Adolescence, between the ages of 10 and 19, is a challenging transitional period. This period is marked by the search for identity and changes in lifestyle habits, which may include harmful behaviors [1,2]. Between 1975 and 2016, there was an increase in the global prevalence of obesity in youth aged 5 to 19 years; this growth was from 0.7% to 5.6% in females and 0.9% to 7.8% in males [3]; with projection for the year 2022 indicating a continuous growth in the number of overweight people [4]; it is estimated that one billion individuals with obesity will reach this mark by 2030 on a global scale.

The consumption of Ultra-Processed Foods (UPF) emerges as a focal point of concern due to its high consumption, as well as its connection to the development of excess weight and chronic diseases (arterial hypertension, dyslipidemia, type 2 diabetes, atherosclerosis and metabolic syndrome) in adulthood [5,6]. In addition, other risk factors, such as short duration and poor quality of sleep [2], lack of time dedicated to daily physical activity [7], and increased screen time [8], also contribute to the scenario of excess weight growing.

Addressing the prevention of overweight among adolescents requires an in-depth analysis of the determinants, including both socioeconomic and behavioral aspects. This understanding is critical for the development of effective strategies that encourage healthy habits in this changing population [9]. Furthermore, it is important to consider the additional challenges that have arisen due to the Coronavirus Disease 2019 (COVID-19) pandemic, which have had significant impacts on adolescents’ living standards and daily routines.

To assess the prevalence of behavioral factors potentially associated with the nutritional status and their association with excess weight in adolescents during the COVID-19 pandemic.

The study involved a population of 302 adolescents, the majority of whom were female (64.6%), having 16.2 years average age, and who attended different vocational courses offered in the high school. The students were distributed between the 1st, 2nd, and 3rd grades: 31.8%, 36.8%, and 31.4%, respectively. The majority identified themselves as being of white complexion; 72.8% lived in their own homes, located either in the central region or on the outskirts of the city, with a minority living in rural areas. The average family size was 3.94 members, with the majority belonging to families with an income between 1 and 3 minimum wages. Parental education varied, with 42.4% of fathers and 47.4% of mothers having nine to 11 years education, although some students did not know their parents’ education level. With regard to parental obesity, 6.0% of participants reported that both parents were obese, while the same 6.0% mentioned that only the father (7.3%) or only the mother (7.9%) was obese. The proportion of students with obesity (8.9%) or underweight (8.6%) was similar. More than a quarter (28.5%) were overweight (28.7% girls and 28.1% boys). Regarding behaviors that can influence the nutritional status of adolescents, it is noteworthy that 40% of them reported eating meals in front of screens (TV, cell phone, computer) every day of the week. Only 13% stated that they prepared the main meal (lunch) alone. The majority (87.7%) had poor sleep quality, with almost one third (29.9%) sleeping less than 7 hours per night. Regarding physical activity, less than a third (29.8%) met the recommendation of practicing moderate or intense activities for at least 1 hour every day of the week (Table 1).

The most frequently consumed UPF by adolescents were sweet treats, soft drinks, and ultra-processed meats. Approximately half of the adolescents consumed sweet treats and ultra-processed meats in three or more days of the week; soft drinks were consumed on two days, and fast food on one day. The average daily time spent in front of screens was very high: 10.02 hours (SD=3.426), median 10 hours, with a minimum of 1 hour and 30 minutes (1.50) and maximum of 20 hours, adding up the time spent on TV, video games, computers, and cell phones. The medians were higher in overweight (11 hours) and obese (12h45 minutes) students compared to those who were underweight (8h30 minutes) and eutrophic (9h15 minutes). These data are not shown in Tables.

Table 2 shows the frequencies of students with different nutritional statuses (underweight, normal weight, overweight and obesity) in relation to the socioeconomic and demographic variables and parental nutritional status. The frequency of overweight and obesity was higher in adolescents whose mothers had higher education levels (p=0.030). When both parents were not obese, the frequency of overweight students was the lowest, but when only the father was obese, the proportion of obese adolescents was the highest (p-value=0.003).

Table 3 shows the frequencies of students according to nutritional status and different behaviors during meals, sleep quality, physical activity and screen time. It is noteworthy that eating meals in front of a screen every day of the week was associated with a higher prevalence of obesity among students. In addition, the frequency of overweight was higher among students who prepared their own meals at lunch, compared to those who only helped with the preparation. No significant differences were observed in the frequency of overweight between adolescents who followed or not the recommendations for sleep duration. On the other hand, adolescents who spent more time in front of the screen, especially those in the third tertile of total time, exhibited a higher prevalence of overweight and obesity. It is worth noting that the prevalence of overweight was higher among students who met the recommendations for time and frequency of daily physical activity.

Table 3 also shows the weekly frequency with which adolescents had their meals in front of some type of screen (p=0.003), the adequacy of sleep duration (p=0.003) and the total screen time (p=0.003). The variables investigated, according to the established criteria (p<0.20) as possible risk factors for the presence of excess weight included family income and responsibility for preparing the adolescent’s lunch, identified as potential confounding variables.

To assess the specific effect of each variable, a multiple logistic regression model was adjusted, the outcome of which was overweight (yes or no) compared to normal weight. Underweight adolescents were excluded from this analysis. The results are shown in Table 4.

Screen time, maternal education and eating in front of screens were identified as risk factors for overweight. Students in the third tertile had more than three times the chance of being overweight (OR=3.345, 95% CI=1.624-6.890), compared to students in the first tertile. Eating in front of screens 5 or more days a week multiplied the chances of being overweight by 3.25 (OR=3.252; 95% CI=1.628-6.495), compared to students who did not do so.

Adolescents with mothers who had studied more than 8 years had a higher chance of being overweight, while having a mother with less than 8 years education reduced this chance by 62.8% (OR=0.372, 95% CI=0.165–0.838). No relationship was identified between overweight and parents’ obesity and also with sleep time.

All these results are independent of each other and were adjusted for gender, physically active individuals and parental nutritional status; these are variables that did not reach the stipulated statistical significance (p<0.05) to establish an association with excess weight, but were maintained in the model because they were potentially capable of exerting some confounding effect.

This study revealed that, during the COVID-19 pandemic, the majority of adolescent students at a technical school presented habits and behaviors associated with health and nutritional problems [17]. Most of them did not comply with physical activity recommendations and the time spent on screens/electronic devices was very high, greater than the time spent in classes. Eating meals in front of screens was frequent and the quality and quantity of sleep was unsatisfactory for most participants. These results represent a situation of concern: high prevalence of risk factors for chronic non-communicable diseases and obesity in adolescents during the COVID-19 pandemic, corroborating similar findings in an international study [18].

The fact that more than ¼ (28.5%) of adolescents were overweight is a cause for concern. This rate is close to that reported in a study carried out in Spain (23.1%) [19] , but it is lower than that reported in other national studies, carried out before the pandemic period: in the Brazilian Northeast (32.5%) [20]; in the interior of the State of São Paulo (47%) [7]]; reaching 87.2% in studies in Southern Brazil [21].

Eating meals in front of screens 5 or more times a week was shown to be a common practice among students and this habit increased the chance of being overweight by 3.25 times (OR=3.252, 95% CI 1.628-6.495), compared to the students who did not adopt this habit. Data from the Pesquisa Nacional de Saúde do Escolar de 2015 (2015 National School Health Survey) [22] and another Brazilian study [23]] associated unhealthy eating patterns to eating while studying or watching TV; there is a study showing that the habit of eating while browsing the web increases the chance of consuming UPF [24]. It is known that frequent screen use negatively affects eating habits, promoting careless and practical eating trends, contributing to excess weight [24]. On the contrary, mindful eating, the practice of eating with full attention, has been associated with more conscious and healthy food selection, being considered a self-care approach [25].

However, a result that is difficult to interpret was the higher mean consumption of UPF among eutrophic adolescents and, in contrast, the lower mean among obese individuals, suggesting the possibility of reverse causality. Perhaps overweight adolescents were trying to change their diet to lose weight, avoiding foods known to be obesogenic, including UPF. This may explain the lack of an independent association between UPF consumption and overweight in the present study.

Among the UPF, adolescents consumed mainly sweets/treats, consistent with studies carried out during the pandemic including Brazil [26], which highlighted an increase in the consumption of fried foods and sweets [17], especially due to remote education and the psychological stress associated with the pandemic. This may be explained by the fact that these foods are convenient to consume during prolonged periods in front of screens, a common condition during the pandemic.

Although 13% of adolescents prepared their own meals, “instant noodles” were not widely consumed, despite this dish easy preparation. A limitation of the present study was the fact that adolescents were not asked about the type of meals that they prepared. The pandemic has restricted school meal distribution, especially affecting adolescents who relied on them as their main source of healthy nutrition [27]. This occurred at a time of widespread unemployment, poverty and economic hardship [28].

Social isolation and online classes during the pandemic likely resulted in an increase in sedentary behavior, with less than a third (29.8%) adolescents complying with the daily physical activity recommendations. However, there was no association between lack of physical activity and overweight, possibly because social isolation caused a standard sedentary behavior among adolescents, regardless of their previous habits. Still, it is essential to emphasize the importance of physical activity for health after the end of social isolation, indicating the need to promote it again in school health initiatives [29,30],

In this study, the average screen time exceeded 10 hours per day, and adolescents who spent more than 10 hours in front of screens were over three times likely to be overweight. However, the comparison with previous studies outside the pandemic scenario has limitations, since the screen time of all students increased substantially during the period of online classes. In addition, the data may contain some overestimation due to the way screen time was assessed, since the daily time spent on each type of screen device was added together, despite the fact that it is common for the participants to use several screen devices at the same time [31].

Despite these caveats, we observed a positive association between screen time and the risk of becoming overweight, which is consistent with previous studies. Previous research conducted before the pandemic had already identified an increased risk of adolescents who spent more time in front of screens becoming overweight compared to those who spent less time. A study of American adolescents showed that spending ≥4 hours watching TV or playing video games increased the likelihood of becoming overweight by 2.19 times, enhancing the hypothesis that screen time is linked to obesity [23]. In addition to the association with overweight, excessive screen time has also been associated with sleep disorders and unhealthy eating habits, which may explain the connection between more screen time and increased obesity [32].

Before the pandemic, the American Academy of Pediatrics recommended to limit screen exposure up to two hours/day [33], But this guideline has become challenging during the pandemic due to the need for studying online. A study in China revealed that 48.2% of high school students spent more than 5 hours on digital devices for learning purposes [34], despite the recommendation to limit screen time to 4 hours/day for high school students [35]. The increasing digital interaction in daily life, both for academic activities and for leisure, requires a continuous assessment of its repercussions on the health and development of children and adolescents. Excessive screen time was already a concern for health professionals, due to its potential adverse effects on the health and development of children and adolescents, and may actually have become even more frequent after the pandemic.

This study revealed a high rate of adolescents with sleep problems, a condition possibly aggravated during the pandemic by emotional factors and excessive screen time. Lack of sleep is a risk factor for obesity [35] and depression [34]. The finding that 87.7% of the adolescents assessed experienced poor sleep quality, a frequency well above that reported for Chinese adolescents (38.5%) [35], and that 1/3 slept less than 7 hours a night is of concern, since sleeping less than eight to ten hours is also considered a risk factor for obesity [19]. Research has shown that factors such as physical inactivity, excessive screen time and insufficient sleep in adolescents tend to occur simultaneously and are both cause and consequence of each other, especially during the pandemic [36].

It is important to highlight two results not related to adolescents’ behavioral factors. One of them was the identification of social inequality regarding the occurrence of excess weight. Adolescents whose mothers had low levels of education (up to eight years) were less likely to exhibit excess weight. In addition, a study reveals that 22.3% of households with low-level education heads of the household (up to four years of education) faced food insecurity during the COVID-19 pandemic in Brazil [37].

Another result observed was the lack of association between the nutritional status of parents and children. Although a higher frequency of overweight was observed among adolescents whose both parents were obese, and a higher frequency of obesity when only the father was obese, the multivariate analyses were unable to establish an independent relationship between the nutritional status of parents and the presence of excess weight in children. This result contradicts the literature, which suggests a relationship between parental obesity and obesity in children, with studies that detected an increased probability of obesity in adolescents when at least one of the parents was obese and an even greater increase when both were obese [38,39]. The discrepancy observed in the nutritional status of parents may be attributed to the use of less precise information, since parents were not weighed or questioned, but rather the report on whether or not their parents were obese was given by the children.

This finding reflects the complexity of the factors that influence excess weight, suggesting that in addition to the nutritional status of parents, it is necessary to consider sociocultural, psychological and environmental factors that impact the eating behavior and weight of adolescents.

During the COVID-19 pandemic, potentially harmful health behaviors were very common among adolescent students, with emphasis on poor quality and inadequate sleep time, physical inactivity, excessive screen time and the habit of eating meals in front of some type of screen; these last two behaviors were identified as factors that, independently of the others, increase the chances of being overweight. The presence of social inequality in the risk of students being overweight was also evident, with adolescents whose mothers had up to eight years education exhibiting a lower chance of being overweight, when compared to adolescents in other situations.