Added sugars and ultra-processed foods in Spanish households (1990–2010)

Published online:



To study the association between ultra-processed foods acquisitions and added sugar content of total food purchases in Spanish households in 2010. Changes over time (1990–2000–2010) in ultra-processed food purchases and added sugars content of total food purchases are also compared.


We used data from three nationally representative Household Budget Surveys (HBS) conducted in 1990, 2000 and 2010. Number of studied households was 21,012, 33,730 and 22,116, respectively. Purchased foods and drinks were classified according to NOVA food groups as ultra-processed foods, processed foods, unprocessed or minimally processed foods, or processed culinary ingredients.

Linear and Poisson regressions were used to estimate the association between quintiles of energy contribution of ultra-processed foods and added sugars contents of total food purchases in 2010.

Changes over time were assessed using tests of linear trend and Student’s t test.


In 2010, ultra-processed foods represented 31.7% of daily energy acquisitions and 80.4% of all added sugars. Added sugars content of food purchases raised from 7.3% in the lowest to 18.2% in the highest quintiles of energy contribution of ultra-processed foods. The risk of exceeding 10% energy from added sugars quadrupled between the lowest and highest quintiles.

The percentage of ultra-processed foods on all food purchases almost tripled between 1990 and 2010 (from 11.0 to 31.7%), paralleling the increase of added sugars content (from 8.4 to 13.0%).


Cutting down exceeding added sugars availability in Spain may require a reduction in ultra-processed food purchasing.

  • Subscribe to European Journal of Clinical Nutrition for full access:



Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.


  1. 1.

    Te Morenga LA, Mallard S, Mann J. Dietary sugars and body weight: systematic review and meta-analyses of randomised controlled trials and cohort studies. BMJ 2013;346:E7492.

  2. 2.

    Moynihan PJ, Kelly SAM. Effect on caries of restricting sugars intake: systematic review to inform WHO guidelines. J Dent Res 2014;93(1):8–18.

  3. 3.

    Te Morenga LA, Howatson AJ, Jones RM, Mann J. Dietary sugars and cardiometabolic risk: systematic review and meta-analyses of randomized controlled trials of the effects on blood pressure and lipids. Am J Clin Nutr 2014;100(1):65–79.

  4. 4.

    Hu FB, Malik VS. Sugar-sweetened beverages and risk of obesity and type 2 diabetes: epidemiologic evidence. Physiol Behav 2010;100(1):47–54.

  5. 5.

    Malik VS, Popkin BM, Bray GA, Després JP, Hu FB. Sugar-sweetened beverages, obesity, type 2 diabetes mellitus, and cardiovascular disease risk. Circulation 2010;121(11):1356–64.

  6. 6.

    Malik VS, Popkin BM, Bray GA, Després JP, Willett WC, Hu FB. Sugar-sweetened beverages and risk ofmetabolic syndrome and type 2 diabetes: a meta-analysis. Diabetes Care 2010;33(11):2477–83.

  7. 7.

    Schulze MB, Manson JE, Ludwig DS, Colditz GA, Stampfer MJ, Willett WC, et al. Sugar-sweetened beverages, weight gain, and incidence of type 2 diabetes in young and middle-aged women. JAMA 2004;292(8):927–34.

  8. 8.

    Basu S, Yoffe P, Hills N, Lustig RH. The relationship of sugar to population-level diabetes prevalence: an econometric analysis of repeated cross-sectional data. PLoS One 2013;8(2):e57873.

  9. 9.

    de Koning L, Malik VS, Kellogg MD, Rimm EB, Willett WC, Hu FB. Sweetened beverage consumption, incident coronary heart disease, and biomarkers of risk in men. Circulation 2012;125(14):1735–41.

  10. 10.

    World Health Organization. Guideline: sugars intake for adults and children. World Health Organization: Geneva; 2015.

  11. 11.

    Dietary Guidelines Advisory Committee. Scientific report of the 2015 dietary guidelines advisory committee—1487697231. 2015.

  12. 12.

    NHS Health Choices. 2016. Eight tips for healthy eating—1487697231. Accessed Aug 2016.

  13. 13.

    Bowman SA, Clemens JC, Thoerig RC, Friday JE, Shimizu M, Moshfegh AJ. Food patterns equivalents database 2009-10: methodology and user guide [Online]. Food Surveys Research Group, Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture: Beltsville, MD; 2013.

  14. 14.

    Ministerio de Salud de Brasil. Guía alimentaria para la población brasileña. Brasília: Ministerio de Salud de Brasil; 2015. p. 152.

  15. 15.

    Monteiro CA, Cannon G, Levy RB, Claro R, Moubarac JC. The food system. ultra-processing. the big issue for nutrition, disease, health, well-being [Commentary]. World Nutr. 2012;3(12):527–69.

  16. 16.

    Monteiro CA, Cannon G, Levy RB, Claro RM, Moubarac J-C. Ultra-processing and a new classification of foods. In: Neff R, (ed). Introduction to the US food system: public health, environment, and equity. San Francisco, CA: Jossey Bass A Wiley Brand; 2015.

  17. 17.

    Monteiro CA, Levy RB, Claro RM, de Castro IRR, Cannon G. A new classification of foods based on the extent and purpose of their processing. Cad Sauìde Puìblica. 2010;26(11):2039–49.

  18. 18.

    Moubarac JC, Parra DC, Cannon G, Monteiro CA. Food classification systems based on food processing: significance and implications for policies and actions: a systematic literature review and assessment. Curr Obes Rep 2014;3(2):256–72.

  19. 19.

    Stuckler D, McKee M, Ebrahim S, Basu S. Manufacturing epidemics: the role of global producers in increased consumption of unhealthy commodities including processed foods, alcohol, and tobacco. PLoS Med 2012;9:e1001235.

  20. 20.

    Monteiro CA, Cannon G. The impact of transnational ‘Big Food’ companies on the South: a view from Brazil. PLoS Med 2012a;9:e1001252.

  21. 21.

    Moodie R, Stuckler D, Monteiro C, Sheron N, Neal B, Thamarangsi T, et al Lancet NCD action group. Profits and pandemics: prevention of harmful effects of tobacco, alcohol, and ultra-processed food and drink industries. Lancet 2013;381(9867):670–9.

  22. 22.

    Monteiro CA, Moubarac JC, Cannon G, Popkin BM. Ultra-processed products are becoming dominant in the global food system. Obes Rev 2013;14(Suppl. 2):21–28.

  23. 23.

    Panamerican Health Organization. Ultra-processed food and drink products in Latin America: trends, impact on obesity, policy implications. Panamerican Health Organization: Washington D.C.; 2015.

  24. 24.

    Monteiro CA, Levy RB, Claro RM, de Castro IRR, Cannon G. Increasing consumption of ultra-processed foods and likely impact on human health: evidence from Brazil. Public Health Nutr 2011;14(1):5–13.

  25. 25.

    Moubarac JC, Martins APB, Claro RM, Levy RB, Cannon G, Monteiro CA. Consumption of ultra-processed foods and likely impact on human health. Evidence from Canada. Public Health Nutr 2013;16(12):2240–8.

  26. 26.

    Crovetto MM, Uauy R, Martins AP, Moubarac JC, Monteiro C. Disponibilidad de productos alimentarios listos para el consumo en los hogares de Chile y su impacto sobre la calidad de la dieta (2006–7). Rev Médica Chile. 2014;142(7):850–8.

  27. 27.

    Da Costa Louzada ML, Martins APB, Canella DS, Baraldi LG, Levy RB, Claro RM, et al. Ultra-processed foods and the nutritional dietary profile in Brazil. Rev Saúde Pública. 2015;49:38.

  28. 28.

    Martínez Steele E, Baraldi LG, Louzada ML, da C, Moubarac JC, Mozaffarian D, Monteiro CA. Ultra-processed foods and added sugars in the US diet: evidence from a nationally representative cross-sectional study. BMJ Open 2016;6:e009892.

  29. 29.

    Instituto Nacional de Estadística (Spanish Statistical Office). Metodología de la Encuesta de Presupuestos Familiares. Accessed Aug 2016.

  30. 30.

    Varela G, Moreiras O, Carbajal A, Campo M. Estudio nacional de nutrición y alimentación 1991 (ENNA 3). Tomo I. Instituto Nacional de Estadística: Madrid; 1995. p. 352.

  31. 31.

    Varela-Moreiras G, Ruiz E, Valero T, Avila JM, del Pozo S. The Spanish diet: an update. Nutr Hosp 2013;28(Suppl 5):13–20.

  32. 32.

    Instituto Nacional de Estadística. Evaluación de la calidad de los datos de la encuesta de presupuestos familiares. Año 2010. Octubre 2012.

  33. 33.

    Monteiro CA. Nutrition and health. The issue is not food, nor nutrients, so much as processing. Public Health Nutr 2009;12(5):729–31.

  34. 34.

    FAO. Guidelines on the collection of information on food processing through food consumption surveys. Rome: FAO; 2015.

  35. 35.

    Panamerican Health Organization. Ultra-processed food and drink products in Latin America: Trends, impact on obesity, policy implications. Washington D.C.: Panamerican Health Organization; 2015.

  36. 36.

    Monteiro CA, Cannon G, Levy RB, Moubarac JC, Jaime P, Martins AP, et al. NOVA. The star shines bright. [Food classification. Public health] World Nutrition January-March 2016;7(1-3):28–38.

  37. 37.

    Ludwig DS. Technology, diet, and the burden of chronic disease. JAMA 2011;305:1352–3.

  38. 38.

    Monteiro C, Cannon G. The big issue is processing. What are ultra-processed products. [Commentary]. World Nutr. 2012;3(6):257–68.

  39. 39.

    Ministerio de Agricultura, Alimentación y Medio Ambiente. Consumo de pan seguìn los datos del Panel de Consumo que elabora el Ministerio de Agricultura, Alimentacioìn y Medio Ambiente. MAGRAMA; 2011. Available at:

  40. 40.

    U.S. Department of Agriculture, Agricultural Research Service, USDA Nutrient Data Laboratory. 2004. USDA National Nutrient Database for Standard Reference, Release 16.

  41. 41.

    United States Department of Agriculture 1987 Sugar Content of Selected Foods: individual and total sugar. Home Economics Research report number 48.

  42. 42.

    Universidade Estadual de Campinas. Núcleo de Estudos e Pesquisas em Alimentação (2004). Tabela Brasileira de Composição de Alimentos–TACO. 1st ed. UNICAMP: Campinas.

  43. 43.

    United States Department of Agriculture. Agricultural Research Service. USDA National Nutrient Database for Standard Reference. Beltsville: USDA; 2002. Release, 15.

  44. 44.

    Barros AJD, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med Res Methodol 2003;3:21.

  45. 45.

    Subar AF, Freedman LS, Tooze JA, Kirkpatrick SI, Boushey C, Neuhouser ML, et al. Addressing current criticism regarding the value of self-report dietary data. The Journal of Nutrition 2015.

  46. 46.

    Naska A, Katsoulis M, Orfanos P, Lachat C, Gedrich K, Rodrigues SS, et al. HECTOR Consortium. Eating out is different from eating at home among individuals who occasionally eat out. A cross-sectional study among middle-aged adults from eleven European countries. Br J Nutr 2015;113(12):1951–64. Epub 2015 Apr 24.

  47. 47.

    Naska A, Vasdekis VG, Trichopoulou A. A preliminary assessment of the use of household budget survey data for the prediction of individual food consumption. Public Health Nutr 2001;4:1159–65.

  48. 48.

    Louzada MLC, Levy RB, Martins APB, Claro RM, Steele EM, Verly Junior E, et al. Validating the usage of household food acquisition surveys to assess the consumption of ultra-processed foods: evidence from Brazil. Food Policy. 2017;72:112–20.

  49. 49.

    Ruiz E, Ávila JM, Valero T, Del Pozo S, Rodriguez P, Aranceta-Bartrina J, et al. Macronutrient distribution and dietary sources in the spanish population: findings from the ANIBES study. Nutrients 2016;8(3):177.

  50. 50.

    Ruiz E, Rodriguez P, Valero T, Ávila JM, Aranceta-Bartrina J, Gil Á, et al. Dietary intake of individual (free and intrinsic) sugars and food sources in the spanish population: findings from the ANIBES study. Nutrients. 2017;9(3). pii: E275.

Download references


We thank Larissa Galastri Baraldi, Renata Bertazzi Levy, Ana Paula Bortoletto Martins for their help in data management and analysis.


This research received funding from Conselho Nacional de Desenvolvimento Científico e Tecnológico, Edital MCTI/CNPq/Universal (Processo CNPq nº 443477/2014-0) and from Fundação de Amparo à Pesquisa do Estado de São Paulo (Processo FAPESP nº 2015/14900-9).

Author information


  1. Servicio de Epidemiología, Dirección General de Salud Pública de la Comunidad de Madrid, Madrid, Spain

    • P. Latasa
  2. Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil

    • M. L. D. C. Louzada
    • , E. Martinez Steele
    •  & C. A. Monteiro
  3. Center for Epidemiological Studies in Health and Nutrition, University of São Paulo, São Paulo, Brazil

    • M. L. D. C. Louzada
    • , E. Martinez Steele
    •  & C. A. Monteiro


  1. Search for P. Latasa in:

  2. Search for M. L. D. C. Louzada in:

  3. Search for E. Martinez Steele in:

  4. Search for C. A. Monteiro in:

Conflict of interest

The authors declare that they have no competing interests.

Corresponding author

Correspondence to C. A. Monteiro.

Electronic supplementary material