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Altering product placement to create a healthier layout in supermarkets: Outcomes on store sales, customer purchasing, and diet in a prospective matched controlled cluster study

['Christina Vogel', 'Medical Research Council Lifecourse Epidemiology Unit', 'University Of Southampton', 'Southampton General Hospital', 'Southampton', 'United Kingdom', 'Nihr Southampton Biomedical Research Centre', 'University Hospital Southampton Nhs Foundation Trust', 'Sarah Crozier', 'Daniel Penn-Newman']

Date: 2021-09

This is a prospective matched controlled cluster trial with 2 intervention components: (i) new fresh fruit and vegetable sections near store entrances (replacing smaller displays at the back) and frozen vegetables repositioned to the entrance aisle, plus (ii) the removal of confectionery from checkouts and aisle ends opposite. In this pilot study, the intervention was implemented for 6 months in 3 discount supermarkets in England. Three control stores were matched on store sales and customer profiles and neighbourhood deprivation. Women customers aged 18 to 45 years, with loyalty cards, were assigned to the intervention (n = 62) or control group (n = 88) of their primary store. The trial registration number is NCT03518151. Interrupted time series analysis showed that increases in store-level sales of fruits and vegetables were greater in intervention stores than predicted at 3 (1.71 standard deviations (SDs) (95% CI 0.45, 2.96), P = 0.01) and 6 months follow-up (2.42 SDs (0.22, 4.62), P = 0.03), equivalent to approximately 6,170 and approximately 9,820 extra portions per store, per week, respectively. The proportion of purchasing fruits and vegetables per week rose among intervention participants at 3 and 6 months compared to control participants (0.2% versus −3.0%, P = 0.22; 1.7% versus −3.5%, P = 0.05, respectively). Store sales of confectionery were lower in intervention stores than predicted at 3 (−1.05 SDs (−1.98, −0.12), P = 0.03) and 6 months (−1.37 SDs (−2.95, 0.22), P = 0.09), equivalent to approximately 1,359 and approximately 1,575 fewer portions per store, per week, respectively; no differences were observed for confectionery purchasing. Changes in dietary variables were predominantly in the expected direction for health benefit. Intervention implementation was not within control of the research team, and stores could not be randomised. It is a pilot study, and, therefore, not powered to detect an effect.

Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests:No funding was received from the supermarket involved in this study and all analyses were conducted independently, without involvement of supermarket staff. CV, SC, DPN, KB, GM and JL have no conflicts of interest to declare. JB has received grant research support from Danone Nutricia Early Life Nutrition. CC has has received consultancy, lecture fees and honoraria from AMGEN, GKS, Alliance for Better Bone Health, MSD, Eli Lilly, Pfizer, Novartis, Servier, Medtronic and Roche. The study described in this manuscript is not related to these conflicted relationships.

Funding: This research and the authors of this paper are supported by the following funding sources: The Academy of Medical Sciences and Wellcome Trust (grant to CV: HOP001\1067, acmedsci.ac.uk); Faculty of Medicine, University of Southampton (fellowship to CV: PCTA36/2015, grant to CV, JB: RMC1516-12, www.southampton.ac.uk/about/departments/faculties/medicine.page ); National Institute for Health Research (NIHR) Southampton Biomedical Research Centre, University of Southampton (grant to CV, JB: NBRC RS4h, www.uhs.nhs.uk/ClinicalResearchinSouthampton/Home.aspx ); Medical Research Council (quinquennial grant to CC, JB, mrc.ukri.org ); National Health and Medical Research Council (NHMRC) (fellowship to KB, www.nihr.ac.uk ). The views expressed in this publication are those of the author(s) and not necessarily those of the research funders. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability: Data cannot be shared publicly because of the conditions of the agreement with the commercial collaborator. Data collected by the research team are available from the MRC Lifecourse Epidemiology Unit Data Manager ( [email protected] ) for researchers who meet the criteria for access to confidential data.

Copyright: © 2021 Vogel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

This study will help to address current evidence gaps regarding the use of prominent placement strategies to support improvements in population diet. It aims to assess whether creating a healthier layout in discount supermarkets in England improves the healthiness of store sales (primary outcome) and the purchasing and dietary behaviours of women customers aged 18 to 45 years (secondary outcomes) after 3 and 6 months. To our knowledge, this study is unique in its analysis of individual loyalty card data, in addition to store sales data, as well as collecting dietary data from more than 1 family member [ 13 , 26 ]. The study also evaluated possible cost implications of the intervention from individual and retailer perspectives.

While many supermarkets do place fresh fruits and vegetables in a position that customers encounter when first entering the store, a number of discount and small supermarket chains do not routinely place fruits and vegetables near the store entrance. UK research shows that discount and small supermarkets have less healthy environments than other UK supermarkets, including lower availability and less prominent placement of fresh fruits and vegetables [ 20 ]. These poorer in-store environments may be contributing to dietary inequalities because families experiencing disadvantage and younger adults, known to have poorer quality diets, frequently rely on these stores for their food [ 21 , 22 ]. Retail intervention studies in the United States have shown promising effects on food purchasing habits among low-income, minority groups when fresh fruit and vegetable displays were moved to the front of the store [ 23 , 24 ]. Evaluation of the effects of such a strategy, in combination with the removal of confectionery from checkouts, is needed and could inform future government policy.

Previous studies testing the effect of “healthier checkouts” in supermarkets, which placed healthier snack items alongside or at alternate checkouts to unhealthy snacks, have shown limited success at reducing sales of unhealthy food and beverages [ 16 – 18 ]. Few supermarket trials have tested the effects of removing unhealthy products from all checkouts, and none, to our knowledge, have additionally tested the effects of removing unhealthy products from all the end-of-aisle displays opposite checkouts. Furthermore, little prior research has considered the impact of replacing unhealthy food products at checkout areas with nonfood items in an effort to restrict opportunities for impulsive calorie purchases while aiming to preserve impulse expenditure. Positioning products near the store entrance is another prominent placement strategy used by supermarkets to tempt customers [ 19 ].

In an effort to curb the influence of unhealthy marketing tactics on population diet, the UK government announced their intention to ban the use of prominent placement strategies for unhealthy food and drink products in supermarkets and other outlets [ 14 ]. This proposal forms part of the national strategy to address childhood obesity [ 15 ]. There is a pressing need for further evidence from local, well-designed intervention studies aimed at testing the effect, and cost impact, of healthier product placement strategies. Such evidence could assist UK policy makers appropriately frame the proposed ban, as well as help guide future government intervention to improve diet across the world.

Obesity and poor diet constitute 2 of the greatest threats to the population health [ 1 , 2 ]. They are costly to society [ 3 ] and disproportionately affect those who are socioeconomically disadvantaged [ 4 ]. The importance of improving population diet is ever more apparent with obesity and poor diet emerging as key risk factors for a severe response to the Coronavirus Disease 2019 (COVID-19) infection, particularly among adults aged under 65 years [ 5 , 6 ]. Most families rely on supermarkets for their food [ 7 ]; during COVID-19 lockdown, this reliance increased [ 8 ]. Such dependence on supermarkets as a primary food source makes them an appropriate setting for interventions to improve dietary behaviours. Despite online grocery sales increasing from 7% to 10% of the United Kingdom market recently [ 9 ], the majority of sales occur in-store where customers are exposed to marketing techniques that attempt to influence their food choices and preferences [ 10 , 11 ]. Product placement is one marketing technique used in supermarkets that predominantly promotes unhealthy food and beverage choices. For example, in the UK, two-thirds of all food and drink products placed in prominent in-store locations, such as checkouts, store entrances, end of aisles, and freestanding display units, have been found to be sugary or calorie-dense, ultraprocessed products; less than 1% of food products positioned in these prominent supermarket locations were fruits or vegetables [ 12 ]. This finding is a concern for population health, with growing evidence that these placement strategies can prompt customers to buy these unhealthy products [ 13 ].

2. Methodology

2.1 Study design and setting This was a pilot study with a prospective matched controlled cluster design, with participants clustered within 6 study supermarkets to account for the store-based intervention. The flow diagram, Fig A in S1 File, illustrates the time frame of store sales, participant purchasing dietary data collection. The study, which took place between April 2016 and March 2017, was approved by the University of Southampton, Faculty of Medicine Ethics Committee (ID 20986.A2) and was conducted in accordance with the Declaration of Helsinki and data protection regulations; it was registered with ClinicalTrials.gov (NCT03518151, pre-results). The setting for this study was stores of a discount supermarket chain located in more socioeconomically deprived neighbourhoods (within the most deprived 5 Index of Multiple Deprivation (IMD) deciles [27]) across England. The collaborating supermarket has over 900 stores nationwide and holds approximately 2% of the grocery market share in the UK [28]. This pilot study sampled 6 stores, 3 intervention and 3 control stores. The number of stores included was determined by the refurbishment schedule of the supermarket chain. Recruitment of additional stores and randomisation of stores were not viable within the company’s business model; intervention stores were selected because structural changes to their in-store environment had already been planned at the time of the study by the company, had an average sales profile, and were located in areas with higher neighbourhood deprivation. Control stores were matched to an intervention store based on (i) sales profile; (ii) customer profile; and (iii) neighbourhood deprivation (IMD). Matching on these factors aimed to increase the similarity of intervention and control stores and reduce the effects of confounding. Control stores were geographically distant from intervention stores to reduce contamination effects of control women shopping at intervention stores.

2.2 Intervention and control conditions The intervention was implemented continuously for 6 months and had 2 components executed simultaneously: (i) more prominent placement of fruits and vegetables; and (ii) removal of unhealthy foods from checkouts and the end-of-aisle opposite checkouts. The first intervention component involved expanding the produce section to increase the availability of fresh fruits and vegetables and positioning the produce near the store entrance. Frozen vegetables were also relocated to the first aisle, a more prominent position in store. All unhealthy foods (confectionery, crisps, biscuits, etc.), but predominantly confectionery (chocolate, sweets, or candy), were removed from all checkouts and displays at the end-of-aisle opposite checkouts and replaced with nonfood items (i.e., tissues, painkillers, lip balm, cleansing wipes, toothpaste, soap, deodorant, and hand wash), water, and sugar-free gum. One intervention store also positioned some fresh fruits and vegetables at the checkouts because of the size and shape of the checkout display unit. In each intervention store, the confectionery section was moved to the least prominent position, the last aisle of the store. Seasonal confectionery (i.e., Easter, Christmas, Mother’s/Father’s Day, Valentine’s Day, and Halloween) and branded confectionery for which marketing space was already paid was positioned at the store entrance and in freestanding displays in the aisles but not at the checkouts or end-of-aisle opposite checkouts during the intervention period. Intervention stores also underwent improvements in presentation (e.g., cleaning, painting, and updated signage) at the time the intervention was implemented. The control condition was the previous layout of stores, as at the baseline period, with (i) a limited range of fresh fruits and vegetables, placed at the back of the store; (ii) frozen vegetables placed in a middle aisle of the store; and (iii) confectionery placed at the checkouts and the confectionery section positioned at end-of-aisle opposite checkouts.

2.3 Participant eligibility and recruitment Women of childbearing age were targeted for this intervention because of their role as household food gatekeepers [29] and their influence on the short-and long-term health of the next generation [30]. For the children of these women, establishing good dietary habits early in life is important for optimal growth, development, and long-term health [31]. Eligible participants were women, aged 18 to 45 years, who held a loyalty card with the study supermarket chain and had shopped in a study store in the 12 weeks before recruitment (according to loyalty card data). Women under the age of 18 or over 45 years at the time of the study who did not hold a loyalty card or only shopped online were not eligible to participate. Recruitment occurred in 3 waves between July and September 2016. Women from each pair of stores were recruited over the same period, prior to the implementation period for that intervention store. Eligible women in all 6 study stores, identified from the loyalty card register, were sent a letter inviting them to participate in a study that was investigating the food shopping and eating patterns of women aged 18 to 45 years. The letter did not contain details about the intervention. The letter was sent by the supermarket on behalf of the research team in order to comply with data protection laws. Interested women contacted the research team directly via freephone number, text, or email and were screened for eligibility and then provided informed consent. In addition to being mailed a letter, participants in the first pair of stores were initially contacted by the supermarket via email and text message, and advertisements about the study were placed on the back of shopping receipts and on Facebook. These additional recruitment methods, however, yielded very little interest from participants and were thus phased out over the duration of the study. In order to boost participant numbers in the first pair of stores, in-store recruitment was used, whereby members of the research team approached women customers while shopping and provided them with a study information sheet. Interested women registered with the researcher in-store and were subsequently phoned and consented. This method proved effective at enhancing representation of disadvantaged customers and was used for all 6 study stores. To promote retention, all participants were offered up to 3× £10 Love2Shop vouchers for taking part in the study. For comparison, the national minimum living wage rate for adults over 25 years in 2016 was £7.20/hour. Love2Shop vouchers are multioption vouchers that can be used at 150 leading high street retailers, which span a range of retail categories.

2.4 Outcome measures The data collected included 9 months continuous store sale transaction data (primary outcome) and participant loyalty card data (secondary outcome) provided by the collaborating supermarket to cover 3 time periods: time (1) baseline (3 months prior to intervention implementation; time (2) short-term intervention effects (0 to 3 months postintervention commencement because evidence suggests that this represents an appropriate interval for habit formation [32]; and time (3) longer-term intervention effects (3 to 6 months postintervention commencement to assess sustained behavioural changes). In order to obtain an understanding of intervention effects on household members’ diets (secondary outcomes), interview-administered telephone questionnaires obtained information about participants’ diets and diets of their children aged 2 to 6 years (where applicable) at 3 time points: baseline (time 1) and 3 (time 2) and 6 months (time 3) following intervention commencement. Store sales of fresh fruits and vegetables, frozen vegetables, confectionery, and intervention checkout items were provided as numbers of items for each product sold in each week of the study period. Participant purchasing data covering the same categories were provided as the number of items for each product purchased at each store visit during the study period. The research team aggregated these purchasing data from each visit to a weekly structure for analysis to enable our data to be presented as items per household per week in order to be able to detect changes in visit frequency as well as purchasing quantity, a method used in previous supermarket trials [33,34]. Store closure for structural changes to intervention stores affected 2 weeks of sales and purchasing data; these 2 weeks of data were removed from the analysis for both the intervention and matched control stores. Christmas notably impacted another 2 weeks, requiring a further 2 weeks of data to be removed. Store sales and individual purchasing datasets consisted of the 11 weeks prior to the intervention and 24 weeks afterward. Measures of women’s dietary quality, and their young children’s dietary quality (where relevant), were assessed using published, validated tools [35,36]. Participants were asked to indicate how often in the previous month they (or their child) consumed each of 20 foods in a Food Frequency Questionnaire (FFQ). A dietary quality score for each woman (or child) was calculated by multiplying their reported frequency of consumption of each of the 20 items from their FFQ by corresponding weightings derived from the published tools (based on principal component analysis) and then summing the results. Dietary quality scores were then standardised to have a mean of 0 and standard deviation (SD) of 1. Higher scores represent better dietary quality characterised by higher intakes of vegetables, fruit, water, and whole grain bread and lower intakes of white bread, processed meats, chips, crisps, and sugar. Women’s daily fruit and vegetable intake was measured using a 2-item tool [37]. This measure details the amount (quantity) of fruits and vegetables eaten and complemented the frequency data collected by the FFQ. The financial effects of the intervention on stores and women was assessed by calculating changes in total weekly store sales and changes in the amounts of money participants spent on grocery foods per week respectively, from before to after the intervention. Participants reported, at each survey wave, the total amount of money they spent on groceries in the past month. Participants’ weekly household spend on groceries at the collaborating supermarket chain were provided by the loyalty card data, and weekly total sales for each store were provided by the store transaction data.

2.5 Fidelity assessment All stores were visited by a member of the research team during the baseline period prior to intervention implementation to assess whether the preintervention and control layouts were similar for each pair of stores. Post-intervention visits and phone calls were made to all stores to assess fidelity of both control and intervention conditions using photographic monitoring and discussions with supermarket staff.

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