Modern Pediatrics. Ukraine. (2021). 5(117): 35-40. doi 10.15574/SP.2021.117.35
Strashok L. A. ², Buznytska O. V.^1
1Kharkіv Medical Academy of Postgraduate Education, Ukraine
²V.N. Karazin Kharkіv National University, Ukraine

For citation: Strashok LA, Buznytska OV. (2021). Anthropometric characteristics of adolescents with signs of metabolic syndrome. Modern Pediatrics. Ukraine. 5(117): 35-40. doi 10.15574/SP.2021.117.35.
Article received: May 22, 2021. Accepted for publication: Sep 08, 2021.

An analysis of recent global research on the prevalence of obesity and its consequences, including metabolic syndrome, among adolescents is a matter of considerable concern. The same unfavorable tendencies are observed in Ukraine among modern youth. Therefore, an effective strategy for the detection and follow-up of adolescents is urgently needed for the timely treatment of obesity and the prevention of threatening complications.
Purpose — to analyze and generalize anthropometrical indicators in adolescents with signs of metabolic syndrome to improve the management of this category of patients.
Materials and methods. 200 obese adolescents (aged 16 years: 100 boys and 100 girls) were examined in the clinic of the Institute of Children and Adolescents Health Care of the National Academy of Medical Sciences of Ukraine. The control group consisted of 30 healthy children of the same age category. The criteria for the diagnosis of metabolic syndrome (MS) in children, proposed by the International Diabetes Federation [IDF, 2007], were used, which allowed to divide patients into two groups: 1 — with signs of MS (50.0%) and 2 — without signs of MS (50.0%), each of which included 100 patients. Patients underwent an anthropometric examination with the calculation of the following indicators: body mass index (BMI), the waist;to;growth ratio (WC/height) and waist circumference to hip circumference ratio (WC/HC). Blood lipid profile as a marker of atherogenesis, carbohydrate metabolism (fasting serum glucose, the level of immunoreactive insulin with the calculation of insulin resistance index HOMA) were also studied in detail.
Results. The anthropometric analysis showed that in adolescents with MS the main indicators (BMI, WC/height, WC/HC), the degree of abdominal obesity were statistically significantly higher (p<0.05). When comparing the results by gender, probable differences were found between boys and girls: indicators of body weight, waist circumference, WC/HC, which were statistically significantly higher in boys (p<0.05). Characterization of lipid metabolism in the patients showed signs of atherogenic dyslipidemia (increased cholesterol levels, low and very low density lipoproteins, atherogenic factor, triglycerides, β-lipoproteins levels and tendencies to lower the levels of high density lipoproteins) with a significant predominance among those surveyed with MS (p<0.05).
Conclusions. Promising careful anthropometric monitoring of obese adolescents will identify and predict trends in the disease, the risk of complications, which will increase the effectiveness of preventive measures for metabolic syndrome.
The research was carried out in accordance with the principles of the Helsinki Declaration. The study protocol was approved by the Local Ethics Committee of all participating institution. The informed consent of the patient was obtained for conducting the studies.
No conflict of interest was declared by the authors.
Key words: adolescents, metabolic syndrome, anthropometry, diagnostics, dyslipidemia.

REFERENCES

1. Al-Hamad Dania, Raman V. (2017). Metabolic syndrome in children and adolescents. Translational Pediatrics. 6 (4): 397-407. https://doi.org/10.21037/tp.2017.10.02; PMid:29184820 PMCid:PMC5682379

2. Buznytska OV. (2019). Diagnostic significance of biochemical indicators of liver fibrogenesis in adolescents with obesity. UBJ. 91 (1): 74-79. https://doi.org/10.15407/ubj91.01.074

3. Campbell MK. (2016). Biological, environmental, and social influences on childhood obesity. Pediatr Res. 79 (1-2): 205-211. https://doi.org/10.1038/pr.2015.208; PMid:26484623

4. Fang Y, Ma Y, Mo D et al. (2019). Methodology of an exercise intervention program using social incentives and gamification for obese children. BMC Public Health. 19 (1): 686-692. https://doi.org/10.1186/s12889-019-6992-x; PMid:31159776 PMCid:PMC6547593

5. Gromnatska N, Cherkas A, Lemishko B, Kulya O. (2019). The pattern of metabolic syndrome in children with abdominal obesity. Georgian Med News. 289: 68-72.

6. Hemmingsson E. (2018). Early childhood obesity risk factors: socioeconomic adversity, family dysfunction, offspring distress, and junk food self-medication. Curr. Obes. Rep. 7 (2): 204-209. https://doi.org/10.1007/s13679-018-0310-2; PMid:29704182 PMCid:PMC5958160

7. Huang JY, Qi SJ. (2015). Childhood obesity. World J Pediatr. 11 (2): 101-107. https://doi.org/10.1007/s12519-015-0018-2; PMid:25920590

8. Kawada T. (2019). Socioeconomic status and childhood metabolic syndrome. Int J Cardiol. 283: 189-195. https://doi.org/10.1016/j.ijcard.2019.01.106; PMid:30890248

9. Marty L, Chambaron S, Nicklaus S, Monnery-Patris S. (2018). Learned pleasure from eating: An opportunity to promote healthy eating in children? Appetite. 1 (120): 265-274. https://doi.org/10.1016/j.appet.2017.09.006; PMid:28890391

10. O'Neill S, L O'Driscoll. (2015). Metabolic syndrome: a closer look at the growing epidemic and its associated pathologies. Obesity Reviews. 16 (1): 1-12. https://doi.org/10.1111/obr.12229; PMid:25407540

11. Schoentgen B, Lancelot C, Le Gall D. (2017). Eating behavior in pediatric obesity: Of the advantages of combining the neurobiological and neuropsychological approaches. Arch Pediatr. 24 (3): 273-279. https://doi.org/10.1016/j.arcped.2016.12.004; PMid:28131560

12. Seo SH, Shim YS. (2019). Association of Sleep Duration with Obesity and Cardiometabolic Risk Factors in Children and Adolescents: A Population-Based Study. Sci Rep. 9 (1): 9463. https://doi.org/10.1038/s41598-019-45951-0; PMid:31263172 PMCid:PMC6603036

13. Spreghini N, Cianfarani S, Spreghini MR et al. (2019). Oral glucose effectiveness and metabolic risk in obese children and adolescents. Acta Diabetol. 56 (8): 955-962. https://doi.org/10.1007/s00592-019-01303-y; PMid:30868315

14. Strashok LA, Buznytska OV. (2020). Indicators of lipid metabolism disorders in the blood serum of adolescents with metabolic syndrome. UBJ. 92 (6): 137-142. https://doi.org/10.15407/ubj92.06.137

15. Tagi VM, Giannini C, Chiarelli F. (2019). Insulin Resistance in Children. Front Endocrinol (Lausanne). 10: 342-348. https://doi.org/10.3389/fendo.2019.00342; PMid:31214120 PMCid:PMC6558106

16. Zimmet P, Alberti KG, Kaufman FT et.al. (2007). IDF Consensus. The metabolic syndrome in children and adolescents – an IDF consensus report. Pediat Diabetes. 5: 299-306. https://doi.org/10.1111/j.1399-5448.2007.00271.x; PMid:17850473