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.

  • Original Article
  • Published:

Predictors of new-onset diabetes mellitus in hypertensive patients: the VALUE trial

Journal of Human Hypertension volume 22, pages 520–527 (2008)Cite this article

Abstract

Diabetes mellitus often develops in patients with hypertension. We investigated predictors of diabetes mellitus development in hypertensives at risk of developing the disease in the VALUE trial population. Among the 9995 non-diabetic hypertensive patients at baseline, 1298 patients developed diabetes mellitus during the average follow-up of 4.2 years. New-onset diabetes mellitus was defined from adverse event reports, information about new antidiabetic medication and/or a fasting glucose ⩾7.0 mmol l−1 at the end of trial. Twenty-five potential baseline predictors of new-onset diabetes mellitus were analysed by univariate logistic regression and 14 of 25 predictors were found to be statistically significant with a P-value <0.05. The predictors were in order of decreasing significance; glucose, body mass index (BMI), age, uric acid, non-Caucasian race, haemoglobin, heart rate, randomized study treatment, history of coronary heart disease (CHD), gender, total cholesterol, proteinuria, potassium and creatinine. Multivariate stepwise logistic regression analyses were used and potential baseline predictors of new-onset diabetes mellitus were considered significant by four different models (P-value <0.001). The final multivariate model selected included all patients, but not treatment group as a potential predictor, and the six significant predictors identified from this model were glucose, BMI, non-Caucasian race, age, heart rate and history of CHD. In conclusion, glucose and BMI were the most important predictors of new-onset diabetes mellitus in hypertensive patients at high cardiovascular risk, and easily accessible clinical characteristics strongly predict patients at risk of developing diabetes mellitus.

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

Similar content being viewed by others

References

  1. Howard BV, Rodriguez BL, Bennett PH, Harris MI, Hamman R, Kuller LH et al. Prevention Conference VI: Diabetes and Cardiovascular disease: Writing Group I: epidemiology. Circulation 2002; 105: e132–e137.

    Article  Google Scholar 

  2. Lindholm LH, Ibsen H, Borch-Johnsen K, Olsen MH, Wachtell K, Dahlöf B et al. Risk of new-onset diabetes in the Losartan Intervention For Endpoint reduction in hypertension study. J Hypertens 2002; 20: 1879–1886.

    Article  CAS  Google Scholar 

  3. Niklason A, Hedner T, Niskanen L, Lanke J . Development of diabetes is retarded by ACE inhibition in hypertensive patients—a subanalysis of the Captopril Prevention Project (CAPPP). J Hypertens 2004; 22: 645–652.

    Article  CAS  Google Scholar 

  4. Mann J, Julius S . The Valsartan Antihypertensive Long-term Use Evaluation (VALUE) trial of cardiovascular events in hypertension. Rationale and design. Blood Press 1998; 7: 176–183.

    Article  CAS  Google Scholar 

  5. Kjeldsen SE, Julius S, Brunner H, Hansson L, Henis M, Ekman S et al. Characteristics of 15,314 hypertensive patients at high coronary risk. The VALUE trial. The Valsartan Antihypertensive Long-term Use Evaluation. Blood Press 2001; 10: 83–91.

    Article  CAS  Google Scholar 

  6. Julius S, Kjeldsen SE, Weber M, Brunner HR, Ekman S, Hansson L et al. Outcomes in hypertensive patients at high cardiovascular risk treated with regimens based on valsartan or amlodipine: the VALUE randomised trial. Lancet 2004; 363: 2022–2031.

    Article  CAS  Google Scholar 

  7. WHO. Diabetes mellitus. Report of a WHO Study Group. World Health Organ Tech Rep Ser 1985; 727: 1–113.

    Google Scholar 

  8. Alberti KG, Zimmet PZ . Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998; 15: 539–553.

    Article  CAS  Google Scholar 

  9. Weber MA, Julius S, Kjeldsen SE, Brunner HR, Ekman S, Hansson L et al. Blood pressure dependent and independent effects of antihypertensive treatment on clinical events in the VALUE Trial. Lancet 2004; 363: 2049–2051.

    Article  CAS  Google Scholar 

  10. Genuth S . Lowering the criterion for impaired fasting glucose is in order. Diabetes Care 2003; 26: 3331–3332.

    Article  Google Scholar 

  11. Stern MP, Williams K, Haffner SM . Identification of persons at high risk for type 2 diabetes mellitus: do we need the oral glucose tolerance test? Ann Intern Med 2002; 136: 575–581.

    Article  Google Scholar 

  12. Tirosh A, Shai I, Tekes-Manova D, Israeli E, Pereg D, Shochat T et al. Normal fasting plasma glucose levels and type 2 diabetes in young men. N Engl J Med 2005; 353: 1454–1462.

    Article  CAS  Google Scholar 

  13. Boden G . Role of fatty acids in the pathogenesis of insulin resistance and NIDDM. Diabetes 1997; 46: 3–10.

    Article  CAS  Google Scholar 

  14. Lam TK, Pocai A, Gutierrez-Juarez R, Obici S, Bryan J, Aguilar-Bryan L et al. Hypothalamic sensing of circulating fatty acids is required for glucose homeostasis. Nat Med 2005; 11: 320–327.

    Article  CAS  Google Scholar 

  15. Wei M, Gaskill SP, Haffner SM, Stern MP . Waist circumference as the best predictor of noninsulin dependent diabetes mellitus (NIDDM) compared to body mass index, waist/hip ratio and other anthropometric measurements in Mexican Americans—a 7-year prospective study. Obes Res 1997; 5: 16–23.

    Article  CAS  Google Scholar 

  16. Stevens J, Couper D, Pankow J, Folsom AR, Duncan BB, Nieto FJ et al. Sensitivity and specificity of anthropometrics for the prediction of diabetes in a biracial cohort. Obes Res 2001; 9: 696–705.

    Article  CAS  Google Scholar 

  17. Olsen MH, Fossum E, Hjerkinn E, Wachtell K, Höieggen A, Nesbitt SD et al. Relative influence of insulin resistance versus blood pressure on vascular changes in longstanding hypertension. ICARUS, a LIFE sub-study. Insulin Carotids US Scandinavia. J Hypertens 2000; 18: 75–81.

    Article  CAS  Google Scholar 

  18. Lipton RB, Liao Y, Cao G, Cooper RS, McGee D . Determinants of incident non-insulin-dependent diabetes mellitus among blacks and whites in a national sample. The NHANES I Epidemiologic Follow-up Study. Am J Epidemiol 1993; 138: 826–839.

    Article  CAS  Google Scholar 

  19. Resnick HE, Valsania P, Halter JB, Lin X . Differential effects of BMI on diabetes risk among black and white Americans. Diabetes Care 1998; 21: 1828–1835.

    Article  CAS  Google Scholar 

  20. Conn JW . Hypertension, the potassium ion and impaired carbohydrate tolerance. N Engl J Med 1965; 273: 1135–1143.

    Article  CAS  Google Scholar 

  21. Julius S, Gudbrandsson T, Jamerson K, Tariq SS, Andersson O . The hemodynamic link between insulin resistance and hypertension. J Hypertens 1991; 9: 983–986.

    Article  CAS  Google Scholar 

  22. Ligtenberg G, Blankestijn PJ, Oey PL, Klein IH, Jkhorst-Oei LT, Boomsma F et al. Reduction of sympathetic hyperactivity by enalapril in patients with chronic renal failure. N Engl J Med 1999; 340: 1321–1328.

    Article  CAS  Google Scholar 

  23. Kjeldsen SE, Julius S, Mancia G, McInnes GT, Hua T, Weber MA et al. Effects of valsartan compared to amlodipine on preventing type 2 diabetes in high-risk hypertensive patients: the VALUE trial. J Hypertens 2006; 24: 1405–1412.

    Article  CAS  Google Scholar 

  24. Dahlöf B, Devereux RB, Kjeldsen SE, Julius S, Beevers G, de Faire U et al. Cardiovascular morbidity and mortality in the Losartan Intervention For Endpoint reduction in hypertension study (LIFE): a randomised trial against atenolol. Lancet 2002; 359: 995–1003.

    Article  Google Scholar 

  25. Hansson L, Lindholm LH, Niskanen L, Lanke J, Hedner T, Niklason A et al. Effect of angiotensin-converting-enzyme inhibition compared with conventional therapy on cardiovascular morbidity and mortality in hypertension: the Captopril Prevention Project (CAPPP) randomised trial. Lancet 1999; 353: 611–616.

    Article  CAS  Google Scholar 

  26. Freeman DJ, Norrie J, Caslake MJ, Gaw A, Ford I, Lowe GD et al. C-reactive protein is an independent predictor of risk for the development of diabetes in the West of Scotland Coronary Prevention Study. Diabetes 2002; 51: 1596–1600.

    Article  CAS  Google Scholar 

  27. Sattar N, Gaw A, Scherbakova O, Ford I, O’Reilly DS, Haffner SM et al. Metabolic syndrome with and without C-reactive protein as a predictor of coronary heart disease and diabetes in the West of Scotland Coronary Prevention Study. Circulation 2003; 108: 414–419.

    Article  CAS  Google Scholar 

  28. Sattar N, Scherbakova O, Ford I, O’Reilly DS, Stanley A, Forrest E et al. Elevated alanine aminotransferase predicts new-onset type 2 diabetes independently of classical risk factors, metabolic syndrome, and C-reactive protein in the west of Scotland coronary prevention study. Diabetes 2004; 53: 2855–2860.

    Article  CAS  Google Scholar 

  29. American Diabetes Association. Diabetes Risk Test. 2007 Internet Communication (http://www.diabetes.org/risk-test.jsp).

  30. Finnish Diabetes Association. FINDRISC. 2007 Internet Communication (http://www.diabetes.fi/English).

  31. Lawrence JM, Bennett P, Young A, Robinson AM . Screening for diabetes in general practice: cross sectional population study. BMJ 2001; 323: 548–551.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The VALUE trial was supported by Novartis Pharma AG, and we thank Sajda Ghani and Bjoern Holzhauer of Novartis Pharma for statistical help. The trial was designed interactively between an advisory board (later VALUE Executive Committee) and the sponsor Novartis Pharma AG. The sponsor managed operational execution, storage of data and performed the analyses. The Executive Committee has full access to the data, is responsible for the data analysis, and has full control over the right to publish.

Author information

Authors and Affiliations

  1. Department of Cardiology, Ullevaal University Hospital, Oslo, Norway

    T A Aksnes & S E Kjeldsen

  2. Department of Acute Medicine, Ullevaal University Hospital, Oslo, Norway

    M Rostrup

  3. Department of Internal Medicine, Akershus University Hospital, Lörenskog, Norway

    Ö Störset

  4. Novartis Pharma, , East Hanover, NJ, USA

    T A Hua

  5. Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA

    S Julius

Authors
  1. T A Aksnes
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S E Kjeldsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M Rostrup
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ö Störset
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. T A Hua
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. S Julius
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to T A Aksnes.

Additional information

Conflict of interest

S Julius and SE Kjeldsen have served as consultants or received grants from Novartis and other major pharmaceutical companies. TA Hua is a Novartis employee.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Aksnes, T., Kjeldsen, S., Rostrup, M. et al. Predictors of new-onset diabetes mellitus in hypertensive patients: the VALUE trial. J Hum Hypertens 22, 520–527 (2008). https://doi.org/10.1038/jhh.2008.41

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/jhh.2008.41

Keywords

This article is cited by

Search

Advanced search

Quick links