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Exploring the use of supermarket loyalty card data in health research: A scoping review
R Burgess1, A Suhag1, A Skatova1
1Digital Footprints Lab & Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Population Health Sciences, Bristol Medical School, University of Bristol, UK.
Objectives:
As loyalty cards gain popularity, their role in population health research is expanding. This scoping review examines the use of supermarket loyalty card data for health research, synthesising existing literature to explore: (1) types of loyalty card data analysed, (2) health outcomes studied, and (3) advantages and limitations of loyalty card data.
Study Design:
We used a scoping review to address the research questions.
Methods:
Four electronic databases (MEDLINE, EMBASE, PsycINFO, and Scopus) were searched. Studies were included if they used loyalty card data from major supermarkets to investigate health-related outcomes. Two researchers independently screened studies, extracting data on population characteristics, loyalty card and product details, health outcomes, and advantages and limitations. Findings were synthesised using a narrative approach.
Results:
We identified 44 studies using various loyalty schemes. Most studies focused on grocery products, categorised either by pre-defined criteria (e.g., nutritional value) or product groups (e.g., fruit and vegetables). Health outcomes primarily addressed diet and nutrition, with several studies examining interventions and sociodemographic inequalities. Other studies evaluated responses to government campaigns or tracked medication use. Advantages of loyalty cards included large-scale, objective data collection and individual-, household- and population-level insights. Challenges included missing purchasing activity (e.g., from not using a card), difficulties with linking purchases to nutritional information, and the over-representation of certain demographic groups.
Conclusion:
Future research should expand data integration (e.g., linking with health records), explore novel dietary research areas, and refine analytical methodologies (e.g., probabilistic product matching) to maximise the use of loyalty card data in health research.
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