SciELO - Scientific Electronic Library Online

vol.29 issue4Nutritional content of food, and nonalcoholic beverages advertisements broadcasted in children´s slot of Colombian national televisionTexture modified diet: digestibility, nutritional value, and contributions to menu of hospitals and nursing homes author indexsubject indexarticles search
Home Pagealphabetic serial listing  


Services on Demand




Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google


Nutrición Hospitalaria

On-line version ISSN 1699-5198Print version ISSN 0212-1611

Nutr. Hosp. vol.29 n.4 Madrid Apr. 2014 

ORIGINAL / Síndrome metabólico


Metabolic syndrome and associated factors in children and adolescents of a Brazilian municipality

Síndrome metabólico y factores asociados en niños y adolescentes de un municipio brasileño



Jacqueline Costa Dias Pitangueira1, Luciana Rodrigues Silva2, Mônica Leila Portela de Santana3, Maria da Conceição Monteiro da Silva3, Priscila Ribas de Farias Costa1, Vânia D´Almeida4 and Ana Marlúcia de Oliveira Assis5

1Professor. Center for Health Sciences. Federal University of Recôncavo of Bahia. Santo Antônio de Jesus. State of Bahia. Brazil.
2Professor PhD. School of Medicine of Bahia. Head of the Paediatric Gastroenterology and Hepatology Unity. Federal University of Bahia. Salvador. State of Bahia. Brazil.
3Professor PhD. School of Nutrition. Federal University of Bahia. Salvador, state of Bahia, Brazil.
4Professor PhD. Department of Psychobiology. Federal University of São Paulo. São Paulo. Brazil.
5Professor PhD. School of Nutrition. Federal University of Bahia. Salvador. State of Bahia. Brazil.

This study was supported by grants from Fundação de Amparo a Pesquisa do Espírito Santo (FAPESB- no 8814/2006).





Background: the risk factors associated to metabolic syndrome (MS) have been extensively studied in adults, but in children and adolescents it is poorly explored.
Objective: To identify the prevalence of MS and associated factors in children and adolescents.
Methods: A cross-sectional study with 540 children and adolescents from 7 to 14 years of age. The socioeconomic, demographic and lifestyle data and the family history of chronic diseases were reported by the individual and/or guardian and recorded in a structured questionnaire. Biochemical tests (fasting blood glucose, triacylglycerols, reduced high-density lipoprotein, very-low-density lipoprotein, homocysteine and cysteine), an anthropometric assessment and a blood pressure measurement were performed. MS was defined according to the criteria of The National Cholesterol Education Program Adult Treatment Panel III adapted by Ferranti. A Poisson regression was used to identify the factors statistically associated with MS.
Results: The MS prevalence was 12.8%, in which the most frequent component was a decreased high-density lipoprotein level (58.2%), followed by hypertriglyceridemia (41.8%), elevated blood pressure (29.1%), increased waist circumference (26.7%) and hyperglycemia (7.2%). Associations between metabolic syndrome and overweight [prevalence ratio (PR): 2.2 (1.22-3.95)], father education [PR: 2.19 (1.10-4.37)], serum very low-density lipoprotein concentration [PR: 1.08 (1.04-1.11)] and concomitantly increased serum homocysteine and cysteine concentrations [PR: 2.58 (1.32-5.04)] were observed.
Conclusions: The MS prevalence is high in children and adolescents and it is increased in patients with overweight, higher father education, increased serum very-low-density lipoprotein concentrations and a concomitant serum homocysteine and cysteine high levels.

Key words: Metabolic syndrome X. Obesity. Homocysteine. Cysteine. Children.


Introducción: Los factores asociados al Síndrome metabòlico (SM) han sido ampliamente estudiados en adultos, pero aún son poco explorado en niños y adolescentes
Objetivo: Identificar la superioridad de SM y los factores asociados en niños y adolescentes.
Métodos: Se trata de estudio transversal, con 540 niños de 7 a 14 años de edad. Los datos socioeconómicos, demográficos, estilo de vida e historia familiar de enfermedades crònicas fueron informados por la persona y/o responsable y registrados en cuestionario estructurado. Fueron realizadas dosificaciones bioquímicas (glicemia en ayuno, triglicérides, lipoproteína de alta densidad reducida, lipoproteína de muy baja densidad, ho-mocisteina y cisteina), evaluación antropométrica y verificación de la presión arterial. La SM fue definida de acuerdo con los criterios del The National Cholesterol Education Program Adult Treatment Panel III adaptado por Ferranti. Se utilizó regresión de Poisson como técnica estadística para identificar los factores asociados a la SM.
Resultados: La superioridad de la SM fue del 12,8%, siendo a lipoproteína de alta densidad reducida (58,2%) el componente más frecuente, seguido por la hipertrigliceridemia (41,8%), presión arterial aumentada (29,1%), circunferencia de la cintura aumentada (26,7%) e hiperglicemia (7,2%). Fue observada asociación entre SM y exceso de peso (RP: 2,2 [1,22-3,95]), escolaridad paterna (RP: 2,19 [1,10-4,37]), concentración sérica de la lipoproteína de muy baja densidad (RP: 1,08 [1,04-1,11]) y concentraciones séricas simultáneamente aumentadas de homo-cisteina y cisteina (RP: 2,58 [1,32-5,04]).
Conclusiones: La superioridad de SM es elevada en niños y adolescentes y se encuentra aumentada en paciente con exceso de peso, mayor escolaridad paterna, concentraciones séricas aumentadas de la lipoproteína de muy baja densidad, y elevación simultánea de los niveles séricos de homocisteína y cisteína.

Palabras clave: Síndrome metabólico X. Obesidad. Homocis-teína. Cisteína. Niños.

WC: Waist circumference.
TG: Triacylglycerols.
MS: Metabolic syndrome.
BP: Blood pressure.
WHO: World Health Organization.
BMI/A: Body mass index per age.
TC: Total cholesterol.
VLDL-C: Very-low-density lipoprotein cholesterol.
HDL-C: High-density lipoprotein cholesterol.
LDL-C: Low-density lipoprotein cholesterol.
NCEP/ATP III: The National Cholesterol Education
Program Adult Treatment Panel III.
AIC: Akaike´s information criterion.
NHANES: National Health and Nutrition Examination Surveys.
SE: Standard error.
HCY. Homocysteine.
CYS: Cysteine.



The occurrence of obesity in childhood and adolescence has increased in the last 4 decades and has become an important health problem in many regions worldwide1.

The prevalence of overweight and obesity has increased considerably between the years 1974/75 and 2008/09 in Brazilian children and adolescents. During this period, the occurrence of obesity increased by nearly 6-fold, and overweight tripled in children of both genders. In adolescents, the problem expanded with greater intensity among males2. Currently, the prevalences of overweight and obesity in Brazil are 33.5% and 14.3% in children and 20.5% and 4.9% in adolescents, respectively2.

Excessive weight gain in childhood and adolescence may favor the waist circumference (WC) increase and the development of metabolic disorders such as hypertension, hyperglycemia, elevated serum triacylglyc-erols (TG) and decreased high-density lipoprotein1. The combination of 3 or more of these components constitutes metabolic syndrome (MS), a condition that is well established as an additional complication of obesity in adults and is also currently becoming common among children and adolescents. This syndrome is considered an important risk factor for the development of cardiovascular disease and diabetes in children, adolescents and adults3,4.

MS is well defined, but there is no global consensus for its diagnosis, making it difficult to compare the prevalence rates of MS between different regions5. The criteria used for diagnosis in adults are also being adopted in children and adolescents, after adjusting for the pediatric reference standards1,5. However, there is no consensus for the adoption of this practice among all researchers of the subject1,5.

Although excess weight6-8 and insulin resistance have often been associated with MS, the broad range of determining factors has hampered a complete understanding of the pathogenesis of MS.

Other factors have been associated with MS in children and adolescents, such as gender8, low birth weight, fetal macrosomia, low levels of maternal and paternal education7,9, physical inactivity, the time spent on sedentary activities7,9, a family history of obesity, diabetes, hypertension and an unhealthy diet9.

Elevated serum homocysteine concentrations have also recently been associated with MS in adults10-12. However, little is known regarding the relationship of these factors with the occurrence of MS in children.

Thus, although the study of the factors associated with MS in adults has raised the interest of Brazilian researchers, few studies have sought to identify the presence of MS and the alterations that may increase the risk of developing the disease in children and adolescents. This article aimed to identify the prevalence and risk factors associated to MS in children and adolescents.



Study design and sample

This cross-sectional study examined a random sample of 540 children and adolescents aged between 7 and 14 years old from the municipality of Reconcavo Baiano. The data were obtained from a broader study entitled "Strategy to promote a healthy lifestyle and diet at school and at home - an interventional study" and have a power of 80% to identify the prevalence of MS in this population with a significance level of 5%.

Inclusion and exclusion criteria and losses

The study included schoolchildren from 7 to 14 years of age who were enrolled in public or private schools in the urban area of the municipality of Mutuipe, state of Bahia, Brazil, in 2006.

Pregnant adolescents, nursing mothers or schoolchildren with some type of disability or physical trauma that prevented obtaining anthropometric data; those previously diagnosed with diabetes, liver disease or chronic kidney disease; and those using medication to control blood pressure (BP) and lipid profile or medication that alters serum homocysteine and cysteine levels were excluded from the study.

Students from the enrollment list who moved to other municipalities or who were not found were considered losses.

Ethics Statement

The study was approved by the Research Ethics Committee of the School of Nutrition, Federal University of Bahia (number 03/2006). The students´ participation in the study was subject to written permission from parents and/or guardians, who signed an informed consent form after being informed about the objectives of the study.

Data collection

The data were collected by nutritionists and by laboratory technicians duly trained in the standard techniques adopted in this study.

Socioeconomic and demographic data, lifestyle and family history of morbidity

The data regarding socioeconomic status, demographic information and lifestyle and the family history of morbidity were reported by the individuals and/or guardians and recorded in a structured questionnaire.

An index was developed to assess the socioeconomic status that considered the number of rooms in the house, the number of people living in the household and the occupation of the household head. Each variable that composed the socioeconomic index comprised answers ranging from 0 (worst condition) to 4 points (best condition). Thus, the index had a minimum score of 0 and a maximum of 12 points. Those who obtained scores above the median were considered to have an adequate socioeconomic status (reference = 0), while the others were deemed to have an inadequate socioeconomic status (risk = 1).

The parental educational level was categorized with regard to years of study (s 8 years = 0 and > 8 years = 1).

The variables that characterized alcohol consumption (no = 0, yes = 1), smoking (no = 0, yes = 1), the number of daily hours spent watching TV, playing videogames or using the computer (< 2 hours = 0, a 2 hours = 1) and the practice of regular exercise outside of school (yes = 0, no = 1) were adopted to assess the lifestyle of the participants. The presence (1) of chronic non-communicable diseases such as obesity, dyslipidemia and hypertension in first-degree relatives of the participant, as well as their absence (0), were considered as the family history of morbidity.

Anthropometric data

Weight was measured on a digital scale (Filizola®) with a 150 kg capacity and 100 g precision. Weighing was performed with the participant barefoot, wearing lightweight clothing and with an empty bladder. The individual remained standing on the scale platform with the body weight equally distributed between the feet13. Height was measured with a portable stadiometer (Leicester Height Measure). The measurement was performed with the participant barefoot, without accessories or caps on the head, in an upright position with arms hanging at the sides of the body, shoulders relaxed, heels together and with the head positioned in the Frankfort plane13.

The Waist Circumference (WC) was measured in the horizontal plane at the midpoint between the last right rib and the iliac crest using an inelastic fiberglass tape14.

All of the anthropometric measurements were repeated by different evaluators, and the maximum acceptable variations between measurements were as follows: weight = 0.1 kg, height = 0.1 cm and WC = 0.5 cm. The mean of the measurements was adopted as the final measure.

Body mass index (BMI)

The anthropometric diagnosis was based on body mass index per age (BMI/A), considering the growth curves for each gender and the cutoff points proposed by the World Health Organization (WHO) (2007)15. The student was classified as having excess weight when he/she was overweight (BMI/A ≥ 85th percentile) or obese (BMI/A ≥ 97th percentile).

Blood pressure

The Blood Pressure (BP) was obtained using an aneroid sphygmomanometer with a cuff appropriate for the arm circumference and age of the participant following the techniques proposed by the IV Brazilian Guidelines on Hypertension16. The measurements were performed in duplicate, and the mean of the 2 readings was used as the final measure.

The BP was classified according to the criteria proposed by The Fourth Report on the Diagnosis, Evaluation, and Treatment of High Blood Pressure in Children and Adolescents, considering gender, age and height percentile as follows: normal BP (systolic or diastolic BP < 90th percentile), prehypertensive (90th to 95th percentiles), hypertensive (BP ≥ 95th percentile)17.

Biochemical tests

An 8 ml blood sample was collected after a 12-hour fasting period to determine the lipid profile, the fasting blood glucose level and the levels of homocysteine and cysteine. Total cholesterol (TC), very-low-density lipoprotein cholesterol (VLDL-C), high-density lipoprotein cholesterol (HDL-C), triacylglycerols (TG) and fasting blood glucose levels were determined with the enzymatic calorimetric method, while the low-density lipoprotein cholesterol (LDL-C) level was obtained using the Friedewald equation [LDL-C = TC - HDL-C - (TG/5)]. To classify MS, the categorization of the TG, HDL-C and blood glucose levels was performed according to the cutoff points proposed by Ferranti18.

Due to the lack of reference values for VLDL-C in children and adolescents, this parameter was included as a continuous variable in the final model.

Serum homocysteine and cysteine levels were measured using high-performance liquid chromatography with an isocratic elution and fluorimetric detection, which is considered the gold standard for this procedure19. These analyses were performed at the Laboratory of Inborn Errors of Metabolism of the Federal University of Sao Paulo. Because the reference values for homocysteine and cysteine in healthy children and adolescents have not been established, the 80th percentile was adopted as a cutoff point based on the values of the sample itself.


Definition of MS

The criterion proposed by The National Cholesterol Education Program Adult Treatment Panel III (NCEP / ATP III) and adapted by Ferranti et al (2004) was used to characterize the metabolic disorders (MS)18. The criterion entails the presence of 3 or more of the following alterations in the same individual: WC ≥ 75th percentile, BP ≥ 90th percentile, TG ≥ 100 mg/dL, HDL-C < 50 mg/dL and blood glucose > 100 mg/dL.

Due to the lack of reference values for the classification of WC in Brazilian children and adolescents, the classification of the participants in this study was performed according to percentile values of the sample, considering gender and age8,18.

Statistical analysis

The characterization of the study population was conducted through descriptive analysis using prevalence. A Poisson regression was used to identify the factors associated with MS. The variables with a p-value < 0.20 in the bivariate analysis were tested in the multivariate model, and the variables that presented the adopted level of significance of p < 0.05 remained in the final model. The Akaike Information Criterio (AIC) and the Pseudo-R2 were used to evaluate, respectively, the full model adjustment and explanation ability. The analyses were performed using the Stata software (version 12.0).



Characterization of the population, the prevalence of MS and its components

Table I contains the socio-demographic and lifestyle characteristics of the study participants. There was a predominance of females (57.6%) and those who were more than or equal to 10 years old (69.9%). A lower level of education was observed in 91.4% of fathers and 82.8% of mothers.

Regarding the lifestyle of the participants, smoking and alcohol consumption were observed in 0.8% and 12.8% of participants, respectively. Moreover, 24.5% of the students regularly engaged in sports, while 80.1% spent 2 or more hours daily in sedentary activity.

Table II has the clinical and biochemical data of the children and adolescents in the study. Excess weight, hyperhomocysteinemia and hypercysteinemia were identified in 20.5%, 20.5% and 24.7% of the participants, respectively. Among the alterations that compose MS, there was a higher prevalence of low concentrations of HDL-C (58.2%), followed by hypertriglyceridemia (41.8%), elevated BP (29.1%), high WC (26.7%) and hyperglycemia (7.2%).

The prevalence of MS identified among the students in the study was 12.8%. However, the presence of at least 1 component of MS was detected in 85.7% of the participants, and 2 components were found in 32.5% of the students (fig. 1).

Factors associated with MS

Table III has the results of the bivariate analysis of the relationship between MS and the covariates of interest in this study. Statistically significant associations between MS and excess weight (p < 0.001), higher father education (p = 0.01), hyperhomocysteinemia (p < 0.01), hypercysteinemia (p < 0.01), concomitantly elevated serum homocysteine and cysteine concentrations (p < 0.01), increased VLDL-C levels (p < 0.001) and a family history of obesity (p = 0.046) were identified.

The Poisson regression analysis results for MS and the exposure variables are shown in table IV. Excess weight contributed to an increase of 120% in the prevalence of MS compared to the prevalence observed in normal-weight individuals (p < 0.01). The prevalence of MS in students whose fathers studied for more than 8 years was 119% (p = 0.026) higher than that in children and adolescents whose fathers had a lower education level. An increase of 1 mg/dL in the mean VLDL-C value increased the prevalence of MS by 8% (p < 0.001), and the prevalence of MS was 158% higher in students who had serum homocysteine and cysteine concentrations concomitantly elevated compared to that in children and adolescents with adequate concentrations of these biochemical parameters (p < 0.001).

This final model fitted well to the data, showing an AIC (Akaike´s information criterion) improvement from 373.47 for the reduced model (including the outcome variable MS and the independent variable weight excess) to 287.42 when adjusted by the independents variables father education level, VLDL-c value and homocysteine and cysteine high levels (full model), indicating little loss of information when included all the variables of the full model. This final model tested, containing all the exposure variables associated with MS, demonstrated a good explanatory power, measured by the pseudo-R2, indicating that these variables explain 15% of the cases of MS in the population studied (table IV).

A loss was registered in 38 cases (7.04%), of which 37 were not located and 1 was not tested biochemically.



The prevalence of MS in this study was 12.8%, which indicates a clinically relevant condition in the pediatric population. This study also found a higher incidence of MS among children with excess weight, higher paternal education, elevated serum very low-density lipoprotein concentrations and concomitantly elevated serum homocysteine and cysteine levels.

Prevalence of MS and its components

The most frequent component of MS was low HDLC, followed by hypertriglyceridemia, while hyperglycemia was the least frequent. These results confirm the findings of Kelishadi et al (2008)9, which are in agreement regarding the ranking of the MS components; however, these authors found a higher prevalence of low HDL-C (72%) and a lower prevalence of elevated BP (7%) and hyperglycemia (4%).

The early identification of abnormal parameters associated with MS is essential to determine the necessary treatment, to prevent the accumulation of MS components and consequently to prevent the development of MS in childhood. The presence of at least 1 of the identified components among schoolchildren in this study was greater than that found in other regions of the world9,20,21, while the presence of 2 components occurred less frequently than that observed in children and adolescents from Portugal20 and more frequently that that observed in Chinese children21.

The prevalence of MS in children and adolescents (12.8%) found in this study was similar to that recorded by researchers who adopted the same classification criteria in the United States (12.7%)22, Korea (13.4%) and Iran (14.1%)9. In the studies performed in Brazil 23 and in Portugal20, the occurrence of MS was higher (22.6% and 34.9%, respectively) than that observed in the present study, however, the majority of participants in those studies were obese, which may have favored these results. Notably, lower frequencies (6.6% and 2.6%) of MS have been reported in China4,21.

Ferranti et al (2006)22 determined that the prevalence of MS in American adolescents increased from 9.2% to 12.7% in the period from 1988-94 to 1999/2000 according to the National Health and Nutrition Examination Surveys (NHANES) and that this growth is partly related to the higher occurrence of abdominal obesity. The prevalence of MS has remained stable in normal-weight individuals but has grown considerably among those with excess weight (31.2% to 38.6%) in the same period. Thus, these results indicate that the increases in overweight and obesity in children observed in recent years may favor the development of MS in children and adolescents and, therefore, the earlier onset of cardiovascular disease and diabetes.

Factors associated with MS

Other studies4,6-8,21 have also reported an association between excess weight and MS in children and adolescents. MS was 5.1 and 11.1 times more prevalent among adolescents who were overweight and obese, respectively, than those with a normal weight for their height, as reported by Stabelini et al (2012)8. These results indicate that MS may be associated with excess weight in children and adolescents.

The results of several studies conducted to date have not provided consistent evidence of the association of MS with an individual´s life situation. In that context, a higher parental education level was associated with MS, unlike other studies that found no association9 or that found an association between MS and less education7,24. Regarding these results, it is possible to believe that the higher father education level can indicate a better acquisitive power and, consequently, an easier access to industrialized foods at home and at scholar environment and to consumer goods (television, electronics products) which favor a sedentary lifestyle.

This study is one of the few that evaluates the relationship between MS and VLDL-C. From the results, it can be postulated that high serum VLDL-C concentrations lead to hypertriglyceridemia, which results from the increased synthesis of VLDL-C or from reduced triglyceride lipolysis25,26. Consequently, the high levels of VLDL-C also favor a reduction in serum HDL-C levels, which favors the development of MS26,27.

Finally, it is worth mentioning that this study breaks new ground by seeking to identify the relationship between MS and serum homocysteine and cysteine concentrations in children and adolescents. Although few studies have been performed with this age group, recent studies have reported the association between concomitantly elevated serum homocysteine and cysteine concentrations and obesity28,29 and increased WC28 in children and adolescents. The concomitant elevation of serum homocysteine and cysteine levels was also associated with reduced HDL-C levels in adults30.

Therefore, homocysteine and cysteine high levels may enhance the MS development in children and adolescents. Although this study did not observe a significant association between MS and serum homocysteine and cysteine concentrations alone, hyperhomocysteinemia was found to be associated with hypertension and weight gain in children and adolescents by Ganji and Kafai (2003)31 and with increased WC32, hypertension31, low HDL-C 30 and hyperglycemia32 in adults. Recent studies10-12 were also able to identify the occurrence of MS in adults with elevated serum homocysteine concentrations.

Although the causal mechanism between hyperho-mocisteinemia, hypercysteinemia and MS is not completely clarified, some pathophysiological mechanisms have been suggested to explain the role of these parameters in the onset of the metabolic disorders that compose the SM. The causal relation between hyper-homocisteinemia and hypertension have been associated to the arterial stiffening, endothelial dysfunction due the nitric oxide decreased action, serum folate decrease and insulin resistance33. Hyperhomocysteinemia may also promote the HDL-c reduction34 and the tryacilglycerol increase35, because it seems to be responsible for the Apolipoprotein AI factor transcription inhibition involved in the HDL-c synthesis and for the SREBP-1 (sterol regulatory element-binding protein 1) expression increase which is important to the TG synthesis34, 35.

The association between hypercysteinemia and overweight and increased WC may be explained by the fatty acid stimulation synthesis promoted by the cysteine high levels, resulting in adipose tissue accumulation, mainly in the abdominal region. Furthermore, in adipocytes, the cysteine suffers autoxidation and liberates hydrogen peroxide, which acts as a lipo-lysis inhibitor29. The results indicate that the combination of both elevated parameters may promote an increase in the prevalence of MS in children and adolescents.

One of the limitations of the present study can be attributed, in particular, to the nature of its design, which does not allow assessing causality. However, statistical analyses that are appropriate for the study design were adopted as an initial step to identify the factors associated with MS in children and adolescents. Another limitation is related to the absence of an international consensus for classifying MS, which restricts comparison of the results between studies that adopt different criteria. Therefore, one of the most commonly used criteria to diagnose MS was selected20, using cutoff points adapted to the age group studied.

The prevalence of MS is high in children and adolescents and is increased in patients with excess weight, higher father education, increased serum concentrations of very low-density lipoprotein and a concomitant elevation of serum homocysteine and cysteine levels. These findings highlight the need to identify the components of MS and the factors associated with this disease early and, thereby, to control existing alterations and prevent the development of MS in the pediatric population.



The authors would like to thank all students and their parents for their participation.



1. Kim SJ, Lee J, Nam CM, Lee SY. Impact of obesity on metabolic syndrome among adolescents as compared with adults in Korea. Yonsei Med J 2011; 52 (5): 746-52.         [ Links ]

2. IBGE. Pesquisa de orçamentos familiares 2008-2009: antropometria e estado nutricional de crianças, adolescentes e adultos no Brasil. Rio de Janeiro: IBGE, Coordenaçâo de Trabalhos e Rendimentos; 2010.         [ Links ]

3. Codoner-Franch P, Murria-Estal R, Tortajada-Girbes M, del Castillo-Villaescusa C, Valls-Belles V, Alonso-Iglesias E. New factors of cardiometabolic risk in severely obese children: influence of pubertal status. Nutr Hosp 2010; 25 (5): 845-51.         [ Links ]

4. Xu H, Li Y, Liu A, et al. Prevalence of the metabolic syndrome among children from six cities of China. BMC Public Health 2012; 12: 13.         [ Links ]

5. Kassi E, Pervanidou P, Kaltsas G, Chrousos G. Metabolic syndrome: definitions and controversies. BMC Med 2011; 9: 48.         [ Links ]

6. Chen F, Wang Y, Shan X, et al. Association between childhood obesity and metabolic syndrome: evidence from a large sample of Chinese children and adolescents. PLoS One 2012; 7 (10): e47380.         [ Links ]

7. Mehairi AE, Khouri AA, Naqbi MM, et al. Metabolic syndrome among Emirati adolescents: a school-based study. PLoS One 2013; 8 (2): e56159.         [ Links ]

8. Stabelini NA, Bozza R, Ulbrich A, Mascarenhas LP, Boguszewski MC, Campos W. Metabolic syndrome in adolescents of different nutritional status. Arq Bras Endocrinol Metabol 2012; 56 (2): 104-9.         [ Links ]

9. Kelishadi R, Gouya MM, Adeli K, et al. Factors associated with the metabolic syndrome in a national sample of youths: CASPIAN Study. Nutr Metab Cardiovasc Dis 2008; 18 (7): 461-70.         [ Links ]

10. Hajer GR, van der Graaf Y, Olijhoek JK, Verhaar MC, Visseren FL. Levels of homocysteine are increased in metabolic syndrome patients but are not associated with an increased cardiovascular risk, in contrast to patients without the metabolic syndrome. Heart 2007; 93 (2): 216-20.         [ Links ]

11. Bellia C, Bivona G, Scazzone C, Ciaccio M. Association between homocysteinemia and metabolic syndrome in patients with cardiovascular disease. Ther Clin Risk Manag 2007; 3 (6): 999-1001.         [ Links ]

12. Vuksan-Cusa B, Jakovljevic M, Sagud M, et al. Metabolic syndrome and serum homocysteine in patients with bipolar disorder and schizophrenia treated with second generation antipsychotics. Psychiatry Res 2011; 189 (1): 21-5.         [ Links ]

13. Lohman TG, Roche AF, Martorell F. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics Books; 1988.         [ Links ]

14. World Health Organization. Waist circumference and waist-hip ratio report of a WHO expert consultation, Geneva, 8-11 December 2008. Geneva: World Health Organization; 2011.         [ Links ]

15. De OM, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ 2007; 85 (9): 660-7.         [ Links ]

16. IV Brazilian guidelines in arterial hypertension. Arq Bras Cardiol 2004; 82 (Supl.) 4: 7-22.         [ Links ]

17. The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics 2004; 114 (2 Supl. 4th Report): 555-76.         [ Links ]

18. 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.         [ Links ]

19. Pfeiffer CM, Huff DL, Gunter EW. Rapid and accurate HPLC assay for plasma total homocysteine and cysteine in a clinical laboratory setting. Clin Chem 1999; 45 (2): 290-2.         [ Links ]

20. Braga-Tavares H, Fonseca H. Prevalence of metabolic syndrome in a Portuguese obese adolescent population according to three different definitions. Eur J Pediatr 2010; 169 (8): 935-40.         [ Links ]

21. Liu W, Lin R, Liu A, Du L, Chen Q. Prevalence and association between obesity and metabolic syndrome among Chinese elementary school children: a school-based survey. BMC Public Health 2010; 10: 780.         [ Links ]

22. de Ferranti SD, Gauvreau K, Ludwig DS, Newburger JW, Rifai N. Inflammation and changes in metabolic syndrome abnormalities in US adolescents: findings from the 1988-1994 and 1999-2000 National Health and Nutrition Examination Surveys. Clin Chem 2006; 52 (7): 1325-30.         [ Links ]

23. Guimaraes IC, Moura de AA, Guimaraes AC. Metabolic syndrome in Brazilian adolescents: the effect of body weight. Diabetes Care 2008; 31 (2): e4.         [ Links ]

24. Li Y, Yang X, Zhai F, et al. Prevalence of the metabolic syndrome in Chinese adolescents. Br J Nutr 2008; 99 (3): 565-70.         [ Links ]

25. Sposito AC, Caramelli B, Fonseca FA, et al. IV Brazilian Guideline for Dyslipidemia and Atherosclerosis prevention: Department of Atherosclerosis of Brazilian Society of Cardiology. Arq Bras Cardiol 2007; 88 (Supl. 1): 2-19.         [ Links ]

26. Brites FD, Bonavita CD, De GC, et al. Alterations in the main steps of reverse cholesterol transport in male patients with primary hypertriglyceridemia and low HDL-cholesterol levels. Atherosclerosis 2000; 152 (1): 181-92.         [ Links ]

27. Pozzan R, Pozzan R, Magalhaes MEC, Brandao AA, Brandao AP. Dsilipidemia, sindrome metabolica e risco cardiovascular. Revista da SOCERJ 2004; 17 (2): 97-104.         [ Links ]

28. da Silva NP, de Souza FI, Pendezza AI, et al. Homocysteine and cysteine levels in prepubertal children: association with waist circumference and lipid profile. Nutrition 2013; 29 (1): 166-71.         [ Links ]

29. Elshorbagy AK, Smith AD, Kozich V, Refsum H. Cysteine and obesity. Obesity (Silver Spring) 2012; 20 (3): 473-81.         [ Links ]

30. Xiao Y, Zhang Y, Lv X, et al. Relationship between lipid profiles and plasma total homocysteine, cysteine and the risk of coronary artery disease in coronary angiographic subjects. Lipids Health Dis 2011; 10: 137.         [ Links ]

31. Ganji V, Kafai MR. Demographic, health, lifestyle, and blood vitamin determinants of serum total homocysteine concentrations in the third National Health and Nutrition Examination Survey, 1988-1994. Am J Clin Nutr 2003; 77 (4): 826-33.         [ Links ]

32. Rhee EJ, Hwang ST, Lee WY, et al. Relationship between metabolic syndrome categorized by newly recommended by International Diabetes Federation criteria with plasma homocysteine concentration. Endocr J 2007; 54 (6): 995-1002.         [ Links ]

33. van GC, Nanayakkara PW, Stehouwer CD. Homocysteine and blood pressure. Curr Hypertens Rep 2003; 5 (1): 26-31.         [ Links ]

34. Liao D, Yang X, Wang H. Hyperhomocysteinemia and high-density lipoprotein metabolism in cardiovascular disease. Clin Chem Lab Med 2007; 45 (12): 1652-9.         [ Links ]

35. Werstuck GH, Lentz SR, Dayal S, et al. Homocysteine-induced endoplasmic reticulum stress causes dysregulation of the cholesterol and triglyceride biosynthetic pathways. J Clin Invest 2001; 107 (10): 1263-73.         [ Links ]



Jacqueline Pitangueira.

Recibido: 9-XII-2013.
1.a Revisión: 3-I-2014.
Aceptado: 14-I-2014.

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License