Relationship Between Ultra-Processed Food Consumption and Cognitive Function among Children Ages 7-11 in Terengganu, Malaysia

Shazwina Aqmar Fatnin  Zulkornain; Asma' Ali; Noor Salihah  Zakaria; Khairil Shzamin Kamarudin; Hamid Jan Jan Mohamed; Ahmad Ali Zainuddin; Hayati Mohd Yusof

doi:10.25182/jgp.2025.20.3.147-156

Shazwina Aqmar Fatnin Zulkornain⁽¹⁾ , Asma' Ali⁽²⁾ , Noor Salihah Zakaria⁽³⁾ , Khairil Shzamin Kamarudin⁽⁴⁾ , Hamid Jan Jan Mohamed⁽⁵⁾ , Ahmad Ali Zainuddin⁽⁶⁾ , Hayati Mohd Yusof⁽⁷⁾

(1) Food Service and Nutrition Programme, Faculty of Food Science and Agrotechnology, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Malaysia,

(2) Food Service and Nutrition Programme, Faculty of Food Science and Agrotechnology, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Malaysia,

(3) Food Service and Nutrition Programme, Faculty of Food Science and Agrotechnology, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Malaysia,

(4) Food Service and Nutrition Programme, Faculty of Food Science and Agrotechnology, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Malaysia,

(5) Nutrition and Dietetics Programme, School of Health Sciences, Universiti Sains Malaysia, Kota Bharu 16150, Malaysia,

(6) Institute for Public Health, 40170 Shah Alam, Selangor, Malaysia,

(7) Food Service and Nutrition Programme, Faculty of Food Science and Agrotechnology, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Malaysia

https://doi.org/10.25182/jgp.2025.20.3.147-156

Issue
Vol. 20 No. 3 (2025)

Submitted
April 27, 2025

Accepted
October 1, 2025

Published
November 30, 2025

Keywords:

children, cognitive function, nova classification system, raven progressive matrices, Terengganu, ultra-processed food

PDF

Abstract

This study aimed to examine the correlation between Ultra-Processed Foods (UPF) consumption and cognitive function among school-aged children (7–11 years) in Terengganu. A cross-sectional study (n=200; 53.5% girls; ages: 7–8y 13.0%, 9y 11.0%, 10y 17.0%, 11y 59.0%) was employed. Two non-consecutive 24-h recalls (one weekday, one weekend) were coded and foods classified with NOVA; UPF intake expressed as % of total energy. Cognitive function was assessed with Raven’s Coloured Progressive Matrices. Spearman’s correlation tested UPF–cognition associations (α=0.05). Mean energy intake was 1,623 kcal/day, approximating 84–101% of Malaysian Recommended Nutrient Intakes (RNI) across ages 7–11. UPFs contributed 26.7% of energy (weekday 25.8%, weekend 27.4%). Mean cognitive score was 105.4±18.7, with 28.5% in the average range. No significant correlation was observed between UPF energy share and cognitive scores (rs=0.065, p=0.361). While moderate UPF consumption did not directly impair cognitive function, this study reveals a compelling narrative about the protective role of traditional diets and parental involvement in shaping children's health and cognitive development.

Full text article

Generated from XML file

References

Ali JAH, Gaffinet B, Panetto H, Naudet Y. 2024. Cognitive systems and interoperability in the enterprise: A systematic literature review. Annu Rev Control 57:100954. https://doi.org/10.1016/j.arcontrol.2024.100954

Asma A, Gan HJ, Hayati MY, Khairil-Shazmin K, Zainudin AA. 2019. Food classification system based on food processing and its relationship with nutritional status of adults in Terengganu, Malaysia. Food Res 4(2):539–546. https://doi.org/10.26656/fr.2017.4(2).320

Ben-Mimouna S, Chemek M, Boughammoura S, Haouas Z, Messaoudi I. 2018. Protective role of zinc against the neurotoxicity induced by exposure to cadmium during gestation and lactation periods on hippocampal volume of pups tested in early adulthood. Drug Chem Toxicol 41(4):424–433. https://doi.org/10.1080/01480545.2018.1461901

Carroll JE, Sturgeon SR, Bertone-Johnson E, VanKim N, Longacre MR, Dalton MA, Emond JA. 2024. Factors correlated with ultra-processed food (UPF) intake in preschool-aged children and association with weight. J Nutr Educ Behav 56(4):196–208. https://doi.org/10.1016/j.jneb.2023.12.008

Chadha M, Shukla R, Tiwari RK, Dubey DK, Singh K. 2024. Impact of ultra-processed foods on food sustainability: Exposure assessment and health implications. Recent Adv Food Nutr Agric 15. https://doi.org/10.2174/012772574x327683240910063234

D’Cunha NM, Sergi D, Lane MM, Naumovski N, Gamage E, Rajendran A, Kouvari M, Gauci S, Dissanayka T, Marx W, Travica N. 2022. The effects of dietary advanced glycation end-products on neurocognitive and mental disorders. Nutr 14(12):2421. https://doi.org/10.3390/nu14122421

Delgado-Rodríguez R, Moreno-Padilla M, Moreno-Domínguez S, Cepeda-Benito A. 2023. Food addiction correlates with emotional and craving reactivity to industrially prepared (ultra-processed) and home-cooked (processed) foods but not unprocessed or minimally processed foods. Food Qual Prefer 110:104961. https://doi.org/10.1016/j.foodqual.2023.104961

Fu Q, DeJager J, Gardner EM. 2024. Supplementation and mitigating cognitive decline in older adults with or without mild cognitive impairment or dementia: A systematic review. Nutr 16(20):3567. https://doi.org/10.3390/nu16203567

Gould JF, Smithers LG, Makrides M. 2013. The effect of maternal omega-3 (n-3) LCPUFA supplementation during pregnancy on early childhood cognitive and visual development: A systematic review and meta-analysis of randomized controlled trials. Am J Clin Nutr 97(3):531–544. https://doi.org/10.3945/ajcn.112.045781

Granero R, Guillazo-Blanch G. 2025. Nutrition and dietary patterns: Effects on brain function. Nutr 17(7):1169. https://doi.org/10.3390/nu17071169

Gutema BT, Sorrie MB, Megersa ND, Yesera GE, Yeshitila YG, Pauwels NS, De Henauw S, Abbeddou S. 2023. Effects of iron supplementation on cognitive development in school-age children: Systematic review and meta-analysis. Plos One 18(6):e0287703. https://doi.org/10.1371/journal.pone.0287703

He J, Ryder AG, Li S, Liu W, Zhu X. 2018. Glycemic extremes are related to cognitive dysfunction in children with type 1 diabetes: A meta-analysis. J Diabetes Investig 9(6):1342–1353. https://doi.org/10.1111/jdi.12840

Hemmer A, Blanc S, Mareschal J, Biolley E, Phillips NE, Umwali S, Gendre D, Fiammingo O, Sinturel F, Genton L, et al. 2023. Evaluation of underreporting of energy intake using a smartphone food application and 24h dietary recall compared to resting energy expenditure in overweight and obesity. Clin Nutr ESPEN 58:660. https://doi.org/10.1016/j.clnesp.2023.09.690

Henn RE, Elzinga SE, Glass E, Parent R, Guo K, Allouch AM, Mendelson FE, Hayes J, Webber-Davis I, Murphy GG, et al. 2022. Obesity-induced neuroinflammation and cognitive impairment in young adult versus middle-aged mice. Immun Ageing 19(1):67. https://doi.org/10.1186/s12979-022-00323-7

Kennedy DO. 2016. B vitamins and the brain: Mechanisms, dose and efficacy—A review. Nutr 8(2):68. https://doi.org/10.3390/nu8020068

Li P, Xu J, Guo Y, Ma X, Wang X, Liu L, Ren X, Li J, Wang Y, Meng L, Zhou S & Yuan L. 2025. Impact of vitamin A on aged people’s cognition and Alzheimer’s disease progression in an animal model. NPJ Sci Food 9(1):67.

Liu J, Steele EM, Li Y, Karageorgou D, Micha R, Monteiro CA, Mozaffarian D. 2022. Consumption of ultra-processed foods and diet quality among U.S. children and adults. Am J Prev Med 62(2):252–264. https://doi.org/10.1016/j.amepre.2021.08.014

Liu S, Mo C, Lei L, Lv F, Li J, Xu X, Lu P, Wei G, Huang X, Zeng X, et al. 2023. Association of ultra-processed foods consumption and cognitive function among children aged 4–7 years: A cross-sectional data analysis. Front Nutr 10:1272126. https://doi.org/10.3389/fnut.2023.1272126

Mescolotto SB, Pongiluppi G, Domene SMÁ. 2024. Ultra-processed food consumption and children and adolescents’ health. J Pediatr 100:S18–S30. https://doi.org/10.1016/j.jped.2023.09.006

Mok KT, Tung SEH. 2022. Picky eating behavior, feeding practices, dietary habits, weight status and cognitive function among school children in Kuala Lumpur, Malaysia. MJMHS 18(4):10–18. https://doi.org/10.47836/mjmhs.18.4.3

Monteiro CA, Astrup A, Ludwig DS. 2022. Does the concept of “ultra-processed foods” help inform dietary guidelines, beyond conventional classification systems? YES. Am J Clin Nutr 116(6):1476–1481. https://doi.org/10.1093/ajcn/nqac122

Monteiro CA, Cannon G, Moubarac J, Levy RB, Louzada MLC, Jaime PC. 2018. 2017. The UN Decade of Nutrition, the NOVA food classification and the trouble with ultra-processing. Public Health Nutr 21(1):5–17. https://doi.org/10.1017/s1368980017000234

Mirnalini K, Zalilah MS, Safiah MY, Tahir A, Haslinda MDS, Rohana DS, Zarina MYK, Hasyami SM, Normah H. 2008. Energy and nutrient intakes: Findings from the Malaysian Adult Nutrition Survey (MANS). Malays J Nutr 14(1):1–24. https://pubmed.ncbi.nlm.nih.gov/22691761

Peña-Jorquera H, Martínez-Flores R, Espinoza-Puelles JP, López-Gil JF, Ferrari G, Zapata-Lamana R, Lofrano-Prado MC, Landaeta-Díaz L, Cigarroa I, Durán-Agüero S, et al. 2024. Adolescents with a favorable Mediterranean – style-based pattern show higher cognitive and academic achievement: A cluster analysis—The Cogni-Action Project. Nutr 16(5):608. https://doi.org/10.3390/nu16050608

Popkin BM, Miles DR, Taillie LS, Dunford EK. 2024. A policy approach to identifying food and beverage products that are ultra-processed and high in added salt, sugar and saturated fat in the United States: A cross-sectional analysis of packaged foods. Lancet Reg Health Am 32:100713. https://doi.org/10.1016/j.lana.2024.100713

Rodoman I, Timotin A, Lozan O. 2024. Parental socio-demographic influences on school-aged children’s diets: A comprehensive study in the Republic of Moldova. OH&RM 5(2):25–33. https://doi.org/10.38045/ohrm.2024.2.03

Sandjaja, Poh B.K, Rojroonwasinkul N, Nyugen BKL, Budiman B, Ng LO, Soonthorndhada K, Xuyen HT, Deurenberg P, Parikh P. 2013. Relationship between anthropometric indicators and cognitive performance in Southeast Asian school-aged children. Br J Nutr 110(S3):S57–S64. https://doi.org/10.1017/s0007114513002079

Schnermann ME, Nöthlings U, Alexy U. 2024. Empirically derived portion sizes from the DONALD study for 4 to 18 year old children and adolescents to simplify analysis of dietary data using FFQ. Public Health Nutr 27(1):e49. https://doi.org/10.1017/s136898002400017x

Song B, Li M, Xia X, Xia C, He T, Wu L, Chen S, Bu W. 2023. Effects of ultra-processed foods on the microbiota–gut–brain axis. Food Res Int 170:113073. https://doi.org/10.1016/j.foodres.2023.113073

Tay JEF, Kaur S, Tham WW, Gan WY, Ya NNC, Tan CH, Tung SEH. 2023. Food security and diet quality among urban poor adolescents in Kuala Lumpur, Malaysia. Nutr Res Pract 17(2):269. https://doi.org/10.4162/nrp.2023.17.2.269

Travica N, Ried K, Sali A, Scholey A, Hudson I, Pipingas A. 2017. Vitamin C status and cognitive function: A systematic review. Nutr 9(9):960. https://doi.org/10.3390/nu9090960

Valdés-Undurraga I, Lobos P, Sánchez-Robledo V, Arias-Cavieres A, SanMartín CD, Barrientos G, More J, Muñoz P, Paula-Lima AC, Hidalgo C, Adasme T. 2023. Long-term potentiation and spatial memory training stimulate the hippocampal expression of RyR2 calcium release channels. Front Cell Neurosci 21(17):1132121. https://doi.org/10.3389/fncel.2023.1132121

Via E, Contreras-Rodríguez O. 2023. Binge-eating precursors in children and adolescents: neurodevelopment, and the potential contribution of ultra-processed foods. Nutr 15(13):2994. https://doi.org/10.3390/nu15132994

Warthon-Medina M, Moran VH, Stammers A-L, Dillon S, Qualter P, Nissensohn M, Serra-Majem L, Lowe NM. 2015. Zinc intake, status and indices of cognitive function in adults and children: A systematic review and meta-analysis. Eur J Clin Nutr 69(6):649–661. https://doi.org/10.1038/ejcn.2015.60

Wei TS, Ali A. 2018. Breakfast consumption and its relationship with cognitive performance among fisherman’s children in Terengganu. Malays Appl Biol 47(4):25–34.

Yang WY, Wong SY, Ong SH, Arasu K, Chang CY, Chong MHZ, Mavinkurve M, Khoo EJ, Chinna K, Weaver CM, et al. 2023. Characteristics of dietary intakes including NOVA foods among pre-adolescents living in urban Kuala Lumpur–Findings from the PREBONE-Kids study. Malays J Nutr 29(3). https://doi.org/10.31246/mjn-2022-0068