GPS tracking. This may help us to understand this relation better.

Keywords: GIS; local food environment; BMI; nutrition; diet quality; food availability; Dutch Healthy Diet Index; spatial analysis; eating behaviour; residence characteristics; spatial configuration of food environment.