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Association of the percentage contribution of food and beverage consumption at dinner and evening snack with overweight in Brazilian schoolchildren: a cross-sectional study
Published online by Cambridge University Press: 10 February 2026
Abstract
This study aimed to verify whether a higher percentage contribution of food and beverage consumption at dinner and evening snack was associated with overweight in schoolchildren from a city in southern Brazil. Cross-sectional study conducted with schoolchildren aged 7–14 years from the Prevalence Study of Obesity in Children and Adolescents of Florianopolis/SC. Weight and height were measured individually by trained researchers. The assessment of the weight status of the schoolchildren was conducted using the BMI, classified according to the Z-score for age. The self-reported food consumption was obtained through the online Web-CAAFE questionnaire. Multivariate logistic was used to verify the association between the percentage contribution of food groups in the dinner and evening snack meals with overweight. A total of 1379 schoolchildren participated in the study, of which 33·8 % were overweight. It was observed that a higher percentage contribution of meat, eggs, and seafood consumption at dinner was positively associated with overweight (OR: 1·61; 95 % CI: 1·27, 2·04); P = 0·001). In contrast, a higher percentage contribution of water consumption at dinner and dairy products and sugary drinks at the evening snack were negatively associated with overweight (OR: 0·67; OR: 0·61; and OR: 0·67, respectively). It is concluded that a higher percentage contribution of food groups in schoolchildren’s diet at dinner and evening snack is associated with overweight. However, further studies are recommended to assess food consumption in schoolchildren during dinner and evening snack meals for more conclusive findings.
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- © The Author(s), 2026. Published by Cambridge University Press on behalf of The Nutrition Society
References
Lee, EY & Yoon, KH (2018) Epidemic obesity in children and adolescents: risk factors and prevention. Front Med 12, 658–666.Google Scholar
Farias, EDS, Moreira, KFA, Santos, JPD, et al. (2020) Overweight and obesity: prevalence in children and adolescents in Northern Brazil. J Hum Growth Dev 30, 266–273.Google Scholar
Ministério da Saúde (2019) Atlas da Obesidade Infantil no Brasil (Atlas of Childhood Obesity in Brazil). Brasília: Ministério da Saúde.Google Scholar
Aggarwal, B & Jain, V (2018) Obesity in children: definition, etiology and approach. Indian J Pediatr 85, 463–471.Google Scholar
Flanagan, A, Bechtold, DA, Pot, GK, et al. (2020) Chrono-nutrition: from molecular and neuronal mechanisms to human epidemiology and timed feeding patterns. J Neurochem 157, 53–72.Google Scholar
Asher, G & Sassone-Corsi, P (2015) Time for food: the intimate interplay between nutrition, metabolism, and the circadian clock. Cell 161, 84–92.Google Scholar
Thompson, OM, Ballew, C, Resnicow, K, et al. (2006) Dietary pattern as a predictor of change in BMI z-score among girls. Int J Obes 30, 176–182.Google Scholar
Vilela, S, Oliveira, A, Severo, M, et al. (2019) Chrono-nutrition: the relationship between time-of-day energy and macronutrient intake and children’s body weight status. J Biol Rhythms 34, 332–342.Google Scholar
Venkatapoorna, CMK, Ayine, P, Selvaraju, V, et al. (2020) The relationship between obesity and sleep timing behavior, television exposure, and dinnertime among elementary school-age children. J Clin Sleep Med 16, 129–136.Google Scholar
Zou, M, Northstone, K, Perry, R, et al. (2022) The association between later eating rhythm and adiposity in children and adolescents: a systematic review and meta-analysis. Nutr Rev 80, 1459–1479.Google Scholar
Se, W & Guo, JL (2018) Childhood overweight and obesity: affecting factors, education and intervention. J Child Obes 3, 9.Google Scholar
Ministério da Saúde (2014) Guia Alimentar para a população brasileira (Food Guide for the Brazilian Population), 2ª ed. Brasília: Ministério da Saúde.Google Scholar
Brasil. Ministério da Saúde (2013) Política Nacional de Alimentação e Nutrição (National Food and Nutrition Policy) (Internet), 2ª ed. Brasília: Ministério da Saúde. https://bvsms.saude.gov.br/bvs/publicacoes/politica_nacional_alimentacao_nutricao.pdf
Google Scholar
Pereira, LJ, Vieira, FGK, Belchor, ALL, et al. (2023) Methodological aspects and characteristics of participants in the study on the prevalence of obesity in children and adolescents in Florianópolis, Southern Brazil, 2018–2019: EPOCA study. Ann Epidemiol 77, 13–23.Google Scholar
Instituto Brasileiro de Geografia e Estatística (2024) Florianópolis (SC) | Cidades e Estados IBGE (Brazilian Institute of Geography and Statistics. Florianópolis (SC) | Cities and States IBGE). https://www.ibge.gov.br/cidades-e-estados/sc/florianopolis.html (accessed 11 October 2024).Google Scholar
Corrêa, EN, Rossi, CE, Das Neves, J, et al. (2018) Utilization and environmental availability of food outlets and overweight/obesity among schoolchildren in a city in the south of Brazil. J Public Health 40, 106–113.Google Scholar
Luciano, AP, Benedet, J, De Abreu, LC, et al. (2013) Median ages at stages of sexual maturity and excess weight in school children. Reprod Health 10, 56.Google Scholar
Pereira, LJ, Hinnig, PDF, Di Pietro, PF, et al. (2020) Trends in food consumption of schoolchildren from 2nd to 5th grade: a panel data analysis. Rev Nutr 33, e190164.Google Scholar
Marfell-Jones, M, Stewart, A & Olds, T (2006) Kinanthropometry IX: Proceedings of the 9th International Conference of the International Society for the Advancement of Kinanthropometry. London: Taylor & Francis Group.Google Scholar
De Onis, M, Onyango, AW, Borghi, E, et al. (2007) Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ 85, 660–667.Google Scholar
World Health Organization (2009) WHO AnthroPlus for Personal Computers: Software for Assessing Growth of the World’s Children and Adolescents (Internet). Geneva: WHO. https://www.who.int/growthref/tools/en/
Google Scholar
Da Costa, FF, Schmoelz, CP, Davies, VF, et al. (2013) Assessment of diet and physical activity of Brazilian schoolchildren: usability testing of a web-based questionnaire. JMIR Res Protoc 2, e31.Google Scholar
Davies, VF, Kupek, E, De Assis, MA, et al. (2015) Validation of a web-based questionnaire to assess the dietary intake of Brazilian children aged 7–10 years. J Hum Nutr Diet 28, 93–102.Google Scholar
Jesus, GMD, Assis, MAAD, Kupek, E, et al. (2016) Avaliação da atividade física de escolares com um questionário via internet (Assessment of physical activity in schoolchildren using a web-based questionnaire). Rev Bras Med Esporte 22, 261–266.Google Scholar
Jesus, GMD, Assis, MAAD & Kupek, E (2017) Validade e reprodutibilidade de questionário baseado na Internet (Web-CAAFE) para avaliação do consumo alimentar de escolares de 7 a 15 anos (Validity and reproducibility of an Internet-based questionnaire (Web-CAAFE) for assessing the dietary intake of schoolchildren aged 7 to 15 years). Cad Saúde Pública 33, e00163016.Google Scholar
Perazi, FM, Kupek, E, Assis, MAAD, et al. (2020) Efeito do dia e do número de dias de aplicação na reprodutibilidade de um questionário de avaliação do consumo alimentar de escolares (Effect of the day and the number of days of application on the reproducibility of a questionnaire for assessing the dietary intake of schoolchildren). Rev Bras Epidemiol 23, e200084.Google Scholar
Shahid, A, Wilkinson, K, Marcu, S, et al. (2012) STOP, THAT and One Hundred Other Sleep Scales. New York: Springer. pp. 303–312.Google Scholar
Hirshkowitz, M, Whiton, K, Albert, SM, et al. (2015) National Sleep Foundation’s sleep time duration recommendations: methodology and results summary. Sleep Health 1, 40–43.Google Scholar
Butte, NF, Watson, KB, Ridley, K, et al. (2018) A youth compendium of physical activities: activity codes and metabolic intensities. Med Sci Sports Exerc 50, 246–256.Google Scholar
Cezimbra, VG, Assis, MAAD, De Oliveira, MT, et al. (2021) Meal and snack patterns of 7–13-year-old schoolchildren in southern Brazil. Public Health Nutr 24, 2542–2553.Google Scholar
Kupek, E, Lobo, AS, Leal, DB, et al. (2016) Dietary patterns associated with overweight and obesity among Brazilian schoolchildren: an approach based on the time-of-day of eating events. Br J Nutr 116, 1954–1965.Google Scholar
Taillie, LS, Afeiche, MC, Eldridge, AL, et al. (2015) Increased snacking and eating occasions are associated with higher energy intake among Mexican children aged 2–13 years. J Nutr 145, 2570–2577.Google Scholar
Roberto, DMT, Kupek, E, De Assis, MAA, et al. (2022) Most meal and snack patterns are stable over a 3-year period in schoolchildren in southern Brazil. Nutr Bull 47, 79–92.Google Scholar
Wang, D, Van Der Horst, K, Jacquier, E, et al. (2016) Snacking among US children: patterns differ by time of day. J Nutr Educ Behav 48, 369–375.e1.Google Scholar
Osei Bonsu, E & Addo, IY (2022) Prevalence and correlates of overweight and obesity among under-five children in Egypt. Front Public Health 10, 1067522.Google Scholar
Fogelholm, M, Anderssen, S, Gunnarsdottir, I, et al. (2012) Dietary macronutrients and food consumption as determinants of long-term weight change in adult populations: a systematic literature review. Food Nutr Res 56, 19103.Google Scholar
Vergnaud, AC, Norat, T, Romaguera, D, et al. (2010) Meat consumption and prospective weight change in participants of the EPIC-PANACEA study. Am J Clin Nutr 92, 398–407.Google Scholar
Mahdi, S, Dickerson, A, Infield Solar, G, et al. (2023) Timing of energy intake and BMI in children: differential impacts by age and sex. Br J Nutr 130, 71–82.Google Scholar
Jansen, EC, Peterson, KE, Lumeng, JC, et al. (2019) Associations between sleep and dietary patterns among low-income children attending preschool. J Acad Nutr Diet 119, 1176–1187.Google Scholar
Spaeth, AM, Hawley, NL, Raynor, HA, et al. (2019) Sleep, energy balance, and meal timing in school-aged children. Sleep Med 60, 139–144.Google Scholar
Garaulet, M & Gómez-Abellán, P (2014) Timing of food intake and obesity: a novel association. Physiol Behav 134, 44–50.Google Scholar
Moreno, LA, Bel-Serrat, S, Santaliestra-Pasías, A, et al. (2015) Dairy products, yogurt consumption, and cardiometabolic risk in children and adolescents. Nutr Rev 73, 8–14.Google Scholar
Feng, Y, Zhao, Y, Liu, J, et al. (2022) Consumption of dairy products and the risk of overweight or obesity, hypertension, and type 2 diabetes mellitus: a dose–response meta-analysis and systematic review of cohort studies. Adv Nutr 13, 2165–2179.Google Scholar
Lu, L, Xun, P, Wan, Y, et al. (2016) Long-term association between dairy consumption and risk of childhood obesity: a systematic review and meta-analysis of prospective cohort studies. Eur J Clin Nutr 70, 414–423.Google Scholar
Babio, N, Becerra-Tomás, N, Nishi, SK, et al. (2022) Total dairy consumption in relation to overweight and obesity in children and adolescents: a systematic review and meta-analysis. Obes Rev 23, e13400.Google Scholar
Muckelbauer, R, Libuda, L, Clausen, K, et al. (2009) Promotion and provision of drinking water in schools for overweight prevention: randomized, controlled cluster trial. Pediatrics 123, e661–e667.Google Scholar
Andersen, LBB, Arnberg, K, Trolle, E, et al. (2016) The effects of water and dairy drinks on dietary patterns in overweight adolescents. Int J Food Sci Nutr 67, 314–324.Google Scholar
Dubnov-Raz, G, Constantini, NW, Yariv, H, et al. (2011) Influence of water drinking on resting energy expenditure in overweight children. Int J Obes 35, 1295–1300.Google Scholar
Dubois, L, Farmer, A, Girard, M, et al. (2007) Regular sugar-sweetened beverage consumption between meals increases risk of overweight among preschool-aged children. J Am Diet Assoc 107, 924–934.Google Scholar
Bleich, SN & Vercammen, KA (2018) The negative impact of sugar-sweetened beverages on children’s health: an update of the literature. BMC Obes 5, 6.Google Scholar
Cedernaes, J, Waldeck, N & Bass, J (2019) Neurogenetic basis for circadian regulation of metabolism by the hypothalamus. Genes Dev 33, 1136–1158.Google Scholar
Henry, CJ, Kaur, B & Quek, RYC (2020) Chrononutrition in the management of diabetes. Nutr Diabetes 10, 6.Google Scholar
Jiang, P & Turek, FW (2017) Timing of meals: when is as critical as what and how much. Am J Physiol-Endocrinol Metab 312, E369–E380.Google Scholar
Morris, CJ, Aeschbach, D & Scheer, FAJL (2012) Circadian system, sleep and endocrinology. Mol Cell Endocrinol 349, 91–104.Google Scholar
Bo, S, Fadda, M, Castiglione, A, et al. (2015) Is the timing of caloric intake associated with variation in diet-induced thermogenesis and in the metabolic pattern? A randomized cross-over study. Int J Obes 39, 1689–1695.Google Scholar
Lobo, AS, De Assis, MAA, Leal, DB, et al. (2019) Empirically derived dietary patterns through latent profile analysis among Brazilian children and adolescents from Southern Brazil, 2013–2015. PLoS One 14, e0210425.Google Scholar
Vermohlem Garcia et al. supplementary material
Vermohlem Garcia et al. supplementary material
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