The Impact of Non-Price In-premise Marketing on Food and Beverage Purchasing and Consumer Behaviour: A Systematic Review
Whitehead, R.; Greci, S.; Thomson, H.; Armour, G.; Angus, K.; Martin, L.
Show abstract
In-premise marketing is commonly used to promote foods that are high in fat, sugar or salt. In order to inform development of public policy in this area, this systematic review sought to determine the quantity and quality of English-language evidence which examines the role and impact of in-premise advertising (e.g., signage, posters) and positional promotions (e.g., checkout displays) on consumer behaviour and diet-related outcomes in retail, out-of-home (i.e., cafes, restaurants, takeaways) and online purchasing environments. Sixty-two studies met inclusion criteria, of which 69% (n=42) were identified as being methodologically weak. The best-available evidence constitutes findings from four methodologically strong studies, and ten moderate studies which are not confounded by additional promotions such as price or availability. These studies predominantly found evidence that in-premise marketing is likely to be successful in influencing consumer behaviour towards targeted items, across retail and out-of-home settings. These findings provide a basis for authorities to consider acting to restrict in-premise marketing of unhealthy foods and encouraging the in-premise marketing of healthier products. This review identified gaps in the evidence available on non-sales outcomes, and on online purchase environments. These gaps, and identified methodological limitations of the extant evidence remain to be addressed by future research.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Estimating the lagged effect of price discounting: a time-series study using transaction data of sugar sweetened beverages 95%
- Assessing the impact of a mandatory calorie labelling policy in out-of-home food outlets in England on consumer behaviour: a natural experimental study 94%
- A mixed methods study evaluating food insecurity and diet quality in households accessing food aid in England 92%
Similar papers in this journal
- Wearable Sensing in Eating Episode Monitoring: An Updated Systematic Review Protocol 92%
- Unpacking the behavioural components and delivery features of early childhood obesity prevention interventions in the TOPCHILD Collaboration: a systematic review and intervention coding protocol 91%
- Examining the associations between the food environment and dietary intake in British Columbia: A cross-sectional study 90%
Similar papers in this journal
- Self-reported decreases in the purchases of selected unhealthy foods resulting from the implementation of warning labels in Mexican youth and adult population 92%
- The impact of deprivation and neighbourhood food environments on home food environments, parental feeding practices, and child eating behaviours, food preferences and BMI: The Family Food Experience Study-London 92%
- Calorie reformulation: A systematic review and meta-analysis examining the effect of manipulating food energy density on daily energy intake and body weight 92%
Similar papers in this journal
- Implementation and enforcement of mandatory calorie labelling regulations for the out-of-home sector in England: qualitative study of the experiences of business implementers and regulatory enforcers 93%
- Monitoring sodium content in packaged foods sold in the Americas and compliance with the Updated Regional Sodium Reduction Targets 92%
- Weight-normative messaging predominates on TikTok – a qualitative content analysis 91%
Similar papers in this journal
- Preventing childhood obesity primary schools: a realist review from UK perspective 92%
- Impostor Phenomenon in the Nutrition and Dietetics Profession: An Online Cross-Sectional Survey 90%
- Can a greenhouse gas emissions tax on food also be healthy and equitable? A systematized review and modelling study from Aotearoa New Zealand 89%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.