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. 2021 Apr 27;13(5):1481.
doi: 10.3390/nu13051481.

Dietary Patterns Derived from UK Supermarket Transaction Data with Nutrient and Socioeconomic Profiles

Stephen D Clark  1 , Becky Shute  2 , Victoria Jenneson  1 , Tim Rains  2 , Mark Birkin  1 , Michelle A Morris  3
Affiliations

Dietary Patterns Derived from UK Supermarket Transaction Data with Nutrient and Socioeconomic Profiles

Stephen D Clark et al. Nutrients. .

Abstract

Poor diet is a leading cause of death in the United Kingdom (UK) and around the world. Methods to collect quality dietary information at scale for population research are time consuming, expensive and biased. Novel data sources offer potential to overcome these challenges and better understand population dietary patterns. In this research we will use 12 months of supermarket sales transaction data, from 2016, for primary shoppers residing in the Yorkshire and Humber region of the UK (n = 299,260), to identify dietary patterns and profile these according to their nutrient composition and the sociodemographic characteristics of the consumer purchasing with these patterns. Results identified seven dietary purchase patterns that we named: Fruity; Meat alternatives; Carnivores; Hydrators; Afternoon tea; Beer and wine lovers; and Sweet tooth. On average the daily energy intake of loyalty card holders -who may buy as an individual or for a household- is less than the adult reference intake, but this varies according to dietary purchase pattern. In general loyalty card holders meet the recommended salt intake, do not purchase enough carbohydrates, and purchase too much fat and protein, but not enough fibre. The dietary purchase pattern containing the highest amount of fibre (as an indicator of healthiness) is bought by the least deprived customers and the pattern with lowest fibre by the most deprived. In conclusion, supermarket sales data offer significant potential for understanding population dietary patterns.

Keywords: big data; dietary assessment; dietary patterns; nutrients; nutrition analytics; socioeconomic; transaction data.

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Conflict of interest statement

M.A.M. is an inventor and shareholder at Dietary Assessment Ltd., but receives no financial income, and is not involved in the running of the company. B.S. and T.R. are employees at Sainsbury’s.

Figures

Figure A1
Figure A1
Fruity (n = 57,232).
Figure A2
Figure A2
Meat Alternatives (n = 61,065).
Figure A3
Figure A3
Carnivores (n = 49,923).
Figure A4
Figure A4
Hydrators (n = 22,804).
Figure A5
Figure A5
Afternoon tea (n = 41,309).
Figure A6
Figure A6
Beer and wine lovers (n = 35,486).
Figure A7
Figure A7
Sweet tooth (n = 31,441).
Figure 1
Figure 1
Characteristics of our loyalty card holders.
Figure 2
Figure 2
(A) Scree plot and (B) change in within group sum of square for identifying number of dietary patterns.
Figure 3
Figure 3
Summary of the dietary pattern contents. Please see Appendix A for more details.
Figure 4
Figure 4
Distribution of groups of loyalty card holders amongst Index of Multiple Deprivation (IMD) deciles.
Figure 5
Figure 5
Distribution of groups of loyalty card holders amongst Output Area Classification (OAC) Super Groups.
See this image and copyright information in PMC

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