Can point-of-sale nutrition information and health warnings encourage reduced preference for sugary drinks?: An experimental study

Journal Pre-proof Can point-of-sale nutrition information and health warnings encourage reduced preference for sugary drinks?: An experimental study Maree Scully, Belinda Morley, Melanie Wakefield, Helen Dixon PII:

S0195-6663(19)31268-1

DOI:

https://doi.org/10.1016/j.appet.2020.104612

Reference:

APPET 104612

To appear in:

Appetite

Received Date: 2 October 2019 Revised Date:

13 January 2020

Accepted Date: 18 January 2020

Please cite this article as: Scully M., Morley B., Wakefield M. & Dixon H., Can point-of-sale nutrition information and health warnings encourage reduced preference for sugary drinks?: An experimental study, Appetite (2020), doi: https://doi.org/10.1016/j.appet.2020.104612. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Ltd.

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Can point-of-sale nutrition information and health warnings

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encourage reduced preference for sugary drinks?: an experimental

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study

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Maree Scully1, Belinda Morley1, Melanie Wakefield1,2, Helen Dixon1,2,3*

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Centre for Behavioural Research in Cancer, Cancer Council Victoria, Melbourne, Australia.

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Melbourne School of Psychological Sciences, The University of Melbourne, Parkville,

Australia. 3

School of Psychology, Faculty of Health Sciences, Curtin University, Bentley, Australia.

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* Corresponding author:

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Helen Dixon

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Centre for Behavioural Research in Cancer

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Cancer Council Victoria

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615 St Kilda Road

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Melbourne 3004, Victoria, Australia

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Phone number: +61 3 9514 6480

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Email: [email protected]

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Abstract

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Point-of-sale (POS) interventions that prompt consumers to more critically evaluate sugary

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drinks could encourage reduced consumption of these drinks and reinforce public health

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campaign messages. This study tested whether: (i) POS nutrition information and health

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warnings about sugary drinks promote healthier drink choices and (ii) impacts of prominent

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POS signs on drink choices vary based on participants’ self-reported prior exposure to a

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sugary drink public health campaign. In an online experiment, 3,034 Australian adults aged

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18-59 years who were past-week sugary drink consumers were randomly assigned to one of

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five POS signage conditions (no signage (control); sugar content of specific beverages;

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Health Star Rating of specific beverages; generic text health warning about sugary drinks;

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generic graphic health warning about sugary drinks) and shown their randomly assigned POS

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sign alone, then alongside a drinks product display and asked to select which drink they

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would choose to buy. The proportion selecting a sugary drink was significantly lower among

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participants who viewed either the sugar content (29%), Health Star Rating (33%) or graphic

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health warning (34%) signs compared to those who saw no sign (43%). These effects held for

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participants who did not recall previously seeing the campaign; however, for participants

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with self-reported prior exposure to the campaign, POS signs did not promote significant

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reductions in sugary drink choices. POS signage has the potential to shift consumers away

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from choosing sugary drinks and could complement mass media campaigns by reaching

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people who may not otherwise be exposed to sugary drink public health messages.

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Keywords: Sugar-sweetened beverages, adults, public health intervention, obesity

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prevention, point-of-sale

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Abbreviations: Point-of-sale (POS); front-of-pack (FOP); nutrition information panel (NIP);

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socio-economic position (SEP); body mass index (BMI)

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Introduction

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Energy-dense, nutrient-poor sugary drinks (defined in this paper as non-alcoholic water based

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beverages with added sugar including sugar-sweetened soft drinks, fruit drinks, energy

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drinks, sports drinks, iced tea and flavoured water, but not milk-based products, 100% fruit

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juice or non-sugar sweetened drinks) are of little nutritional value, with consumption of these

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‘empty kilojoules’ increasing people’s risk of obesity and associated health problems.

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Consumption of sugary drinks is associated with weight gain in both adults and children

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(Malik, Pan, Willett, & Hu, 2013). Sugary drinks may promote weight gain through

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stimulating appetite or suppressing satiety, or as a result of individuals not adequately

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adjusting their overall food intake to compensate for the high amount of energy they consume

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from these drinks (DiMeglio & Mattes, 2000; St-Onge et al., 2004; Vartanian, Schwartz, &

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Brownell, 2007). Excess energy intake is important in the aetiology of obesity, with those

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affected at increased risk of a range of chronic conditions (World Health Organization, 2000),

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including 13 types of cancer (Lauby-Secretan et al., 2016). Sugary drinks are also

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independently associated with increased cancer risk (Chazelas et al., 2019; Hodge, Bassett,

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Milne, English, & Giles, 2018). Furthermore, they contain acid which weakens tooth enamel

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and can lead to dental decay (Bernabe, Vehkalahti, Sheiham, Aromaa, & Suominen, 2014).

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Regular consumption of sugary drinks predisposes people to exceeding recommended daily

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energy intakes for free sugars. The World Health Organization (2015) recommends free

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sugars should contribute less than 10% of total energy intake, with some evidence that a

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further reduction to below 5% total energy intake can provide additional health benefits. In

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Australia, where percentage daily intakes are based on an average adult diet of 8700

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kilojoules (2080 calories), the upper limit for 10% intake of free sugars is <870 kilojoules

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(<208 calories). However, many single servings of sugary drinks (e.g. a 600ml bottle of

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Coca-Cola or 500ml can of Red Bull) contain in excess of this amount of energy from sugar,

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placing regular consumers at higher risk of weight gain and dental caries. According to

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figures from the 2017-18 National Health Survey, around 40% of Australian adults aged 18

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to 64 years consume sugary drinks at least once per week, with this rate peaking at 68%

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among young men (18-24 years) (Australian Bureau of Statistics, 2018a). Of particular

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concern, 10% of 18 to 64 year-old Australians usually consume sugary drinks on a daily basis

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(Australian Bureau of Statistics, 2018a). Australasia, along with North America, Latin

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America and Western Europe is among the four regions of the world with the highest sugary

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drink consumption (Popkin & Hawkes, 2016). There is a pressing global need for public

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health strategies that help people curb their consumption of sugary drinks.

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A number of governments have already implemented public health initiatives to reduce

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sugary drink consumption, such as taxation, limiting availability in schools, restricting

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marketing to children, public awareness campaigns and positive and negative front-of-pack

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(FOP) labelling schemes (Hawkes, Jewell, & Allen, 2013; Popkin & Hawkes, 2016; Roberto

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et al., 2015). In Australia, where this study was conducted, there have been several

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government and non-government-led obesity prevention campaigns that have recommended

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reduced sugary drink consumption as well as other simple diet and lifestyle changes to reduce

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energy intake and increase energy expenditure (Kite et al., 2018; Morley et al., 2019; O'Hara

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et al., 2016). Public health mass media campaigns have the capacity to produce positive

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changes or prevent negative changes in health-related behaviours across large populations

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when they are well designed and of sufficient duration and intensity (Wakefield, Loken, &

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Hornik, 2010). Following a mass media campaign (LiveLighter®) highlighting the negative

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health effects of sugary drink consumption and being overweight in Western Australia, a

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cohort study found a reduction in self-reported sugary drink consumption among heavy

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consumers in the intervention state (Morley et al., 2019). A controlled cohort study found

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evidence of reduced sugary drink consumption also among adult frequent consumers in

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Victoria, Australia following implementation of the same campaign in that state (Morley et

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al., 2018). The present study was conducted following the launch of a new graphic obesity

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prevention campaign (13 Types of Cancer, herein referred to as 13 Cancers) in Victoria,

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Australia, highlighting the link between sugary drink consumption, weight gain and increased

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risk of 13 types of cancer that urged people to avoid sugary drinks. This television-led

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campaign was complemented by digital, cinema, radio and outdoor advertising, and had a

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primary target audience of adults aged 25 to 59 years. The present study was conducted

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during the last three weeks of the five-week campaign, enabling us to assess whether self-

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reported exposure to this campaign influenced consumers’ beliefs and preferences for sugary

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drinks.

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In addition to using mass media as a tool for obesity prevention (World Health Organization,

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2000), leading public health experts recommend that legislation for consumer-friendly

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nutrition labelling be part of comprehensive policy action to influence a cultural shift toward

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healthier preferences (Hawkes et al., 2015). The provision of nutrition and health information

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at the point-of-sale (POS) has the potential to positively change food and drink purchasing

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behaviour by increasing awareness and knowledge about products (Liberato, Bailie, &

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Brimblecombe, 2014). POS interventions have potential to reach consumers further along the

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path to purchase than mass media campaigns, providing a timely, context-relevant prompt

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that could complement other education efforts directed at reducing sugary drink consumption.

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Many countries now have voluntary interpretive nutrition labelling schemes, and some

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countries have laws requiring certain food and beverages to carry traffic light labels (Ecuador

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and Sri Lanka) or health warning labels (Chilé and Mexico) (World Cancer Research Fund

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International, 2016).

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In Australia, FOP food labelling is regulated at a national level, while POS labelling is

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regulated at a state level. Most packaged foods and beverages are required to display a

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nutrition information panel (NIP) that usually appears on the back or side of the package in a

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small font; there is no mandatory national FOP nutrition labelling scheme. However, a

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voluntary FOP labelling scheme, the Health Star Rating (Commonwealth of Australia, 2016),

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appears on some packaged products. The Health Star Rating rates the overall nutritional

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profile of foods and assigns an interpretive rating from 1/2 to 5 stars (with more stars

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indicating healthier products) to provide consumers with a tool for comparing the healthiness

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of similar packaged products (MP Consulting, 2019). In terms of POS labelling, most states

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in Australia now require fast food chains to declare the kilojoule content of standard products

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on menus (Obesity Evidence Hub, 2019). Some other nutrition labelling schemes have also

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been proposed, including warning labels for nutrients of concern and pictorial approaches to

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labelling sugar content (Australian and New Zealand Ministerial Forum on Food Regulation,

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2019; COAG Health Council, 2019).

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A recent online choice experiment with young Australian adults found that FOP labels

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identifying the nutritional quality (as per the Health Star Rating) or sugar content (teaspoons

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of added sugar) of each drink alternative, or highlighting the health risks of sugary drinks (via

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a graphic or text warning on these drinks) reduced intended sugary drink purchases, with the

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strongest effect found for the graphic warning label (Billich et al., 2018). However, this

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research focused on consumers within a relatively narrow age range and did not assess their

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perceptions of sugary drinks in response to seeing the FOP labels, which could help us to

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understand the mechanisms for behaviour change.

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Other experiments testing effects of various FOP labelling schemes on preferences or

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purchasing of sugary drinks have been conducted in New Zealand (Bollard, Maubach,

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Walker, & Ni Mhurchu, 2016), the United Kingdom (Mantzari, Vasiljevic, Turney, Pilling, &

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Marteau, 2018) and the United States (Grummon, Hall, Taillie, & Brewer, 2019; Grummon,

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Taillie, et al., 2019; Roberto, Wong, Musicus, & Hammond, 2016; VanEpps & Roberto,

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2016). All these studies were conducted online, except one conducted in a replica

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convenience store (Grummon, Taillie, et al., 2019). Most of these studies had adult

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participants, two focused on parents (Mantzari et al., 2018; Roberto et al., 2016), while some

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involved teens (Bollard et al., 2016; VanEpps & Roberto, 2016). Across these studies, FOP

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labels were found to influence perceptions of and discourage preference for sugary drinks.

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However, some labelling schemes performed better than others. Studies that included graphic

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health warnings among the labelling schemes tested found that these labels outperformed

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text-only warnings (Billich et al., 2018; Bollard et al., 2016), messages about sugar content

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(Billich et al., 2018; Mantzari et al., 2018), and the Health Star Rating (Billich et al., 2018)

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respectively. However, such visually confronting, graphic labelling schemes may be more

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difficult to implement in practice due to industry opposition (Popova, 2016; Swinburn et al.,

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2019). Available research indicates that text-based health warnings are still effective in

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prompting consumers to evaluate sugary drinks more critically, increase intentions to reduce

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sugary drink consumption and reduce preferences for sugary drinks (Billich et al., 2018;

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Bollard et al., 2016; Grummon, Hall, et al., 2019; Grummon, Taillie, et al., 2019; Roberto et

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al., 2016; VanEpps & Roberto, 2016). Thus, text-based warning label schemes are well

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justified and have been successfully mandated in Chilé and Mexico (World Cancer Research

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Fund International, 2016), with evaluation results from Chilé indicating the scheme is being

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well received by parents and children who report it positively influences their food choices

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(Correa et al., 2019).

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In Australia, where this research was conducted, progress on FOP food and drink labelling

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has been historically slow (Swinburn & Wood, 2013), warranting investigation of alternative

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methods for communicating nutrition information to consumers that may be implemented

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more expediently than mandatory FOP labels. Two alternative channels for reaching

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consumers with messaging about sugary drinks are POS signs displayed in food retail and

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service settings, and mass media campaigns. The present study is concerned with both these

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approaches.

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Several previous studies have tested the effectiveness of POS signs in influencing consumer’s

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drink choices. Two US studies tested effects of different POS signs about energy content on

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teens’ drink purchases in a store-based intervention in low-income predominantly Black

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neighbourhoods. The first study tested calories, percentage of total recommended daily intake

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and physical activity equivalent signs respectively, finding that all conditions reduced sugary

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drink purchases, but the POS sign about a physical activity equivalent (minutes of running)

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was the most effective (Bleich, Herring, Flagg, & Gary-Webb, 2012). The second study

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tested four different POS signs about the energy content in sugary drinks (calories; minutes of

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running; miles of walking; sugar content) finding again that all conditions promoted a

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reduction in sugary drink purchases (with effects on SSB purchases persisting six weeks after

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signs were removed), but messages about miles of walking were the most effective (Bleich,

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Barry, Gary-Webb, & Herring, 2014). Another US study testing effects of several POS signs

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(text health warnings; graphic health warnings; calories) in hospital cafeterias found that only

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the graphic health warnings affected purchases, with further testing revealing that graphic

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health warnings heightened negative affect and prompted consideration of health

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consequences of consuming sugary drinks (Donnelly, Zatz, Svirsky, & John, 2018). POS

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signs conveying information about the amount of sugar in sugary drinks have been shown to

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be effective in reducing selection of these types of drinks in a discrete choice experiment

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conducted online with Australian adults (Blake, Lancsar, Peeters, & Backholer, 2018). To our

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knowledge, no previous studies testing reactions to POS signs about sugary drinks have

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compared how health warning signs perform relative to signs about sugar content or the

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Health Star Rating scheme.

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Prior to real-world implementation, it is crucial that POS nutrition messaging options

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undergo careful pre-testing to ensure they are acceptable to the public and effective among

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varying population groups under simulated conditions. Thus, the primary aim of the present

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study is to examine the relative efficacy of various POS signs (teaspoons of sugar, Health

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Star Rating, text-only or graphic health warnings)

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accurately evaluate the nutritional content of drinks and make healthier drink choices in a

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hypothetical shopping scenario. A secondary research question is whether impacts of such

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POS signage on consumer drink choices differ based on self-reported prior exposure to the

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recent 13 Cancers obesity prevention campaign which urged people to avoid sugary drinks.

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The campaign was launched in the weeks prior to this study, enabling exploration of

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complementary effects of a mass media campaign and a simulated POS signage intervention

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on adults’ perceptions and preferences for sugary drinks.

in encouraging consumers to more

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Method

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Design and procedure

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During the final three weeks of a five-week television-led graphic obesity prevention

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campaign (13 Cancers) produced by the Cancer Council and broadcast only in the Australian

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state of Victoria, a between-subjects national online experiment was conducted, with

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participants randomly assigned to one of five POS signage conditions: (A) no signage

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(control); (B) sugar content of specific beverages; (C) Health Star Rating of specific

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beverages; (D) generic text health warning about sugary drinks; (E) generic graphic health

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warning about sugary drinks. Screening questions were used to determine study eligibility

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(i.e. aged 18-59 years, consumed a sugary drink in the past week, not currently living in

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Western Australia). Eligible participants were exposed to their assigned POS sign alone, and

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then prominently alongside a display of generic (i.e. unbranded) drink products and asked to

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select which drink they would choose to buy for themselves. Following the drink choice task,

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participants answered questions assessing their perceptions of various non-alcoholic drink

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products and knowledge about sugary drinks, before completing ratings of their cognitive and

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emotional responses to their assigned POS sign. Finally, all participants were shown the 13

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Cancers video advertisement on screen to assess prompted recall in order to identify

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participants who had previously been exposed to this campaign. Ethical approval for the

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study was obtained from Cancer Council Victoria’s Institutional Research Review Committee

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(IER 1704).

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Participants

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A sample of Australian adults aged 18 to 59 years was recruited from two non-probability

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(i.e. opt-in) online panels managed by i-Link Research and Lightspeed. Panellists from both

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panels receive points for completing surveys that can be accumulated and redeemed for

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rewards such as shopping gift vouchers. After individually accessing the survey at a time of

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their convenience and completing a series of basic demographic questions, participants were

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asked “During the past 7 days, on how many days did you drink a can, bottle or glass of a

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sugary drink such as soft drinks, energy drinks, fruit drinks, sports drinks and cordial? Do not

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include artificially sweetened drinks. Please note that fruit drinks are those that do not contain

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100% fruit juice.” Those who indicated ‘0 days’ (i.e. irregular or never consumers) were

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excluded from participating. Age (18-29, 30-44, 45-59) and gender (male, female) quotas

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were applied to achieve approximately equal numbers of these groups in each POS signage

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condition. To help ensure there were sufficient numbers of participants who had seen the 13

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Cancers video advertisement, half of the sample were recruited from Victoria (i.e. the state in

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which the advertisement aired) and the remaining half were recruited from all other states and

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territories except Western Australia (due to this state’s higher exposure to public health mass

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media advertising about sugary drinks (Morley et al., 2019)). Based on power calculations

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using results from a previous experimental study examining the effect of FOP labels on

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adult’s drink selections (Billich et al., 2018), as well as campaign awareness figures from the

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evaluation of the LiveLighter® ‘Sugary Drinks’ advertisement which ran in Victoria in 2016

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(Morley et al., 2018), it was estimated that a sample size of 3,000 adults (i.e. n=600 per

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condition) would allow for the detection of small effects in relation to both study aims.

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Intervention

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Full-colour digital POS signs representing each condition were designed by a graphic

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designer, with existing health promotion materials used to inform their layout, imagery and

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content (see Figure 1). The sugar content sign visibly displayed the number of teaspoons of

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sugar found in seven popular types of non-alcoholic drinks: soft drinks, 100% fruit juice,

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flavoured milk, flavoured water, energy drinks, sports drinks and water. The amount of sugar

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for each drink type was determined by referring to nutritional information for key branded

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products (whereby 4 grams of sugar was deemed equivalent to one teaspoon), and then

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asking an Accredited Practicing Dietitian to review them for accuracy. The number of

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teaspoons of sugar displayed for flavoured milk was subsequently adjusted to remove the

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amount attributable to naturally occurring lactose (which is also present in plain milk). No

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adjustment was made for 100% fruit juice, which also contains naturally occurring sugar,

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given the somewhat mixed evidence regarding its association with chronic health conditions

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(Auerbach, Dibey, Vallila-Buchman, Kratz, & Krieger, 2018; Chazelas et al., 2019).

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The Health Star Rating sign showed the same seven types of drinks as the sugar content

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sign, each accompanied by a Health Star Rating providing an overall rating of their

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nutritional profile (per 100 ml) taking into account both risk (e.g. energy content, saturated

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fat, sugar, sodium) and positive components (e.g. protein, fibre, calcium, fruit/vegetable

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content) of the drink. The Health Star Rating is a government-led initiative that rates the

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nutritional value of packaged foods from 1/2 to 5 stars, with more stars indicating a healthier

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choice (Commonwealth of Australia, 2016). For each drink type, the rating displayed on the

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sign was determined by inputting the nutritional information for key branded products into

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the Health Star Rating online calculator (Australian Department of Health, 2014). Where the

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rating varied between brands (i.e. ≥1/2 star difference), an Accredited Practicing Dietitian

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was consulted to determine the most appropriate rating to use.

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The text health warning sign reinforced one of the key messages that the Cancer Council

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has communicated through the LiveLighter® ‘Sugary Drinks’ campaign and more recently the

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13 Cancers campaign, namely that “Drinking sugary drinks can lead to toxic fat around your

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vital organs”. The graphic health warning sign featured this same message with an image

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underneath from the 13 Cancers video advertisement graphically depicting the build-up of

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visceral fat around an internal organ. Neither of the health warning signs singled out

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particular beverages.

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Measures

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The primary outcome was drink choice following exposure to the POS signage intervention

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which was measured using a hypothetical shopping scenario developed by Billich and

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colleagues (2018). Participants were asked to imagine they had gone to a convenience store

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or take-away café or up to a vending machine with the intention of buying a pre-packaged

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drink (in a bottle, can or carton) to drink immediately themselves. They were shown their

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randomly assigned POS sign alongside a display of 15 drink products and asked to select

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which drink they would choose, if any, in this situation (see Figure 2). Responses were

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categorised into sugary drinks (regular soft drink (cola and non-cola), fruit drink (with added

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sugar), iced tea, sports drink, energy drink, flavoured water), diet drinks (diet soft drink (cola

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and non-cola), diet energy drink), high (≥4) health star rating drinks (fruit juice (100%

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juice), plain milk, coconut water, bottled water), flavoured milk and no drink.

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As secondary outcome measures, participants’ perceptions of how healthy (1 = ‘not healthy at

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all’ to 7 = ‘very healthy’) they considered each type of drink product and how much sugar (1

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= ‘no sugar’ to 7 = ‘high sugar content’) they thought each drink contained were assessed.

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Participants’ ratings of regular soft drink, fruit drink (with added sugar), iced tea, sports

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drink, energy drink and flavoured water were then averaged to create summary indices of

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participants’ perceptions of the (i) healthiness and (ii) sugar content of sugary drinks in

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general. To evaluate their knowledge about sugary drinks, participants were asked to indicate

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how many teaspoons of sugar an average 600ml bottle of soft drink contains (open-ended

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question), with responses of 15 to 17 teaspoons classified as correct (i.e. within 10% margin

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of error of 16 teaspoons). In addition, participants were asked to indicate which, if any,

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diseases or health effects they associate with drinking sugary drinks from the following pre-

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coded list of seven options: asthma; cancer; diabetes (type 2); epilepsy; heart disease; tooth

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decay; weight gain/obesity.

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To provide potential insight into why particular POS signs may or may not be effective in

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promoting healthier drink choices, participants were asked to indicate their level of

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agreement (1 = ‘strongly disagree’ to 7 = ‘strongly agree’) that their assigned POS sign: was

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easy to understand; was believable; was relevant to me; made me stop and think; is one that I

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would talk to other people about; taught me something new; was convincing; made a strong

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argument for why I should drink less sugary drinks; made me feel concerned; was effective;

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and was exaggerated. To gauge emotional responses, participants were asked to indicate, on a

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scale ranging from 1 = ‘not at all’ to 7 = ‘extremely’, whether reading their assigned POS

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sign made them feel: confused; surprised; reassured; worried; bored; encouraged; amused;

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disgusted; guilty; and anxious. The extent to which participants agreed they felt motivated to

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reduce the amount of sugary drinks they currently drink after reading their assigned POS sign

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was also assessed.

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To distinguish those with self-reported prior exposure to the 13 Cancers campaign, all

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participants were shown the 30-second video advertisement and then asked to indicate

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whether they had previously seen the advertisement. Participants who responded ‘Yes’ to this

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question were categorised as having self-reported prior exposure to the 13 Cancers campaign

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whereas those who responded ‘No’ or ‘Don’t know / can’t say’ were deemed not to recall

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previously seeing the campaign; any participants who were unable to clearly see or hear the

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advertisement were excluded (5%; n=155).

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Data on participants’ gender, age, residential postal code, highest level of educational

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attainment, parental status and frequency of consuming water and sugary drinks in the past

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week was collected. Socio-economic position (SEP) was estimated according to the

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Australian Bureau of Statistics’ Index of Relative Socio-Economic Disadvantage, based on

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participant’s residential postal code (Australian Bureau of Statistics, 2018b). Finally, self-

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reported height and weight were assessed to enable computation of participants’ body mass

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index (BMI) [weight (kg)/height (m)2].

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Statistical analysis

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Data were analysed using Stata/MP V.14.2 (StataCorp, 2016). For the primary and secondary

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outcome measures, a combination of logistic (categorical outcomes: type of drink selected;

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correct number of teaspoons of sugar; awareness of association between drinking sugary

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drinks and each disease/health effect) and linear (continuous outcomes: perceived healthiness

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and sugar content of sugary drinks) regression analyses with Bonferroni-adjusted pairwise

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comparisons (to control for type 1 error rates) were conducted to test for differences by POS

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signage condition on each outcome. Each model was then rerun with an interaction term to

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assess if the effects of the POS signs were consistent among participants with self-reported

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prior exposure to the 13 Cancers campaign vs. those who did not recall previously seeing the

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campaign. Where a significant interaction was found, this is reported in the text. In addition,

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unplanned exploratory analyses were performed to test the interaction between POS signage

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condition and the other sample characteristics listed in Table 1 for each type of drink selected

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(i.e. primary outcomes). To assess whether participants’ cognitive and emotional responses to

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the POS signs varied according to their assigned condition, one-way analysis of variance with

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Bonferroni-adjusted pairwise comparisons was used.

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Results

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Sample characteristics

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A total of 4,942 panellists accessed the survey over a three-week period (5th – 25th November

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2018) coinciding with the airing of the 13 Cancers campaign in Victoria. Of these, 1,608

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were excluded prior to randomisation either due to not meeting the eligibility criteria

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(n=1,477) or dropping out during screening (n=131). A further 26 panellists did not receive

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their allocated intervention as condition quotas had been reached. After accounting for

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incomplete surveys (n=87) and cases removed where data quality was not assured (e.g.

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survey completed below minimum threshold for acceptable time to complete and/or

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consistent straight-lined responses to scaled data; n=187), a final sample of 3,034 eligible

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adults was available for analysis (see Figure 3 for CONSORT flow diagram).

16

361

Table 1 shows the demographic profile of the sample. Compared to the Australian

362

population, the sample was similar in terms of socio-economic status (Australian Bureau of

363

Statistics, 2018b) but skewed towards higher education (Australian Bureau of Statistics,

364

2018c) and lower BMI (Australian Bureau of Statistics, 2018a). Overall, 29% (n=839) of

365

those surveyed recalled previously seeing the 13 Cancers campaign advertisement.

366

Sugary drink selection

367

Selection of a sugary drink differed by POS signage condition (χ2(4)=29.88, p<0.001). As

368

Table 2 highlights, compared to the no signage condition, participants exposed to either the

369

sugar content (p<0.001), Health Star Rating (p=0.001) or graphic health warning (p=0.004)

370

sign had a significantly lower prevalence of selecting a sugary drink in the hypothetical

371

shopping scenario. However, the text health warning group did not differ from the control

372

group on this outcome.

373

There was a significant interaction between self-reported prior exposure to the 13 Cancers

374

campaign and POS signage condition (χ2(4)=9.93, p=0.042), which is illustrated in Figure 4.

375

Specifically, participants who reported not previously being exposed to the campaign were

376

less likely to select a sugary drink if they had seen either the sugar content, Health Star

377

Rating or graphic health warning sign (all p<0.001). However, for those who reported

378

previously been exposed to the 13 Cancers campaign, none of the four POS signs tested

379

influenced the likelihood of participants making a sugary drink selection (all p>0.05). It

380

should be noted, though, that the proportion of participants who chose a sugary drink in the

381

no signage control condition was significantly lower among those with self-reported 13

382

Cancers campaign exposure compared to those who did not recall previously seeing the

383

campaign (36% cf. 47%; χ2(1)=6.08, p=0.014).

17

384

There were no significant interactions between POS signage condition and participant’s

385

gender, age group, highest level of education, area-based SEP, geographic location, parental

386

status and BMI category or their past week consumption of sugary drinks and water in

387

exploratory analyses.

388

Non-sugary drink selection

389

Selection of a high health star rating drink differed by POS signage condition (χ2(4)=42.42,

390

p<0.001). Participants were significantly more likely to choose a high health star rating drink

391

if they had been exposed to the Health Star Rating sign compared to if they saw the text

392

(p<0.006) or graphic (p<0.049) health warning sign or no signage (p<0.001). Participants

393

exposed to the sugar content sign also had a significantly higher likelihood of choosing a high

394

health star rating drink than those who saw the text health warning sign (p=0.014) or no

395

signage (p<0.001). The prevalence of selecting a diet drink, flavoured milk or no drink did

396

not vary based on the type of POS signage participants were exposed to (Table 2).

397

No significant interaction between self-reported prior exposure to the 13 Cancers campaign

398

and POS signage condition was found for any of the non-sugary drink selections. Exploratory

399

analyses did, however, reveal a significant condition by gender interaction for choosing a

400

high health star rating drink (χ2(4)=11.44, p=0.022). For female participants, all of the POS

401

signs increased the likelihood of making a high health star rating drink selection compared to

402

the no signage condition (all p<0.001; see Supplementary file 1); whereas for male

403

participants, only the Health Star Rating sign led to an increase in selection of a high health

404

star rating drink relative to the text (p=0.002) and graphic (p=0.030) health warning signs as

405

well as no signage (p=0.023). A significant condition by SEP interaction for choosing

406

flavoured milk was also observed in these exploratory analyses (χ2(8)=15.96, p=0.043);

18

407

however, no significant effects of the POS signs were found when running separate models

408

for each SEP group (see Supplementary file 2).

409

Perceived healthiness and sugar content of sugary drinks

410

Participants’ mean rating of the perceived healthiness of sugary drinks differed by POS

411

signage condition (F(4, 3029)=4.98, p<0.001). Compared to the control condition (Mean

412

(M)=3.18), participants perceived sugary drinks to be less healthy if they had been exposed to

413

either the sugar content (M=2.88; p<0.001) or text health warning (M=2.97; p=0.047) sign.

414

Those who saw the sugar content sign also perceived sugary drinks to be less healthy than

415

participants who saw the Health Star Rating sign (M=3.09; p=0.038). There were no

416

significant effects found for the graphic health warning sign (M=3.00). Exposure to the POS

417

signage did not affect participants’ perceptions of the sugar content of sugary drinks (means

418

ranged from 5.33 for no signage and the Health Star Rating sign to 5.42 for the graphic health

419

warning sign).

420

Knowledge about sugary drinks

421

Knowledge of the number of teaspoons of a sugar in a 600ml bottle of soft drink was

422

associated with POS signage condition (χ2(4)=283.52, p<0.001). Specifically, participants in

423

the sugar content POS signage condition (34%) were significantly more likely to nominate

424

the correct number of teaspoons compared to participants who saw either the Health Star

425

Rating (6%), text (8%) or graphic (8%) health warning signs or no signage (5%; all p<0.001).

426

Across conditions, most participants associated drinking sugary drinks with diabetes (82%),

427

tooth decay (81%) and weight gain/obesity (80%). Just over half (55%) believed there to be a

428

link between heart disease and sugary drink consumption, while one-third (33%) thought that

19

429

cancer was associated with drinking sugary drinks. A minority of participants associated

430

sugary drink consumption with asthma (9%) or epilepsy (6%).

431

Participants’ perceptions of a link between drinking sugary drinks and diabetes (χ2(4)=13.75,

432

p=0.008), heart disease (χ2(4)=9.76, p=0.045) and weight gain/obesity (χ2(4)=10.72, p=0.030)

433

varied by POS signage condition. Those exposed to the text health warning sign (87%) were

434

more likely to believe that drinking sugary drinks is associated with diabetes

435

participants exposed to the sugar content (81%; p=0.049) or graphic health warning signs

436

(81%; p=0.049) or no signage (79%; p=0.004). Participants who saw the text health warning

437

sign were also more likely than those who saw the Health Star Rating sign to associate

438

drinking sugary drinks with heart disease (59% cf. 51%; p=0.048), and more likely than those

439

who saw the graphic health warning sign to associate drinking sugary drinks with weight

440

gain/obesity (84% cf. 77%; p=0.023). A significant interaction between self-reported prior

441

exposure to the 13 Cancers campaign and POS signage condition was found for asthma

442

(χ2(4)=12.98, p=0.011). In exploring this further, the POS signs had no effect among those

443

with self-reported 13 Cancers campaign exposure; however, for those who did not recall

444

previously seeing the campaign, knowledge of a link between asthma and sugary drink

445

consumption was higher after seeing the graphic health warning sign compared to the sugar

446

content sign (9% cf. 4%; p=0.015).

447

Point-of-sale signage ratings

448

As shown in Table 3, the sugar content sign generated stronger cognitive responses than the

449

other conditions on most items except ‘was exaggerated’, which was highest for the graphic

450

health warning sign. The graphic health warning sign tended to elicit stronger negative

451

emotional reactions (i.e. feelings of confusion, worry, disgust, guilt and anxiety) from

452

participants, while the Health Star Rating sign tended to provoke more positive emotional

than

20

453

reactions such as reassurance, encouragement and amusement. The sugar content sign made

454

participants feel more surprised than the other POS signs. Participants who saw the sugar

455

content sign reported stronger motivation to reduce their own sugary drink consumption than

456

those who saw the Health Star Rating sign.

457

Discussion

458

Overall, the results from this experimental study suggest that prominent POS signage has the

459

potential to shift consumers away from choosing sugary drinks, with three of the four types of

460

POS signs tested—sugar content, Health Star Rating and graphic health warning—prompting

461

a significantly lower proportion of adults to select a sugary drink in a hypothetical shopping

462

scenario compared to those who saw no signage. Importantly, this reduction was observed

463

across key demographic factors such as gender, age group, education or weight status,

464

suggesting that POS signage is an equitable method for promoting healthier drink choices

465

among adults.

466

Of all the POS signs tested, the sugar content sign promoted the most favourable cognitive

467

responses. This sign displayed concrete information that was likely to be meaningful to

468

people. In line with its content, this sign appeared to provide consumers with clear

469

information about the amount of sugar in particular drinks, as evidenced by consumers’

470

greater accuracy in estimating how many teaspoons of sugar were in a soft drink following

471

exposure to this sign. Visually displaying the 16 teaspoons of sugar contained in a bottle of

472

soft drink may have better allowed participants to imagine what consuming this amount of

473

sugar on its own would be like rather than if the sign had simply stated the number of

474

teaspoons or the amount of sugar in grams (as appears on the mandated nutrition information

475

panel). Clearly illustrating the different amounts of harmful sugars in various drinks may also

21

476

have enabled consumers to more critically compare products, than the more ‘gain framed’

477

symbolism of health stars, or the singular messaging of the health warnings which did not

478

explicitly compare different drinks to one another.

479

In our study, the graphic health warning signs tended to elicit stronger negative emotional

480

reactions than the other signs, plus perceptions that the sign was exaggerated. However, they

481

were equally effective as the sugar content and Health Star Rating signs in encouraging

482

healthier drink choices compared to the control condition. In an analogous study conducted

483

by Billich and colleagues (2018) that empirically tested the same four types of educational

484

messages in a FOP label format, they found that the graphic health warning label was most

485

effective at reducing intended choice of a sugary drink. The stronger performance of the

486

graphic health warning relative to the other message formats in the Billich et al. (2018) study

487

may be due to their use of a health warning image portraying a visible and more immediate

488

health outcome associated with consuming sugary drinks (i.e. dental caries) compared to the

489

less perceptible, longer-term health outcome of build-up of visceral fat around internal organs

490

which was the health warning image used in the present study to correspond with the 13

491

Cancers campaign. Other studies that found FOP graphic health warnings prompted healthier

492

drink preferences featured dental decay as their health outcome (Bollard et al., 2016;

493

Mantzari et al., 2018). It is also possible that graphic health warnings are more salient for

494

participants when making their drink selection if displayed on or near specific drinks (as in

495

the studies simulating exposure to FOP labels) rather than alongside a display of various

496

drink products (as in the present study to simulate POS signage) where the health warning is

497

not linked to particular types of drink. Future research comparing different types of graphic

498

health warnings (e.g. dental caries vs. internal fat) in FOP label and POS signage formats

499

would help explicate these findings and provide valuable information for governments when

500

considering such policy initiatives.

22

501

The sugar content and Health Star Rating POS signs prompted participants to shift towards

502

selecting high health star rating drinks (i.e. 100% fruit juice, plain milk, coconut water,

503

bottled water). Given these two conditions presented nutritional information about specific

504

drinks and the two health warning conditions did not, we cannot determine the extent to

505

which this finding was driven by the sign topic (i.e. sugar content, health star rating) or the

506

inclusion of information about particular drinks in these two conditions. Our finding that the

507

Health Star Rating condition prompted people to select drinks with higher health star ratings

508

parallels Billich et al’s (2018) finding when testing FOP labels. None of the signs affected

509

participants’ propensity to choose diet drinks, flavoured milk or no drink. With the long-term

510

health impacts of artificially sweetened beverages largely unknown (Borges et al., 2017), it is

511

pleasing that the POS signs did not appear to promote diet drinks as an alternative to sugary

512

drinks. While fruit juice was assigned a health star rating of 5 in our study and was thus

513

considered a high health star rating drink, the recent five year review of this FOP labelling

514

system has recommended changes that would result in fruit juices receiving health star

515

ratings between 2.5 and 4, based on their sugars and energy content (MP Consulting, 2019).

516

This change would mean that fruit juice is no longer treated as equivalent to whole fruit, and

517

would better align the system with the Australian Dietary Guidelines (National Health and

518

Medical Research Council, 2013) and the World Health Organization’s guidelines regarding

519

free sugars (World Health Organization, 2015).

520

Exposure to the text health warning sign was associated with improvements in knowledge

521

specific to the educational message (i.e. awareness of the link between drinking sugary drinks

522

and weight gain/obesity) whereas a similar effect was not found for the graphic health

523

warning sign. Examination of participants’ ratings of the four POS signs point to a couple of

524

possible explanations for this finding. First, the graphic health warning sign was more likely

525

to be perceived as ‘exaggerated’ which may have led to increased derogation of the message

23

526

by participants in this condition. Second, this sign was rated lower than the text-only warning

527

in terms of ease of understanding and higher for provoking feelings of confusion which could

528

have reduced participants’ motivation to critically process the information being presented to

529

them. Nonetheless, we found that the graphic health warning promoted healthier drink

530

choices compared to the control condition, whereas the text-only warning did not impact

531

drink choices. Evidence from other studies that have tested text versus pictorial health

532

warnings on sugary drinks indicates that graphic health warnings are more effective than text-

533

only warnings in promoting stronger negative emotional reactions, consideration of health

534

effects and healthier drink choices (Billich et al., 2018; Bollard et al., 2016; Donnelly et al.,

535

2018; Mantzari et al., 2018). The latter findings are consistent with a meta-analysis on

536

cigarette pack health warnings which found that while graphic warnings tend to elicit more

537

reactance than text-only warnings, they are also consistently found to be more effective (Noar

538

et al., 2016).

539

This is the first study to have assessed the impacts of POS signage on consumer drink choices

540

in the context of a relevant mass media campaign airing concurrently. We found that the POS

541

signs only led to significant reductions in sugary drink choices among those who did not

542

recall previously seeing the 13 Cancers video advertisement. The failure of the POS signs to

543

produce additional effects over and above what exposure to the campaign could have

544

provided is not surprising given the relatively low intensity of the experimental POS signage

545

intervention. It is conceivable that repeated exposure to POS signage could indeed boost the

546

effects of mass media campaigns; although further research is needed to test this proposition.

547

Encouragingly, our results suggest that POS signs could complement and reinforce mass

548

media campaigns by reaching consumers who may not otherwise be exposed to public health

549

messages about sugary drinks. This is a particularly important finding in light of people’s

550

changing media use patterns which demands use of a wider range of media channels to

24

551

achieve sufficient reach to change population health behaviour (Durkin & Wakefield, 2018).

552

While research indicates that FOP labels and POS signs can both be effective in promoting

553

healthier drink choices, in the Australian context we believe that POS signs could be more

554

quickly and readily implemented (either voluntarily in particular retail settings such as

555

cafeterias or through being mandated by state governments) than FOP labels (as this would

556

require changes to national regulations). While all our POS signage formats except the text-

557

only health warning were effective in promoting healthier drink choices, it seems likely that

558

industry and the public would be more accepting of health star ratings or sugar content

559

signage than the more confronting graphic health warnings.

560

Several study limitations should be acknowledged. Our primary outcome was drink choice

561

which we measured using a hypothetical shopping scenario; thus, we are unable to infer what

562

effect the observed reduction in participants choosing sugary drinks in response to the POS

563

signage would have on actual consumption levels. We tested the signs under ideal conditions

564

of exposure, whereas in a real-world retail setting other factors may compete for consumers’

565

attention. As participants were recruited from a non-probability based online panel with age

566

and gender quotas applied, the sample cannot be considered representative of the general

567

Australian population; although obtaining a representative sample was not a major

568

consideration given this was an experimental study whereby participants were randomised to

569

conditions. An important limitation relates to the way we operationalised the POS signage

570

manipulations. While our primary focus was on varying the message topic of the signs, two

571

of the conditions (sugar content and Health Star Rating) also singled out particular drinks to

572

illustrate healthier versus unhealthy drink options, while the two health warning conditions

573

did not. Future research could overcome this limitation by testing POS signs that differ by

574

topic but are equivalent in whether they single out particular drinks. Also, for practical

575

reasons, not all drinks from the choice task featured on the sugar content and Health Star

25

576

Rating POS signs. If testing POS signage options in a real-world setting without the same

577

size constraints as an online survey, a wider array of drink types could be shown. However, it

578

would be important for any expanded signs to first be pre-tested to ensure that consumers’

579

understanding of the message is not diminished by the additional information. Finally, our

580

exploration of how prior campaign exposure might impact reactions to the experimental POS

581

signage manipulation relied on an opportunistic approach, whereby data collection was timed

582

to be coincident with a real-world campaign. The limitation to this approach is that campaign

583

exposure was not randomised but relied on participant’s self-reported recall of the campaign.

584

Therefore, an alternative explanation for the findings could be that people who recalled this

585

campaign were already less likely to choose a sugary drink, rather than the campaign causing

586

this, and therefore were unaffected by the POS signs. However, previous population-level

587

evaluations using cohort and controlled cohort designs showing that such campaigns can

588

promote reduced reported sugary drink consumption, adds support to the notion that exposure

589

to the 13 Cancers campaign may have encouraged healthier drink choices, and the POS signs

590

did not add to this impact.

591

Conclusions

592

The findings from this simulation study add to growing evidence that POS signage can

593

positively impact consumer drink choices. We found that POS signs employing sugar

594

content, health star ratings or graphic health warnings in their messaging all promoted

595

healthier drink choices. Of these, the sugar content sign produced the most favourable

596

cognitive responses, whereas the graphic health warnings prompted stronger negative

597

emotions than the other signs. As a next step, we recommend that the effectiveness of such

598

signs be evaluated in actual retail or food service settings to determine their capacity to

26

599

decrease purchasing of sugary drinks and ultimately reduce sugary drink consumption at the

600

population level.

601

602

Acknowledgements

603

The authors thank Hannah Ngaei for designing and producing the four POS signs that were

604

used as experimental stimuli in this research.

605

Author contributions

606

HD designed the study with input from MS, BM and MW. MS managed the data collection.

607

MS and HD analysed and interpreted the data, and drafted the manuscript, with critical input

608

from all other authors. All authors gave final approval for the submitted manuscript.

609

Funding

610

This study was funded by VicHealth and the Victorian Department of Health and Human

611

Services. M.W. was supported by funding from an NHMRC Principal Research Fellowship.

612

The funders had no role in the design, analysis or writing of this article.

613

Availability of data and materials

614

Data and materials are available from the corresponding author upon reasonable request.

27

615

Ethics approval and consent to participate

616

Cancer Council Victoria’s Institutional Research Review Committee approved all study

617

procedures (reference number IER 1704), and all participants provided informed consent.

618

Declaration of interests

619

All authors are currently employed by an organisation involved in public health research and

620

advocacy.

621

622

28

623

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36

Figure captions Figure 1: Point-of-sale signs (clockwise from top left): sugar content; Health Star Rating; graphic health warning; text health warning.

Figure 2: Example of the online drink choice task, for the sugar content point-of-sale signage condition.~ Note: ~ Each participant viewed the point-of-sale sign for their assigned condition alongside a display of drinks they were required to choose from.

Figure 3: CONSORT flow diagram.

Figure 4: Proportion of participants in each point-of-sale signage condition who selected a sugary drink by self-reported prior exposure to the 13 Cancers campaign. Notes: Pairwise differences were assessed with a Bonferroni correction applied. a Significant difference compared to no signage (control) condition at p<0.05.

37

Table 1: Sample characteristics by point-of-sale signage condition.

Point-of-sale signage condition Total (N=3,034)

No signage (control) (n=605)

Sugar content (n=613)

Health Star Rating (n=608)

Text health warning (n=601)

Graphic health warning (n=607)

%

%

%

%

%

Gender Male

49.5

50.1

49.4

49.2

49.1

49.9

Female

50.3

49.6

50.6

50.8

50.6

50.1

0.1

0.3

0.0

0.0

0.3

0.0

18-29 years

32.6

33.7

32.8

32.4

31.1

33.1

30-44 years

32.9

32.4

32.8

32.9

33.9

32.5

45-59 years

34.5

33.9

34.4

34.7

34.9

34.4

Secondary school or less

29.7

29.6

29.0

29.6

30.8

29.3

TAFE or Trade Certificate or Diploma

28.1

31.1

27.9

24.8

26.3

30.6

University degree

42.2

39.3

43.1

45.6

42.9

40.0

Low (1-33%)

29.1

27.9

29.5

28.5

31.3

28.5

Medium (34-67%)

32.2

32.4

32.8

34.9

27.3

33.4

High (68-100%)

38.7

39.7

37.7

36.7

41.4

38.1

48.0

47.9

48.1

48.2

47.6

47.9

Other Age group

Highest level of education

SEP (area-based)#

Location Victoria

38

Other state/territory

52.0

52.1

51.9

51.8

52.4

52.1

61.3

62.5

62.3

61.3

59.7

60.6

38.7

37.5

37.7

38.7

40.3

39.4

Healthy weight/underweight

46.8

47.4

43.4

44.9

47.2

51.1

Overweight

29.8

29.8

32.0

34.5

25.9

26.9

Obese

23.4

22.8

24.6

20.6

26.9

22.0

<7 cups/week

58.4

57.9

62.2

57.1

57.7

57.2

7+ cups/week

41.6

42.1

37.8

42.9

42.3

42.8

<28 cups/week

36.8

38.0

34.9

37.7

38.4

35.3

28+ cups/week

63.2

62.0

65.1

62.3

61.6

64.7

No/Don’t know/Can’t say

70.9

67.7

70.6

66.7

74.1

75.2

Yes

29.1

32.3

29.4

33.3

25.9

24.8

Parent/carer of child aged <18 No Yes $

BMI category

Sugary drink consumption

Water consumption

Prompted recall of 13 Cancers campaign advertisement^

Note: Percentages may not sum to 100% due to rounding. # Socio-economic position (SEP) was determined according to the Australian Bureau of Statistic’s Index of Relative Socio-Economic Disadvantage ranking for Australia using participant’s residential postcode. This index ranks areas on a continuum of disadvantage (from most disadvantaged to least disadvantaged) taking into consideration characteristics that may enhance or reduce socio-economic conditions of the area. $ Body Mass Index (BMI) information is missing for 675 respondents as they did not self-report their height and/or weight. ^ Prompted campaign recall information is missing for 155 respondents who were unable to see and hear the advertisement clearly.

39

Table 2: Type of drink selected in hypothetical shopping scenario by point-of-sale signage condition.

Point-of-sale signage condition No signage (control) (n=605)

Sugar content (n=613)

Health Star Rating (n=608)

Text health warning (n=601)

Graphic health warning (n=607)

%

%

%

%

%

Sugary drink

43.5

29.4a

32.7a

36.6

33.6a

Diet drink

13.2

12.7

9.0

13.5

13.2

31.1

45.8

46.5

36.8

38.6c

Flavoured milk

6.1

5.5

6.4

5.3

5.8

No drink

6.1

6.5

5.3

7.8

8.9

High (≥4) health star rating drink

a

a

bc

Notes: For each type of drink, pairwise differences were assessed with a Bonferroni correction applied. a Significant difference compared to no signage (control) condition at p<0.05; b Significant difference compared to sugar content sign at p<0.05; c Significant difference compared to Health Star Rating sign at p<0.05.

40

Table 3: Participants’ cognitive and emotional responses to point-of-sale signs.

Sugar content

Point-of-sale signage condition Health Star Rating Text health warning

(n=613) M Cognitive responses Easy to understand Believable Relevant to me Made me stop and think Would talk to others about Taught me something new Convincing Made strong argument Made me feel concerned Effective Exaggerated Emotional responses Confused Surprised Reassured Worried Bored Encouraged Amused Disgusted Guilty Anxious

(n=608) SD

M

Graphic health warning

(n=601)

(n=607)

SD

M

SD

M

SD

6.03d 5.80bcd 5.09cd 5.34bd 5.00bcd 5.19bcd 5.62bcd 5.63b 5.15b 5.55bcd 2.97

1.17 1.30 1.64 1.58 1.69 1.67 1.34 1.57 1.65 1.46 1.75

5.87d 5.54d 5.09cd 4.93 4.50 4.81c 5.24 5.25 4.61 5.27 3.16

1.28 1.37 1.66 1.67 1.77 1.75 1.52 1.66 1.72 1.51 1.83

5.91d 5.48 4.71 5.12 4.59 4.46 5.27 5.45 5.02b 5.15 3.38a

1.25 1.39 1.76 1.67 1.80 1.82 1.46 1.61 1.68 1.50 1.81

5.59 5.32 4.52 5.04 4.48 4.70 5.15 5.39 5.02b 5.11 3.75abc

1.49 1.51 1.78 1.71 1.86 1.85 1.60 1.62 1.72 1.66 1.85

2.36 4.40bcd 3.88cd 4.15b 2.66 4.32cd 2.91d 4.10bc 3.89b 3.35b

1.70 1.87 1.80 1.88 1.76 1.73 1.84 2.03 1.94 1.85

2.58 3.88 4.20acd 3.58 2.97ad 4.46cd 3.05cd 3.31 3.46 2.97

1.79 1.91 1.74 1.89 1.81 1.73 1.85 1.96 1.99 1.85

2.46 3.73 3.37 4.21b 2.70 3.97 2.64 3.52 3.87b 3.60b

1.68 1.86 1.89 1.83 1.76 1.89 1.76 1.92 1.93 1.92

2.78ac 4.08c 3.29 4.41b 2.66 3.85 2.57 4.50abc 3.89b 3.80ab

1.81 1.90 1.90 1.83 1.72 1.84 1.81 1.91 1.89 1.87

41

Motivation To reduce own sugary drink consumption

5.29b

1.67

4.90

1.72

5.04

1.69

5.08

1.73

Notes: Boldfaced figures highlight where a point-of-sale sign produced a stronger response among participants than the other three signs. Pairwise differences were assessed using one-way analysis of variance with Bonferroni correction. a Significantly higher than sugar content sign at p<0.05; b Significantly higher than Health Star Rating sign at p<0.05; c Significantly higher than text health warning sign at p<0.05; d Significantly higher than graphic health warning sign at p<0.05.

Panellists who started the survey (n=4,942)

Excluded (n=1,608) ♦ Outside required age range (n=73) ♦ Reside in Western Australia (n=10) ♦ Did not consume a sugary drink in past 7 days (n=1,394) ♦ Dropped out during screening (n=131)

Randomised (n=3,334)

Allocated to A: No signage (control) (n=673) ♦ Did not receive intervention: quota full (n=4)

Allocated to B: Sugar content (n=668) ♦ Did not receive intervention: quota full (n=5)

Allocated to C: Health Star Rating (n=666) ♦ Did not receive intervention: quota full (n=8)

Allocated to D: Text health warning (n=662) ♦ Did not receive intervention: quota full (n=5)

Allocated to E: Graphic health warning (n=665) ♦ Did not receive intervention: quota full (n=4)

Analysed (n=605) ♦ Excluded from analysis (n=64) - Dropped out (n=24) - Data quality not assured (n=40)

Analysed (n=613) ♦ Excluded from analysis (n=50) - Dropped out (n=19) - Data quality not assured (n=31)

Analysed (n=608) ♦ Excluded from analysis (n=50) - Dropped out (n=14) - Data quality not assured (n=36)

Analysed (n=601) ♦ Excluded from analysis (n=56) - Dropped out (n=13) - Data quality not assured (n=43)

Analysed (n=607) ♦ Excluded from analysis (n=54) - Dropped out (n=17) - Data quality not assured (n=37)

Regular soft drink (cola)

Regular soft drink (non-cola)

Diet soft drink (cola)

Diet soft drink (non-cola)

Fruit juice (100% juice)

Fruit drink (with added sugar)

Iced tea

Plain milk

Flavoured milk

Sports drink

Energy drink

Diet energy drink

Bottled water

Coconut water

Flavoured water

No drink

Ethics approval and consent to participate Cancer Council Victoria’s Institutional Research Review Committee approved all study procedures (reference number IER 1704), and all participants provided informed consent.