Ambulatory, home, and office blood pressure (BP) variability are often treated as a single entity. Our aim was to assess the agreement between these three methods for measuring BP variability.
Twenty-four-hour ambulatory BP monitoring, 28 home BP measurements, and eight office BP measurements were performed on 461 population-based or hypertensive participants. Five variability indices were calculated for all measurement methods: SD, coefficient of variation, maximum–minimum difference, variability independent of the mean, and average real variability. Pearson's correlation coefficients were calculated for indices measured with different methods. The agreement between different measurement methods on the diagnoses of extreme BP variability (participants in the highest decile of variability) was assessed with kappa (κ) coefficients.
SBP/DBP variability was greater in daytime (coefficient of variation: 9.8 ± 2.9/11.9 ± 3.6) and night-time ambulatory measurements (coefficient of variation: 8.6 ± 3.4/12.1 ± 4.5) than in home (coefficient of variation: 4.4 ± 1.8/4.7 ± 1.9) and office (coefficient of variation: 4.6 ± 2.4/5.2 ± 2.6) measurements (P < 0.001/0.001 for all). Pearson's correlation coefficients for systolic/diastolic daytime or night-time ambulatory–home, ambulatory–office, and home–office variability indices ranged between 0.07–0.25/0.12–0.23, 0.13–0.26/0.03–0.22 and 0.13–0.24/0.10–0.19, respectively, indicating, at most, a weak positive (r < 0.3) relationship. The agreement between measurement methods on diagnoses of extreme SBP/DBP variability was only slight (κ < 0.2), with the κ coefficients for daytime and night-time ambulatory–home, ambulatory-office, and home-office agreement varying between-0.014–0.20/0.061–0.15, 0.037–0.18/0.082–0.15, and 0.082–0.13/0.045–0.15, respectively.
Shorter-term and longer-term BP variability assessed by different methods of BP measurement seem to correlate only weakly with each other. Our study suggests that BP variability measured by different methods and timeframes may reflect different phenomena, not a single entity.
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aDepartment of Health, National Institute for Health and Welfare
bDepartment of Medicine
cTyks and Turku Region Joint Emergency Services, Turku University Hospital, Turku, Finland
Correspondence to Eeva P. Juhanoja, Department of Health, National Institute for Health and Welfare, P.O. Box 57, Turku 20521, Finland. Tel: +358 50 464 1350; e-mail: firstname.lastname@example.org
Abbreviations: ARV, average real variability; BP, blood pressure; MMD, maximum–minimum difference; VIM, variability independent of the mean
Received 2 June, 2015
Revised 11 September, 2015
Accepted 11 September, 2015
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