https://orcid.org/0000-0002-1927-4496
Figures
Abstract
Background
Consumption of ultra-processed foods and low dietary diversity are risk factors for chronic diseases.
Aim
To evaluate the association between food consumption and sedentary and unhealthy eating behaviors of Brazilian schoolchildren between 6 and 11 years old.
Methods
Cross-sectional study. A prevalence sample was calculated considering the number of children enrolled in elementary school. This sample was distributed proportionally to Brazil’s macro-regions and the type of school (public or private). The questionnaire was developed in Google Forms and disseminated through the snowball technique. The questionnaire was filled in by the children’s parents, with information about the child’s identification and health. Afterward, the child completed a questionnaire by her/himself. We used the previously validated Illustrated Questionnaire on Food Consumption for Brazilian Schoolchildren and the Illustrated Questionnaire on Eating and Sedentary Behaviors. Food consumption was analyzed using the NOVA score and the dietary diversity score. Poisson’s regression with robust variance was performed (p<0.05).
Results
The study included 2,021 dyads. Of these, 27.6% of children reported eating five or more ultra-processed foods and 39.0% four or fewer natural or staple foods the previous day. Using screens, proxy of sedentary behavior (Prevalence Ratio–PR = 1.8, Confidence Interval–CI95%1.2–2.8) and eating at irregular hours (PR = 1.6, CI95%1.2–2.2) were risk factors for high consumption of ultra-processed foods and low dietary diversity in schoolchildren. In addition, eating the three main meals on the previous day (PR = 0.6, CI95%0.4–0.8) was identified as protective factors against the consumption of ultra-processed foods and in favor of dietary diversity among schoolchildren.
Citation: Oliveira GAL, Santos Gonçalves VS, Nakano EY, Toral N (2024) Consumption of ultra-processed foods and low dietary diversity are associated with sedentary and unhealthy eating behaviors: A nationwide study with Brazilian Schoolchildren. PLoS ONE 19(1): e0294871. https://doi.org/10.1371/journal.pone.0294871
Editor: Flavia Mori Sarti, Universidade de Sao Paulo, BRAZIL
Received: July 28, 2023; Accepted: November 8, 2023; Published: January 12, 2024
Copyright: © 2024 Oliveira et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: NT Grant 2019/ 24063.93.31025.30052018 [Project No. 326 - Notice No. 03/2018], Distrito Federal Research Foundation (FAPDF). Link: https://www.fap.df.gov.br/ GALO Doctoral grant from the Coordination for the Improvement of Higher Education Personnel (CAPES). Link: https://www.gov.br/capes/pt-br The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Chronic diseases are a burden on the economy and the world’s leading causes of death and loss of quality of life [1]. In 2017, more than 2.1 billion children were affected by chronic diseases, and more than two-thirds of risk factors for chronic diseases emerged during childhood and adolescence [2]. The last Global Burden of Diseases showed that in 2019 non-communicable diseases killed equivalent to 22.5% of children 5–9 years globally and 44.4% in Brazil [3]. Non-communicable diseases, also known as chronic diseases, tend to have slow progress and long duration. They result from a combination of sociodemographic, genetic, physiological, environmental, medical conditions, and behavioral factors. Unhealthy diets and physical inactivity are modifiable behavioral risk factors that significantly contribute to the development of chronic diseases [4].
Dietary habits are formed during childhood and consolidated in adulthood [5]. A report by the Food and Agriculture Organization of the United Nations (FAO) shows the association between ultra-processed food consumption and the risk of various diet-related non-communicable diseases, such overweight/obesity [6]. In Brazil, primary healthcare data from the Food and Nutrition Surveillance System (SISVAN) in 2022 showed that 93% of children between 5 and 9 years of age had consumed ultra-processed foods on the day prior to the consultation. On the other hand, the prevalence of the consumption of natural or staple foods, such as beans, fruits, and vegetables, was 15%, 13%, and 79%, respectively [7].
Furthermore, children’s eating behaviors can be associated with risk factors for their health and habit formation [8]. The Dietary Guidelines for the Brazilian Population present some healthy eating behaviors such as eating regularly and mindfully, eating in appropriate environments, eating in company, and developing, exercising, and sharing culinary skills [9]. Eating behaviors reflect what and how children eat, and they are influenced by children’s eating patterns, taste preferences, appetite, psychosocial factors, as well as the level of physical activity [10].
Sedentary behavior is associated with poor health outcomes such as increased adiposity, poorer cardiometabolic health, and reduced sleep duration [11]. Sedentary behavior includes activities involving small movements during the day, and the most frequent in children is screen use. The WHO Guidelines on Physical Activity and Sedentary Behavior recommend that children should limit the amount of sedentary time, particularly the amount of recreational screen time [12].
So far, no comprehensive national studies have examined food consumption, eating and sedentary behaviors among schoolchildren or their interconnectedness. The association between food consumption and behaviors has already been evaluated in other audiences, such as adults [13,14], adolescents [15–19], university students [20], pregnant women [21], and early childhood children [22–24]. Consequently, our study aims to fill this gap by investigating the association between food consumption—emphasizing on the consumption of ultra-processed foods and dietary diversity—and sedentary and eating behaviors among Brazilian schoolchildren.
Methods
Study design
An online cross-sectional study was conducted as part of the Schoolchildren Nutrition Study (Estudo de Nutrição de Crianças Escolares–ENUCE in Portuguese). The project was approved by the Research Ethics Committee of the Faculty of Health Sciences at the University of Brasília (number 3,675,033 on October 31, 2019). The responsible and the children agreed to the Informed Consent Form.
Participants
The study population consisted of children in the elementary school grades, particularly the first to fifth grades, in public and private Brazilian schools.
A sample was calculated considering a population of 14,533,651 children, referring to the number of enrollments in these elementary school grades according to the 2021 National School Census [25]; a confidence level of 95%; a prevalence of ultra-processed food consumption of 89%, data from SISVAN in 2021 [7]; and a relative error of approximately 0.01%, totaling 2,019 children.
This sample value was distributed proportionally to Brazilian macro-regions and type of school (public and private), according to the population of the 2021 National School Census [25]. We considered adequacy 30% for more or less of the minimum calculated sample of each macro-region and type of school (Table 1).
Brazil, 2022.
All children between 6 and 11 years old enrolled in the first to fifth grades of Brazilian elementary schools with internet access were considered eligible for our study. The exclusion criteria were children with conditions that could make it difficult to complete the questionnaire, such as cerebral palsy, intellectual disability, microcephaly, hemiplegia, and Dunner syndrome. We also excluded children with eating difficulties or problems that could alter food consumption, such as food allergy or intolerance, Asper syndrome, Silver Russell syndrome, Hashimoto’s thyroid, diabetes, kidney disease, Ehler-Danlos, G6PD deficiency, irritable intestine syndrome, megacolon, adrenal hyperplasia, high ferritin, gastritis, and reflux. After data collection, we applied the inclusion and exclusion criteria to the database.
Study procedures
Our questionnaire was developed in Google Forms. Participants (parents and children) were recruited using the snowball sampling technique [26]. We selected all parents who had access to the questionnaire for the research. The access link to the questionnaire was published on the researchers’ social networks and sent by e-mail to state and municipal education departments, public and private schools, unions of education professionals, nutritionists’ councils, and councils of secretaries of education. The link was available from February to November 2022, when the minimum calculated sample was reached.
Initially, the questionnaire was filled in by the children’s parents, with information about the child’s identification and health. Afterward, the child completed a questionnaire by her/himself. The questionnaire guided the parents to avoid interfering with the children’s responses. The questionnaire was tested in a pilot study. The Dietary Guidelines for the Brazilian Population [9] was made available at the end of the questionnaire. In addition, participants received individual results and a booklet with guidelines on healthy eating, physical activity, and mental health in children written by the researchers. The schools that supported the dissemination of the study received collaboration certificates.
Measures
The first part of the questionnaire, filled in by the child’s parent, asked for information about the child, such as date of birth, location of residence, the type of school (public or private) that the child attends, and data about the child’s health (for exclusion criterion).
After the parent filled in the first part of the questionnaire, a recommendation was presented for the child to continue completing the form by her/himself. The child was asked to mark the meals he/she did yesterday and answer the Illustrated Questionnaire on Food Consumption for Brazilian Schoolchildren (QUACEB–Questionário Ilustrado de Consumo Alimentar para Crianças Escolares Brasileiras) and the Illustrated Questionnaire on Eating and Sedentary Behaviors (QUICAS–Questionário Ilustrado de Comportamentos alimentares e sedentários). The QUACEB is a validated questionnaire to investigate the food consumption of elementary schoolchildren between six and ten years of age. This questionnaire is a self-reported recall with 43 foods illustrated [27]. The QUICAS is a validated questionnaire to investigate the eating and sedentary behaviors on the previous day in schoolchildren seven to ten years old. It is an illustrated questionnaire with ten eating behaviors (referring to the act of eating without distractions, with company, on a regular basis, and participation in tasks involved in meal preparation) and five sedentary behaviors (related to the use of television, computer, tablet, cell phone, and video game) with four frequency options each (morning, afternoon, night, and never) [28].
Data analysis
Regarding food consumption obtained by the QUACEB application, we calculated the NOVA score and the dietary diversity score. The NOVA score was calculated from the sum of reported groups of ultra-processed foods: for each “yes” as an answer, the value 1 was assigned, and for the “no” answers, the value 0 was assigned. Therefore, the score ranged from 0 (none of the foods was consumed on the previous day) to 10 (at least one ultra-processed food from each of the 10 groups was consumed on the previous day) [29]. The same grouping of ultra-processed foods adopted in the original simplified instrument [30] was used in our study (Table 1). For the dietary diversity score, the list of foods adapted for the Brazilian population was used [30], based on the FAO indicator [31]. For the classification of the dietary diversity score, the value 1 was assigned for the presence of each of the 10 food groups: grains and tubers; legumes; meats; eggs; milk; dark green leafy vegetables; fruits and vegetables rich in vitamin A; light green leafy vegetables; other vegetables and other fruits (Table 2). This score was summed up, ranging from 0 to 10.
Brazil, 2022.
The scores were divided into quartiles. The highest risk group was the combination of high consumption of ultra-processed foods (fourth quartile) and low dietary diversity (first quartile).
The sedentary behaviors were classified as “acceptable screen” use behavior for those who reported using television, computer, tablet, cell phone, and video game in a single period (morning or afternoon, or night) or had not used them on the previous day; and “excessive screen” use behavior for those who reported using them (even if it was only one of the screens asked) in two or more periods in the previous day.
A descriptive analysis was performed. For categorical variables, the prevalence was calculated with a Confidence Interval (CI) of 95%. The Poisson regression model with robust variance estimation was performed to calculate the prevalence ratios (PRs) of behavioral variables associated with high consumption of ultra-processed food and low dietary diversity. Eating and sedentary behaviors were considered exposure variables, and food consumption on the previous day in quartiles was the outcome variable. Analyses were conducted both individually and in combination with exposure and outcome variables. A significance level of less 0.05 was considered. The association was adjusted for the variables of the Brazilian macro-region, type of school (proxy of socioeconomic status), gender, and age of the child. Analyses were performed using Stata software version 16.
Results
The questionnaire was answered by 2,206 people. Of these, 185 were excluded, including 25 responses whose parents had not agreed with the informed consent form; 2 duplicate responses from the same person; 13 children that had not agreed with the informed consent form; 78 children under 6 years and over 11 years old; 10 children with cognitive disorders; and 57 children with eating disorders.
Therefore, the study included 2,021 Brazilian children. According to the last National School Census [25], participants were distributed proportionally to Brazilian macro-regions and type of school (Table 3).
Brazil, 2022.
Most children were male (51.7%), and the mean age was 8 years old (Standard Deviation–SD = 1.5). The mean consumption of ultra-processed foods (NOVA score) on the previous day was approximately 3.5 groups (SD = 2.1) and the mean consumption of natural or staple foods (dietary diversity score) was 5.1 groups (SD = 2.1). Children in the last quartile of the NOVA score (27.6%) consumed five or more groups of ultra-processed foods, and children in the first quartile of the dietary diversity score (39.0%) consumed four or fewer groups of natural or staple foods. Regarding sedentary behavior, the majority of children (75.7%) used screens (such as tablets, cell phones, computers, televisions, or video games) in more than one period (morning, afternoon, or night) on the previous day. In general, children showed healthy eating behaviors but had a high prevalence of eating meals watching TV or using a cell phone (47.2%) and low participation in household activities involving meal preparation (34.2%) (Table 4). On average, children consumed four meals (SD = 1.0) on the previous day.
Brazil, 2022.
The prevalence of food consumption, according to the quartiles of the NOVA score and the dietary diversity score, by eating and sedentary behaviors are presented in Table 5.
Brazil, 2022.
High consumption of ultra-processed foods and low dietary diversity (4th quartile of the NOVA score and 1st quartile of the dietary diversity score) were associated with sedentary behavior of the screen use [Prevalence Ratio–PR = 2.21; p<0.01]; and with eating behaviors, such as eating while watching television or using a cell phone [PR = 1.71; p<0.01], eating alone [PR = 1.65; p = 0.02], eating at irregular times [PR = 1.97; p<0.01], but not participating in household activities involving meal preparation [PR = 1.53; p<0.01], consuming three main meals [PR = 0.56; p<0.01], and eating breakfast [PR = 0.67; p = 0.01] (Table 6).
Brazil, 2022.
The association between eating and sedentary behaviors and food consumption shown in Table 6 (crude analysis) was maintained after adjusting for the variables: type of school, macro-regions, gender, and age of the child (Table 7). Therefore, children who used screens excessively had a 115% greater chance of belonging to the higher risk group (higher consumption of ultra-processed foods and lower consumption of natural or staple foods) than those with acceptably used screens. Regarding eating behaviors, children who presented unhealthy behaviors, such as watching television or using cell phones during meals, eating alone, not eating at regular times, and not participating in household activities involving meal preparation, had 65%, 66%, 91%, and 53% greater chance, respectively, of belonging to the higher risk group (high consumption of ultra-processed foods and low consumption of natural or staple foods) than children who reported healthy eating behaviors on the previous day. Furthermore, children who consumed breakfast and consumed three main meals (breakfast, lunch, and dinner) had a lower chance for each of belonging to the group with high consumption of ultra-processed foods and low consumption of natural or staple foods (Table 7).
Brazil, 2022.
In the adjusted multiple Poisson regression, the models were found to be statistically significant (p<0.01). This indicates that at least some of the explanatory variables significantly predict the dependent variables. Specifically, using screens (as a proxy for sedentary behavior) [PR = 1.86; p<0.01], eating at irregular times [PR = 1.62; p<0.01], and consuming all three main meals on the previous day [PR = 0.59; p<0.01] maintained a statistically significant predictive effect in children who fell into the 4th quartile of the NOVA score and the 1st quartile of the dietary diversity score (Table 8).
Brazil, 2022.
Discussion
This is the first Brazilian online study in a nationwide sample that assessed the relationship between intake of ultra-processed and natural or staple foods with eating and sedentary behaviors on schoolchildren. We discovered an association between food consumption and eating and sedentary behaviors, similar to studies with adults [13,14], adolescents [15–19], and early childhood children [22–24].
In this study, approximately 10% of children were in the highest risk group, considered when children reported high consumption of ultra-processed foods (fourth quartile of the NOVA score) at the same time as low dietary diversity (first quartile of dietary diversity score). The last Household Budget Survey (POF), conducted in 2017–2018, indicated a decline in the availability of natural or minimally processed foods, as well as an increase in the percentage of ultra-processed foods in Brazilian homes [32], which may have affected the food consumption of Brazilian children.
This situation may have been aggravated after the COVID-19 pandemic. After the COVID-19 outbreak, there was a trend of decreasing dietary diversity among children in northern China. This could be related to food availability and lifestyle changes, particularly decreased household income [33]. Lockdown measures have had an impact on diet, inducing an increase in snacking, processed food consumption, and sedentary behavior in children [34]. In Brazil, studies with adults showed that during the period of social restriction, the practice of physical activity decreased, the time in front of screens increased, and the intake of ultra-processed foods increased [35]. In addition, there was an upward trend in the consumption of ultra-processed foods in less economically developed regions by people with less education [36]. We could predict similar effects among Brazilian children.
The consumption of ultra-processed foods harms the quality of the diet, in particular by increasing the energy density of the diet and the levels of sugar, saturated fat, and trans-fat while decreasing the levels of fiber and potassium [37]. On the other hand, the consumption of a diversified diet might raise nutrition levels and help prevent undernutrition, obesity, and non-communicable diseases [31]. A diet rich in fat, salt, and sugar and fewer vegetables and fruits was linked to worse cardiovascular risk markers in 9-year-old Portuguese school children from Lisbon [38]. Furthermore, greater diet diversity was negatively associated with airway inflammation among Portuguese children between 7 and 12 years old from Porto [39].
For dietary diversity, we found the mean consumption of natural or staple foods of 5.1 groups (SD = 2.1). In the West Region of Cameroon, the mean dietary diversity score of the pupils between 5 and 15 years of age was worse than 3.43 (SD = 1.02) (score range: 1–10) [40]. These data indicate that Brazilian children had a more diverse diet than children from other regions. Although 27.6% of the children in our study had a high consumption of ultra-processed foods on the previous day (fourth quartile), most Brazilian children (61.0%) also consumed natural or staple foods (second, third, and fourth quartile).
A positive characteristic in Brazil uncovered by the last Family Budget Survey (POF) was that half of the calories purchased by households came from fresh or minimally processed foods, thus indicating a predominance of food consumption patterns based on natural foods and culinary preparations [32]. This may be part of Brazilian food culture and/or a result of public policies, with emphasis on actions based on the Dietary Guideline for the Brazilian Population, whose golden rule recommends basing your diet on natural or minimally processed foods and avoiding ultra-processed foods [9]
Regarding sedentary behavior, excessive use of screens during childhood and adolescence has been associated with different health risks. Higher sedentary screen time was associated with a higher risk of metabolic syndrome in children 6–14 years of age in Beijing [41], with excessive weight in Chinese children and adolescents from 6 to 18 years old [42], and with overweight/obesity in 6–7-year-old Italian children [43]. Similarly, school-age children who spent more than 2 hours per day in sedentary activities or screen-based activities (tablet/computer/mobile phone use, watching TV, and video game use) were associated with unhealthy dietary habits, such as inadequate fruits and vegetables consumption, drinking sugary beverages daily, skipping breakfast, consuming carbonated drinks, consuming food in front of the television, and intake of at least one ultra-processed food per day [43–46].
Regarding eating behavior, we noted that approximately half of the children (47.2%) ate main meals (lunch or dinner) with distractions, watching TV, or using a cell phone. Similarly, the SISVAN indicates that 54% of children between 5 and 9 years old monitored in primary healthcare habitually eat their meals watching television [7]. Cell phones on the table and television sets turned on while eating can negatively affect health, with problems such as overeating (less attention to their food and consuming larger portions), poor digestion (chewing food less often, which can make it harder for their bodies to digest the food properly), and poor nutritional intake (choosing junk food or snacks that are high in calories, fat, and sugar, and less likely to eat fruits and vegetables) [9].
A positive finding of our study was that most children (93.9%) reported eating the main meals in company. Eating in company is recommended by the Dietary Guidelines for the Brazilian Population because meals eaten in company avoid eating quickly and favor more appropriate eating environments [9]. This warns against substituting consumption of traditional meals (seated at a table, with a plate, tableware, and with family or friends around) for ultra-processed foods that can be eaten while carrying out other activities (study/work) and in any space (desk, means of transport). Thus, it aims to reestablish the normative systems of dietary practices, which are considered protective against the consumption of ultra-processed foods [47]. In adolescents, eating meals with their parents and avoiding sedentary behaviors, such as watching television during meals, were found to be significantly associated with healthy behavior towards food consumption, this highlights the influence of the environment on individual choices [16,19].
Furthermore, most of the children in this study (85.3%) reported eating main meals at the usual and regular times. Beyond the quality of food, when we eat also plays a key role in health. The timing of the meals of the day could impact metabolism, glucose tolerance, obesity-related factors, and the circadian system. Therefore, eating at regular times could be an effective dietary strategy to prevent obesity, type 2 diabetes, and cardiovascular disease [48,49].
In contrast, a minority of children (34.2%) report participation in household activities involving meal preparation. Having culinary skills and the pleasure of cooking can reduce the consumption of ultra-processed foods, increase the consumption of fruits and vegetables, and reduce the risk of being overweight and obese [50]. A review of studies demonstrated improvement in children’s psychosocial outcomes, nutrition behavior, and food consumption after participating in hands-on meal preparation activities [51]. Another review identified improved overall dietary quality, increased consumption of fruits and vegetables, greater preference for vegetables, higher self-efficacy for cooking, and choosing healthy foods after involvement in-home meal preparation [52].
On the other hand, most of the children participating in this study (76.8%) consumed all three main meals (breakfast, lunch, and dinner) on the previous day. That is much more than observed by SISVAN, in which 16% of children between 5 and 9 years old had the habit of eating at least the three main meals [7]. This discrepancy may have been caused by the socioeconomic differences of the evaluated public. The Food Guide for the Brazilian Population recommends that individuals should consume three main meals daily. This is important to meet their nutritional requirements and to maintain a balanced and healthy diet [9]. Finnish children, ages 6–8, who ate three meals a day had smaller waist circumferences and a 63% lower risk of being overweight or obese than those who skipped some major meals [53]. Adolescents who had the habit of having three main meals a day (PR = 0.81; 95% CI 0.73;0.89 p < 0.05) and who consumed fresh fruit the previous day (PR = 0.91; 95% CI 0.84;0.98 p < 0.001) had a lower prevalence of obesity [54].
In addition, it was observed that 85.9% of schoolchildren consumed breakfast on the previous day. This result is similar to the findings of studies conducted in two different places in Brazil: the city of Florianopolis, where breakfast consumption was reported by 85% of the children with 7 to 13 years, and the state of Minas Gerais, where breakfast was consumed by 79.9% of children aged 8 and 9 years [55,56]. Breakfast consumption was inversely associated with ultra-processed dietary patterns [55]. Furthermore, skipping breakfast was associated with a more proinflammatory diet in school-age children, and there was significant interaction with sedentary behavior [56], reinforcing the importance of this meal in this stage of life.
We found that schoolchildren with unhealthy eating and sedentary behaviors (with excessive screen time use, with screens during meals, eating alone, not eating at regular times, not participating in household activities involving meal preparation, not consuming three main meals, or skipping breakfast) had a greater chance of belonging to the higher risk group (higher consumption of ultra-processed foods and lower consumption of natural or staple foods). This risk was identified regardless of the type of school, the macro-region, gender, or age of the child, and reached 91% and 115% for behaviors of eating at irregular times and for excessive screen use, respectively, showing the relevance of these behaviors on the quality of the diet in this stage of life, as described before. These results suggest that interventions aimed at promoting child health should not only focus on diet quality but also take behaviors into consideration.
Our study has some limitations. One of them is the use of a non-probabilistic sample; nonetheless, this study includes a sizable population proportionally from five geographic regions in Brazil. Another limitation includes data collected using a parent-guided online survey, although the study used validated tools and a pilot test was conducted before use among this population. In addition, the cross-sectional design of the study prevents the inference of causality in the observed associations; however, the cross-sectional design is a starting point for future longitudinal studies that will be able to perform more robust causal analyses. Finally, we tested associations considering only the previous day of food consumption. It would have been useful to consider the habit or eating frequency, as it may have been an atypical day in the child’s diet. However, this kind of questionnaire could not be filled in by the children themselves, because of their inability to correctly report the frequency of a complex behavior such as eating.
Conclusions
In conclusion, sedentary and unhealthy eating behaviors were associated with the consumption of ultra-processed foods and low dietary diversity in Brazilian schoolchildren. We suggest prioritizing strategies aimed at accessing a greater diversity of food groups and less ultra-processed foods. Additionally, we recommend that future studies focus on evaluating children at lower nutritional risk (those with low consumption of ultra-processed foods and high dietary diversity) to further understand the dynamics of their eating and sedentary behaviors. Furthermore, interventions for promoting healthy eating behaviors, such as eating without distractions from television or cell phones, eating in the company of others, adhering to regular mealtimes, and participating in activities involving meal preparation while discouraging screen use, may be useful to prevent negative consequences. This implies that interventions in clinical practice and public health policies should take a holistic approach to children’s health. This includes considering not only the quality of food consumption but also their eating and sedentary behaviors.
References
- 1. UNICEF. Programme guidance for early life prevention of non-communicable diseases. 2019.
- 2. Guariguata L, Jeyaseelan S. Children and non-communicable disease: Global Burden Report 2019. NCD CHILD. 2019.
- 3. IHME. Global Burden of Disease Study. In: Results [Internet]. 2019. Available: https://vizhub.healthdata.org/gbd-results/.
- 4. Budreviciute A, Damiati S, Sabir DK, Onder K, Schuller-Goetzburg P, Plakys G, et al. Management and prevention strategies for Non-communicable Diseases (NCDs) and their risk factors. Front Public Health. 2020;8: 1–11. pmid:33324597
- 5. Andueza N, Navas-Carretero S, Cuervo M. Effectiveness of nutritional strategies on improving the quality of diet of children from 6 to 12 years old: a systematic review. Nutrients. 2022;14: 1–17. pmid:35057552
- 6. Monteiro CA, Cannon G, Lawrence M, Louzada ML da C, Machado PP. Ultra-processed foods, diet quality, and health using the NOVA classification system. 2019. p. 48.
- 7.
Brasil. Sistema de Vigilância Alimentar e Nutricional—SISVAN Web: relatório de acesso público do consumo alimentar. In: Secretaria de Atenção Primária à Saúde, Ministério da Saúde [Internet]. 2023 [cited 18 Jan 2022]. Available: https://sisaps.saude.gov.br/sisvan/relatoriopublico/index.
- 8. Klotz-Silva J, Prado SD, Seixas CM. Comportamento alimentar no campo da Alimentação e Nutrição: do que estamos falando? Physis: Revista de Saúde Coletiva. 2016;26: 1103–1123.
- 9.
Brasil. Guia alimentar para a população brasileira. Brasília: Ministério da Saúde; 2014. p. 156 p.
- 10. UNICEF. Food Systems for Children and Adolescents: working together to secure nutritious diets. 2018; 12.
- 11. WHO. Who guidelines on physical activity and sedentary behaviour. 2020.
- 12. Azabdaftari F, Jafarpour P, Asghari-Jafarabadi M, Shokrvash B, Reyhani P. Unrestricted prevalence of sedentary behaviors from early childhood. BMC Public Health. 2020;20: 1–11. pmid:32075605
- 13. Shinozaki N, Murakami K, Masayasu S, Sasaki S. Highly processed food consumption and its association with anthropometric, sociodemographic, and behavioral characteristics in a nationwide sample of 2742 Japanese adults: an analysis based on 8-day weighed dietary records. Nutrients. 2023;15. pmid:36904297
- 14. Andrade GC, Julia C, Deschamps V, Srour B, Hercberg S, Kesse-Guyot E, et al. Consumption of ultra-processed food and its association with sociodemographic characteristics and diet quality in a representative sample of French adults. Nutrients. 2021;13: 1–14. pmid:33672720
- 15. Azeredo CM, De Rezende LFM, Canella DS, Moreira Claro R, De Castro IRR, Luiz ODC, et al. Dietary intake of Brazilian adolescents. Public Health Nutr. 2015;18: 1215–1224. pmid:25089589
- 16. Haddad MR, Sarti FM. Sociodemographic determinants of health behaviors among Brazilian adolescents: Trends in physical activity and food consumption, 2009–2015. Appetite. 2020;144. pmid:31521768
- 17. Silva RMA, de Souza Andrade AC, Caiaffa WT, de Medeiros DS, Bezerra VM. National Adolescent School-based Health Survey—PeNSE 2015: Sedentary behavior and its correlates. PLoS One. 2020;15. pmid:31999792
- 18. Gonçalves HVB, Batista LS, de Amorim ALB, Bandoni DH. Association between Consumption of Ultra-Processed Foods and Sociodemographic Characteristics in Brazilian Adolescents. Nutrients. 2023;15. pmid:37432151
- 19. Haddad MR, Sarti FM, Nishijima M. Association between selected individual and environmental characteristics in relation to health behavior of Brazilian adolescents. Eating and Weight Disorders. 2021;26: 331–343. pmid:32026377
- 20. Detopoulou P, Dedes V, Syka D, Tzirogiannis K, Panoutsopoulos GI. Relation of minimally processed foods and ultra-processed foods with the mediterranean diet score, time-related meal patterns and waist circumference: rResults from a cross-sectional study in university students. Int J Environ Res Public Health. 2023;20: 1–16. pmid:36833504
- 21. Pereira MT, Cattafesta M, Santos Neto ET dos, Salaroli LB. Maternal and sociodemographic factors influence the consumption of ultraprocessed and minimally-processed foods in pregnant women. Rev Bras Ginecol Obstet. 2020;42: 380–389.
- 22. Cainelli EC, Gondinho BVC, Palacio D da C, Oliveira DB de, Reis RA, Cortellazzi KL, et al. Consumo de alimentos ultraprocessados por crianças e fatores socioeconômicos e demográficos associados. Einstein. 2021;19: 1–8.
- 23. Batalha MA, França AKTDC, da Conceição SIO, dos Santos AM, Silva F de S, Padilha LL, et al. Consumo de alimentos processados e ultraprocessados e fatores associados em crianças entre 13 e 35 meses de idade. Cad Saúde Pública. 2017;33: 1–16. pmid:29166483
- 24. Pereira AM, Buffarini R, Domingues MR, Barros FCLF, Silveira MF da. Ultra-processed food consumption by children from a Pelotas Birth Cohort. Rev Saude Publica. 2022;56: 79. pmid:36043657
- 25.
BRASIL. Censo Escolar da Educação básica 2021: notas estatísticas. Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira. 2022; 38.
- 26. Biernacki P, Waldorf D. Snowball sampling: problems and techniques of chain referral sampling. Sociol Methods Res. 1981;10: 141–163.
- 27. Oliveira GAL, Barrio DOL, Araújo GS, Saldanha MP, Schincaglia RM, Gubert MB, et al. Validation of the illustrated questionnaire on food consumption for Brazilian schoolchildren (QUACEB) for 6- to 10-year-old children. Front Public Health. 2023;11. pmid:37808993
- 28. Oliveira GAL, Saldanha MP, Araújo GS, Barrio DOL, Gubert MB, Toral N. Validation of the illustrated questionnaire on eating and sedentary behaviors (QUICAS) for seven to ten-year-old children. Appetite. 2023;180: 1–10. pmid:36332848
- 29. Costa C dos S, Faria FR de, Gabe KT, Sattamini IF, Khandpur N, Leite FHM, et al. Escore Nova de consumo de alimentos ultraprocessados: descrição e avaliação de desempenho no Brasil. Rev Saúde Pública. 2021;55: 1–10. pmid:33886951
- 30. Sattamini IF. Instrumentos de avaliação da qualidade de dietas: desenvolvimento, adaptação e validação no Brasil. 2019.
- 31. FAO. Dietary Assessment: a resource guide to method selection and application in low resource settings. 2018.
- 32.
IBGE. Pesquisa de Orçamentos Familiares 2017–2018: avaliação nutricional da disponibilidade domiciliar de alimentos no Brasil. Instituto Brasileiro de Geografia e Estatística. 2019.
- 33. Cui Y, Si W, Zhao Q, Glauben T, Feng X. The impact of COVID-19 on the dietary diversity of children and adolescents: evidence from a rural/urban panel study. China and World Economy. 2021;29: 53–72.
- 34. Cena H, Fiechtner L, Vincenti A, Magenes VC, De Giuseppe R, Manuelli M, et al. Covid 19 pandemic as risk factors for excessive weight gain in pediatrics: The role of changes in nutrition behavior. a narrative review. Nutrients. 2021;13: 1–20. pmid:34959805
- 35. Malta DC, Szwarcwald CL, Barros MB de A, Gomes CS, Machado ÍE, Souza Júnior PRB de, et al. A pandemia da COVID-19 e as mudanças no estilo de vida dos brasileiros adultos: um estudo transversal, 2020. Epidemiol Serv Saude. 2020;29: e2020407. pmid:32997069
- 36. Steele EM, Rauber F, Costa C dos S, Leite MA, Gabe KT, Louzada ML da C, et al. Dietary changes in the NutriNet Brasil cohort during the covid-19 pandemic TT—Mudanças alimentares na coorte NutriNet Brasil durante a pandemia de covid-19. Rev saúde pública (Online). 2020;54: 91.
- 37. Gibney MJ. Ultra-processed foods: definitions and policy issues. Curr Dev Nutr. 2019;3: 1–7. pmid:30820487
- 38. Mascarenhas P, Furtado JM, Almeida SM, Ferraz ME, Ferraz FP, Oliveira P. Pediatric Overweight, Fatness and Risk for Dyslipidemia Are Related to Diet: A Cross-Sectional Study in 9-year-old Children. Nutrients. 2023;15: 1–14. pmid:36678200
- 39. de Castro‐Mendes F, Cunha P, Paciência I, Rufo JC, Farraia M, Silva D, et al. The influence of eating at home on dietary diversity and airway inflammation in Portuguese school‐aged children. Int J Environ Res Public Health. 2021;18: 1–15. pmid:33808006
- 40. Boh NM, Aba ER, Lemfor CB. Dietary practices and nutrient intake of internally displaced school children in the West region of Cameroon. Int J Food Sci. 2023;2023. pmid:36852392
- 41. Yin N, Yu X, Wang F, Yu Y, Wen J, Guo D, et al. Self-Reported Sedentary Behavior and Metabolic Syndrome among Children Aged 6–14 Years in Beijing, China. Nutrients. 2022;14: 1–12. pmid:35565836
- 42. Su Y, Li X, Li H, Xu J, Xiang M. Association between Sedentary Behavior during Leisure Time and Excessive Weight in Chinese Children, Adolescents, and Adults. Nutrients 2023, 2023;15: 1–12. pmid:36678295
- 43. Paduano S, Greco A, Borsari L, Salvia C, Tancredi S, Pinca J, et al. Physical and sedentary activities and childhood overweight/obesity: A cross-sectional study among first-year children of primary schools in Modena, Italy. Int J Environ Res Public Health. 2021;18: 1–13. pmid:33804662
- 44. Soltero EG, Jáuregui A, Hernandez E, Barquera S, Jáuregui E, Taylor JLY, et al. Associations between screen-based activities, physical activity, and dietary habits in Mexican schoolchildren. Int J Environ Res Public Health. 2021;18: 1–10. pmid:34202680
- 45. Viola PC de AF, Ribeiro SAV, Carvalho RRS de, Andreoli CS, Novaes JF de, Priore SE, et al. Situação socioeconômica, tempo de tela e de permanência na escola e o consumo alimentar de crianças. Cien Saude Colet. 2023;28: 257–267. pmid:36629570
- 46. Fontes PA dos S de, Siqueira JH, Martins HX, Oliosa PR, Zaniqueli D, Mill JG, et al. Comportamento sedentário, hábitos alimentares e risco cardiometabólico em crianças e adolescentes fisicamente ativos. Arq Bras Cardiol. 2023;120: 1–9.
- 47. Oliveira MS da S, Santos LA da S. Dietary guidelines for Brazilian population: An analysis from the cultural and social dimensions of food. Ciência e Saúde Coletiva. 2020;25: 2519–2528. pmid:32667536
- 48. Lopez-Minguez J, Gómez-Abellán P, Garaulet M. Timing of breakfast, lunch, and dinner. Effects on obesity and metabolic risk. Nutrients. 2019;11: 1–15. pmid:31684003
- 49. Manoogian ENC, Chaix A, Panda S. When to Eat: the importance of eating patterns in health and disease. J Biol Rhythms. 2019;34: 579–581. pmid:31813351
- 50. Mills S, White M, Brown H, Wrieden W, Kwasnicka D, Halligan J, et al. Health and social determinants and outcomes of home cooking: A systematic review of observational studies. Appetite. 2017;111: 116134. pmid:28024883
- 51. Ng CM, Kaur S, Koo HC, Mukhtar F. Involvement of children in hands-on meal preparation and the associated nutrition outcomes: A scoping review. Journal of Human Nutrition and Dietetics. 2021;35: 350–362. pmid:33938062
- 52. Quelly SB. Helping with Meal Preparation and Children’s Dietary Intake: A Literature Review. Journal of School Nursing. 2019;35: 51–60. pmid:29895188
- 53. Eloranta A-M, Lindi V, Schwab U, Tompuri T, Kiiskinen S, Lakka H-M, et al. Dietary factors associated with overweight and body adiposity in Finnish children aged 6–8 years: the PANIC Study. Int J Obes. 2012;36: 950–955.
- 54. Alves RL, Toral N, Gonçalves VSS. Individual and Socioeconomic Contextual Factors Associated with Obesity in Brazilian Adolescents: VigiNUTRI Brasil. Int J Environ Res Public Health. 2023;20. pmid:36612753
- 55. Belchor ALL, de Assis MAA, Cezimbra VG, Pereira LJ, Roberto DMT, Giacomelli S de C, et al. Is breakfast consumption among Brazilian schoolchildren associated with an ultra-processed food dietary pattern? Nutr Bull. 2022;47: 488–500. pmid:36317890
- 56. Suhett LG, Lopes LJ, Silva MA, Ribeiro SAV, Hermsdorff HM, Shivappa N, et al. Interaction effect between breakfast skipping and sedentary behavior in the dietary inflammatory potential of Brazilian school-age children. Nutrition. 2022;102: 1–6. pmid:35841808