Abstract:

Objective:

Evaluate association of dietary patterns with metabolic syndrome (MetS) and metabolic markers.

Materials and methods:

654 adolescents from Guadalajara, Jalisco, participated in a cross-sectional study. Diet was evaluated using a food frequency questionnaire; 24 food groups were integrated, and dietary patterns were derived using cluster analysis. MetS was defined according to International Diabetes Federation (IDF), Cook and colleagues, Ford and colleagues, and de Ferranti and colleagues criteria.

Results:

Dietary patterns identified were: “DP1”, “DP2”, and “DP3”. Among males, “DP3” was associated with MetS (Cook and collaborators) (OR, 12.14; 95%CI, 1.66-89.05), hypertriglyceridemia (OR, 3.89; 95%CI, 1.01-15.07), and insulin resistance (OR, 6.66; 95%CI, 1.12-39.70). “DP2” was associated with abdominal obesity (OR, 5.11; 95%CI, 1.57-16.66).

Conclusions:

“DP3” entertained a greater risk of MetS, hypertriglyceridemia, and insulin resistance, while “DP2” possessed a greater risk of abdominal obesity among adolescent males.

Keywords:
metabolic syndrome; dietary patterns; fast foods; sugar-sweetened beverages; adolescents

Resumen:

Objetivo:

Evaluar la asociación de patrones dietarios (PD) con síndrome metabólico (SM) y marcadores metabólicos.

Material y métodos:

Estudio transversal con 654 adolescentes. Dieta evaluada con el cuestionario “frecuencia de consumos de alimentos”; se identificaron 24 grupos de alimentos, para obtener PD mediante análisis de conglomerados. SM se definió según los criterios: Federación de Diabetes Internacional (IDF), Cook y colaboradores, Ford y colaboradores y Ferranti y colaboradores.

Resultados:

Se identificaron tres PD: “PD1”, “PD2” y “PD3”. En hombres, “PD3” se asoció con SM (Cook y colaboradores) (RM, 12.14; IC95%, 1.66-89.05), hipertrigliceridemia (RM, 3.89; IC95%, 1.01-15.07) y resistencia a insulina (RM, 6.66; IC95%, 1.12-39.70). El patrón “PD2” se asoció con obesidad abdominal (RM, 5.11; IC95%, 1.57-16.66).

Conclusiones:

El patrón “PD3” aumenta el riesgo de SM, hipertrigliceridemia y resistencia a insulina y el “PD2” el riesgo de obesidad abdominal en adolescentes hombres.

Palabras clave:
síndrome metabólico; patrones dietarios; comida rápida; bebidas endulzadas; adolescentes

Introduction

The prevalence of metabolic syndrome (MetS) in Mexican adolescents is higher (6.5-19.2%)¹1. Rodríguez-Morán M, Salazar-Vázquez B, Violante R, Guerrero-Romero F. Metabolic syndrome among children and adolescents aged 10-18 years. Diabetes Care. 2004;27(10):2516-17. https://doi.org/10.2337/diacare.27.10.2516
https://doi.org/10.2337/diacare.27.10.25... ^,22. Halley-Castillo E, Borges G, Talavera JO, Orozco R, Vargas-Alemán C, Huitrón-Bravo G,et al. Body mass index and the prevalence of metabolic syndrome among children and adolescents in two Mexican populations. J Adolesc Health. 2007;40(6):521-6. https://doi.org/10.1016/j.jadohealth.2006.12.015
https://doi.org/10.1016/j.jadohealth.200... than in other ethnic groups (4.5%).³3. Ford ES, Li C, Pearson WS, Mokdad AH. Prevalence of the metabolic syndrome among U.S. adolescents using the definition from the International Diabetes Federation. Diabetes Care . 2008;31(3):587-9. https://doi.org/10.2337/dc07-1030
https://doi.org/10.2337/dc07-1030... Diet and physical activity play a role in the development of MetS.⁴4. Pitsavos C, Panagiotakos D, Weinem M, Stefanadis C. Diet, exercise and the metabolic syndrome. Rev Diabet Stud. 2006;3(3):118-26. https://doi.org/10.1900/RDS.2006.3.118
https://doi.org/10.1900/RDS.2006.3.118...

Dietary patterns (DP) are defined as “nutritional variables grouped according to some nutritional criteria, in which variables are reduced into a smaller number of variables through statistical manipulation”.⁵5. Newby PK, Tucker KL. Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev. 2004;62(5):177-203. https://doi.org/10.1111/j.1753-4887. 2004 .tb00040.x
https://doi.org/10.1111/j.1753-4887. 200... DP have the advantage of evaluating the potential synergistic effects of foods and nutrients and of reducing epidemiological limitations in comparison with single-food or nutrient approaches. Dietary guidelines might be focused on a food-based approach and not only on a nutrient-based approach that is unclear and favors the consumption of industrialized products designed to meet individual nutrient goals rather than achieving a healthy diet.⁶6. Mozaffarian D, Ludwig DS. Dietary guidelines in the 21st century-a time for food. JAMA. 2010;304(6):681-2 https://doi.org/10.1001/jama. 2010 .1116
https://doi.org/10.1001/jama. 2010 .1116...

In adults, DP predict obesity, MetS, and other chronic diseases; nevertheless, some inconsistencies exist.⁵5. Newby PK, Tucker KL. Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev. 2004;62(5):177-203. https://doi.org/10.1111/j.1753-4887. 2004 .tb00040.x
https://doi.org/10.1111/j.1753-4887. 200... ^,77. Flores M, Macias N, Rivera M, Lozada A, Barquera S, Rivera-Dommarco J,et al. Dietary patterns in Mexican adults are associated with risk of being overweight or obese. J Nutr. 2010 ;140(10):1869-73. https://doi.org/10.3945/jn.110.121533
https://doi.org/10.3945/jn.110.121533... ^,88. Denova-Gutiérrez E, Castañón S, Talavera JO, Flores M, Macías N, Rodríguez-Ramírez S,et al. Dietary patterns are associated with different indexes of adiposity and obesity in an urban Mexican population. J Nutr. 2011;141(5):921-7. https://doi.org/10.3945/jn.110.132332
https://doi.org/10.3945/jn.110.132332... In adolescents, some reports suggest that a “Western” or “obesogenic” DP is positively associated with overweight.⁹9. Song Y, Park MJ, Paik HY, Joung H. Secular trends in dietary patterns and obesity-related risk factors in Korean adolescents aged 10-19 years. Int J Obes (Lond). 2010 ;34(1):48-56. https://doi.org/10.1038/ijo.2009.203
https://doi.org/10.1038/ijo.2009.203... Others failed to detect such association¹⁰10. Pérez-Rodrigo C, Gil Á, González-Gross M, Ortega RM, Serra-Majem L, Varela-Moreiras G,et al. Clustering of dietary patterns, lifestyles, and overweight among Spanish children and adolescents in the ANIBES Study. Nutrients. 2015;8(1):E11. https://doi.org/10.3390/nu8010011
https://doi.org/10.3390/nu8010011... or with MetS.¹¹11. Shang X, Li Y, Liu A, Zhang Q, Hu X, Du S,et al. Dietary pattern and its association with the prevalence of obesity and related cardiometabolic risk factors among Chinese children. PLoS One. 2012;7(8):e43183. https://doi.org/10.1371/journal.pone.0043183
https://doi.org/10.1371/journal.pone.004... Moreover, an inverse association between the “fast food and sweet” DP and obesity was reported.¹²12. Araújo J, Teixeira J, Gaio AR, Lopes C, Ramos E. Dietary patterns among 13-y-old Portuguese adolescents. Nutrition. 2015;31(1):148-54. https://doi.org/10.1016/j.nut.2014.06.007
https://doi.org/10.1016/j.nut.2014.06.00... More studies are needed in adolescents because they have unique nutritional needs and cultural particularities and the still existing inconsistencies require further evaluation. We evaluated the association of DP with MetS and metabolic markers (insulin resistance [IR] and lipids) in adolescents.

Materials and methods

We conducted a cross-sectional study in public high schools in Guadalajara, Jalisco, Mexico. Adolescents who were willing to participate were included in the study (n= 681). Participation rate was 89.3%. Participants with incomplete data (n= 9), or with implausible total energy intake (<800 kcal/day or >6000 kcal/day) (n= 18) were excluded from analysis. Finally, 654 participants were included. Previous studies including some of these participants have been reported.¹³13. Ramírez-López G, Morán-Villota S, Mendoza-Carrera F, Portilla-de Buen E, Valles-Sánchez V, Castro-Martínez XH,et al. Metabolic and genetic markers’ associations with elevated levels of alanine aminotransferase in adolescents. J Pediatr Endocrinol Metab. 2018;31(4):407-14. https://doi.org/10.1515/jpem-2017-0217
https://doi.org/10.1515/jpem-2017-0217... The Institutional Review Board of the Mexican Institute of Social Security approved the protocol. Written informed consent was obtained from all the participants and their parents.

Questionnaires and anthropometric measurements were performed by nutritionists. After five minutes of rest, two systolic blood pressure (SBP) and diastolic blood pressure (DBP) readings were taken with a digital baumanometer (Omron HEM-751; Vernon Hills, IL, USA).

A venipuncture blood sample was collected after a 12-h fast. Serum samples were centrifuged and stored at -80^oC until analysis. Glucose levels were determined with the hexokinase method in an automated system (Synchron CX4; Beckman Coulter, Inc., Brea, CA, USA) and insulin with an immunometric method utilizing an Immulite 2000 analyzer (Diagnostic Products Co., Los Angeles CA, USA). IR was estimated with HOMA-IR= fasting insulin (μU/ml) × fasting glucose (mmol/l)/22.5. Total cholesterol and triglycerides were estimated by conventional enzymatic procedures. High-density lipoprotein-cholesterol (HDL-C) and low-density lipoprotein-cholesterol (LDL-C) were determined directly by immunochemical methods utilizing an ILab 300 Plus analyzer (Instrumentation Laboratory, Ltd., Birchwood, Warrington, UK).

Assessment of exposure variables

Diet was assessed using a semi-quantitative food-frequency questionnaire (FFQ).¹⁴14. Hernández-Avila M, Romieu I, Parra S, Hernández-Avila J, Madrigal H, Willett W. Validity and reproducibility of a food frequency questionnaire to assess dietary intake of women living in Mexico City. Salud Publica Mex. 1998;40(2):133-40.The questionnaire included 116 food items with eight options of frequency consumption (ranging from never to four or more times per day) in the previous year. For each food item, a commonly used portion was used. Food or beverage intake was computed multiplying food frequency consumption by the specific portion size of each food item. Food and beverages were converted into total daily energy, macro and micronutrient intake with the Evaluation System of Nutritional Habits and Nutrient Intake.¹⁵15. Hernández-Ávila M, Resoles M, Parra S. Sistema de evaluación de hábitos nutricionales y consumo de nutrimentos (SNUT). Cuernavaca: Instituto Nacional de Salud Pública, 2000.

In order to identify the DP, foods were first integrated into 24 mutually exclusive food groups; the criteria for integrating a food group was based on macronutrient composition, as well as on other components (dietary fiber, sucrose content, culinary aspects, or traditional foods). The food groups employed are listed in table I. DP were derived using cluster analysis, which allows reducing data into patterns according to individual differences in mean intakes.⁵5. Newby PK, Tucker KL. Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev. 2004;62(5):177-203. https://doi.org/10.1111/j.1753-4887. 2004 .tb00040.x
https://doi.org/10.1111/j.1753-4887. 200... Energy percent values were obtained for each food group as follows: percentage of energy intake for a food group = Σ (energy intake of each food in a food group X 100/daily total energy intake).⁷The percentage of energy intake value for each food group was standardized (z-scores) for their entry into cluster analysis. We used a k-means method, which partitions subjects into clusters that maximize the Euclidian distance among clusters. We selected a three-cluster solution based on its size, ease of dietary interpretation, and according to our knowledge of the Mexican diet.

The following items concerning eating habits were included at the last part of the FFQ: How often did you have breakfast on average last year? (<1 a week, 1-2 times a week, 3-4 times a week, 5-6 times a week, daily). Do you eat while watching TV? (yes/no). How often did you eat away from home last year? (<1 a week, 1-3 times a week, 4-6 times a week, daily). During the last year, did you take vitamins? (yes/no). Where did you more frequently eat hamburgers, hot dogs, pizza? (home, fast-food restaurant, school, another place). When you eat chicken, do you remove its skin? (yes/no). When you eat meat, do you remove its fat? (yes/no). How many teaspoons of sugar do you add to your drinks to sweeten them?

Assessment of covariates

Smoking was defined as at least one cigarette/day during the past month.¹⁶16. Marcus SE, Giovino GA, Pierce JP, Harel Y. Measuring tobacco use among adolescents. Public Health Rep. 1993;108(suppl 1):20-24.Pubertal development was defined according to Tanner stages.¹⁷17. Schlossberger NM, Turner RA, Irwin CE. Validity of self-report of pubertal maturation in early adolescents. J Adolesc Health. 1992;13(2):109-13.Overweight and obesity were defined according to International Obesity Task Force criteria and body fat percentage, with the Slaughter equation.¹⁸18. Slaughter MH, Lohman TG, Boileau RA, Horswill CA, Stillman RJ, Van Loan MD,et al. Skinfold equations for estimation of body fatness in children and youth. Hum Biol. 1988;60(5):709-23.Physical activity was evaluated with a Questionnaire on Physical Activity and Inactivity in Mexican Children.¹⁹19. Hernández B, Gortmaker SL, Laird NM, Colditz GA, Parra-Cabrera S, Peterson KE. Validez y reproducibilidad de un cuestionario de actividad e inactividad física para escolares de la ciudad de México. Salud Publica Mex. 2000;42(4):315-23.

Assessment of outcome variables

MetS was defined according to International Diabetes Federation (IDF) criteria. For adolescents aged 10-15 years, abdominal obesity (AO) (waist circumference [WC] ≥90^thpercentile for age and sex), and two or more of the following: glucose ≥100 mg/dl; triglycerides ≥150 mg/dl; HDL-C <40 mg/dl, and SBP >130 mmHg or DBP >85 mmHg. For adolescents aged ≥16 years, AO (WC ≥90 cm [males] and ≥80 cm [females]), and two or more of the following: glucose ≥100 mg/dl; triglycerides ≥150 mg/dl; HDL-C <40 mg/dl (males) or <50 mg/dl (females), and SBP >130 mmHg or DBP >85 mmHg.²⁰20. Zimmet P, Alberti KG, Kaufman F, Tajima N, Silink M, Arslanian S,et al. IDF Consensus Group. The metabolic syndrome in children and adolescents -an IDF consensus report. Pediatr Diabetes. 2007;8(5):299-306. https://doi.org/10.1111/j.1399-5448.2007.00271.x
https://doi.org/10.1111/j.1399-5448.2007...

Other MetS definitions for adolescents were used; these include three or more of the following criteria. Cook and collaborators definition: WC ≥90^thpercentile for age and sex; glucose ≥110 mg/dl; triglycerides ≥110 mg/dl; HDL-C ≥40 mg/dl, and SBP or DBP, ≥90^thpercentile for age, sex, and height.²¹21. Cook S, Weitzman M, Auinger P, Nguyen M, Dietz WH. Prevalence of a metabolic syndrome phenotype in adolescents: findings from the third National Health and Nutrition Examination Survey, 1988-1994. Arch Pediatr Adolesc Med. 2003;157(8):821-27. https://doi.org/10.1001/archpedi.157.8.821
https://doi.org/10.1001/archpedi.157.8.8... De Ferranti and collaborators definition: WC >75th percentile for age and sex; glucose ≥110 mg/dl; triglycerides ≥100 mg/dl; HDL-C <45 mg/dl (15-19 years, males) and <50 mg/dl (everyone else), and SBP or DBP >90^th percentile for age, sex, and height.²²22. De Ferranti SD, Gauvreau K, Ludwig DS, Neufeld EJ, Newburger JW, Rifai N. Prevalence of the metabolic syndrome in American adolescents: findings from the Third National Health and Nutrition Examination Survey. Circulation. 2004 ;110(16):2494-7. https://doi.org/10.1161/01.CIR.0000145117.40114.C7
https://doi.org/10.1161/01.CIR.000014511... Ford and collaborators definition: WC ≥90th percentile for age and sex; glucose ≥100 mg/dl; triglycerides ≥110 mg/dl; HDL-C ≤40 mg/dl, and SBP or DBP, ≥90th percentile for age, sex and height.²³23. Ford ES, Ajani UA, Mokdad AH. The metabolic syndrome and concentrations of C-reactive protein among U.S. youth. Diabetes Care . 2005;28(4):878-81. https://doi.org/10.2337/diacare.28.4.878
https://doi.org/10.2337/diacare.28.4.878...

Metabolic markers. High total cholesterol was defined as ≥200 mg/dl, high LDL-C as ≥130 mg/dl,²⁴24. National Cholesterol Education Program (NCEP) Highlights of the report of the Expert Panel on Blood Cholesterol Levels in Children and Adolescents. Pediatrics. 1992;89(3):495-501.high insulin as ≥15.05 mU/ml, and HOMA-IR as ≥3.43.²⁵25. García-Cuartero B, García-Lacalle C, Jiménez-Lobo C, González-Vergaz A, Calvo-Rey C, Alcázar-Villar MJ,et al. Índice HOMA y QUICKI, insulina y péptido C en niños sanos. Puntos de corte de riesgo cardiovascular. An Pediatr. 2007;66(5):481-90. https://doi.org/10.1157/13102513
https://doi.org/10.1157/13102513...

Statistical analysis

Descriptive analysis included means (SD), medians (25^thpercentile, 75^thpercentile) and percentages. Student’sttest to evaluate mean differences, Kruskal-Wallis to evaluate median differences and Dunn´s test for multiple comparisons. Chi-squared test or Fisher exact test to evaluate differences in percentages. The associations of DP with MetS and with metabolic markers were evaluated using crude and multivariate logistic regression analyses. First, interactions of DP with covariates were evaluated using logistic regression models. If an effect modifier was identified, multiple logistic regressions were run after stratifying by the specific effect modifier. Adjustments were performed by sexual development, smoking, body fat, total physical activity, and energy consumption. Statistical analyses were realized with STATA v9.2 (Stata Corp., TX, USA) and SigmaSTAT 4.0 (Systat Software Inc., CA, USA). Apvalue of <0.05 was considered as statistically significant.

Results

Mean age of the participants was 15.8 ± 1.0 years, 51.7% were women, 28.8% were overweight or obese. MetS prevalence according to different definitions was: 5.1% (IDF); 7.2% (Cook and collaborators); 8.1% (Ford and collaborators), and 16.4% (Ferranti and collaborators).

Three DP were identified (table II): 1) “DP1”, characterized by lower energy intake and lower consumption of cholesterol; 2) “DP2”, characterized by higher intake of protein, cholesterol, saturated fats, sodium, dietary fiber, vitamins, and minerals, and 3) “DP3”, characterized by higher energy, carbohydrate, sucrose, fructose, and alcohol intake and lower protein intake (table III). Regarding food composition, the “DP1” was characterized bytortilla, the “DP2” by whole fat dairy products, meat, refined grains, fruits, and milk beverages, and, the “DP3”, by Mexican food, sweetened beverages, sweet baked goods, sweets with fat, snacks, sweets, and alcohol. It is noteworthy that the energy intake of unhealthy foods (fast foods, sweetened beverages, sweet baked goods, sweets with fat, snacks, sweets, and alcohol) was high in the three DP, being highest in the “DP3” (49.3%), then the “DP1” (40.2%), and finally, the “DP2” (36.9%). Contrariwise, the energy intake of healthy foods (legumes and nuts, fruits, vegetables, wholegrains,tortilla, eggs, fish, poultry, low-fat dairy products, and avocado) was low in the three DP: 17.1% in the “DP3”, 21.2% in the “DP1”, and finally, 20.1% in the “DP2”.

Adolescents consuming mainly the “DP3” were older, mainly female, smokers and physically active (p<0.05 for all, data not shown).

Unhealthy eating habits were different according to DP; more than one half of adolescents who skipped breakfast were in the “DP1” or in the “DP3”. Moreover, lunch away-from-home, fast food consumption away-from-home, eating chicken skin and adding ≥3 teaspoons of sugar to beverages was higher in the “DP3” (p<0.05 for all) (table IV). The remaining eating habits did not differ among dietary groups.

Finally, interactions between sex and DP were found (p<0.05); therefore, multiple logistic regression analyses were performed after stratifying by sex. Among males, the “DP3” was associated with MetS (Cook and colleagues OR, 12.14; 95%CI, 1.66-89.05; de Ferranti and colleagues OR, 5.10; 95%CI, 1.20-21.72, and Ford and colleagues OR, 9.29; 95%CI, 1.44-59.73), high triglycerides (OR, 3.89; 95%CI, 1.01-15.07), and HOMA-IR (OR, 6.66; 95%CI, 1.12-39.70). Also, the “DP2” was associated with AO (OR, 5.11; 95%CI, 1.57-16.66). Females showed no statistically significant association (table V).

Discussion

Our results suggest that DP are associated in different ways with obesity and MetS, and the “DP3” has the greatest risk of MetS, hypertriglyceridemia, and IR, while the “DP2” exhibits a greater risk of AO among adolescent males, but not among females.

The “DP3” was associated with MetS (defined by Cook and colleagues, de Ferranti and colleagues, and Ford and colleagues), hypertriglyceridemia, and IR in this study. Sucrose consumption was higher in the 75th percentile (11.9% of total energy). In this DP, compared with the other two, sucrose consumption exceeds the World Health Organization recommendation (≤10% of total energy intake).²⁶26. World Health Organization. Guideline: Sugars intake for adults and children. Geneva: WHO, 2015.In the Mexican adolescents studied in Ensanut 2006, high-energy beverages (soft drinks, sweetened juices, aguas frescas) accounted for 12.7% of the total kcal/day,²⁷27. Barquera S, Hernandez-Barrera L, Tolentino ML, Espinosa J, Ng SW, Rivera JA,et al. Energy intake from beverages is increasing among Mexican adolescents and adults. J Nutr. 2008;138(12):2454-61. https://doi.org/10.3945/jn.108.092163
https://doi.org/10.3945/jn.108.092163... a figure lower than in our findings (13.2%) in the “DP3”. In Mexican adolescents studied in the Health Workers Cohort Study, a Western DP (characterized by soft drinks, snacks, and corn tortillas) was found to be associated with IR.²⁸28. Romero-Polvo A, Denova-Gutiérrez E, Rivera-Paredez B, Castañón S, Gallegos-Carrillo K, Halley-Castillo E,et al. Association between dietary patterns and insulin resistance in Mexican children and adolescents. Ann NutrMetab. 2012;61(2):142-50. https://doi.org/10.1159/000341493
https://doi.org/10.1159/000341493... Some studies in adult populations suggest that unfavorable diets (rich in sugar-sweetened beverages, fried potatoes, and red and processed meats) are associated with glucose and insulin;²⁹29 Nettleton JA, Hivert MF, Lemaitre RN, McKeown NM, Mozaffarian D, Tanaka T,et al. Meta-analysis investigating associations between healthy diet and fasting glucose and insulin levels and modification by loci associated with glucose homeostasis in data from 15 cohorts. Am J Epidemiol. 2013;15(2):103-15. https://doi.org/10.1093/aje/kws297
https://doi.org/10.1093/aje/kws297... the consumption of fructose-sweetened beverages decreases insulin sensitivity and increases postprandial hypertriglyceridemia.³⁰30. Stanhope KL, Schwarz JM, Keim NL, Griffen SC, Bremer AA, Graham JL,et al. Consuming fructose-sweetened, not glucose-sweetened, beverages increases visceral adiposity and lipids and decreases insulin sensitivity in overweight/obese humans. J Clin Invest. 2009;119(5):1322-34. https://doi.org/10.1172/JCI37385
https://doi.org/10.1172/JCI37385... In addition, one or two servings/day of sugar-sweetened beverages increase the risk for diabetes and MetS.³¹31. Malik VS, Popkin BM, Bray GA, Després JP, Willett WC, Hu FB. Sugar-sweetened beverages and risk of metabolic syndrome and type 2 diabetes: a meta-analysis. Diabetes Care . 2010 ;33(11):2477-83. https://doi.org/10.2337/dc10-1079
https://doi.org/10.2337/dc10-1079... We do not know the mechanism of the relationship between the “DP3” with IR and with triglycerides; however, fructose might play a key role in hepatic IR through activation of the carbohydrate-responsive element-binding protein which prevents insulin from suppressing glucose production and stimulates de novo lipogenesis.³²32. Kim MS, Krawczyk SA, Doridot L, Fowler AJ, Wang JX, Trauger SA,et al. ChREBP regulates fructose-induced glucose production independently of insulin signaling. J Clin Invest . 2016;126(11):4372-86. https://doi.org/10.1172/JCI81993
https://doi.org/10.1172/JCI81993...

Furthermore, in our study, only 21.3% of adolescents consumed the dietary fiber recommendation of at least 14 g /1 000 kcal³³33. Institute of Medicine (U.S.). Standing Committee on the Scientific Evaluation of Dietary Reference Intakes. Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein, and amino acids. Washington DC: National Academies Press, 2005 [cited March 5, 2019]. Available from:https://www.nap.edu/download/10490
https://www.nap.edu/download/10490... and no differences were found between dietary patterns (“DP1”= 20.7%, “DP2” = 26.2% and “DP3”= 16.7%;p= 0.320). These results are similar to a study in Mexican adolescents in which almost 80% did not consume the recommended dietary fiber.²⁸28. Romero-Polvo A, Denova-Gutiérrez E, Rivera-Paredez B, Castañón S, Gallegos-Carrillo K, Halley-Castillo E,et al. Association between dietary patterns and insulin resistance in Mexican children and adolescents. Ann NutrMetab. 2012;61(2):142-50. https://doi.org/10.1159/000341493
https://doi.org/10.1159/000341493...

Fast food accounted for highest energy consumption in the three DP in our study (13.7-15.5%). This reached 16.8% in males from “DP2”, which may explain, in part, the association of this DP with AO. Similar to our study, fast food energy intake in adolescents of the NHANES 2011-2012 study was 16.9% and increased to 18.6% in obese.³⁴34. Vikraman S, Fryar CD, Ogden CL. Caloric intake from fast food among children and adolescents in the United States, 2011-2012. NCHS data brief, no 213. Hyattsville, MD: National Center for Health Statistics, 2015.A study in Iranian adolescents found that fast food consumption in the highest vs. the lowest quartile increased the incidence of AO.³⁵35. Asghari G, Yuzbashian E, Mirmiran P, Mahmoodi B, Azizi F. Fast food intake increases the incidence of metabolic syndrome in children and adolescents: Tehran Lipid and Glucose Study. PLoSOne. 12015;10(10):e0139641. https://doi.org/10.1371/journal.pone.0139641
https://doi.org/10.1371/journal.pone.013...

On the other hand, we found that sodium and sucrose intakes in the “DP3” were higher than in the “DP1”. Previously, a three-times higher risk of developing MetS in the highest vs. the lowest quartile of sweet and salty snacks was found in children and adolescents.³⁶36. Asghari G, Yuzbashian E, Mirmiran P, Bahadoran Z, Azizi F. Prediction of metabolic syndrome by a high intake of energy-dense nutrient-poor snacks in Iranian children and adolescents. Pediatr Res. 2016;79(5):697-704. https://doi.org/10.1038/pr.2015.270
https://doi.org/10.1038/pr.2015.270... Additionally, Mexican school-children, consuming a Western DP (high in sweetened beverages, salty snacks, cakes, and sweets) had more overweight.³⁷37. Rodríguez-Ramírez S, Mundo-Rosas V, García-Guerra A, Shamah-Levy T. Dietary patterns are associated with overweight and obesity in Mexican school-age children. Arch Latinoam Nutr. 2011;61(3):270-8.Moreover, in USA adolescents, sweetened beverage consumption increased 74 g/day per each additional 1g/salt/day.³⁸38. Grimes CA, Wright JD, Liu K, Nowson CA, Loria CM. Dietary sodium intake is associated with total fluid and sugar-sweetened beverage consumption in US children and adolescents aged 2-18 y: NHANES 2005-2008. Am J ClinNutr. 2013;98(1):189-96. https://doi.org/10.3945/ajcn.112.051508
https://doi.org/10.3945/ajcn.112.051508... In a study in children from Mexico City, salty-food consumption was mentioned as one of the reasons for drinking soft sweetened drinks.³⁹39. Théodore F, Bonvecchio A, Blanco I, Irizarry L, Nava A, Carriedo A. Significados culturalmente construidos para el consumo de bebidas azucaradas entre escolares de la Ciudad de México. Rev Panam Salud Publica. 2011 ;30(4):327-34. Unfortunately energy-dense food consumption has increased in children and adolescents; not only because these foods are inexpensive, good-tasting, and available,⁴⁰40. Drewnowski A. Obesity, diets, and social inequalities. Nutr Rev. 2009;67(suppl 1):S36-9. https://doi.org/10.1111/j.1753-4887.2009.00157.x
https://doi.org/10.1111/j.1753-4887.2009... but because of their ability to exert an effect on hedonic and motivational processes.⁴¹41. Berthoud HR. The neurobiology of food intake in an obesogenic environment. Proc Nutr Soc. 2012;71(4):478-87. https://doi.org/10.1017/S0029665112000602
https://doi.org/10.1017/S002966511200060...

Additionally, unhealthy eating habits (skipping breakfast, eating away-from-home, fast food consumption away-from-home, eating chicken skin, and sugar added to beverages) were higher in the “DP3” in our study. An increase in the consumption of calories in USA children and adolescents was found between 1977 and 2006: consumption away-from-home increased 255% during this period and fast foods contributed to the largest energy intake from foods prepared away-from-home.⁴²42. Poti JM, Popkin BM. Trends in energy intake among US children by eating location and food source, 1977-2006. J Am Diet Assoc. 2011 ;111(8):1156-64. https://doi.org/10.1016/j.jada. 2011 .05.007
https://doi.org/10.1016/j.jada. 2011 .05... In Mexican children, the availability of unhealthy foods (snacks, chocolates, sweets, sugary drinks, and antojitos) on the way to school ranged from 22-31%, and foods and beverages eaten away-from-home contributed to obesity increase.⁴³43. Shamah-Levy T, Cuevas-Nasu L, Méndez-Gómez-Humarán I, Jimenez-Aguilar A, Mendoza-Ramirez AJ, Villalpando S. Obesity in Mexican school age children is associated with out-of-home food consumption: in the journey from home to school. Arch Latinoam Nutr . 2011 ;61(3):288-95.On the other hand, Lebanese adolescents consuming a Western DP were more likely to eat away-from-home and to skip breakfast than the traditional DP⁴⁴44. Naja F, Hwalla N, Itani L, Karam S, Sibai AM, Nasreddine L. A Western dietary pattern is associated with overweight and obesity in a national sample of Lebanese adolescents (13-19 years): a cross-sectional study. Br J Nutr. 2015;114(11):1909-19. https://doi.org/10.1017/S0007114515003657
https://doi.org/10.1017/S000711451500365... In our study, such behaviors were more frequent in the “DP3”.

Sample size was higher in females than in males, nevertheless, only significant associations were found in males. We cannot establish a biological reason for this, but in our adolescents MetS prevalence according to Cook and colleagues, was higher in males than females (12.1 vs. 7.6%;p= 0.090), as well as according to Ford and colleagues (11.1 vs. 5.3%;p= 0.007) and de Ferranti and colleagues (19.7 vs. 14.2%;p= 0.061). Energy intake was also higher among males than females (2 795 vs. 2 464 kcal/day;p<0.001). Others have found that, only among males, an increase in the percentage of energy from fat was associated with AO, and a Western DP was associated with a higher risk of overweight and hypertriglyceridemia.⁹9. Song Y, Park MJ, Paik HY, Joung H. Secular trends in dietary patterns and obesity-related risk factors in Korean adolescents aged 10-19 years. Int J Obes (Lond). 2010 ;34(1):48-56. https://doi.org/10.1038/ijo.2009.203
https://doi.org/10.1038/ijo.2009.203... To the contrary, among Korean prepubertal girls, a balanced DP was negatively associated with triglycerides and a Western DP was positively associated with MetS.⁴⁵45. Park SJ, Lee SM, Kim SM, Myoungsook L. Gender specific effect of major dietary patterns on the metabolic syndrome risk in Korean pre-pubertal children. Nutr Res Pract. 2013;7(2):139-45. https://doi.org/10.4162/nrp.2013.7.2.139
https://doi.org/10.4162/nrp.2013.7.2.139... More studies evaluating these associations according to sex are needed.

We must be careful in the interpretation of our results, because the nature of our cross-sectional analysis cannot establish causal relationships. Thus, future studies are required to answer this question. The FFQ is widely used in epidemiological studies due to its advantages; however, it overestimates consumption; therefore, interpretation of results should be conducted with caution. Although food groups were formed according to their nutritional value, it is possible that complete objectivity might not been achieved. Despite such limitations, we found associations between obesity (and MetS) and DP that are similar to those of previous studies. On the other hand, the strengths of the study are that confounders were controlled with multiple logistic regressions.

In conclusion, we found that the “DP3” increased the risk of MetS, hypertriglyceridemia, and IR, and that the “DP2” increased the risk of AO in male adolescents. Moreover, unhealthy eating habits were higher among “DP3” consumers. Promotion of a healthy DP is needed in order to reduce obesity and MetS in adolescents.

Acknowledgments

We thank students, parents, school authorities, and those who participated in data collection. This study was supported by Conacyt, grant 37951-M.

References

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