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Evaluating intake levels of nutrients linked to non-communicable diseases in Australia using the novel combination of food processing and nutrient profiling metrics of the PAHO Nutrient Profile Model

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Abstract

Purpose

To investigate intake levels of nutrients linked to non-communicable diseases in Australia using the novel combination of food processing and nutrient profiling metrics of the PAHO Nutrient Profile Model.

Methods

Dietary intakes of 12,153 participants from the Australian Health Survey (2011–12) aged 2 + years were evaluated. Food items reported during a 24 h recall were classified using the NOVA system. The Pan-American Health Organization Nutrient Profile Model (PAHO NPM) was applied to identify processed and ultra-processed products with excessive content of critical nutrients. Differences in mean intakes and prevalence of excessive intakes of critical nutrients for groups of the population whose diets were made up of products with and without excessive content in critical nutrients were examined.

Results

The majority of Australians consumed daily at least three processed and ultra-processed products identified as excessive in critical nutrients according to the PAHO NPM. Individuals consuming these products had higher intakes of free sugars (β = 8.9), total fats (β = 11.0), saturated fats (β = 4.6), trans fats (β = 0.2), and sodium (β = 1788 for adolescents and adults; β = 1769 for children 5–10 years; β = 1319 for children aged < 5 years) (p ≤ 0.001 for all nutrients) than individuals not consuming these foods. The prevalence of excessive intake of all critical nutrients also followed the same trend.

Conclusion

The PAHO NPM has shown to be a relevant tool to predict intake levels of nutrients linked to non-communicable diseases in Australia and, therefore, could be used to inform policy actions aimed at increasing the healthiness of food environments.

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References

  1. GBD 2015 Risk Factors Collaborators (2016) Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 388(10053):1659–1724. https://doi.org/10.1016/S0140-6736(16)31679-8

    Article  Google Scholar 

  2. Baker P, Machado P, Santos T, Sievert K, Backholer K, Hadjikakou M, Russell C, Huse O, Bell C, Scrinis G, Worsley A, Friel S, Lawrence M (2020) Ultra-processed foods and the nutrition transition: global, regional and national trends, food systems transformations and political economy drivers. Obes Rev. https://doi.org/10.1111/obr.13126

    Article  PubMed  Google Scholar 

  3. Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, Rauber F, Khandpur N, Cediel G, Neri D, Martinez-Steele E, Baraldi LG, Jaime PC (2019) Ultra-processed foods: what they are and how to identify them. Public Health Nutr. https://doi.org/10.1017/S1368980018003762

    Article  PubMed  Google Scholar 

  4. Zinocker MK, Lindseth IA (2018) The western diet-microbiome-host interaction and its role in metabolic disease. Nutrients. https://doi.org/10.3390/nu10030365

    Article  PubMed  PubMed Central  Google Scholar 

  5. Fardet A, Rock E (2019) Ultra-processed foods: a new holistic paradigm? Trends Food Sci Technol 93:174–184. https://doi.org/10.1016/j.tifs.2019.09.016

    Article  CAS  Google Scholar 

  6. Elizabeth L, Machado P, Zinocker M, Baker P, Lawrence M (2020) Ultra-processed foods and health outcomes: a narrative review. Nutrients. https://doi.org/10.3390/nu12071955

    Article  PubMed  PubMed Central  Google Scholar 

  7. Chen X, Zhang Z, Yang H, Qiu P, Wang H, Wang F, Zhao Q, Fang J, Nie J (2020) Consumption of ultra-processed foods and health outcomes: a systematic review of epidemiological studies. Nutr J 19(1):86. https://doi.org/10.1186/s12937-020-00604-1

    Article  PubMed  PubMed Central  Google Scholar 

  8. Askari M, Heshmati J, Shahinfar H, Tripathi N, Daneshzad E (2020) Ultra-processed food and the risk of overweight and obesity: a systematic review and meta-analysis of observational studies. Int J Obes (Lond). https://doi.org/10.1038/s41366-020-00650-z

    Article  Google Scholar 

  9. Pagliai G, Dinu M, Madarena MP, Bonaccio M, Iacoviello L, Sofi F (2020) Consumption of ultra-processed foods and health status: a systematic review and meta-analysis. Br J Nutr. https://doi.org/10.1017/S0007114520002688

    Article  PubMed  PubMed Central  Google Scholar 

  10. Monteiro CA, Cannon G, Lawrence M, Louzada MLC, Pereira Machado P (2019) Ultra-processed foods, diet quality, and health using the NOVA classification system. Food and Agriculture Organization of the United Nations, Rome

    Google Scholar 

  11. Machado PP, Steele EM, Levy RB, Sui Z, Rangan A, Woods J, Gill T, Scrinis G, Monteiro CA (2019) Ultra-processed foods and recommended intake levels of nutrients linked to non-communicable diseases in Australia: evidence from a nationally representative cross-sectional study. BMJ Open 9(8):e029544. https://doi.org/10.1136/bmjopen-2019-029544

    Article  PubMed  PubMed Central  Google Scholar 

  12. Machado PP, Steele EM, Louzada M, Levy RB, Rangan A, Woods J, Gill T, Scrinis G, Monteiro CA (2019) Ultra-processed food consumption drives excessive free sugar intake among all age groups in Australia. Eur J Nutr. https://doi.org/10.1007/s00394-019-02125-y

    Article  PubMed  Google Scholar 

  13. Moubarac JC, Parra DC, Cannon G, Monteiro CA (2014) Food classification systems based on food processing: significance and implications for policies and actions: a systematic literature review and assessment. Curr Obes Rep 3(2):256–272. https://doi.org/10.1007/s13679-014-0092-0

    Article  PubMed  Google Scholar 

  14. Lawrence MA, Baker PI (2019) Ultra-processed food and adverse health outcomes. BMJ 365:l2289. https://doi.org/10.1136/bmj.l2289

    Article  PubMed  Google Scholar 

  15. Monteiro CA (2009) Nutrition and health. The issue is not food, nor nutrients, so much as processing. Public Health Nutr 12(5):729–731. https://doi.org/10.1017/S1368980009005291

    Article  PubMed  Google Scholar 

  16. Machado PP, Steele EM, Levy RB, Louzada MLC, Rangan A, Woods J, Gill T, Scrinis G, Monteiro CA (2020) Ultra-processed food consumption and obesity in the Australian adult population. Nutr. Diabetes. https://doi.org/10.1038/s41387-020-00141-0

    Article  PubMed  PubMed Central  Google Scholar 

  17. Khandpur N, Neri DA, Monteiro C, Mazur A, Frelut ML, Boyland E, Weghuber D, Thivel D (2020) Ultra-processed food consumption among the paediatric population: an overview and call to action from the European Childhood Obesity Group. Ann Nutr Metab. https://doi.org/10.1159/000507840

    Article  PubMed  Google Scholar 

  18. Swinburn BA, Kraak VI, Allender S, Atkins VJ, Baker PI, Bogard JR, Brinsden H, Calvillo A, De Schutter O, Devarajan R, Ezzati M, Friel S, Goenka S, Hammond RA, Hastings G, Hawkes C, Herrero M, Hovmand PS, Howden M, Jaacks LM, Kapetanaki AB, Kasman M, Kuhnlein HV, Kumanyika SK, Larijani B, Lobstein T, Long MW, Matsudo VKR, Mills SDH, Morgan G, Morshed A, Nece PM, Pan A, Patterson DW, Sacks G, Shekar M, Simmons GL, Smit W, Tootee A, Vandevijvere S, Waterlander WE, Wolfenden L, Dietz WH (2019) The global syndemic of obesity, undernutrition, and climate change: The Lancet Commission report. Lancet 393(10173):791–846. https://doi.org/10.1016/S0140-6736(18)32822-8

    Article  PubMed  Google Scholar 

  19. Khandpur N, Swinburn B, Monteiro CA (2018) Nutrient-based warning labels may help in the pursuit of healthy diets. Obesity (Silver Spring) 26(11):1670–1671. https://doi.org/10.1002/oby.22318

    Article  Google Scholar 

  20. Hernandez FM, Batis C, Rivera JA, Colchero MA (2019) Reduction in purchases of energy-dense nutrient-poor foods in Mexico associated with the introduction of a tax in 2014. Prev Med 118:16–22. https://doi.org/10.1016/j.ypmed.2018.09.019

    Article  Google Scholar 

  21. Rayner M (2017) Nutrient profiling for regulatory purposes. Proc Nutr Soc 76(3):230–236. https://doi.org/10.1017/S0029665117000362

    Article  PubMed  Google Scholar 

  22. Labonte ME, Poon T, Gladanac B, Ahmed M, Franco-Arellano B, Rayner M, L’Abbe MR (2018) Nutrient profile models with applications in government-led nutrition policies aimed at health promotion and noncommunicable disease prevention: a systematic review. Adv Nutr 9(6):741–788. https://doi.org/10.1093/advances/nmy045

    Article  PubMed  PubMed Central  Google Scholar 

  23. Dickie S, Woods JL, Lawrence M (2018) Analysing the use of the Australian Health Star Rating system by level of food processing. Int J Behav Nutr Phys Act 15(1):128. https://doi.org/10.1186/s12966-018-0760-7

    Article  PubMed  PubMed Central  Google Scholar 

  24. Pan American Health Organization (2016) Nutrient profile model. Pan American Health Organization, Washington

    Google Scholar 

  25. World Health Organization (2015) Sugars intake for adults and children. World Health Organization, Geneva

    Google Scholar 

  26. World Health Organization (2003) Diet, nutrition and the prevention of chronic diseases: report of a joint WHO/FAO expert consultation. World Health Organization, Geneva

    Google Scholar 

  27. World Health Organization (2012) Sodium intake for adults and children. World Health Organization, Geneva

    Google Scholar 

  28. Joint WHO/FAO Food Standards Programme Codex Committee on Nutrition and Foods for Special Dietary Uses (2019) Discussion paper on general guidelines to establish nutrient profiles for foods labelling. Rome

  29. Egnell M, Seconda L, Neal B, Mhurchu CN, Rayner M, Jones A, Touvier M, Kesse-Guyot E, Hercberg S, Julia C (2020) Prospective associations of the original Food Standards Agency nutrient profiling system and three variants with weight gain, overweight and obesity risk: results from the French NutriNet-Sante cohort. Br J Nutr. https://doi.org/10.1017/S0007114520003384

    Article  PubMed  Google Scholar 

  30. Deschasaux M, Huybrechts I, Murphy N, Julia C, Hercberg S, Srour B, Kesse-Guyot E, Latino-Martel P, Biessy C, Casagrande C, Jenab M, Ward H, Weiderpass E, Dahm CC, Overvad K, Kyro C, Olsen A, Affret A, Boutron-Ruault MC, Mahamat-Saleh Y, Kaaks R, Kuhn T, Boeing H, Schwingshackl L, Bamia C, Peppa E, Trichopoulou A, Masala G, Krogh V, Panico S, Tumino R, Sacerdote C, Bueno-de-Mesquita B, Peeters PH, Hjartaker A, Rylander C, Skeie G, Ramon Quiros J, Jakszyn P, Salamanca-Fernandez E, Huerta JM, Ardanaz E, Amiano P, Ericson U, Sonestedt E, Huseinovic E, Johansson I, Khaw KT, Wareham N, Bradbury KE, Perez-Cornago A, Tsilidis KK, Ferrari P, Riboli E, Gunter MJ, Touvier M (2018) Nutritional quality of food as represented by the FSAm-NPS nutrient profiling system underlying the Nutri-Score label and cancer risk in Europe: results from the EPIC prospective cohort study. PLoS Med 15(9):e1002651. https://doi.org/10.1371/journal.pmed.1002651

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Gomez-Donoso C, Martinez-Gonzalez MA, Perez-Cornago A, Sayon-Orea C, Martinez JA, Bes-Rastrollo M (2020) Association between the nutrient profile system underpinning the Nutri-Score front-of-pack nutrition label and mortality in the SUN project: a prospective cohort study. Clin Nutr. https://doi.org/10.1016/j.clnu.2020.07.008

    Article  PubMed  Google Scholar 

  32. Dickie S, Woods JL, Baker P, Elizabeth L, Lawrence MA (2020) Evaluating nutrient-based indices against food- and diet-based indices to assess the health potential of foods: how does the australian health star rating system perform after five years? Nutrients. https://doi.org/10.3390/nu12051463

    Article  PubMed  PubMed Central  Google Scholar 

  33. Food Standards Australia New Zealand (2014) AUSNUT 2011–2013—Food Composition Database. http://www.foodstandards.gov.au/science/monitoringnutrients/ausnut/pages/default.aspx

  34. Wu JDS, Catterall E, Bloem M, Zheng M, Veerman L, Barendregt J, Thomas B (2017) Levels of trans fats in the food supply and population consumption in Australia: an Expert Commentary rapid review brokered by the Sax Institute (www.saxinstitute.org.au) for The National Heart Foundation of Australia

  35. FAO/WHO/UNU (2004) Human energy requirements. Food and Agriculture Organization of the United Nations and World Health Organization, Rome

    Google Scholar 

  36. Spiteri SA, Olstad DL, Woods JL (2018) Nutritional quality of new food products released into the Australian retail food market in 2015—is the food industry part of the solution? BMC Public Health 18(1):222. https://doi.org/10.1186/s12889-018-5127-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Ni Mhurchu C, Brown R, Jiang Y, Eyles H, Dunford E, Neal B (2016) Nutrient profile of 23 596 packaged supermarket foods and non-alcoholic beverages in Australia and New Zealand. Public Health Nutr 19(3):401–408. https://doi.org/10.1017/S1368980015000968

    Article  PubMed  Google Scholar 

  38. Pulker CE, Scott JA, Pollard CM (2018) Ultra-processed family foods in Australia: nutrition claims, health claims and marketing techniques. Public Health Nutr 21(1):38–48. https://doi.org/10.1017/S1368980017001148

    Article  PubMed  Google Scholar 

  39. World Cancer Research Fund/American Institute for Cancer Research (2018) Continuous Update Project Expert Report 2018. Preservation and processing of foods and the risk of cancer. World Cancer Research Fund/American Institute for Cancer Research

  40. Vital Strategies and University of North Carolina at Chapel Hill (2020) What’s in our food? A guide to introducing effective front-of-package nutrient labels. Trish Cotter, Lindsey Smith Taillie, Nandita Murukutla, Luyanda Majija, Alexey Kotov, Marissa Hall, Sandra Mullin, Barry Popkin

  41. Popkin B (2019) Ultra-processed foods’ impacts on health. 2030—Food Agriculture and rural development in Latin America and the Caribbean. FAO, Santiago de Chile

    Google Scholar 

  42. The Israeli Ministry of Health (2019) Nutritional recommendations. Available at https://www.health.gov.il/PublicationsFiles/dietary%20guidelines%20EN.pdf

  43. Ministère Des Solidarités Et De La Santé (2019) Programme National Nutrition Santé 2019–2023. Available at https://solidarites-sante.gouv.fr/IMG/pdf/pnns4_2019-2023.pdf

  44. Moreira PV, Hyseni L, Moubarac JC, Martins APB, Baraldi LG, Capewell S, O’Flaherty M, Guzman-Castillo M (2018) Effects of reducing processed culinary ingredients and ultra-processed foods in the Brazilian diet: a cardiovascular modelling study. Public Health Nutr 21(1):181–188. https://doi.org/10.1017/S1368980017002063

    Article  PubMed  Google Scholar 

  45. Moreira PVL, Baraldi LG, Moubarac J-C, Monteiro CA, Newton A, Capewell S, O’Flaherty M (2015) Comparing different policy scenarios to reduce the consumption of ultra-processed foods in UK: impact on cardiovascular disease mortality using a modelling approach. PLoS ONE 10(2):e0118353. https://doi.org/10.1371/journal.pone.0118353

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Russell C, Grimes C, Baker P, Sievert K, Lawrence MA (2020) The drivers, trends and dietary impacts of non-nutritive sweeteners in the food supply: a narrative review. Nutr Res Rev. https://doi.org/10.1017/S0954422420000268

    Article  PubMed  PubMed Central  Google Scholar 

  47. Srour B, Fezeu LK, Kesse-Guyot E, Alles B, Mejean C, Andrianasolo RM, Chazelas E, Deschasaux M, Hercberg S, Galan P, Monteiro CA, Julia C, Touvier M (2019) Ultra-processed food intake and risk of cardiovascular disease: prospective cohort study (NutriNet-Sante). BMJ 365:l1451. https://doi.org/10.1136/bmj.l1451

    Article  PubMed  PubMed Central  Google Scholar 

  48. Stanhope KL, Goran MI, Bosy-Westphal A, King JC, Schmidt LA, Schwarz JM, Stice E, Sylvetsky AC, Turnbaugh PJ, Bray GA, Gardner CD, Havel PJ, Malik V, Mason AE, Ravussin E, Rosenbaum M, Welsh JA, Allister-Price C, Sigala DM, Greenwood MRC, Astrup A, Krauss RM (2018) Pathways and mechanisms linking dietary components to cardiometabolic disease: thinking beyond calories. Obes Rev 19(9):1205–1235. https://doi.org/10.1111/obr.12699

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Mora-Plazas M, Gomez LF, Miles DR, Parra DC, Taillie LS (2019) Nutrition quality of packaged foods in Bogota, Colombia: a comparison of two nutrient profile models. Nutrients. https://doi.org/10.3390/nu11051011

    Article  PubMed  PubMed Central  Google Scholar 

  50. Astrup A, Bertram HC, Bonjour JP, de Groot LC, de Oliveira Otto MC, Feeney EL, Garg ML, Givens I, Kok FJ, Krauss RM, Lamarche B, Lecerf JM, Legrand P, McKinley M, Micha R, Michalski MC, Mozaffarian D, Soedamah-Muthu SS (2019) WHO draft guidelines on dietary saturated and trans fatty acids: time for a new approach? BMJ 366:l4137. https://doi.org/10.1136/bmj.l4137

    Article  PubMed  Google Scholar 

  51. Scrinis G, Monteiro CA (2018) Ultra-processed foods and the limits of product reformulation. Public Health Nutr 21(1):247–252. https://doi.org/10.1017/S1368980017001392

    Article  PubMed  Google Scholar 

  52. Dodd KW, Guenther PM, Freedman LS, Subar AF, Kipnis V, Midthune D, Tooze JA, Krebs-Smith SM (2006) Statistical methods for estimating usual intake of nutrients and foods: a review of the theory. J Am Diet Assoc 106(10):1640–1650. https://doi.org/10.1016/j.jada.2006.07.011

    Article  PubMed  Google Scholar 

  53. Santos JA, Webster J, Land MA, Flood V, Chalmers J, Woodward M, Neal B, Petersen KS (2017) Dietary salt intake in the Australian population. Public Health Nutr 20(11):1887–1894. https://doi.org/10.1017/S1368980017000799

    Article  PubMed  Google Scholar 

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Acknowledgements

The study received support from Resolve to Save Lives, an initiative of Vital Strategies. Resolve to Save Lives is funded by grants from Bloomberg Philanthropies, Gates Philanthropy Partners (with support from the Chan Zuckerberg Initiative) and the Bill & Melinda Gates Foundation. This research is supported by an Australian Research Council Discovery Project; DP190101323, ‘Reforming evidence synthesis and translation for food and nutrition policy’. PM receives income through an Alfred Deakin Postdoctoral Research Fellowship provided by Deakin University.

Funding

The study received support from Resolve to Save Lives, an initiative of Vital Strategies. Resolve to Save Lives is funded by grants from Bloomberg Philanthropies, Gates Philanthropy Partners (with support from the Chan Zuckerberg Initiative) and the Bill & Melinda Gates Foundation. This research is supported by an Australian Research Council Discovery Project; DP190101323, ‘Reforming evidence synthesis and translation for food and nutrition policy’.

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Authors and Affiliations

Authors

Contributions

PM, GC and FSG designed the research; GC developed the first statistical script for data analysis; PM classified foods based on  level of processing, and led the analysis and interpretation of results; all authors supported the interpretation of the data; PM wrote the first draft of the manuscript and was responsible for subsequent revisions; all authors revised each draft for important intellectual content, read and approved the final manuscript. FSG is a staff member of the Pan-American Health Organization. The authors alone are responsible for the views expressed in this publication, and they do not necessarily represent the decisions or policies of the Pan-American Health Organization.

Corresponding author

Correspondence to Priscila Machado.

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Conflict of interest

The authors declare that they have no conflict of interest.

Availability of data and material

This study was a secondary analysis using de-identified data from the ABS Basic Confidentialised Unit Record Files.

Code availability

Code is available under request from the corresponding author.

Ethics approval

This study was a secondary analysis using de-identified data from the ABS Basic Confidentialised Unit Record Files, and permission to use the data was obtained. Ethics approval for the survey was granted by the Australian Government Department of Health and Ageing Departmental Ethnics Committee in 2011.

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Machado, P., Cediel, G., Woods, J. et al. Evaluating intake levels of nutrients linked to non-communicable diseases in Australia using the novel combination of food processing and nutrient profiling metrics of the PAHO Nutrient Profile Model. Eur J Nutr 61, 1801–1812 (2022). https://doi.org/10.1007/s00394-021-02740-8

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