A copula-based clustering algorithm to analyse EU country diets

•A novel copula-based clustering algorithm is suggested to group EU countries.•Average calories of different food aggregates are used as segmentation variables.•Complex multivariate associations in Countries dietary structures are identified.•Changes towards a (un)common (un)healthier food dietary s...

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Published inKnowledge-based systems Vol. 132; pp. 72 - 84
Main Authors Di Lascio, F.Marta L., Disegna, Marta
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 15.09.2017
Elsevier Science Ltd
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Online AccessGet full text
ISSN0950-7051
1872-7409
1872-7409
DOI10.1016/j.knosys.2017.06.004

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Abstract •A novel copula-based clustering algorithm is suggested to group EU countries.•Average calories of different food aggregates are used as segmentation variables.•Complex multivariate associations in Countries dietary structures are identified.•Changes towards a (un)common (un)healthier food dietary structure are investigated.•Countries at risk of an increase in obesity and diet-related disease are identified. The aim of the paper is to explore the evolution of food diets in 40 European countries according to the common European policies and guidelines on healthy diets. To this end, an innovative clustering method, called CoClust, has been adopted. By means of the copula function, this algorithm is able to find clusters based on the complex multivariate dependence structure of the data generating process, overcoming the limits of classical approaches that cope with only linear bivariate relationships. The analysed database contains information on the average calories from 16 food aggregates in 40 European countries observed over 40 years by the Food and Agriculture Organisation of the United Nations (FAO). Our findings suggest that European country diets are changing, individually or as a group, but not in a unique direction. Central and Eastern European countries are becoming unhealthier, while the tendency followed by the majority of the remaining countries is to integrate the common European guidelines on healthy, balanced, and diversified diets in their national policies.
AbstractList The aim of the paper is to explore the evolution of food diets in 40 European countries according to the common European policies and guidelines on healthy diets. To this end, an innovative clustering method, called CoClust, has been adopted. By means of the copula function, this algorithm is able to find clusters based on the complex multivariate dependence structure of the data generating process, overcoming the limits of classical approaches that cope with only linear bivariate relationships. The analysed database contains information on the average calories from 16 food aggregates in 40 European countries observed over 40 years by the Food and Agriculture Organisation of the United Nations (FAO). Our findings suggest that European country diets are changing, individually or as a group, but not in a unique direction. Central and Eastern European countries are becoming unhealthier, while the tendency followed by the majority of the remaining countries is to integrate the common European guidelines on healthy, balanced, and diversified diets in their national policies.
•A novel copula-based clustering algorithm is suggested to group EU countries.•Average calories of different food aggregates are used as segmentation variables.•Complex multivariate associations in Countries dietary structures are identified.•Changes towards a (un)common (un)healthier food dietary structure are investigated.•Countries at risk of an increase in obesity and diet-related disease are identified. The aim of the paper is to explore the evolution of food diets in 40 European countries according to the common European policies and guidelines on healthy diets. To this end, an innovative clustering method, called CoClust, has been adopted. By means of the copula function, this algorithm is able to find clusters based on the complex multivariate dependence structure of the data generating process, overcoming the limits of classical approaches that cope with only linear bivariate relationships. The analysed database contains information on the average calories from 16 food aggregates in 40 European countries observed over 40 years by the Food and Agriculture Organisation of the United Nations (FAO). Our findings suggest that European country diets are changing, individually or as a group, but not in a unique direction. Central and Eastern European countries are becoming unhealthier, while the tendency followed by the majority of the remaining countries is to integrate the common European guidelines on healthy, balanced, and diversified diets in their national policies.
Author Di Lascio, F.Marta L.
Disegna, Marta
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Keywords Coclust
EU countries
Clustering
Dietary energy
Healthy diet
Convergence
Language English
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Snippet •A novel copula-based clustering algorithm is suggested to group EU countries.•Average calories of different food aggregates are used as segmentation...
The aim of the paper is to explore the evolution of food diets in 40 European countries according to the common European policies and guidelines on healthy...
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SubjectTerms Algorithms
Bivariate analysis
Clustering
Coclust
Convergence
Diet
Dietary energy
EU countries
Guidelines
Health promotion
Healthy diet
Policies
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Title A copula-based clustering algorithm to analyse EU country diets
URI https://dx.doi.org/10.1016/j.knosys.2017.06.004
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http://eprints.bournemouth.ac.uk/26586/1/BAFES04.pdf
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