Dietary intake and food sources of added sugar in the Australian population

Linggang Lei1, Anna Rangan1, Victoria M. Flood2,3 and Jimmy Chun Yu Louie1*1School of Molecular Bioscience, Charles Perkins Centre, Faculty of Science, The University of Sydney, Sydney, NSW 2006, Australia2Faculty of Health Sciences, The University of Sydney, Sydney, NSW 2006, Australia3St Vincents Hospital, Darlinghurst, NSW 2010, Australia

(Submitted 17 September 2015 Final revision received 17 November 2015 Accepted 3 December 2015)

AbstractPrevious studies in Australian children/adolescents and adults examining added sugar (AS) intake were based on now out-of-date nationalsurveys. We aimed to examine the AS and free sugar (FS) intakes and the main food sources of AS among Australians, using plausible dietarydata collected by a multiple-pass, 24-h recall, from the 201112 Australian Health Survey respondents (n 8202). AS and FS intakes wereestimated using a previously published method, and as defined by the WHO, respectively. Food groups contributing to the AS intake weredescribed and compared by age group and sex by one-way ANOVA. Linear regression was used to test for trends across age groups. Usualintake of FS (as percentage energy (%EFS)) was computed using a published method and compared with the WHO cut-off of

beverages and dietary supplements, as well as information ondietary behaviours. Dietary data were collected using a computer-assisted, multiple-pass, 24-h recall from 12153 individuals aged 2years and over in a face-to-face interview. Where possible, atleast 8d after the first interview, respondents were contacted toparticipate in a second 24-h dietary recall via a telephone interview(n 7735)(20). Data from this second recall were excluded from theprimary analyses, and were only used to generate usual intake data(See the Statistical analyses section). Food and beverage intakeswere then translated into energy and nutrient intakes using theAUStralian Food and NUTrient Database (AUSNUT) 201113 foodcomposition database(21).

Anthropometric measurements

Weight and height were measured without shoes and heavyclothing where possible, using a digital scale (to the nearest01 kg) and a stadiometer (to the nearest 01 cm), respectively.BMI was calculated as weight in kilograms divided by the squareof height in metres. Subjects were then classified as underweight,normal weight, overweight or obese based on their BMI. Forchildren and adolescents (218 years), age- (in half yearlyintervals) and sex-specific BMI cut-offs(22) were used. For adults(19+ years) the following cut-offs(23) were used: underweight(185 kg/m2), normal weight (1852499kg/m2), overweight(2502999kg/m2) and obese (300kg/m2).

Non-dietary variables

Information on household income was collected from an adultrespondent within each of the sampled households, whichrepresents the combined income of all household membersaged 15 years and over. This was then classified into deciles.The Socio-Economic Indexes for Areas (SEIFA)(24), a ranking ofsocio-economic status based on regions/areas, were derivedbased on the geographical location of the household. SEIFAquintiles were created where the highest quintile represents themost advantaged areas. Urbanity of the household locationwas classified based on the Australian Standard GeographicalClassification remoteness classification(25), and in thisstudy households classified as located in major cities ofAustralia and inner regional Australia were considered asurban. Respondents reported their country of birth, which wasclassified into Australia, major English-speaking countries andother countries.

Data cleaning

The plausibility of the food intake data was assessed using theGoldberg cut-off(26) for specific physical activity level (PAL). AsPAL data were not available from the survey, we assigned astandard PAL of 155 to all respondents as per the advice of theAustralian Bureau of Statistics(20) and similar to previousstudies(2729). Participants with an energy intake:BMR ratiooutside the 95% CI were excluded from the analysis. Weexcluded 1847 extremely low reporters and 2104 extremelyhigh reporters based on this method. The final data set included8202 participants, of which 478% were female. The demographiccharacteristics of the participants are summarised in Table 1.

Method for estimating added sugar and free sugar contentof foods

In this study, the term added sugar refers to sugars and syrupsthat are added to foods or beverages when they are processedor prepared(30), which is the definition used by the U.S.Department of Agriculture(31).

A method developed by our group(30) was used to estimatethe added sugar content of the 5740 foods in the AUSNUT201113 food composition database(21). In brief, the ten stepsare as follows:

Step 1: Assign 0 g added sugar to foods with 0 g total sugars(n 1329).Step 2: Assign 0 g added sugar to foods in food groups thatare either unprocessed or minimally processed with noadded sugar (n 1369).Step 3: Assign 100% of total sugar as added sugar for foodsin food groups that contain no naturally occurring sugars(n 462).Step 4: Calculation based on standard recipe used in thefood composition database (n 772).Step 5: Calculation based on comparison with values fromthe unsweetened variety (n 63).Step 6: Decision based on analytical data for example, alllactose in dairy foods was considered naturally occurring (n 131).Step 7: Use borrowed values from similar products fromsteps 16 or from overseas databases (n 130).Step 8: Subjective estimation based on ingredients and/orcommon recipes (n 277).Step 9: Calculation based on the standard recipe thatincludes ingredients with values assigned at steps 58, usingthe proportion method (n 1182).Step 10: Assign 50% of total sugars as added sugar to foodsthat are not included in steps 19 (n 25).

Free sugar contents of foods were defined based on the WHOdefinition as 100% of added sugar for non-fruit juice sources(including honey and syrups) and 100% of total sugars for fruitjuices and drinks(13). The added and free sugar values werethen linked to the NNPAS database to generate the intake ofadded and free sugar of individual respondents.

Food groupings

To determine the food sources of added sugar of the population,foods considered likely to contain added sugar were classified intothe following categories: sugar-sweetened beverages (fruit drinks,cordial/mixer, soft drinks, energy drinks and other sweetenedbeverages); cakes, biscuits, pastries and batter-based products(sweet and savoury biscuits, cakes, buns, pastries, muffins andscones); sugar and sweet spreads (sugar, honey, jam, syrup andother sweet spreads); chocolate and confectionery (chocolate,chocolate-based confectionery and other confectionery);sweetened dairy products (flavoured or condensed milk, yoghurt,frozen yoghurt and custard); bread and cereals (bread, breakfastcereal and bars); ice cream and ice confection (ice cream, frozendesserts and ice confection). All other food groups were groupedinto other food sources (detailed food grouping decision can befound in online Supplementary Table S1).

Added sugar intake of Australians 869

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Statistical analyses

All the statistical analyses were performed using SPSS version 22.0(IBM), and weighting factors were applied in all analyses. All theresults are presented as mean values and standard deviations forcontinuous variables and as percentages for categorical variables.Data were weighted to control for under- and/or over-sampling inparticular categories of persons and households, which mayoccur because of the random nature of sampling or non-response(20). This enables representation of the general Australianpopulation aged 2 years or above. Usual percentage energy fromfree sugars (%EFS) of the participants, computed by the MultipleSource Method(32) to account for intra-personal variability bytaking into account the data from the second 24-h recall, wascompared with the WHO recommendation for free sugar intake(

respectively), as well as the highest mean proportion ofenergy intake from added sugar (136 (SD 82)%) and %EFS(147 (SD 83)%).

Table 3 summarises the per capita percentage contribution ofadded sugar from the major added sugar-contributing foodgroups, stratified by age. Sugar-sweetened beverages accoun-ted for the greatest proportion of added sugar intake of theAustralian population (214 (SD 301)%), followed by sugar andsweet spreads (163 (SD 245)%) and cakes, biscuits, pastriesand batter-based products (157 (SD 244)%). For children aged23 years, cakes, biscuits, pastries and batter-based productscontributed the largest proportion of daily added sugar intake(203 (SD 265)%). However, sugar-sweetened beverages werethe largest contributors of added sugar in those aged 48, 913,1418, 1930 and 3150 years (225 (SD 278), 281 (SD 291),339 (SD 329), 318 (SD 342) and 203 (SD 300)%, respectively).Sugar and sweet spreads were the main contributors to addedsugar among older Australians aged 51 years or above. Childrenand adolescents had a significantly higher proportion oftheir added sugar intake from sugar-sweetened beverages(268 (SD 300) v. 198 (SD 299); P< 0001), cakes, biscuits,pastries and batter-based products (174 (SD 242) v. 152(SD 244); P< 0001), sweetened dairy products (90 (SD 184) v.62 (SD 165); P< 0001), bread and cereals (92 (SD 173) v.79 (SD 174); P= 0004) and ice cream and ice confection(79 (SD 163) v. 43 (SD 134); P< 0001), and had a lowerproportion of their added sugar intake from sugar and sweetspreads (92 (SD 170) v. 184 (SD 259); P< 0001) comparedwith adults.

The per consumer percentage contribution of added sugarfrom the major added sugar-contributing food groups aresummarised in Table 4. Consumers of sugar-sweetened bev-erages derived 503 (SD 259)% of their daily added sugar intakefrom this food group. Among sugar-sweetened beverage con-sumers, those aged 1930 years had the greatest proportion ofenergy contributed by added sugar (578 (SD 248)%), followedby those aged 1418 years (542 (SD 250)%). Except for con-sumers aged over 71 years, all sugar-sweetened beverageconsumers had more than 40% of added sugar from this foodgroup. Consumers of sweetened dairy products and ice creamand ice confection aged 48 years derived 353 (SD 248)% and317 (SD 203)% of their daily added sugar intake from these twofood groups, respectively.

Fig. 1(a) and (b) present data on the per capita percentagecontribution of added sugar from major added sugar-contributing food groups, stratified by age group and sex. Nosignificant sex differences were observed for children aged8 years or below. For children aged 913 years, males obtaineda higher proportion of added sugar from breads and cerealsthan females (116 (SD 200) v. 75 (SD 150)%; P= 0003). Boysaged 1418 years had a higher proportion of added sugar fromsugar-sweetened beverages (402 (SD 338) v. 276 (SD 306)%;P< 0001), cakes, biscuits, pastries and batter-based products(112 (SD 198) v. 169 (SD 253)%; P= 0006) and a lowerproportion of added sugar from chocolate and confectionery(64 (SD 140) v. 123 (SD 206)%; P< 0001) and sweetened dairyproducts (44 (SD 126) v. 95 (SD 170)%; P< 0001) comparedwith girls of the same age. Similar patterns were observed inTa

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