- Research article
- Open Access
Who drinks sugar sweetened beverages and juice? An Australian population study of behaviour, awareness and attitudes
BMC Obesity volume 6, Article number: 1 (2019)
The rate of overweight and obesity in Australia is among the highest in the world. Yet Australia lags other countries in developing comprehensive educative or regulatory responses to address sugary drink consumption, a key modifiable risk factor that contributes substantial excess sugar to the diet. Measurement of sugary drink consumption is typically sporadic and nutrition focussed and there is limited knowledge of community perceptions and awareness of the health risks associated with excess sugary drink consumption. The aim of this study was to assess the demographic characteristics, behavioural risk factors and attitudes and knowledge associated with sugar-sweetened beverage (SSB) and 100% fruit juice consumption.
A face-to-face household survey was conducted in 2014 using a stratified random sampling strategy to represent the South Australian population aged 15 years and over. The survey contained questions on sugary drinks, with past week SSB consumption and 100% fruit juice consumption used as outcome variables. Associations were examined with demographic characteristics, behavioural risk factors, and sugary drink attitudes and knowledge.
Of the 2732 respondents, 35% had consumed SSBs 1–6 times (moderate consumers) and 16% had consumed SSBs 7 or more times (frequent consumers) in the past week. Furthermore, 35% had consumed 100% fruit juice in the past week, with 10% consuming every day. Rates of SSB consumption were consistently higher among males, younger age groups, and groups with lower education attainment, as well as smokers and frequent consumers of fast food. Awareness of health risks and sugar content of SSBs was low, especially among frequent SSB consumers. Fruit juice consumption was higher among males, younger age groups, the physically active and among those believing that 100% fruit juice did not contain more sugar than SSBs.
Consumption of SSBs and 100% fruit juice is common but awareness of health risks and sugar content of these drinks is low. There is a need for greater consumer understanding which could be achieved through educative approaches such as public education campaigns, on-package warning labels and improved nutrition information panels.
Excess consumption of added and free sugars are gaining increasing attention as an environmental driver of obesity . Within this context, sugar-sweetened beverages (SSBs) are a focus due to their energy density, coupled with poor nutritional value, and the strength of evidence linking their consumption with weight gain, obesity , Type 2 diabetes , tooth decay  and emergent evidence of cardiovascular risks . Countries are moving to try to reduce their population consumption of SSBs and a raft of educative and regulatory interventions are being implemented [6, 7]. Australia lags other countries in comprehensive educative or regulatory responses to address SSB consumption and obesity more broadly .
At 63%, the rate of overweight and obesity in Australia is among the highest in the world , with the rate of obese Australians tripling since 1990. Australians are also high consumers of SSBs , and SSBs contribute substantial excess sugar to the national diet. Over half of Australians exceed the World Health Organization (WHO) recommendations for free sugar in the diet, with 52% of free sugars coming from beverages, notably soft drinks (sodas), electrolyte (sports) and energy drinks (19%), as well as fruit and vegetable juices and drinks (13%) .
To date, detailed monitoring of SSB consumption patterns has been infrequent and protracted due to the complexity of population-level dietary surveys. Consequently, it has offered limited insight into the behavioural and attitudinal correlates of SSB consumption. Australian national data collection last occurred in 2011–12, indicating that 50% of Australians consumed an SSB on the day before the interview . Rates of consuming 100% fruit juice were lower at 23% for children (2–18 years) and 15% for adults (19 years and over) with few demographic differences . Rates of SSB consumption were higher among males compared to females, and for adolescents and young adults compared to other age groups . Another study reporting on state-based data collected in 2009 (Western Australia) and 2012 (South Australia) indicated that SSB consumers were more likely to be male, have little interest in health, or have purchased meals away from home . Other research has demonstrated that frequent SSB consumption is associated with other poorer dietary consumption patterns, including regular fast food consumption [14,15,16,17].
Measurement of sugary drink consumption is typically sporadic and nutrition focussed, and there is limited knowledge of community perceptions and awareness of the health risks associated with excess SSB consumption. The current study sought to fill this gap by generating essential population-based evidence to inform public health efforts to reduce consumption. A key aim of the study was to determine the frequency of past week SSB consumption and examine the correlates of consumption. SSB consumption was defined as frequency of past week consumption of any of the following: soft drinks; energy drinks; sports drinks; fruit drinks or cordials; and excluded 100% fruit juice and artificially sweetened drinks. The SSB definition excluded 100% fruit juice, which, although somewhat controversial (e.g. Rampersaud et al. ) is increasingly acknowledged as a problematic source of free sugar and excess calories (e.g. Popkin & Hawkes ). A second unique aim of the study was to explore the prevalence and correlates of 100% fruit juice consumption.
The South Australian Health Omnibus Survey (SAHOS) was used to collect data. The survey utilised a multi-stage, stratified, random sampling strategy to identify households eligible for inclusion. The sampling frame represented the South Australian population aged 15 years and over residing in areas with 1000 people or more. One interview was conducted per household, with the person whose birthday occurred last selected for interview. Up to six call back visits were made to obtain the interview of the eligible selected person. Participants were interviewed face-to-face by trained research assistants. An approach letter was sent 2 weeks in advance of the interview. The letter contained the study aims, ethics committee contact information, and details about participation, including that it was voluntary and results would be anonymous. Verbal agreement to participate in the study was considered informed consent and explicit verbal consent was obtained from parents/guardians for participants aged 15 to 17 years. Pilot testing occurred in August and field-work for the full study occurred between September and December 2014. From the 5200 households selected, 2732 interviews were conducted, yielding a response rate (i.e. proportion of completed interviews from initial eligible sample) of 54.5% and a participation rate (i.e. proportion of completed interviews from initial eligible sample where contact was established) of 60.6%. The study, including the approach to informed consent, was approved by the University of Adelaide Human Research Ethics Committee.
The SAHOS contained approximately 150 health and socio-demographic related questions requiring self-reported responses. This study reports on responses to a subset of questions pertaining to correlates of SSB consumption. The wording of questions, including definitions, are reported in Additional file 1 along with the corresponding variable sub-categories used in the analysis. For the first set of the analyses, SSB consumption was the outcome variable. SSBs were defined as all non-alcoholic water-based beverages with added sugar, including soft drinks, energy drinks, fruit drinks, sports drinks and cordials. The definition excluded milk-based products, 100% fruit juice or artificially sweetened beverages. SSB consumption was calculated by multiplying two questions: ‘number of days consumed SSBs in past week’ and ‘frequency of consumption per day’. Responses were split into categories: ‘none’ vs ‘any’ (1 or more drinks per week). As daily consumption is often reported in studies using dietary interviews (e.g. 11), ‘any’ consumption was split into ‘moderate’ (1 to 6 drinks) and ‘frequent’ (7 or more drinks) to approximate levels of consumption equivalent to less than daily versus daily, respectively. Predictor variables were grouped into three categories: demographic characteristics (gender, age, highest qualification and postcode derived socio-economic disadvantage  and remoteness ); risk factors (Body Mass Index [BMI; calculated from self-reported height and weight], past week physical activity, fast food consumption, 100% fruit juice consumption and smoking status); and SSB attitudes and knowledge (teaspoons of sugar in can of soft drink, perceived healthiness of diet soft drinks compared to SSBs, beliefs about sugar content of 100% fruit juice compared to SSBs, and knowledge of illnesses related to SSB consumption). The association between 100% fruit juice consumption, defined as having ‘none’ or ‘any’ (1 or more in the past week), and demographic characteristics and risk factors were also explored.
Statistical analyses were conducted using SPSS version 24 . Descriptive analyses of the association between participant characteristics and 1) SSB consumption (none, moderate or frequent) and 2) 100% fruit juice consumption (none or any) were undertaken using Pearson’s chi-square tests. The adjusted standardised residual for each cell of the Pearson’s chi-square test was used to detect whether the obtained value for each demographic subgroup was lower or higher than expected relative to the percentages for overall SSB consumption. The Mantel-Haenszel test of linear trends was also used for the SSB outcome variable. Multivariate analyses were used to test the same relationships while also controlling for the influence of other variables. The ‘Complex samples: Logistic regression’ analysis in SPSS was used to control for the clustered sampling design frame. Demographic characteristics were analysed as a group of predictors for both SSB and 100% fruit juice consumption. Subsequent analyses controlled for demographic characteristics while testing the association between SSB consumption and 1) risk factors and 2) SSB attitudes and knowledge; and between 100% fruit juice consumption and risk factors. Data were weighted by the inverse of the individual’s probability of selection, as well as the response rate in metropolitan and country regions and then re-weighted to benchmarks derived from the June 2013 ABS Estimated Resident Population .
Just over half of respondents had consumed SSBs at least once in the past week, either 1 to 6 times (i.e., moderate consumption; 35%) or 7 or more times (i.e. frequent consumption; 16%). Just over a third of respondents had consumed 100% fruit juice either 1 to 6 days (25%) or every day (10%) in the past week. Overall 19.7% had consumed both 100% fruit juice and SSBs in the past week, whereas 33.8% had consumed neither 100% fruit juice nor SSBs.
Demographic, BMI and behavioural risk factors and attitude and knowledge characteristics of the 2732 respondents included in the study are displayed in Table 1. SSB consumption was significantly associated with nearly all the variables listed in Table 1. Many of the relationships exhibited a linear trend with each categorical increase in consumption. Moderate and frequent consumers shared similar characteristics, and the most pronounced differences were between frequent consumers and non-consumers. Based on the adjusted standardised residuals of the Pearson chi-square test, frequent consumers were more likely than non-consumers to be male compared to female, younger (15–24 years) compared to older (45–64 years) participants, have lower compared to higher education, live in areas of higher disadvantage compared to low disadvantage, and live in remote compared to metropolitan areas. The highest rates of frequent SSB consumption in the past week were among those consuming fast food two or more times in the past week (42%) and current smokers (38%). Consumption of 100% fruit juice was more likely among moderate SSB consumers than non-consumers. Physical activity had a non-linear trend with SSB consumption group; frequent consumers were less likely to be physically active, moderate consumers were more likely to participate in some activity, and non-consumers were more likely to be the most active. There was no association between consumption and self-reported Body Mass Index.
Differences in attitudes and knowledge between consumption subgroups were also greatest between frequent consumers and non-consumers, although trends were not always linear. Overall, 34% of participants gave a response approximating the correct number of teaspoons of sugar (8 to 12) in a 375 ml (12.7 oz) can of soft drink (soda). Underestimating sugar content in soft drink was more common in moderate and frequent consumers than in non-consumers. Diet soft drinks (soda) and SSBs were rated as having the same level of healthiness by 51% of participants whereas 27% rated diet soft drinks as less healthy. Frequent consumers of SSBs were more likely to rate diet soft drinks as less healthy than the same level of healthiness. Equivalent proportions of participants accurately believed that 100% fruit juice contained the same amount of sugar as SSBs (43%) or believed juice had less (41%). Compared to non-consumers, frequent SSB consumers were less likely to rate 100% fruit juice as having the same amount of sugar as SSBs, but were more likely to rate it as having either more sugar or less sugar. Unprompted awareness of illnesses known to be associated with SSB consumption ranged from 15% for heart disease risk to 61% for diabetes. Awareness of illnesses/health effects (weight gain, diabetes and heart disease) was negatively associated with consumption.
Table 2 displays logistic regression results that tested the association between ‘none’ versus ‘any’ SSB consumption and demographic characteristics, BMI and behavioural risk factors and attitudes and knowledge. The odds of being a SSB consumer was consistently greater for males compared to females, for all age groups under 65 years compared to over 65 years, and was greatest for those aged 15 to 24 years, for those with vocational qualifications or less compared to university qualifications, and for those living in remote/very remote areas compared to metropolitan areas. Risk factors associated with consumption, controlling for demographics, were fast food consumption, 100% fruit juice consumption and smoking status. The association between SSB consumption and consuming fast food two or more times in the past week (compared to none) was particularly strong at over 5 times the odds. There were few statistically significant relationships between attitudes and knowledge and consumption when controlling for demographics. The odds of being a consumer were slightly greater for those who rated diet soft drink as less healthy than SSBs compared to those who rated them as healthier, and for those who did not recall weight gain as being related to consumption compared to those who did.
As shown in Table 3, 35% of respondents reported consuming 1 or more 100% fruit juice drinks in the past week. There were bi-variate associations between 100% fruit juice consumption and all the demographics and risk factor variables listed in Table 3 except for self-reported Body Mass Index. In the logistic regression testing demographic characteristics only (not reported in table), 100% fruit juice consumption in the past week was only associated with gender (males more likely than females; OR = 1.5, 95%CI = 1.2–1.8, p < 0.001) and age (15–24 years [OR = 1.4, 95%CI = 1.1–1.9, p = 0.005] and 25–44 years [OR = 1.4, 95%CI = 1.1–1.97, p = 0.005] more likely than those aged 65 years and over). In the combined demographic and risk factor model (see Table 3), past week 100% fruit juice consumption was more likely among males compared to females, those who participated in physical activity everyday compared to none in the past week, and those who rated 100% fruit juice as having the same or less sugar as SSBs rather than more sugar. There was less likelihood of consuming 100% fruit juice among ex-smokers compared to those who had never smoked.
Using our brief measure, more than half of the participants in this study had consumed SSBs in the past week, with 16% consuming SSBs frequently (7 or more drinks weekly). Over one third of respondents had consumed 100% fruit juice in the past week, with 10% consuming every day. Consistent with other Australian data [10, 13, 24], consumption of SSBs in the past week was consistently higher among males, younger age groups and groups with lower educational attainment. Similarly, 100% fruit juice consumption was higher among males (in both bivariate and multivariate comparisons), and among younger age groups in bivariate (unadjusted) analyses. Unlike SSB consumption, 100% fruit juice consumption was higher among those with higher educational attainment and among less disadvantaged groups, although these factors were not significant when also accounting for age and gender.
Among the behavioural risk factors assessed, fast food consumption was most strongly associated with SSB consumption. Those who had consumed fast food in the past week had nearly twice the odds of being a consumer of SSBs and more frequent consumers of fast food (twice or more in past week) had over 5 times the odds. The linear relationship we observed between SSB consumption and other fast food consumption is consistent with other findings [13,14,15,16,17, 25, 26]. A qualitative study conducted with young adults in Australia identified strong social cues to purchase and consume SSBs . This study found that SSB consumption was considered normal because of the ready availability, cheapness, and advertising and promotion of these drinks, and that SSB consumption was closely linked to purchasing fast-food and take-away meals. The strong association between fast food and SSB consumption is important because of compounding dietary risks from excess sugar, salt and fat. The pairing of SSBs with fast food is likely driven by availability at times of purchase, promotions, as well as pricing and ‘packaging’ of SSBs with food. Those who consumed juice were marginally more likely to have consumed fast food in the past week (bi-variate analysis only), and while 84% of those who consumed fast food twice or more per week also consumed SSBs, only 37% consumed 100% fruit juice.
We observed a clustering of ‘unhealthy’ behaviours (smoking and fast food consumption) with SSB consumption and not 100% fruit juice consumption, and an association between healthy behaviour (exercise) and 100% fruit juice consumption. Although juices frequently contain as much free sugar as soft drink (soda), community awareness of this is mixed, as we observed in our sample, and juice may have a ‘health halo’ not applied to soft drink [28, 29]. The relationship between exercise and different SSB types, e.g. sports drinks, was not investigated in this study; however, there was a positive association between exercise and consumption of 100% fruit juice, which persisted in the multivariate analysis. Given that some drinks are marketed as offering functional or health benefits, and the relationships we have observed in this study between health behaviours and juice consumption, consumer perceptions of different types of beverages high in free sugar (including juice) warrant further investigation.
This study found no relationship between self-reported weight status (BMI) and SSB consumption or 100% fruit juice consumption. Systematic reviews of prospective cohort and randomised control trial studies have clearly demonstrated that SSB consumption can lead to weight gain . However, correlational studies are less consistent and the relationship tends to vary according to drink type and location. For example, one Australian study found that soft drink consumption was higher for those classified as either overweight or obese in South Australia but was only higher for those classified as obese in Western Australia . Another Western Australian study found that those classified as overweight/obese were more likely to consume both sugar-sweetened and artificially sweetened soft drinks but there was no relationship for those who only consumed sugar-sweetened soft drinks . BMI was not associated with SSB consumption but was associated with fruit juice consumption in a Norwegian study . A US study of sports and energy drinks found that consumption was more likely for those classified as healthy weight . It is important for future studies to assess drink types independently because a combined measure may mask important differences in the risk factors associated with consumption.
The results of this study suggested a lack of awareness of the contents of the drinks participants are consuming, as well as of the potential risks associated with excess consumption. Only 34% of respondents knew the approximate amount of sugar in a can of soft drink and a further one third underestimated the sugar content. While there was reasonable awareness of diabetes as a potential risk of excess SSB consumption among this sample (approx. two thirds of participants were aware), less than half recalled weight gain (42.5%), tooth decay (29.1%), or heart disease (14.9%) as potential risks. Frequent SSB consumers had lower rates of awareness of health risks and were more likely to underestimate sugar content in a can of soft drink than non-consumers. While the evidence of cardiovascular risk as a result of excess consumption is emergent, evidence for dental caries and weight gain is longer standing, highlighting the deficit in community understanding of the risks of excess SSB consumption. While one US study observed higher (70–80%) levels of awareness of weight gain, diabetes and dental caries  than that observed in the present study, these data reflected prompted awareness rather than unprompted, top-of-mind responses such as those assessed in this study. Several other US studies have also established poor awareness of the sugar content and calorie count of soft drinks [33, 34]. The results also indicate confusion about the relative merits of diet soft drinks compared to SSBs. Approximately one quarter of participants indicated diet drinks were less healthy than SSBs, a minority (17%) indicated they were healthier, and half indicated they were ‘about the same’. This consumer confusion is unsurprising given the changing state of evidence regarding diet beverages. Similarly to juice, consumers knowledge and beliefs about diet beverages warrant further investigation.
Industry repeatedly argues that information about sugar content and caloric count is available to consumer in nutrition information panels. While the US Food and Drug Administration has mandated the inclusion of added sugar on nutrition information labels in recognition of the scientific evidence about free sugars , information on added sugar content is not available to Australian consumers, despite advocacy for such a change. Furthermore, greater health literacy (i.e. capacity to understand basic health information needed to make appropriate health decisions) has been shown to be related to lower SSB intake . This also highlights the need to either increase health literacy or provide information that is easy to understand, or both. There is a growing body of evidence that shows that that on-pack health warning labels [37,38,39,40] and mass media advertising on health effects of SSBs [41,42,43] help to improve understanding of the potentially harmful effects of consuming SSBs and may reduce SSB sales .
The present study analysed data from a representative face-to-face household survey in one Australian state and, while the results may not necessarily generalise to other states or countries, the results are consistent with those reported in other jurisdictions. The present study was cross-sectional so it is difficult to infer causality from the observed significant associations. Another limitation was the use of a brief, self-report consumption measure which relied on participants’ memory without additional prompting or cueing to aid recall. This may have produced an under-estimate of SSB consumption compared to an assessment using a 24-h recall interview method. It is possible that participants were not accurate in their self-reported body weight which may have reduced the likelihood of detecting an effect associated with BMI. It was not possible to compare responders to non-responders. However, an under-estimate of SSB consumption rates could have occurred through non-response bias if those with unhealthy lifestyles were less likely to respond to a health survey than those with healthy lifestyles.
To conclude, the low rates of awareness of the health risks associated with SSB consumption and the low awareness of sugar content in SSBs, demonstrate that there is a need for greater consumer understanding. This is especially the case among frequent consumers who are the most at risk of harms associated with SSB consumption, and where there is also clustering with other unhealthy consumption behaviours. Potential strategies include public communication campaigns, the use of on-package warning labels which contain sugar content and/or risk information, and improvements to existing nutrition information panels so that quantity of ‘added sugar’ is clear. Further research that explores consumer response to risk information and perceptions of substitute beverages of fruit juice and diet drinks is warranted.
Body Mass Index
South Australian Health Omnibus Survey
Sugar sweetened beverage
World Health Organisation
World Health Organization. Guideline: sugars intake for adult and children. Geneva: WHO; 2015.
Malik VS, Pan A, Willett WC, Hu FB. Sugar-sweetened beverages and weight gain in children and adults: a systematic review and meta-analysis. Am J Clin Nutr. 2013;98(4):1084–102.
Malik VS, Popkin BM, Bray GA, Despres JP, Hu FB. Sugar-sweetened beverages, obesity, type 2 diabetes mellitus, and cardiovascular disease risk. Circulation. 2010;121(11):1356–64.
Bernabe E, Vehkalahti MM, Sheiham A, Aromaa A, Suominen AL. Sugar-sweetened beverages and dental caries in adults: a 4-year prospective study. J Dent. 2014;42(8):952–8.
Keller A, Heitmann BL, Olsen N. Sugar-sweetened beverages, vascular risk factors and events: a systematic literature review. Public Health Nutr. 2015;18(7):1145–54.
World Health Organization. Fiscal policies for diet and prevention of noncommunicable diseases. Geneva: World Health Organization; 2016.
Backholer K, Blake M, Vandevijvere S. Sugar-sweetened beverage taxation: an update on the year that was 2017. Public Health Nutr. 2017;20(18):3219–24.
Sacks G for the Food-Epi Australia project team. Policies for tackling obesity and creating healthier food environments: scorecard and priority recommendations for Australian governments. Melbourne: Deakin University; 2017.
Australian Institute of Health and Welfare. A picture of overweight and obesity in Australia 2017. Cat. no.PHE 216. Canberra: AIHW; 2017.
Australian Bureau of Statistics. Australian Health Survey: consumption of added sugars. Australia 2011–12. Cat. no. 4364.0.55.011. Canberra: ABS; 2016. http://www.ausstats.abs.gov.au/ausstats/subscriber.nsf/0/84F8A7C39FBBDDEDCA257FA1002308ED/$File/4364.0.55.011_2011-12.pdf. Accessed 19 Apr 2018
Australian Bureau of Statistics. Australian health survey: nutrition first results - foods and nutrients, 2011–12. Cat. no. 4364.0.55.007 (2014). http://www.abs.gov.au/ausstats/abs@.nsf/lookup/4364.0.55.007main+features12011-12. Accessed 19 Apr 2018.
Fruit Juice Australia. The role of fruit juice in the Australian diet. A secondary analysis of the Australian Health Survey: National Nutrition and Physical Activity Survey (2011–12). Waterloo: Australian Beverages Council. http://fruitjuiceaustralia.org/wp-content/uploads/2015/08/FJA-Report-FA1.pdf (2013). Accessed 26 Feb 2018
Pollard CM, Meng X, Hendrie GA, Hendrie D, Sullivan D, Pratt IS, et al. Obesity, socio-demographic and attitudinal factors associated with sugar-sweetened beverage consumption: Australian evidence. Aust N Z J Public Health. 2016;40(1):71–7.
Larson N, Neumark-Sztainer D, Laska MN, Story M. Young adults and eating away from home: associations with dietary intake patterns and weight status differ by choice of restaurant. J Am Diet Assoc. 2011;111(11):1696–703.
Sharkey JR, Johnson CM, Dean WR. Less-healthy eating behaviors have a greater association with a high level of sugar-sweetened beverage consumption among rural adults than among urban adults. Food Nutr Res. 2011;55(1):5819.
Taksler GB, Kiszko K, Abrams C, Elbel B. Adults who order sugar-sweetened beverages: sociodemographics and meal patterns at fast food chains. Am J Prev Med. 2016;51(6):890–7.
Duffey KJ, Popkin BM. Adults with healthier dietary patterns have healthier beverage patterns. J Nutr. 2006;136(11):2901–7.
Rampersaud GC, Kim H, Gao Z, House LA. Knowledge, perceptions, and behaviors of adults concerning nonalcoholic beverages suggest some lack of comprehension related to sugars. Nutr Res. 2014;34(2):134–42.
Popkin BM, Hawkes C. Sweetening of the global diet, particularly beverages: patterns, trends, and policy responses. Lancet Diabetes Endocrinol. 2016;4(2):174–86.
Australian Bureau of Statistics. Census of Population and Housing: Socio-economic Indexes for Areas (SEIFA), Australia. Cat. no. 2033.0.55.001 (2011). http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/2033.0.55.001main+features32011. Accessed 19 Apr 2018.
Australian Bureau of Statistics. Australian Statistical Geography Standard (ASGS): Volume 5 - Remoteness Structure, July 2011. Cat. no. 1270.0.55.005 (2013). http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/1270.0.55.005Main+Features1July%202011?OpenDocument. Accessed 19 Apr 2018.
IBM Corp. IBM SPSS Statistics for Windows, Version 21.0. Armonk: IBM Corp; 2012.
Australian Bureau of Statistics. Australian demographic statistics, Jun 2013. Cat. no. 3101.0 (2013). http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/3101.0Main+Features1Jun%202013?OpenDocument. Accessed 26 Feb 2018.
French S, Rosenberg M, Wood L, Maitland C, Shilton T, Pratt IS, et al. Soft drink consumption patterns among Western Australians. J Nutr Educ Behav. 2013;45(6):525–32.
Gustafson AA, Putnam N, Adams I, Wu Q, Christian WJ, Spees C, et al. Family meals and neighborhood food resources influence on intake of sugar-sweetened beverages and added sugars among parents and adolescents in rural counties. J Community Med Health Educ. 2014;4(4). https://doi.org/10.4172/2161-0711.1000300.
Park S, Pan L, Sherry B, Blanck HM. Consumption of sugar-sweetened beverages among US adults in 6 states: behavioral risk factor surveillance system, 2011. Prev Chronic Dis. 2014;11:E65.
Hattersley L, Irwin M, ing L, Allman-Farinelli M. Determinants and patterns of soft drink consumption in young adults: a qualitative analysis. Public Health Nutr. 2009;12(10):1816–22.
Duffett RG. Consumption patterns and demographic factors influence on fruit juice classifications, health benefits and sugar content perceptions in two municipal districts in Cape Town, Western cape, South Africa. SAJCN. 2018;31(1):20–8.
Duffett RG. Consumer perceptions toward sugar content of fruit juice products in a developing country. J Food Prod Mark. 2018;24(6):745–60.
Paulsen M, Myhre J, Andersen L. Beverage consumption patterns among Norwegian adults. Nutrients. 2016;8(9):561.
Park S, Onufrak S, Blanck HM, Sherry B. Characteristics associated with consumption of sports and energy drinks among US adults: National Health Interview Survey, 2010. J Acad Nutr Diet. 2013;113(1):112–9.
Park S, Lundeen EA, Pan L, Blanck HM. Impact of knowledge of health conditions on sugar-sweetened beverage intake varies among US adults. Am J Health Promot. 2017;32:1402–8.
Park S, Onufrak S, Sherry B, Blanck HM. The relationship between health-related knowledge and sugar-sweetened beverage intake among US adults. J Acad Nutr Diet. 2014;114(7):1059–66.
Gase LN, Robles B, Barragan NC, Kuo T. Relationship between nutritional knowledge and the amount of sugar-sweetened beverages consumed in Los Angeles County. Health Educ Behav. 2014;41(4):431–9.
U.S Food & Drug Administration. Changes to the Nutrition Facts Label (2017). https://www.fda.gov/Food/GuidanceRegulation/GuidanceDocumentsRegulatoryInformation/LabelingNutrition/ucm385663.htm. Accessed 26 Feb 2018.
Zoellner J, You W, Connell C, Smith-Ray RL, Allen K, Tucker KL, et al. Health literacy is associated with healthy eating index scores and sugar-sweetened beverage intake: findings from the rural lower Mississippi Delta. J Am Diet Assoc. 2011;111(7):1012–20.
Acton RB, Hammond D. The impact of price and nutrition labelling on sugary drink purchases: results from an experimental marketplace study. Appetite. 2018;121(Supplement C):129–37.
VanEpps EM, Roberto CA. The influence of sugar-sweetened beverage warnings: a randomized trial of adolescents’ choices and beliefs. Am J Prev Med. 2016;51(5):664–72.
Roberto CA, Wong D, Musicus A, Hammond D. The influence of sugar-sweetened beverage health warning labels on parents’ choices. Pediatrics. 2016;137(2):131.
Bollard T, Maubach N, Walker N, Ni Mhurchu C. Effects of plain packaging, warning labels, and taxes on young people’s predicted sugar-sweetened beverage preferences: an experimental study. Int J Behav Nutr Phys Act. 2016;13(1):1–7.
Jordan A, Bleakley A, Hennessy M, Vaala S, Glanz K, Strasser AA. Sugar-sweetened beverage-related public service advertisements and their influence on parents. Am Behav Sci. 2015;59(14):1847–65.
Boles M, Adams A, Gredler A, Manhas S. Ability of a mass media campaign to influence knowledge, attitudes, and behaviors about sugary drinks and obesity. Prev Med. 2014;67:S40–5.
Barragan NC, Noller AJ, Robles B, Gase LN, Leighs MS, Bogert S, et al. The “sugar pack” health marketing campaign in Los Angeles County, 2011-2012. Health Promot Pract. 2014;15(2):208–16.
Farley TA, Halper HS, Carlin AM, Emmerson KM, Foster KN, Fertig AR. Mass media campaign to reduce consumption of sugar-sweetened beverages in a rural area of the United States. Am J Public Health. 2017;107(6):989–95.
Undertaken with the financial support of Cancer Council’s Beat Cancer Project on behalf of its donors and the State Government through the Department of Health. The funding body had no input into any aspect of the study.
Availability of data and materials
The datasets analysed during the current study available from the corresponding author on reasonable request.
Ethics approval and consent to participate
The University of Adelaide Human Research Ethics Committee approved all aspects of this study, including the verbal informed consent procedure. As the interview was conducted face-to-face by trained interviewers, informed consent was obtained using a verbal agreement to participate in the study 2 weeks after receiving an introductory letter which explained that participation was voluntary and results would be anonymous. Explicit verbal consent to interview participants aged 15 to 17 years was obtained from parents/guardians.
Consent for publication
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Miller, C., Wakefield, M., Braunack-Mayer, A. et al. Who drinks sugar sweetened beverages and juice? An Australian population study of behaviour, awareness and attitudes. BMC Obes 6, 1 (2019). https://doi.org/10.1186/s40608-018-0224-2
- Sugar-sweetened beverages
- 100% fruit juice
- Population survey
- Risk factors