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      Ultra-processed foods and recommended intake levels of nutrients linked to non-communicable diseases in Australia: evidence from a nationally representative cross-sectional study

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          Abstract

          Objective

          This study aimed to describe the consumption of ultra-processed foods in Australia and its association with the intake of nutrients linked to non-communicable diseases (NCDs).

          Design

          Cross-sectional study.

          Setting

          National Nutrition and Physical Activity Survey (2011-2012).

          Participants

          12,153 participants aged 2+ years.

          Main outcome measures

          Average dietary content of nutrients linked to NCDs and the prevalence of intake outside levels recommended for the prevention of NCDs.

          Data analysis

          Food items were classified according to the NOVA system, a classification based on the nature, extent and purpose of industrial food processing. The contribution of each NOVA food group and their subgroups to total energy intake was calculated. Mean nutrient content of ultra-processed food and non-ultra-processed food fractions of the diet were compared. Across quintiles of the energy contribution of ultra-processed foods, differences in the intake of nutrients linked to NCDs as well as in the prevalence of intakes outside levels recommended for the prevention of NCDs were examined.

          Results

          Ultra-processed foods had the highest dietary contribution (42.0% of energy intake), followed by unprocessed or minimally processed foods (35.4%), processed foods (15.8%) and processed culinary ingredients (6.8%). A positive and statistically significant linear trend was found between quintiles of ultra-processed food consumption and intake levels of free sugars (standardised β 0.43, p<0.001); total (β 0.08, p<0.001), saturated (β 0.18, p<0.001) and trans fats (β 0.10, p<0.001); sodium (β 0.21, p<0.001) and diet energy density (β 0.41, p<0.001), while an inverse relationship was observed for dietary fibre (β -0.21, p<0.001) and potassium (β -0.27, p<0.001). The prevalence of non-recommended intake levels of all studied nutrients increased linearly across quintiles of ultra-processed food intake, notably from 22% to 82% for free sugars, from 6% to 11% for trans fat and from 2% to 25% for dietary energy density, from the lowest to the highest ultra-processed food quintile.

          Conclusion

          The high energy contribution of ultra-processed foods impacted negatively on the intake of non-ultra-processed foods and on all nutrients linked to NCDs in Australia. Decreasing the dietary share of ultra-processed foods would substantially improve the diet quality in the country and help the population achieve recommendations on critical nutrients linked to NCDs.

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          Most cited references24

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          Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013.

          Marie Ng, Tom Fleming, Margaret W. Robinson … (2015)
          In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and 3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013. We systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports. We used mixed effects linear regression to correct for bias in self-reports. We obtained data for prevalence of obesity and overweight by age, sex, country, and year (n=19,244) with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs). Worldwide, the proportion of adults with a body-mass index (BMI) of 25 kg/m(2) or greater increased between 1980 and 2013 from 28·8% (95% UI 28·4-29·3) to 36·9% (36·3-37·4) in men, and from 29·8% (29·3-30·2) to 38·0% (37·5-38·5) in women. Prevalence has increased substantially in children and adolescents in developed countries; 23·8% (22·9-24·7) of boys and 22·6% (21·7-23·6) of girls were overweight or obese in 2013. The prevalence of overweight and obesity has also increased in children and adolescents in developing countries, from 8·1% (7·7-8·6) to 12·9% (12·3-13·5) in 2013 for boys and from 8·4% (8·1-8·8) to 13·4% (13·0-13·9) in girls. In adults, estimated prevalence of obesity exceeded 50% in men in Tonga and in women in Kuwait, Kiribati, Federated States of Micronesia, Libya, Qatar, Tonga, and Samoa. Since 2006, the increase in adult obesity in developed countries has slowed down. Because of the established health risks and substantial increases in prevalence, obesity has become a major global health challenge. Not only is obesity increasing, but no national success stories have been reported in the past 33 years. Urgent global action and leadership is needed to help countries to more effectively intervene. Bill & Melinda Gates Foundation. Copyright © 2014 Elsevier Ltd. All rights reserved.
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            A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

            Stephen S Lim, Theo Vos, Abraham D. Flaxman … (2012)
            The Lancet, 380(9859), 2224-2260
            Article 0 comments Cited 3831 times – based on 0 reviews     Review now
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              Consumption of ultra-processed foods predicts diet quality in Canada.

              E Martinez Steele, C A Monteiro, Jean-Claude Moubarac … (2017)
              This study describes food consumption patterns in Canada according to the types of food processing using the Nova classification and investigates the association between consumption of ultra-processed foods and the nutrient profile of the diet. Dietary intakes of 33,694 individuals from the 2004 Canadian Community Health Survey aged 2 years and above were analyzed. Food and drinks were classified using Nova into unprocessed or minimally processed foods, processed culinary ingredients, processed foods and ultra-processed foods. Average consumption (total daily energy intake) and relative consumption (% of total energy intake) provided by each of the food groups were calculated. Consumption of ultra-processed foods according to sex, age, education, residential location and relative family revenue was assessed. Mean nutrient content of ultra-processed foods and non-ultra-processed foods were compared, and the average nutrient content of the overall diet across quintiles of dietary share of ultra-processed foods was measured. In 2004, 48% of calories consumed by Canadians came from ultra-processed foods. Consumption of such foods was high amongst all socioeconomic groups, and particularly in children and adolescents. As a group, ultra-processed foods were grossly nutritionally inferior to non-ultra-processed foods. After adjusting for covariates, a significant and positive relationship was found between the dietary share of ultra-processed foods and the content in carbohydrates, free sugars, total and saturated fats and energy density, while an inverse relationship was observed with the dietary content in protein, fiber, vitamins A, C, D, B6 and B12, niacin, thiamine, riboflavin, as well as zinc, iron, magnesium, calcium, phosphorus and potassium. Lowering the dietary share of ultra-processed foods and raising consumption of hand-made meals from unprocessed or minimally processed foods would substantially improve the diet quality of Canadian.
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                Author and article information

                Journal
                Journal ID (nlm-ta): BMJ Open
                Journal ID (iso-abbrev): BMJ Open
                Journal ID (hwp): bmjopen
                Journal ID (publisher-id): bmjopen
                Title: BMJ Open
                Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                ISSN (Electronic): 2044-6055
                Publication date Collection: 2019
                Publication date (Electronic): 28 August 2019
                Volume: 9
                Issue: 8
                Electronic Location Identifier: e029544
                Affiliations
                [1 ] departmentGraduate Program in Nutrition in Public Health , School of Public Health, University of Sao Paulo , Sao Paulo, Brazil
                [2 ] departmentCenter for Epidemiological Research in Nutrition and Health , University of Sao Paulo , Sao Paulo, Brazil
                [3 ] departmentDepartment of Preventive Medicine, School of Medicine , University of Sao Paulo , Sao Paulo, Brazil
                [4 ] departmentSchool of Public Health and Community Medicine , University of New South Wales , Sydney, New South Wales, Australia
                [5 ] departmentSchool of Life and Environmental Sciences , Charles Perkins Centre, The University of Sydney , Sydney, New South Wales, Australia
                [6 ] departmentInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences , Deakin University , Geelong, Victoria, Australia
                [7 ] departmentBoden Institute of Obesity, Nutrition, Exercise and Eating Disorders , Charles Perkins Centre, The University of Sydney , Sydney, New South Wales, Australia
                [8 ] departmentSchool of Agriculture and Food , The University of Melbourne , Melbourne, Victoria, Australia
                [9 ] departmentDepartment of Nutrition , School of Public Health, University of Sao Paulo , Sao Paulo, Brazil
                Author notes
                [Correspondence to ] Dr Carlos A Monteiro; carlosam@ 123456usp.br
                Author information
                http://orcid.org/0000-0003-4607-5094
                Article
                Publisher ID: bmjopen-2019-029544
                DOI: 10.1136/bmjopen-2019-029544
                PMC ID: 6720475
                PubMed ID: 31462476
                SO-VID: 5db34b74-75e6-4367-aad4-8638f308478f
                Copyright © © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
                License:

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                Date received : 31 January 2019
                Date revision received : 27 May 2019
                Date accepted : 10 July 2019
                Categories
                Subject: Public Health
                Subject: Research
                Subject: 1506
                Subject: 1724
                Custom metadata
                special-feature unlocked

                ScienceOpen disciplines: Medicine
                Keywords: food processing,diet,quality of diet,food consumption,australia
                Data availability:
                ScienceOpen disciplines: Medicine
                Keywords: food processing, diet, quality of diet, food consumption, australia

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