The prevalence of obesity and cardiometabolic disorders are increasing among children and adolescents [1]. In Brazil, the prevalence of overweight among adolescents has been increasing since the 1980s, reaching 25% [1]. Additionally, one in five adolescents has prediabetes [2], and high blood pressure affects approximately 10% of the population [3]. To prevent these risk factors during adolescence is important, as it is associated with a reduced risk of cardiovascular disease, diabetes, and mortality in adulthood [4]. In this context, promoting healthy eating habits is essential as it is a modifiable risk factor in the prevention and management of obesity and other cardiovascular diseases. However, the consumption of ultra-processed foods (UPF) is increasing among adolescents, leading to unhealthy changes in their dietary patterns [5].

According to the NOVA classification [6], UPF are industrially developed products that have high energy density and elevated levels of saturated fats, trans fats, refined starches, simple sugars, salt, as well as additives such as dyes, stabilizers, and flavor enhancers [6]. According to the 2008–2009 Brazilian Household Budget Survey, 14.3% of energy consumption was attributed to UPF [7] and, a decade later, this percentage increased to 19.4% [8]. Brazilian adolescents have an even higher consumption of UPF, with studies indicating that they obtain between 28% and 39.7% of their daily caloric intake from UPF [9, 10].

However, few studies have investigated the association between increased UPF consumption, especially among adolescents, and cardiometabolic outcomes [11]. Even though, higher UPF intake in children and adolescents is associated to increased rates of overweight [12], dyslipidemia [13], metabolic syndrome [14], and inadequate intake of vitamins and minerals [15]. These studies often have small sample sizes, different methodologies to assess food consumption, and lack a standardized classification of food processing degree [14, 15].

Our study aims to fill this research gap by utilizing data from a representative sample of Brazilian adolescents. Therefore, our objective is to investigate the association between UPF consumption, based on the NOVA classification, and cardiometabolic risk factors in adolescents.


Study design and sampling

The Study of Cardiovascular Risk in Adolescents (Estudo de Riscos Cardiovasculares em Adolescentes–ERICA) is a national, multicenter, school-based, and cross-sectional study conducted from 2013 to 2014. The sample included adolescents aged 12 to 17 years living in Brazilian cities with a population of more than 100,000 inhabitants. The sample was stratified into 32 geographic strata, which included the 27 capitals, the Federal District, and five additional strata comprising cities with more than 100,000 inhabitants from each region of Brazil (North, Northeast, South, Southeast, and Midwest). In each stratum, schools were selected proportionally based on the number of students enrolled from the seventh year of elementary school to the third year of high school, and inversely to the distance between the school and the state capital. Within each school, three combinations of school year and shift (morning or afternoon) were selected participation in this study. All students from the selected classes were invited to participate in the study [16].

ERICA was conducted in accordance with the principles outlined in the Declaration of Helsinki. Adolescents who agreed to participate completed an assent form. An informed consent form signed by the adolescent’s legal guardian was also requested. The ERICA was approved by the Research Ethics Committees of all participating centers.

The analyzed sample comprised 36,952 adolescents aged 12–17 years, attending public and private schools in the morning shift (Fig. 1). All adolescents who completed the questionnaires and food recall and participated in the anthropometric assessment and blood collection, were included in this study. Pregnant adolescents and those with permanent or temporary physical limitations or mental impairments that hindered their participation in the study were excluded from the analysis. The details of the sampling procedures and study design have been previously published [16, 17].

Fig. 1
figure 1

Flowchart of eligible adolescents for this study.

Food consumption assessment

Food consumption was assessed through an interview format conducted by trained researchers using a 24-h food recall (24hR). This recall was administered using a software developed for the study [18]. The software included a list of 1,626 foods, previously used by the Brazilian Institute of Geography and Statistics (IBGE) in the National Food Survey (INA) and Family Budget Survey (POF 2002–2003) [19]. The 24hR was implemented following the multiple pass method [20], which allowed for detailed information on food preparation and estimation of consumption using pre-defined household measures. The nutritional composition of each food was determined using the Brazilian food composition table [21], and conversion to grams was performed to enhance the reliability of the estimated daily energy intake based on the food composition table [21].

To assess UPF consumption in the sample, the NOVA food classification system was utilized [6]. The NOVA categorizes food into four distinct groups based on the extent and purpose of processing: (1) In natura or minimally processed (foods that have undergone no changes to their composition or have undergone basic process such as cleaning, selection, and portioning without addition of other substances); (2) Culinary ingredients (natural ingredients like sugar, salt, oils, and fats used to enhance flavor in preparations without food additives); (3) Processed (foods that have undergone some processing and had culinary ingredients added during their manufacturing process, such as jellies, jams and homemade cookies); (4) Ultra-processed (foods that have undergone an extensive processing, involving the addition of substantial amounts of additives such as colorings, preservatives, flavor enhancers, sweeteners, and chemical stabilizers, which contribute to enhanced palatability and extended shelf life).

The culinary preparations and ingredients reported in the 24hR were classified according to the aforementioned categorization. Two independent researchers performed this classification, and any disagreements were resolved by a third researcher [9]. The daily energy percentage derived from UPF was calculated and then categorized into consumption tertiles as follows: T1 < 18.6% kcal/day; T2 = 18.6 to 38.7% kcal/day; and T3 > 38.7% kcal/day.

Anthropometric and laboratory assessment

Anthropometric assessment was performed by trained researchers in a reserved place at the schools. Adolescents were oriented to wear the study uniform and to remove their shoes. Weight was measured using a digital scale (model P150m, 200 kg capacity, Líder®, São Paulo, Brazil), and height was measured using a portable stadiometer (Alturexata®, Minas Gerais, Brazil). The body mass index (BMI) was calculated dividing weight (kg) by the square of the body height (m²). The nutritional status was classified according to age- and sex-specific curves reference created by the World Health Organization (WHO) [22]. For the analysis, the categories were grouped into normal weight (BMI Z score ≤ 1), overweight (BMI Z score > 1 and ≤2), and obesity (BMI Z score > 2).

In this study, only students from the morning shift (n = 36,952) were chosen because overnight fasting was necessary to collect the blood samples [23, 24]. Their lipid and glycemic profile were assessed. The cutoff points used to define changes in each variable were as follows: high total cholesterol ≥170 mg/dl; [25] low HDL cholesterol (HDL-c) <45 mg/dl; [25] elevated LDL cholesterol (LDL-c) ≥130 mg/dl; [25] elevated triglycerides ≥130 mg/dl; [25] high fasting glucose ≥100 mg/dl; [26] elevated glycated hemoglobin (Hb1Ac) ≥ 5.7%; [26] elevated HOMA-IR for girls > 2.32 and for boys > 2.87 [27].

Participants’ blood pressure was measured using an oscillometric digital monitor (Omron 705-IT) validated for adolescents [28]. Three measurements were taken, with a three-minute interval between each measurement. All measurements were conducted on the participant’s right arm, using an appropriately sized cuff. Throughout the measurements, participants remained seated with their feet on the floor. For analysis, the average of the last two measurements was calculated. Blood pressure was classified as elevated when the values were ≥ the 95th percentile for sex, age, and height [29].


The questionnaire data were self-completed by the adolescents using a Personal Digital Assistant (PDA). The covariates investigated in this study included sex, age (recorded in complete years and later categorized into age groups), geographic region (North, Northeast, Southeast, South, Midwest), skin color (“White,” “Brown,” “Black,” and others), and school type (public or private). Smoking status was assessed using a simple question: “Do you currently smoke?,” with “yes” or “no” as response options. Physical activity levels (active ≥60 min/day or inactive <60 min/day) were evaluated based on the amount of time reported by the participants for activities practiced over a week [30]. Screen time was assessed by asking the question: “On a typical weekday, how many hours do you spend using the computer, watching TV, or playing video games?” The responses were categorized as ≤2 h/day or >2 h/day [31].

The socioeconomic level was assessed using the ABEP Brazil criterion, which considers the family goods, the presence of a house cleaner, and the education of the head of the family [32]. The score obtained can range from zero to 46 points, with a higher score indicating a better economic condition. For analysis, this score was classified into the following classes: A = 35–46; B = 23–34; C = 14–22; D and E = 0–13 points.

Data analysis

All the variables analyzed were described using the mean or proportion along with their respective 95% confidence intervals (95%CI) for the total sample and stratified by tertiles of UPF consumption. The prevalence of cardiometabolic risk factors across of UPF consumption tertiles was investigated using Wald’s test for trends. Heterogeneity was assessed by the non-overlapping of 95%CI, and statistical significance was represented by p value < 0.05.

Poisson regression models were utilized to test the association between tertiles of UPFs consumption and cardiovascular risk factors. The use of Poisson regression, as opposed to other models, provides accurate estimates of prevalence ratios, which are more easily interpretable for non-specialists compared to odds ratios [33]. The prevalence ratios (PR) and their 95%CI were presented in hierarchical models that involved four levels of adjustment: sex, age, type of school, country region, and skin color (Model 1); Model 1 plus level of physical activity, smoking, and screen time (Model 2); Model 2 plus total energy consumption (Model 3); Model 3 plus BMI (Model 4). In the majority of cases, variables were categorized and included in the models, except for age (years), total energy consumption (kcal), and BMI z-score. The selection of variables for inclusion in the models was based on the literature. Once included, the variables remained in the models, and those corresponding to the subsequent adjustment level were added.

All analyses were conducted using Stata software, version 14.0 (StataCorp, TX, USA). The “svy” commands were employed to account for the complex sample design and to ensure representation of the entire population of Brazilian adolescents included in the study [16].


Table 1 presents the description of the studied sample. This sample consisted 36,952 adolescents, mostly females, with ages ranging from 15 to 17 years. The mean of UPF consumption was 30.7% (95%CI: 29.7–31.6) of the daily energy intake. The girls and those with higher economic status reported higher consumption of UPF, whereas students from the Northern region reported lower consumption. Additionally, participants who spent more than two hours per day in front of screens, were physically inactive, and had normal weight, also reported higher UPF consumption (Table 1).

Table 1 Characteristics of the sample of 36,952 adolescents (12 to 17 years) participating in the ERICA 2013–2014 included in the study.

The most consumed UPFs were cookies and soft drinks, while the least consumed were margarine, ready-made sauces and snacks (Table 2). Table 3 provides the mean intake of macro and micronutrients based on each tertile of UPF consumption. Adolescents in the highest tertile of UPF consumption, who consume more than 38.7% of their daily calories from these foods, showed higher intake of carbohydrates, sodium, saturated and trans fats, and lower intake of proteins, fibers, polyunsaturated fats, vitamins, and minerals compared to adolescents in the lower consumption tertiles, regardless of the total energy consumption.

Table 2 Food groups relative contribution (%) according to the NOVA classification and the main foods of the ultra-processed group regarding to the total caloric intake of adolescents in ERICA (n = 36,952), Brazil, 2013–2014.
Table 3 Adjusted means of nutrient intake by energy (grams) according to ultra-processed foods intake tertiles. ERICA 2013–2014.

Figure 2 illustrates the frequency of change in cardiometabolic risk factors based on UPF consumption tertiles. The prevalence of elevated LDL-c (4.5%, 95%CI 3.8–5.5) is higher among adolescents who consume a higher proportion of calories from UPF, while the prevalence of alteration in HDL-c (43.5%, 95%CI 40.9–46.1) decreases as UPF consumption increases. The prevalence of alterations in HOMA-IR (27.0%, 95%CI 24.7–29.5) is higher among individuals with intermediate UPF consumption. No significant changes in the prevalence of alterations were observed for others cardiometabolic risk factors such as total cholesterol, triglycerides, fasting glucose, and Hb1Ac, in relation to UPF consumption.

Fig. 2: Overall and change frequency in cardiovascular risk variables according to tertiles of consumption of ultra-processed foods in adolescents from ERICA (n = 36,952), Brazil, 2013–2014.
figure 2

ERICA: Study of Cardiovascular Risks in Adolescents; high total cholesterol ≥170 mg/dl; low HDL-c < 45 mg/dl; high LDL-c ≥ 130 mg/dl; high triglycerides ≥130 mg/dl; high fasting glucose ≥100 mg/dl; high Hba1c ≥ 5.7%; high HOMA-IR: girls > 2.32 and boys > 2.87; high blood pressure ≥ p95th, and high body mass index z-score >1.

In the analysis using the final adjusted model (Model 4), we observed a positive association between higher UPF consumption and altered LDL-c (PR = 1.017; 95%CI = 1.005–1.029) (Table 4). Additionally, an inverse association was observed between higher UPF consumption and low HDL-c (PR = 0.972; 95%CI = 0.952–0.993). In the partially adjusted models (Model 1 and 2), high blood pressure (PR = 0.878; 95%CI = 0.801–0.963) and overweight/obesity (PR = 0.961; 95%CI = 0.934–0.988) showed an inverse association with UPF consumption. However, we did not observe this association when the models are adjusted for BMI and total caloric consumption, respectively (Table 4). No significant associations were found between UPF consumption and the other cardiovascular risk factors. Similar results were obtained when evaluating a 10% increase in UPF consumption for each analyzed cardiometabolic risk factor, rather than using tertile categories (Supplementary Table 1).

Table 4 Prevalence ratios for cardiovascular risk variables according to ultra-processed foods consumption tertiles in adolescents from ERICA (n = 36,952), Brazil, 2013–2014.


In total, UPF account for 30% of the total daily calorie intake among Brazilian adolescents. A high consumption of UPF is associated with increased intake of sodium, saturated and trans fats, and decreased intake of protein, fiber, vitamins, and minerals. After adjusting for confounding variables, we found that elevated LDL-c levels were the cardiometabolic risk factor directly associated with UPF consumption. Additionally, we observed an inverse association between UPF consumption and HDL-c levels.

A systematic review [34] also reported an association between increase consumption of UPF and elevated LDL-c levels in adolescents. It appears that the saturated and trans fats present in UPFs are associated with a proatherogenic lipid profile [35]. High consumption of saturated fats has been shown to increase LDL-c concentrations [36]. As a result, it is recommended to limit their consumption of saturated fats to 10% of the total caloric intake [37]. In our study, adolescents in the highest tertile of UPF consumption had an mean of saturated fat intake that represented more than 12% of their total caloric intake, which may contribute to the alteration in LDL-c levels. On the other hand, trans fats not only lead to increased LDL-c levels but are also associated with reduced HDL-c concentrations [37, 38].

Our findings regarding the association between UPF consumption and low HDL-c levels differ from previous studies [39,40,41] as we observed a protective factor among those with higher UPF consumption. These contrasting results can be partially explained by the age of our study participants, who had been exposed to the consumption of UPF for a shorter duration, which might not have been sufficient to significantly impact HDL-c levels. Moreover, adolescents with higher UPF consumption in our study exhibited favorable characteristics associated with a higher prevalence of high HDL-c levels, such as being female, having low/normal weight, being non-smoker, and engaging in physical active for more than 420 min per week. Furthermore, it is important to consider that HDL-c levels have a significant genetic contribution [42], and variations in population characteristics have been documented [43, 44], suggesting that the cutoff points defining low and high levels of HDL-c may vary. Another hypothesis to consider is that the association observed could be due to a higher consumption of fats contained in UPFs, which in turn could lead to increased intake of monounsaturated and polyunsaturated fatty acids, resulting in higher HDL-c levels. However, further studies are needed to investigate the relationship between UPF consumption and lipid profiles in order to provide more clarify on this issue.

Literature reviews, primarily based on cross-sectional studies, indicate that high consumption of UPF is associated with increased body weight [45,46,47,48] and a higher prevalence of overweight and obesity [49]. However, findings from a longitudinal study, the Estudo Longitudinal de Avaliação Nutricional de Adolescentes (ELANA), involving 1,039 Brazilian adolescents followed for three years to assess the impact of UPF consumption on adiposity indicators, did not confirm the hypothesis that high UPF consumption is associated with weight gain in adolescents [50]. In our study, the association between UPF consumption and overweight/obesity remained non-significant after adjusting for total energy intake. It is worth noting that research suggests that young individuals with excess body fat tend to underestimate their caloric intake [51], which may be particularly true when it comes to UPF. Due to their convenience and easy consumption, teenagers may not accurately account for their intake of these foods, which can hinder weight loss efforts. Finally, the data collected in ERICA do not provide information on the adolescents’ specific dietary practices at the time of the study, preventing us from evaluating the hypothesis that lower UPF consumption among adolescents with excess weight is due to dietary modifications.

Our study found no association between UPF consumption and most cardiometabolic risk factors analyzed. We highlight that the short time of UPF exposure and the expectation that most adolescents have a healthy cardiometabolic profile may have contributed to our results. However, unhealthy habits beginning in adolescence can continue into adulthood, and long-term exposure can hinder adulthood healthiness [52,53,54,55,56,57,58]. The long-term use of food additives in UPFs can have a negative impact on health. Studies have shown that these additives can lead to changes in the satiety mechanism, insulin resistance, and inflammation of the intestinal mucosa [59, 60]. This, in turn, can promote an increase in intestinal permeability and other disorders, leading to impaired immune system function, dyslipidemias, and disruption of hormonal regulation [61]. These effects can intensify the systemic inflammatory process and may be linked to the development of cardiovascular disease, related to weight gain, oxidative stress, and inflammation [62, 63]. Additionally, the increase in UPF consumption can lead to a consequent reduction of in natura and minimally processed foods consumption, which are essential for a diet rich in vitamins, minerals, and fiber [64].

Our observations may have implications for public health since UPF consumption corresponds to an average of 1/3 of the calories consumed by adolescents. A diet imbalance and an increase in the high LDL-c prevalence occur among those with higher UPFs consumption. Longitudinal studies reinforce the importance of reducing the consumption of nutrients found in UPF, such as sodium [65] and saturated fats [66], to prevent cardiovascular disease and to control LDL-c levels [67]. Thus, strategies to limit consumption of UPFs, such as taxation, regulations on the sale, marketing rules, labeling, and limited supply in schools have already proven effective in some countries [68] and studies aiming to establish an acceptable range of UPF consumption among adolescents should be encouraged since UPF consumption tends to remain part of the diet of most individuals, tending to increase over time in the absence of interventions.

The strengths of our study include the sample of Brazilian adolescent population from the entire country, which was interviewed by trained researchers to minimize measurement errors. Additionally, all biochemical analyses were performed in a single laboratory. However, there are also some limitations to report. Firstly, we relied on data from a single 24hR, which may have resulted in a report of food consumption that deviates from the participants’ usual diet. Secondly, we did not evaluate weekend consumption, which could lead to an underestimation of UPF consumption. Furthermore, when participants provided reports of culinary preparations, we were unable to specify the quantities of each ingredient used, although we used illustrations of homemade measurements tests to mitigate imprecision in the reports. Lastly, since this is a cross-sectional study, we cannot rule out the possibility of reverse causality in the associations. However, our hypothesis is that changes in food consumption precede the development of cardiovascular risk factors, with the exception being the presence of overweight/obesity and pre-existing morbidities that can stimulate diets.


Ultra-processed food consumption accounts for approximately one-third of the daily caloric intake among Brazilian adolescents. Those in the highest tertile of UPF consumption reported higher levels of sodium, saturated and trans fats, and lower intake of proteins, fibers, polyunsaturated fats, vitamins, and minerals, indicating a poor dietary pattern. We observed as association between increased UPF consumption and changes in LDL-c levels, but we did not find associations with other cardiometabolic risk factors that were assessed. Further studies are necessary to get a better understanding of the relationship between UPF consumption and health outcomes in adolescents. It is also important to investigate the potential long-term effects of UPF consumption on cardiometabolic health outcomes.