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Cluster analysis of fruit and vegetable‐related perceptions: an alternative approach of consumer segmentation

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Abstract:



How to cite this article Simunaniemi A.‐M., Nydahl M. & Andersson A. (2012) Cluster analysis of fruit and vegetable related perceptions: an alternative approach of consumer segmentation. J Hum Nutr Diet. 26, 38–47
Abstract

Background:  Audience segmentation optimises health communication aimed to promote healthy dietary habits, such as fruit and vegetable (F&V) consumption. The present study aimed to segment respondents into clusters based on F&V‐related perceptions, and to describe these clusters with respect to F&V consumption and sex.

Methods:  The cross‐sectional study was conducted using a semi‐structured questionnaire. The respondents were randomly selected among Swedish adults (n = 1304; response rate 51%; 56% women). A two‐step cluster analysis was conducted followed by a binary logistic regression with cluster membership as a dependent variable. The clusters were compared using t‐tests and chi‐squared tests. P < 0.05 (two‐sided) was considered statistically significant. The respondents’ open‐ended answers of determinants of F&V consumption were used as a descriptive support for the conducted multivariate analysis.

Results:  Of the two identified clusters, the Positive cluster (n = 476) was older and consumed more vegetables (both sexes) and fruit (women only), whereas men in the Indifferent cluster (n = 715) consumed more juice. Indifferent cluster reported more F&V consumption preventing factors, such as storage and preparation difficulties and low satisfaction with F&V selection and price. Not liking or not having a habit of F&V consumption, laziness, forgetting and a lack of time were mentioned as main barriers to F&V consumption.

Conclusions:  The Indifferent cluster reports more practical and life‐style related difficulties. The Positive cluster consumes more vegetables, perceives fewer F&V‐related difficulties, and looks for more dietary information. The findings confirm that cluster analysis is an appropriate way of identifying consumer subgroups for targeted health and nutrition communication.

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1365-277X.2012.01272.x

Affiliations: Department for Food, Nutrition and Dietetics, University of Uppsala, Uppsala, Sweden

Publication date: February 1, 2013

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