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Factors associated with meal quality among schoolchildren in three Brazilian cities

Published online by Cambridge University Press:  02 June 2025

Stella Lemke
Affiliation:
Federal University of Santa Catarina, Health Sciences Center, Nutrition Postgraduate Program, Florianópolis, Brazil
Dalton Francisco de Andrade
Affiliation:
Federal University of Santa Catarina, Informatics and Statistics Department, Florianópolis, Brazil
Patrícia de Fragas Hinnig
Affiliation:
Federal University of Santa Catarina, Health Sciences Center, Nutrition Postgraduate Program, Florianópolis, Brazil
Silvio Aparecido da Silva
Affiliation:
Federal Institute of Education, Science and Technology of Santa Catarina, Florianópolis, Brazil
Francilene Gracieli Kunradi Vieira
Affiliation:
Federal University of Santa Catarina, Health Sciences Center, Nutrition Postgraduate Program, Florianópolis, Brazil
Gilmar Mercês de Jesus
Affiliation:
State University of Feira de Santana, Feira de Santana, Brazil
Iris Emanueli Segura
Affiliation:
Public Health Faculty, University of São Paulo, São Paulo, Brazil
Betzabeth Slater
Affiliation:
Public Health Faculty, University of São Paulo, São Paulo, Brazil
Maria Alice Altenburg de Assis
Affiliation:
Federal University of Santa Catarina, Health Sciences Center, Nutrition Postgraduate Program, Florianópolis, Brazil
Patricia Faria Di Pietro*
Affiliation:
Federal University of Santa Catarina, Health Sciences Center, Nutrition Postgraduate Program, Florianópolis, Brazil
*
Corresponding author: Patricia Faria Di Pietro; Email: patricia.di.pietro@ufsc.br

Abstract

The purpose of this study was to measure meal quality in representative samples of schoolchildren in three cities located in different Brazilian regions using the Meal and Snack Assessment Quality (MESA) scale and examine association with weight status, socio-demographic characteristics and behavioural variables. This cross-sectional study analysed data on 5612 schoolchildren aged 7–12 years who resided in cities in Southern, Southeastern and Northeastern Brazil. Dietary intake was evaluated using the WebCAAFE questionnaire. Body weight and height were measured to calculate the BMI. Weight status was classified based on age- and sex-specific Z-scores. Meal quality was measured using the MESA scale. Associations of meal quality with weight status and socio-demographic and behavioural variables were investigated using multinomial regression analysis. Schoolchildren in Feira de Santana, São Paulo and Florianópolis had a predominance of healthy (41·8 %), mixed (44·4 %) and unhealthy (42·7 %) meal quality, respectively. There was no association with weight status. Schoolchildren living in Feira de Santana, those who reported weekday dietary intakes, and those with lower physical activity and screen activity scores showed higher meal quality. Schoolchildren aged 10–12 years, those who reported dietary intakes relative to weekend days, and those with higher screen activity scores exhibited lower meal quality.

Type
Research Article
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of The Nutrition Society

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References

Schwingshackl, L, Bogensberger, B & Hoffmann, G (2018) Diet quality as assessed by the healthy eating index, alternate healthy eating index, dietary approaches to stop hypertension score, and health outcomes: an updated systematic review and meta-analysis of cohort studies. J Acad Nutr Diet 118, 74100.Google Scholar
Monteiro, CA, Cannon, G, Lawrence, M, et al. (2019) Ultra-Processed Foods, Diet Quality, and Health Using the NOVA Classification System. Rome: FAO.Google Scholar
Pagliai, G, Dinu, M, Madarena, MP, et al. (2021) Consumption of ultra-processed foods and health status: a systematic review and meta-analysis. Br J Nutr 125, 308318.Google Scholar
Louzada, ML, Cruz, GL, Silva, KA, et al. (2023) Consumption of ultra-processed foods in Brazil: distribution and temporal evolution 2008–2018. Rev Saude Publica 57, 12.Google Scholar
Lacerda, AT, Carmo, AS, Sousa, TM, et al. (2020) Participation of ultra-processed foods in Brazilian school children’s diet and associated factors. Rev Paul Pediatr 38, 18.Google Scholar
Rauber, F, Campagnolo, PDB, Hoffman, DJ, et al. (2015) Consumption of ultra-processed food products and its effects on children’s lipid profiles: a longitudinal study. Nutr Metab Cardiovasc Dis 25, 116122.Google Scholar
Karnopp, EVN, dos Santos Vaz, J, Schafer, AA, et al. (2017) Food consumption of children younger than 6 years according to the degree of food processing. J Pediatr (Rio J) 93, 7078.Google Scholar
Cezimbra, VG, Assis, MAA, De Oliveira, MT, et al. (2020) Meal and snack patterns of 7–13-year-old schoolchildren in southern Brazil. Public Health Nutr 24, 25422553.Google Scholar
Instituto Brasileiro de Geografia e Estatística (2020) Pesquisa de Orçamentos Familiares 2017–2018: Avaliação Nutricional Da Disponibilidade Domiciliar de Alimentos No Brasil. (Household Budget Survey 2017–2018: Nutritional Analysis of Household Food Availability in Brazil). Rio de Janeiro: IBGE.Google Scholar
Ministério da Saúde (2014) Guia Alimentar Para a População Brasileira. (Dietary Guidelines for the Brazilian Population), 2a ed. Brasília: Ministério da Saúde.Google Scholar
Guan, VX, Probst, YC, Neale, EP, et al. (2018) Identifying usual food choices at meals in overweight and obese study volunteers: implications for dietary advice. Br J Nutr 120, 472480.Google Scholar
Leech, RM, Worsley, A, Timperio, A, et al. (2015) Understanding meal patterns: definitions, methodology and impact on nutrient intake and diet quality. Nutr Res Rev 28, 121.Google Scholar
Lemke, S, de Andrade, DF, de Fragas Hinnig, P, et al. (2024) Development and application of the Meal and Snack Assessment (MESA) quality scale for children and adolescents using item response theory. Nutr J 23, 114.Google Scholar
Davies, VF, Kupek, E, Assis, MAA, 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, 93102.Google Scholar
Perazi, FM, Kupek, E, Assis, MAA, et al. (2020) Effect of the day and the number of days of application on reproducibility of a questionnaire to assess the food intake in schoolchildren. Rev Bras Epidemiol 23, e200084.Google Scholar
Jesus, GM, Assis, MAA, 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 do Esporte 22, 261266.Google Scholar
Jesus, GM, Assis, MAA & 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) to evaluate the food consumption of students aged 7 to 15 years). Cad Saude Publica 33, e00163016.Google Scholar
Segura, IE (2019) Avaliação do estado nutricional e consumo alimentar de escolares da rede municipal de educação de São Paulo (Dissertação) (Assessment of Nutritional Status and Food Consumption of Schoolchildren in Municipal Public Schools of São Paulo). São Paulo Fac Saúde Pública da USP. 2019:111. –http://www.teses.usp.br/teses/disponiveis/6/6138/tde-30092019–142610/ (accessed June 2023).Google Scholar
de Jesus, GM, de Oliveira Araujo, RH, Dias, LA, et al. (2022) Attendance in physical education classes, sedentary behavior, and different forms of physical activity among schoolchildren: a cross-sectional study. BMC Public Health 22, 1461.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, 1323.Google Scholar
Monteiro, CA, Cannon, G, Moubarac, JC, et al. (2018) The UN Decade of Nutrition, the NOVA food classification and the trouble with ultra-processing. Public Health Nutr 21, 517.Google Scholar
Ridley, K, Ainsworth, BE & Olds, TS (2008) Development of a compendium of energy expenditures for youth. Int J Behav Nutr Phys Act 5, 45.Google Scholar
Lohman, T, Roche, A & Martorell, R (1988) Anthropometric Standardization Reference Manual. Champaign, IL: Human Kinetics.Google Scholar
WHO (2006) WHO Child Growth Standards: Length/Height-for-Age, Weight-for-Age, Weight-for-Length, Weight-for- Height and Body Mass Index-for-Age: Methods and Development. Geneva: WHO.Google Scholar
Food and Agriculture Organization of the United Nations (2019) World Health Organization. Sustainable Healthy Diets Guiding Principles. Rome: FAO, WHO.Google Scholar
dos Santos Costa, C, Steele, EM, de Faria, FR, et al. (2022) Score of ultra-processed food consumption and its association with sociodemographic factors in the Brazilian National Health Survey, 2019. Cad Saude Publica 38, 111.Google Scholar
Corrêa, RD, Vencato, PH, Rockett, FC, et al. (2017) Dietary patterns: are there differences between children and adolescents? Cien Saude Colet 22, 553562.Google Scholar
Golley, RK, Hendrie, GA & McNaughton, SA (2011) Scores on the Dietary Guideline Index for children and adolescents are associated with nutrient intake and socio-economic position but not adiposity. J Nutr 141, 13401347.Google Scholar
Pereira, LJ, Hinnig, PF, Pietro, PFD, et al. (2020) Trends in food consumption of schoolchildren from 2nd to 5th grade: a panel data analysis. Rev Nutr 33, e190164.Google Scholar
Elinder, LS, Heinemans, N, Zeebari, Z, et al. (2014) Longitudinal changes in health behaviours and body weight among Swedish school children - associations with age, gender and parental education - the SCIP school cohort. BMC Public Health 14, 19.Google Scholar
Svensson, Å, Larsson, C, Eiben, G, et al. (2014) European children’s sugar intake on weekdays v. weekends: the IDEFICS study. Eur J Clin Nutr 68, 822828.Google Scholar
McCarthy, S (2014) Weekly patterns, diet quality and energy balance. Physiol Behav 134, 5559.Google Scholar
Locatelli, NT, Canella, DS & Bandoni, DH (2018) Positive influence of school meals on food consumption in Brazil. Nutrition 53, 140144.Google Scholar
Horta, PM, Do Carmo, AS, Junior, EV, et al. (2019) Consuming school meals improves Brazilian children’s diets according to their social vulnerability risk. Public Health Nutr 22, 27142719.Google Scholar
Bento, BMA, Moreira, AD, Carmo, AS, et al. (2018) A higher number of school meals is associated with a less-processed diet. J Pediatr (Rio J) 94, 404409.Google Scholar
LeBlanc, AG, Katzmarzyk, PT, Barreira, TV, et al. (2015) Correlates of total sedentary time and screen time in 9–11 year-old children around the world: the international study of childhood obesity, lifestyle and the environment. PLoS One 10, 120.Google Scholar
Matias, TS, Silva, KS, Silva, JA, et al. (2018) Clustering of diet, physical activity, sedentary behavior among Brazilian adolescents in the national school – based health survey (PeNSE 2015). BMC Public Health 18, 1283.Google Scholar
Guerra, PH, de Farias Júnior, JC & Florindo, AA (2016) Sedentary behavior in Brazilian children and adolescents: a systematic review. Rev Saude Publica 50, 9.Google Scholar
Schrempft, S, van Jaarsveld, CHM, Fisher, A, et al. (2015) The obesogenic quality of the home environment: associations with diet, physical activity, TV viewing, and BMI in preschool children. PLoS One 10, 117.Google Scholar
Leech, RM, McNaughton, SA & Timperio, A (2014) The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review. Int J Behav Nutr Phys Act 11, 19. https://doi.org/10.1186/1479-5868-11-4 Google Scholar
Barros, AKC, de Jesus, GM, Vieira, GO, et al. (2023) Use of screens and intake of unhealthy food among children and adolescents: association with physical activity in a cross-sectional study. BMC Nutr 9, 19.Google Scholar
Cunha, DB, Costa, THM, Veiga, GV, et al. (2018) Ultra-processed food consumption and adiposity trajectories in a Brazilian cohort of adolescents: ELANA study. Nutr Diabetes 8, 28.Google Scholar
Thompson, FE, Kirkpatrick, SI, Subar, AF, et al. (2015) The National Cancer Institute’s dietary assessment primer: a resource for diet research. J Acad Nutr Diet 115, 19861995.Google Scholar