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Ultra-processed food consumption and obesity in the Australian adult population

Pereira Machado, Priscila, Steele, EM, Levy, RB, da Costa Louzada, ML, Rangan, A, Woods, Julie, Gill, T, Scrinis, G and Monteiro, CA 2020, Ultra-processed food consumption and obesity in the Australian adult population, Nutrition & Diabetes, vol. 10, no. 1, pp. 1-11, doi: 10.1038/s41387-020-00141-0.

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Title Ultra-processed food consumption and obesity in the Australian adult population
Author(s) Pereira Machado, PriscilaORCID iD for Pereira Machado, Priscila orcid.org/0000-0003-4607-5094
Steele, EM
Levy, RB
da Costa Louzada, ML
Rangan, A
Woods, JulieORCID iD for Woods, Julie orcid.org/0000-0002-2717-310X
Gill, T
Scrinis, G
Monteiro, CA
Journal name Nutrition & Diabetes
Volume number 10
Issue number 1
Article ID 39
Start page 1
End page 11
Total pages 11
Publisher Springer
Place of publication Berlin, Germany
Publication date 2020-12-05
ISSN 2044-4052
2044-4052
Keyword(s) Science & Technology
Life Sciences & Biomedicine
Endocrinology & Metabolism
Nutrition & Dietetics
DIET
PRODUCTS
QUALITY
HEALTH
Summary Background: Rapid simultaneous increases in ultra-processed food sales and obesity prevalence have been observed worldwide, including in Australia. Consumption of ultra-processed foods by the Australian population was previously shown to be systematically associated with increased risk of intakes of nutrients outside levels recommended for the prevention of obesity. This study aims to explore the association between ultra-processed food consumption and obesity among the Australian adult population and stratifying by age group, sex and physical activity level. Methods: A cross-sectional analysis of anthropometric and dietary data from 7411 Australians aged ≥20 years from the National Nutrition and Physical Activity Survey 2011–2012 was performed. Food consumption was evaluated through 24-h recall. The NOVA system was used to identify ultra-processed foods, i.e. industrial formulations manufactured from substances derived from foods and typically added of flavours, colours and other cosmetic additives, such as soft drinks, confectionery, sweet or savoury packaged snacks, microwaveable frozen meals and fast food dishes. Measured weight, height and waist circumference (WC) data were used to calculate the body mass index (BMI) and diagnosis of obesity and abdominal obesity. Regression models were used to evaluate the association of dietary share of ultra-processed foods (quintiles) and obesity indicators, adjusting for socio-demographic variables, physical activity and smoking. Results: Significant (P-trend ≤ 0.001) direct dose–response associations between the dietary share of ultra-processed foods and indicators of obesity were found after adjustment. In the multivariable regression analysis, those in the highest quintile of ultra-processed food consumption had significantly higher BMI (0.97 kg/m2; 95% CI 0.42, 1.51) and WC (1.92 cm; 95% CI 0.57, 3.27) and higher odds of having obesity (OR = 1.61; 95% CI 1.27, 2.04) and abdominal obesity (OR = 1.38; 95% CI 1.10, 1.72) compared with those in the lowest quintile of consumption. Subgroup analyses showed that the trend towards positive associations for all obesity indicators remained in all age groups, sex and physical activity level. Conclusion: The findings add to the growing evidence that ultra-processed food consumption is associated with obesity and support the potential role of ultra-processed foods in contributing to obesity in Australia.
Language eng
DOI 10.1038/s41387-020-00141-0
Indigenous content off
Field of Research 1103 Clinical Sciences
1111 Nutrition and Dietetics
1601 Anthropology
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2020, The Author(s)
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30146190

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.