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:

Within-visit blood pressure variability: relevant factors in the general population

Journal of Human Hypertension volume 27, pages 328–334 (2013)Cite this article

Subjects

Abstract

The objective of this study was to use a nationwide epidemiological survey to investigate the factors that affect within-visit blood pressure (BP) variability. We analyzed the Korean National Health and Nutrition Examination Survey (KNHNES) data for 2005 (n=5488). We examined three within-visit BP variability parameters that include the following: the alarm reaction (AR), defined as the first BP reading minus the third BP reading; the BP discrepancy, defined as the maximal BP reading minus the minimal BP reading (ΔBPmax); and the s.d. (BPSD). Age, fasting glucose, eGFR, total cholesterol, LDL cholesterol, and the metabolic syndrome (MetS) score were the relevant factors that affected the systolic AR, ΔSBPmax and SBPSD. Multiple linear regression models revealed that age (P<0.0001), the office systolic BP (SBP) level (P<0.0001), the MetS score (P<0.0001), the female gender (P=0.007) and the eGFR (P=0.049) were independently associated with the systolic AR, whereas age (P<0.0001), the office SBP level (P<0.0001), and the female gender (P=0.024 and 0.022) were independently associated with ΔSBPmax and SBPSD, respectively. Within-visit BP variability, especially the variability associated with the SBP, was significantly associated with increased age, female gender and cardiovascular risk factors, such as hypertension, low eGFR and adverse glucose and lipid profiles. In addition, increased age, female gender, the eGFR and the MetS score were independently relevant factors that affected the systolic AR. Systolic within-visit BP variability and systolic AR are associated with cardiovascular risk factors.

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. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL et al. Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension 2003; 42 (6): 1206–1252.

    Article  CAS  PubMed  Google Scholar 

  2. Mancia G, De Backer G, Dominiczak A, Cifkova R, Fagard R, Germano G et al. 2007 Guidelines for the Management of Arterial Hypertension: The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens 2007; 25 (6): 1105–1187.

    Article  CAS  PubMed  Google Scholar 

  3. Pickering TG, Hall JE, Appel LJ, Falkner BE, Graves J, Hill MN et al. Recommendations for blood pressure measurement in humans and experimental animals: Part 1: blood pressure measurement in humans: a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research. Hypertension 2005; 45 (1): 142–161.

    Article  CAS  PubMed  Google Scholar 

  4. Rothwell PM . Limitations of the usual blood-pressure hypothesis and importance of variability, instability, and episodic hypertension. Lancet 2010; 375 (9718): 938–948.

    Article  PubMed  Google Scholar 

  5. Rothwell PM, Howard SC, Dolan E, O'Brien E, Dobson JE, Dahlof B et al. Effects of beta blockers and calcium-channel blockers on within-individual variability in blood pressure and risk of stroke. Lancet Neurol 2010; 9 (5): 469–480.

    Article  CAS  PubMed  Google Scholar 

  6. Rothwell PM, Howard SC, Dolan E, O’Brien E, Dobson JE, Dahlof B et al. Prognostic significance of visit-to-visit variability, maximum systolic blood pressure, and episodic hypertension. Lancet 2010; 375 (9718): 895–905.

    Article  PubMed  Google Scholar 

  7. Webb AJ, Fischer U, Mehta Z, Rothwell PM . Effects of antihypertensive-drug class on interindividual variation in blood pressure and risk of stroke: a systematic review and meta-analysis. Lancet 2010; 375 (9718): 906–915.

    Article  CAS  PubMed  Google Scholar 

  8. Parati G . Blood pressure variability: its measurement and significance in hypertension. J Hypertens Suppl 2005; 23 (1): S19–S25.

    Article  CAS  PubMed  Google Scholar 

  9. Kikuya M, Hozawa A, Ohokubo T, Tsuji I, Michimata M, Matsubara M et al. Prognostic significance of blood pressure and heart rate variabilities: the Ohasama study. Hypertension 2000; 36 (5): 901–906.

    Article  CAS  PubMed  Google Scholar 

  10. Mancia G, Bombelli M, Facchetti R, Madotto F, Corrao G, Trevano FQ et al. Long-term prognostic value of blood pressure variability in the general population: results of the Pressioni Arteriose Monitorate e Loro Associazioni Study. Hypertension 2007; 49 (6): 1265–1270.

    Article  CAS  PubMed  Google Scholar 

  11. Sega R, Corrao G, Bombelli M, Beltrame L, Facchetti R, Grassi G et al. Blood pressure variability and organ damage in a general population: results from the PAMELA study (Pressioni Arteriose Monitorate E Loro Associazioni). Hypertension 2002; 39 (2 Pt 2): 710–714.

    Article  CAS  PubMed  Google Scholar 

  12. Kim HM, Kim DJ, Jung IH, Park C, Park J . Prevalence of the metabolic syndrome among Korean adults using the new International Diabetes Federation definition and the new abdominal obesity criteria for the Korean people. Diabetes Res Clin Pract 2007; 77 (1): 99–106.

    Article  PubMed  Google Scholar 

  13. Lawlor DA, Smith GD, Ebrahim S . Does the new International Diabetes Federation definition of the metabolic syndrome predict CHD any more strongly than older definitions? Findings from the British Women’s Heart and Health Study. Diabetologia 2006; 49 (1): 41–48.

    Article  CAS  PubMed  Google Scholar 

  14. Bovet P, Gervasoni JP, Ross AG, Mkamba M, Mtasiwa DM, Lengeler C et al. Assessing the prevalence of hypertension in populations: are we doing it right? J Hypertens 2003; 21 (3): 509–517.

    Article  CAS  PubMed  Google Scholar 

  15. Manios ED, Koroboki EA, Tsivgoulis GK, Spengos KM, Spiliopoulou IK, Brodie FG et al. Factors influencing white-coat effect. Am J Hypertens 2008; 21 (2): 153–158.

    Article  PubMed  Google Scholar 

  16. Pickering TG, Gerin W, Schwartz AR . What is the white-coat effect and how should it be measured? Blood Press Monit 2002; 7 (6): 293–300.

    Article  PubMed  Google Scholar 

  17. Su H, Wang J, Zhu Y, Wang G, Cheng X . Discrepancy among three blood pressure readings within one measurement and relevant influencing factors. Blood Press Monit 2010; 15 (3): 152–157.

    Article  PubMed  Google Scholar 

  18. Mancia G, Parati G, Pomidossi G, Casadei R, Di Rienzo M, Zanchetti A . Arterial baroreflexes and blood pressure and heart rate variabilities in humans. Hypertension 1986; 8 (2): 147–153.

    Article  CAS  PubMed  Google Scholar 

  19. Spruill TM, Pickering TG, Schwartz JE, Mostofsky E, Ogedegbe G, Clemow L et al. The impact of perceived hypertension status on anxiety and the white coat effect. Ann Behav Med 2007; 34 (1): 1–9.

    Article  PubMed  Google Scholar 

  20. Myers MG, Reeves RA . White coat effect in treated hypertensive patients: sex differences. J Hum Hypertens 1995; 9 (9): 729–733.

    CAS  PubMed  Google Scholar 

  21. Gosse P, Promax H, Durandet P, Clementy J . ‘White coat’ hypertension. No harm for the heart. Hypertension 1993; 22 (5): 766–770.

    Article  CAS  PubMed  Google Scholar 

  22. Muntner P, Levitan EB, Reynolds K, Mann DM, Tonelli M, Oparil S et al. Within-visit variability of blood pressure and all-cause and cardiovascular mortality among US adults. J Clin Hypertens 2012; 14 (3): 165–171.

    Article  Google Scholar 

  23. Michell AR . Prognostic significance of blood-pressure variability. Lancet 2010; 376 (9739): ): 413; author reply 414–415.

    Google Scholar 

  24. Klungel OH, de Boer A, Paes AH, Nagelkerke NJ, Seidell JC, Bakker A . Estimating the prevalence of hypertension corrected for the effect of within-person variability in blood pressure. J Clin Epidemiol 2000; 53 (11): 1158–1163.

    Article  CAS  PubMed  Google Scholar 

  25. Keenan K, Hayen A, Neal BC, Irwig L . Long term monitoring in patients receiving treatment to lower blood pressure: analysis of data from placebo controlled randomised controlled trial. BMJ 2009; 338: b1492.

    Article  PubMed Central  PubMed  Google Scholar 

  26. Ohkubo T, Asayama K, Imai Y . The value of self-measured home blood pressure in predicting stroke. Expert Rev Neurother 2006; 6 (2): 163–173.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank the Korea Centers for Disease Control and Prevention, which performed the KNHANES, and all the participants in the present study for their generous cooperation.

Author information

Authors and Affiliations

  1. Cardiology Division, Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Korea

    J H Shin, J Shin, B K Kim, Y-H Lim, H-C Park, S I Choi, S G Kim & J H Kim

Authors
  1. J H Shin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J Shin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. B K Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Y-H Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. H-C Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. S I Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. S G Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. J H Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J Shin.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Shin, J., Shin, J., Kim, B. et al. Within-visit blood pressure variability: relevant factors in the general population. J Hum Hypertens 27, 328–334 (2013). https://doi.org/10.1038/jhh.2012.39

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/jhh.2012.39

Keywords

This article is cited by

Search

Advanced search

Quick links