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:

Prediabetes is associated with abnormal circadian blood pressure variability

Journal of Human Hypertension volume 22, pages 627–633 (2008)Cite this article

Abstract

Blood pressure (BP) exhibits a circadian variation characterized by a morning increase, followed by a small postprandial valley and a deeper descent during nocturnal rest. Although abnormal 24-h variability (abnormal circadian variability (ACV)) predicts adverse cardiovascular disease (CVD) outcomes, a 7-day automatic ambulatory BP monitoring (ABPM) and subsequent chronobiologic analysis of the gathered data, permits identification of consistency of any abnormal circadian variation. To test whether normal overweight healthy men and women with prediabetes differed from subjects with normoglycemia in having ACV with a 7-day ABPM. Consent for a 7-day ABPM was obtained from subjects with family history of diabetes mellitus, who were participating in the screening phase for a randomized, double blind, placebo-controlled weight loss trial in prediabetics to prevent progression to diabetes mellitus. The automatic 7-day ABPM device recorded BP and heart rate every 30 min during the day and every 60 min during the night. Normoglycemic and prediabetic subjects matched for age, sex, race, BP, BMI, waist circumference and glycemic control, differed statistically significantly only in their fasting and/or 2-h postprandial serum glucose concentrations. Chronobiologically-interpreted 7-day ABPM uncovered no abnormalities in normoglycemics, whereas prediabetics had a statistically significantly higher incidence of high mean BP (MESOR-hypertension), excessive pulse pressure and/or circadian hyper-amplitude-tension (CHAT) (P<0.001). ACV detected with 7-day ABPM may account for the enhanced CVD risk in prediabetes. These findings provide a basis for larger-scale studies to assess the predictive value of 7-day ABPM over the long term.

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

Figure 1
Figure 2
Figure 3
Figure 4

Similar content being viewed by others

References

  1. Halberg F, Conner RL . Circadian organization and microbiology: variance spectra and a periodogram on behavior of Escherichia coli growing in fluid culture. Proc Minn Acad Sci 1961; 29: 227–239.

    Google Scholar 

  2. Halberg F, Cornélissen G, Katinas G, Tvildiani L, Gigolashvili M, Janashia K et al. International BIOCOS Group. Chronobiology's progress: season's appreciations 2004-2005. Time, frequency, phase, variable, individual, age- and site-specific chronomics. J Appl Biomed 2006; 4: 1–38.

    Article  Google Scholar 

  3. Halberg F, Cornélissen G, Katinas G, Tvildiani L, Gigolashvili M, Janashia K et al. International BIOCOS Group. Chronobiology's progress: part II, chronomics for an immediately applicable biomedicine. J Appl Biomed 2006; 4: 73–86.

    Article  Google Scholar 

  4. Yamamoto T, Nakahata Y, Soma H, Akashi M, Mamine T, Takumi T . Transcriptional oscillation of canonical clock genes in mouse peripheral tissues. BMC Mol Biol 2004; 5: 18. doi:10.1186/1471-2199-5-18.

    Article  PubMed  Google Scholar 

  5. Haus E . Chronobiology in the endocrine system. Adv Drug Deliv Rev 2007; 59: 985–1014.

    Article  CAS  Google Scholar 

  6. O'Brien E . Ambulatory blood pressure measurement: a trove of hidden gems? Hypertension 2006; 48: 364–365.

    Article  CAS  Google Scholar 

  7. Staessen JA, Thijs L, Fagard R, O′Brien ET, Clement D, de Leeuw PW et al. Predicting cardiovascular risk using conventional vs ambulatory blood pressure in older patients with systolic hypertension. Systolic Hypertension in Europe Trial Investigators. JAMA 1999; 282: 539–546.

    Article  CAS  Google Scholar 

  8. White WB . How well does ambulatory blood pressure predict target-organ disease and clinical outcome in patients with hypertension? Blood Press Monit 1999; 4 (Suppl 2): S17–S21 (review).

    Google Scholar 

  9. Juutilainen A, Lehto S, Ronnemaa T, Pyorala K, Laakso M . Type 2 diabetes as a ‘coronary heart disease equivalent’: an 18-year prospective population-based study in Finnish subjects. Diabetes Care 2005; 28: 2901–2907.

    Article  Google Scholar 

  10. Whiteley L, Padmanabhan S, Hole D, Isles C . Should diabetes be considered a coronary heart disease risk equivalent?: results from 25 years of follow-up in the Renfrew and Paisley survey. Diabetes Care 2005; 28: 1588–1593.

    Article  Google Scholar 

  11. The Diabetes Control and Complications Trial Research Group. The effect of intensive treatment of diabetes on the development and progression of long term complications in the diabetes control in insulin dependent diabetes mellitus. N Engl J Med 329: 977–986.

  12. Nielson C, Lange T, Hadjokas N . Blood glucose and coronary artery disease in nondiabetic patients. Diabetes Care 2006; 29: 998–1001.

    Article  Google Scholar 

  13. Schnell O, Standl E . Impaired glucose tolerance, diabetes, and cardiovascular disease. Endocr Pract 2006; 12 (Suppl 1): 16–19.

    Article  Google Scholar 

  14. Barr EL, Zimmet PZ, Welborn TA, Jolley D, Magliano DJ, Dunstan DW et al. Risk of cardiovascular and all-cause mortality in individuals with diabetes mellitus, impaired fasting glucose, and impaired glucose tolerance: the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab). Circulation 2007; 116: 151–157.

    Article  CAS  Google Scholar 

  15. Diamantopoulos EJ, Andreadis EA, Tsourous GI, Katsanou PM, Georgiopoulos DX, Nestora KC et al. Early vascular lesions in subjects with metabolic syndrome and prediabetes. Int Angiol 2006; 25: 179–183.

    CAS  Google Scholar 

  16. Meigs JB, Larson MG, D′Agostino RB, Levy D, Clouse ME, Nathan DM et al. Coronary artery calcification in type 2 diabetes and insulin resistance: the Framingham offspring study. Diabetes Care 2002; 25: 1313–1319.

    Article  CAS  Google Scholar 

  17. Kim SH, Reaven GM . The metabolic syndrome: one step forward, two steps back. Diab Vasc Dis Res 2004; 1: 68–75.

    Article  Google Scholar 

  18. Reaven GM . Insulin resistance, the insulin resistance syndrome, and cardiovascular disease. Panminerva Med 2005; 47: 201–210.

    CAS  Google Scholar 

  19. Ninomiya JK, L′Italien G, Criqui MH, Whyte JL, Gamst A, Chen RS . Association of the metabolic syndrome with history of myocardial infarction and stroke in the Third National Health and Nutrition Examination Survey. Circulation 2004; 109: 42–46.

    Article  PubMed  Google Scholar 

  20. Bingham C, Arbogast B, Guillaume GC, Lee JK, Halberg F . Inferential statistical methods for estimating and comparing cosinor parameters. Chronobiologia 1982; 9: 397–439.

    CAS  Google Scholar 

  21. Zaslavskaya RM . Chronodiagnosis and chronotherapy of cardiovascular diseases, 2nd edn. Translation into English from Russian Medicina: Moscow, 1993, pp 397.

    Google Scholar 

  22. Katinas GS, Cornélissen G, Otsuka K, Haus E, Bakken EE, Halberg F . Why continued surveillance? Intermittent blood pressure and heart rate abnormality under treatment. Biomed Pharmacother 2005; 59 (Suppl 1): S141–S151. Diabetes Care. 1999; 22:233-40.

    Article  PubMed  Google Scholar 

  23. Coutinho M, Gerstein HC, Wang Y, Yusuf S . The relationship between glucose and incident cardiovascular events. A meta regression analysis of published data from 20 studies of 95 783 individuals followed for 12.4 years. Diabetes Care 1999; 22: 1385–1387.

    Article  Google Scholar 

  24. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo Jr JL et al. National Heart, Lung, and Blood Institute Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure; National High Blood Pressure Education Program Coordinating Committee. The Seventh Report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure: the JNC 7 report. JAMA 2003; 289: 2560–2572.

    Article  CAS  PubMed  Google Scholar 

  25. Stolarz K, Staessen JA, O′Brien ET . Night-time blood pressure: dipping into the future? J Hypertens 2002; 20: 2131–2133 (review).

    Article  CAS  Google Scholar 

  26. Giles TD . Circadian rhythm of blood pressure and the relation to cardiovascular events. J Hypertens Suppl 2006; 24: S11–S16 (review).

    Article  CAS  Google Scholar 

  27. Jerrard-Dunne P, Mahmud A, Feely J . Circadian blood pressure variation: relationship between dipper status and measures of arterial stiffness. J Hypertens 2007; 25: 1233–1239.

    Article  CAS  Google Scholar 

  28. Hermida RC, Ayala DE, Portaluppi F . Circadian variation of blood pressure: the basis for the chronotherapy of hypertension. Adv Drug Deliv Rev 2007; 59: 904–922.

    Article  CAS  Google Scholar 

  29. Dolan E, Stanton A, Thijs L, Hinedi K, Atkins N, McClory S et al. Superiority of ambulatory over clinic blood pressure measurement in predicting mortality: the Dublin outcome study. Hypertension 2005; 46: 156–161.

    Article  CAS  Google Scholar 

  30. Dolan E, Li Y, Thijs L, McCormack P, Staessen JA, O'Brien E et al. Ambulatory arterial stiffness index: rationale and methodology. Blood Press Monit 2006; 11: 103–105.

    Article  Google Scholar 

  31. Li Y, Dolan E, Wang JG, Thijs L, Zhu DL, Staessen JA et al. Ambulatory arterial stiffness index: determinants and outcome. Blood Press Monit 2006; 11: 107–110.

    Article  PubMed  Google Scholar 

  32. Kikuya M, Staessen JA, Ohkubo T, Thijs L, Metoki H, Asayama K et al. Ambulatory arterial stiffness index and 24-h ambulatory pulse pressure as predictors of mortality in Ohasama, Japan. Stroke 2007; 38: 1161–1166.

    Article  Google Scholar 

  33. Mayer B, Lieb W, Radke PW, Götz A, Fischer M, Bässler A et al. Association between arterial pressure and coronary artery calcification. J Hypertens 2007; 25: 1731–1738.

    Article  CAS  Google Scholar 

  34. O′Brien E . Sleepers versus nonsleepers: another twist to the dipper/nondipper concept. Hypertension 2007; 49: 769–770.

    Article  Google Scholar 

  35. Schwartzkopff O, Halberg F, Katinas G, Cornélissen G, Otsuka K, Watanabe Y et al. Strain tests: gauging variability in a day, week, year or decade. In: Proceedings 59th Annual Meeting Japan Society of Neurovegetative Research, Tokyo, November 1–3, 2006, pp 64–68.

  36. Cornélissen G, Halberg F, Bakken EE, Singh RB, Otsuka K, Tomlinson B et al. 100 or 30 years after Janeway or Bartter, Healthwatch helps avoid ‘flying blind’. Biomed Pharmacother 2004; 58(Suppl 1): S69–S86.

    Article  Google Scholar 

  37. De La Pena SS, Gonzalez C, Cornelissen G, Halberg F . Blood Pressure (BP), Heart Rate (HR) and Non-Insulin-Dependent Diabetes Mellitus (NIDDM) Chronobiology. Int J Cardiol 2004; 97 (Suppl 2): S14.

    Article  Google Scholar 

  38. Cornélissen G, Halberg F, Otsuka K, Singh RB, Chen CH . Chronobiology predicts actual and proxy outcomes when dipping fails. Hypertension 2007; 49: 237–239.

    Article  Google Scholar 

  39. Halberg F, Cornélissen G, Halberg J, Schwartzkopff O . Pre-hypertensive and other variabilities also await treatment. Am J Med 2007; 120: e19–e20.

    Article  PubMed  Google Scholar 

  40. Després JP . Cardiovascular disease under the influence of excess visceral fat. Crit Pathw Cardiol 2007; 6: 51–59 (review).

    Article  Google Scholar 

  41. Rajala MW, Scherer PE . Minireview: the adipocyte—at the crossroads of energy homeostasis, inflammation, and atherosclerosis. Endocrinology 2003; 144: 3765–3773.

    Article  CAS  Google Scholar 

  42. Moreno-Aliaga MJ, Campion J, Milagro FI, Berjon A, Martinez JA . Adiposity and proinflammatory state: the chicken or the egg. Adipocytes 2005; 1: 1–16.

    Google Scholar 

  43. Fantuzzi G . Adipose tissue, adipokines, and inflammation. J Allergy Clin Immunol 2005; 115: 911–919; quiz 920.

    Article  CAS  Google Scholar 

  44. Vettor R, Milan G, Rossato M, Federspil G . Review article: adipocytokines and insulin resistance. Aliment Pharmacol Ther 2005; 22 (Suppl 2): 3–10 (review).

    Article  CAS  Google Scholar 

  45. Xu H, Barnes GT, Yang Q, Tan G, Yang D, Chou CJ et al. Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. J Clin Invest 2003; 112: 1785–1788.

    Article  Google Scholar 

  46. Kougias P, Chai H, Lin PH, Yao Q, Lumsden AB, Chen C . Effects of adipocyte-derived cytokines on endothelial functions: implication of vascular disease. J Surg Res 2005; 126: 121–129.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This study was supported by grants from NIH (GM-13981) (FH) and University of Minnesota Supercomputing Institute (GC and FH).

Author information

Authors and Affiliations

  1. Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, Louisiana, USA

    A K Gupta, F L Greenway & W Pan

  2. University of Minnesota, Minneapolis, Minnesota, USA

    G Cornelissen & F Halberg

Authors
  1. A K Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. F L Greenway
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. G Cornelissen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. W Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. F Halberg
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A K Gupta.

Additional information

Presented at The Obesity Society 2007.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gupta, A., Greenway, F., Cornelissen, G. et al. Prediabetes is associated with abnormal circadian blood pressure variability. J Hum Hypertens 22, 627–633 (2008). https://doi.org/10.1038/jhh.2008.32

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/jhh.2008.32

Keywords

This article is cited by

Search

Advanced search

Quick links