English

Autores/as

  • Arieli Fernandes Dias Português
  • Caroline Brand English
  • Vanilson Batista Lemes Português
  • Adroaldo Cezar Araujo Gaya Português
  • Anelise Reis Gaya Português

DOI:

https://doi.org/10.7322/jhgd.152160

Palabras clave:

adolescents, anthropometry, health

Resumen

Introduction: Metabolic disorders in childhood and adolescence have been increasing considerably. Thus, the importance of performing an early diagnosis is emphasized.

Objective: To analyse the occurrence of metabolic risk using a non-invasive marker in schoolchildren.

Methods: This is a descriptive study with a quantitative approach, with random sample of 174 schoolchildren (70 boys and 104 girls) from 10 state high schools in the city of Passo Fundo, Rio Grande do Sul, Brazil. The height (cm) was verified according to the procedures of the Brazilian Sport Project and the waist circumference (cm) was measured with a flexible and inelastic tape measure. From this the waist-to-height ratio was calculated, which takes into account the proportion of abdominal fat by the individual’s height, considering the cut-off point of Ashwell & Hsieh. For data analysis we used descriptive and chi-square statistics.

Results: The metabolic risk of schoolchildren was 13.8%, when stratified by sex, the occurrences were 11.4% for males and 15.4% for females, but there was no significant difference between the sexes (X2= 0.54; p= 0.45).

Conclusion: The use of non-invasive markers for the diagnosis of metabolic risk indicated a high occurrence of it in schoolchildren, with the girls presenting a higher risk. The use of this method is important because it allows the evaluation of a greater number of schoolchildren and the early identification of health risk. In addition to being a low-cost, easy-to-apply method.

Biografía del autor/a

  • Arieli Fernandes Dias, Português

     Programa de Pós-Graduação em Ciências do Movimento Humano. Grupo de pesquisa Projeto Esporte Brasil (PROESP-Br). Porto Alegre, Rio Grande do Sul, Brasil.

  • Caroline Brand, English

     Programa de Pós-Graduação em Ciências do Movimento Humano. Grupo de pesquisa Projeto Esporte Brasil (PROESP-Br). Porto Alegre, Rio Grande do Sul, Brasil

  • Vanilson Batista Lemes, Português

     Programa de Pós-Graduação em Ciências do Movimento Humano. Grupo de pesquisa Projeto Esporte Brasil (PROESP-Br). Porto Alegre, Rio Grande do Sul, Brasil

  • Adroaldo Cezar Araujo Gaya, Português

     Programa de Pós-Graduação em Ciências do Movimento Humano. Grupo de pesquisa Projeto Esporte Brasil (PROESP-Br). Porto Alegre, Rio Grande do Sul, Brasil

  • Anelise Reis Gaya, Português

     Programa de Pós-Graduação em Ciências do Movimento Humano. Grupo de pesquisa Projeto Esporte Brasil (PROESP-Br). Porto Alegre, Rio Grande do Sul, Brasil

Referencias

1. Ogden CL, Carrol MD, Kit BK, Flegal KM. Prevalence of Obesity and Trends in Body Mass Index Among US Children and Adolescents, 1999-2010. J Am Med Assoc. 2012;307(5):483. DOI: http://dx.doi.org/10.1001/jama.2012.40

2. Pereira-Lancha LO, Campos-Ferraz PL, Lancha AH Jr. Obesity: considerations about etiology, metabolism, and the use of experimental models. Diabetes Metab Syndr Obes. 2012;5:75-87. DOI: http://dx.doi.org/10.2147/DMSO.S25026

3. Andersen LB, Lauersen JB, Brond JC, Anderssen SA, Sardinha LB, Steene-Johannessen J, et al. A new approach to define and diagnose cardiometabolic disorder in children. J Diabetes Res. 2015. DOI: http://dx.doi.org/10.1155/2015/539835

4. Juonala M, Juhola J, Magnussen CG, Wurtz P, Viikari JSA, Thomson R, et al. Childhood environmental and genetic predictors of adulthood obesity: the cardiovascular risk in young Finns Study. J Clin Endocrinol Metab. 2011;96(9):1542-9. DOI: http://dx.doi.org/10.1210/jc.2011-1243

5. Barros MVG, Nahas MV, Hallal PC, Farias Junior JC, Florindo AA, Barros SSH. Effectiveness of a school-based intervention on physical activity for high school students in Brazil: the Saude na Boa project. J Phys Act Health. 2009;6(2):163-9.

6. Kahan D, Mckenzie TL. The Potential and Reality of Physical Education in Controlling Overweight and Obesity. Am J Public Health. 2015;105(4):4-11. DOI: http://dx.doi.org/10.2105/AJPH.2014.302355

7. Oliveira LCV, Braga FCC, Lemes VB, Dias AF, Brand C, Mello JB, et al. Effect of na intervention in Physical education classes on health related levels of physical fitness in youth. Rev Bras Ativ Fís Saúde. 2017;22(1):46-53. DOI: http://dx.doi.org/10.12820/rbafs.v.22n1p46-53

8. Sardinha LB, Santos DA, Silva AM, Grøntved A, Andersen LB, Ekelund U. A comparison between BMI, Waist Circumference, and Waist-To-Height Ratio for identifying cardio-metabolic risk in children and adolescents. PLoS One. 2016;11(2): e0149351. DOI: http://dx.doi.org/10.1371/journal.pone.0149351

9. Okada R, Yasuda Y, Tsushita K, Wakai K, Hamajima N, Matsuo S. Upper-normal waist circumference is a risk marker for metabolic syndrome in normal-weight subjects. Nutr Metab Cardiovasc Dis. 2016;26(1):67-76. DOI: http://dx.doi.org/10.1016/j.numecd.2015.10.001

10. El Mabchour A, Delisle H, Vilgrain C, Larco P, Sodjinou R, Batal M. Specific cut-off points for waist circumference and waist-to-height ratio as predictors of cardiometabolic risk in Black subjects: a cross-sectional study in Benin and Haiti. Diabetes Metab Syndr Obes. 2015;8:513-23. DOI: http://dx.doi.org/10.2147/DMSO.S88893

11. Ashwell M, Hsieh SD. Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health risks of obesity and how its use could simplify the international public health message on obesity. Int J Food Sci Nutr. 2005;56(5):303-7. DOI: http://dx.doi.org/10.1080/09637480500195066

12. Browning LM, Hsieh SD, Ashwell M. A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0·5 could be a suitable global boundary value. Nutr Res Rev. 2010;23(2):247-69. DOI: http://dx.doi.org/10.1017/S0954422410000144

13. Gaya ACA, Garlipp D, Silva M, Et A. Ciências do movimento humano: Introdução à metodologia da pesquisa. Artmed, 2008.

14. Callaway CW, Chumlea WC, Bouchard C, Himes JH, Lohman TG, Martin AD, et al. Circumferences. In: Lohman TG, Roche AF, Martorell R, editors. Anthropometric standardization reference manual. Champaign: Human Kinetics Books; 1991.

15. Gaya A, Lemos A, Gaya A, Teixeira D, Pinheiro E, Moreira R. Projeto Esporte Brasil (PROESP-Br). Manual de testes e avaliação. 2012; p.1-20.

16. Andersen LB, Harro M, Sardinha LB, Froberg K, Ekelund U, Brage S, et al. Physical activity and clustered cardiovascular risk in children: a cross-sectional study. Lancet. 2006;368(9532):299-304. DOI: http://dx.doi.org/10.1016/S0140-6736(06)69075-2

17. Schröder H, Ribas L, Koebnick C, Funtikova A, Gomez SF, Fíto M, et al. Prevalence of abdominal obesity in Spanish children and adolescents. Do we need waist circumference measurements in pediatric practice? PLoS One. 2014;9(1):e87549. DOI: http://dx.doi.org/10.1371/journal.pone.0087549

18. Suder A, Janusz M, Jagielski P, Głodzik J, Pałka T, Cisoń T, et al. Prevalence and risk factors of abdominal obesity in Polish rural children. Homo. 2015;66(4):357-68. DOI: http://dx.doi.org/10.1016/j.jchb.2014.09.008

19. Xi B, Mi J, Zhao M, Zhang T, Jia C, Li J, et al. Trends in abdominal obesity among us children and adolescents. Pediatrics. 2014;134(2):334-9. DOI: http://dx.doi.org/10.1542/peds.2014-0970

20. Carson V, Tremblay MS, Chaput JP, Chastin SF. Associations between sleep duration, sedentary time, physical activity, and health indicators among Canadian children and youth using compositional analyses. Appl Physiol Nutr Metab. 2016;41(6 Suppl.3):294-302. DOI: http://dx.doi.org/10.1139/apnm-2016-0026

21. Pinto ICS, Arruda IKG, Diniz AS, Cavalcanti AMTS. Prevalence of overweight and abdominal obesity according to anthropometric parameters and the association with sexual maturation in adolescent schoolchildren. Cad Saúde Pública. 2010;26(9):1727-37. DOI: http://dx.doi.org/10.1590/S0102-311X2010000900006

22. Moraes AC, Falcão MC. Lifestyle factors and socioeconomic variables associated with abdominal obesity in Brazilian adolescents. Ann Hum Biol. 2013;40(1):1-8. DOI: http://dx.doi.org/10.3109/03014460.2012.745900

23. Carvalho CA, Fonseca PCA, Barbosa JB, Machado SP, Santos AM, Silva AAM. Associação entre fatores de risco cardiovascular e indicadores antropométricos de obesidade em universitários de São Luís, Maranhão, Brasil. Cien Saúde Coletiva. 2015;20(2):479-90. DOI: http://dx.doi.org/10.1590/1413-81232015202.02342014

24. Taylor RW, Jones IE, Williams SM, Goulding A. Evaluation of waist circumference, waist to hip ratio, and the conicity index as screening tools for high trunk fat mass, as measured by dual energy X-ray absorptiometry in children aged 3-19y. Am J Clin Nutr. 2000;72(2):490-5. DOI: http://dx.doi.org/10.1093/ajcn/72.2.490

25. Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: Systematic review and meta-analysis. Obes Rev. 2012;13(3):275-86. DOI: http://dx.doi.org/10.1111/j.1467-789X.2011.00952.x

26. Ribeiro-Silva RC, Florence TCM, Conceição-Machado MEP, Fernandes GB, Couto RD. Anthropometric indicators for prediction of metabolic syndrome in children and adolescents: a population-based study. Rev Bras Saude Mater Infant. 2014;14(2):173-81. DOI: http://dx.doi.org/10.1590/S1519-38292014000200007

Publicado

2018-11-28

Número

Sección

Artigos Originais