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  • Research article
  • Open Access
  • Open Peer Review

Who drinks sugar sweetened beverages and juice? An Australian population study of behaviour, awareness and attitudes

BMC Obesity20196:1

https://doi.org/10.1186/s40608-018-0224-2

  • Received: 24 April 2018
  • Accepted: 18 December 2018
  • Published:
Open Peer Review reports

Abstract

Background

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.

Methods

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.

Results

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.

Conclusions

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.

Keywords

  • Sugar-sweetened beverages
  • 100% fruit juice
  • Population survey
  • Risk factors
  • Attitudes
  • Knowledge
  • Awareness

Background

Excess consumption of added and free sugars are gaining increasing attention as an environmental driver of obesity [1]. 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 [2], Type 2 diabetes [3], tooth decay [4] and emergent evidence of cardiovascular risks [5]. 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 [8].

At 63%, the rate of overweight and obesity in Australia is among the highest in the world [9], with the rate of obese Australians tripling since 1990. Australians are also high consumers of SSBs [10], 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%) [10].

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 [11]. 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 [12]. Rates of SSB consumption were higher among males compared to females, and for adolescents and young adults compared to other age groups [11]. 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 [13]. Other research has demonstrated that frequent SSB consumption is associated with other poorer dietary consumption patterns, including regular fast food consumption [1417].

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. [18]) is increasingly acknowledged as a problematic source of free sugar and excess calories (e.g. Popkin & Hawkes [19]). A second unique aim of the study was to explore the prevalence and correlates of 100% fruit juice consumption.

Methods

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 [20] and remoteness [21]); 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 [22]. 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 [23].

Results

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.
Table 1

Respondent characteristics and sugar sweetened beverage (SSB) consumption by demographic subgroup (N = 2372)

 

Overall sample

SSB consumption in past week by demographic subgroupa

Chi-square tests

 

None

 

Moderate (1–6 times)

Frequent (7+ times)

 

Pearson

Trendf

%

N

%

 

%

 

%

 

N

P-value

P-value

SSB consumption in past weeke

100.0

2732

48.8

 

34.7

 

16.0

    

Demographics

Gender

        

2719

< 0.001

< 0.001

 Male

49.2

1337

38.4

40.8

20.8

   

 Female

50.8

1382

59.3

29.2

11.4

   

Age (years)

        

2717

< 0.001

< 0.001

 15–24

16.0

430

27.4

50.0

22.6

   

 25–44

32.1

872

38.6

39.8

21.6

   

 45–64

31.6

861

54.5

32.9

 

12.7

   

 65 and over

20.3

554

73.8

18.8

7.4

   

Highest qualificationb

        

2716

< 0.001

< 0.001

 High School or less

39.4

1069

45.0

35.3

 

19.7

   

 Vocational

35.8

977

47.5

 

34.7

 

17.8

    

 University

24.7

670

57.6

34.8

 

7.6

   

Disadvantage quintile

        

2719

< 0.001

< 0.001

 Quintile 1 (most disadvantaged)

23.2

628

46.2

 

32.2

 

21.7

   

 Quintile 2

16.2

441

44.7

34.9

 

20.4

   

 Quintile 3

20.1

548

47.6

 

35.8

 

16.6

    

 Quintile 4

21.1

577

50.8

 

39.3

9.9

   

 Quintile 5 (least disadvantaged)

19.3

525

55.8

32.4

 

11.8

   

Remoteness

        

2721

< 0.001

< 0.001

 Metropolitan

74.8

2034

49.9

 

35.9

 

14.2

   

 Inner Regional

9.5

259

48.3

 

37.5

 

14.3

    

 Outer Regional

13.4

366

47.0

 

27.9

25.1

   

 Remote/very remote

2.3

62

35.5

32.3

 

32.3

   

Body Mass Indexd

        

2710

0.719

0.494

 Underweight or healthy

38.6

1048

49.0

 

35.3

 

15.6

    

 Overweight

29.9

814

47.5

 

35.9

 

16.6

    

 Obese

21.0

572

52.1

 

32.2

 

15.7

    

 Don’t know either height or weight

10.1

276

47.1

 

35.9

 

17.0

    

Behavioural risk factors

Physical activity (past week)c

        

2718

< 0.001

0.071

 None

18.7

509

47.5

 

32.0

 

20.4

   

 1 to 6 days

58.0

1578

47.7

 

38.7

13.7

   

 Everyday

23.1

631

53.7

27.9

18.4

    

Fast food consumption (past week)b

       

2718

< 0.001

< 0.001

 None

52.4

1430

64.3

28.0

7.7

   

 Once

29.2

790

42.2

43.0

14.8

    

 Two or more times

18.3

498

16.3

41.8

42.0

   

100% fruit juice consumption (past week)d

        

2712

< 0.001

0.007

 None

64.7

1764

52.3

31.3

16.4

    

 One or more times

35.0

948

43.2

41.5

15.3

    

Smoking status

        

2718

< 0.001

< 0.001

 Current smoker

15.3

417

30.7

31.2

 

38.1

   

Ex-smoker

28.9

789

56.9

29.8

13.3

   

Never smoked

55.7

1512

50.0

 

38.6

11.4

   

Attitudes and knowledge

Teaspoons of sugar in can of soft drinkc

        

2713

< 0.001

0.093

 Underestimate 0 to 7

29.8

809

42.4

38.6

19.0

   

 Approx correct 8 to 12g

33.5

910

48.6

 

37.1

 

14.3

    

 Overestimate 13 to 99

20.9

568

52.5

 

35.7

 

11.8

   

 Don’t know

15.6

426

58.0

22.5

19.5

   

Diet soft drinks versus SSBsb

        

2718

0.002

0.436

 More healthy

17.3

473

52.9

 

33.0

 

14.2

    

 Less healthy

26.8

727

44.4

35.2

 

20.4

   

 The same

50.8

1384

49.3

 

36.1

 

14.6

   

 Don’t know

4.9

134

57.5

28.4

 

14.2

    

100% fruit juice versus SSBsb

       

2717

< 0.001

< 0.001

 More sugar

8.6

234

47.0

 

31.6

 

21.4

   

 Less sugar

40.8

1111

45.4

36.3

 

18.4

   

 The sameg

42.5

1156

52.2

35.2

 

12.6

   

 Don’t know

8.1

216

53.7

 

29.6

 

16.7

    

Awareness of illnesses/health effects related to SSB consumption

        

2719

< 0.001

< 0.001

Weight gain

 No

57.5

1566

45.7

36.7

17.7

   

 Yesg

42.5

1153

53.7

32.5

13.8

   

Diabetes

        

2719

< 0.001

< 0.001

 No

39.0

1061

44.8

34.0

 

21.2

   

 Yesg

61.0

1658

51.8

35.5

 

12.7

   

Tooth decay

        

2719

0.601

0.761

 No

70.9

1933

49.5

 

34.4

 

16.2

    

 Yesg

29.1

786

48.0

 

36.4

 

15.6

    

Heart disease

        

2718

0.022

0.036

 No

85.1

2314

48.6

 

34.5

 

16.9

   

 Yes

14.9

404

51.5

 

37.1

 

11.4

   

Note: Adjusted standardised residuals used to detect statistical significance within cells of Pearson’s chi-square results (represented as arrows); Relative to percentages for overall SSB consumption in the past week, cells with percentages greater than expected = ↑ and cells with values lower than expected = ↓ at the p < 0.05 level

aExcluding ‘not stated’ response category; bNot stated = 0.1%, cnot stated = 0.2%, dnot stated = 0.3%, enot stated = 0.5%

fMantel-Haenszel test of linear trends; gMost correct answer based on current evidence

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.
Table 2

Logistic regression of ‘any’ versus ‘none’ past week sugar sweetened beverage (SSB) consumption

 

1. Demographics

2. Demographics & risk factors

3. Demographics & knowledge

OR

95% CI

OR

95% CI

OR

95% CI

Lower

Upper

Lower

Upper

Lower

Upper

(N)

2714

  

2696

  

2705

  

Demographics

Gender

 Male

2.5***

2.0

3.1

2.1***

1.7

2.6

2.4***

1.9

2.9

 Female

1

  

1

  

1

  

Age (years)

 15–24

7.6***

5.3

10.8

4.3***

2.9

6.5

7.4***

4.9

11.2

 25–44

5.5***

4.2

7.1

3.3***

2.5

4.4

5.7***

4.3

7.4

 45–64

2.5***

1.9

3.3

1.9***

1.5

2.5

2.6***

2.0

3.5

 65 and over

1

  

1

  

1

  

Highest qualification

 High School or less

2.0***

1.5

2.6

1.7***

1.4

2.2

1.9***

1.5

2.4

 Vocational

1.7***

1.3

2.2

1.6**

1.2

2.1

1.6***

1.3

2.1

 University

1

  

1

  

1

  

Disadvantage quintile

 Quintile 1 (most disadvantaged)

1.4

1.0

1.9

1.1

0.8

1.6

1.3

0.9

1.9

 Quintile 2

1.4

1.0

1.9

1.1

0.8

1.6

1.2

0.9

1.8

 Quintile 3

1.4

1.0

1.9

1.2

0.9

1.7

1.3

0.9

1.9

 Quintile 4

1.2

0.9

1.6

1.0

0.8

1.4

1.1

0.8

1.5

 Quintile 5 (least disadvantaged)

1

  

1

  

1

  

Remoteness

 Metropolitan

1

  

1

  

1

  

 Inner Regional

1.0

0.7

1.6

1.1

0.7

1.7

1.1

0.7

1.6

 Outer Regional

1.0

0.8

1.4

1.0

0.8

1.2

1.0

0.8

1.4

 Remote/very remote

1.7**

1.3

2.4

1.4*

1.1

1.9

1.8***

1.4

2.4

BMI and Behavioural risk factors

Body Mass Index (BMI)

 Underweight or healthy

   

1

     

 Overweight

   

1.2

0.9

1.5

   

 Obese

   

1.0

0.8

1.2

   

 Don’t know height or weight

   

0.9

0.6

1.4

   

Physical activity (past week)

 None

   

1

     

 1 to 6 days

   

1.0

0.8

1.2

   

 Everyday

   

0.8

0.5

1.1

   

Fast food consumption (past week)

 None

   

1

     

 Once

   

1.9***

1.6

2.4

   

 Two or more times

   

5.3***

3.5

8.0

   

100% fruit juice consumption (past week)

 None

   

1

     

 One or more times

   

1.3*

1.0

1.7

   

Smoking status

 Current smoker

   

1.7**

1.2

2.5

   

 Ex-smoker

   

0.9

0.7

1.1

   

 Never smoked

   

1

     

Attitudes and knowledge

Teaspoons of sugar in can of soft drink

 Approx correct 8 to 12

      

1

  

 Underestimate 0 to 7

      

1.2

1.0

1.6

 Overestimate 13 to 99

      

0.8

0.6

1.0

 Don’t know

      

0.8

0.6

1.1

Diet soft drinks versus SSBs

 More healthy

      

1

  

 Less healthy

      

1.3*

1.0

1.8

 The same

      

1.1

0.8

1.4

 Don’t know

      

1.1

0.7

1.8

100% Fruit juice versus SSBs

 More sugar

      

1

  

 Less sugar

      

1.1

0.8

1.5

 The same

      

0.9

0.7

1.3

 Don’t know

      

0.8

0.5

1.4

Awareness of illnesses/health effects related to SSB consumption

Weight gain (ref = Recalled)

      

1

  

 Not recalled

      

1.2*

1.0

1.4

Diabetes (ref = Recalled)

      

1

  

 Not recalled

      

1.1

1.0

1.3

Tooth decay (ref = Recalled)

      

1

  

 Not recalled

      

1.0

0.8

1.3

Heart disease (ref = Recalled)

      

1

  

 Not recalled

      

1.0

0.8

1.3

Logistic regression outcome variable: Any SSB consumption in past week = 1, none = 0

***p < 0.001; **p < 0.01; *p < 0.05

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.
Table 3

Association between 100% fruit juice consumption and respondent characteristics (N = 2732)

 

100% fruit juice consumption in past week

Logistic regression

None

1 or more

Pearson χ2

OR

95% CI

%

%

P-value

(N = 2702)

Lower

Upper

100% fruit juice consumption in past weekc

64.7

35.0

    

Demographics

Gender

  

< 0.001

   

 Male

60.4

39.6

 

1.5***

1.2

1.8

 Female

69.2

30.8

    

Age (years)

  

0.001

   

 15–24

60.5

39.5

 

1.2

0.9

1.5

 25–44

61.3

38.7

 

1.2

0.9

1.5

 45–64

67.7

32.3

 

1.0

0.8

1.2

 65 and over

69.5

30.5

 

1

  

Highest qualificationa

  

0.017

   

 High School or less

66.5

33.5

 

0.9

0.6

1.2

 Vocational

66.2

33.8

 

0.8

0.7

1.0

 University

60.3

39.7

 

1

  

Disadvantage quintile

  

0.002

   

 Quintile 1 (most disadvantaged)

70.8

29.2

 

0.8

0.6

1.2

 Quintile 2

65.4

34.6

 

1.0

0.7

1.4

 Quintile 3

63.6

36.4

 

1.1

0.8

1.5

 Quintile 4

60.0

40.0

 

1.3

0.9

1.7

 Quintile 5 (least disadvantaged)

64.1

35.9

 

1

  

Remoteness

  

0.006

   

 Metropolitan

63.4

36.6

 

1

  

 Inner Regional

64.1

35.9

 

1.0

0.6

1.5

 Outer Regional

72.9

27.1

 

0.7

0.5

1.1

 Remote/very remote

67.7

32.3

 

0.9

0.6

1.3

BMI and behavioural risk factors

Body Mass Index (BMI)c

  

0.205

   

 Underweight or healthy

64.5

35.5

 

1

  

 Overweight

62.9

37.1

 

1.2

0.9

1.5

 Obese

68.4

31.6

 

1.1

0.8

1.3

 Don’t know height or weight

65.2

34.8

 

1.1

0.7

1.8

Physical activity (past week)b

  

< 0.001

   

 None

73.0

27.0

 

1

  

 1 to 6 days

64.2

35.8

 

1.3

1.0

1.9

 Everyday

60.6

39.4

 

1.8***

1.3

2.5

Fast food consumption (past week) a

  

0.006

   

 None

67.6

32.4

 

1

  

 Once

61.2

38.8

 

1.2

1.0

1.5

 Two or more times

62.8

37.2

 

1.1

0.9

1.5

Smoking status

  

< 0.001

   

 Current smoker

64.5

35.5

 

0.9

0.7

1.2

 Ex-smoker

71.7

28.3

 

0.6***

0.5

0.8

 Never smoked

61.4

38.6

 

1

  

100% fruit juice versus SSBsa

  

< 0.001

   

 More sugar

75.3

24.7

 

1

  

 Less sugar

60.9

39.1

 

2.1***

1.6

2.9

 The same

65.2

34.8

 

1.7**

1.2

2.5

 Don’t know

72.1

27.9

 

1.4

0.8

2.3

Logistic regression outcome variable: Any 100% fruit juice consumption in past week = 1, none = 0

aNot stated = 0.1%, bnot stated = 0.2%, cnot stated = 0.3%

***p < 0.001; **p < 0.01; *p < 0.05

Discussion

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 [1317, 25, 26]. A qualitative study conducted with young adults in Australia identified strong social cues to purchase and consume SSBs [27]. 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 [2]. 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 [13]. 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 [24]. BMI was not associated with SSB consumption but was associated with fruit juice consumption in a Norwegian study [30]. A US study of sports and energy drinks found that consumption was more likely for those classified as healthy weight [31]. 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 [32] 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 [35], 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 [36]. 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 [3740] and mass media advertising on health effects of SSBs [4143] help to improve understanding of the potentially harmful effects of consuming SSBs and may reduce SSB sales [44].

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.

Conclusion

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.

Abbreviations

BMI: 

Body Mass Index

SAHOS: 

South Australian Health Omnibus Survey

SSB: 

Sugar sweetened beverage

WHO: 

World Health Organisation

Declarations

Acknowledgements

Not applicable.

Funding

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.

Authors’ contributions

CM and KE designed the study with input from MW, ABM, DR & KOD. JD analysed the results. CM and JD drafted the manuscript and all authors assisted with interpretation and revision of the manuscript. All authors read and approved the final manuscript.

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

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
School of Public Health, University of Adelaide, Adelaide, Australia
(2)
South Australian Health and Medical Research Institute (SAHMRI), Population Health Research Group, North Terrace, Adelaide, South Australia, Australia
(3)
Cancer Council Victoria, Centre for Behavioural Research in Cancer, Melbourne, Australia
(4)
School of Health & Society, University of Wollongong, Wollongong, New South Wales, Australia
(5)
Centre for Population Health Research, University of South Australia, Adelaide, Australia

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Copyright

© The Author(s). 2019

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