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

Who drinks sugar sweetened beverages and juice? An Australian population study of behaviour,... 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 * Correspondence: caroline.miller@sahmri.com School of Public Health, University of Adelaide, Adelaide, Australia South Australian Health and Medical Research Institute (SAHMRI), Population Health Research Group, North Terrace, Adelaide, South Australia, Australia Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This 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. Miller et al. BMC Obesity (2019) 6:1 Page 2 of 12 Background SSB consumption was defined as frequency of past week Excess consumption of added and free sugars are gaining consumption of any of the following: soft drinks; energy increasing attention as an environmental driver of obesity drinks; sports drinks; fruit drinks or cordials; and excluded [1]. Within this context, sugar-sweetened beverages (SSBs) 100% fruit juice and artificially sweetened drinks. The SSB are a focus due to their energy density, coupled with poor definition excluded 100% fruit juice, which, although nutritional value, and the strength of evidence linking somewhat controversial (e.g. Rampersaud et al. [18]) is their consumption with weight gain, obesity [2], Type 2 increasingly acknowledged as a problematic source of free diabetes [3], tooth decay [4] and emergent evidence of sugar and excess calories (e.g. Popkin & Hawkes [19]). A cardiovascular risks [5]. Countries are moving to try to second unique aim of the study was to explore the preva- reduce their population consumption of SSBs and a raft lence and correlates of 100% fruit juice consumption. of educative and regulatory interventions are being imple- mented [6, 7]. Australia lags other countries in compre- Methods hensive educative or regulatory responses to address SSB The South Australian Health Omnibus Survey (SAHOS) consumption and obesity more broadly [8]. was used to collect data. The survey utilised a multi-stage, At 63%, the rate of overweight and obesity in Australia stratified, random sampling strategy to identify households is among the highest in the world [9], with the rate of eligible for inclusion. The sampling frame represented the obese Australians tripling since 1990. Australians are South Australian population aged 15 years and over resid- also high consumers of SSBs [10], and SSBs contribute ing in areas with 1000 people or more. One interview was substantial excess sugar to the national diet. Over half of conducted per household, with the person whose birthday Australians exceed the World Health Organization (WHO) occurred last selected for interview. Up to six call back recommendations for free sugar in the diet, with 52% of visits were made to obtain the interview of the eligible free sugars coming from beverages, notably soft drinks selected person. Participants were interviewed face-to-face (sodas), electrolyte (sports) and energy drinks (19%), as well by trained research assistants. An approach letter was sent as fruit and vegetable juices and drinks (13%) [10]. 2 weeks in advance of the interview. The letter contained To date, detailed monitoring of SSB consumption the study aims, ethics committee contact information, and patterns has been infrequent and protracted due to the details about participation, including that it was voluntary complexity of population-level dietary surveys. Conse- and results would be anonymous. Verbal agreement to quently, it has offered limited insight into the behavioural participate in the study was considered informed consent and attitudinal correlates of SSB consumption. Australian and explicit verbal consent was obtained from parents/ national data collection last occurred in 2011–12, indicat- guardians for participants aged 15 to 17 years. Pilot testing ing that 50% of Australians consumed an SSB on the day occurred in August and field-work for the full study before the interview [11]. Rates of consuming 100% fruit occurred between September and December 2014. From juice were lower at 23% for children (2–18 years) and 15% the 5200 households selected, 2732 interviews were con- for adults (19 years and over) with few demographic ducted, yielding a response rate (i.e. proportion of com- differences [12]. Rates of SSB consumption were higher pleted interviews from initial eligible sample) of 54.5% and among males compared to females, and for adolescents a participation rate (i.e. proportion of completed interviews and young adults compared to other age groups [11]. from initial eligible sample where contact was established) Another study reporting on state-based data collected of 60.6%. The study, including the approach to informed in 2009 (Western Australia) and 2012 (South Australia) consent, was approved by the University of Adelaide indicated that SSB consumers were more likely to be Human Research Ethics Committee. male, have little interest in health, or have purchased meals The SAHOS contained approximately 150 health and away from home [13]. Other research has demonstrated socio-demographic related questions requiring self-reported that frequent SSB consumption is associated with other responses. This study reports on responses to a subset of poorer dietary consumption patterns, including regular fast questions pertaining to correlates of SSB consumption. The food consumption [14–17]. wording of questions, including definitions, are reported in Measurement of sugary drink consumption is typically Additional file 1 along with the corresponding variable sporadic and nutrition focussed, and there is limited sub-categories used in the analysis. For the first set of the knowledge of community perceptions and awareness of analyses, SSB consumption was the outcome variable. SSBs the health risks associated with excess SSB consumption. were defined as all non-alcoholic water-based beverages The current study sought to fill this gap by generating with added sugar, including soft drinks, energy drinks, fruit essential population-based evidence to inform public drinks, sports drinks and cordials. The definition excluded health efforts to reduce consumption. A key aim of the milk-based products, 100% fruit juice or artificially study was to determine the frequency of past week SSB sweetened beverages. SSB consumption was calculated consumption and examine the correlates of consumption. by multiplying two questions: ‘number of days consumed Miller et al. BMC Obesity (2019) 6:1 Page 3 of 12 SSBs in past week’ and ‘frequency of consumption per consumed 100% fruit juice either 1 to 6 days (25%) or every day’. Responses were split into categories: ‘none’ vs ‘any’ (1 day (10%) in the past week. Overall 19.7% had consumed or more drinks per week). As daily consumption is often both 100% fruit juice and SSBs in the past week, whereas reported in studies using dietary interviews (e.g. 11), ‘any’ 33.8% had consumed neither 100% fruit juice nor SSBs. consumption was split into ‘moderate’ (1 to 6 drinks) and Demographic, BMI and behavioural risk factors and ‘frequent’ (7 or more drinks) to approximate levels of attitude and knowledge characteristics of the 2732 consumption equivalent to less than daily versus daily, respondents included in the study are displayed in Table 1. respectively. Predictor variables were grouped into three SSB consumption was significantly associated with nearly all categories: demographic characteristics (gender, age, high- the variables listed in Table 1.Manyofthe relationships est qualification and postcode derived socio-economic exhibited a linear trend with each categorical increase in disadvantage [20] and remoteness [21]); risk factors (Body consumption. Moderate and frequent consumers shared Mass Index [BMI; calculated from self-reported height similar characteristics, and the most pronounced differences and weight], past week physical activity, fast food con- were between frequent consumers and non-consumers. sumption, 100% fruit juice consumption and smoking Based on the adjusted standardised residuals of the Pearson status); and SSB attitudes and knowledge (teaspoons of chi-square test, frequent consumers were more likely than sugar in can of soft drink, perceived healthiness of diet non-consumers to be male compared to female, younger soft drinks compared to SSBs, beliefs about sugar content (15–24 years) compared to older (45–64 years) participants, of 100% fruit juice compared to SSBs, and knowledge of have lower compared to higher education, live in areas of illnesses related to SSB consumption). The association higher disadvantage compared to low disadvantage, and live between 100% fruit juice consumption, defined as having in remote compared to metropolitan areas. The highest ‘none’ or ‘any’ (1 or more in the past week), and demo- rates of frequent SSB consumption in the past week were graphic characteristics and risk factors were also explored. among those consuming fast food two or more times in the Statistical analyses were conducted using SPSS version past week (42%) and current smokers (38%). Consumption 24 [22]. Descriptive analyses of the association between of 100% fruit juice was more likely among moderate SSB participant characteristics and 1) SSB consumption consumers than non-consumers. Physical activity had a (none, moderate or frequent) and 2) 100% fruit juice non-linear trend with SSB consumption group; frequent consumption (none or any) were undertaken using Pearson’s consumers were less likely to be physically active, moderate chi-square tests. The adjusted standardised residual for each consumers were more likely to participate in some activity, cell of the Pearson’s chi-square test was used to detect and non-consumers were more likely to be the most active. whether the obtained value for each demographic subgroup There was no association between consumption and self-re- was lower or higher than expected relative to the percent- ported Body Mass Index. ages for overall SSB consumption. The Mantel-Haenszel test Differences in attitudes and knowledge between con- of linear trends was also used for the SSB outcome variable. sumption subgroups were also greatest between frequent Multivariate analyses were used to test the same relation- consumers and non-consumers, although trends were ships while also controlling for the influence of other vari- not always linear. Overall, 34% of participants gave a ables. The ‘Complex samples: Logistic regression’ analysis in response approximating the correct number of teaspoons SPSS wasusedtocontrolfor the clusteredsamplingdesign of sugar (8 to 12) in a 375 ml (12.7 oz) can of soft drink frame. Demographic characteristics were analysed as a (soda). Underestimating sugar content in soft drink was group of predictors for both SSB and 100% fruit juice more common in moderate and frequent consumers than consumption. Subsequent analyses controlled for demo- in non-consumers. Diet soft drinks (soda) and SSBs were graphic characteristics while testing the association between rated as having the same level of healthiness by 51% of SSB consumption and 1) risk factors and 2) SSB attitudes participants whereas 27% rated diet soft drinks as less and knowledge; and between 100% fruit juice consumption healthy. Frequent consumers of SSBs were more likely to and risk factors. Data were weighted by the inverse of rate diet soft drinks as less healthy than the same level of the individual’s probability of selection, as well as the healthiness. Equivalent proportions of participants accur- response rate in metropolitan and country regions and ately believed that 100% fruit juice contained the same then re-weighted to benchmarks derived from the June amount of sugar as SSBs (43%) or believed juice had less 2013 ABS Estimated Resident Population [23]. (41%). Compared to non-consumers, frequent SSB con- sumers were less likely to rate 100% fruit juice as having Results the same amount of sugar as SSBs, but were more likely Just over half of respondents had consumed SSBs at least to rate it as having either more sugar or less sugar. Un- once in the past week, either 1 to 6 times (i.e., moderate prompted awareness of illnesses known to be associated consumption; 35%) or 7 or more times (i.e. frequent with SSB consumption ranged from 15% for heart disease consumption; 16%). Just over a third of respondents had risk to 61% for diabetes. Awareness of illnesses/health Miller et al. BMC Obesity (2019) 6:1 Page 4 of 12 Table 1 Respondent characteristics and sugar sweetened beverage (SSB) consumption by demographic subgroup (N = 2372) Overall sample SSB consumption in past week by demographic subgroup Chi-square tests None Moderate Frequent Pearson Trend (1–6 times) (7+ times) % N % %%N P-value P-value SSB consumption in past week 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 qualification 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 Index 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) 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) 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) 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 Miller et al. BMC Obesity (2019) 6:1 Page 5 of 12 Table 1 Respondent characteristics and sugar sweetened beverage (SSB) consumption by demographic subgroup (N = 2372) (Continued) Overall sample SSB consumption in past week by demographic subgroup Chi-square tests None Moderate Frequent Pearson Trend (1–6 times) (7+ times) % N % %%N P-value P-value 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 drink 2713 < 0.001 0.093 Underestimate 0 to 7 29.8 809 42.4 ↓ 38.6 ↑ 19.0 ↑ Approx correct 8 to 12 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 SSBs 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 SSBs 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 same 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 2719 < 0.001 < 0.001 related to SSB consumption Weight gain No 57.5 1566 45.7 ↓ 36.7 ↑ 17.7 ↑ Yes 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 ↑ Yes 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 Yes 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 a b c d e Excluding ‘not stated’ response category; Not stated = 0.1%, not stated = 0.2%, not stated = 0.3%, not stated = 0.5% f g Mantel-Haenszel test of linear trends; Most correct answer based on current evidence effects (weight gain, diabetes and heart disease) was nega- and demographic characteristics, BMI and behavioural risk tively associated with consumption. factors and attitudes and knowledge. The odds of being a Table 2 displays logistic regression results that tested SSB consumer was consistently greater for males compared the association between ‘none’ versus ‘any’ SSB consumption to females, for all age groups under 65 years compared to Miller et al. BMC Obesity (2019) 6:1 Page 6 of 12 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 Miller et al. BMC Obesity (2019) 6:1 Page 7 of 12 Table 2 Logistic regression of ‘any’ versus ‘none’ past week sugar sweetened beverage (SSB) consumption (Continued) 1. Demographics 2. Demographics & risk factors 3. Demographics & knowledge OR 95% CI OR 95% CI OR 95% CI Lower Upper Lower Upper Lower Upper 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 over 65 years, and was greatest for those aged 15 to 24 years, a consumer were slightly greater for those who rated diet for those with vocational qualifications or less compared to soft drink as less healthy than SSBs compared to those who university qualifications, and for those living in remote/very rated them as healthier, and for those who did not recall remote areas compared to metropolitan areas. Risk factors weight gain as being related to consumption compared to associated with consumption, controlling for demographics, those who did. were fast food consumption, 100% fruit juice consumption As shown in Table 3, 35% of respondents reported and smoking status. The association between SSB consump- consuming 1 or more 100% fruit juice drinks in the past tion and consuming fast food two or more times in the past week. There were bi-variate associations between 100% week (compared to none) was particularly strong at over 5 fruit juice consumption and all the demographics and times the odds. There were few statistically significant rela- risk factor variables listed in Table 3 except for self-re- tionships between attitudes and knowledge and consump- ported Body Mass Index. In the logistic regression test- tion when controlling for demographics. The odds of being ing demographic characteristics only (not reported in Miller et al. BMC Obesity (2019) 6:1 Page 8 of 12 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 χ OR 95% CI % % P-value (N = 2702) Lower Upper 100% fruit juice consumption in past week 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 qualification 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) 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) < 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) 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 Miller et al. BMC Obesity (2019) 6:1 Page 9 of 12 Table 3 Association between 100% fruit juice consumption and respondent characteristics (N = 2732) (Continued) 100% fruit juice consumption in past week Logistic regression None 1 or more Pearson χ OR 95% CI % % P-value (N = 2702) Lower Upper Never smoked 61.4 38.6 1 100% fruit juice versus SSBs < 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 a b c Not stated = 0.1%, not stated = 0.2%, not stated = 0.3% ***p < 0.001; **p < 0.01; *p < 0.05 table), 100% fruit juice consumption in the past week linear relationship we observed between SSB consumption was only associated with gender (males more likely than and other fast food consumption is consistent with other females; OR = 1.5, 95%CI = 1.2–1.8, p < 0.001) and age findings [13–17, 25, 26]. A qualitative study conducted (15–24 years [OR = 1.4, 95%CI = 1.1–1.9, p = 0.005] and with young adults in Australia identified strong social cues 25–44 years [OR = 1.4, 95%CI = 1.1–1.97, p = 0.005] more to purchase and consume SSBs [27]. This study found likely than those aged 65 years and over). In the combined that SSB consumption was considered normal because demographic and risk factor model (see Table 3), past week of the ready availability, cheapness, and advertising and 100% fruit juice consumption was more likely among promotion of these drinks, and that SSB consumption males compared to females, those who participated in was closely linked to purchasing fast-food and take-away physical activity everyday compared to none in the past meals. The strong association between fast food and SSB week, and those who rated 100% fruit juice as having the consumption is important because of compounding diet- same or less sugar as SSBs rather than more sugar. There ary risks from excess sugar, salt and fat. The pairing of was less likelihood of consuming 100% fruit juice among SSBs with fast food is likely driven by availability at times ex-smokers compared to those who had never smoked. of purchase, promotions, as well as pricing and ‘packaging’ of SSBs with food. Those who consumed juice were Discussion marginally more likely to have consumed fast food in Using our brief measure, more than half of the participants the past week (bi-variate analysis only), and while 84% in this study had consumed SSBs in the past week, with of those who consumed fast food twice or more per 16% consuming SSBs frequently (7 or more drinks weekly). week also consumed SSBs, only 37% consumed 100% Over one third of respondents had consumed 100% fruit fruit juice. juice in the past week, with 10% consuming every day. We observed a clustering of ‘unhealthy’ behaviours Consistent with other Australian data [10, 13, 24], con- (smoking andfastfoodconsumption)withSSB consump- sumption of SSBs in the past week was consistently higher tion and not 100% fruit juice consumption, and an associ- among males, younger age groups and groups with lower ation between healthy behaviour (exercise) and 100% fruit educational attainment. Similarly, 100% fruit juice con- juice consumption. Although juices frequently contain as sumption was higher among males (in both bivariate and much free sugar as soft drink (soda), community awareness multivariate comparisons), and among younger age groups of this is mixed, as we observed in our sample, and juice in bivariate (unadjusted) analyses. Unlike SSB consump- may have a ‘health halo’ notappliedtosoftdrink [28, 29]. tion, 100% fruit juice consumption was higher among The relationship between exercise and different SSB types, those with higher educational attainment and among less e.g. sports drinks, was not investigated in this study; how- disadvantaged groups, although these factors were not ever, there was a positive association between exercise and significant when also accounting for age and gender. consumption of 100% fruit juice, which persisted in the Among the behavioural risk factors assessed, fast food multivariate analysis. Given that some drinks are marketed consumption was most strongly associated with SSB as offering functional or health benefits, and the rela- consumption. Those who had consumed fast food in the tionships we have observed in this study between health past week had nearly twice the odds of being a consumer behaviours and juice consumption, consumer perceptions of SSBs and more frequent consumers of fast food (twice of different types of beverages high in free sugar (including or more in past week) had over 5 times the odds. The juice) warrant further investigation. Miller et al. BMC Obesity (2019) 6:1 Page 10 of 12 This study found no relationship between self-reported consumer confusion is unsurprising given the changing weight status (BMI) and SSB consumption or 100% fruit state of evidence regarding diet beverages. Similarly to juice consumption. Systematic reviews of prospective juice, consumers knowledge and beliefs about diet bever- cohort and randomised control trial studies have clearly ages warrant further investigation. demonstrated that SSB consumption can lead to weight Industry repeatedly argues that information about gain [2]. However, correlational studies are less consistent sugar content and caloric count is available to consumer and the relationship tends to vary according to drink type in nutrition information panels. While the US Food and and location. For example, one Australian study found Drug Administration has mandated the inclusion of that soft drink consumption was higher for those classified added sugar on nutrition information labels in recognition as either overweight or obese in South Australia but was of the scientific evidence about free sugars [35], informa- only higher for those classified as obese in Western tion on added sugar content is not available to Australian Australia [13]. Another Western Australian study found consumers, despite advocacy for such a change. Further- that those classified as overweight/obese were more likely more, greater health literacy (i.e. capacity to understand to consume both sugar-sweetened and artificially sweetened basic health information needed to make appropriate soft drinks but there was no relationship for those who only health decisions) has been shown to be related to lower consumed sugar-sweetened soft drinks [24]. BMI was not SSB intake [36]. This also highlights the need to either associated with SSB consumption but was associated with increase health literacy or provide information that is fruit juice consumptioninaNorwegianstudy [30]. A US easy to understand, or both. There is a growing body of study of sports and energy drinks found that consumption evidence that shows that that on-pack health warning was more likely for those classified as healthy weight labels [37–40] and mass media advertising on health [31]. It is important for future studies to assess drink effectsofSSBs[41–43]help to improve understanding types independently because a combined measure may of the potentially harmful effects of consuming SSBs mask important differences in the risk factors associated and may reduce SSB sales [44]. with consumption. The present study analysed data from a representative The results of this study suggested a lack of awareness face-to-face household survey in one Australian state of the contents of the drinks participants are consuming, and, while the results may not necessarily generalise to as well as of the potential risks associated with excess other states or countries, the results are consistent with consumption. Only 34% of respondents knew the approxi- those reported in other jurisdictions. The present study mate amount of sugar in a can of soft drink and a further was cross-sectional so it is difficult to infer causality from one third underestimated the sugar content. While there the observed significant associations. Another limitation was reasonable awareness of diabetes as a potential risk of was the use of a brief, self-report consumption measure excess SSB consumption among this sample (approx. two which relied on participants’ memory without additional thirds of participants were aware), less than half recalled prompting or cueing to aid recall. This may have produced weight gain (42.5%), tooth decay (29.1%), or heart disease an under-estimate of SSB consumption compared to an as- (14.9%) as potential risks. Frequent SSB consumers had sessment using a 24-h recall interview method. It is possible lower rates of awareness of health risks and were more that participants were not accurate in their self-reported likely to underestimate sugar content in a can of soft drink body weight which may have reduced the likelihood of than non-consumers. While the evidence of cardiovascu- detecting an effect associated with BMI. It was not possible lar risk as a result of excess consumption is emergent, to compare responders to non-responders. However, an evidence for dental caries and weight gain is longer standing, under-estimate of SSB consumption rates could have highlighting the deficit in community understanding of the occurred through non-response bias if those with unhealthy risks of excess SSB consumption. While one US study lifestyles were less likely to respond to a health survey than observed higher (70–80%) levels of awareness of weight those with healthy lifestyles. gain, diabetes and dental caries [32]thanthatobservedin the present study, these data reflected prompted awareness Conclusion rather than unprompted, top-of-mind responses such as To conclude, the low rates of awareness of the health those assessed in this study. Several other US studies have risks associated with SSB consumption and the low also established poor awareness of the sugar content and awareness of sugar content in SSBs, demonstrate that calorie count of soft drinks [33, 34]. The results also indicate there is a need for greater consumer understanding. This confusion about the relative merits of diet soft drinks is especially the case among frequent consumers who compared to SSBs. Approximately one quarter of par- are the most at risk of harms associated with SSB con- ticipants indicated diet drinks were less healthy than sumption, and where there is also clustering with other SSBs, a minority (17%) indicated they were healthier, unhealthy consumption behaviours. Potential strategies and half indicated they were ‘about the same’. This include public communication campaigns, the use of Miller et al. BMC Obesity (2019) 6:1 Page 11 of 12 on-package warning labels which contain sugar content Received: 24 April 2018 Accepted: 18 December 2018 and/or risk information, and improvements to existing nutrition information panels so that quantity of ‘added sugar’ is clear. Further research that explores consumer References 1. World Health Organization. Guideline: sugars intake for adult and children. response to risk information and perceptions of substitute Geneva: WHO; 2015. beverages of fruit juice and diet drinks is warranted. 2. 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. Additional file 3. Malik VS, Popkin BM, Bray GA, Despres JP, Hu FB. Sugar-sweetened beverages, obesity, type 2 diabetes mellitus, and cardiovascular disease risk. Additional file 1: Questionnaire and corresponding variable sub-categories. Circulation. 2010;121(11):1356–64. 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Who drinks sugar sweetened beverages and juice? An Australian population study of behaviour, awareness and attitudes

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Springer Journals
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Copyright © 2019 by The Author(s).
Subject
Medicine & Public Health; Endocrinology; Public Health
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2052-9538
DOI
10.1186/s40608-018-0224-2
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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 * Correspondence: caroline.miller@sahmri.com School of Public Health, University of Adelaide, Adelaide, Australia South Australian Health and Medical Research Institute (SAHMRI), Population Health Research Group, North Terrace, Adelaide, South Australia, Australia Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This 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. Miller et al. BMC Obesity (2019) 6:1 Page 2 of 12 Background SSB consumption was defined as frequency of past week Excess consumption of added and free sugars are gaining consumption of any of the following: soft drinks; energy increasing attention as an environmental driver of obesity drinks; sports drinks; fruit drinks or cordials; and excluded [1]. Within this context, sugar-sweetened beverages (SSBs) 100% fruit juice and artificially sweetened drinks. The SSB are a focus due to their energy density, coupled with poor definition excluded 100% fruit juice, which, although nutritional value, and the strength of evidence linking somewhat controversial (e.g. Rampersaud et al. [18]) is their consumption with weight gain, obesity [2], Type 2 increasingly acknowledged as a problematic source of free diabetes [3], tooth decay [4] and emergent evidence of sugar and excess calories (e.g. Popkin & Hawkes [19]). A cardiovascular risks [5]. Countries are moving to try to second unique aim of the study was to explore the preva- reduce their population consumption of SSBs and a raft lence and correlates of 100% fruit juice consumption. of educative and regulatory interventions are being imple- mented [6, 7]. Australia lags other countries in compre- Methods hensive educative or regulatory responses to address SSB The South Australian Health Omnibus Survey (SAHOS) consumption and obesity more broadly [8]. was used to collect data. The survey utilised a multi-stage, At 63%, the rate of overweight and obesity in Australia stratified, random sampling strategy to identify households is among the highest in the world [9], with the rate of eligible for inclusion. The sampling frame represented the obese Australians tripling since 1990. Australians are South Australian population aged 15 years and over resid- also high consumers of SSBs [10], and SSBs contribute ing in areas with 1000 people or more. One interview was substantial excess sugar to the national diet. Over half of conducted per household, with the person whose birthday Australians exceed the World Health Organization (WHO) occurred last selected for interview. Up to six call back recommendations for free sugar in the diet, with 52% of visits were made to obtain the interview of the eligible free sugars coming from beverages, notably soft drinks selected person. Participants were interviewed face-to-face (sodas), electrolyte (sports) and energy drinks (19%), as well by trained research assistants. An approach letter was sent as fruit and vegetable juices and drinks (13%) [10]. 2 weeks in advance of the interview. The letter contained To date, detailed monitoring of SSB consumption the study aims, ethics committee contact information, and patterns has been infrequent and protracted due to the details about participation, including that it was voluntary complexity of population-level dietary surveys. Conse- and results would be anonymous. Verbal agreement to quently, it has offered limited insight into the behavioural participate in the study was considered informed consent and attitudinal correlates of SSB consumption. Australian and explicit verbal consent was obtained from parents/ national data collection last occurred in 2011–12, indicat- guardians for participants aged 15 to 17 years. Pilot testing ing that 50% of Australians consumed an SSB on the day occurred in August and field-work for the full study before the interview [11]. Rates of consuming 100% fruit occurred between September and December 2014. From juice were lower at 23% for children (2–18 years) and 15% the 5200 households selected, 2732 interviews were con- for adults (19 years and over) with few demographic ducted, yielding a response rate (i.e. proportion of com- differences [12]. Rates of SSB consumption were higher pleted interviews from initial eligible sample) of 54.5% and among males compared to females, and for adolescents a participation rate (i.e. proportion of completed interviews and young adults compared to other age groups [11]. from initial eligible sample where contact was established) Another study reporting on state-based data collected of 60.6%. The study, including the approach to informed in 2009 (Western Australia) and 2012 (South Australia) consent, was approved by the University of Adelaide indicated that SSB consumers were more likely to be Human Research Ethics Committee. male, have little interest in health, or have purchased meals The SAHOS contained approximately 150 health and away from home [13]. Other research has demonstrated socio-demographic related questions requiring self-reported that frequent SSB consumption is associated with other responses. This study reports on responses to a subset of poorer dietary consumption patterns, including regular fast questions pertaining to correlates of SSB consumption. The food consumption [14–17]. wording of questions, including definitions, are reported in Measurement of sugary drink consumption is typically Additional file 1 along with the corresponding variable sporadic and nutrition focussed, and there is limited sub-categories used in the analysis. For the first set of the knowledge of community perceptions and awareness of analyses, SSB consumption was the outcome variable. SSBs the health risks associated with excess SSB consumption. were defined as all non-alcoholic water-based beverages The current study sought to fill this gap by generating with added sugar, including soft drinks, energy drinks, fruit essential population-based evidence to inform public drinks, sports drinks and cordials. The definition excluded health efforts to reduce consumption. A key aim of the milk-based products, 100% fruit juice or artificially study was to determine the frequency of past week SSB sweetened beverages. SSB consumption was calculated consumption and examine the correlates of consumption. by multiplying two questions: ‘number of days consumed Miller et al. BMC Obesity (2019) 6:1 Page 3 of 12 SSBs in past week’ and ‘frequency of consumption per consumed 100% fruit juice either 1 to 6 days (25%) or every day’. Responses were split into categories: ‘none’ vs ‘any’ (1 day (10%) in the past week. Overall 19.7% had consumed or more drinks per week). As daily consumption is often both 100% fruit juice and SSBs in the past week, whereas reported in studies using dietary interviews (e.g. 11), ‘any’ 33.8% had consumed neither 100% fruit juice nor SSBs. consumption was split into ‘moderate’ (1 to 6 drinks) and Demographic, BMI and behavioural risk factors and ‘frequent’ (7 or more drinks) to approximate levels of attitude and knowledge characteristics of the 2732 consumption equivalent to less than daily versus daily, respondents included in the study are displayed in Table 1. respectively. Predictor variables were grouped into three SSB consumption was significantly associated with nearly all categories: demographic characteristics (gender, age, high- the variables listed in Table 1.Manyofthe relationships est qualification and postcode derived socio-economic exhibited a linear trend with each categorical increase in disadvantage [20] and remoteness [21]); risk factors (Body consumption. Moderate and frequent consumers shared Mass Index [BMI; calculated from self-reported height similar characteristics, and the most pronounced differences and weight], past week physical activity, fast food con- were between frequent consumers and non-consumers. sumption, 100% fruit juice consumption and smoking Based on the adjusted standardised residuals of the Pearson status); and SSB attitudes and knowledge (teaspoons of chi-square test, frequent consumers were more likely than sugar in can of soft drink, perceived healthiness of diet non-consumers to be male compared to female, younger soft drinks compared to SSBs, beliefs about sugar content (15–24 years) compared to older (45–64 years) participants, of 100% fruit juice compared to SSBs, and knowledge of have lower compared to higher education, live in areas of illnesses related to SSB consumption). The association higher disadvantage compared to low disadvantage, and live between 100% fruit juice consumption, defined as having in remote compared to metropolitan areas. The highest ‘none’ or ‘any’ (1 or more in the past week), and demo- rates of frequent SSB consumption in the past week were graphic characteristics and risk factors were also explored. among those consuming fast food two or more times in the Statistical analyses were conducted using SPSS version past week (42%) and current smokers (38%). Consumption 24 [22]. Descriptive analyses of the association between of 100% fruit juice was more likely among moderate SSB participant characteristics and 1) SSB consumption consumers than non-consumers. Physical activity had a (none, moderate or frequent) and 2) 100% fruit juice non-linear trend with SSB consumption group; frequent consumption (none or any) were undertaken using Pearson’s consumers were less likely to be physically active, moderate chi-square tests. The adjusted standardised residual for each consumers were more likely to participate in some activity, cell of the Pearson’s chi-square test was used to detect and non-consumers were more likely to be the most active. whether the obtained value for each demographic subgroup There was no association between consumption and self-re- was lower or higher than expected relative to the percent- ported Body Mass Index. ages for overall SSB consumption. The Mantel-Haenszel test Differences in attitudes and knowledge between con- of linear trends was also used for the SSB outcome variable. sumption subgroups were also greatest between frequent Multivariate analyses were used to test the same relation- consumers and non-consumers, although trends were ships while also controlling for the influence of other vari- not always linear. Overall, 34% of participants gave a ables. The ‘Complex samples: Logistic regression’ analysis in response approximating the correct number of teaspoons SPSS wasusedtocontrolfor the clusteredsamplingdesign of sugar (8 to 12) in a 375 ml (12.7 oz) can of soft drink frame. Demographic characteristics were analysed as a (soda). Underestimating sugar content in soft drink was group of predictors for both SSB and 100% fruit juice more common in moderate and frequent consumers than consumption. Subsequent analyses controlled for demo- in non-consumers. Diet soft drinks (soda) and SSBs were graphic characteristics while testing the association between rated as having the same level of healthiness by 51% of SSB consumption and 1) risk factors and 2) SSB attitudes participants whereas 27% rated diet soft drinks as less and knowledge; and between 100% fruit juice consumption healthy. Frequent consumers of SSBs were more likely to and risk factors. Data were weighted by the inverse of rate diet soft drinks as less healthy than the same level of the individual’s probability of selection, as well as the healthiness. Equivalent proportions of participants accur- response rate in metropolitan and country regions and ately believed that 100% fruit juice contained the same then re-weighted to benchmarks derived from the June amount of sugar as SSBs (43%) or believed juice had less 2013 ABS Estimated Resident Population [23]. (41%). Compared to non-consumers, frequent SSB con- sumers were less likely to rate 100% fruit juice as having Results the same amount of sugar as SSBs, but were more likely Just over half of respondents had consumed SSBs at least to rate it as having either more sugar or less sugar. Un- once in the past week, either 1 to 6 times (i.e., moderate prompted awareness of illnesses known to be associated consumption; 35%) or 7 or more times (i.e. frequent with SSB consumption ranged from 15% for heart disease consumption; 16%). Just over a third of respondents had risk to 61% for diabetes. Awareness of illnesses/health Miller et al. BMC Obesity (2019) 6:1 Page 4 of 12 Table 1 Respondent characteristics and sugar sweetened beverage (SSB) consumption by demographic subgroup (N = 2372) Overall sample SSB consumption in past week by demographic subgroup Chi-square tests None Moderate Frequent Pearson Trend (1–6 times) (7+ times) % N % %%N P-value P-value SSB consumption in past week 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 qualification 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 Index 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) 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) 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) 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 Miller et al. BMC Obesity (2019) 6:1 Page 5 of 12 Table 1 Respondent characteristics and sugar sweetened beverage (SSB) consumption by demographic subgroup (N = 2372) (Continued) Overall sample SSB consumption in past week by demographic subgroup Chi-square tests None Moderate Frequent Pearson Trend (1–6 times) (7+ times) % N % %%N P-value P-value 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 drink 2713 < 0.001 0.093 Underestimate 0 to 7 29.8 809 42.4 ↓ 38.6 ↑ 19.0 ↑ Approx correct 8 to 12 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 SSBs 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 SSBs 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 same 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 2719 < 0.001 < 0.001 related to SSB consumption Weight gain No 57.5 1566 45.7 ↓ 36.7 ↑ 17.7 ↑ Yes 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 ↑ Yes 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 Yes 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 a b c d e Excluding ‘not stated’ response category; Not stated = 0.1%, not stated = 0.2%, not stated = 0.3%, not stated = 0.5% f g Mantel-Haenszel test of linear trends; Most correct answer based on current evidence effects (weight gain, diabetes and heart disease) was nega- and demographic characteristics, BMI and behavioural risk tively associated with consumption. factors and attitudes and knowledge. The odds of being a Table 2 displays logistic regression results that tested SSB consumer was consistently greater for males compared the association between ‘none’ versus ‘any’ SSB consumption to females, for all age groups under 65 years compared to Miller et al. BMC Obesity (2019) 6:1 Page 6 of 12 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 Miller et al. BMC Obesity (2019) 6:1 Page 7 of 12 Table 2 Logistic regression of ‘any’ versus ‘none’ past week sugar sweetened beverage (SSB) consumption (Continued) 1. Demographics 2. Demographics & risk factors 3. Demographics & knowledge OR 95% CI OR 95% CI OR 95% CI Lower Upper Lower Upper Lower Upper 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 over 65 years, and was greatest for those aged 15 to 24 years, a consumer were slightly greater for those who rated diet for those with vocational qualifications or less compared to soft drink as less healthy than SSBs compared to those who university qualifications, and for those living in remote/very rated them as healthier, and for those who did not recall remote areas compared to metropolitan areas. Risk factors weight gain as being related to consumption compared to associated with consumption, controlling for demographics, those who did. were fast food consumption, 100% fruit juice consumption As shown in Table 3, 35% of respondents reported and smoking status. The association between SSB consump- consuming 1 or more 100% fruit juice drinks in the past tion and consuming fast food two or more times in the past week. There were bi-variate associations between 100% week (compared to none) was particularly strong at over 5 fruit juice consumption and all the demographics and times the odds. There were few statistically significant rela- risk factor variables listed in Table 3 except for self-re- tionships between attitudes and knowledge and consump- ported Body Mass Index. In the logistic regression test- tion when controlling for demographics. The odds of being ing demographic characteristics only (not reported in Miller et al. BMC Obesity (2019) 6:1 Page 8 of 12 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 χ OR 95% CI % % P-value (N = 2702) Lower Upper 100% fruit juice consumption in past week 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 qualification 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) 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) < 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) 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 Miller et al. BMC Obesity (2019) 6:1 Page 9 of 12 Table 3 Association between 100% fruit juice consumption and respondent characteristics (N = 2732) (Continued) 100% fruit juice consumption in past week Logistic regression None 1 or more Pearson χ OR 95% CI % % P-value (N = 2702) Lower Upper Never smoked 61.4 38.6 1 100% fruit juice versus SSBs < 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 a b c Not stated = 0.1%, not stated = 0.2%, not stated = 0.3% ***p < 0.001; **p < 0.01; *p < 0.05 table), 100% fruit juice consumption in the past week linear relationship we observed between SSB consumption was only associated with gender (males more likely than and other fast food consumption is consistent with other females; OR = 1.5, 95%CI = 1.2–1.8, p < 0.001) and age findings [13–17, 25, 26]. A qualitative study conducted (15–24 years [OR = 1.4, 95%CI = 1.1–1.9, p = 0.005] and with young adults in Australia identified strong social cues 25–44 years [OR = 1.4, 95%CI = 1.1–1.97, p = 0.005] more to purchase and consume SSBs [27]. This study found likely than those aged 65 years and over). In the combined that SSB consumption was considered normal because demographic and risk factor model (see Table 3), past week of the ready availability, cheapness, and advertising and 100% fruit juice consumption was more likely among promotion of these drinks, and that SSB consumption males compared to females, those who participated in was closely linked to purchasing fast-food and take-away physical activity everyday compared to none in the past meals. The strong association between fast food and SSB week, and those who rated 100% fruit juice as having the consumption is important because of compounding diet- same or less sugar as SSBs rather than more sugar. There ary risks from excess sugar, salt and fat. The pairing of was less likelihood of consuming 100% fruit juice among SSBs with fast food is likely driven by availability at times ex-smokers compared to those who had never smoked. of purchase, promotions, as well as pricing and ‘packaging’ of SSBs with food. Those who consumed juice were Discussion marginally more likely to have consumed fast food in Using our brief measure, more than half of the participants the past week (bi-variate analysis only), and while 84% in this study had consumed SSBs in the past week, with of those who consumed fast food twice or more per 16% consuming SSBs frequently (7 or more drinks weekly). week also consumed SSBs, only 37% consumed 100% Over one third of respondents had consumed 100% fruit fruit juice. juice in the past week, with 10% consuming every day. We observed a clustering of ‘unhealthy’ behaviours Consistent with other Australian data [10, 13, 24], con- (smoking andfastfoodconsumption)withSSB consump- sumption of SSBs in the past week was consistently higher tion and not 100% fruit juice consumption, and an associ- among males, younger age groups and groups with lower ation between healthy behaviour (exercise) and 100% fruit educational attainment. Similarly, 100% fruit juice con- juice consumption. Although juices frequently contain as sumption was higher among males (in both bivariate and much free sugar as soft drink (soda), community awareness multivariate comparisons), and among younger age groups of this is mixed, as we observed in our sample, and juice in bivariate (unadjusted) analyses. Unlike SSB consump- may have a ‘health halo’ notappliedtosoftdrink [28, 29]. tion, 100% fruit juice consumption was higher among The relationship between exercise and different SSB types, those with higher educational attainment and among less e.g. sports drinks, was not investigated in this study; how- disadvantaged groups, although these factors were not ever, there was a positive association between exercise and significant when also accounting for age and gender. consumption of 100% fruit juice, which persisted in the Among the behavioural risk factors assessed, fast food multivariate analysis. Given that some drinks are marketed consumption was most strongly associated with SSB as offering functional or health benefits, and the rela- consumption. Those who had consumed fast food in the tionships we have observed in this study between health past week had nearly twice the odds of being a consumer behaviours and juice consumption, consumer perceptions of SSBs and more frequent consumers of fast food (twice of different types of beverages high in free sugar (including or more in past week) had over 5 times the odds. The juice) warrant further investigation. Miller et al. BMC Obesity (2019) 6:1 Page 10 of 12 This study found no relationship between self-reported consumer confusion is unsurprising given the changing weight status (BMI) and SSB consumption or 100% fruit state of evidence regarding diet beverages. Similarly to juice consumption. Systematic reviews of prospective juice, consumers knowledge and beliefs about diet bever- cohort and randomised control trial studies have clearly ages warrant further investigation. demonstrated that SSB consumption can lead to weight Industry repeatedly argues that information about gain [2]. However, correlational studies are less consistent sugar content and caloric count is available to consumer and the relationship tends to vary according to drink type in nutrition information panels. While the US Food and and location. For example, one Australian study found Drug Administration has mandated the inclusion of that soft drink consumption was higher for those classified added sugar on nutrition information labels in recognition as either overweight or obese in South Australia but was of the scientific evidence about free sugars [35], informa- only higher for those classified as obese in Western tion on added sugar content is not available to Australian Australia [13]. Another Western Australian study found consumers, despite advocacy for such a change. Further- that those classified as overweight/obese were more likely more, greater health literacy (i.e. capacity to understand to consume both sugar-sweetened and artificially sweetened basic health information needed to make appropriate soft drinks but there was no relationship for those who only health decisions) has been shown to be related to lower consumed sugar-sweetened soft drinks [24]. BMI was not SSB intake [36]. This also highlights the need to either associated with SSB consumption but was associated with increase health literacy or provide information that is fruit juice consumptioninaNorwegianstudy [30]. A US easy to understand, or both. There is a growing body of study of sports and energy drinks found that consumption evidence that shows that that on-pack health warning was more likely for those classified as healthy weight labels [37–40] and mass media advertising on health [31]. It is important for future studies to assess drink effectsofSSBs[41–43]help to improve understanding types independently because a combined measure may of the potentially harmful effects of consuming SSBs mask important differences in the risk factors associated and may reduce SSB sales [44]. with consumption. The present study analysed data from a representative The results of this study suggested a lack of awareness face-to-face household survey in one Australian state of the contents of the drinks participants are consuming, and, while the results may not necessarily generalise to as well as of the potential risks associated with excess other states or countries, the results are consistent with consumption. Only 34% of respondents knew the approxi- those reported in other jurisdictions. The present study mate amount of sugar in a can of soft drink and a further was cross-sectional so it is difficult to infer causality from one third underestimated the sugar content. While there the observed significant associations. Another limitation was reasonable awareness of diabetes as a potential risk of was the use of a brief, self-report consumption measure excess SSB consumption among this sample (approx. two which relied on participants’ memory without additional thirds of participants were aware), less than half recalled prompting or cueing to aid recall. This may have produced weight gain (42.5%), tooth decay (29.1%), or heart disease an under-estimate of SSB consumption compared to an as- (14.9%) as potential risks. Frequent SSB consumers had sessment using a 24-h recall interview method. It is possible lower rates of awareness of health risks and were more that participants were not accurate in their self-reported likely to underestimate sugar content in a can of soft drink body weight which may have reduced the likelihood of than non-consumers. While the evidence of cardiovascu- detecting an effect associated with BMI. It was not possible lar risk as a result of excess consumption is emergent, to compare responders to non-responders. However, an evidence for dental caries and weight gain is longer standing, under-estimate of SSB consumption rates could have highlighting the deficit in community understanding of the occurred through non-response bias if those with unhealthy risks of excess SSB consumption. While one US study lifestyles were less likely to respond to a health survey than observed higher (70–80%) levels of awareness of weight those with healthy lifestyles. gain, diabetes and dental caries [32]thanthatobservedin the present study, these data reflected prompted awareness Conclusion rather than unprompted, top-of-mind responses such as To conclude, the low rates of awareness of the health those assessed in this study. Several other US studies have risks associated with SSB consumption and the low also established poor awareness of the sugar content and awareness of sugar content in SSBs, demonstrate that calorie count of soft drinks [33, 34]. The results also indicate there is a need for greater consumer understanding. This confusion about the relative merits of diet soft drinks is especially the case among frequent consumers who compared to SSBs. Approximately one quarter of par- are the most at risk of harms associated with SSB con- ticipants indicated diet drinks were less healthy than sumption, and where there is also clustering with other SSBs, a minority (17%) indicated they were healthier, unhealthy consumption behaviours. Potential strategies and half indicated they were ‘about the same’. This include public communication campaigns, the use of Miller et al. 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BMC ObesitySpringer Journals

Published: Jan 3, 2019

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