Food purchase behaviour in a Finnish population: patterns, carbon footprints and expenditures

Abstract

Objective: To identify food purchase patterns, and to assess their carbon footprint and expenditure. Design: Cross-sectional. Setting: Purchase patterns were identified by factor analysis from the annual purchases of 3435 product groups. The associations between purchase patterns and the total purchases’ carbon footprints (based on life-cycle assessment) and expenditure were analyzed using linear regression and adjusted for nutritional energy content of the purchases. Participants: Loyalty card holders (n=22,860) of the largest food retailer in Finland. Results: Eight patterns explained 55% of the variation in food purchases. The Animal-based pattern made the greatest contribution to the annual carbon footprint, followed by the Easy-cooking, and Ready-to-eat patterns. High-energy, Traditional, and Plant-based patterns made the smallest contribution to the carbon footprint of the purchases. Animal-based, Ready-to-eat, Plant-based, and High-energy patterns made the greatest contribution whereas the Traditional, and Easy-cooking pattern made the smallest contribution to food expenditure. Carbon footprint per euros spent increased with stronger adherence to the Traditional, Animals-based, and Easy-cooking patterns. Conclusions: The Animal-based, Ready-to-eat, and High-energy patterns were associated with relatively high expenditure on food, suggesting no economic barrier to a potential shift towards a plant-based diet for consumers adherent to those patterns. Strong adherence to the Traditional pattern resulted in a low energy-adjusted carbon footprint but high carbon footprint per euro. This suggests a preference for cheap nutritional energy rather than environment-conscious purchase behavior. Whether a shift towards a plant-based pattern would be affordable for those with more traditional and cheaper purchase patterns requires more research.

Examining consumer food waste through grocery retailers' customer data: Segments and practical implications

“…Customer data that are complemented with appropriate information can provide unique empirical access to study many contemporary challenges, such as obesity, malnutrition, or unsustainable diets. Furthermore, using customer data for research purposes can uncover new opportunities––for example, studying health (e.g., Aiello et al, 2019; Nevalainen et al, 2018), alcohol consumption (Lintonen et al, 2020), sustainable food purchasing (Erkkola et al, 2022; Meinilä et al, 2022), and nicotine replacements (Timberlake et al, 2019)––and thus, direct attention towards using customer data to benefit individuals and society at large (Hermann, 2022; Saarijärvi et al, 2019). While there seems to be increasing interest in examining tensions revolving around collecting, analysing, and leveraging customer data in retailing (see Krafft et al, 2021; Martin & Palmatier, 2020; Wieringa et al, 2021), harnessing data's potential to benefit society through scientific research can increase customers' willingness to continue to share their data.…”

Tensorial Principal Component Analysis in Detecting Temporal Trajectories of Purchase Patterns in Loyalty Card Data: Retrospective Cohort Study

“…A traditional Finnish diet is characterized by sausages, potatoes, milk, coffee, and butter [53]. A ready-to-eat pattern has also often been identified, characterized by a high consumption of ready-to-eat meals [51,54]. Similarly, a pattern indicating alcohol consumption has been identified previously in Finland [55].…”

“…Traditional PCA has been widely used for nutrition data among different settings, cultures, and sociodemographic groups. Although the naming of the patterns and the foods loading to the components may vary slightly, typically at least 2 common patterns are identified in most countries, as in Finland: a prudent, healthy dietary pattern and an unhealthy "Western" pattern [47][48][49][50][51]. A third, almost equally typical pattern is often termed "traditional" [52], and this pattern is generally more context specific.…”

“…The use of grocery purchase data for health research purposes is still relatively novel, and, to the best of our knowledge, only a few earlier studies have identified dietary patterns based on customer loyalty card data. One such study was conducted in the United Kingdom [3], whereas the other is an earlier study conducted by our group [51]. Both studies used the standard PCA method for analysis.…”

Consumer resistance diminishes environmental gains of dietary change

“…Several studies have used food affordability to determine the preferable scope of, and barriers to, a sustainable dietary transition, in individual countries [27][28][29], and globally [26,30,31]. Coupling food expenditure data and nutritional energy of food items, Meinilä and colleagues [32] derive food consumption archetypes of consumers towards this end. Kramer and colleagues [33] ascribe popularity to foodstuffs based on their current intake levels by consumer sub-groups.…”