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Clustering of unhealthy food around German schools and its influence on dietary behavior in school children: a pilot study.

Buck C, Börnhorst C, Pohlabeln H, Huybrechts I, Pala V, Reisch L, Pigeot I, IDEFICSI Family consort - Int J Behav Nutr Phys Act (2013)

Bottom Line: Comparing the 95% confidence envelopes to the observed K-function, we showed that food stores and fast food restaurants do not significantly cluster around schools.Apart from this result, the food retail index showed no effect on BMI (β=0.01,p=0.11) or food intake variables assessed by FFQ and 24-HDR.In the built environment of the German study region, clustering of food retailers does not depend on the location of schools.

View Article: PubMed Central - HTML - PubMed

Affiliation: Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.

ABSTRACT

Background: The availability of fast foods, sweets, and other snacks in the living environment of children is assumed to contribute to an obesogenic environment. In particular, it is hypothesized that food retailers are spatially clustered around schools and that a higher availability of unhealthy foods leads to its higher consumption in children. Studies that support these relationships have primarily been conducted in the U.S. or Australia, but rarely in European communities. We used data of FFQ and 24-HDR of the IDEFICS study, as well as geographical data from one German study region to investigate (1) the clustering of food outlets around schools and (2) the influence of junk food availability on the food intake in school children.

Methods: We geocoded food outlets offering junk food (e.g. supermarkets, kiosks, and fast food restaurants). Spatial cluster analysis of food retailers around child-serving institutions was conducted using an inhomogeneous K-function to calculate global 95% confidence envelopes. Furthermore, a food retail index was implemented considering the kernel density of junk food supplies per service area, adjusted for residential density. We linked the food retail index to FFQ and 24-HDR data of 384 6- to 9-year-old school children in the study region and investigated the impact of the index on food intake, using multilevel regression models adjusted for sex, age, BMI, parent's education and income, as well as adjusting for over- and underreporting of food intake.

Results: Comparing the 95% confidence envelopes to the observed K-function, we showed that food stores and fast food restaurants do not significantly cluster around schools. Apart from this result, the food retail index showed no effect on BMI (β=0.01,p=0.11) or food intake variables assessed by FFQ and 24-HDR.

Conclusion: In the built environment of the German study region, clustering of food retailers does not depend on the location of schools. Additionally, the results suggest that the consumption of junk food in young children is not influenced by spatial availability of unhealthy food. However, investigations should be replicated in other European communities to increase environmental variability.

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Kernel density approach. Kernel density of food retailer, i.e. number per km2, in the study area Delmenhorst.
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Figure 2: Kernel density approach. Kernel density of food retailer, i.e. number per km2, in the study area Delmenhorst.

Mentions: which is the inhomogeneous estimate of the mean number of food stores and restaurants ), in the study area . Each point is weighted by the kernel function depending on the bandwidth h[26]. Here, the kernel density-tool in ArcGIS 10 uses a quadratic kernel function , a bandwidth of h=1 km and a raster of 10 m*10 m cells , where the number l=1,…,L depends on the size of the study area W. The farther away a store or restaurant is located from a cell , the lower the weight given by the function . For a distance greater than the bandwidth, the weight is zero. For each cell, the weights of all stores within the bandwidth were summed up and standardized for square kilometers (see Equation (3)). Figure 2 shows the kernel density of supermarkets, food stores, and restaurants in the study region. The values of the kernel density represent the estimated number of food retailers per km2.


Clustering of unhealthy food around German schools and its influence on dietary behavior in school children: a pilot study.

Buck C, Börnhorst C, Pohlabeln H, Huybrechts I, Pala V, Reisch L, Pigeot I, IDEFICSI Family consort - Int J Behav Nutr Phys Act (2013)

Kernel density approach. Kernel density of food retailer, i.e. number per km2, in the study area Delmenhorst.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3686694&req=5

Figure 2: Kernel density approach. Kernel density of food retailer, i.e. number per km2, in the study area Delmenhorst.
Mentions: which is the inhomogeneous estimate of the mean number of food stores and restaurants ), in the study area . Each point is weighted by the kernel function depending on the bandwidth h[26]. Here, the kernel density-tool in ArcGIS 10 uses a quadratic kernel function , a bandwidth of h=1 km and a raster of 10 m*10 m cells , where the number l=1,…,L depends on the size of the study area W. The farther away a store or restaurant is located from a cell , the lower the weight given by the function . For a distance greater than the bandwidth, the weight is zero. For each cell, the weights of all stores within the bandwidth were summed up and standardized for square kilometers (see Equation (3)). Figure 2 shows the kernel density of supermarkets, food stores, and restaurants in the study region. The values of the kernel density represent the estimated number of food retailers per km2.

Bottom Line: Comparing the 95% confidence envelopes to the observed K-function, we showed that food stores and fast food restaurants do not significantly cluster around schools.Apart from this result, the food retail index showed no effect on BMI (β=0.01,p=0.11) or food intake variables assessed by FFQ and 24-HDR.In the built environment of the German study region, clustering of food retailers does not depend on the location of schools.

View Article: PubMed Central - HTML - PubMed

Affiliation: Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.

ABSTRACT

Background: The availability of fast foods, sweets, and other snacks in the living environment of children is assumed to contribute to an obesogenic environment. In particular, it is hypothesized that food retailers are spatially clustered around schools and that a higher availability of unhealthy foods leads to its higher consumption in children. Studies that support these relationships have primarily been conducted in the U.S. or Australia, but rarely in European communities. We used data of FFQ and 24-HDR of the IDEFICS study, as well as geographical data from one German study region to investigate (1) the clustering of food outlets around schools and (2) the influence of junk food availability on the food intake in school children.

Methods: We geocoded food outlets offering junk food (e.g. supermarkets, kiosks, and fast food restaurants). Spatial cluster analysis of food retailers around child-serving institutions was conducted using an inhomogeneous K-function to calculate global 95% confidence envelopes. Furthermore, a food retail index was implemented considering the kernel density of junk food supplies per service area, adjusted for residential density. We linked the food retail index to FFQ and 24-HDR data of 384 6- to 9-year-old school children in the study region and investigated the impact of the index on food intake, using multilevel regression models adjusted for sex, age, BMI, parent's education and income, as well as adjusting for over- and underreporting of food intake.

Results: Comparing the 95% confidence envelopes to the observed K-function, we showed that food stores and fast food restaurants do not significantly cluster around schools. Apart from this result, the food retail index showed no effect on BMI (β=0.01,p=0.11) or food intake variables assessed by FFQ and 24-HDR.

Conclusion: In the built environment of the German study region, clustering of food retailers does not depend on the location of schools. Additionally, the results suggest that the consumption of junk food in young children is not influenced by spatial availability of unhealthy food. However, investigations should be replicated in other European communities to increase environmental variability.

Show MeSH
Related in: MedlinePlus