Open-access Association between screen use at night, food consumption at dinner, and evening snack in schoolchildren aged 7 to 14 years with and without overweight, Florianópolis, Santa Catarina, Brazil

Associação entre o uso de tela no período noturno e consumo alimentar no jantar e lanche da noite em escolares de 7 a 14 anos com e sem sobrepeso, Florianópolis, Santa Catarina, Brasil

ABSTRACT

Objective   Analyze the association between screen use at night, food consumption at dinner, and evening snack in schoolchildren with and without overweight.

Methods   Cross-sectional study with a probabilistic sample of 1396 schoolchildren from 7 to 14 years of age from public and private schools of Florianópolis, Santa Catarina, Brazil. Dietary intake and frequency of screen use of the previous day were obtained through the questionnaire Consumo Alimentar e Atividades Físicas de Escolares (Food Consumption and Physical Activities of Schoolchildren). The association between screen use at night (exposure) and consumption of food groups (outcome) according to weight status was assessed using multivariate logistic regression.

Results   At dinner, schoolchildren without overweight who used screens once had a lower chance of consuming fruits and vegetables (OR: 0.62, p=0.017) compared to those who did not use screens. In addition, those who used screens twice were more likely to consume sweets (OR: 2.01, p=0.002), and screen use three times or more was inversely associated with beans (OR: 0.24, p=0.003) and meat, eggs, and seafood (OR: 0.35, p=0.011) consumption. Overweight schoolchildren who used screens three times or more were more likely to consume ultra-processed foods and pizza/hamburger/hot dogs (OR: 2.51, p=0.009). For the evening snack, it was observed that schoolchildren without overweight who used screens three times or more had a greater chance of consuming ultra-processed foods and pizza/hamburger/hot dogs (OR: 8.26; p=0.016).

Conclusion   Overweight and non-overweight schoolchildren who used screens were more likely to consume ultra-processed foods. Schoolchildren without overweight and who use screens more often at night are less likely to consume healthy foods.

Keywords: Children; Dinner; Food consumption; Screen time; Snacks

RESUMO

Objetivo   Analisar a associação entre o uso de dispositivo de tela no período noturno, o consumo alimentar no jantar e lanche da noite em escolares com e sem sobrepeso.

Métodos   Estudo transversal com uma amostra probabilística de 1.396 escolares de 7 a 14 anos de idade de escolas públicas e privadas de Florianópolis, Santa Catarina, Brasil. O consumo alimentar e a frequência de uso de dispositivos de telas do dia anterior foram obtidas por meio do questionário Consumo Alimentar e Atividades Físicas de Escolares. A associação entre o uso de dispositivo de tela no período noturno (exposição) e o consumo alimentar (desfecho) foi verificada por meio de regressão logística.

Resultados   No jantar, os escolares sem sobrepeso que utilizaram dispositivo de tela uma vez tiveram menor chance de consumir frutas, verduras e legumes (OR: 0,62, p=0,017) comparado com aqueles que não usaram dispositivos de telas. Além disso, aqueles que usaram dispositivo de tela duas vezes, tiveram maior chance de consumir doces (OR: 2,01, p=0,002) e a utilização de dispositivo de tela três vezes ou mais foi inversamente associado ao consumo de feijão (OR: 0,24, p=0.003), carnes, ovos e peixes (OR: 0,35, p=0,011). Os escolares com sobrepeso que utilizaram dispositivo de tela três vezes ou mais tiveram maior chance de consumirem ultraprocessados e lanches tipo pizza/hambúrguer/cachorro-quente (OR: 2,51, p=0,009). No lanche da noite, observou-se que os escolares sem sobrepeso que utilizaram dispositivo de tela três vezes ou mais, tiveram maior chance de consumir ultraprocessados e lanches (OR: 8,26; p=0,016).

Conclusão   Os escolares com e sem sobrepeso que utilizaram dispositivo de tela tiveram mais chances de consumir alimentos ultraprocessados. Os escolares sem sobrepeso que utilizam dispositivo de tela mais vezes a noite possuem menor chance de consumir alimentos saudáveis.

Palavras-chave: Crianças; Jantar; Consumo alimentar; Tempo de tela; Lanches

INTRODUCTION

Increased screen time (characterized as the use of mobile phones, tablets, video games, and television [1]) is associated with an increased risk for the development of overweight and obesity in children and adolescents [2]. This association can be explained by replacing activities with higher energy expenditure by sedentary behavior [3] and by the greater consumption of high-calorie density foods such as ultra-processed foods [3,4]. The Brazilian Society of Pediatrics recommends avoiding exposure to screen devices for children under two years of age, limiting screen time for children between two and five years of age to one hour daily, for children between six and ten years of age to 1-2 hours, and for children and adolescents between 11 and 18 years of age to 2-3 hours per day. In addition, it recommends that screens not be used during meals [5]. However, a survey conducted in 2022 with 1,745 parents of Brazilian children up to 12 years old identified that 44% of children owned a mobile phone/smartphone, 35% use their parents' mobile phone, and children spend an average of four hours a day using the device [6].

The survey on Internet Use by children and adolescents in Brazil (TIC Kids Online Brazil 2021) conducted with 2,651 Brazilian children and adolescents aged nine to 17 years showed an increase in internet users (93% in 2021 compared to 89% in 2019). The primary device used for internet access was the mobile phone (93%), with 84% of children and adolescents watching videos, series, and movies and 78% using social media. The survey also reveals that 57% of users reported seeing videos, photos, or texts that showed publicity or advertisements for foods, drinks, and sweets [7]. It should be noted that the impact of food marketing through social media is still unknown [8].

Evidence suggests the importance of the time of day when food is consumed for body weight regulation [9-11]. In this sense, a higher percentage of energy consumption at night has been positively associated with increased risk for overweight and obesity in children and adolescents [12,13]. Studies have identified the association between higher consumption of ultra-processed foods and children and adolescents' use of cell phones, tablets, video games, and television [14-16]. The foods generally purchased ready-to-eat or quickly prepared claim convenience and practicality, although they have low nutritional quality and a large amount of fats, added sugar, and sodium [17]. Screen devices serve food advertisements, mostly of ultra-processed foods [18], stimulating its acquisition and consumption by children and adolescents. The consumption of these foods is associated with a higher risk of developing overweight and obesity and other chronic Non-Communicable Diseases [17]. Data on food consumption at nighttime meals, such as dinner and evening snack, are scarce in children and adolescents. Cezimbra et al. (2020) identified meal and snack patterns in schoolchildren aged seven to 13 who attended the public school system in a capital in southern Brazil. The main dinner pattern was described as 'traditional Brazilian', consisting of rice, beans, beef/poultry, manioc flour, eggs, vegetables and green leaves. In addition, the authors identified an “unhealthy" pattern for the first evening snack pattern, which was composed of pizza/hamburger/hot dog, chips, sodas, cake, and fruit juices [19]. In Florianópolis, cross-sectional surveys of the Estudo da Prevalência e da Obesidade em Crianças e Adolescentes de Florianópolis (EPOCA, Study on the Prevalence of Obesity in Children and Adolescents of Florianópolis) aiming to monitor the trend in the prevalence of overweight and obesity and their associated factors in schoolchildren between seven to 14 years of age have been conducted since 2002. An increase in the prevalence of overweight, including obesity, was identified, being 30.3% in 2002, 34.4% in 2007 [20], and 34.2% in 2012 [21]. Although the 2018/2019 panel identified a prevalence of 33.7% [22], this percentage is still high. Studies investigated the association of overweight and obesity with food consumption [23], birth weight [24], age at menarche [25], breastfeeding [26], aspects of the built environment [27], physical activity, and socioeconomic factors [28]. Pinho et al. (2017) investigated the association between screen time and dietary patterns with overweight among adolescents aged 11 to 14 who participated in the EPOCA survey in 2012. It was identified that 39.1% of adolescents performed screen activities three times or more, lasting two hours or more daily [29]. Although this study found no association between screen time and overweight/obesity, other studies have shown that longer screen time is associated with a higher prevalence of overweight and obesity in children and adolescents [30]. Thus, this study aims to evaluate the association between screen use at night, food consumption at dinner, and evening snack in schoolchildren aged 7 to 14 years with and without overweight in Florianópolis, Santa Catarina.

METHODS

This is a cross-sectional study, inserted in the EPOCA study whose objective is to analyze the prevalence of obesity and associated factors in schoolchildren aged 7 to 14 years in the municipality of Florianópolis, Santa Catarina [22].

We used information from the school census for schoolchildren aged 7 to 14 enrolled in elementary school in public and private schools to calculate the sample [31]. The final sample size considered a prevalence of overweight, including obesity of 39% [32], margin of error of 3.5%, 95% confidence interval (CI), and design effect of 1.8. The sample size was doubled to allow comparisons with previous surveys and increased by 10% for possible losses and refusals, resulting in 2,891 schoolchildren. The sampling procedure was previously described by Pereira et al. (2023) [22]. A team of trained researchers collected data from 30 randomly selected schools representative of the five regions of Florianópolis (North, South, East, Center, and Continent), 19 of which were public and 11 private, taking place between November 2018 and December 2019.

The participants were schoolchildren enrolled between the 2nd and 9th grades. The inclusion criteria were students aged seven to 14 bearing a Free and Informed Consent Form signed by the parents or guardians and the Free and Informed Acceptance Form signed by the schoolchild. The research protocol was submitted to the Human Research Ethics Committee of the Universidade Federal de Santa Catarina (protocol number 7539718.1.0000.0121). A total of 1,691 schoolchildren were included in the study, of which 188 were excluded from the database due to the absence of food consumption data and 87 for presenting implausible dietary data (consumption of less than three food items per day or consumption of a number of items greater than the mean +3 standard deviations, [23]). Only schoolchildren who consumed at least one food item (except for water) at dinner and in the evening snack were considered for this study, totaling 1,273 and 647 schoolchildren, respectively.

Data on dietary intake and screen use activities were obtained through the Consumo Alimentar e Atividade Física de Escolares (Web-CAAFE, Food Intake and Physical Activities of Schoolchildren) online questionnaire developed for schoolchildren of the municipal school system of Florianópolis. This instrument aims to obtain data concerning the previous day and has been subjected to reproducibility, usability, and validity tests [33-36]. Web-CAAFE does not provide quantification of the amount of food consumed or the time spent on screen activities since it was developed considering the cognitive development of children aged seven to ten years [37]. Thus, the instrument allows us to identify markers of healthy and unhealthy eating and the performance of physical activities and sedentary behavior through daily frequency. Data were collected on school days (Monday to Friday), making it possible to obtain data from Sunday, representing the weekend. The Web-CAAFE begins with a registration section, followed by a section on food intake and another on physical activities and sedentary behaviors. The food intake section is divided into three meals and three snacks ordered chronologically (breakfast, mid-morning snack, lunch, mid-afternoon snack, dinner, and evening snack), presenting icons of 31 food items for each eating event. Therefore, the student can select rice, vegetables, green leaves, vegetable soup, beans, manioc flour, pasta, instant noodles, French fries, beef/poultry, eggs, fish/seafood, maize/potatoes, sausage, breakfast cereal, fruits, bread, cheese bread, cake without icing, cheese, coffee with milk, milk, yogurt, chocolate milk, fruit juices, cream cookies, soda, sweets (chocolate bars, ice cream, candies, cake with icing), chips, pizza/hamburger/hot dog, and water [36].

The food items selected for dinner and evening snack were considered according to the instructions provided by the avatar “cafito”. For dinner, “[...] is the main meal we make at night”, and for the evening snack, “[...] is what you ate after dinner and before bed”. Web-CAAFE does not specify the time in hours of these meals. Dinner and the evening snack were considered when the schoolchild included at least one food item, except for water. The selected items were grouped into seven food groups considering nutritional similarity, groups proposed by the Brazilian Dietary Guidelines [38], and the use of this classification in previous studies [39,40]. The food groups were: Dairy Products (Milk, coffee with milk, yogurt, and cheese); Cereals (bread, cake without icing, manioc flour, maize/potatoes, pasta, rice, breakfast cereal, and cheese bread); Beans; Meats, eggs, and seafood (meat/poultry, egg, fish/seafood); Fruits, and vegetables (fruits, legumes, green leaves, and vegetable soup); Sweets (chocolate milk, cream cookies, soda, fruit juice, and chocolate/candy/lollipop/ice cream/cake with icing); and Ultra-processed foods (instant noodles, French fries, sausage, chips, and pizza/hamburger/hot dog). The frequency of consumption greater than 5% of each food group at each meal was considered for this study [41]. Thus, the group of beans and meat, eggs, and seafood were excluded since they had a frequency of consumption of less than 5% in the evening snack.

The physical activities and sedentary behaviors section of Web-CAAFE is divided into three times of day (morning, afternoon, and evening) and presents 32 types of activities, including four screen-use activities at each time: watching television, using the computer, using the cell phone/tablet, and playing video games. For this study, frequency of screen use at night was considered and classified into the following categories: does not use; uses once; uses twice; uses three times or more [42]. Thus, the child selecting the item "television" at night is counted as one use. If the child selects one more item like "computer”, it will be counted as two uses.

Data on age, gender, and school shift were obtained from a list provided by the schools. Weight and height were measured by a previously trained team following standardized procedures [43]. Body weight was collected using an electronic scale with a capacity of 200 kg and an accuracy of 50 g (Marte brand, model LC 200 PP). Height was measured using a portable stadiometer fixed to the wall (Alturexata® brand), with a zero point at ground level and a scale of 1 mm. The schoolchildren were classified according to BMI z-score for age, referencing the growth curves from 5 to 19 years of the WHO of 2007, adopting the following criteria for the weight status classification: overweight (including obesity) z-score ≥ +1 and non-overweight z-score < +1 [44].

The association between screen use at night and consumption of food groups at dinner and evening snack was verified through logistic regression stratified by weight status (non-overweight and overweight including obesity). The consumption of the food group (yes or no) was considered as a dependent variable, and the frequency of screen use at night (does not use; uses once; uses twice; uses three times or more) adjusted for gender, age (7 to 10 years and 11 to 14 years), type of school (public and private), and day of consumption report (weekday or weekend) were considered independent variables. All variables were entered simultaneously, and a statistical significance level of p<0.05 was considered for statistical decision. The statistical program Stata 16.0 was used for analyses. The Stata command “svy" was used due to the type of sampling.

RESULTS

The total sample consisted of 1,396 schoolchildren aged seven to 14 from Florianópolis. Table 1 presents the sample characteristics. Most schoolchildren were female (53.5%), aged 7 to 10 years (57.9%), and attended public schools (59.9%). The highest number of reports occurred on weekdays (87.6%). It was observed that 36.8% of the schoolchildren did not use a screen, 36.6% used a screen once at night, and the most used device was the cell phone/tablet (41.2%). Concerning dinner, 92.2% of the students ate the meal, and 43.3% consumed the evening snack. The highest proportion among overweight children was 7 and 10 years old (59.3%), and among schoolchildren with non-overweight, the highest proportion was female (58.5%).

Table 1 -
Description of the sample of schoolchildren aged 7 to 14 years according to weight status. Florianópolis (SC), Brazil, 2018/2019.

Tables 2 and 3 show the results of the association between screen use at night and the consumption of food groups at dinner of schoolchildren with and without overweight, respectively. Schoolchildren without overweight who used screens once had a lower chance of consuming fruits and vegetables (OR: 0.62, 95% CI 0.43; 0.90) compared to those who did not use screens. Schoolchildren without overweight and who used screens twice had a higher chance of consuming sweets (OR: 2.01, 95% CI 1.40; 2.91) than those who did not. Schoolchildren without overweight who used screens three times or more were less likely to consume beans, meat, eggs, and seafood (OR: 0.24, 95% CI 0.11; 0.54 and OR: 0.35, 95% CI 0.16; 0.74, respectively) compared to those who did not use screens (Table 2).

Table 2 -
Association of screen use at night with the consumption of food groups at dinner in non-overweight schoolchildren aged 7 to 14 years, Florianópolis (SC), Brazil, 2018/2019. (n=843)

It was identified that overweight schoolchildren who used screens three times or more had a greater chance of consuming ultra-processed foods and pizza/ hot dog/ hamburger (OR: 2.51, 95% CI 1.35; 4.67) compared to those who did not use a screen (Table 3).

Table 3 -
Association of screen use at night with the consumption of food groups at dinner in overweight schoolchildren aged 7 to 14 years, Florianópolis, 2018/2019. (n= 415)

Schoolchildren without overweight and who used screens three times or more had a higher chance of consuming ultra-processed foods and pizza/hamburger/hot dog in the evening snack (OR: 8.26, 95% CI 1.63; 41.88) than those who did not (Table 4). No differences were observed in the evening snack of overweight schoolchildren (Table 5).

Table 4 -
Association of screen use at night with the consumption of food groups in the evening snack in non-overweight schoolchildren aged 7 to 14 years, Florianópolis (SC), Brazil, 2018/2019. (n= 445)
Table 5 -
Association of screen use at night with the consumption of food groups in the evening snack in overweight schoolchildren aged 7 to 14 years, Florianópolis (SC), Brazil, 2018/2019. (n=192)

DISCUSSION

This study investigated the association between screen use at night, the consumption of food groups at dinner, and evening snack in schoolchildren aged 7 to 14 years with and without overweight. The main results observed were (i) At dinner, higher frequency of screen use was inversely associated with consumption of fruits and vegetables, beans, meats, eggs, and seafood and a higher likelihood of consuming sweets in schoolchildren without overweight; (ii) Overweight schoolchildren who used screens more frequently had a higher chance of consuming ultra-processed foods and pizza/hamburger/hot dog at dinner; (iii) In the evening snack, schoolchildren without overweight who used screens more frequently had a higher chance of consuming ultra-processed foods and pizza/hamburger/hot dog.

The most used screen device was the mobile phone/tablet, similar to the results of other studies with children and adolescents [42,45]. The mobile phone was the most used device in a study of British female adolescents, followed by the tablet and laptop [45]. These data corroborate the results observed by Oliveira et al. (2020), who showed that the mobile phone/tablet was more used among schoolchildren aged 7 to 13 years in the public schools of Florianópolis in 2017 [42].

This study identified that screen use at night was associated with greater consumption of unhealthy foods at dinner and evening snack. These results corroborate other studies with children and adolescents that have identified an association between screen use and higher daily consumption of ultra-processed foods [15,46]. Melo et al. (2019) identified a positive correlation between the consumption of ultra-processed foods and the use of mobile phones, tablets, video games, and television in a study with schoolchildren aged 7 to 10 years from a private school in the municipality of Teresina, Brazil [15]. Similar results were observed in a study of 13486 Iranian schoolchildren between the ages of 6 and 18, in which screen use for more than four hours daily was associated with higher daily consumption of sweets, sugary drinks, packaged snacks, and fast food [14]. It is noteworthy that there was lower consumption of healthy foods among schoolchildren with and without overweight who used screens. This result corroborates the result found by Shang et al. (2015), who studied 630 Canadian children aged 8 to 10 years, in which a longer screen time (≥2 hours daily) was associated with lower daily consumption of fruits and vegetables, in children with and without overweight [47]. Kelishadi et al. (2017) identified lower milk consumption among students who used screens for more than four hours daily, although without stratifying according to weight status [14].

Pearson et al. (2017) investigated the presence of health risk behaviors by cluster analysis. One of the behaviors grouped was "increased screen time and unhealthy eating habits". The study identified that schoolchildren who used more screens also consumed fewer fruits and vegetables and more high-calorie density foods [16]. It should be noted that the Brazilian Dietary Guidelines recommends that foods in natura and minimally processed be the basis of the diet and that the consumption of ultra-processed foods should be avoided, given its relationship with an increase in the prevalence of overweight and obesity and Non-Communicable Diseases [38].

National research has identified an association between screen use and less healthy eating habits. According to a study that used data from the Pesquisa Nacional de Saúde do Escolar (National School Health Survey) (2015), adolescents with more than two hours daily of sedentary behavior (television, computer, video games, talking to friends, etc.) had a higher prevalence of daily consumption of ultra-processed foods (42.8%) compared to 28% of students who spend less than two hours a day in sedentary behavior and consume ultra-processed foods [48]. Likewise, a study with Brazilian adolescents participating in the Estudo de Riscos Cardiovasculares em Adolescentes (Study of Cardiovascular Risks in Adolescents) identified that 40% of adolescents almost always or always consumed snacks (packet snacks, popcorn, sandwiches, chocolates, and candies) while using screens [46]. It is important to note that screen devices can distract the child or adolescent, making it difficult to perceive satiety, leading to excessive consumption and eating without hunger [49,50]. Therefore, these habits can directly affect the health of schoolchildren, reflecting the increase in the prevalence of overweight and obesity [51].

A hypothesis for children and adolescents to consume more ultra-processed foods and, consequently, less food in natura or minimally processed while using screen devices is exposure to advertisements of ultra-processed foods, which aim to cause greater interest in consuming these products [50,52]. In addition, it is convenient to consume ultra-processed foods since they are purchased in ready-to-eat or quick-preparation packaging [17]. A study conducted in two Brazilian open television stations identified that about 50% of the foods served in the commercials were rich in sugars, and the most displayed foods in ads were soft drinks, yogurts/fermented drinks, and biscuits [53]. A study by Santos et al. (2012) mapped 239 food advertisements broadcast by Brazilian open television stations, finding that 85% presented foods rich in fats and sugars and that no commercials encouraged the acquisition and consumption of fruits and vegetables [54]. Although the impact of social media and digital influencers on the consumption of unhealthy foods is still unknown, evidence suggests that this type of advertising content can especially persuade children and adolescents [55,56]. Coates et al. (2019) investigated the impact of food advertising by influencers on social media in a sample of 176 children between nine and 11 years of age [56]. They identified that children exposed to influencer content containing unhealthy foods (such as cookies) had a higher caloric intake soon after exposure and consumed more unhealthy foods compared to children who were exposed to healthy food content or without the presence of food on social media. The authors also indicate that exposure to healthy food (banana) content did not change children's food consumption [56]. Finally, it should be noted that these ultra-processed foods are being consumed at night, therefore close to bedtime, and can cause changes in the circadian cycle, responsible for hormonal and metabolic oscillations related to overweight and obesity [57]

The strengths of this study are the use of data from children and adolescents from public and private schools, data collection by trained researchers, and the use of a food consumption and sedentary behavior questionnaire validated for schoolchildren [33,34,36,39]. One of the limitations of this study is that Web-CAAFE does not allow the identification of screen time or the amount of food consumed since it was developed to be a relatively brief questionnaire and to simplify the completion by the schoolchildren [36]. Data on food consumption and screen use were obtained from one day, which may not represent schoolchildren's usual food consumption and screen use behaviors. However, this method has been used to evaluate these behaviors in studies with large samples [58]. The smaller number of students who consumed the evening snack may have contributed to the greater confidence interval range and the classification of the variable “screen use at night”. Therefore, future studies should use larger samples to reduce the confidence interval range and the bias of reverse causality since it is a cross-sectional study.

CONCLUSION

The present study identified that using screens at night was associated with a higher consumption of unhealthy foods and a lower consumption of healthy foods at dinner in non- overweight students. In addition, there was a higher consumption of ultra-processed foods in the evening snack by students without overweight who used screens three times or more. A higher frequency of screen use was associated with higher consumption of ultra-processed foods and fast food at dinner in overweight schoolchildren.

Therefore, it should be noted that screens at night can impact food consumption at dinner and evening snack in children. In this sense, these findings indicate the need for guidance on the “screen use at night” and consumption of ultra-processed foods by schoolchildren, considering the impact of these habits on the health of children and adolescents with and without overweight. These actions can be performed in the school environment as part of the School Health Program or Food and Nutrition Education activities. It is essential that these actions also reach families and be associated with other health promotion actions within the scope of Primary Health Care.

REFERENCES

  • 1. Kaye LK, Orben A, Ellis DA, Hunter SC, Houghton S. The Conceptual and Methodological Mayhem of “Screen Time”. Int J Environ Res Public Health. 2020;17(10):33661. https://doi.org/10.3390/ijerph17103661
    » https://doi.org/10.3390/ijerph17103661
  • 2. Wu Y, Amirfakhraei A, Ebrahimzadeh F, Jahangiry L, Abbasalizad-Farhangi M. Screen Time and Body Mass Index Among Children and Adolescents: A Systematic Review and Meta-Analysis. Front Pediatr. 2022;10:561. https://doi.org/10.3389/fped.2022.822108
    » https://doi.org/10.3389/fped.2022.822108
  • 3. Barnett TA, Kelly CAS, Young DR, Perry CK, Pratt CA, Edwards NM, et al. Sedentary Behaviors in Today’s Youth: Approaches to the Prevention and Management of Childhood Obesity: A Scientific Statement From the American Heart Association. Circulation. 2018;138(11):e142-59. https://doi.org/10.1161/CIR.0000000000000591
    » https://doi.org/10.1161/CIR.0000000000000591
  • 4. Vasconcellos MB, Anjos LA, de Vasconcellos MTL. Estado nutricional e tempo de tela de escolares da Rede Pública de Ensino Fundamental de Niterói, Rio de Janeiro, Brasil. Cad Saude Publica. 2013;29(4):713-22. https://doi.org/10.1590/S0102-311X2013000400009
    » https://doi.org/10.1590/S0102-311X2013000400009
  • 5. Sociedade Brasileira de Pediatria. Manual de orientação: saúde de crianças e adolescentes na era digital [Internet]. Rio de Janeiro; 2016 [cited 2023 May 2]. Available from: https://nutritotal.com.br/pro/wp-content/uploads/2019/03/Manual_orientações_era_digital.pdf
    » https://nutritotal.com.br/pro/wp-content/uploads/2019/03/Manual_orientações_era_digital.pdf
  • 6. Mobile Time, Oinion Box. Panorama Mobile Time/Opinion Box - Crianças e smartphones no Brasil [Internet]. São Paulo; 2022 [cited 2023 May 18]. Available from: https://www.mobiletime.com.br/pesquisas/criancas-e-smartphones-no-brasil-outubro-de-2022/
    » https://www.mobiletime.com.br/pesquisas/criancas-e-smartphones-no-brasil-outubro-de-2022/
  • 7. Núcleo de Informação e Coordenação do Ponto BR. Pesquisa sobre o uso da Internet por crianças e adolescentes no Brasil : TIC Kids Online Brasil 2021 [Internet]. São Paulo: Comitê Gestor da Internet no Brasil; 2022 [cited 2023 May 2]. Available from: https://cetic.br/media/docs/publicacoes/2/20221121120124/tic_kids_online_2021_livro_eletronico.pdf
    » https://cetic.br/media/docs/publicacoes/2/20221121120124/tic_kids_online_2021_livro_eletronico.pdf
  • 8. Qutteina Y, De Backer C, Smits T. Media food marketing and eating outcomes among pre-adolescents and adolescents: A systematic review and meta-analysis. Obes Rev. 2019;20(12):1708-19. https://doi.org/10.1111/obr.12929
    » https://doi.org/10.1111/obr.12929
  • 9. Almoosawi S, Vingeliene S, Karagounis LG, Pot GK. Chrono-nutrition: A review of current evidence from observational studies on global trends in time-of-day of energy intake and its association with obesity. Proc Nutr Soc2016;75(4):487-500. http://dx.doi.org/10.1017/s0029665116000306
    » http://dx.doi.org/10.1017/s0029665116000306
  • 10. Almoosawi S, Prynne CJ, Hardy R, Stephen AM. Time-of-day and nutrient composition of eating occasions: Prospective association with the metabolic syndrome in the 1946 British birth cohort. Int J Obes. 2013;37(5):725-31. http://dx.doi.org/10.1038/ijo.2012.103
    » http://dx.doi.org/10.1038/ijo.2012.103
  • 11. Kupek E, Lobo AS, Leal DB, Bellisle F, Assis MA. Dietary patterns associated with overweight and obesity among Brazilian schoolchildren: An approach based on the time-of-day of eating events. Br J Nutr. 2016;116(11):1954-65. https://doi.org/10.1017/s0007114516004128
    » https://doi.org/10.1017/s0007114516004128
  • 12. Wang JB, Patterson RE, Ang A, Emond JA, Shetty N, Arab L. Timing of energy intake during the day is associated with the risk of obesity in adults. J Hum Nutr Diet. 2014;27 Suppl 2:255-62. https://doi.org/10.1111/jhn.12141
    » https://doi.org/10.1111/jhn.12141
  • 13. Thompson OM, Ballew C, Resnicow K, Gillespie C, Must A, Bandini LG, et al. Dietary pattern as a predictor of change in BMI z-score among girls. Int J Obes. 2006;30(1):176-82. https://doi.org/10.1038/sj.ijo.0803072
    » https://doi.org/10.1038/sj.ijo.0803072
  • 14. Kelishadi R, Mozafarian N, Qorbani M, Maracy MR, Motlagh ME, Safiri S, et al. Association between screen time and snack consumption in children and adolescents: The CASPIAN-IV study. J Pediatr Endocrinol Metab. 2017;30(2):211-9.
  • 15. Melo JCB, Lustoza GF, Ibiapina DFN, Landim LA dos SR. Influência da mídia no consumo de alimentos ultraprocessados e no estado nutricional de escolares. Rev Eletr Acervo Saude. 2019;(29):e1016-e1016. https://doi.org/10.25248/reas.e1016.2019
    » https://doi.org/10.25248/reas.e1016.2019
  • 16. Pearson N, Griffiths P, Biddle SJ, Johnston JP, McGeorge S, Haycraft E. Clustering and correlates of screen-time and eating behaviours among young adolescents. BMC Public Health. 2017;17(1):1-12. https://doi.org/10.1186/s12889-017-4441-2
    » https://doi.org/10.1186/s12889-017-4441-2
  • 17. Monteiro CA, Cannon G, Moubarac JC, Levy RB, Louzada MLC, Jaime PC. The UN Decade of Nutrition, the NOVA food classification and the trouble with ultra-processing. Public Heal Nutr. 2018;21(1):5-17. https://doi.org/10.1017/s1368980017000234
    » https://doi.org/10.1017/s1368980017000234
  • 18. Chemas-Velez MM, Gómez LF, Velasquez A, Mora-Plazas M, Parra DC. Scoping review of studies on food marketing in Latin America: Summary of existing evidence and research gaps. Rev Saude Publica. 2019;53:107. https://doi.org/10.11606/S1518-8787.2019053001184
    » https://doi.org/10.11606/S1518-8787.2019053001184
  • 19. Cezimbra VG, Assis MAA, De Oliveira MT, Pereira LJ, Vieira FGK, Di Pietro PF, et al. Meal and snack patterns of 7-13-year-old schoolchildren in southern Brazil. Public Health Nutr. 2021;24(9):2542-53. https://doi.org/10.1017/S1368980020003808
    » https://doi.org/10.1017/S1368980020003808
  • 20. Leal DB, Assis MAA, Conde WL, Lobo AS, Bellisle F, Andrade DF. Individual characteristics and public or private schools predict the body mass index of Brazilian children: a multilevel analysis. Cad Saude Publica. 2018;34(5). https://doi.org/10.1590/0102-311X00053117
    » https://doi.org/10.1590/0102-311X00053117
  • 21. Motter AF, Vasconcelos FAG, Correa EN, Andrade DF. Pontos de venda de alimentos e associação com sobrepeso/obesidade em escolares de Florianópolis, Santa Catarina, Brasil. Cad Saude Publica. 2015;31(3):620-32. https://doi.org/10.1590/0102-311X00097814
    » https://doi.org/10.1590/0102-311X00097814
  • 22. Pereira LJ, Vieira FGK, Belchor ALL, Cezimbra VG, Alves Junior CAS, Matsuo LH, et al. 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. 2022;77:13-23. https://doi.org/10.1016/j.annepidem.2022.10.017
    » https://doi.org/10.1016/j.annepidem.2022.10.017
  • 23. Leal DB, Assis MA, Hinnig PF, Schmitt J, Soares Lobo A, Bellisle F, et al. Changes in Dietary Patterns from Childhood to Adolescence and Associated Body Adiposity Status. Nutrients. 2017;9(10). https://doi.org/10.3390/nu9101098
    » https://doi.org/10.3390/nu9101098
  • 24. Rossi CE, Vasconcelos FAG. Relationship between birth weight and overweight/obesity among students in Florianópolis, Santa Catarina, Brazil: a retrospective cohort study. Sao Paulo Med J. 2014;132(5):273-81. https://doi.org/10.1590/1516-3180.2014.1325630
    » https://doi.org/10.1590/1516-3180.2014.1325630
  • 25. Matsuo LH, Adami F, Pereira LJ, Silva DAS, Vasconcelos FAG, Longo GZ, et al. Age at menarche and its association with overweight including obesity and socio-economic conditions of Brazilian schoolgirls: A time-trend analysis. Nutr Bull. 2022;47(1):70-81. https://doi.org/10.1111/nbu.12544
    » https://doi.org/10.1111/nbu.12544
  • 26. Wagner KJP, Fragas Hinnig P, Rossi CE, Almeida Alves M, Leite MS, Vasconcelos FAG. Time trends in the prevalence of breastfeeding among schoolchildren from public and private schools in Florianópolis, Southern Brazil: From 2002 to 2013. Am J Hum Biol. 2020;32(5):e23386. https://doi.org/10.1002/ajhb.23386
    » https://doi.org/10.1002/ajhb.23386
  • 27. Correa EN, Rossi CE, Neves J, Silva DAS, Vasconcelos FAG, Corrêa EN, et al. Utilization and environmental availability of food outlets and overweight/obesity among schoolchildren in a city in the south of Brazil. J Public Health. 2017;40(1):106-13.
  • 28. D’Avila GL, Silva DAS, Vasconcelos FAG. Associação entre consumo alimentar, atividade física, fatores socioeconômicos e percentual de gordura corporal em escolares. Cien Saude Colet. 2016;21(4):1071-81.
  • 29. Pinho MGM, Adami F, Benedet J, Vasconcelos FAG. Association between screen time and dietary patterns and overweight/obesity among adolescents. Rev Nutr. 2017;30(3):377-89.
  • 30. Fang K, Mu M, Liu K, He Y. Screen time and xhildhood overweight/obesity: A systematic review and meta-analysis. Child Care Health Dev. 2019;45(5):744-53. https://doi.org/10.1111/cch.12701
    » https://doi.org/10.1111/cch.12701
  • 31. Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira. Censo escolar. [Internet]. Brasília: Ministério da Educação; 2017[cited: 2023 May 2]. Available from: https://www.gov.br/inep/pt-br/areas-de-atuacao/pesquisas-estatisticas-e-indicadores/censo-escolar/resultados
    » https://www.gov.br/inep/pt-br/areas-de-atuacao/pesquisas-estatisticas-e-indicadores/censo-escolar/resultados
  • 32. Corrêa EN, Retondario A, Alves A, Bricarello LP, Rockenbach G, Hinnig PF, et al. Utilization of food outlets and intake of minimally processed and ultra-processed foods among 7 to 14-year-old schoolchildren. A cross-sectional study. Sao Paulo Med J. 2018;136(3):200-7. https://doi.org/10.1590/1516-3180.2017.0211061217
    » https://doi.org/10.1590/1516-3180.2017.0211061217
  • 33. Davies VF, Kupek E, Assis MAA, Natal S, Di Pietro PF, Baranowski T. Validation of a web-based questionnaire to assess the dietary intake of Brazilian children aged 7-10 years. J Hum Nutr Diet. 2015;28 Suppl 1:93-102. http://dx.doi.org/10.1111/jhn.12262
    » http://dx.doi.org/10.1111/jhn.12262
  • 34. Perazi FM, Kupek E, Assis MAA, Pereira LJ, Cezimbra VG, Oliveira MT, et al. Efeito do dia e do número de dias de aplicação na reprodutibilidade de um questionário de avaliação do consumo alimentar de escolares. Rev Bras Epidemiol. 2020;23:e200084. https://doi.org/10.1590/1980-549720200084
    » https://doi.org/10.1590/1980-549720200084
  • 35. Jesus G, Assis MA, Kupek E, Dias L. Avaliação da atividade física de escolares com um questionário via internet. Rev Bras Med do Esporte. 2016;22:261-6. https://doi.org/10.1590/1517-869220162204157067
    » https://doi.org/10.1590/1517-869220162204157067
  • 36. Costa FF, Schmoelz CP, Davies VF, Di Pietro PF, Kupek E, Assis MAA. Assessment of diet and physical activity of brazilian schoolchildren: usability testing of a web-based questionnaire. JMIR Res Protoc. 2013;2(2):e31. https://doi.org/10.2196/resprot.2646
    » https://doi.org/10.2196/resprot.2646
  • 37. Baranowski T, Domel S. A cognitive model of children’s reporting of food intake. Am J Clin Nutr. 1994;59(1Suppl). https://doi.org/10.1093/ajcn/59.1.212S
    » https://doi.org/10.1093/ajcn/59.1.212S
  • 38. Brasil. Ministério da Saúde. Guia alimentar para a população brasileira. Brasília: Ministério da Saúde, Secretaria de Atenção à Saúde, Departamento de Atenção Básica; 2014 [cited2023 May 2]. Available from: https://bvsms.saude.gov.br/bvs/publicacoes/guia_alimentar_populacao_brasileira_2ed.pdf
    » https://bvsms.saude.gov.br/bvs/publicacoes/guia_alimentar_populacao_brasileira_2ed.pdf
  • 39. Jesus GM, Assis MAA, Kupek E. 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. 2017;33(5):e00163016. https://doi.org/10.1590/0102-311x00163016
    » https://doi.org/10.1590/0102-311x00163016
  • 40. Pereira LJ, Hinnig PF, DI Pietro PF, Assis MAA, Vieira FGK.Trends in food consumption of schoolchildren from 2nd to 5th grade: a panel data analysis. Rev Nutr. 2020;33:r190164. https://doi.org/10.1590/1678-9865202033e190164
    » https://doi.org/10.1590/1678-9865202033e190164
  • 41. Oliveira Santos R, Fisberg RM, Marchioni DM, Troncoso Baltar V. Dietary patterns for meals of Brazilian adults. Br J Nutr. 2015;114(5):822-8. https://doi.org/10.1017/S0007114515002445
    » https://doi.org/10.1017/S0007114515002445
  • 42. Oliveira MT, Lobo AS, Kupek E, Assis MAA, Cezimbra VG, Pereira LJ, et al. Association between sleep period time and dietary patterns in Brazilian schoolchildren aged 7-13 years. Sleep Med. 2020;74:179-88. https://doi.org/10.1016/j.sleep.2020.07.016
    » https://doi.org/10.1016/j.sleep.2020.07.016
  • 43. Lohman T, Roche A, Martorell R. Anthropometric Standardization Reference Manual. Champaign: Human Kinetics Books; 1988.
  • 44. Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85(9):660-7.
  • 45. Harrington DM, Ioannidou E, Davies MJ, Edwardson CL, Gorely T, Rowlands AV, et al. Concurrent screen use and cross-sectional association with lifestyle behaviours and psychosocial health in adolescent females. Acta Paediatr. 2021;110(7):2164-70. https://doi.org/10.1111/apa.15806
    » https://doi.org/10.1111/apa.15806
  • 46. Oliveira JS, Barufaldi LA, Azevedo Abreu G, Leal VS, Brunken GS, Vasconcelos SML, et al. ERICA: Use of screens and consumption of meals and snacks by Brazilian adolescents. Rev Saude Publica. 2016;50:7s. https://doi.org/10.1590/S01518-8787.2016050006680
    » https://doi.org/10.1590/S01518-8787.2016050006680
  • 47. Shang L, Wang JW, O’Loughlin J, Tremblay A, Mathieu MÈ, Henderson M, et al. Screen time is associated with dietary intake in overweight Canadian children. Prev Med Reports. 2015;2:265-9. https://doi.org/10.1016/j.pmedr.2015.04.003
    » https://doi.org/10.1016/j.pmedr.2015.04.003
  • 48. Costa CS, Flores TR, Wendt A, Neves RG, Assunção MCF, Santos IS. Comportamento sedentário e consumo de alimentos ultraprocessados entre adolescentes brasileiros: Pesquisa Nacional de Saúde do Escolar (PeNSE), 2015. Cad Saude Publica. 2018;34(3):e00021017. https://doi.org/10.1590/0102-311X00021017
    » https://doi.org/10.1590/0102-311X00021017
  • 49. Bellissimo N, Pencharz PB, Thomas SG, Anderson GH. Effect of Television Viewing at Mealtime on Food Intake After a Glucose Preload in Boys. Pediatr Res. 2007;61(6):745-9. https://doi.org/10.1203/pdr.0b013e3180536591
    » https://doi.org/10.1203/pdr.0b013e3180536591
  • 50. Tabares-Tabares M, Moreno Aznar LA, Aguilera-Cervantes VG, León-Landa E, López-Espinoza A. Screen use during food consumption: Does it cause increased food intake? A systematic review. Appetite. 2022;171:105928. https://doi.org/10.1016/j.appet.2022.105928
    » https://doi.org/10.1016/j.appet.2022.105928
  • 51. Jackson DM, Djafarian K, Stewart J, Speakman JR. Increased television viewing is associated with elevated body fatness but not with lower total energy expenditure in children. Am J Clin Nutr. 2009;89(4):1031-6. https://doi.org/10.3945/ajcn.2008.26746
    » https://doi.org/10.3945/ajcn.2008.26746
  • 52. Micheletti NJ, Mello APQ. A influência da mídia na formação dos hábitos alimentares de crianças e adolescentes. Sci Saude. 2020;21(2):73-87.
  • 53. Pimenta DV, Masson DF, Bueno MB. Analysis of food advertisements on television in children programs. J Health Sci Inst; 2011;29(1):52-5.
  • 54. Santos CC, Stuchi RAG, Arreguy-Sena C, Pinto NAVD. A influência da televisão nos hábitos, costumes e comportamento alimentar. Cogitare Enferm. 2012;17(1):65-71. https://doi.org/10.5380/ce.v17i1.26376
    » https://doi.org/10.5380/ce.v17i1.26376
  • 55. Boyland EJ, Nolan S, Kelly B, Tudur-Smith C, Jones A, Halford JCG, et al. Advertising as a cue to consume: A systematic review and meta-analysis of the effects of acute exposure to unhealthy food and nonalcoholic beverage advertising on intake in children and adults. Am J Clin Nutr. 2016;103(2):519-33. https://doi.org/10.3945/ajcn.115.120022
    » https://doi.org/10.3945/ajcn.115.120022
  • 56. Coates AE, Hardman CA, Halford JCG, Christiansen P, Boyland EJ. Social Media Influencer Marketing and Children’s Food Intake: A Randomized Trial. Pediatrics. 2019;143(4). https://doi.org/10.1542/peds.2018-2554
    » https://doi.org/10.1542/peds.2018-2554
  • 57. Oosterman JE, Kalsbeek A, la Fleur SE, Belsham DD. Impact of nutrients on circadian rhythmicity. Am J Physiol Regul Integr Comp Physiol. 2015;308(5):R337-50. https://doi.org/10.1152/ajpregu.00322.2014
    » https://doi.org/10.1152/ajpregu.00322.2014
  • 58. Patterson E, Warnberg J, Kearney J, Sjostrom M. The tracking of dietary intakes of children and adolescents in Sweden over six years: The European Youth Heart Study. Int J Behav Nutr Phys Act. 2009;6:91. https://doi.org/10.1186/1479-5868-6-9
    » https://doi.org/10.1186/1479-5868-6-9
  • Support:
    Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina (FAPESC) (Grant Term nº 2017TR1759), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (Process nº 303550/2015-5), and Coordenação de Desenvolvimento de Pessoal de Nível Superior (Capes) (D.M.T.R.: 88887.572470/2020-00).

Edited by

  • Editor:
    Francisco de Assis Guedes de Vasconcelos

Publication Dates

  • Publication in this collection
    03 May 2024
  • Date of issue
    2024

History

  • Received
    21 May 2023
  • Reviewed
    21 Aug 2023
  • Accepted
    17 Oct 2023
location_on
Pontifícia Universidade Católica de Campinas Núcleo de Editoração SBI - Campus II , Av. John Boyd Dunlop, s/n. - Prédio de Odontologia, 13059-900 Campinas - SP Brasil, Tel./Fax: +55 19 3343-6875 - Campinas - SP - Brazil
E-mail: sbi.submissionrn@puc-campinas.edu.br
rss_feed Acompanhe os números deste periódico no seu leitor de RSS
Acessibilidade / Reportar erro