Annals of Pediatric Endocrinology and Metabolism

Korean Society of Pediatric Endocrinology (대한소아내분비학회)
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Association between hemoglobin glycation index and cardiometabolic risk factors in Korean pediatric nondiabetic population

  • Lee, Bora (Department of Pediatrics, Seoul National University Children's Hospital, Seoul National University College of Medicine) ;
  • Heo, You Jung (Department of Pediatrics, Seoul National University Children's Hospital, Seoul National University College of Medicine) ;
  • Lee, Young Ah (Department of Pediatrics, Seoul National University Children's Hospital, Seoul National University College of Medicine) ;
  • Lee, Jieun (Department of Pediatrics, Inje University Ilsan Paik Hospital) ;
  • Kim, Jae Hyun (Department of Pediatrics, Seoul National University Bundang Hospital) ;
  • Lee, Seong Yong (Department of Pediatrics, Seoul Metropolitan Government-Seoul National University Boramae Medical Center) ;
  • Shin, Choong Ho (Department of Pediatrics, Seoul National University Children's Hospital, Seoul National University College of Medicine) ;
  • Yang, Sei Won (Department of Pediatrics, Seoul National University Children's Hospital, Seoul National University College of Medicine)
  • Received : 2018.07.24
  • Accepted : 2018.11.28
  • Published : 2018.12.30
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Abstract

Purpose: The hemoglobin glycation index (HGI) represents the degree of nonenzymatic glycation and has been positively associated with cardiometabolic risk factors (CMRFs) and cardiovascular disease in adults. This study aimed to investigate the association between HGI, components of metabolic syndrome (MS), and alanine aminotransferase (ALT) in a pediatric nondiabetic population. Methods: Data from 3,885 subjects aged 10-18 years from the Korea National Health and Nutrition Examination Survey (2011-2016) were included. HGI was defined as subtraction of predicted glycated hemoglobin ($HbA1_c$) from measured $HbA1_c$. Participants were divided into 3 groups according to HGI tertile. Components of MS (abdominal obesity, fasting glucose, triglycerides, high-density lipoprotein cholesterol, and blood pressure), and proportion of MS, CMRF clustering (${\geq}2$ of MS components), and elevated ALT were compared among the groups. Results: Body mass index (BMI) z-score, obesity, total cholesterol, ALT, abdominal obesity, elevated triglycerides, and CMRF clustering showed increasing HGI trends from lower-to-higher tertiles. Multiple logistic regression analysis showed the upper HGI tertile was associated with elevated triglycerides (odds ratio, 1.65; 95% confidence interval, 1.18-2.30). Multiple linear regression analysis showed HGI level was significantly associated with BMI z-score, $HbA1_c$, triglycerides, and ALT. When stratified by sex, age group, and BMI category, overweight/obese subjects showed linear HGI trends for presence of CMRF clustering and ALT elevation. Conclusion: HGI was associated with CMRFs in a Korean pediatric population. High HGI might be an independent risk factor for CMRF clustering and ALT elevation in overweight/obese youth. Further studies are required to establish the clinical relevance of HGI for cardiometabolic health in youth.

Keywords

References

  1. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014;384:766-81. https://doi.org/10.1016/S0140-6736(14)60460-8
  2. Fazeli Farsani S, van der Aa MP, van der Vorst MM, Knibbe CA, de Boer A. Global trends in the incidence and prevalence of type 2 diabetes in children and adolescents: a systematic review and evaluation of methodological approaches. Diabetologia 2013;56:1471-88. https://doi.org/10.1007/s00125-013-2915-z
  3. Nam HK, Kim HR, Rhie YJ, Lee KH. Trends in the prevalence of extreme obesity among Korean children and adolescents from 2001 to 2014. J Pediatr Endocrinol Metab 2017;30:517-23.
  4. Lee JH, Kim YM, Kwak MJ, Kim SY, Kim HJ, Cheon CK, et al. Incidence trends and associated factors of diabetes mellitus in Korean children and adolescents: a retrospective cohort study in Busan and Gyeongnam. Ann Pediatr Endocrinol Metab 2015;20:206-12. https://doi.org/10.6065/apem.2015.20.4.206
  5. Styne DM, Arslanian SA, Connor EL, Farooqi IS, Murad MH, Silverstein JH, et al. Pediatric obesity-assessment, treatment, and prevention: an endocrine society clinical practice guideline. J Clin Endocrinol Metab 2017;102:709-57.
  6. Zeitler P, Fu J, Tandon N, Nadeau K, Urakami T, Barrett T, et al. ISPAD clinical practice consensus guidelines 2014. Type 2 diabetes in the child and adolescent. Pediatr Diabetes 2014;15 Suppl 20:26-46. https://doi.org/10.1111/pedi.12179
  7. Cameron FJ, Wherrett DK. Care of diabetes in children and adolescents: controversies, changes, and consensus. Lancet 2015;385:2096-106. https://doi.org/10.1016/S0140-6736(15)60971-0
  8. Seo JY, Kim JH. Validation of surrogate markers for metabolic syndrome and cardiometabolic risk factor clustering in children and adolescents: a nationwide population-based study. PLoS One 2017;12:e0186050. https://doi.org/10.1371/journal.pone.0186050
  9. Nightingale CM, Rudnicka AR, Owen CG, Newton SL, Bales JL, Donin AS, et al. Birthweight and risk markers for type 2 diabetes and cardiovascular disease in childhood: the Child Heart and Health Study in England (CHASE). Diabetologia 2015;58:474-84. https://doi.org/10.1007/s00125-014-3474-7
  10. American Diabetes Association. 6. Glycemic targets: standards of medical care in diabetes-2018. Diabetes Care 2018;41(Suppl 1):S55-S64. https://doi.org/10.2337/dc18-S006
  11. Koenig RJ, Peterson CM, Jones RL, Saudek C, Lehrman M, Cerami A. Correlation of glucose regulation and hemoglobin AIc in diabetes mellitus. N Engl J Med 1976;295:417-20. https://doi.org/10.1056/NEJM197608192950804
  12. Cavagnolli G, Pimentel AL, Freitas PA, Gross JL, Camargo JL. Factors affecting A1C in non-diabetic individuals: review and meta-analysis. Clin Chim Acta 2015;445:107-14. https://doi.org/10.1016/j.cca.2015.03.024
  13. Rohlfing C, Wiedmeyer HM, Little R, Grotz VL, Tennill A, England J, et al. Biological variation of glycohemoglobin. Clin Chem 2002;48:1116-8.
  14. Cohen RM, Snieder H, Lindsell CJ, Beyan H, Hawa MI, Blinko S, et al. Evidence for independent heritability of the glycation gap (glycosylation gap) fraction of HbA1c in nondiabetic twins. Diabetes Care 2006;29:1739-43. https://doi.org/10.2337/dc06-0286
  15. Seo JY, Hwang SS, Kim JH, Lee YA, Lee SY, Shin CH, et al. Distribution of glycated haemoglobin and its determinants in Korean youth and young adults: a nationwide population-based study. Sci Rep 2018;8:1962. https://doi.org/10.1038/s41598-018-20274-8
  16. Herman WH, Ma Y, Uwaifo G, Haffner S, Kahn SE, Horton ES, et al. Differences in A1C by race and ethnicity among patients with impaired glucose tolerance in the Diabetes Prevention Program. Diabetes Care 2007;30:2453-7. https://doi.org/10.2337/dc06-2003
  17. Hempe JM, Gomez R, McCarter RJ Jr, Chalew SA. High and low hemoglobin glycation phenotypes in type 1 diabetes: a challenge for interpretation of glycemic control. J Diabetes Complications 2002;16:313-20. https://doi.org/10.1016/S1056-8727(01)00227-6
  18. Ahn CH, Min SH, Lee DH, Oh TJ, Kim KM, Moon JH, et al. Hemoglobin glycation index is associated with cardiovascular diseases in people with impaired glucose metabolism. J Clin Endocrinol Metab 2017;102:2905-13. https://doi.org/10.1210/jc.2017-00191
  19. Marini MA, Fiorentino TV, Succurro E, Pedace E, Andreozzi F, Sciacqua A, et al. Association between hemoglobin glycation index with insulin resistance and carotid atherosclerosis in non-diabetic individuals. PLoS One 2017;12:e0175547. https://doi.org/10.1371/journal.pone.0175547
  20. Fiorentino TV, Marini MA, Succurro E, Andreozzi F, Sciacqua A, Hribal ML, et al. Association between hemoglobin glycation index and hepatic steatosis in nondiabetic individuals. Diabetes Res Clin Pract 2017;134:53-61. https://doi.org/10.1016/j.diabres.2017.09.017
  21. Soros AA, Chalew SA, McCarter RJ, Shepard R, Hempe JM. Hemoglobin glycation index: a robust measure of hemoglobin A1c bias in pediatric type 1 diabetes patients. Pediatr Diabetes 2010;11:455-61. https://doi.org/10.1111/j.1399-5448.2009.00630.x
  22. Kim JH, Yun S, Hwang SS, Shim JO, Chae HW, Lee YJ, et al. The 2017 Korean National Growth Charts for children and adolescents: development, improvement, and prospects. Korean J Pediatr 2018;61:135-49. https://doi.org/10.3345/kjp.2018.61.5.135
  23. Zimmet P, Alberti KG, Kaufman F, Tajima N, Silink M, Arslanian S, et al. The metabolic syndrome in children and adolescents - an IDF consensus report. Pediatr Diabetes 2007;8:299-306. https://doi.org/10.1111/j.1399-5448.2007.00271.x
  24. Magge SN, Goodman E, Armstrong SC; Committee on Nutrition; Section on Endocrinology; Section on Obesity. The metabolic syndrome in children and adolescents: shifting the focus to cardiometabolic risk factor clustering. Pediatrics 2017;140(2). pii: e20171603. https://doi.org/10.1542/peds.2017-1603.
  25. Vos MB, Abrams SH, Barlow SE, Caprio S, Daniels SR, Kohli R, et al. NASPGHAN clinical practice guideline for the diagnosis and treatment of nonalcoholic fatty liver disease in children: recommendations from the Expert Committee on NAFLD (ECON) and the North American Society of Pediatric Gastroenterology, Hepatology and Nutrition (NASPGHAN). J Pediatr Gastroenterol Nutr 2017;64:319-34. https://doi.org/10.1097/MPG.0000000000001482
  26. Park HK, Hwang JS, Moon JS, Lee JA, Kim DH, Lim JS. Healthy range of serum alanine aminotransferase and its predictive power for cardiovascular risk in children and adolescents. J Pediatr Gastroenterol Nutr 2013;56:686-91. https://doi.org/10.1097/MPG.0b013e31828b4e67
  27. Kang Y, Park S, Kim S, Koh H. Estimated prevalence of adolescents with nonalcoholic fatty liver disease in Korea. J Korean Med Sci 2018;33:e109. https://doi.org/10.3346/jkms.2018.33.e109
  28. McCarter RJ, Hempe JM, Gomez R, Chalew SA. Biological variation in HbA1c predicts risk of retinopathy and nephropathy in type 1 diabetes. Diabetes Care 2004;27:1259-64. https://doi.org/10.2337/diacare.27.6.1259
  29. Hempe JM, Liu S, Myers L, McCarter RJ, Buse JB, Fonseca V. The hemoglobin glycation index identifies subpopulations with harms or benefits from intensive treatment in the ACCORD trial. Diabetes Care 2015;38:1067-74. https://doi.org/10.2337/dc14-1844
  30. Johnson WD, Kroon JJ, Greenway FL, Bouchard C, Ryan D, Katzmarzyk PT. Prevalence of risk factors for metabolic syndrome in adolescents: National Health and Nutrition Examination Survey (NHANES), 2001-2006. Arch Pediatr Adolesc Med 2009;163:371-7. https://doi.org/10.1001/archpediatrics.2009.3
  31. Morrison JA, Friedman LA, Wang P, Glueck CJ. Metabolic syndrome in childhood predicts adult metabolic syndrome and type 2 diabetes mellitus 25 to 30 years later. J Pediatr 2008;152:201-6. https://doi.org/10.1016/j.jpeds.2007.09.010
  32. Pan DA, Lillioja S, Kriketos AD, Milner MR, Baur LA, Bogardus C, et al. Skeletal muscle triglyceride levels are inversely related to insulin action. Diabetes 1997;46:983-8. https://doi.org/10.2337/diab.46.6.983
  33. Kelley DE, Goodpaster BH. Skeletal muscle triglyceride. An aspect of regional adiposity and insulin resistance. Diabetes Care 2001;24:933-41. https://doi.org/10.2337/diacare.24.5.933
  34. Asrih M, Jornayvaz FR. Metabolic syndrome and nonalcoholic fatty liver disease: Is insulin resistance the link? Mol Cell Endocrinol 2015;418 Pt 1:55-65. https://doi.org/10.1016/j.mce.2015.02.018

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