Related Experiment Video
Updated: Aug 5, 2026
04:56
Assessment of Social Transmission of Food Preferences Behaviors
Published on: January 25, 2018
Conflict or Interest? Using consumer purchase data to support food systems transformation
Michelle A Morris1, Nilani Sritharan2, Alice Kininmonth1
1School of Food Science and Nutrition and Leeds Institute for Data Analytics, University of Leeds.
The Proceedings of the Nutrition Society
|July 27, 2026
Summary
Supermarket purchase data offers a novel way to monitor population diets for health and environmental benefits. Careful governance and collaboration are key to unlocking insights from this smart data for a sustainable food system.
Area of Science:
- Public Health Nutrition
- Environmental Sustainability
- Data Science and AI
Background:
- Population dietary behaviors significantly impact global challenges like noncommunicable diseases, climate change, and food insecurity.
- Aligning diets with national guidelines (e.g., UK Eatwell Guide) offers co-benefits for health and environmental sustainability.
- Scalable and timely dietary monitoring methods are crucial for accelerating progress.
Purpose of the Study:
- To review the use of routinely generated smart data, specifically supermarket transaction and loyalty card records, for population-level dietary assessment.
- To highlight methodological challenges and opportunities in deriving nutrition, health, and sustainability insights from consumer purchase data.
- To provide recommendations for future research utilizing consumer purchasing data to strengthen evidence generation for food system transformation.
Main Methods:
- Review of academic and industry insights on utilizing novel data sources like supermarket transaction records.
- Analysis of challenges in computational infrastructure, data science, AI, and nutrition interpretation for smart data.
- Examination of governance and data security challenges associated with commercial sales data.
Main Results:
- Supermarket transaction data provides objective, high-resolution, near real-time information on food purchasing behaviors.
- These datasets enable the evaluation of natural experiments within real-world food environments.
- Effective utilization requires advanced computational capabilities and specialist nutrition interpretation, alongside robust data governance.
Conclusions:
- Consumer purchase data, when appropriately governed, can complement traditional dietary assessment methods.
- Strong collaborative partnerships between industry and academia, supported by champions in both sectors, are essential for effective data sharing.
- This approach can support the transformation of the wider food system for improved population and planetary health.
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