Fatores associados ao consumo não frequente de café da manhã em adolescentes (Estudo EVA-JF)

rn Revista de Nutrição Rev Nutr 1415-5273 1678-9865 Pontifícia Universidade Católica de Campinas RESUMO Objetivo Estimar as associações do consumo não frequente de café da manhã com fatores socioeconômicos, comportamentais e individuais em uma amostra de adolescentes de escolas públicas. Métodos Estudo transversal realizado com adolescentes de 14 a 19 anos matriculados em escolas públicas de Juiz de Fora (MG). Foram avaliadas a frequência de consumo de café da manhã, lanches, refrigerantes e bebidas industrializadas, consumo alimentar usual, IMC, percentual de gordura corporal e perímetro da cintura. Demais dados socioeconômicos, comportamentais e individuais foram obtidos através de questionários. A análise de regressão logística e seleção hierárquica das variáveis foram usadas para verificar fatores associados. Resultados A amostra foi composta por 805 adolescentes e 53,4% deles relataram consumo não frequente de café da manhã. Através da análise de regressão logística hierarquizada, evidenciou-se que a ocupação em domicílio próprio (OR: 0,618; IC95%: 0,441-0,865; p=0,005) foi o fator distal associado ao consumo não frequente de café da manhã, além dos fatores intermediários “consumo não frequente de bebidas industrializadas” (OR: 0,658; IC95%: 0,486-0,890; p=0,007) e “percentual de energia proveniente de alimentos processados” (OR: 0,935; IC95%: 0,907-0,964; p<0,001) e dos fatores proximais “sexo masculino” (OR: 0,696; IC95%: 0,520-0,932; p=0,0015) e “cor da pele não branca” (OR: 1,529; IC95%: 1,131-2,069; p=0,006). Conclusão Adolescentes que residiam em domicílios próprios, com consumo não frequente de bebidas industrializadas, com maior percentual de energia proveniente de alimentos processados e do sexo masculino apresentaram menores chances de consumo não frequente de café da manhã, enquanto, adolescentes com cor da pele não branca apresentaram maiores chances. INTRODUCTION From 10 to 19 years of age, adolescence is the transition period between childhood and adult life, when several physical, hormonal, psychological, and behavioral alterations occur [1,2]. Social, economic, cultural, environmental, behavioral, and psychological factors during this stage may impact the person’s choices and habits, including the eating habits, which will be a part of his or her identity and reflect on morbidity patterns and future health spending [3]. Studies report faulty eating habits among adolescents, such as the elevated consumption of ultra-processed foods like soft and industrialized drinks and fast food, and the omission of fundamental meals, such as breakfast [4-7]. According to the Dietary Guidelines for the Brazilian Population, breakfast is one of the three most important meals of the day [8]. Its consumption is associated with improved anthropometric profiles and body composition, higher diet quality, superior academic performance, and more cognitive capacity [9,10]. On the other hand, its omission or occasional consumption is associated with unfavorable socioeconomic conditions and the development of cardiometabolic risk factors, favoring the development of non-communicable chronic diseases [11,7]. Henceforth, understanding the determinant and conditioning potential factors associated with the infrequent consumption of breakfast is essential to base decision-making and plan actions for effectively promoting healthy eating habits, including having breakfast every day. Thus, this study’s objective is to estimate the associations between occasional breakfast consumption and socioeconomic, behavioral, and individual factors in a sample of Brazilian adolescents using hierarchical analysis. METHODS This cross-sectional study used data from research conducted with adolescents in the selected municipality (Juiz de Fora, in the Brazilian state of Minas Gerais) named Study of the Lifestyle in Adolescence – Juiz de Fora (EVA-JF Study, Portuguese acronym). We considered adolescents of both sexes, between 14 and 19 years old, who went to public schools in the city’s urban area. Of the 49 schools with students in this age range, 20 were not eligible. To simplify the logistics and reduce the costs related to collecting and processing blood samples, we decided to consider only students enrolled in morning classes. The sample calculation (n=790) was estimated with the software Epi Info (version 7.2.2.6, Center for Disease Control and Prevention, USA) using the following parameters: 9502 students enrolled in Basic Education in 2018 and 2019 (9th grade in elementary school and 1st, 2nd, and 3rd grades in high school); an 8% prevalence of obesity in the adolescent population; a 2% precision of the prevalence, with a standard error of 1%; confidence interval of 95% (95%CI), and expected losses of 20% [12,14]. The sample was stratified by the city’s administrative regions (Central, Eastern, Northeastern, Northern, Western, Southeastern, and Southern), school year, school facility, class, and sex. The layers’ sample size corresponded to their proportion in the general population (proportional allocation). To select the participants, the records of the eligible classes were reordered with software that generated random numbers (Stats, version 2.0, Decision Analyst, USA). Adolescents were picked until the necessary number was reached and, in case of refusals or school transference, the next adolescent selected was called. The data collection was performed by trained professionals in the institutions during the mornings between May 2018 and May 2019. More information on the study is available at Neves et al. [15]. The work was conducted in compliance with the Declaration of Helsinki and approved by the Ethics Committee in Research of the Federal University of Juiz de Fora (Universidade Federal de Juiz de Fora) (CAEE: 68601617.1.0000.5147). Participation was voluntary. Those above 18 years old signed a Free and Informed Consent Form. Minors signed a Free and Informed Assent Form, and their parents or the responsible adults also signed. In relation to socioeconomic variables, the analysis considered the age, sex, self-referred race/ethnicity [white and non-white (brown, Black, Indigenous, or Asian-descendant)], house occupancy status (rented/ceded or owned), mother’s schooling (illiterate, incomplete elementary school, incomplete high school, complete high school or college), mother’s current employment status (working or not working), socioeconomic status [medium/high (classes A or B1), medium (B2 or C1), and medium/low (classes C2 or DE), as per the Brazilian Economic Classification Criteria of the Associação Brasileira de Empresas de Pesquisa (Brazilian Association of Research Companies) [16]. The information was collected with an structured questionnaire applied in person with the adolescents. The frequency of breakfast consumption was evaluated with the question: “Do you usually have breakfast?” The possible answers included: never; hardly ever; 1 or 2 days a week; 3 or 4 days a week; 5 or 6 days a week; every day. To analyze the frequency, the categories were: not frequent (0 to 4 days a week) and frequent (5 to 7 days a week). Along with the categorial analysis, a trained team conducted two 24-hour recalls of eating habits on non-consecutive weekdays using the multiple-pass method [17]. We used a photographic album to estimate the ingested portions and quantities [18]. The total and macronutrient-related energetic values (both measured in kcal) were assessed with a table of nutritional composition and nutritional labels [19]. The food items were evaluated according to the NOVA classification system proposed by Monteiro et al. [20], which considers the food items’ degree of industrial processing, dividing them into natural or minimally processed foods; culinary ingredients; processed and ultra-processed foods. In this study, culinary ingredients were grouped with natural or minimally processed foods, as they are usually used in culinary preparations, not in isolation. Afterwards, to estimate the usual ingestion of food, nutrients, and energy, the data were adjusted in the program Multiple Source Method (version 1.0.1, German Institute of Human Nutrition, Potsdam-Rehbrucke, Department of Epidemiology), reducing intra-individual variation [21,22]. Later, we calculated the average daily energy contribution of each food group according to the NOVA classification. A questionnaire also verified how often adolescents consumed ultra-processed food items in restaurants or fast-food chains, and soft and other industrialized drinks (powdered juice, juice and teas sold in cans or cartons, flavored water, guarana and currant syrup, energy drinks, fermented milk, chocolate drinks, sweetened and flavored yogurt). The periodicity with which these items were consumed was classified as non-frequent (0 to 4 days a week) and frequent (5 to 7 days a week) consumption, similarly to classification found in other works [23,24]. The evaluation of the participants’ nutritional status started with measurements of their weight and height for the subsequent calculation of the body mass index. The weight was measured with the Tanita Ironman scale (model BC-553, Tanita Corp., Japan), which has a maximum capacity of 200 kg and a 50 g precision; the height was measured with a portable stadiometer (Alturexata, Brazil), with centimeter scales and 1mm precision, following a standard protocol [15]. The body mass index was classified within the growth curves of the World Health Organization according to sex and age, expressed in z-score and then categorized as per the weight status variable into non-overweight (z-score <1) and overweight (z-score ≥+1) [25]. The body fat percentage was assessed by bipolar electrical bioimpedance with Tanita Ironman (model BC-553, Tanita Corp., Japan) and classified with Lohman’s cut-off points [15,26,27]. After, adolescents were classified as at risk or not at risk (≥25% for girls and ≥20% for boys). The waistline was measured once in the intermediary point between the inferior border of the last rib and the iliac crest’s superior limit, or in the smallest diameter between the thorax and the hips (for adolescents who were overweight), with a Sanny measuring tape (American Medical Ltda., Brazil) [28]. As there is no consensus on the specific cut-off points for adolescents waist circumference, the risk classification was attributed to those with measures ≥the 90th percentile of the sample, according to sex and age. All anthropometric and body composition assessments were conducted by a properly trained health professional [29,30]. To estimate the regular practice of physical education in the 12 months before the research, we used the International Physical Activity Questionnaire, a validated instrument that measures the frequency and type of exercise, as well as the time spent exercising in a habitual week [31,32]. Adolescents who exercised for more than 300 minutes a week (considering the five usual weekdays, excluding weekends) were understood as physically active [33]. Information regarding the total hours of sleep per night during weekdays was collected with the Pittsburgh Sleep Quality Index, which assessed sleep quality and duration [34]. According to the National Sleep Foundation, adolescents must sleep 8 to 10 hours a night [35]. Thus, sleep was classified as inadequate when <8 hours/night (<480 minutes) or adequate when ≥8 hours/night (>480 minutes). The data were analyzed with the software SPSS®IBM® (version 20.0), with a significance level of 5% (p<0.05). First, the quantitative continuous variables underwent the normality Kolmogorov-Smirnov test, with the normality parameters expressed with measures of central tendency (means) and dispersion (standard deviation). The qualitative variables were described with absolute (n) and relative (%) frequencies. To examine the factors associated with the non-frequent consumption of breakfast, we used hierarchical multiple logistic regression. For the hierarchization of variables, we established and maintained a conceptual model during the data analysis [36,37]. The literature does not offer a specific model to determine the frequency of breakfast consumption. The model we created for this purpose was based on the conceptual model proposed by Dahlgren and Whitehead [38], which approaches social determinants of health, and the one proposed by Alexandre et al. [39], discussing the variables influencing the adoption of healthy eating choices. The hierarchical analysis was conducted as soon as the conceptual model of independent variables was established (Figure 1). First, we performed a univariate logistic regression considering a 95%CI. Then, the multivariate analysis started from the hierarchical entry into groups of variables that presented a statistical significance below 20% (p<0.20) in the previous stage, ordered as follows: Group 1: Socioeconomic characteristics; Group 2: Behavioral characteristics; Group 3: individual characteristics. The frequency of breakfast consumption (frequent or not frequent) was a dependent variable in every stage. Figure 1 Conceptual hierarchical model for determining the factors associated with infrequent breakfast consumption. Source: Model adapted from Alexandre et al. [39] and Dahlgren and Whitehead [38]. The backward LR method, employed in the hierarchical multiple logistic regression analysis, initially incorporates all the variables in each group separately, which may be eliminated in later stages depending on the results of F partial tests until the final model is produced. To interpret the results, we considered p<0.05. The statistical significances were obtained with the Wald test for heterogeneity. The Hosmer-Lemeshow test evaluated the final model’s consistency, considering the adjustment adequate when p>0.05. To assess the model’s explanatory power, we used the Nagelkerke R Square test. RESULTS The initial number of adolescents participating the EVA-JF study was 835. However, with the losses referring to the lack of data regarding food consumption, the study’s final sample consisted of 805 adolescents. Table 1 presents the description of the participants’ socioeconomic, behavioral, and individual characteristics, including the frequency of breakfast consumption. Most participants (53.4%) reported not having breakfast frequently (0 to 4 days a week). Table 1 Adolescents’ socioeconomic, behavioral, and individual characteristics. Juiz de Fora (MG), Brazil, 2018-2019. Group 3 Socioeconomic characteristics n % Socioeconomic status ♠       Medium/low 161 20.0   Medium 471 58.5   Medium/high 173 21.5 House occupancy status       Rent/concession 202 25.1   Ownership 603 74.9 Mother’s employment status       Not working 227 29.0   Working 556 71.0 Mother’s education       Illiterate or incomplete elementary school 30 4.2   Complete elementary school/ incomplete high school 31 43.0   High school 273 37.9   University 108 15.0 Group 2 Behavioral characteristics n % or M(SD)a † Level of physical activity ●       Insufficiently active 287 35.7   Active 518 64.3 Hours of sleep per night ┤       Inadequate 133 16.5   Adequate 672 83.5 Consumption of ultra-processed foods in restaurants or fast-food chains δ       Frequent 35 4.3   Not frequent 770 95.7   Consumption of soda δ       Frequent 139 17.3   Not frequent 666 82.7 Consumption of industrialized drinks δ       Frequent 289 35.9   Not frequent 516 64.1 % of energy from ultra-processed foods --- 45.7 (12.9) a % of energy from processed foods --- 10.9 (4.9) a % of energy from natural or minimally processed foods --- 43.3 (12.1) a Group 1 Individual characteristics n % Sex       Female 464 57.6   Male 341 42.4 Age range ‡       14 and 15 248 30.8   16 and 17 456 56.6   18 and 19 101 12.5 Race/ethnicity       White 281 35.2   Non-white ⸸ 517 64.8 Weight status       Not overweight 563 71.3   Overweight 227 28.7 % of body fat ||       Not at risk 346 51.0   At risk 332 49.0 Waist circumference ¶       Not at risk 723 89.8   At risk 82 10.2 Frequency of consumption δ Breakfast n %   Frequent 375 46.6   Not frequent 430 53.4 Note: a M (SD). † Valid percentages, considering eventual losses. ♠ Medium/low: classes C2 or D-E. Medium: classes B2 or C1. Medium/high: classes A or B1. ● Insufficiently active: <300 minutes/week. Active: ≥300 minutes/week. ┤ Inadequate: <480 minutes. Adequate: ≥480 minutes. δ Frequent: 5 to 7 days/week. Not frequent: 0 to 4 days/week. ‡ Average age of 16.1 years (SD=1.2). ⸸ Non-white: brown, Black, Indigenous, or Asian. || Not at risk <25% (female) and <20% (male). At risk: ≥25% (female) and ≥20% (male). ¶ Not at risk: <90th percentile of the sample, according to sex. At risk: ≥90th percentile of the sample, according to sex. M: Mean; SD: Standard-Deviation. Table 2 presents the socioeconomic, behavioral, and individual characteristics associated with non-frequent consumption of breakfast, according to the univariate logistic regression analysis. All the variables that presented p>0.20 were selected for the analysis of hierarchical regression. Table 2 Model of univariate logistic regression explaining non-frequent consumption of breakfast among adolescents. Juiz de Fora (MG), Brazil, 2018-2019. Group 3 Socioeconomic characteristics OR 95% CI p * Socioeconomic status ♠         Middle/low Reference       Middle 0.660 0.425-1.011 0.050   Middle/high 0.790 0.552-1.139 0.209 House occupancy status         Rent/concession Reference       Ownership 0.633 0.460-0.871 0.005 Mother’s employment status         Not working Reference       Working 0.931 0.687-1.262 0.645 Mother’s education         Illiterate or incomplete elementary school Reference       Complete elementary school/ incomplete high school 1.190 0.587-2.414 0.629   High school 1.058 0.519-2.156 0.876   University 0.897 0.415-1.935 0.781 Group 2 Behavioral characteristics OR 95% CI p * Level of physical activity ●         Insufficiently active Reference       Active 1.075 0.805-1.435 0.626 Hours of sleep per night ┤         Inadequate Reference       Adequate 0.940 0.650-1.351 0.720 Consumption of ultra-processed foods in restaurants or fast-food chains δ         Frequent Reference       Not frequent 1.502 0.746-3.024 0.255 Consumption of soda δ         Frequent Reference       Not frequent 0.734 0.506-1.064 0.103 Consumption of industrialized drinks δ         Frequent Reference       Not frequent 0.635 0.471-0.856 0.002 % of energy from ultra-processed foods 1.012 1.002-1.024 0.025 % of energy from processed foods 0.933 0.906-0.961 <0.001 % of energy from natural or minimally processed foods 0.997 0.986-1.008 0.593 Group 1 Individual characteristics OR 95% CI p * Sex         Female Reference       Male 0.617 0.468-0.813 0.001 Age group         14 and 15 Reference       16 and 17 0.894 0.658-1.215 0.474   18 and 19 1.011 0.643-1.589 0.963 Group 1 Individual characteristics OR 95% CI p * Race/ethnicity         White Reference       Non white ⸸ 1.670 1.253-2.225 <0.001 Weight status         Overweight Reference       Not overweight 0.821 0.602-1.121 0.214 % of body fat ||         At risk Reference       Not at risk 0.734 0.541-0.995 0.046 Waist circumference ¶         At risk Reference       Not at risk 0.709 0.444-1.131 0.149 Note: * The statistical significances were obtained with the Wald test for heterogeneity. ♠ Medium/low: classes C2 or D-E. Medium: classes B2 or C1. Medium/high: classes A or B1. ● Insufficiently active: <300 minutes/week. Active: ≥300 minutes/week. ┤ Inadequate: <480 minutes. Adequate: ≥480 minutes. δ Frequent: 5 to 7 days/week. Not frequent: 0 to 4 days/week. ⸸ Non-white: brown, Black, Indigenous, or Asian. || At risk: <25% (female) and <20% (male). Not at risk: ≥25% (female) and ≥20% (male). ¶ Not at risk: <90th percentile, according to sex. At risk: ≥90th percentile, according to sex. 95% CI: Confidence Interval of 95%; OR: Odds Ratio. Through the final model of hierarchical multiple logistic regression shown in Table 3, we observed that the single socioeconomic variable in Group 3 that is associated with non-frequent consumption of breakfast was house occupancy status. Adolescents living in owned homes presented smaller chances of not consuming breakfast frequently (OR: 0.618; 95%CI: 0.441-0.865; p=0.005). Regarding the behavioral variables present in Group 2, the outcome was negatively associated with the consumption of industrialized drinks (OR: 0.658; 95%CI: 0.486-0.890; p=0.007) and the percentage of ingestion of processed foods (OR: 0.935; 95%CI: 0.907-0.964; p <0.001), which reduced the chances of incurrence. As to the individual variables in Group 3, both sex (OR: 0.696; 95%CI: 0.520–0.932; p=0.015) and race/ethnicity (OR: 1.529; 95%CI: 1.131-2.069; p=0.006) were associated with the outcome, with male adolescents presenting reduced chances of non-frequent breakfast consumption, while nonwhite adolescents had greater chances. In table 3, the Hosmer and Lemeshow tests are also described, demonstrating the adequate adjustment of the final model (p=0.723). The explanatory power was of about 9%, according to the Nagelkerke R Square test. Table 3 Final model of hierarchical multiple logistic regression explaining the non-frequent consumption of breakfast among adolescents. Juiz de Fora (MG), Brazil. Group 3 Socioeconomic characteristics OR 95% CI p * House occupancy status         Rent/concession Reference       Ownership 0.618 0.441-0.865 0.005 Group 2 Behavioral characteristics OR 95% CI p * Consumption of industrialized drinks δ         Frequent Reference       Not frequent 0.658 0.486-0.890 0.007   % of energy from processed foods 0.935 0.907-0.964 <0.001 Group 1 Individual characteristics OR 95% CI p * Sex         Female Reference       Male 0.696 0.520-0.932 0.015 Race/ethnicity ⸸         White Reference       Non-white 1.529 1.131-2.069 0.006 Note: Hosmer and Lemeshow Test=0.723; Nagelkerke R Square=0.089. * The statistical significances were obtained with the Wald test for heterogeneity. δ Frequent: 5 to 7 days/week. Not frequent: 0 to 4 days/week. ⸸ Non-white: brown, Black, Indigenous, or Asian. 95% CI: Confidence Interval of 95%; OR: Odds Ratio. DISCUSSION The results of the present study demonstrate a high prevalence of adolescents who do not have breakfast frequently. The creation of a conceptual model of multiple hierarchical logistic regression evidenced that socioeconomic (house occupancy status), behavioral (consumption of industrialized drinks and percentage of energy from processed items), and individual (male sex and being nonwhite) variables were associated to not having breakfast frequently. The percentage of adolescents who did not have breakfast frequently in this study (53.4%) was similar to that found in the Study of Estudo de Riscos Cardiovasculares em Adolescentes (Cardiovascular Risks in Adolescents), a national health survey in which 51.4% of adolescents reported not having breakfast often or at all [40]. Our results were superior to the percentage found by Simões et al. [41] for the city of Curitiba, in the state of Paraná (41.4%; 95%CI: 36.8-46.1), and by Azeredo et al. [42] (38.1%), referring to 11- to 14-year-old adolescents assessed by the 2012 Pesquisa Nacional de Saúde do Escolar (National Adolescent School-based Health Survey). These differences may be due to methodological variations, such as the definition of frequency and the number of evaluated days. The hierarchical regression analysis demonstrated that the only socioeconomic variable, that is, the single distal factor, associated with non-frequent breakfast consumption was house occupancy status. Adolescents who resided in owned houses had smaller chances of not having breakfast frequently. Along with other factors, such as the house’s structural characteristics and the family’s buying power, this variable is employed as an indirect indicator of socioeconomic status [43]. In the present study, the socioeconomic status and the mother’s schooling were not associated with the outcome. However, some authors demonstrated that not having breakfast frequently was significantly more common among children and adolescents with lower socioeconomic status or whose mothers had fewer years of schooling [11,44-47]. Some studies also pointed to other socioeconomic variables associated with poorer dietary behavior. Another research with children and adolescents in Juiz de Fora [48] concluded that adolescents whose mothers had more children had fewer meals a day. Examining the eating habits of adolescents who participated in the 2009 Pesquisa Nacional de Saúde do Escolar, Tavares et al. [49] observed a direct association between the Human Development Index and healthier eating practices, suggesting a possible synergic influence between income, education, and health conditions. Regarding behavioral variables, in an intermediary position concerning the outcome, the unusual consumption of industrialized drinks and the percentage of energy from processed foods were associated with smaller chances of non-frequent consumption of breakfast in the hierarchical regression final model. Similarly, Ramsay et al. [50] noticed that adolescents who did not have breakfast often presented an enlarged contribution of caloric ingestion from items like non-alcoholic industrialized drinks and fruit juices. In a study with Norwegian adolescents, Medin et al. [51] observed that the irregular consumption of breakfast was associated with enlarged consumption of food items rich in sugar, fat, and sodium, including processed foods like fruit and bar candies, crystallized fruit, and industrialized and ultra-processed foods. Having breakfast is a possible marker of healthy eating [38]. Thus, its omission or infrequent consumption is often related to the augmented consumption of industrialized foods and lower diet quality [40,45,50,51]. As for Group 3, comprising the individual variables proximal to the outcome, the final conceptual model included sex and race/ethnicity, both with significant association with the outcome. Male adolescents had smaller chances of not having breakfast frequently than female ones. Similarly, other studies [52-54] demonstrated that the omission or unusual consumption of breakfast is more common among female children or adolescents. According to these authors, this is possibly so because girls are often more concerned or conscious of their appearance, with a relevant influence of the media on these issues. Reinforcing this hypothesis, in their study with Jordanian adolescents of both sexes, Ali et al. [52] observed that over a third of the participants believed that omitting breakfast would lead to weight loss. Non-white adolescents had more chances of unusual breakfast consumption. These results are close to those of the research by Affenito et al. [55], who worked with data from the National Growth and Health Study, a cohort study with Black and white female children and adolescents. According to them, white girls had breakfast more often than non-white girls. On the other hand, in a cohort study with 809 adolescents who participated in the Estudo Longitudinal de Avaliação Nutricional do Adolescente (Adolescent Nutritional Assessment Longitudinal Study) in the state of Rio de Janeiro, Hassan et al. [56] did not find a significant association between race/ethnicity and irregular breakfast consumption. However, it is known that race-related inequalities produce vulnerabilities, especially health-related ones, and more exposure to general risk factors and behaviors [57]. Thus, the non-frequent consumption of breakfast is associated with female, non-white adolescents who live in rented or ceded houses, usually have industrialized drinks, and with a lesser proportion of energy derived from processed food items. That shows critical social, behavioral, and individual deficiencies that may be the object of public intervention geared toward adolescents. Our study’s main positive points were: 1) data collection with rigorous methods and trained professionals; 2) two non-consecutive 24-hour recalls, following the multiple-pass method, and the posterior estimation of eating habits with the Multiple Source Method, which counts on advanced statistical modeling techniques, generating more precise ingestion measures for individuals and populations. The study also presents the following limitations: 1) as a cross-sectional epidemiological study, it cannot establish causal relations, even as it may help produce hypotheses of possible health outcomes; 2) the lack of a conceptual model specifically for the non-frequent consumption of breakfast, which made it necessary to use an adapted model; 3) although the sample is representative, it is composed only of adolescents from public schools in Juiz de Fora, suggesting a cautious approach when extrapolating the results for students in private schools and other Brazilian cities. CONCLUSION The results of the present study identified determining sociodemographic, behavioral, and individual factors associated with non-frequent consumption of breakfast. Consequently, directed intervention actions are made possible, such as those targeting awareness regarding the benefits of breakfast, leading to positive health impacts during adolescence and adult life. Article based on the master’s thesis of ACO CÂNDIDO, intitled “Consumo de café da manhã e sua associação com determinantes sociais, nutricionais, bioquímicos e pressão arterial entre adolescentes de Juiz de Fora, MG: Estudo EVA-JF”. Universidade Federal de Juiz de Fora; 2021. How to cite tis article Cândido ACO, Neves FS, Faria ER, Netto MP, Oliveira RMS, Cândido APC. Factors associated with non-frequent breakfast consumption in adolescents (EVA-JF Study). Rev Nutr. 2022;35:e210166. https://doi.org/10.1590/1678-9865202235e210166 REFERENCES 1 1 World Health Organization. Nurition in adolescence: issues and challenges for the health sector: issues in adolescent health and development. Geneva: Organization; 2005 [cited 2021 Apr 21]. Available from: https://apps.who.int/iris/bitstream/handle/10665/43342/9241593660_eng.pdf?sequence=1&isAllowed=y World Health Organization Nurition in adolescence: issues and challenges for the health sector: issues in adolescent health and development Geneva Organization 2005 2021 Apr 21 Available from: https://apps.who.int/iris/bitstream/handle/10665/43342/9241593660_eng.pdf?sequence=1&isAllowed=y 2 2 Bulboz CTR, Rombaldi AJ, Gonzales NG, Azevedo MR, Madruga SW. Consumo alimentar conforme o tipo de alimentação consumida em escolas de zona rural no Sul do Brasil. Cien Saude Colet. 2018;23(8): 2705-12. Bulboz CTR Rombaldi AJ Gonzales NG Azevedo MR Madruga SW Consumo alimentar conforme o tipo de alimentação consumida em escolas de zona rural no Sul do Brasil Cien Saude Colet 2018 23 8 2705 2712 3 3 Ministério da Saúde (Brasil). Diretrizes nacionais para a atenção integral à saúde de adolescentes e jovens na promoção, proteção e recuperação da saúde. Brasília: Ministério; 2010 [cited 2021 Apr 21]. Available from: http://bvsms.saude.gov.br/bvs/publicacoes/diretrizes_nacionais_atencao_saude_adolescentes_jovens_promocao_saude.pdf Ministério da Saúde (Brasil) Diretrizes nacionais para a atenção integral à saúde de adolescentes e jovens na promoção, proteção e recuperação da saúde Brasília Ministério 2010 2021 Apr 21 Available from: http://bvsms.saude.gov.br/bvs/publicacoes/diretrizes_nacionais_atencao_saude_adolescentes_jovens_promocao_saude.pdf 4 4 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 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 10.1590/0102-311X00021017 5 5 Melo AST, Neves FS, Batista AP, Coelho-Machado GLL, Sartorelli DS, Faria ER, et al. Percentage of energy contribution according to the degree of industrial food processing and associated factors in adolescents (EVA-JF study, Brazil). Public Health Nutr. 2021;24(13):1-10. https://doi.org/10.1017/S1368980021000100 Melo AST Neves FS Batista AP Coelho-Machado GLL Sartorelli DS Faria ER Percentage of energy contribution according to the degree of industrial food processing and associated factors in adolescents (EVA-JF study, Brazil) Public Health Nutr 2021 24 13 1 10 10.1017/S1368980021000100 6 6 Enes CC, Camargo CM, Justino MIC. Ultra-processed food consumption and obesity in adolescents. Rev. Nutr. 2019;32:e180170. https://doi.org/10.1590/1678-9865201932e180170 Enes CC Camargo CM Justino MIC Ultra-processed food consumption and obesity in adolescents Rev. Nutr 2019 32 e180170 10.1590/1678-9865201932e180170 7 7 Monzani A, Ricotti R, Caputo M, Solito A, Archero F, Bellone S, et al. A Systematic Review of the Association of Skipping Breakfast with Weight and Cardiometabolic Risk Factors in Children and Adolescents. What Should We Better Investigate in the Future? Nutrients. 2019;11(2):1-23 Monzani A Ricotti R Caputo M Solito A Archero F Bellone S A Systematic Review of the Association of Skipping Breakfast with Weight and Cardiometabolic Risk Factors in Children and Adolescents What Should We Better Investigate in the Future? Nutrients 2019 11 2 1 23 8 8 Ministério da Saúde (Brasil). (Guia alimentar para a população brasileira. Brasília: Ministério; 2014 [cited 2021 Mar 02]. Available from: http://bvsms.saude.gov.br/bvs/publicacoes/guia_alimentar_populacao_brasileira_2ed.pdf Ministério da Saúde (Brasil) Guia alimentar para a população brasileira Brasília Ministério 2014 2021 Mar 02 Available from: http://bvsms.saude.gov.br/bvs/publicacoes/guia_alimentar_populacao_brasileira_2ed.pdf 9 9 Rampersaud GC. Benefits of breakfast for children and adolescents: update and recommendations for practitioners. Am J Lifestyle Medicine. 2008;3:86-103. Rampersaud GC Benefits of breakfast for children and adolescents: update and recommendations for practitioners Am J Lifestyle Medicine 2008 3 86 103 10 10 Hopkins LC, Sattler M, Steeves EA, Smith- Jones JC, Gittelsohn. Breakfast Consumption Frequency and Its Relationships to Overall Diet Quality, Using Healthy Eating Index 2010, and Body Mass Index among Adolescents in a Low-Income Urban Setting. Ecol Food Nutr. 2017;56(4):297-311. Hopkins LC Sattler M Steeves EA Smith- Jones Breakfast Consumption Frequency and Its Relationships to Overall Diet Quality, Using Healthy Eating Index 2010, and Body Mass Index among Adolescents in a Low-Income Urban Setting Ecol Food Nutr 2017 56 4 297 311 11 11 Timlin MT, Pereira MA, Story M, Sztainer DN. Breakfast Eating and Weight Change in a 5-Year Prospective Analysis of Adolescents: Project EAT (Eating Among Teens). Pediatrics. 2008;121(3):e638-45. https://doi.org/10.1542/peds.2007-1035 Timlin MT Pereira MA Story M Sztainer DN. Breakfast Eating and Weight Change in a 5-Year Prospective Analysis of Adolescents: Project EAT (Eating Among Teens) Pediatrics 2008 121 3 e638 e645 10.1542/peds.2007-1035 12 12 Instituto Brasileiro de Geografia e Estatística. Pesquisa Nacional de Saúde do Escolar 2015. Rio de Janeiro: Instituto; 2016 [cited 2021 Dec 14]. Available from: https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=297870 Instituto Brasileiro de Geografia e Estatística Pesquisa Nacional de Saúde do Escolar 2015 Rio de Janeiro Instituto 2016 2021 Dec 14 Available from: https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=297870 13 13 Bloch KV, Klein CH, Szklo M, Kuschnir MCC, Abreu GA, Barufaldi LA, et al. ERICA: prevalências de hipertensão arterial e obesidade em adolescentes brasileiros. Rev Saude Publica. 2016;50(1):9s. Bloch KV Klein CH Szklo M Kuschnir MCC Abreu GA Barufaldi LA ERICA: prevalências de hipertensão arterial e obesidade em adolescentes brasileiros Rev Saude Publica 2016 50 1 9s 9s 14 14 Instituto Brasileiro de Geografia e Estatística. Antropometria e análise do estado nutricional de crianças, adolescentes e adultos no Brasil. Rio de Janeiro: Instituto; 2010 [cited 2020 Dec 14]. Available from: https://biblioteca.ibge.gov.br/visualizacao/livros/liv45419.pdf Instituto Brasileiro de Geografia e Estatística Antropometria e análise do estado nutricional de crianças, adolescentes e adultos no Brasil Rio de Janeiro Instituto 2010 2020 Dec 14 Available from: https://biblioteca.ibge.gov.br/visualizacao/livros/liv45419.pdf 15 15 Neves FS, Fontes VS, Pereira PM, Campos AAL, Batista AP, Machado-Coelho GLL, et al. Estudo EVA-JF: aspectos metodológicos, características gerais da amostra e potencialidades de uma pesquisa sobre o estilo de vida de adolescentes brasileiros. Adolesc Saude. 2019;16:113-29. Neves FS Fontes VS Pereira PM Campos AAL Batista AP Machado-Coelho GLL Estudo EVA-JF: aspectos metodológicos, características gerais da amostra e potencialidades de uma pesquisa sobre o estilo de vida de adolescentes brasileiros Adolesc Saude 2019 16 113 129 16 16 Associação Brasileira de Empresas de Pesquisa. Critério de Classificação Econômica Brasil 2018. São Paulo: Associação; 2018 [cited 2020 June 15]. Available from: http://www.abep.org/criterio-brasil Associação Brasileira de Empresas de Pesquisa Critério de Classificação Econômica Brasil 2018 São Paulo Associação 2018 2020 June 15 Available from: http://www.abep.org/criterio-brasil 17 17 Conway JM, Ingwersen LA, Vinyard BT, Moshfegh AJ. Effectiveness of the US Department of Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. Am J Clin Nutr. 2003;77(5):1171-78. Conway JM Ingwersen LA Vinyard BT Moshfegh AJ Effectiveness of the US Department of Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women Am J Clin Nutr 2003 77 5 1171 1178 18 18 Zaboto CB. Photographic record for dietary surveys: utensils and servings. Campinas: Unicamp; 1996. Zaboto CB. Photographic record for dietary surveys: utensils and servings Campinas Unicamp 1996 19 19 Instituto Brasileiro de Geografia e Estatística. Pesquisa de Orçamentos Familiares 2008-2009: Tabela de composição nutricional dos alimentos consumidos no Brasil. Rio de Janeiro: Instituto; 2010 [cited 2020 June 15]. Available from: https://biblioteca.ibge.gov.br/visualizacao/livros/liv50002.pdf Instituto Brasileiro de Geografia e Estatística Pesquisa de Orçamentos Familiares 2008-2009: Tabela de composição nutricional dos alimentos consumidos no Brasil Rio de Janeiro Instituto 2010 2020 June 15 Available from: https://biblioteca.ibge.gov.br/visualizacao/livros/liv50002.pdf 20 20 Monteiro CA, Levy RB, Claro RM, Castro IRR, Cannon G. A new classification of foods based on the extent and purpose of their processing. Cad Saude Publica. 2010;26(11): 2039-49. Monteiro CA Levy RB Claro RM Castro IRR Cannon G. A new classification of foods based on the extent and purpose of their processing Cad Saude Publica 2010 26 11 2039 2049 21 21 Harttig U, Haubrock J, Knüppel S, Boeing H, EFCOVAL Consortium. The MSM program: web-based statistics package for estimating usual dietary intake using the Multiple Source Method. Eur J Clin Nutr. 2011;65(1):S87-891. Harttig U Haubrock J Knüppel S Boeing H EFCOVAL Consortium The MSM program: web-based statistics package for estimating usual dietary intake using the Multiple Source Method Eur J Clin Nutr 2011 65 1 S87 891 22 22 Laureano GH, Torman VB, Crispim SP, Dekkers ALM, Camey SA. Comparison of the ISU, NCI, MSM, and SPADE Methods for estimating usual intake: a simulation study of nutrients consumed daily. Nutrients. 2016;8(3):166. Laureano GH Torman VB Crispim SP Dekkers ALM Camey SA Comparison of the ISU, NCI, MSM, and SPADE Methods for estimating usual intake: a simulation study of nutrients consumed daily Nutrients 2016 8 3 166 166 23 23 Martins BG, Ricardo CZ, Machado PP, Rauber F, Azeredo CM, Levy RB. Fazer refeições com os pais está associado à maior qualidade da alimentação de adolescentes brasileiros. Cad Saude Publica. 2019;35(7):e00153918. https://doi.org/10.1590/0102-311X00153918 Martins BG Ricardo CZ Machado PP Rauber F Azeredo CM Levy RB Fazer refeições com os pais está associado à maior qualidade da alimentação de adolescentes brasileiros Cad Saude Publica 2019 35 7 e00153918 10.1590/0102-311X00153918 24 24 Tavares LF, Castro IRR, Levy RB, Cardoso LO, Passos MD, Brito FSB. Validade relativa de indicadores de práticas alimentares da Pesquisa Nacional de Saúde do Escolar entre adolescentes do Rio de Janeiro. Cad Saude Publica. 2014;30(5):1029-41. Tavares LF Castro IRR Levy RB Cardoso LO Passos MD Brito FSB Validade relativa de indicadores de práticas alimentares da Pesquisa Nacional de Saúde do Escolar entre adolescentes do Rio de Janeiro Cad Saude Publica 2014 30 5 1029 1041 25 25 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. 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 9 660 667 26 26 Wu YT, Nielsen DH, Cassady SL, Cook JS, Janz KF, Hansen JR. Cross-validation of bioelectrical impedance analysis of body composition in children and adolescents. Phys Ther. 1993;73(5):320-28. Wu YT Nielsen DH Cassady SL Cook JS Janz KF Hansen JR Cross-validation of bioelectrical impedance analysis of body composition in children and adolescents Phys Ther 1993 73 5 320 328 27 27 Lohman TG. The use of skinfold to estimate body fatness on children and youth. J Phys Educ Recreat Dance. 1987;58:98-103. Lohman TG. The use of skinfold to estimate body fatness on children and youth J Phys Educ Recreat Dance 1987 58 98 103 28 28 World Health Organization. Waist circumference and waist-hip ratio. Report of a WHO Expert Consultation. Geneva: Organization; 2008 [cited 2020 June 15]. Available from: https://apps.who.int/iris/bitstream/handle/10665/44583/9789241501491_eng.pdf?ua=1 World Health Organization Waist circumference and waist-hip ratio. Report of a WHO Expert Consultation Geneva Organization 2008 2020 June 15 Available from: https://apps.who.int/iris/bitstream/handle/10665/44583/9789241501491_eng.pdf?ua=1 29 29 Bacopoulou F, Efthymiou V, Landis G, Rentoumis A, Chrousos GP. Waist circumference, waist-to-hip ratio and waist-to-height ratio reference percentiles for abdominal obesity among Greek adolescents. BMC Pediatr. 2015;15:1-9. http://doi.org/10.1186/s12887-015-0366-z Bacopoulou F Efthymiou V Landis G Rentoumis A Chrousos GP Waist circumference, waist-to-hip ratio and waist-to-height ratio reference percentiles for abdominal obesity among Greek adolescents BMC Pediatr 2015 15 1 9 10.1186/s12887-015-0366-z 30 30 International Diabetes Federation. The IDF consensus definition of the metabolic syndrome in children and adolescents. Brussels: IDF; 2007 [cited 2020 June 15]. Available from: https://www.idf.org/e-library/consensus-statements/61-idf-consensus-definition-of-metabolic-syndrome-in-children-and-adolescents.html International Diabetes Federation The IDF consensus definition of the metabolic syndrome in children and adolescents Brussels IDF 2007 2020 June 15 Available from: https://www.idf.org/e-library/consensus-statements/61-idf-consensus-definition-of-metabolic-syndrome-in-children-and-adolescents.html 31 31 Matsudo S, Araújo T, Matsudo V, Andrade D, Andrade E, Oliveira LC, et al. International physical activity questionnaire (IPAQ): study of validity and reliability in Brazil. Rev Bras Ativ Fis Saúde. 2001;6(2):5-18. Matsudo S Araújo T Matsudo V Andrade D Andrade E Oliveira LC International physical activity questionnaire (IPAQ): study of validity and reliability in Brazil Rev Bras Ativ Fis Saúde 2001 6 2 5 18 32 32 Guedes DP, Lopes CC, Guedes JERP. Reproducibility and validity of the International Physical Activity Questionnaire in adolescents. Rev Bras Med Esporte. 2005;11:151-8. Guedes DP Lopes CC Guedes JERP Reproducibility and validity of the International Physical Activity Questionnaire in adolescents Rev Bras Med Esporte 2005 11 151 158 33 33 World Health Organization. Who guidelines on physical activity and sedentary behaviour. Geneva: Organization; 2020 [cited 2020 June 15]. Available from: https://www.who.int/publications/i/item/9789240015128 World Health Organization Who guidelines on physical activity and sedentary behaviour Geneva Organization 2020 2020 June 15 Available from: https://www.who.int/publications/i/item/9789240015128 34 34 Passos MHP, Silva HA, Pitangui ACR, Oliveira VMA, Lima AS, Araújo RC. Reliability and validity of the Brazilian version of the Pittsburgh Sleep Quality Index in adolescents. J Pediatr. 2017;93(2):200-6. Passos MHP Silva HA Pitangui ACR Oliveira VMA Lima AS Araújo RC Reliability and validity of the Brazilian version of the Pittsburgh Sleep Quality Index in adolescents J Pediatr. 2017 93 2 200 206 35 35 Hirshkowitz M, Whiton K, Albert SM, Alessi C, Bruni O, DonCarlos L, et al. National Sleep Foundation’s updated sleep duration recommendations: final report. Sleep Health. 2015;1(4):233-43. Hirshkowitz M Whiton K Albert SM Alessi C Bruni O DonCarlos L National Sleep Foundation’s updated sleep duration recommendations: final report Sleep Health 2015 1 4 233 243 36 36 Victora CG, Huttly RS, Fuchs SC, Olinto MT. The role of conceptual frameworks in epidemiological analysis: a hierarchical approach. J Epidemiol. 1997;26(1):224-7. Victora CG Huttly RS Fuchs SC Olinto MT The role of conceptual frameworks in epidemiological analysis: a hierarchical approach J Epidemiol 1997 26 1 224 227 37 37 Fuchs SC, Victora CG, Fachel J. Modelo hierarquizado: uma proposta de modelagem aplicada à investigação de fatores de risco para diarréia grave. Rev Saude Publica. 1996;30(2):168-78. Fuchs SC Victora CG Fachel J. Modelo hierarquizado: uma proposta de modelagem aplicada à investigação de fatores de risco para diarréia grave Rev Saude Publica 1996 30 2 168 178 38 38 Dahlgren G, Whitehead M. Policies and Strategies to Promote Social Equity in Health Stockholm. Stockholm: Institute for Future Studies; 1991. Dahlgren G Whitehead M. Policies and Strategies to Promote Social Equity in Health Stockholm Stockholm Institute for Future Studies 1991 39 39 Alexandre VP, Peixoto MRG, Schmitz BAS, Moura EC. Fatores associados às práticas alimentares da população adulta de Goiânia, Goiás, Brasil. Rev Bras Epidemiol. 2014;17:267-80. Alexandre VP Peixoto MRG Schmitz BAS Moura EC Fatores associados às práticas alimentares da população adulta de Goiânia, Goiás, Brasil Rev Bras Epidemiol 2014 17 267 280 40 40 Barufaldi LA, Abreu GZ, Oliveira JS, Santos DF, Fujimori E, Vasconcelos SML, et al. ERICA: prevalência de comportamentos alimentares saudáveis em adolescentes brasileiros. Rev Saude Publica. 2016;50(1):6s. Barufaldi LA Abreu GZ Oliveira JS Santos DF Fujimori E Vasconcelos SML ERICA: prevalência de comportamentos alimentares saudáveis em adolescentes brasileiros Rev Saude Publica 2016 50 1 6s 6s 41 41 Simões AM, Machado CO, Hofelmann DA. Associação do consumo regular de café da manhã e comportamentos relacionados à saúde em adolescentes. Cien Saude Colet. 2019 [cited 2021 July 20]. Available from: http://www.cienciaesaudecoletiva.com.br/artigos/associacao-do-consumo-regular-de-cafe-da-manha-e-comportamentos-relacionados-a-saude-em-adolescentes/17315?id=17315 Simões AM Machado CO Hofelmann DA Associação do consumo regular de café da manhã e comportamentos relacionados à saúde em adolescentes Cien Saude Colet 2019 2021 July 20 Available from: http://www.cienciaesaudecoletiva.com.br/artigos/associacao-do-consumo-regular-de-cafe-da-manha-e-comportamentos-relacionados-a-saude-em-adolescentes/17315?id=17315 42 42 Azeredo CM, Rezende LF, Canella DS, Claro RM, Castro IRR, Luiz OC, et al. Dietary intake of Brazilian adolescents. Public Health Nutr. 2015;18(7):1215-24. Azeredo CM Rezende LF Canella DS Claro RM Castro IRR Luiz OC Dietary intake of Brazilian adolescents Public Health Nutr 2015 18 7 1215 1224 43 43 Buchmann C. Measuring family background in international studies of education: conceptual issues and methodological challenges. In: National Research Council. Methodological advances in cross-national surveys of educational achievement. Washington: The National Academies Press; 2002. Buchmann C. Measuring family background in international studies of education: conceptual issues and methodological challenges National Research Council. Methodological advances in cross-national surveys of educational achievement Washington The National Academies Press 2002 44 44 Lazzeri G, Ahluwalia N, Niclasen B, Pammolli A, Vereecken C, Rasmussen M, Pedersen TP, et al. Trends from 2002 to 2010 in daily breakfast consumption and its socio-demographic correlates in adolescents across 31 countries participating in the HBSC study. Plos One. 2016;11:e0151052. https://doi.org/10.1371/journal.pone.0151052 Lazzeri G Ahluwalia N Niclasen B Pammolli A Vereecken C Rasmussen M Pedersen TP Trends from 2002 to 2010 in daily breakfast consumption and its socio-demographic correlates in adolescents across 31 countries participating in the HBSC study Plos One 2016 11 e0151052 10.1371/journal.pone.0151052 45 45 Rampersaud GC, Pereira MA, Girard BL, Adams J, Metzl JD. Breakfast habits, nutritional status, body weight, and academic performance in children and adolescents. J Am Diet Assoc. 2005;105(5):743-60. Rampersaud GC Pereira MA Girard BL Adams J Metzl JD Breakfast habits, nutritional status, body weight, and academic performance in children and adolescents J Am Diet Assoc. 2005 105 5 743 760 46 46 Hallström L, Vereecken CA, Ruiz JR, Patterson E, Gilbert CC, Catasta G. Breakfast habits and factors influencing food choices at breakfast in relation to socio-demographic and family factors among European adolescents. The HELENA Study. Appetite. 2011;56(3):649-57. Hallström L Vereecken CA Ruiz JR Patterson E Gilbert CC Catasta G. Breakfast habits and factors influencing food choices at breakfast in relation to socio-demographic and family factors among European adolescents The HELENA Study Appetite 2011 56 3 649 657 47 47 Moreno-Maldonado C, Ramos P, Moreno C, Rivera F. How family socioeconomic status, peer behaviors, and school-based intervention on healthy habits influence adolescent eating behaviors. Sch Psychol Int. 2018;39(1):92-118. Moreno-Maldonado C Ramos P Moreno C Rivera F. How family socioeconomic status, peer behaviors, and school-based intervention on healthy habits influence adolescent eating behaviors Sch Psychol Int 2018 39 1 92 118 48 48 Silva FA, Candiá SM, Pequeno MS, Sartorelli DS, Mendes LL, Oliveira RMS, et al. Frequência de refeições diárias e variáveis associadas em crianças e adolescentes. J Pediatr. 2017;93(1):79-86. Silva FA Candiá SM Pequeno MS Sartorelli DS Mendes LL Oliveira RMS Frequência de refeições diárias e variáveis associadas em crianças e adolescentes J Pediatr 2017 93 1 79 86 49 49 Tavares LF, Castro IRR, Levy RB, Cardoso LO, Claro RM. Padrões alimentares de adolescentes brasileiros: resultados da Pesquisa Nacional de Saúde do Escolar (PeNSE). Cad Saude Publica. 2014;30(12):2679-90. Tavares LF Castro IRR Levy RB Cardoso LO Claro RM. Padrões alimentares de adolescentes brasileiros: resultados da Pesquisa Nacional de Saúde do Escolar (PeNSE) Cad Saude Publica 2014 30 12 2679 2690 50 50 Ramsay SA, Bloch TD, Marriage B, Shriver LH, Spees CK, Taylor CA. Skipping breakfast is associated with lower diet quality in young US children. Eur J Clin Nutr. 2018;72(4):548-56. Ramsay SA Bloch TD Marriage B Shriver LH Spees CK Taylor CA. Skipping breakfast is associated with lower diet quality in young US children Eur J Clin Nutr 2018 72 4 548 556 51 51 Medin AC, Myhre JB, Diep LF, Anderson LF. Diet quality on days without breakfast or lunch – Identifying targets to improve adolescents’ diet. Appetite. 2019;135:123-30. Medin AC Myhre JB Diep LF Anderson LF. Diet quality on days without breakfast or lunch – Identifying targets to improve adolescents’ diet Appetite 2019 135 123 130 52 52 Ali RA, Abdel NMR, Al-Kloub MI, Alzoubi FA. Predictors of breakfast skipping among 14 to 16 years old adolescents in Jordan: The influential role of mothers. Int J Nurs Pract. 2019;25(6):e12778. https://doi.org/10.1111/ijn.12778 Ali RA Abdel NMR Al-Kloub MI Alzoubi FA. Predictors of breakfast skipping among 14 to 16 years old adolescents in Jordan: The influential role of mothers Int J Nurs Pract 2019 25 6 e12778 10.1111/ijn.12778 53 53 Fiuza RFP, Muraro AP, Rodrigues PRM, Sena EMS, Ferreira MG. Skipping breakfast and associated factors among Brazilian adolescentes. Rev Nutr. 2017;30(5):615-26. Fiuza RFP Muraro AP Rodrigues PRM Sena EMS Ferreira MG Skipping breakfast and associated factors among Brazilian adolescentes Rev Nutr 2017 30 5 615 626 54 54 Marchioni DML, Gorgulho BM, Teixeira JA, Verly Junior E, Fisberg RM. Prevalence of breakfast omission and associated factors among adolescents in São Paulo: ISA-Capital. Nutr Rev Soc Bras Aliment Nutr. 2015;40(1):10-20. Marchioni DML Gorgulho BM Teixeira JA Verly E Junior Fisberg RM Prevalence of breakfast omission and associated factors among adolescents in São Paulo: ISA-Capital Nutr Rev Soc Bras Aliment Nutr 2015 40 1 10 20 55 55 Affenito SG, Thompson DR, Barton BA, Franko DL, Daniels SR, Obarzanek E, et al. Breakfast consumption by African-American and white adolescent girls correlates positively with calcium and fiber intake and negatively with Body Mass Index. J Am Diet Assoc. 2005;105(6):938-45. Affenito SG Thompson DR Barton BA Franko DL Daniels SR Obarzanek E Breakfast consumption by African-American and white adolescent girls correlates positively with calcium and fiber intake and negatively with Body Mass Index J Am Diet Assoc 2005 105 6 938 945 56 56 Hassan BK, Cunha DB, Veiga GV, Pereira RA, Sichieri R. Changes in breakfast frequency and composition during adolescence: the Adolescent Nutritional Assessment Longitudinal Study, a cohort from Brazil. Plos One. 2018;1:e0200587. https://doi.org/10.1371/journal.pone.0200587 Hassan BK Cunha DB Veiga GV Pereira RA Sichieri R. Changes in breakfast frequency and composition during adolescence: the Adolescent Nutritional Assessment Longitudinal Study, a cohort from Brazil Plos One 2018 1 e0200587 10.1371/journal.pone.0200587 57 57 Malta DC, Stopa SR, Santos MAS, Andrade SSCA, Oliveira MM, Prado RR, et al. Fatores de risco e proteção de doenças e agravos não transmissíveis em adolescentes segundo raça/cor: Pesquisa Nacional de Saúde do Escolar. Rev Bras Epidemiol. 2017;20(2):247-59. Malta DC Stopa SR Santos MAS Andrade SSCA Oliveira MM Prado RR Fatores de risco e proteção de doenças e agravos não transmissíveis em adolescentes segundo raça/cor: Pesquisa Nacional de Saúde do Escolar Rev Bras Epidemiol 2017 20 2 247 259