Home Metabolic risk factors in prepubertal and pubertal patients with overweight and obesity
Article
Licensed
Unlicensed Requires Authentication

Metabolic risk factors in prepubertal and pubertal patients with overweight and obesity

  • Matheus Alves Alvares EMAIL logo , Guilherme Sanchez Wanderley , Isabela Mesquita Mitre , Alessandra Caivano Rodrigues Ribeiro and Cristiane Kochi
Published/Copyright: July 10, 2023

Abstract

Objectives

Metabolic syndrome (MetS) is a cluster of conditions linked to obesity that increases cardiovascular risk. We evaluated the frequency of clinical abnormalities associated with overweight and obesity in childhood, to determine whether a diagnosis of MetS is appropriate in this population.

Methods

Cross-sectional study with 116 pubertal and prepubertal children with a mean age (SD) of 10.9 (2.5) years, with overweight and obesity. We defined MetS using the International Diabetes Federation criteria, regardless of the age.

Results

45 patients met the criteria, 20 had at least one metabolic abnormality in addition to a high waist circumference (WC), and seven with WC below percentile 90th, had at least one metabolic abnormality. The prepubertal had higher zBMI [3.1 (2.6–3.8) vs. 2.8 (2.4–3.3); p=0.037], less lean body mass (kg) [27.13 (7.3) vs. 34.13 (9.8); p=0.005] and a similar frequency of non-alcoholic fatty liver disease (NAFLD) compared to the pubertal [44.7 vs. 35.9; p=0.323]. Prepubertal with NAFLD had higher zBMI, lower HDL levels, higher TG/HDL ratios and higher fat percentages; while pubertal with NAFLD had higher WC/height, aspartate aminotransferase and oxaloacetic transaminase.

Conclusions

The diagnosis of MetS in childhood is not fundamental. Individualized management, focusing on the earliest age groups, in which we identified a more severe degree of obesity, should be done. We also recommend screening for NAFLD in all ages, due to the high prevalence observed.


Corresponding author: Matheus Alves Alvares, Santa Casa de São Paulo School of Medical Sciences, Rua Dr. Cesário Mota Júnior, 112, Vila Buarque, São Paulo, SP, Brazil, CEP: 01238-010, Phone: +55 (11) 3367 7883, E-mail:

  1. Research funding: None declared.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. Matheus Alves Alvares: Conceptualization, Formal analysis, Methodology, Project administration, Writing original draft, Writing review & editing. Guilherme Sanchez Wanderley: Writing review & editing. Isabela Mesquita Mitre: Writing review & editing. Alessandra Caivano Rodrigues Ribeiro: Investigation, Methodology, Project Administration, Writing original draft. Cristiane Kochi: Conceptualization, Formal analysis, Methodology, Project administration, Supervision, Writing original draft, Writing review & editing

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Informed consent was obtained from all individuals included in this study. Parents or guardians signed the consent form, and the patients themselves signed the assent form.

  5. Ethical approval: This study was approved by the Research Ethics Committee of Santa Casa de São Paulo with opinion number 4,927,362.

References

1. World Health Organization. Obesity and overweight. Available at: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight [Accessed 20 Apr 2022].Search in Google Scholar

2. World Health Organization. Report of the commission on ending childhood obesity. Geneva: WHO; 2016. Available at: https://www.who.int/publications/i/item/9789241510066 [Accessed 20 Apr 2022].Search in Google Scholar

3. Reaven, GM. Role of insulin resistance in human disease. Diabetes 1988;37:1595–607. https://doi.org/10.2337/diab.37.12.1595.Search in Google Scholar PubMed

4. Wittcopp, C, Conroy, R. Metabolic syndrome in children and adolescents. Pediatr Rev 2016;37:193–202. https://doi.org/10.1542/pir.2014-0095.Search in Google Scholar PubMed

5. Al-Hamad, D, Raman, V. Metabolic syndrome in children and adolescents. Transl Pediatr 2017;6:397–407. https://doi.org/10.21037/tp.2017.10.02.Search in Google Scholar PubMed PubMed Central

6. Magge, SN, Goodman, E, Armstrong, SC. The metabolic syndrome in the child and adolescent: shifting the focus to cardiometabolic risk factor aggregation. Pediatrics 2017;140:e20171603. https://doi.org/10.1542/peds.2017-1603.Search in Google Scholar PubMed

7. Lee, AM, Gurka, MJ, DeBoer, MD. Trends in metabolic syndrome severity and lifestyle factors among adolescents. Pediatrics 2016;137:e20153177. https://doi.org/10.1542/peds.2015-3177.Search in Google Scholar PubMed PubMed Central

8. Messiah, SE, Arheart, KL, Luke, B, Lipshultz, SE, Miller, TL. Relationship between body mass index and metabolic syndrome risk factors among 8- to 14-year-old U.S. children, 1999 to 2002. J Pediatr 2008;153:215–21. https://doi.org/10.1016/j.jpeds.2008.03.002.Search in Google Scholar PubMed

9. Walker, SE, Gurka, MJ, Oliver, MN, Johns, DW, DeBoer, MD. Racial/ethnic discrepancies in the metabolic syndrome begin in childhood and persist after adjustment for environmental factors. Nutr Metabol Cardiovasc Dis 2012;22:141–8. https://doi.org/10.1016/j.numecd.2010.05.006.Search in Google Scholar PubMed PubMed Central

10. Ford, ES, Li, C, Zhao, G, Pearson, WS, Mokdad, AH. Prevalence of the metabolic syndrome among U.S. adolescents using the International Diabetes Federation definition. Diabetes Care 2008;3:587–9. https://doi.org/10.2337/dc07-1030.Search in Google Scholar PubMed

11. World Health Organization. BMI-for-age (5–19 years). Available at: https://www.who.int/tools/growth-reference-data-for-5to19-years/indicators/bmi-for-age [Accessed 20 Apr 2022].Search in Google Scholar

12. Savva, SC, Tornaritis, M, Savva, ME, Kourides, Y, Panagi, A, Silikiotou, N, et al.. Waist circumference and waist-to-height ratio are better predictors of cardiovascular disease risk factors in children than body mass index. Int J Obes Relat Metab Disord 2000;24:1453–8. https://doi.org/10.1038/sj.ijo.0801401.Search in Google Scholar PubMed

13. Marshall, WA, Tanner, JM. Variations in the pattern of pubertal changes in girls. Arch Dis Child 1969;44:291–303. https://doi.org/10.1136/adc.44.235.291.Search in Google Scholar PubMed PubMed Central

14. Marshall, WA, Tanner, JM. Variations in the pattern of pubertal changes in boys. Arch Dis Child 1970;45:13–23. https://doi.org/10.1136/adc.45.239.13.Search in Google Scholar PubMed PubMed Central

15. Flynn, JT, Kaelber, DC, Baker-Smith, CM, Blowey, D, Carroll, AE, Daniels, SR, et al.. Clinical practice guideline for screening and management of high blood pressure in children and adolescents. Pediatrics 2017;140:e20171904. https://doi.org/10.1542/peds.2017-1904.Search in Google Scholar PubMed

16. Pereira, A, Gagliardi, A, Lottenberg, A, Chacra, A, Faludi, A. I Brazilian guideline of familial hypercholesterolemia (HF). Arq Bras Cardiol 2012;99:1–28. https://doi.org/10.5935/abc.20120202.Search in Google Scholar PubMed

17. Matthews, DR, Hosker, JP, Rudenski, AS, Naylor, BA, Treacher, DF, Turner, RC. Homeostasis model assessment: insulin resistance and beta cell function of fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412–9. https://doi.org/10.1007/bf00280883.Search in Google Scholar

18. Matsuda, M, DeFronzo, RA. Insulin sensitivity indices obtained by oral glucose tolerance testing: comparison with the euglycemic insulin armband. Diabetes Care 1999;22:1462–70. https://doi.org/10.2337/diacare.22.9.1462.Search in Google Scholar PubMed

19. Kim, SH, Lee, JM, Kim, JH, Kim, KG, Han, JK, Lee, KH, et al.. Appropriateness of a donor liver with respect to macrosteatosis: application of artificial neural networks to US images – initial experience. Radiology 2005;234:793–803. https://doi.org/10.1148/radiol.2343040142.Search in Google Scholar PubMed

20. Hernaez, R, Lazo, M, Bonekamp, S, Kamel, I, Brancati, FL, Guallar, E, et al.. Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: a meta-analysis. Hepatology 2011;54:1082–90. https://doi.org/10.1002/hep.24452.Search in Google Scholar PubMed PubMed Central

21. Dasarathy, S, Dasarathy, J, Khiyami, A, Joseph, R, Lopez, R, McCullough, AJ. Validity of real-time ultrasound in the diagnosis of hepatic steatosis: a prospective study. J Hepatol 2009;51:1061–7. https://doi.org/10.1016/j.jhep.2009.09.001.Search in Google Scholar PubMed PubMed Central

22. Alberti, KG, Zimmet, P, Shaw, J. Metabolic syndrome–a new world-wide definition. A consensus statement from the International Diabetes Federation. Diabet Med 2006;23:469–80. https://doi.org/10.1111/j.1464-5491.2006.01858.x.Search in Google Scholar PubMed

23. Freedman, DS, Khan, LK, Dietz, WH, Srinivasan, SR, Berenson, GS. Relationship of childhood obesity to risk factors for coronary heart disease in adult life: the Bogalusa Heart Study. Pediatrics 2001;108:712–8. https://doi.org/10.1542/peds.108.3.712.Search in Google Scholar PubMed

24. Simmonds, M, Llewellyn, A, Owen, CG, Woolacott, N. Predicting adult obesity from childhood obesity: a systematic review and meta-analysis. Obes Rev 2016;17:95–107. https://doi.org/10.1111/obr.12334.Search in Google Scholar PubMed

25. Di Cesare, M, Soric, M, Bovet, P, Miranda, JJ, Bhutta, Z, Stevens, GA, et al.. The epidemiological burden of obesity in childhood: a worldwide epidemic requiring urgent action. BMC Med 2019;17:212. https://doi.org/10.1186/s12916-019-1449-8.Search in Google Scholar PubMed PubMed Central

26. Silva, CC, Zambon, MP, Vasques, ACJ, Camilo, DF, Antonio, MRGM, Geloneze, B. The threshold value for identifying insulin resistance (HOMA-IR) in an admixed adolescent population: a hyperglycemic clamp validated study. Arch Endocrinol Metab 2023;67:119–25.10.20945/2359-3997000000533Search in Google Scholar PubMed PubMed Central

27. Cuartero, G, Lacalle, CG, Lobo, CJ, Vergaz, AG, Rey, CC, Villar, MJA, et al.. Índice HOMA y QUICKI, insulina y péptido C en niños sanos. Puntos de corte de riesgo cardiovascular. Anales de Pediatría 2007;66:481–90. https://doi.org/10.1157/13102513.Search in Google Scholar PubMed

28. Page, KA, Luo, S, Wang, X, Chow, T, Alves, J, Buchanan, TA, et al.. Children exposed to maternal obesity or gestational diabetes mellitus during early fetal development have hypothalamic changes that predict future weight gain. Diabetes Care 2019;42:1473–80. https://doi.org/10.2337/dc18-2581.Search in Google Scholar PubMed PubMed Central

29. Godfrey, KM, Reynolds, RM, Prescott, SL, Nyirenda, M, Jaddoe, VWV, Eriksson, JG, et al.. Influence of maternal obesity on the long-term health of offspring. Lancet Diabetes Endocrinol 2017;5:53–64. https://doi.org/10.1016/s2213-8587(16)30107-3.Search in Google Scholar PubMed PubMed Central

30. Sun, X, Li, P, Yang, X, Li, W, Qiu, X, Zhu, S. From genetics and epigenetics to the future of precision treatment for obesity. Gastroenterol Rep 2017;5:266–70. https://doi.org/10.1093/gastro/gox033.Search in Google Scholar PubMed PubMed Central

31. Oken, E, Fields, DA, Lovelady, CA, Redman, LM. TOS scientific position statement: breastfeeding and obesity. Obesity 2017;25:1864–6. https://doi.org/10.1002/oby.22024.Search in Google Scholar PubMed PubMed Central

32. Brambilla, P, Pietrobelli, A. Behind and beyond the pediatric metabolic syndrome. Ital J Pediatr 2009;35:41. https://doi.org/10.1186/1824-7288-35-41.Search in Google Scholar PubMed PubMed Central

33. Weihe, P, Weihrauch-Blüher, S. Metabolic syndrome in children and adolescents: diagnostic criteria, therapeutic options, and perspectives. Curr Obes Rep 2019;8:472–9. https://doi.org/10.1007/s13679-019-00357-x.Search in Google Scholar PubMed

34. Marcovecchio, ML, Chiarelli, F. Metabolic syndrome in youth: chimera or useful concept? Curr Diabetes Rep 2013;13:56–62. https://doi.org/10.1007/s11892-012-0331-2.Search in Google Scholar PubMed

35. Higgins, PB, Gower, BA, Hunter, GR, Goran, MI. Defining health-related obesity in prepubertal children. Obes Res 2001;9:233–40. https://doi.org/10.1038/oby.2001.27.Search in Google Scholar PubMed

36. Stewart, J, McCallin, T, Martinez, J, Chacko, S, Yusuf, S. Hyperlipidemia. Pediatr Ver 2020;41:393–402. https://doi.org/10.1542/pir.2019-0053.Search in Google Scholar PubMed

37. Khan, L. Overview of dyslipidemia in childhood and adolescence: why is it important and what do we do about it? Pediatr Ann 2021;50:e4–9. https://doi.org/10.3928/19382359-20201207-01.Search in Google Scholar PubMed

38. Saadeh, S, Younossi, ZM, Remer, EM, Gramlich, T, Ong, JP, Hurley, M, et al.. The utility of radiological imaging in nonalcoholic fatty liver disease. Gastroenterology 2002;123:745–50. https://doi.org/10.1053/gast.2002.35354.Search in Google Scholar PubMed

39. Pelicciari, C, Artioli, TO, Longui, CA, Monte, O, Kochi, C. The impact of COVID-19 in children and adolescents with obesity in Brazil. Arch Endocrinol Metab 2022;66:256–60. https://doi.org/10.20945/2359-3997000000462.Search in Google Scholar PubMed PubMed Central

Received: 2022-10-19
Accepted: 2023-06-21
Published Online: 2023-07-10
Published in Print: 2023-08-28

© 2023 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Original Articles
  3. Metabolic risk factors in prepubertal and pubertal patients with overweight and obesity
  4. Blood pressure in girls with central precocious puberty receiving GnRH analogue therapy
  5. Norethindrone dosing for adequate menstrual suppression in adolescents
  6. Apparent diffusion coefficient (ADC) measurements and morphometric evaluation of the cranium in age-matched children with central precocious puberty
  7. Characteristics of vitamin D deficiency hypocalcemia inpatient admissions at a single tertiary center
  8. Early pregnancy exposure of maternal triglyceride levels and its effects on birth weight
  9. Evaluation of the clinical, biochemical, and genetic presentation of neonatal and adult-onset 5,10-methylene tetrahydrofolate reductase (MTHFR) deficiency in patients from Pakistan
  10. Congenital hypothyroidism in Bogotá, Colombia: a current description (2015–2021)
  11. Case Reports
  12. Case report: mitochondrial diabetes mellitus in a Chinese family due to m.3243A>G
  13. Novel pathogenic variant of DICER1 in an adolescent with multinodular goiter, ovarian Sertoli–Leydig cell tumor and pineal parenchymal tumor of intermediate differentiation
  14. Fibroblast growth factor 23 levels in cord and peripheral blood during early neonatal period as possible predictors of affected offspring of X-linked hypophosphatemic rickets: report of three female cases from two pedigrees
  15. A rare cause of hyperphenylalaninemia: four cases from a single family with DNAJC12 deficiency
  16. The benefit of rhGH therapy in a Chinese child with 12q14 microdeletion syndrome: a case report
  17. Adjustment of octreotide dose given via insulin pump based on continuous glucose monitoring (CGM) in a child with congenital hyperinsulinism
Downloaded on 15.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/jpem-2022-0532/html
Scroll to top button