Frontiers in Nutrition 01 frontiersin.org
Metabolic syndrome, adiposity, 
diet, and emotional eating are 
associated with oxidative stress in 
adolescents
Sonia L. Ramírez-Garza 1, Emily P. Laveriano-Santos 1,2, 
Juan J. Moreno 1,2, Patricia Bodega 3,4, Amaya de Cos-Gandoy 3,4, 
Mercedes de Miguel 3,4, Gloria Santos-Beneit 3,5, 
Juan Miguel Fernández-Alvira 4, Rodrigo Fernández-Jiménez 4,6,7, 
Jesús Martínez-Gómez 4, Ana María Ruiz-León 2,8, 
Ramon Estruch 2,8, Rosa M. Lamuela-Raventós 1,2 and 
Anna Tresserra-Rimbau 1,2*
1 Department of Nutrition, Food Science and Gastronomy, XIA, School of Pharmacy and Food Sciences, 
Institute for Nutrition and Food Safety Research, University of Barcelona, Barcelona, Spain, 2 Consorcio 
CIBER, M.P. Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain, 
3 Foundation for Science, Health and Education, Barcelona, Spain, 4 Centro Nacional de Investigaciones 
Cardiovasculares, Madrid, Spain, 5 The Zena and Michael A. Wiener Cardiovascular Institute, Icahn 
School of Medicine at Mount Sinai, New York, NY, United States, 6 Hospital Universitario Clínico San 
Carlos, Madrid, Spain, 7 Centro de Investigación Biomédica En Red en Enfermedades CardioVasculares, 
Madrid, Spain, 8 Department of Internal Medicine Hospital Clinic, Institut d’Investigacions Biomèdiques 
August Pi i Sunyer, University of Barcelona, Barcelona, Spain
Background: Metabolic syndrome (MS), a condition related to adiposity and 
oxidative stress, can develop in adolescence, a critical stage in life that impacts 
health in adulthood. However, there is scarce scientific research about the 
relationship between lifestyle factors, emotion management, and oxidative stress 
in this phase of life.
Aim: To analyze whether nutritional parameters, lifestyle factors, emotion 
management, and MS in adolescents are associated with oxidative stress 
measured by the biomarker 8-isoprostane.
Methods: A cross-sectional study was carried out in 132 adolescents (48.5% 
girls, aged 12  ±  0.48  years) and data were collected on nutritional parameters 
(anthropometric measurements, biochemical analyzes, and blood pressure), 
lifestyle factors (physical activity, sleep, and diet), and emotion management 
(self-esteem, emotional eating, and mood). 8-isoprostane was analyzed in spot 
urine samples. The study population was categorized in three groups (healthy, 
at-risk, and with MS) using the International Diabetes Federation definition 
of MS in adolescents. To capture more complex interactions, a multiple linear 
regression was used to analyze the association between 8-isoprostane and the 
aforementioned variables.
Results: Urinary 8-isoprostane levels were significantly higher in the MS 
group compared to the healthy group (1,280  ±  543  pg./mg vs. 950  ±  416  pg./
mg respectively). In addition, univariable analysis revealed positive significant 
associations between 8-isoprostane and body mass index, waist circumference, 
waist-to-height ratio, body fat percentage, blood lipid profile and glucose, 
emotional eating, and refined cereal intake. Conversely, a negative significant 
association was found between 8-isoprostane and sleep duration and fish 
OPEN ACCESS
EDITED BY
Ji-Chun Zhang,  
Jinan University, China
REVIEWED BY
Wei Yao,  
Jinan University, China  
Octavian Vasiliu,  
Dr. Carol Davila University Emergency Military 
Central Hospital, Romania  
Henda Jamoussi,  
National Institute of Nutrition and Food 
Technology, Tunisia
*CORRESPONDENCE
Anna Tresserra-Rimbau  
 annatresserra@ub.edu
RECEIVED 03 May 2023
ACCEPTED 15 August 2023
PUBLISHED 12 September 2023
CITATION
Ramírez-Garza SL, Laveriano-Santos EP, 
Moreno JJ, Bodega P, de Cos-Gandoy A, de 
Miguel M, Santos-Beneit G, 
Fernández-Alvira JM, Fernández-Jiménez R, 
Martínez-Gómez J, Ruiz-León AM, Estruch R, 
Lamuela-Raventós RM and 
Tresserra-Rimbau A (2023) Metabolic 
syndrome, adiposity, diet, and emotional eating 
are associated with oxidative stress in 
adolescents.
Front. Nutr. 10:1216445.
doi: 10.3389/fnut.2023.1216445
COPYRIGHT
© 2023 Ramírez-Garza, Laveriano-Santos, 
Moreno, Bodega, de Cos-Gandoy, de Miguel, 
Santos-Beneit, Fernández-Alvira, Fernández-
Jiménez, Martínez-Gómez, Ruiz-León, Estruch, 
Lamuela-Raventós and Tresserra-Rimbau. This 
is an open-access article distributed under the 
terms of the Creative Commons Attribution 
License (CC BY). The use, distribution or 
reproduction in other forums is permitted, 
provided the original author(s) and the 
copyright owner(s) are credited and that the 
original publication in this journal is cited, in 
accordance with accepted academic practice. 
No use, distribution or reproduction is 
permitted which does not comply with these 
terms.
TYPE Original Research
PUBLISHED 12 September 2023
DOI 10.3389/fnut.2023.1216445
Ramírez-Garza et al. 10.3389/fnut.2023.1216445
Frontiers in Nutrition 02 frontiersin.org
intake. The multiple linear regression analysis revealed associations between 
8-isoprostane and LDL-c (β  =  0.173 value of p  =  0.049), emotional eating (low 
β  =  0.443, value of p  =  0.036; high β  =  0.152, value of p  =  0.470), refined cereal 
intake (β =0.191, value of p  =  0.024), and fish intake (β  = −0.187, value of p  =  0.050).
Conclusion: The MS group, LDL-c, emotional eating, and high refined cereals 
and low fish intakes were associated with higher levels of oxidative stress in an 
adolescent population.
KEYWORDS
nutritional status, nutrition assessment, fish, refined cereals, obesity, emotion, anxiety, 
depression
1. Introduction
Adolescence is a critical stage in life, when healthy or risk 
behaviors of adulthood are first established, and social and emotional 
development affects decision-making and behavior (1, 2). The 
development of obesity or cardiovascular diseases can be accompanied 
by the emergence of mental health disorders such as depression, eating 
disorders, and low self-esteem (3, 4). Furthermore, oxidative stress has 
been linked with depression (5, 6), whereas a healthy dietary pattern 
is associated with good mental health (1, 7).
Obesity and metabolic syndrome (MS) are multifactorial diseases 
estimated to affect 5% of the global adolescent population in 2020 (8). 
MS is a cluster of risk factors for cardiovascular disease, type 2 
diabetes, or prediabetes. These conditions include high blood pressure 
(BP), high triglycerides, and abdominal obesity, the latter being the 
key factor for MS diagnosis in adolescents (9). When these 
pathological triggers are present chronically, a dysfunctional 
mitochondria could be developed, which can cause an oxidative stress 
(10, 11), increasing its levels of biomarkers such as 8-isoprostane (12, 
13). Isoprostanes are biosynthesized by a free radical-catalyzed 
peroxidation primarily from arachidonic acid, but also from 
docosahexaenoic and eicosapentaenoic acids (14, 15) and 
8-isoprostane serves as a biomarker of oxidative stress status (16, 17). 
Due to the scant research on the relationship between 8-isoprostane 
and MS in adolescents, it is important to study this research topic and 
its association with factors such as lifestyle, emotion, and nutrition.
The aim of the present study was to analyze the association of 
nutritional parameters, lifestyle, emotion management, and MS with 
oxidative stress, measured by 8-isoprostane levels, in a cohort of 
adolescents enrolled in the SI! Program for Secondary Schools in Spain.
2. Materials and methods
The present cross-sectional analysis was performed in a 
sub-sample of participants enrolled at baseline (1st grade of Secondary 
School) in the SI! Program for Secondary Schools in Spain (clinical 
trials register: NCT03504059); all details have been previously 
published (18). A schematic view of the design and different phases of 
the present study is provided in Supplementary Figure S1.
2.1. Anthropometric measurements
Measurements were obtained after overnight fasting by trained 
nutritionists. Height was measured with a Seca 213 portable 
stadiometer (0.1 cm of precision). Body weight, body fat percentage, 
and skeletal muscle percentage were measured by bioelectrical 
impedance analysis (OMRON BF511 with 0.1 Kg precision), with 
participants wearing light clothes and no shoes. Body mass index 
(BMI) was calculated as body weight divided by height squared (kg/
m2). Waist circumference (WC) was measured three times with a 
Holtain tape to the nearest 0.1 cm. Waist-to-height ratio (WHtR) was 
calculated as WC divided by height. BMI, WC, and WHtR were 
adjusted for age and sex to obtain z-score values (19, 20).
2.2. Biochemical analyzes
Biochemical blood analysis was performed by trained nurses 
using samples taken early in the morning after overnight fasting. 
Glucose, triglycerides, total cholesterol, high density lipoprotein 
cholesterol (HDL-c), and low density lipoprotein cholesterol (LDL-c) 
were determined in capillary blood samples using the Cardio Check 
Plus device and PTS Panels test strips (21). Fasting spot urine samples 
were collected in the morning. The urine was aliquoted and stored at 
−80°C for subsequent analysis. 8-Isoprostane concentration in urine 
was determined using the ELISA Kit protocol (Cayman Chemical, 
Ann Arbor, MI, United  States, Item No. 516351). Creatinine was 
measured by the validated Jaffé alkaline picrate method (22). 
8-Isoprostane levels were normalized by creatinine and the results 
were expressed as pg./mg creatinine.
2.3. Blood pressure
BP was measured with an OMRON M6 monitor with 2–3 min 
intervals between measurements. When the differences between the 
measurements were less than 10 mmHg for systolic blood pressure 
(SBP) and less than 5 mmHg for diastolic blood pressure (DBP), two 
Abbreviations: BMI, body mass index; BP, blood pressure; DBP, diastolic blood 
pressure; EE, emotional eating; HDL-c, high density lipoprotein cholesterol; LDL-c, 
low-density lipoprotein cholesterol; MS, metabolic syndrome; SBP, systolic blood 
pressure; WC, waist circumference; WHtR, waist-to-height ratio.
Ramírez-Garza et al. 10.3389/fnut.2023.1216445
Frontiers in Nutrition 03 frontiersin.org
measurements were taken; otherwise, a third reading was performed. 
Average values were calculated for the final SBP and DBP, which were 
adjusted for age, sex, and height to obtain percentile and z-score 
values (23, 24).
2.4. Physical activity and sleep 
characteristics
Moderate and vigorous physical activity levels and sleep duration 
were estimated from data from the triaxial accelerometer (Actigraph 
wGT3X-BT) worn on the non-dominant wrist for seven consecutive 
days. Activity information was considered valid if data were available 
for a minimum of 4 days, with at least 600 min of wear time per day. 
Physical activity intensities were estimated using the cut-off points of 
Chandler et al. (25). The sleep algorithm proposed by Sadeh et al. (26) 
was used to obtain sleep duration (total of hours asleep), sleep 
efficiency (number of sleep minutes divided by the total number of 
minutes the subject was in bed), awakenings (the number of 
awakenings per night), and time spent awake after initially falling 
asleep (the average length of all awakening episodes in minutes). All 
measurements were obtained using ActiLife software (Version 
6.13.4, LLC).
2.5. Emotion management
To assess emotion management, three different subscales were 
used, namely “self-esteem,” “emotional eating” (EE), and “mood,” 
which were measured through validated questionnaires filled out by 
the participants. Four response categories on the Likert scale were 
used for self-esteem and EE items, and five response categories for 
mood items.
Self-esteem was assessed with five items of the Child Health and 
Illness Profile–Adolescent Edition test (CHIP-AE) (27). An example 
of an item is, “I like the way I am,” to which there are four response 
options: strongly disagree = 1, disagree = 2, agree = 3, and strongly 
agree = 4. Thus, higher scores designate better health-related outcomes. 
The score was obtained by calculating the mean scores. Internal 
reliability (Cronbach’s ⍺) was 0.797.
EE was assessed with three items of the Three-Factor Eating 
Questionnaire-R18 (Tfeq-Sp) (28). An example of an item is, “When 
I feel anxious, I find myself eating,” to which there are four response 
options: definitely false = 1, mostly false = 2, mostly true = 3, and 
definitely true = 4. Higher scores indicate greater levels of EE. Scores 
were categorized as “No EE,” “Low EE,” and “High EE.” The “No EE” 
category reflected a score of 3. To create the “Low EE” and “High EE” 
categories, a median split was used (excluding the “No” category), and 
scores below the median were categorized as “Low EE” and scores 
above the median as “High EE” (4). Internal reliability (Cronbach’s ⍺) 
was 0.791.
Mood was assessed with a six items of the validated FRESC 
(Factors de Risc en Estudiants de SeCundària) lifestyle risk-factor 
survey for secondary school students (29). An example of an item is, 
“I am too tired to do anything,” with the following response options: 
never, almost never, sometimes, frequently, and always. The variable 
was dichotomized, whereby the response “always” or “frequently” to 
three or more of the six items indicated a negative mood state, whereas 
a positive mood state was assigned for the other responses. Internal 
reliability (Cronbach’s ⍺) was 0.673 as reported by Ahonen et al. (30).
2.6. Dietary data
A validated semi-quantitative food frequency questionnaire with 
157-items was filled out by the families of the participants to provide 
information about their dietary habits from the previous year (31, 32). 
The items were organized by food groups and the response categories 
were as follows: never or almost never, 1–3 per month, 1 per week, 2–4 
per week, 5–6 per week, 1 per day, 2–3 per day, 4–6 per day, and 6 or 
more per day. This questionnaire results were analyzed using Evaldara 
software and the food composition tables of the Centro de Enseñanza 
Superior de Nutrición y Dietética and adjusted for total energy intake 
(33, 34).
2.7. Metabolic groups
The study population was categorized in three metabolic groups 
(healthy, at-risk, and MS) as defined by the International Diabetes 
Federation (9). Those in the MS group had abdominal obesity (≥ 90th 
percentile of WC) plus two or more clinical symptoms: ≥ 150 mg/dL 
of triglycerides or < 40 mg/dL of HDL-c or ≥ 100 mg/dL of blood 
glucose or high BP (SBP ≥ 130 mm Hg or DBP ≥ 85 mm Hg). The 
at-risk population included participants with MS symptoms but not 
enough to belong to the MS group. Those in the healthy population 
showed none of the aforementioned symptoms. After the participants 
were categorized, a randomized sampling from each group was carried 
out to define the at-risk and healthy groups. Supplementary Figure S2 
shows a schematic view of the process followed in the different phases 
of defining the study groups.
2.8. Statistical analyzes
A minimum of 118 participants were required to provide 95% 
power of test and a significance level of 5% when performing multiple 
regression. Given that 44 participants presented MS, a total of 132 
participants were enrolled to achieve a ratio of 1:1:1 for the three 
groups (44  in each); more details are provided in 
Supplementary Figure S2.
A seven-step statistical process was followed; a value of p ≤0.05 
was considered statistically significant. First, a 98% winsorizing 
technique was used to minimize the influence of outliers. Second, 
numerical variables without prior standardization (i.e., adjusted for 
age, sex, and height) were standardized (z-scores) prior to the 
statistical analysis. Third, the normality of variables was determined 
by the Kolmogorov–Smirnov test. Fourth, to estimate differences, a 
chi-square test was used for categorical variables, an analysis of 
variance (ANOVA) for parametric numerical variables, and a 
Kruskal–Wallis test for non-parametric numerical variables, whereas 
Dunn–Bonferroni correction was used to ascertain differences 
between the metabolic groups. Fifth, a simple linear regression was 
used to identify the association between 8-isoprostane levels and each 
studied variable. Sixth, principal component analysis was used to 
eliminate collinearity among variables. Finally, to capture more 
Ramírez-Garza et al. 10.3389/fnut.2023.1216445
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complex interactions between different factors, a multiple linear 
regression model was generated. All statistical analyzes were 
conducted using R software version 4.1.0 (R Studio, 250 Northern Ave, 
Boston, MA, United States).
3. Results
The present study enrolled 132 adolescents (48.5% girls) aged 
12 ± 0.48 years. The healthy group had the highest percentage of girls 
(56.8%), and the MS group the highest percentage of boys (63.6%) 
(Table 1).
The characteristics of the study population and the differences 
between the three metabolic groups are described in Table  1 and 
Supplementary Table S1 shows the differences between sexes. 
Significant differences in all anthropometric measurements and blood 
glucose levels were observed for all metabolic groups. Triglycerides, 
HDL-c, 8-isoprostane levels, BP, sleep duration, time spent awake after 
initially falling asleep, and fish intake differed significantly between 
the healthy and MS groups. It is worth noting that the adolescents in 
the healthy group had longer periods of sleep interrupted by shorter 
awake periods compared to the MS group.
Levels of 8-isoprostane were higher in the MS group than the 
healthy group (Figure  1). Table  2 shows the association between 
8-isoprostane and each nutritional parameter and lifestyle variable. 
The BMI, WC, and WHtR z-scores, and body fat percentage were 
positively associated with 8-isoprostane levels, suggesting the 
biomarker was positively related to adiposity. Similarly, blood glucose, 
total cholesterol, LDL-c, EE, categorization in the MS group, and 
refined cereal intake were positively associated with 8-isoprostane; in 
contrast, sleep duration and fish intake showed a negative association 
with 8-isoprostane (Table 2). Total cholesterol and z-scores for BMI, 
WC, and WHtR acted as collinear variables in the dataset 
under analysis.
Finally, the multiple adjusted linear regression model (Figure 2) 
showed an association between 8-isoprostane and metabolic group 
(at-risk β = 0.140, value of p = 0.513; MS β = 0.213, value of p = 0.470), 
blood glucose (β = 0.124, value of p = 0.247), LDL-c (β = 0.173, value of 
p = 0.049), sleep duration (β = −0.026, value of p = 0.798), EE (low 
β = 0.443, value of p = 0.036; high β = 0.151, value of p = 0.470), refined 
cereal intake (β =0.191, value of p = 0.024), and fish intake (β = −0.187, 
value of p = 0.050).
4. Discussion
Three principal observations were made in the course of the 
present study. First, 8-isoprostane was associated with an unhealthy 
metabolic status in the adolescent cohort, being positively related with 
adiposity (high z-scores for BMI, WHtR, and WC, and high body fat 
percentage), LDL-c, and MS. Second, an association between EE and 
8-isoprostane was found, which to our knowledge has not been 
previously reported in adolescents. Finally, our results suggest that diet 
can significantly influence 8-isoprostane levels, which were positively 
associated with refined cereal intake and negatively associated with 
fish intake.
Consistent with our results, higher 8-isoprostane levels have 
been observed in obese children and adolescents compared to those 
with normal weight (35–37). This biomarker has also been 
positively correlated with measures of fatness, as well as WC, 
WHtR, and body fat (38–40). The association we found between 
oxidative stress, manifested by increased levels of 8-isoprostane, 
and MS in an adolescent population is also supported by previous 
studies in children (38, 41, 42) and adolescents (35), which report 
higher levels of 8-isoprostane in those with symptoms of 
MS. Moreover, overweight children with MS showed higher 
8-isoprostane levels than overweight children without metabolic 
risk factors (42); it is possible that risk factors such as 
hyperglycemia, hypertriglyceridemia, presents in MS contribute to 
the presence of oxidative stress (10). Adolescents with a high BMI 
were observed to have higher levels of 8-isoprostane if they were 
insulin-resistant as opposed to insulin-sensitive, but no difference 
was observed with a low BMI and resistance/sensitivity to insulin 
(37), suggesting that both, adiposity and risk factors, could conduce 
to oxidative stress (10, 43). Therefore, it is possible that oxidative 
stress worsens with obesity, especially when coupled with MS risk 
factors. In the present study, consistent with the symptoms of MS, 
LDL-c was positively associated with 8-isoprostane; similar results 
have been reported in children with excess weight (38), children 
with diabetes mellitus type 1 (44), and adolescents with insulin 
resistance (45).
Although a relationship between high EE and MS has been 
described in adults (4, 46, 47), it remains poorly researched in 
adolescents. The most closely related study was carried out with 
adolescents diagnosed with type 1 diabetes, in whom higher EE values 
were associated with higher levels of HbA1, total cholesterol and 
LDL-c, which are risk factor of MS (48). On the other hand, an 
association between EE and obesity, which is the principal 
characteristic of MS, has been observed in adults (49–55), but has 
been scarcely studied in adolescents (56).
Since sleeping and physical activity are very important factors in 
the health of adolescents, we evaluated these variables and consistently 
with others results, we observed an association between 8-isoprostane 
and sleep duration (57) and between MS and sleep duration (58), not 
with physical activity. However, in the multiple linear regression 
analysis, physical activity or sleep duration were not significant factors 
in 8-isoprostane level.
As reported in the aforementioned studies, EE is linked with 
obesity. The association between obesity and 8-isoprostane could 
therefore explain the relationship found in the present study 
between EE and 8-isoprostane. The EE questionnaire evaluates the 
individual’s response to food consumption, focusing on the 
emotions of anxiety, loneliness, and depression. Previous research 
has shown a positive association between 8-isoprostane and 
anxiety as well as depression (59–63), which is in agreement with 
the results obtained here. A possible explanation of these 
relationships could be the effects of oxidative stress on the nervous 
system. The brain has a high rate of oxygen consumption and is 
rich in lipids, which contributes to the susceptibility of its cells to 
oxidative stress (64). The resulting inflammatory processes (65) 
alter the function of serotonin and dopamine, leading to 
symptoms of anxiety and depression (66–68), both of which are 
components of the items in the EE assessment (69, 70). 
Consequently, the directionality of the relationship between 
oxidative stress and EE is not yet clear. The scope of the present 
study is limited to demonstrating that an association exists 
between 8-isoprostane and EE; future work could shed more light 
on this relationship.
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TABLE 1 Description and comparison of the metabolic groups.
Healthy At-risk Metabolic syndrome Value of p †
n 44 44 44
Boys (%) 43.2 50.0 63.6 0.131
Anthropometric variables
  BMI z-score 0.26 ± 0.51 * 1.29 ± 0.87 * 2.42 ± 0.49 * <0.001
  WC z-score −0.13 ± 0.57 * 0.86 ± 0.75 * 1.77 ± 0.28 * <0.001
  WHtR z-score −0.48 ± 0.58 * 0.47 ± 0.9 * 1.63 ± 0.35 * <0.001
  Body fat (%) 19.9 ± 5.46 * 27.3 ± 9.0 * 36.7 ± 4.40 * <0.001
Skeletal muscle (%) 35.4 ± 2.41 * 33.6 ± 3.53 * 30.7 ± 2.23 * <0.001
Biochemistry analysis:
  Total cholesterol (mg/dL) 147 ± 24.1 148 ± 39.9 164 ± 42.7 0.050
  Blood glucose (mg/dL) 91 ± 6.8 * 104 ± 11.9 * 112 ± 9.5 * <0.001
  Triglycerides (mg/dL) 66 ± 11.2 B 91 ± 37.7C 154 ± 96.6 B, C <0.001
  HDL-c (mg/dL) 66 ± 14.2 A, B 54 ± 17.4 A 50 ± 15.0 B <0.001
  LDL-c (mg/dL) 68 ± 20.6 76 ± 34.4 83 ± 36.9 0.079
  Urinary 8-isoprostane (pg/mg) 950 ± 416 B 1,133 ± 447 1,280 ± 543 B 0.005
Blood pressure:
  SBP z-score −0.03 ± 0.84 A, B 1.18 ± 0.89 A 1.22 ± 0.93 B <0.001
  DBP z-score 0.24 ± 0.80 A, B 0.90 ± 0.96 A 1.15 ± 1.02 B <0.001
Physical activity and sleep:
  MVPA (minutes) 72.6 ± 23.4 69.4 ± 27.8 71.4 ± 18.6 0.813
  Sleep duration (hours) 7.83 ± 0.71 B 7.72 ± 0.74C 7.17 ± 0.99 B, C <0.001
  Sleep efficiency (%) 92.9 ± 2.84 92.8 ± 3.02 91.4 ± 3.18 0.059
  Awakenings (Frequency) 16.9 ± 5.32 16.0 ± 6.06 14.2 ± 5.15 0.095
  Awake length (minutes) 2.03 ± 0.38 B 2.06 ± 0.38C 2.63 ± 0.76 B, C <0.001
Emotion management:
Satisfaction: self-esteem (1 to 4) 3.6 (1.4–4.0) 3.6 (2.0–4.0) C 3.4(0.8–4.0) C 0.037
Emotional eating
  No emotional eating (%) 59.1 52.3 38.6 0.148
  Low emotional eating (%) 18.2 29.5 20.5 0.404
  High emotional eating (%) 22.7 18.2 40.9 0.040
Mood
  Positive mood (%) 93.2 90.9 86.4
0.550
  Negative mood (%) 6.8 9.1 13.6
Dietary:
Energy intake (kcal/d) 2,450 ± 586 2,486 ± 679 2,522 ± 534 0.878
 - Carbohydrates (% EI) 39.9 ± 5.98 41.7 ± 6.97 40.5 ± 7.01 0.434
 - Total fat (% EI) 40.2 ± 4.88 39.4 ± 6.47 39.8 ± 6.49 0.822
 - Protein (% EI) 19.8 ± 3.20 18.7 ± 2.94 19.7 ± 2.90 0.206
Intake by groups of foods:
Fruits and vegetables
 - Vegetables (s/d) 1.7 (0.0–5.8) 2.0 (0.2–6.1) 2.1 (0.5–6.5) 0.559
 - Fruits (s/d) 1.4 (0.1–7.4) 1.8 (0.1–8.7) 1.9 (0.1–6.9) 0.729
Cereals
 - Whole grain (s/d) 0.1 (0.0–1.6) 0.1 (0.0–1.0) 0.1 (0.0–1.3) 0.900
(Continued)
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Diet is reported to modulate oxidative stress (15). Accordingly, 
a research work found a reduction in urinary isoprostanes and other 
oxidative stress biomarkers in MS patients who consumed a 
Mediterranean diet (71). In the present study, analysis of the eating 
habits of the adolescent participants revealed a positive association 
between 8-isoprostane and refined cereal intake. The quality of 
ingested carbohydrates is known to affect metabolic risk factors 
(72–75), which is consistent with our findings. A cross-over study in 
adults reported significantly higher levels of 8-isoprostane in 
consumers of a refined wheat diet compared to a wheat aleurone diet 
(76). However, other studies did not find different levels of 
8-isoprostane between the consumers of ground flaxseed or wheat 
bran (77), whole-grain or refined-grain products (78), and whole or 
refined grain foods (79).
The inverse association between the oxidative stress 
biomarker 8-isoprostane and fish intake found in the present 
study is in accordance with prior reports of an inverse association 
between oxidative stress and fish intake (71, 80, 81) or 
supplementation with fish oil (80, 82, 83) or eicosapentaenoic 
acid or docosahexaenoic acid (81, 84, 85). Conversely, other 
studies have failed to find any significant associations between 
oxidative stress and the consumption of fish, including oil 
FIGURE 1
Difference in 8-isoprostane levels between the metabolic groups.
TABLE 1 (Continued)
Healthy At-risk Metabolic syndrome Value of p †
 - Refined cereals (s/d) 0.9 (0.0–1.9) 0.8 (0.0–2.6) 0.9 (0.2–1.7) 0.728
Fats and Oil (g/d) 24 (2.9–129) 26.3 (1.4–79) 20.9 (3.1–67) 0.857
Dairy products (s/d) 2.9 (0.7–15.7) 2.4 (0.0–7.0) 2.4 (0.0–6.9) 0.292
Legumes (s/w) 2.5 (0.0–12.0) 2.4 (0.0–28.0) 3.0 (0.0–14.5) 0.131
Eggs (s/w) 3.0 (0.0–7.0) A 3.0 (0.0–6.0) A 3.0 (0.5–7.0) 0.008
Fish (s/w) 3.2 (0.0–6.0) B 2.0 (0.0–6.0) C 1.0 (0.0–6.0) B, C <0.001
Meat and processed meat (s/w) 13.1 (4.9–31.4) 14.5 (0.9–54.3) 16.9 (4.4–35.0) 0.369
Sugar-sweetened beverages (s/w) 0.7 (0.0–6.0) 0.5 (0.0–6.0) 1.0 (0.0–6.8) 0.913
Numerical variables were standardized prior to the statistical analysis. †value of ps from chi-square (%), ANOVA (mean ± SD), and Kruskal-Wallis (median and range) tests. Significant 
differences (value of p ≤ 0.05) among segments after Bonferroni post-hoc correction; * among all groups; A, between healthy and at-risk groups; B, between healthy and metabolic syndrome 
groups; C, between at-risk and metabolic syndrome groups. 8-Isoprostane is expressed by pg of 8-isoprostane/mg of creatinine in urine. BMI, body mass index; WC, waist circumference; 
WHtR, waist-to-height ratio; HDL-c, high-density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; SBP, systolic blood pressure; DBP, diastolic blood pressure; MVPA, 
moderate and vigorous physical activity. Intake is expressed in % EI; percentage of energy intake; g/d, grams per day; s/d, serving per day; s/w, serving per week.
Ramírez-Garza et al. 10.3389/fnut.2023.1216445
Frontiers in Nutrition 07 frontiersin.org
TABLE 2 Association of individual variables with 8-isoprostane.
Coefficient (β) Value of p
n
  Boys 0.130 0.293
Anthropometric variables:
  BMI z-score 0.275 <0.001
  WC z-score 0.362 <0.001
  WHtR z-score 0.348 <0.001
  Body fat (%) 0.251 0.004
  Skeletal muscle (%) −0.159 0.068
Biochemistry analysis:
  Blood glucose (mg/dL) 0.217 0.012
  Triglycerides (mg/dL) 0.170 0.051
  Total cholesterol (mg/dL) 0.234 0.007
  HDL-C (mg/dL) −0.069 0.434
  LDL-c (mg/dL) 0.232 0.007
Blood pressure:
  SBP z-score 0.028 0.739
  DBP z-score 0.098 0.262
Physical activity and sleep:
  MVPA (minutes) 0.121 0.181
  Sleep duration (hours) −0.236 0.009
  Sleep efficiency (%) −0.087 0.342
  Awakenings (frequency) −0.096 0.292
  Awakenings (length in minutes) 0.074 0.414
Emotion management:
  Self-esteem 0.001 0.984
  Emotional eating*
  - Low emotional eating (%) 0.599 0.006
  - High emotional eating (%) 0.403 0.048
  Negative mood* −0.223 0.448
Metabolic groups*
  - Risk group 0.376 0.070
  - Metabolic syndrome group 0.677 0.001
Dietary:
  Energy intake (kcal/d) 0.021 0.806
  Carbohydrates (% EI) 0.089 0.295
  Total fat (% EI) −0.024 0.781
  Protein (% EI) −0.048 0.572
Intake by groups of foods:
  Fruits and vegetables
  Vegetables (s/d) −0.087 0.309
  Fruits (s/d) −0.021 0.810
Cereals
  Whole grain (s/d) −0.114 0.180
  Refined cereals (s/d) 0.208 0.013
  Fats and Oil (g/d) 0.095 0.263
  Dairy products (s/d) −0.137 0.108
  Legumes (s/w) −0.079 0.356
  Eggs (s/w) 0.012 0.888
  Fish (s/w) −0.318 <0.001
  Meat and processed meat (s/w) 0.033 0.696
  Sugar-sweetened beverages (s/w) 0.016 0.847
Numerical variables were standardized prior to the statistical analysis. p-values and β are of simple linear regression. BMI, body mass index; WC, waist circumference; WHtR, waist-to-height 
ratio; HDL-c, high-density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; SBP, systolic blood pressure; DBP, diastolic blood pressure; MVPA, moderate and vigorous 
physical activity. Intake is expressed in % EI; percentage of energy intake; g/d, grams per day; s/d, serving per day; s/w, serving per week. *Intercept (β) for the reference categories: no 
emotional eating (β = −0.246) for emotional eating; positive mood (β = 0.022) for mood; healthy (β = −0.351) for metabolic groups.
Ramírez-Garza et al. 10.3389/fnut.2023.1216445
Frontiers in Nutrition 08 frontiersin.org
supplements (86–88). On the other hand, review articles show an 
inverse association between fish consumption and prevalence of 
MS (89) and heart failure (90, 91), which is supported by 
our results.
A strength of this study is that, to the best of our knowledge, a 
significant association between 8-isoprostane and EE, refined cereal 
intake, and fish intake has not been previously demonstrated in 
adolescents. Additionally, the study takes a holistic approach in 
which anthropometric and biochemical factors, emotional 
management, and eating habits are analyzed. Other strong points 
include the multicenter design and the use of a standardized 
protocol, which reduces information bias. The limitations of the 
study include the small size and cross-sectional design of the study 
population. Also, sometimes the participants did not wear the 
accelerometer while practicing water activities or a sport requiring 
its removal (e.g., judo, basketball). Finally, blood samples were not 
obtained no to use invasive methods due to the age of the cohort, 
so we were unable to analyze 8-isoprostane in plasma, inflammatory 
or neurotransmitter biomarkers, which would have provided 
greater insight into oxidative stress. The results of the present study 
may contribute to the development of educational programs 
focused on the establishment of healthier lifestyles in early life 
stages. The findings also indicate that more research is needed to 
understand the interaction between food choices, emotion 
management, and oxidative stress status in adolescents with good 
or poor metabolic health.
In conclusion, a significant positive association between 
8-isoprostane and EE, refined cereal intake, indicators of adiposity 
(BMI z-score, WHtR z-score, body fat percentage), and MS, and a 
negative association between 8-isoprostane and fish intake in 
adolescents has been found. This shows that dietary patterns such as 
those exhibited in the Mediterranean diet could help to prevent 
cardiometabolic diseases.
Data availability statement
The datasets presented in this article are not readily available 
because there are restrictions on the availability of the data for the SI! 
Program study, due to signed consent agreements around data sharing, 
which only allow access to external researchers for studies following 
project purposes. Requests to access the datasets should be directed to 
Steering Committee gsantos@fundacionshe.org, rodrigo.fernandez@
cnic.es, juanmiguel.fernandez@cnic.es, lamuela@ub.edu.
FIGURE 2
Multiple linear regression model for 8-isoprostane associations. Adjusted for sex and energy intake. Numerical variables are expressed as z-scores.  
*Statistically significant difference (value of p ≤0.05).
Ramírez-Garza et al. 10.3389/fnut.2023.1216445
Frontiers in Nutrition 09 frontiersin.org
Ethics statement
The studies involving humans were approved by the Ethics 
Committee of Instituto de Salud Carlos III in Madrid (CEI PI 
35_2016), the Fundació Unió Catalana d’Hospitals (CEI 16/41), and 
the University of Barcelona (IRB00003099). The studies were 
conducted in accordance with the local legislation and institutional 
requirements. Written informed consent for participation in this study 
was provided by the participants’ legal guardians/next of kin.
Author contributions
RL-R, GS-B, JF-A, and RF-J designed the study, project 
administration, and funding acquisition. SR-G, EL-S, PB, AC-G, 
MdM, JF-A, and AT-R supervised the study implementation and data 
collection. SR-G performed statistical analysis. SR-G, AT-R, and RL-R 
contributed to writing–original draft manuscript. SR-G, RL-R, AT-R, 
EL-S, JM, PB, AC-G, JF-A, RF-J, JM-G, AR-L, and RE contributed to 
writing–interpreted the study results, review, and editing. All authors 
contributed to the article and approved the submitted version.
Funding
The SI! Program for Secondary Schools trial was supported by the 
SHE Foundation, the la Caixa Foundation (LCF/PR/CE16/10700001), 
the Fundació la Marató de TV3 (grant number 369/C/2016). Support 
was also provided by the Ministerio de Ciencia, Innovación y 
Universidades (PID2020-114022RB-I00), CIBEROBN from the 
Instituto de Salud Carlos III (ISCIII) from the Ministerio de Ciencia, 
Innovación y Universidades (AEI/FEDER, UE), and Generalitat de 
Catalunya. The CNIC is supported by the ISCIII, the Ministerio de 
Ciencia e Innovación (MCIN) and the Pro CNIC Foundation, and is 
a Severo Ochoa Center of Excellence (grant CEX2020-001041-S 
funded by MICIN/AEI/10.13039/501100011033), and INSA-UB a 
María de Maeztu Center of Excellence (grant CEX2021-001234-M 
funded by MICIN/AEI/FEDER, UE). RF-J is recipient of grant 
PI22/01560 funded by the ISCIII and co-funded by the European 
Union. GS-B was the recipient of grant LCF/PR/MS19/12220001 
funded by la Caixa Foundation (ID 100010434). AT-R is a Serra 
Húnter fellow. EL-S was a FI-SDUR (EMC/503/2021) fellowship from 
the Generalitat de Catalunya. JM-G is a recipient of grant 
FPU21/04891 (Ayudas para la formación de profesorado universitario, 
FPU-2021) from the Ministerio de Educación, Cultura y Deporte.
Acknowledgments
The authors especially thank all the volunteers and their families, 
teachers, and schools for their contribution to the SI! Program for 
Secondary Schools. The authors thank the SHE Foundation 
(intellectual owner of the SI! Program) and its partners Isabel Carvajal, 
Domènec Haro, Xavier Orrit, Carla Rodríguez, Vanessa Carral, Rosa 
Casas, Carolina E. Storniolo, for their contribution to the study design, 
coordination, development, and all personnel who performed 
measurements in adolescents at participating schools.
Conflict of interest
The authors declare that the research was conducted in the 
absence of any commercial or financial relationships that could 
be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors 
and do not necessarily represent those of their affiliated organizations, 
or those of the publisher, the editors and the reviewers. Any product 
that may be evaluated in this article, or claim that may be made by its 
manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary material for this article can be found online 
at: https://www.frontiersin.org/articles/10.3389/fnut.2023.1216445/
full#supplementary-material
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