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The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Potential reductions in ultra-processed food consumption substantially improve population cardiometabolic-related dietary nutrient profiles in eight countries

Martinez Steele, E., Marrón Ponce, J.A., Cediel, G., Louzada, M.L.C., Khandpur, N., Machado, P., Moubarac, J.-C., Rauber, F., Corvalán, C., Levy, R.B., Monteiro, C.A.·2022·Nutrition, Metabolism and Cardiovascular Diseases
DOI 10.1016/j.numecd.2022.08.018
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Abstract

Background and aims The negative effect on dietary nutrient profiles is the most obvious mechanism explaining the higher risk of cardiometabolic diseases associated with increased dietary share of UPF observed in large cohort studies. We estimate the proportion of diets with excessive energy density, excessive free sugars or saturated fat contents and insufficient fiber that could be avoided, if UPF consumption was reduced to levels among lowest consumers across eight countries, as well as the proportion of diets with multiple inadequacies. Methods and results Using nationally-representative cross-sectional surveys from Brazil (2008-09), Chile (2010), Colombia (2005), Mexico (2012), Australia (2011-12), the UK (2008-16), Canada (2015), and the US (2015-16), inadequate energy density (≥2.25 kcal/g) or contents of free sugars (>10% of total energy intake), saturated fats (>10% of total energy intake) and fiber ( Conclusions Lowering dietary contribution of UPF to levels among country-specific lowest consumers is a way to improve population cardiometabolic-related dietary nutrient profiles.

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  • Strong evidence already supports the plausibility of several mechanisms acting alone or in combination: gross nutrient imbalances; overeating driven by UPFs with high energy densities and hyper-palatability, as well as degraded food matrices and soft textures; reduced intake of healthy phytochemicals; and increased exposure to toxic compounds, endocrine disruptors, and harmful classes and mixtures

    “Strong evidence already supports the plausibility of several mechanisms acting alone or in combination: gross nutrient imbalances; [46][47][48][49][50][51][52] overeating 46,55,56,58 driven by UPFs with high energy densities and hyper-palatability, 57 as well as degraded food matrices and soft textures; [58][59][60][61][62] reduced intake of healthy phytochemicals; 66,67 and increased exposure to”

    From Ultra-processed foods and human health: the main thesis and the evidence (2025) · cites this paper as [47]

Citations

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Research works printed but not linked: 32

  1. Roth, 2017, Global, Regional, and National Burden of Cardiovascular Diseases for 10 Causes, 1990 to 2015, J Am Coll Cardiol, 10.1016/j.jacc.2017.04.052 · DOI · Paper page
  2. Lichtenstein, 2021, 2021 Dietary guidance to improve cardiovascular health: a scientific statement from the American heart association, Circulation, 144, e472, 10.1161/CIR.0000000000001031 · DOI · Paper page
  3. Srour, 2019, Ultra-processed food intake and risk of cardiovascular disease: prospective cohort study (NutriNet-Santé), BMJ, 365, l1451, 10.1136/bmj.l1451 · DOI · Paper page
  4. Mendonça, 2017, Ultra-processed food consumption and the incidence of hypertension in a mediterranean cohort: the seguimiento universidad de Navarra project, Am J Hypertens, 30, 358, 10.1093/ajh/hpw137 · DOI · Paper page
  5. Srour, 2019, Ultraprocessed food consumption and risk of type 2 diabetes among participants of the NutriNet-santé prospective cohort, JAMA Intern Med
  6. Levy, 2021, Ultra-processed food consumption and type 2 diabetes incidence: a prospective cohort study, Clin Nutr, 40, 3608, 10.1016/j.clnu.2020.12.018 · DOI
  7. Llavero-Valero, 2021, Ultra-processed foods and type-2 diabetes risk in the SUN project: a prospective cohort study, Clin Nutr, 40, 2817, 10.1016/j.clnu.2021.03.039 · DOI
  8. Rauber, 2015, Consumption of ultra-processed food products and its effects on children's lipid profiles: a longitudinal study, Nutr Metabol Cardiovasc Dis, 25, 116, 10.1016/j.numecd.2014.08.001 · DOI
  9. Mendonça, 2016, Ultraprocessed food consumption and risk of overweight and obesity: the University of Navarra Follow-Up (SUN) cohort study, Am J Clin Nutr, 104, 1433, 10.3945/ajcn.116.135004 · DOI · Paper page
  10. Beslay, 2020, Ultra-processed food intake in association with BMI change and risk of overweight and obesity: a prospective analysis of the French NutriNet-Santé cohort, PLoS Med, 17, 10.1371/journal.pmed.1003256 · DOI
  11. Juul, 2021, Ultra-processed foods and cardiovascular diseases: potential mechanisms of action, Adv Nutr, 12, 1673, 10.1093/advances/nmab049 · DOI · Paper page
  12. Costa Louzada, 2015, Ultra-processed foods and the nutritional dietary profile in Brazil, Rev Saude Publica, 49, 38
  13. Cediel, 2020, Ultra-processed foods drive to unhealthy diets: evidence from Chile, Publ Health Nutr, 1–10
  14. Parra, 2019, Association between ultra-processed food consumption and the nutrient profile of the Colombian diet in 2005, Salud Publica Mex, 61, 147, 10.21149/9038 · DOI
  15. Marrón-Ponce, 2019, Associations between consumption of ultra-processed foods and intake of nutrients related to chronic non-communicable diseases in Mexico, J Acad Nutr Diet, S2212–2672, 31402
  16. Machado, 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, 10.1136/bmjopen-2019-029544 · DOI
  17. Moubarac, 2017, Consumption of ultra-processed foods predicts diet quality in Canada, Appetite, 108, 512, 10.1016/j.appet.2016.11.006 · DOI
  18. Steele, 2021, The burden of excessive saturated fatty acid intake attributed to ultra-processed food consumption: a study conducted with nationally representative cross-sectional studies from eight countries, J Nutr Sci, 10, e43, 10.1017/jns.2021.30 · DOI
  19. 2003, Expert consultation on diet, nutrition and the prevention of chronic diseases (2002: geneva, Switzerland) World health organization. Diet, nutrition and the prevention of chronic diseases, Report of a joint FAO/WHO Expert Consultation, 916, 61
  20. Steenland, 2006, An overview of methods for calculating the burden of disease due to specific risk factors, Epidemiology, 17, 512, 10.1097/01.ede.0000229155.05644.43 · DOI
  21. Rezende, 2016, Population attributable fraction: planning of diseases prevention actions in Brazil, Rev Saude Publica, 50, 30, 10.1590/S1518-8787.2016050006269 · DOI
  22. Luiten, 2016, Ultra-processed foods have the worst nutrient profile, yet they are the most available packaged products in a sample of New Zealand supermarkets--CORRIGENDUM, Publ Health Nutr, 19, 539, 10.1017/S1368980015002840 · DOI
  23. Mba, 2015, Palm oil: processing, characterization and utilization in the food industry – a review, Food Biosci, 26, 10.1016/j.fbio.2015.01.003 · DOI
  24. Ozyurt, 2016, Effect of food processing on the physicochemical properties of dietary fibre, Acta Sci Pol Technol Aliment, 15, 233, 10.17306/J.AFS.2016.3.23 · DOI
  25. Guillon, 2000, Structural and physical properties of dietary fibres, and consequences of processing on human physiology, Food Res Int, 33, 233, 10.1016/S0963-9969(00)00038-7 · DOI
  26. Lichtenstein, 2021, Circulation
  27. Popkin, 2021, Towards unified and impactful policies to reduce ultra-processed food consumption and promote healthier eating, Lancet Diabetes Endocrinol, 9, 462, 10.1016/S2213-8587(21)00078-4 · DOI
  28. Prentice, 2011, Evaluation and comparison of food records, recalls, and frequencies for energy and protein assessment by using recovery biomarkers, Am J Epidemiol, 174, 591, 10.1093/aje/kwr140 · DOI
  29. Herrick, 2018, Estimating usual dietary intake from national health and nutrition examination survey data using the National Cancer Institute method, Vital Health Stat, 2
  30. McLean, 2014, Measuring population sodium intake: a review of methods, Nutrients, 6, 4651, 10.3390/nu6114651 · DOI
  31. Baraldi, 2018, Consumption of ultra-processed foods and associated sociodemographic factors in the USA between 2007 and 2012: evidence from a nationally representative cross-sectional study, BMJ Open, 8, 10.1136/bmjopen-2017-020574 · DOI
  32. Vandevijvere, 2020, The cost of diets according to their caloric share of ultraprocessed and minimally processed foods in Belgium, Nutrients, 12, 2787, 10.3390/nu12092787 · DOI

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Metadata

Authors
Martinez Steele, E., Marrón Ponce, J. A., Cediel, G., Louzada, M. L. C., Khandpur, N., Machado, P., Moubarac, J.-C., Rauber, F., Corvalán, C., Levy, R. B., & Monteiro, C. A.
ORCID
Venue
Nutrition, Metabolism and Cardiovascular Diseases
Publisher
Elsevier BV
Published
2022-12
Volume
32
Issue
12
Pages
2739-2750
ISSN
0939-4753
DOI
10.1016/j.numecd.2022.08.018
Cited by
32
References
10
Language
en
Licence
Funders
Fundação de Amparo à Pesquisa do Estado de São Paulo (2015/14900–9, 2018/17972–9)

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