2026/07/27 by Michelle A Morris, Nilani Sritharan, Alice Kininmonth +3
paper · doi:10.1017/s0029665126105345
Abstract Population dietary behaviours have considerable impact on major global challenges including dietrelated noncommunicable diseases, climate change, and food insecurity. Aligning diets with national recommendations, such as the UK Eatwell Guide, have the potential to deliver substantial cobenefits for health and environmental sustainability. To accelerate progress, scalable and timely methods for monitoring dietary patterns are required. Routinely generated smart data, such as supermarket transaction records and loyalty card purchases, represent a novel resource for populationlevel dietary assessment. These datasets provide objective, high-resolution, and near real-time information on food purchasing behaviours. However, deriving meaningful nutrition insights from such data necessitates advanced computational infrastructure, data science and AI capability, and specialist nutrition interpretation. Importantly, these data enable evaluation of natural experiments in realworld food environments. The use of commercial sales data introduces unique governance and datasecurity challenges. Commercial sensitivity requires robust securedata environments, transparent processes, and strong collaborative partnerships between industry and academia. Effective data sharing is contingent on champions within both sectors, as such collaboration is not yet routine. When appropriately governed, consumer purchase data can complement traditional dietary assessment methods and support transformation of the wider food system. This review paper presents academic and industry insights on the use of these novel data sources, highlighting methodological challenges associated with nutrition, health and sustainability metrics. It concludes with recommendations to guide future research employing consumer purchasing data to strengthen evidence generation across the food and population and planetary health landscape.