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

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Previous studies in Australian children/adolescents and adults examining added sugar (AS) intake were based on now out-of-date national surveys. We aimed to examine the AS and free sugar (FS) intakes and the main food sources of AS among Australians, using plausible dietary data collected by a multiple-pass, 24-h recall, from the 2011–12 Australian Health Survey respondents ( n 8202). AS and FS intakes were estimated using a previously published method, and as defined by the WHO, respectively. Food groups contributing to the AS intake were described and compared by age group and sex by one-way ANOVA. Linear regression was used to test for trends across age groups. Usual intake of FS (as percentage energy (%EFS)) was computed using a published method and compared with the WHO cut-off of <10 %EFS. The mean AS intake of the participants was 60·3 ( sd 52·6) g/d. Sugar-sweetened beverages accounted for the greatest proportion of the AS intake of the Australian population (21·4 ( sd 30·1) %), followed by sugar and sweet spreads (16·3 ( sd 24·5) %) and cakes, biscuits, pastries and batter-based products (15·7 ( sd 24·4) %). More than half of the study population exceeded the WHO’s cut-off for FS, especially children and adolescents. Overall, 80–90 % of the daily AS intake came from high-sugar energy-dense and/or nutrient-poor foods. To conclude, the majority of Australian adults and children exceed the WHO recommendation for FS intake. Efforts to reduce AS intake should focus on energy-dense and/or nutrient-poor foods.

Related collections

Most cited references 20

Record: found
Abstract: found
Article: not found

Measurement of dietary intake in children.

M Livingstone, P Robson (2000)

When children and adolescents are the target population in dietary surveys many different respondent and observer considerations surface. The cognitive abilities required to self-report food intake include an adequately developed concept of time, a good memory and attention span, and a knowledge of the names of foods. From the age of 8 years there is a rapid increase in the ability of children to self-report food intake. However, while cognitive abilities should be fully developed by adolescence, issues of motivation and body image may hinder willingness to report. Ten validation studies of energy intake data have demonstrated that mis-reporting, usually in the direction of under-reporting, is likely. Patterns of under-reporting vary with age, and are influenced by weight status and the dietary survey method used. Furthermore, evidence for the existence of subject-specific responding in dietary assessment challenges the assumption that repeated measurements of dietary intake will eventually obtain valid data. Unfortunately, the ability to detect mis-reporters, by comparison with presumed energy requirements, is limited unless detailed activity information is available to allow the energy intake of each subject to be evaluated individually. In addition, high variability in nutrient intakes implies that, if intakes are valid, prolonged dietary recording will be required to rank children correctly for distribution analysis. Future research should focus on refining dietary survey methods to make them more sensitive to different ages and cognitive abilities. The development of improved techniques for identification of mis-reporters and investigation of the issue of differential reporting of foods should also be given priority.

0 comments Cited 181 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Evaluation of under- and overreporting of energy intake in the 24-hour diet recalls in the European Prospective Investigation into Cancer and Nutrition (EPIC).

P. Ferrari, N Slimani, A. Ciampi … (2002)

To evaluate under- and overreporting and their determinants in the EPIC 24-hour diet recall (24-HDR) measurements collected in the European Prospective Investigation into Cancer and Nutrition (EPIC). Cross-sectional analysis. 24-HDR measurements were obtained by means of a standardised computerised interview program (EPIC-SOFT). The ratio of reported energy intake (EI) to estimated basal metabolic rate (BMR) was used to ascertain the magnitude, impact and determinants of misreporting. Goldberg's cut-off points were used to identify participants with physiologically extreme low or high energy intake. At the aggregate level the value of 1.55 for physical activity level (PAL) was chosen as reference. At the individual level we used multivariate statistical techniques to identify factors that could explain EI/BMR variability. Analyses were performed by adjusting for weight, height, age at recall, special diet, smoking status, day of recall (weekday vs. weekend day) and physical activity. Twenty-seven redefined centres in the 10 countries participating in the EPIC project. In total, 35 955 men and women, aged 35-74 years, participating in the nested EPIC calibration sub-studies. While overreporting has only a minor impact, the percentage of subjects identified as extreme underreporters was 13.8% and 10.3% in women and men, respectively. Mean EI/BMR values in men and women were 1.44 and 1.36 including all subjects, and 1.50 and 1.44 after exclusion of misreporters. After exclusion of misreporters, adjusted EI/BMR means were consistently less than 10% different from the expected value of 1.55 for PAL (except for women in Greece and in the UK), with overall differences equal to 4.0% and 7.4% for men and women, respectively. We modelled the probability of being an underreporter in association with several individual characteristics. After adjustment for age, height, special diet, smoking status, day of recall and physical activity at work, logistic regression analyses resulted in an odds ratio (OR) of being an underreporter for the highest vs. the lowest quartile of body mass index (BMI) of 3.52 (95% confidence interval (CI) 2.91-4.26) in men and 4.80 (95% CI 4.11-5.61) in women, indicating that overweight subjects are significantly more likely to underestimate energy intake than subjects in the bottom BMI category. Older people were less likely to underestimate energy intake: ORs were 0.58 (95% CI 0.45-0.77) and 0.74 (95% CI 0.63-0.88) for age (> or =65 years vs. <50 years). Special diet and day of the week showed strong effects. EI tends to be underestimated in the vast majority of the EPIC centres, although to varying degrees; at the aggregate level most centres were below the expected reference value of 1.55. Underreporting seems to be more prevalent among women than men in the EPIC calibration sample. The hypothesis that BMI (or weight) and age are causally related to underreporting seems to be confirmed in the present work. This introduces further complexity in the within-group (centre or country) and between-group calibration of dietary questionnaire measurements to deattenuate the diet-disease relationship.

0 comments Cited 69 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

The real contribution of added sugars and fats to obesity.

Adam Drewnowski (2006)

Obesity rates in the United States are a function of socioeconomic status. Higher rates are found among groups with lower educational and income levels, among racial and ethnic minorities, and in high-poverty areas. Yet, the relation between obesity, nutrition, and diet continues to be viewed in biologic terms, with the search for likely causes focused on consumption of specific macronutrients, foods, or food groups. Epidemiologic evidence linking diet composition and body weight has mostly relied on ecologic comparisons, time trends, and analyses of cross-sectional studies. Plausible physiologic mechanisms have included the metabolic effects of dietary components, mostly sugars and fats, on regulation of food intake and deposition of body fat. However, the evidence could not have been convincing since the blame for rising obesity rates seems to shift regularly, every 10 years or so, from fats to sugars and then back again. This review demonstrates that much of past epidemiologic research is consistent with a single parsimonious explanation: obesity has been linked repeatedly to consumption of low-cost foods. Refined grains, added sugars, and added fats are inexpensive, good tasting, and convenient. The fact that energy-dense foods (megajoules/kilogram) cost less per megajoule than do nutrient-dense foods means that energy-dense diets are not only cheaper but may be preferentially selected by the lower-income consumer. In other words, the low cost of dietary energy (dollars/megajoule), rather than specific food, beverage, or macronutrient choices, may be the main predictor of population weight gain. Examining past studies of the contribution of added sugars and fats to obesity rates through the prism of food prices and diet costs is the purpose of this review.