Identification and Profiling of Socioeconomic and Health Characteristics Associated with Consumer Food Purchasing Behaviours Using Machine Learning

Authors

Daniel Burke, Technological University DublinFollow
Martin Boudou, Technological University DublinFollow
Jennifer McCarthy, Technological University DublinFollow
Majid Bahramian, Technological University DublinFollow
Courage Krah, Technological University DublinFollow
Christina Kenny, Technological University DublinFollow
Paul Hynds, Technological University DublinFollow
Anushree Priyadarshini, National University of Ireland, MaynoothFollow

Author ORCID Identifier

0000-0003-1418-4026

Document Type

Article

Disciplines

Public and environmental health, Nutrition, Dietetics

Publication Details

https://www.sciencedirect.com/science/article/abs/pii/S0950329324003197

https://doi.org/10.1016/j.foodqual.2024.105417

Abstract

Food systems and food-related policies influence food consumption, dietary patterns, and human and environmental health. Consumers play a vital role in enhancing health and sustainability through their purchasing choices. To identify and cluster food purchasing behaviours and map relationships, a cross-sectional survey was conducted across Ireland with a sample size of 957 adults. Two-step cluster analysis, generalised linear models, and recursive partitioning and regression trees were used to elucidate adherence to identified food purchasing behavioural clusters. Three clusters (‘food quality’, ‘taste’, and ‘price’) were identified based on food purchasing priorities and statistically categorised. ‘Food quality’ members were significantly less likely categorically obese (OR = 0.32) and more likely to have a postgraduate degree (OR = 1.59–1.76). ‘Taste’ members were almost twice as likely to be classified as obese (OR = 1.96), have/had diabetes (OR = 2.24), and have secondary-level education as their highest level of attainment (OR = 1.73). ‘Price’ members had the highest mean body mass index (28.03 kg/m2 ), were more likely younger (25–34 years) (OR = 1.43) and were more likely to have lower annual household income (

DOI

https://doi.org/10.1016/j.foodqual.2024.105417

Recommended Citation

Burke, Daniel; Boudou, Martin; McCarthy, Jennifer; Bahramian, Majid; Krah, Courage; Kenny, Christina; Hynds, Paul; and Priyadarshini, Anushree, "Identification and Profiling of Socioeconomic and Health Characteristics Associated with Consumer Food Purchasing Behaviours Using Machine Learning" (2024). Articles. 65.
https://arrow.tudublin.ie/buschmanart/65

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