Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Pediatrics

Contribution of insulin resistance to the relationship between sugar-sweetened beverage intake and a constellation of cardiometabolic abnormalities in adolescents

International Journal of Obesity volume 45, pages 828–839 (2021)Cite this article

Subjects

Abstract

Background

Insulin resistance (IR) is a pathophysiological construct that derives a series of metabolic disturbances that promote cardiometabolic dysfunction. This study evaluated mediating and modifying effects of homeostatic model assessment-based IR (HOMA-IR) on the association between sugar-sweetened beverage (SSB) consumption and a constellation of adolescent cardiometabolic abnormalities.

Methods

Comprehensive data on sociodemographics, diet, physical activity, and anthropometric and biochemical parameters for 1454 adolescents were obtained from a large-scale representative study for adolescent metabolic syndrome (MetS) conducted in Taiwan. The original (HOMA1-IR) and updated nonlinear (HOMA2-IR) HOMA-IR indicators were used as IR biomarkers. Principal component (PC) analysis was employed to create reduced groups of variables and risk scores for retained PCs.

Results

Higher SSB intake was associated with higher levels of HOMA1-IR and HOMA2-IR, and the two IR biomarkers were positively correlated with metabolic dysfunction clustering. Compared with SSB nondrinkers, adolescents who consumed >500 mL/day of hand-shaken high-fructose corn syrup beverages (HHB) had a 0.22 increase in the number of abnormal MetS components, and HOMA-IR mediation explained 33.9–37.9% of the effect. IR biomarkers accounted for 26.5–31.0% of the relationship between >500 mL/day of SSB consumption and bodyweight-enhanced PC scores. The effects of HOMA-IR indicators on all bodyweight-related factors were consistently intensified among >350 mL/day HHB drinkers (all Pinteraction < 0.05).

Conclusions

Fructose-rich SSB intake correlates with a constellation of cardiometabolic abnormalities in adolescents, and this association may be partly mediated by HOMA-IR levels. The adverse effects of HOMA-IR on bodyweight-associated cardiometabolic risk factors depend on the type of SSB consumption, with enhanced risks observed in the intake of high amounts of HFCS-containing SSBs.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Schematic diagram of data analysis for possible associations between sugar-sweetened beverage (SSB) intake, homeostasis model assessment (HOMA)-based insulin resistance (IR), and cardiometabolic (CarMet) risk.

Similar content being viewed by others

References

  1. Shashaj B, Bedogni G, Graziani MP, Tozzi AE, DiCorpo ML, Morano D, et al. Origin of cardiovascular risk in overweight preschool children: a cohort study of cardiometabolic risk factors at the onset of obesity. JAMA Pediatr. 2014;168:917–24.

    Article  PubMed  Google Scholar 

  2. Gaston SA, Tulve NS, Ferguson TF. Abdominal obesity, metabolic dysfunction, and metabolic syndrome in U.S. adolescents: National Health and Nutrition Examination Survey 2011–2016. Ann Epidemiol. 2019;30:30–6.

    Article  PubMed  Google Scholar 

  3. Heshmat R, Hemati Z, Qorbani M, Nabizadeh Asl L, Motlagh ME, Ziaodini H, et al. Metabolic syndrome and associated factors in Iranian children and adolescents: the CASPIAN-V study. J Cardiovasc Thorac Res. 2018;10:214–20.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Vanlancker T, Schaubroeck E, Vyncke K, Cadenas-Sanchez C, Breidenassel C, Gonzalez-Gross M, et al. Comparison of definitions for the metabolic syndrome in adolescents. The HELENA study. Eur J Pediatr. 2017;176:241–52.

    Article  PubMed  Google Scholar 

  5. Kim S, So WY. Prevalence of metabolic syndrome among Korean adolescents according to the national cholesterol education program, adult treatment panel III and international diabetes federation. Nutrients. 2016;8:588.

    Article  PubMed Central  Google Scholar 

  6. Lin WT, Lee CY, Tsai S, Huang HL, Wu PW, Chin YT, et al. Clustering of metabolic risk components and associated lifestyle factors: a nationwide adolescent study in Taiwan. Nutrients. 2019;11:584.

    Article  CAS  PubMed Central  Google Scholar 

  7. Song P, Yu J, Chang X, Wang M, An L. Prevalence and correlates of metabolic syndrome in Chinese children: the China Health and Nutrition Survey. Nutrients. 2017;9:79.

    Article  PubMed Central  Google Scholar 

  8. Morrison JA, Friedman LA, Gray-McGuire C. Metabolic syndrome in childhood predicts adult cardiovascular disease 25 years later: the princeton lipid research clinics follow-up study. Pediatrics. 2007;120:340–5.

    Article  PubMed  Google Scholar 

  9. 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.

    Article  CAS  PubMed  Google Scholar 

  10. DeBoer MD, Gurka MJ, Woo JG, Morrison JA. Severity of metabolic syndrome as a predictor of cardiovascular disease between childhood and adulthood: the Princeton lipid research cohort study. J Am Coll Cardiol. 2015;66:755–7.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Iglesias Molli AE, Penas Steinhardt A, Lopez AP, Gonzalez CD, Vilarino J, Frechtel GD, et al. Metabolically healthy obese individuals present similar chronic inflammation level but less insulin-resistance than obese individuals with metabolic syndrome. PLoS ONE. 2017;12:e0190528.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Ramachandran A, Snehalatha C, Yamuna A, Murugesan N, Narayan KM. Insulin resistance and clustering of cardiometabolic risk factors in urban teenagers in southern India. Diabetes Care. 2007;30:1828–33.

    Article  CAS  PubMed  Google Scholar 

  13. Di Pino A, DeFronzo RA. Insulin resistance and atherosclerosis: implications for insulin-sensitizing agents. Endocr Rev. 2019;40:1447–67.

    Article  PubMed  PubMed Central  Google Scholar 

  14. DeBoer MD. Assessing and managing the metabolic syndrome in children and adolescents. Nutrients. 2019;11:1788.

    Article  CAS  PubMed Central  Google Scholar 

  15. Malik VS, Hu FB. Sugar-sweetened beverages and cardiometabolic health: an update of the evidence. Nutrients. 2019;11:1840.

    Article  CAS  PubMed Central  Google Scholar 

  16. Taskinen MR, Packard CJ, Boren J. Dietary fructose and the metabolic syndrome. Nutrients. 2019;11:1987.

    Article  CAS  PubMed Central  Google Scholar 

  17. Merino B, Fernandez-Diaz CM, Cozar-Castellano I, Perdomo G. Intestinal fructose and glucose metabolism in health and disease. Nutrients. 2019;12:94.

    Article  PubMed Central  Google Scholar 

  18. Lin WT, Chan TF, Huang HL, Lee CY, Tsai S, Wu PW, et al. Fructose-rich beverage intake and central adiposity, uric acid, and pediatric insulin resistance. J Pediatr. 2016;171:90–6 e1.

    Article  CAS  PubMed  Google Scholar 

  19. Mirmiran P, Yuzbashian E, Asghari G, Hosseinpour-Niazi S, Azizi F. Consumption of sugar sweetened beverage is associated with incidence of metabolic syndrome in Tehranian children and adolescents. Nutr Metab. 2015;12:25.

    Article  Google Scholar 

  20. Current economic situation. Department of Statistics. Ministry of Economic Affairs, R.O.C (Taiwan). Available online: https://www.moea.gov.tw/MNS/dos/bulletin/Bulletin.aspx?kind=23&html=1&menu_id=10212&bull_id=6124; https://www.moea.gov.tw/MNS/populace/news/News.aspx?kind=1&menu_id=40&news_id=85094. 2019.

  21. 2018 Annual Report of Health Promotion Administration. Ministry of Health and Welfare. R.O.C. (Taiwan). Available online: https://www.hpa.gov.tw/Pages/Detail.aspx?nodeid=3801&pid=10231. (2018) Accessed 30 July 2020.

  22. Lin WT, Huang HL, Huang MC, Chan TF, Ciou SY, Lee CY, et al. Effects on uric acid, body mass index and blood pressure in adolescents of consuming beverages sweetened with high-fructose corn syrup. Int J Obes. 2013;37:532–9.

    Article  CAS  Google Scholar 

  23. Chan TF, Lin WT, Huang HL, Lee CY, Wu PW, Chiu YW, et al. Consumption of sugar-sweetened beverages is associated with components of the metabolic syndrome in adolescents. Nutrients. 2014;6:2088–103.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Huang MC, Lin KD, Chen HJ, Wu YJ, Chang CI, Shin SJ, et al. Validity of a short food frequency questionnaire assessing macronutrient and fiber intakes in patients of Han Chinese descent with type 2 diabetes. Int J Environ Res Public Health. 2018;15:1142.

    Article  PubMed Central  Google Scholar 

  25. Food and Drug Administration DoH EY, Republic of China. Taiwanese food and nutrients databank http://www.doh.gov.tw/FoodAnalysis/. 1993.

  26. National Health Research Institutes. Nutrition and Health Survey in Taiwan, 2010–2011. https://www.hpa.gov.tw/EngPages/Detail.aspx?nodeid=1077&pid=6201. Accessed 1 July 1 2020.

  27. Ridley K, Ainsworth BE, Olds TS. Development of a compendium of energy expenditures for youth. Int J Behav Nutr Phys Act. 2008;5:45.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Guerrero-Romero F, Rodriguez-Moran M. Abdominal volume index. An anthropometry-based index for estimation of obesity is strongly related to impaired glucose tolerance and type 2 diabetes mellitus. Arch Med Res. 2003;34:428–32.

    Article  PubMed  Google Scholar 

  29. Perloff D, Grim C, Flack J, Frohlich ED, Hill M, McDonald M, et al. Human blood pressure determination by sphygmomanometry. Circulation. 1993;88:2460–70.

    Article  CAS  PubMed  Google Scholar 

  30. Allain CC, Poon LS, Chan CS, Richmond W, Fu PC. Enzymatic determination of total serum cholesterol. Clin Chem. 1974;20:470–5.

    Article  CAS  PubMed  Google Scholar 

  31. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–9.

    Article  CAS  PubMed  Google Scholar 

  32. Levy JC, Matthews DR, Hermans MP. Correct homeostasis model assessment (HOMA) evaluation uses the computer program. Diabetes Care. 1998;21:2191–2.

    Article  CAS  PubMed  Google Scholar 

  33. HOMA Calculator. Tools from the Diabetes Trials Unit (DTU). http://www.dtu.ox.ac.uk/ToolsSoftware/ Accessed 12 June 2014.

  34. 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.

    Article  PubMed  Google Scholar 

  35. Hsu FC, Kritchevsky SB, Liu Y, Kanaya A, Newman AB, Perry SE, et al. Association between inflammatory components and physical function in the health, aging, and body composition study: a principal component analysis approach. J Gerontol A Biol Sci Med Sci. 2009;64:581–9.

    Article  PubMed  Google Scholar 

  36. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51:1173–82.

    Article  CAS  PubMed  Google Scholar 

  37. MacKinnon DP, Fairchild AJ, Fritz MS. Mediation analysis. Annu Rev Psychol. 2007;58:593–614.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Jung SY, Rosenzweig M, Linkov F, Brufsky A, Weissfeld JL, Sereika SM. Comorbidity as a mediator of survival disparity between younger and older women diagnosed with metastatic breast cancer. Hypertension. 2012;59:205–11.

    Article  CAS  PubMed  Google Scholar 

  39. Lee CY, Lin WT, Tsai S, Hung YC, Wu PW, Yang YC, et al. Association of parental overweight and cardiometabolic diseases and pediatric adiposity and lifestyle factors with cardiovascular risk factor clustering in adolescents. Nutrients. 2016;8:567.

    Article  PubMed Central  Google Scholar 

  40. Mickey RM, Greenland S. The impact of confounder selection criteria on effect estimation. Am J Epidemiol. 1989;129:125–37.

    Article  CAS  PubMed  Google Scholar 

  41. Softic S, Stanhope KL, Boucher J, Divanovic S, Lanaspa MA, Johnson RJ, et al. Fructose and hepatic insulin resistance. Crit Rev Clin Lab Sci. 2020:1–15.

  42. Nair J, Velpandian T, Das US, Sharma P, Nag T, Mathur SR, et al. Molecular and metabolic markers of fructose induced hepatic insulin resistance in developing and adult rats are distinct and aegle marmelos is an effective modulator. Sci Rep. 2018;8:15950.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Bremer AA, Auinger P, Byrd RS. Relationship between insulin resistance-associated metabolic parameters and anthropometric measurements with sugar-sweetened beverage intake and physical activity levels in US adolescents: findings from the 1999–2004 National Health and Nutrition Examination Survey. Arch Pediatr Adolesc Med. 2009;163:328–35.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Kondaki K, Grammatikaki E, Jimenez-Pavon D, De Henauw S, Gonzalez-Gross M, Sjostrom M, et al. Daily sugar-sweetened beverage consumption and insulin resistance in European adolescents: the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) Study. Public Health Nutr. 2013;16:479–86.

    Article  PubMed  Google Scholar 

  45. Sakou II, Psaltopoulou T, Sergentanis TN, Karavanaki K, Karachaliou F, Ntanasis-Stathopoulos I, et al. Insulin resistance and cardiometabolic risk factors in obese children and adolescents: a hierarchical approach. J Pediatr Endocrinol Metab. 2015;28:589–96.

    Article  CAS  PubMed  Google Scholar 

  46. Samson SL, Garber AJ. Metabolic syndrome. Endocrinol Metab Clin North Am. 2014;43:1–23.

    Article  PubMed  Google Scholar 

  47. Schwarz JM, Noworolski SM, Erkin-Cakmak A, Korn NJ, Wen MJ, Tai VW, et al. Effects of dietary fructose restriction on liver fat, de novo lipogenesis, and insulin kinetics in children with obesity. Gastroenterology. 2017;153:743–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Erkin-Cakmak A, Bains Y, Caccavello R, Noworolski SM, Schwarz JM, Mulligan K, et al. Isocaloric fructose restriction reduces serum d-lactate concentration in children with obesity and metabolic syndrome. J Clin Endocrinol Metab. 2019;104:3003–11.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Gugliucci A, Lustig RH, Caccavello R, Erkin-Cakmak A, Noworolski SM, Tai VW, et al. Short-term isocaloric fructose restriction lowers apoC-III levels and yields less atherogenic lipoprotein profiles in children with obesity and metabolic syndrome. Atherosclerosis. 2016;253:171–7.

    Article  CAS  PubMed  Google Scholar 

  50. van der Heijden GJ, Toffolo G, Manesso E, Sauer PJ, Sunehag AL. Aerobic exercise increases peripheral and hepatic insulin sensitivity in sedentary adolescents. J Clin Endocrinol Metab. 2009;94:4292–9.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Schlesinger S, Neuenschwander M, Schwedhelm C, Hoffmann G, Bechthold A, Boeing H, et al. Food groups and risk of overweight, obesity, and weight gain: a systematic review and dose-response meta-analysis of prospective studies. Adv Nutr. 2019;10:205–18.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Malik VS, Hu FB. Fructose and cardiometabolic health: what the evidence from sugar-sweetened beverages tells us. J Am Coll Cardiol. 2015;66:1615–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Magge SN, Goodman E, Armstrong SC, Committee On N, Section On E, Section On O. The metabolic syndrome in children and adolescents: shifting the focus to cardiometabolic risk factor clustering. Pediatrics. 2017;140:e20171603.

    Article  PubMed  Google Scholar 

  54. Basu S, McKee M, Galea G, Stuckler D. Relationship of soft drink consumption to global overweight, obesity, and diabetes: a cross-national analysis of 75 countries. Am J Public Health. 2013;103:2071–7.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This research work was supported by the Taiwan Ministry of Science and Technology (MOST 103-2314-B-037-019-MY3, MOST 106-2314-B-037-021-MY3, and MOST 109-2314-B-037-070-MY3). We would like to express our appreciation to the nurses in each school health center and class teachers, who acted as the coordinator for data collection and anthropometric measurements.

Author information

Authors and Affiliations

  1. Department of Public Health, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan

    Pei-Wen Wu, Wei-Ting Lin, Yu-Ting Chin & Chien-Hung Lee

  2. Department of Laboratory Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung, Taiwan

    Sharon Tsai

  3. School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan

    Chun-Ying Lee

  4. Department of Family Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan

    Chun-Ying Lee

  5. Department of Global Community Health and Behavioral Sciences, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA

    Wei-Ting Lin, David W. Seal & Ted Chen

  6. Department of Oral Hygiene, College of Dental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan

    Hsiao-Ling Huang

  7. Research Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan

    Chien-Hung Lee

  8. Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan

    Chien-Hung Lee

Authors
  1. Pei-Wen Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sharon Tsai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chun-Ying Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wei-Ting Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yu-Ting Chin
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hsiao-Ling Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. David W. Seal
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ted Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Chien-Hung Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chien-Hung Lee.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, PW., Tsai, S., Lee, CY. et al. Contribution of insulin resistance to the relationship between sugar-sweetened beverage intake and a constellation of cardiometabolic abnormalities in adolescents. Int J Obes 45, 828–839 (2021). https://doi.org/10.1038/s41366-021-00745-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41366-021-00745-1

This article is cited by

Search

Advanced search

Quick links