Article (Scientific journals)
Stability-based validation of dietary patterns obtained by cluster analysis
Sauvageot, Nicolas; Schritz, Anna; Alkerwi, Ala'a et al.
2017In Nutrition Journal, 16 (3)
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Keywords :
Dietary patterns; Cluster analysis; Stability
Abstract :
[en] Abstract Background Cluster analysis is a data-driven method used to create clusters of individuals sharing similar dietary habits. However, this method requires specific choices from the user which have an influence on the results. Therefore, there is a need of an objective methodology helping researchers in their decisions during cluster analysis. The objective of this study was to use such a methodology based on stability of clustering solutions to select the most appropriate clustering method and number of clusters for describing dietary patterns in the NESCAV study (Nutrition, Environment and Cardiovascular Health), a large population-based cross-sectional study in the Greater Region (N = 2298). Methods Clustering solutions were obtained with K-means, K-medians and Ward’s method and a number of clusters varying from 2 to 6. Their stability was assessed with three indices: adjusted Rand index, Cramer’s V and misclassification rate. Results The most stable solution was obtained with K-means method and a number of clusters equal to 3. The “Convenient” cluster characterized by the consumption of convenient foods was the most prevalent with 46% of the population having this dietary behaviour. In addition, a “Prudent” and a “Non-Prudent” patterns associated respectively with healthy and non-healthy dietary habits were adopted by 25% and 29% of the population. The “Convenient” and “Non-Prudent” clusters were associated with higher cardiovascular risk whereas the “Prudent” pattern was associated with a decreased cardiovascular risk. Associations with others factors showed that the choice of a specific dietary pattern is part of a wider lifestyle profile. Conclusion This study is of interest for both researchers and public health professionals. From a methodological standpoint, we showed that using stability of clustering solutions could help researchers in their choices. From a public health perspective, this study showed the need of targeted health promotion campaigns describing the benefits of healthy dietary patterns.
Disciplines :
Public health, health care sciences & services
Author, co-author :
Sauvageot, Nicolas ;  Université de Liège - ULiège > Form. doct. sc. santé publique
Schritz, Anna
Alkerwi, Ala'a
Stranges, Saverio
Zannad, Faiez
Streel, Sylvie  ;  Université de Liège > Département des sciences de la santé publique > Santé publique : aspects spécifiques
Hoge, Axelle ;  Université de Liège > Département des sciences de la santé publique > Santé publique : aspects spécifiques
Donneau, Anne-Françoise ;  Université de Liège > Département des sciences de la santé publique > Biostatistique
Albert, Adelin  ;  Université de Liège > Département des sciences de la santé publique > Département des sciences de la santé publique
Guillaume, Michèle ;  Université de Liège > Département des sciences de la santé publique > Epidémiologie nutritionnelle
Language :
English
Title :
Stability-based validation of dietary patterns obtained by cluster analysis
Publication date :
14 January 2017
Journal title :
Nutrition Journal
eISSN :
1475-2891
Publisher :
Biomed central, London, United Kingdom
Volume :
16
Issue :
3
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 10 April 2017

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