Skip to main content

Advertisement

Log in

A web-based interactive lifestyle modification program improves lipid profile and serum adiponectin concentrations in patients with metabolic syndrome: the “Red Ruby” study

  • Original Article
  • Published:
International Journal of Diabetes in Developing Countries Aims and scope Submit manuscript

Abstract

The effectiveness of internet-based programs in prevention and treatment of metabolic syndrome has not been fully explored. In the present study, we investigate the effect of a 6-month web-based interactive lifestyle modification program on anthropometric variables and biochemical risk factors of cardiovascular disease. The study had been carried out among 160 patients with metabolic syndrome (intervention, n = 80; control, n = 80). The primary outcomes were change in anthropometric variables, fasting serum glucose (FSG), lipid profile, insulin sensitivity, and serum adiponectin concentrations in intervention and control groups. Significant reductions in anthropometric variables and serum lipids were observed in both intervention and control groups; however, reduction in waist-to-hip ratio (WHR), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) was only significant in intervention group (P < 0.05). Reduction in anthropometric variables and serum triglyceride, systolic and diastolic blood pressure, and liver enzymes were significant in intervention and control groups (P < 0.05) but in women decrease in FSG, TC, and LDL-C were only significant in intervention group (P < 0.05). The present study showed that a web-based intervention was effective in weight loss and improving cardio-metabolic factors in patients with metabolic syndrome after a 6-month intervention.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Aggarwal A, Aggarwal S, Sharma V. Cardiovascular risk factors in young patients of coronary artery disease: differences over a decade. J Cardiovasc Thorac Res. 2014;6(3):169–73.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Saghafi-Asl M, Pirouzpanah S, Ebrahimi-Mameghani M, Asghari-Jafarabadi M, Aliashrafi S, Sadein B. Lipid profile in relation to anthropometric indices and insulin resistance in overweight women with polycystic ovary syndrome. HPP. 2013;3(2):206–16.

    PubMed  PubMed Central  Google Scholar 

  3. Malik S, Wong ND, Franklin SF, Kamath TV, L’Italien GJ, Pio JR, et al. Cardiovascular disease and all causes in United States adults impact of the metabolic syndrome on mortality from coronary heart disease. Circulation. 2004;110:1245–50.

    Article  PubMed  Google Scholar 

  4. Lakka HM, Laaksonen DE, Lakka TA, Niskanen LK, Kumpusalo E, Tuomilehto J, et al. The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA. 2002;288(21):2709–16.

    Article  PubMed  Google Scholar 

  5. Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, et al. The metabolic syndrome and cardiovascular risk. A systematic review and meta-analysis. J Am Coll Cardiol. 2010;56(14):1113–32.

    Article  PubMed  Google Scholar 

  6. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults. JAMA. 2002;287(3):356–9.

    Article  PubMed  Google Scholar 

  7. Azizi F, Salehi P, Etemadi A, Zahedi-Asl S. Prevalence of metabolic syndrome in an urban population: Tehran Lipid and Glucose Study. Diab Res Clin Pract. 2003;61(1):29–37.

    Article  Google Scholar 

  8. Aggarwal A, Aggarwal S, Sarkar PG, Sharma V. Predisposing factors to premature coronary artery disease in young (age ≤ 45 years) smokers: a single center retrospective case control study from India. J Cardiovasc Thorac Res. 2014;6(1):15–9.

    PubMed  PubMed Central  Google Scholar 

  9. Esposito K, Marfella R, Ciotola M, Di Palo C, Giugliano F, Giugliano G, et al. Effect of a Mediterranean-style diet on endothelial dysfunction and markers of vascular inflammation in the metabolic syndrome. JAMA. 2004;292(12):1440–6.

    Article  CAS  PubMed  Google Scholar 

  10. Azadbakht L, Mirmiran P, Esmaillzadeh A, Azizi T, Azizi F. Beneficial effects of a dietary approaches to stop hypertension eating plan (DASH) on features of the metabolic syndrome. Diab Care. 2005;28(12):2823–31.

    Article  CAS  Google Scholar 

  11. Barry VB, Raiff BR. Weight management preferences in a non-treatment seeking sample. HPP. 2013;3(2):147–53.

    PubMed  PubMed Central  Google Scholar 

  12. Bond GE, Burr R, Wolf FM, Price M, Mccurry SM, Teri L. The effects of a web-based intervention on the physical outcomes associated with diabetes among adults age 60 and older: a randomized trial. Diab Technol Ther. 2007;9(1):52–9.

    Article  Google Scholar 

  13. Ramadas A, Quek KF, Chan CK, Oldenburg B. Web-based interventions for the management of type 2 diabetes mellitus: a systematic review of recent evidence. Int J Med Inform. 2011;80(6):389–405.

    Article  CAS  PubMed  Google Scholar 

  14. Wantland DJ, Portillo CJ, Holzemer WL, Slaughter R, Mcghee EM. The effectiveness of web-based vs. non-web-based interventions: a meta-analysis of behavioral change outcomes. J Med Internet Res. 2004;6(4):e 40.

    Article  Google Scholar 

  15. Tate DF, Jackvony EH, Wing RR. Effects of Internet behavioral counseling on weight loss in adults at risk for type 2 diabetes. JAMA. 2003;289(14):1833–6.

    Article  PubMed  Google Scholar 

  16. McKay HG, King D, Eakin EG, Seeley JR, Glasgow RE. The diabetes network Internet-based physical activity intervention: a randomized pilot study. Diab Care. 2001;24(8):1328–34.

    Article  CAS  Google Scholar 

  17. Christensen H, Griffiths KM, Jorm AF. Delivering interventions for depression by using the Internet: randomized controlled trial. BMJ. 2004;328:265–8.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Van-Straten A, Cuijpers P, Smits N. Effectiveness of a web-based self-help intervention for symptoms of depression, anxiety, and stress: randomized controlled trial. J Med Internet Res. 2008;10(1):e7.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Ybarra ML, Bull SS. Current trends in Internet-and cell phone-based HIV prevention and intervention programs. Curr HIV/AIDS Rep. 2007;4(4):201–7.

    Article  PubMed  Google Scholar 

  20. Jahangiry L, Shojaeizadeh D, Najafi M, Mohammad K, Abbasalizad Farhangi M, Montazeri A. ”Red Ruby”: an interactive web-based intervention for lifestyle modification on metabolic syndrome: a study protocol for a randomized controlled trial. BMC Public Health. 2014;14:748–56.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Grundy SM, Hansen B, Smith SC, Cleeman J, Richard A. Clinical management of metabolic syndrome: report of the American Heart Association/National Heart, Lung, and Blood Institute/American Diabetes Association conference on scientific issues related to management. Circulation. 2004;109:551–6.

    Article  PubMed  Google Scholar 

  22. Delavari A, Forouzanfar MH, Alikhani S, Kelishadi R. First nationwide study of the prevalence of the metabolic syndrome and optimal cut-off points of waist circumference in the Middle East: the national survey of risk factors for non-communicable disease of Iran. Diab Care. 2009;32:1092–7.

    Article  Google Scholar 

  23. Esteghamati A, Abbasi M, Rashidi A, Meysamie A, Khalilzadeh O, Haghazali M, et al. Optimal waist circumference cut-offs for the diagnosis of metabolic syndrome in adults: results from the third national survey of risk factors of non-communicable disease (SuRFNCD). Diab Med. 2009;26:745–6.

    Article  CAS  Google Scholar 

  24. Heart N. Lung, and blood institute, obesity education initiative expert panel. Clinical guidelines in identification, evaluation, and treatment of overweight and obesity in adults: the evidence report. Obes Res. 1998;6(suppl):S51–S210.

    Google Scholar 

  25. Hamwi GL. Changing dietary concepts in diabetes mellitus: diagnosis and treatment. New York: American Diabetes Association; 1964.

    Google Scholar 

  26. Alberti KG, Zimmet P, Shaw J. The metabolic syndrome: a new worldwide definition. Diabet Med. 2006;23:469–80.

    Article  CAS  PubMed  Google Scholar 

  27. Farhangi MA, Keshavarz SA, Eshraghian M, Ostadrahimi A, Saboor-Yaraghi AA. White blood cell count in women: relation to inflammatory biomarkers, haematological profiles, visceral adiposity, and other cardiovascular risk factors. J Health Popul Nutr. 2013;31:58–64.

    Article  PubMed  PubMed Central  Google Scholar 

  28. 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;28:412–19.

    Article  CAS  PubMed  Google Scholar 

  29. Viner RM, Segal TY, Lichtarowicz-Krynska E, Hindmarsh P. Prevalence of the insulin resistance syndrome in obesity. Arch Dis Child. 2005;90:10–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Oh EG, Bang SY, Kim SH, Chu SH, Jeon JY, Im JA, et al. Effects of a 6-month lifestyle modification intervention on the cardiometabolic risk factors and health-related qualities of life in women with metabolic syndrome. Metab Clin Exp. 2010;59(7):1035–43.

    Article  CAS  PubMed  Google Scholar 

  31. Matsuo T, Kim MK, Murotake Y, Numao S, Kim MJ, Ohkubo H, et al. Indirect lifestyle intervention through wives improves metabolic syndrome components in men. Int J Obes. 2009;34(1):136–45.

    Article  Google Scholar 

  32. Mcmahon GT, Gomes HE, Hickson HS, Hu TM, Levine BA, Conlin PR. Web-based care management in patients with poorly controlled diabetes. Diab Care. 2005;28:1624–9.

    Article  Google Scholar 

  33. Izquierdo RE, Knudson PE, Meyer S, Kearns J, Ploutzsnyder R, Weinstock RS. A comparison of diabetes education administered through telemedicine versus in person. Diab Care. 2003;26:1002–7.

    Article  Google Scholar 

  34. Moore TJ, Alsabeeh N, Apovian CM, Murphy MC, Coffman GA, Cullum-Dugan D. Weight, blood pressure, and dietary benefits after 12 months of a Web-based Nutrition Education Program (DASH for health): longitudinal observational study. J Med Internet Res. 2008;10(4):e 52.

    Article  Google Scholar 

  35. Oenema A, Brug J, Lechner L. Web-based tailored nutrition education: results of a randomized controlled trial. Health Educ Res. 2001;16(6):647–60.

    Article  CAS  PubMed  Google Scholar 

  36. Gold BC, Burke S, Pintauro S, Buzzell P, Harveya- Berino J. Weight loss on the web: a pilot study comparing a structured behavioral intervention to a commercial program. Obesity. 2007;15(1):155–64.

    Article  PubMed  Google Scholar 

  37. Jackson LA, Ervin KS, Gardner PD, Schmitt N. Gender and the Internet: women communicating and men searching. Sex Roles. 2001;44(5/6):363–79.

    Article  Google Scholar 

  38. Mirinazhad MM, Farhangi MA, Jahangiri L, Yaghoubi A. Serum adiponectin concentrations in relation to lipid profile, anthropometric variables and insulin resistance in patients with metabolic syndrome. Mal J Nutr. 2014;20(3):283–9.

    Google Scholar 

  39. Feizollahzadeh S, Rasuli J, Kheirouri S, Alizadeh M. Augmented plasma adiponectin after prolonged fasting during Ramadan in men. HPP. 2014;4(1):77–81.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

This work was supported by Cardiovascular Research Center–Tabriz University of Medical Sciences (5/92/1228) and by the research undersecretary of Tehran University of Medical Sciences (97/130/1736) and has been registered in IRCT (Identifier: IRCT201111198132N1).

Conflict of interest

The authors declare that they have no competing interests.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Leila Jahangiry.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Farhangi, M.A., Jahangiry, L., Mirinazhad, MM. et al. A web-based interactive lifestyle modification program improves lipid profile and serum adiponectin concentrations in patients with metabolic syndrome: the “Red Ruby” study. Int J Diabetes Dev Ctries 37, 21–30 (2017). https://doi.org/10.1007/s13410-015-0395-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13410-015-0395-z

Keywords

Navigation