Energy contribution from ultra processed foods in Peruvian children
DOI:
https://doi.org/10.17843/rpmesp.2025.423.14339Keywords:
Peru, Children, Food Intake, Energy Intake, Ultra processed FoodsAbstract
Objective. To evaluate the energy contribution of ultra-processed foods (UPFs) and its association with social and demographic covariates in children between 6 and 35 months of age, based on national surveys conducted in 2008‒2010, 2015‒2016, and 2019. Materials and methods. The surveys used multistage stratified random samples. 24-hour recalls were applied on random days per participant, using the modified multiple-pass method, with the support of visual aids and scales. UPFs belonged to the Nova 4 group. Given the bimodal distribution, the covariates were analyzed using two models: a binomial model for the percentage of UPF consumers and a normal model for the average energy contribution, only among UPF consumers. The estimates and models were adjusted according to the sampling design. Results. 2887 children were included. UPFs contributed 27% (95% CI: 25 to 29) of the total energy intake and were consumed by 86% (84 to 89) of children. The main energy contribution from UPFs came from the milk and dairy products group (19% [17 to 20]) and cereals (5% [4 to 6]). The covariates associated with consumption were age, calendar quarter, and poverty. No associations were found with sex or the year of the survey. Conclusions. In children aged 6 to 35 months in Peru, UPFs provided an average of 27% of total energy and were consumed by 86%. The main sources were the milk and dairy products, and the cereals group. UPF consumption was associated with age, poverty, and the calendar quarter
Downloads
References
Swinburn BA, Kraak VI, Allender S, Atkins VJ, Baker PI, Bogard JR, et al. The Global Syndemic of Obesity, Undernutrition, and Climate Change: The Lancet Commission report. The Lancet. 2019;393(10173):791–846. doi: 10.1016/S0140-6736(18)32822-8.
WHO Consultation on Obesity (1999: Geneva S, Organization WH. Obesity : preventing and managing the global epidemic: report of a WHO consultation [Internet]. World Health Organization; 2000 [citado el 17 de mayo de 2023]. Disponible en: https://apps.who.int/iris/handle/10665/42330.
Nyberg ST, Batty GD, Pentti J, Virtanen M, Alfredsson L, Fransson EI, et al. Obesity and loss of disease-free years owing to major non-communicable diseases: a multicohort study. Lancet Public Health. 2018;3(10):e490–7. doi: 10.1016/S2468-2667(18)30139-7.
NCD Risk Factor Collaboration. Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults. Lancet Lond Engl. 2017;390(10113):2627–42. doi: 10.1016/S0140-6736(17)32129-3.
Jaacks LM, Vandevijvere S, Pan A, McGowan CJ, Wallace C, Imamura F, et al. The obesity transition: stages of the global epidemic. Lancet Diabetes Endocrinol. 2019;7(3):231–40. doi: 10.1016/S2213-8587(19)30026-9.
Wells JC, Sawaya AL, Wibaek R, Mwangome M, Poullas MS, Yajnik CS, The double burden of malnutrition: aetiological pathways and consequences for health. The Lancet. 2020;395(10217):75–88. doi: 10.1016/S0140-6736(19)32472-9.
Zhang X, Liu J, Ni Y, Yi C, Fang Y, Ning Q, et al. Global Prevalence of Overweight and Obesity in Children and Adolescents: A Systematic Review and Meta-Analysis. JAMA Pediatr. 2024;178(8):800–13. doi: 10.1001/jamapediatrics.2024.1576.
Di Cesare M, Sorić M, Bovet P, Miranda JJ, Bhutta Z, Stevens GA, et al. The epidemiological burden of obesity in childhood: a worldwide epidemic requiring urgent action. BMC Med. 2019;17(1):212. doi: 10.1186/s12916-019-1449-8.
UNICEF. Análisis del panorama del sobrepeso y obesidad infantil y adolescente en Perú [Internet]. 2023 [citado el 12 de marzo de 2025]. Disponible en: https://www.unicef.org/lac/informes/analisis-del-panorama-del-sobrepeso-y-obesidad-infantil-y-adolescente-en-peru.
Pajuelo-Ramírez J, Miranda-Cuadros M, Campos-Sánchez M, Sánchez-Abanto J. Prevalencia de sobrepeso y obesidad en niños menores de cinco años en el Perú 2007-2010. Rev Peru Med Exp Salud Publica. 2011;28(2):222–7.
Costa CS, Del-Ponte B, Assunção MCF, Santos IS. Consumption of ultra-processed foods and body fat during childhood and adolescen-ce: a systematic review. Public Health Nutr. 2018;21(1):148–59. doi: 10.1017/S1368980017001331.
De Amicis R, Mambrini SP, Pellizzari M, Foppiani A, Bertoli S, Battezzati A, et al. Ultra-processed foods and obesity and adiposity parameters among children and adolescents: a systematic review. Eur J Nutr. 2022;61(5):2297–311. doi: 10.1007/s00394-022-02873-4.
Matos RA, Adams M, Sabaté J. Review: The Consumption of Ultra-Processed Foods and Non-communicable Diseases in Latin America. Front Nutr. 2021;8:622714. doi: 10.3389/fnut.2021.622714.
Moubarac J-C, Monteiro CA, Jacoby, E. Alimentos y bebidas ultraprocesados en América Latina: ventas, fuentes, perfiles de nutrientes e implicaciones – OPS [Internet]. [citado el 25 de mayo de 2022]. Disponible en: https://cesni-biblioteca.org/ultraprocesadoslatam/.
Monteiro CA, Cannon G, Moubarac J-C, Levy RB, Louzada MLC, Jaime PC. The UN Decade of Nutrition, the NOVA food classification and the trouble with ultra-processing. Public Health Nutr. 2018;21(1):5–17. doi: 10.1017/S1368980017000234.
Organización Panamericana de la Salud. Modelo de Perfil de Nutrientes [Internet]. 2016. Disponible en: https://iris.paho.org/bitstream/handle/10665.2/18622/9789275318737_spa.pdf.
Lane MM, Gamage E, Du S, Ashtree DN, McGuinness AJ, Gauci S, et al. Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses. BMJ. 2024;384:e077310. doi: 10.1136/bmj-2023-077310.
Fang Z, Rossato SL, Hang D, Khandpur N, Wang K, Lo C-H, et al. Association of ultra-processed food consumption with all cause and cause specific mortality: population based cohort study. BMJ. 2024;385:e078476. doi: 10.1136/bmj-2023-078476.
Aramburu A, Alvarado-Gamarra G, Cornejo R, Curi-Quinto K, Díaz-Parra CDP, Rojas-Limache G, et al. Ultra-processed foods consumption and health-related outcomes: a systematic review of randomized controlled trials. Front Nutr. 2024;11:1421728. doi: 10.3389/fnut.2024.1421728.
Valicente VM, Peng C-H, Pacheco KN, Lin L, Kielb EI, Dawoodani E, et al. Ultraprocessed Foods and Obesity Risk: A Critical Review of Reported Mechanisms. Adv Nutr Bethesda Md. 2023;14(4):718–38. doi: 10.1016/j.advnut.2023.04.006.
Neri D, Steele EM, Khandpur N, Cediel G, Zapata ME, Rauber F, et al. Ultraprocessed food consumption and dietary nutrient profiles associated with obesity: A multicountry study of children and adolescents. Obes Rev Off J Int Assoc Study Obes. 2022;23 Suppl 1:e13387. doi: 10.1111/obr.13387.
Cediel G, Reyes M, Louzada ML da C, Steele EM, Monteiro CA, Corvalán C, et al. Ultra-processed foods and added sugars in the Chilean diet (2010). Public Health Nutr. 2018;21(1):125–33. doi: 10.1017/S1368980017001161.
Louzada ML da C, 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). doi: 10.1590/S0034-8910.2015049006132.
Marrón-Ponce JA, Sánchez-Pimienta TG, Louzada ML da C, Batis C. Energy contribution of NOVA food groups and sociodemographic determinants of ultra-processed food consumption in the Mexican population. Public Health Nutr. 2018;21(1):87–93. doi: 10.1017/S1368980017002129.
Khandpur N, Cediel G, Obando DA, Jaime PC, Parra DC. Sociodemographic factors associated with the consumption of ultra-processed foods in Colombia. Rev Saúde Pública. 2020;54:19. doi: 10.11606/s1518-8787.2020054001176.
Perú, Instituto Nacional de Salud (INS). Monitoreo Nacional de Indicadores Nutricionales (MONIN), CENAN 2007-2010 | Plataforma Nacional de Datos Abiertos [Internet]. [citado el 19 de septiembre de 2023]. Disponible en: https://www.datosabiertos.gob.pe/dataset/monitoreo-nacional-de-indicadores-nutricionales-monin-cenan-2007-2010.
Perú, Instituto Nacional de Salud (INS). Vigilancia Alimentaria y Nutricional - VIANEV - niños menores de 36 meses - 2015 | Plataforma Nacional de Datos Abiertos [Internet]. [citado el 19 de septiembre de 2023]. Disponible en: https://www.datosabiertos.gob.pe/dataset/vigilancia-alimentaria-y-nutricional-vianev-ni%C3%B1os-menores-de-36-meses-2015.
Perú, Instituto Nacional de Salud (INS). Encuesta VIANEV niños 2016. Estado nutricional, consumo de LM y consumo de alimentos. INS-CENAN | Plataforma Nacional de Datos Abiertos [Internet]. [citado el 19 de septiembre de 2023]. Disponible en: https://www.datosabiertos.gob.pe/dataset/encuesta-vianev-ni%C3%B1os-2016-estado-nutricional-consumo-de-lm-y-consumo-de-alimentos-ins-cenan.
Perú, Instituto Nacional de Salud (INS). Encuesta VIANEV 2019. Estado nutricional y consumo de alimentos del niño menor de 5 años de la Encuesta Vigilancia Alimentaria y Nutricional por Etapas de Vida - VIANEV 2019 | Plataforma Nacional de Datos Abiertos [Internet]. [citado el 19 de septiembre de 2023]. Disponible en: https://www.datosabiertos.gob.pe/dataset/encuesta-vianev-2019-estado-nutricional-y-consumo-de-alimentos-del-ni%C3%B1o-menor-de-5-a%C3%B1os-de.
Moshfegh AJ, Rhodes DG, Baer DJ, Murayi T, Clemens JC, Rumpler WV, et al. The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes. Am J Clin Nutr. 2008;88(2):324–32. doi: 10.1093/ajcn/88.2.324.
Perú, Ministerio de Desarrollo e Inclusión Social. Programa Nacional Cuna Más - PNCM [Internet]. 2023 [citado el 19 de septiembre de 2023]. Disponible en: https://www.gob.pe/cunamas.
Reyes García M, Gómez-Sánchez Prieto I, Espinoza Barrientos C. Tablas peruanas de composición de alimentos [Internet]. Instituto Nacional de Salud; 2017 [citado el 29 de agosto de 2018]. Disponible en: http://repositorio.ins.gob.pe/handle/INS/1034.
Asociación Benéfica Prisma. Análisis Nutricional de la Dieta según Requerimientos y Adecuación (ANDREA®). Lima, PE: Prisma; 2003.
Open Food Facts [Internet]. [citado el 27 de octubre de 2021]. Disponible en: https://pe.openfoodfacts.org.
Rospigliosi J. Estudio de la Ganaderia Lechera en el Perú: Análisis de su estructura , dinamica y propuestas de Desarrollo [Internet]. Ministerio de Desarrollo Agrario y Riego; 2017. Disponible en: https://repositorio.midagri.gob.pe/jspui/bitstream/20.500.13036/73/1/Ganaderia%20de%20la%20Leche.pdf.
Dicken SJ, Qamar S, Batterham RL. Who consumes ultra-processed food? A systematic review of sociodemographic determinants of ultra-processed food consumption from nationally representative samples. Nutr Res Rev. 2024;37(2):416–56. doi: 10.1017/S0954422423000240.
Leung CW, Fulay AP, Parnarouskis L, Martinez-Steele E, Gearhardt AN, Wolfson JA. Food insecurity and ultra-processed food consumption: the modifying role of participation in the Supplemental Nutrition Assistance Program (SNAP). Am J Clin Nutr. 2022;116(1):197–205. doi: 10.1093/ajcn/nqac049.
Juul F, Parekh N, Martinez-Steele E, Monteiro CA, Chang VW. Ultra-processed food consumption among US adults from 2001 to 2018. Am J Clin Nutr. 2022;115(1):211–21. doi: 10.1093/ajcn/nqab305.
Baraldi LG, Martinez Steele E, Canella DS, Monteiro CA. 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. 2018;8(3):e020574. doi: 10.1136/bmjopen-2017-020574.
Valizadeh P, Ng SW. Promoting Healthier Purchases: Ultraprocessed Food Taxes and Minimally Processed Foods Subsidies for the Low Income. Am J Prev Med. 2024;67(1):3–14. doi: 10.1016/j.amepre.2024.02.019.
World Bank (WB). Rising Strong: Peru Poverty and Equity Assessment [Internet]. World Bank. [citado el 12 de marzo de 2025]. Disponible en: https://www.worldbank.org/en/country/peru/publication/resurgir-fortalecidos-evaluacion-de-pobreza-y-equidad-en-el-peru.
Congreso de la República. Ley N.° 30021 [Internet]. [citado el 12 de marzo de 2025]. Disponible en: https://www.gob.pe/institucion/congreso-de-la-republica/normas-legales/118470-30021.
Campos Sánchez M. Informe de Consultoría para la Revisión, Consistencia y Procesamiento y Análisis estadístico de la base de Datos de la Encuesta Nacional por Muestreo Continuo de Vigilancia Nutricional – MONIN XXI al IV trimestre 2009 [Internet]. Disponible en: https://datosabiertos.gob.pe/dataset/monitoreo-nacional-de-indicadores-nutricionales-monin-cenan-2007-2010/resource/87dcb2ba-5855.
Miranda M, Campos M. Estimación de varianzas intra e inter individuales para la determinación de la distribución de la ingesta usual de nutrientes. En Lima, PE: INS; 2013. Disponible en: https://web.ins.gob.pe/sites/default/files/Archivos/cenan/van/vigilacia_poblacion/
ivnu/2013/Poster_2013.pdf.
Sneed NM, Ukwuani S, Sommer EC, Samuels LR, Truesdale KP, Matheson D, et al. Reliability and validity of assigning ultraprocessed food categories to 24-h dietary recall data. Am J Clin Nutr. 2023;117(1):182–90. doi: 10.1016/j.ajcnut.2022.10.016.
Braesco V, Souchon I, Sauvant P, Haurogné T, Maillot M, Féart C, et al. Ultra-processed foods: how functional is the NOVA system? Eur J Clin Nutr. 2022;76(9):1245–53. doi: 10.1038/s41430-022-01099-1.
Bleiweiss-Sande R, Chui K, Evans EW, Goldberg J, Amin S, Sacheck J. Robustness of Food Processing Classification Systems. Nutrients. 2019;11(6):1344. doi: 10.3390/nu11061344.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Gustavo Cediel Giraldo, María Laura da Costa Louzada, Joaquín Alejandro Marrón-Ponce, Marianella Miranda-Cuadros, Miguel Campos-Sánchez
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
