Abstract
There is little information about the reproducibility of the white coat effect, which was treated as a continuous variable. To investigate a long-term interval reproducibility of the white-coat effect as a continuous variable. We selected 153 participants without antihypertensive treatment (men, 22.9%; age, 64.4 years) from the general population of Ohasama, Japan, to assess the repeatedly measured white-coat effect (the difference between blood pressures at the office and home) in a 4-year interval. The reproducibility was assessed by testing the intraclass correlation coefficient (two-way random effect model-single measures). The white-coat effect for systolic/diastolic blood pressure slightly decreased by 0.17/1.56 mmHg at the 4-year visit on average. The Bland–Altman plots showed no significant systemic error for the white-coat effects (P ≥ 0.24). The intraclass correlation coefficient (95% confidence interval) of the white-coat effect for systolic blood pressure, office systolic blood pressure, and home systolic blood pressure were 0.41 (0.27–0.53), 0.64 (0.52–0.74), and 0.74 (0.47–0.86), respectively. Change in the white-coat effect was mainly affected by a change in office blood pressure. Long-term reproducibility of the white-coat effect is limited in the general population without antihypertensive treatment. The change in the white-coat effect is mainly caused by office blood pressure variation.
Similar content being viewed by others
Introduction
White-coat hypertension is defined as a condition in which office blood pressure (BP), but not out-of-office BP, is elevated. Patients with white-coat hypertension have higher cardiovascular or kidney disease risk than those with true normotension, especially in untreated individuals with older age or at high cardiovascular risk1,2,3,4,5,6,7,8,9. White-coat hypertension tends to develop into out-of-office hypertension5,10. Therefore, detecting individuals with white-coat hypertension and following them up can prevent cardiovascular diseases in the long term.
One critical problem in evaluating white-coat hypertension is its reproducibility. According to these previous studies, these hypertension phenotypes are moderately reproducible, especially in short-term intervals and in individuals without antihypertensive treatment11,12,13,14,15,16,17,18,19,20,21. However, the issues exist. First, the hypertension phenotype is generally fluctuant in individuals with BP readings close to the hypertension threshold. It is more important to assess the reproducibility of the white-coat effect as a continuous variable. We recently reported that office BP levels were associated with a higher risk of out-of-office hypertension based on self-measured BP at home (home BP) after adjustments by baseline home BP22. This implies that the white-coat effect, which is calculated as a continuous variable, has clinical significance in the prediction of future out-of-office BP elevation. Second, there is little information about the reproducibility of the white-coat effect over more than a 1-year interval13.
A previous study using multiple ambulatory BP monitoring with a 1.2-year interval reported that hypertension phenotype category, i.e. normotension, white coat hypertension, masked hypertension (only in out-of-office conditions), and sustained hypertension (hypertension both office and out-of-office) was moderately reproducible in 39 untreated patients13. The white coat effect for systolic BP measured in a 1.2-year interval showed moderately good reproducibility13. Therefore, the reproducibility of the white coat effect may be maintained for approximately one year in untreated individuals. Ambulatory BP, which is influenced by daily activities, was used in a previous study13. The white coat effect could be reproducible in the long term by using home BP, which is measured under stable conditions23,24.
The Ohasama study has measured home BP for a long term in residents of Ohasama town, a rural community in Japan. Using data from the Ohasama study, the present study examined the 4-year interval reproducibility of the white-coat effect, treated as a continuous variable, and examined the reproducibility of the BP indices with the longest interval in untreated individuals. By clarifying this, it is possible to determine whether the white coat effect is fixed individually or fluctuates over time. If the long-term reproducibility of the white coat effect is good, its frequent evaluation in clinical practice is not necessary. Furthermore, we can assume that the high cardiovascular risk of white coat hypertension could be caused by a consistently high office BP relative to out-of-office BP during follow-up.
Methods
Because the data have a sensitive nature and are maintained based on the study participants’ agreement, the data and study materials will not be made available to other researchers to reproduce results or replicate the procedure. The present study was reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines25.
Study design
This report was part of the Ohasama study, a prospective cohort study that started in 1986. Details of the study, including the socioeconomic and demographic characteristics of this region, have been described previously6,26. This study complied with the Declaration of Helsinki, and the Institutional Review Boards of Teikyo University (16-075-7), and Tohoku Medical and Pharmaceutical University approved the study protocol (2022-005 [2022-0-006]).
We performed follow-up examinations of home BP measurements every 4 years for each participant. For the current analyses, the data collected between fiscal years (April to March) 2005 and 2019 were used since only two types of devices were used for each home and office BP measurement in this term. The first visit during this period was defined as the baseline, and the second visit 4 years later was defined as a follow-up examination. Data from the entire eligible population were used.
Blood pressure (BP) measurements
Public health nurses or study investigators instructed participants to measure their home BP using the Omron HEM-747ICN or HEM7080IC cuff-oscillometric upper arm-cuff BP-monitoring device (Omron Healthcare, Kyoto, Japan)26,27,28. Participants were instructed to measure their home BP for 4 weeks, after ≥ 2 min of rest in the morning within 1 h after awakening, maintaining the arm-cuff position at heart level during rest, and, if applicable, before taking their BP-lowering medications23,24. They were also instructed to measure their home evening BP every evening just before going to bed. Participants were not asked to measure their home BP twice or more per occasion23. The second measurement value was reportedly lower than the first measurement24. Since only some participants in the present study measured BP twice per measurement occasion, the first value of each measurement occasion was uniformly used to eliminate the differences in BP due to the measurement number variation. We defined home BP as the mean of all measurements during each examination period.
Office BP was measured twice by medical staff at a local medical center, after resting for at least 2 min at a sitting posture with the arm-cuff position maintained at the level of the heart, using a semiautomatic BP-measuring device based on the oscillometric method (HEM-907 or HEM-9000AI, Omron Healthcare Co. Ltd., Kyoto, Japan)29. The mean of the two measurements was used for analysis.
The primary outcome was the 4-year reproducibility of the white coat effect, defined as the difference between office and home BP. We further defined home hypertension as home systolic BP ≥ 135 and/or home diastolic BP ≥ 85 mmHg, and office hypertension as office systolic BP ≥ 140 and/or office diastolic BP ≥ 90 mmHg according to the hypertension management guidelines24,30. Based on these hypertension definitions, we further defined normotension, white-coat hypertension (home BP < 135/ < 85 mmHg and office BP ≥ 140/ ≥ 90 mmHg), masked hypertension (home BP ≥ 135/ ≥ 85 mmHg and office BP < 140/ < 90 mmHg), and sustained hypertension (home BP ≥ 135/ ≥ 85 mmHg and office BP ≥ 140/ ≥ 90 mmHg).
Other information
We gathered information on smoking status, alcohol consumption, medications, and histories of diseases through a questionnaire survey, medical interview, or reviewing medical records. Diabetes was defined as a random glucose level ≥ 11.1 mmol/L (≥ 200 mg/dL), a fasting glucose level ≥ 7.0 mmol/L (≥ 126 mg/dL), hemoglobin A1c based on the National Glycohemoglobin Standardization Program threshold ≥ 6.5%, or the use of oral antidiabetic drugs or insulin. Dyslipidemia was indicated by low-density lipoprotein cholesterol ≥ 3.62 mmol/L (≥ 140 mg/dL), high-density lipoprotein cholesterol < 1.03 mmol/L (< 40 mg/dL), triglycerides ≥ 1.69 mmol/L (≥ 150 mg/dL), or use of anti dyslipidemia medications.
Statistical analyses
We selected the participants without antihypertensive treatment both at baseline and the 4-year visit. The characteristics between follow-up and non-follow-up participants were tested to confirm selection bias. The difference in hypertension phenotype between baseline and the 4-year visit was examined by Bowker’s test of symmetry and kappa statistics. The level of agreement was defined based on the κ value as follows: 0–0.20, minimal agreement; 0.21–0.40, fair agreement; 0.41–0.60, moderate agreement; 0.61–0.80, substantial agreement; and 0.81–1.00, almost perfect or perfect agreement31. The reproducibility of the white-coat effect as a continuous variable was assessed by testing for association, bias, agreement, and consistency. Pearson’s correlation coefficients and regression equations were calculated to examine the association between the white-coat effect at baseline and that at the 4-year visit. To examine the bias between the measurements, we used the Bland–Altman analysis, which plots the average of the two measurements on the x-axis and the difference between the two measurements on the y-axis32. A significant regression slope in the Bland–Altman plot suggests the presence of systematic error in the measurements32. Intraclass correlation coefficients (ICCs) were calculated between the baseline and 4-year visit values to assess agreement and consistency between them. The agreement was assessed using ICC from the two-way random effect model single measures, which is generally indicated as ICC (2, 1)33,34. The ICC (2, 1) values were lower due to age-related changes in BP indices. The consistency was assessed using ICC from the two-way mixed effect model single measures, or the ICC (3, 1)33,34. The ICC (3, 1) model indicates consistency but not an agreement between measurements since it deals with the mean difference between measurements as a systematic error, resulting in ICC values not considering age-related BP changes33,34. The value of the ICC ranges from 0 to 1, where one represents the perfect reliability of the measurement. An ICC of ≥ 0.70 is required as a minimum standard for test–retest reliability35,36, although there is no established threshold of ICC. We also calculated the ICC for the white-coat effect in the participants who measured their home and office BP using the same devices (HEM-747ICN and HEM-907, respectively) in the baseline and 4-year visits to confirm the effect of differences in measurement devices. To exclude the basic characteristics differences, stratification analysis by sex or age (< 65/ ≥ 65 years) was performed.
Participants were stratified by the difference in white-coat effect for systolic BP between the 4-year visit and baseline < − 10 mmHg, − 10–10 mmHg, and > 10 mmHg. To examine factors associated with a change in the white-coat effect, participant characteristics were compared among these three groups.
Statistical differences in means and proportions were assessed using Welch’s t-test or analysis of variance and Fisher’s exact test, respectively. The office statistical significance was set at an α-level < 0.05 on two-tailed tests. Data were expressed as mean ± standard deviation unless otherwise stated. R software (version 4.2.1, R Foundation for Statistical Computing) was used for the calculation of ICCs, and SAS version 9.4 (SAS Institute, Cary, NC, USA) was used for other statistical analyses.
Results
Participant selection
In 2005, 3182 individuals aged ≥ 55 years lived in Ohasama. Figure 1 shows the flowchart of participant selection. Of those, 1005 participated in the examination between the fiscal years 2005 and 2019, and 970 provided informed consent to participate in this study. We excluded 11 participants without office BP data and 4 who did not measure their home BP for ≥ 3 days. We excluded 437 patients under antihypertensive treatment at baseline to exclude the effect of the antihypertensive regimen change. For this analysis, 281 participants were excluded because they did not undergo the 4-year follow-up visit. Among them, those excluded because of loss to follow-up had a higher proportion of alcohol drinkers relative to the 237 participants who underwent the follow-up; there were no significant differences in BP levels between these two groups (Supplementary Table S1). Of the remaining 237 participants, 14.4% (n = 19/132) with normotension, 41.0% (n = 16/39) with white-coat hypertension, 65.2% (n = 15/23) with masked hypertension, and 79.1% (n = 34/43) with sustained hypertension experienced antihypertensive treatment initiation; these 84 participants who initiated antihypertensive treatment between baseline and the 4-year visit were also excluded (baseline characteristics in 84 individuals are shown in Supplementary Table S2). Finally, 153 participants, who were not treated with antihypertensive drugs both at baseline and the 4-year visit, were included in the present analysis. Home and office systolic/diastolic BP levels at baseline were higher in 84 participants excluded due to antihypertensive treatment initiation than in 153 untreated participants (all P < 0.0001).
Participant characteristics
The characteristics of 153 participants at baseline and the 4-year visit are shown in Table 1. From baseline, body mass index and the proportion of alcohol drinkers decreased at the 4-year visit. Office systolic and home systolic/diastolic BP increased. The white-coat effect for diastolic BP significantly decreased, whereas the amplitude of change was small.
Reproducibility of hypertension phenotypes
The prevalence of normotension, white-coat hypertension, masked hypertension, and sustained hypertension at baseline was 113 (73.9%), 23 (15.0%), 8 (5.2%), and 9 (5.9%), respectively. Of those, 103 (67.3%) participants had the same hypertension phenotype at baseline and the 4-year visit. Of the 23 participants with white-coat hypertension, 4 and 8 participants, switched to the normotension or sustained hypertension group at the 4-year visit, respectively (characteristics based on the hypertension phenotype at the 4-year visit are shown in Supplementary Table S3). The agreement between hypertension phenotypes at baseline and the 4-year visit was minimal (Table 2) (κ = 0.36; 95% confidence interval, 0.25–0.48; χ2 for symmetry test = 17.4; df = 6; P = 0.0079).
Reproducibility of difference between office and home BP as a continuous variable
The white-coat effects at baseline were moderately correlated with those at the 4-year visit (r = 0.41 for systolic and r = 0.40 for diastolic) (Fig. 2). The regression coefficients of the white-coat effects at baseline against the values at the 4-year visit were 0.45 for systolic and 0.41 for diastolic (Fig. 2). No significant regression slopes were observed in the Bland–Altman plots (P = 0.24 for systolic and P = 0.93 for diastolic) (Fig. 2).
The white-coat effect for systolic/diastolic BP decreased by 0.17/1.56 mmHg at the 4-year visit. The ICCs of the white-coat effect for systolic and diastolic BPs were 0.41 and 0.40, respectively; those were similar in the analysis based on 94 participants who measured their BP using the same office and home measurement devices (Table 3). The reproducibility was good (ICC > 0.7) only for home BP (Table 3). When home evening BP was used to define the white-coat effect instead of home morning BP, the results were similar to those based on home morning BP: the ICCs (95% confidence intervals) of the white-coat effect for systolic and diastolic BPs were 0.47 (0.34–0.59) and 0.44 (0.30–0.56), respectively (Supplementary Table S4). When home morning BP measured only for 7 days was used, the ICCs (3, 1) of the white-coat effect for systolic and diastolic BPs decreased to 0.34 and 0.35, respectively (Supplementary Table S5).
The stratification analyses according to sex (Supplementary Table S6) or age (Supplementary Table S7) were performed. The point estimates of ICC for the white coat effect ranged from 0.32 to 0.52. The ICC levels for home BP were consistently higher than those for office BP. The ICC (2, 1) and ICC (3, 1) for the white coat effect for systolic BP were 0.17 (− 0.03–0.36) and 0.19 (− 0.03–0.39), respectively, in the 84 participants excluded due to antihypertensive treatment initiation.
Factors associated with the change in the magnitude of the white-coat effect
The white-coat effect for systolic BP at baseline was inversely associated with the 4-year change in the white-coat effect (Table 4). The difference in office systolic BP strongly contributed to the large change in the white-coat effect; for instance, in the participants with ≤ − 10 mmHg change (decreased at the 4-year visit) in the white-coat effect for systolic BP, the office systolic BP decreased by 11.3 mmHg (134.2–122.9 mmHg), whereas the home systolic BP increased only by 7.1 mmHg (119.1–126.2 mmHg) (Table 4). The participants’ characteristics other than BP levels were not associated with the change in the white-coat effect (Table 4).
Discussion
The reproducibility of hypertension phenotypes with a 4-year interval was considered to be minimal to fair from the kappa values. The long-term reproducibility of the white-coat effect, which was used as a continuous variable, was also limited since the ICC value did not reach 0.7, although no significant systemic errors were confirmed. The variability of the white-coat effect change was mainly caused by the large office BP difference.
The reproducibility of hypertension phenotypes was limited when it was reassessed after 4 years (κ-value, 0.36). This is possibly attributed to the high proportion of normotension (73.9% were normotensives in the untreated participants). A previous meta-analysis reported a similar κ-value (0.39) regarding hypertension phenotype reproducibility based on home BP in untreated individuals21. This meta-analysis included the studies conducted within 1 week or half a year21. Therefore, the hypertension phenotype reproducibility appeared not to be good regardless of the measurement interval.
One important issue in the evaluation of hypertension phenotype is that hypertension classification easily changes in individuals with BP readings close to the hypertension threshold. The present findings suggest that the white-coat effect is not reproducible even when it is assessed as a continuous variable. The ICC between white-coat effects at baseline and the 4-year visit was approximately 0.4 and showed no good reproducibility of white-coat effects in the present study. Only half of the participants had the 4-year change of white coat effect for systolic BP within |10| mmHg. The limited reproducibility of the white-coat effect or hypertension phenotype can cause inconsistent results regarding its prognosis1,2,3,4,5,6,7,8,9. A previous study revealed that the test–retest correlation coefficient between the white coat effects for systolic BP measured in a 1.2-year interval was 0.69 in untreated individuals13. The white coat effect may be reproducible within 1 year.
The decrease in the white-coat effect was observed in the participants with a high white-coat effect at baseline, and vice versa. This result can suggest the presence of “regression to the mean” phenomena. The variability of the white-coat effect change appeared to be mainly caused by office BP variation. The previous study assessed the reproducibility of office BP strictly measured by an automated measurement device37. Consequently, the variability in office BP between visits was large even in the absence of an observer (unattended office BP) in 287 outpatients37. Considering this fact37, it could be difficult to capture stable white-coat phenomena. Meanwhile, the reproducibility or repeatability of home BP is reported to be good at least in the 1-year interval37,38,39. The present study expanded this evidence into the longer term.
Apart from the reproducibility issue, the present results also imply that individuals with hypertension cannot easily move to the normotension group. Only 11.1–25.0% of individuals moved to the normotension group among the participants having hypertension. The proportion of antihypertensive treatment initiation was high in the hypertensive participants. If individuals with untreated hypertension are found in a health checkup, we should follow-up with these individuals carefully or should consider initiating treatment.
The strength of the study was the assessment of the long-term reproducibility of the white coat effect as a continuous variable in a general population without antihypertensive treatment. It is difficult to assess an individual’s white coat effect or home BP values in a 4-year interval. White coat hypertension is associated with a long-term, but not short-term, cardiovascular risk40. However, from the limited long-term reproducibility of the white coat effect as per the present findings, the white coat phenomenon can change during the long-term follow-up period and can merely be a temporal condition at baseline. This could not be proven in a short-term study. Notably, in clinical practice, the white-coat effect has variability and should be confirmed at least in a 1-year interval13. We previously suggested that an “introverted” personality is associated with white-coat hypertension41. Future research considering personality is needed to clarify which individuals consistently reveal white coat hypertension in a long term based on a larger sample size.
The present study has some limitations. First, since the present study was conducted on the middle-aged or elderly population from the Japanese rural area, the generalizability and transportability of the findings may be limited. However, the higher reproducibility of home BP than that of office BP was observed similar to the results from the previous studies37,38,39. Third, participants who newly received antihypertensive medications based on each hypertension subtype were excluded. The present results can only be generalized to individuals who do not require antihypertensive treatment. The exclusion of the participants with antihypertensive treatment initiation could affect the reproducibility of the hypertension phenotype and may have underestimated the persistence of hypertension subtypes. Furthermore, we did not assess adherence to antihypertensive treatment in treated participants. Detailed information on the antihypertensive treatment regimen is missing for a proportion of treated participants. For these reasons, we could not assess the accurate reproducibility among the treated participants. The white coat effect in treated patients varies depending on the number of antihypertensive medications or the timing of pill administration42. A previous study reported that the Pearson correlation coefficients for the white-coat effect taken 3 months apart were 0.22 for systolic and 0.25 for diastolic pressure in treated patients with resistant hypertension, suggesting poor reproducibility of white-coat hypertension in treated individuals20. Fourth, the exclusion of those who were lost to follow-up (n = 281) may have contributed to the poor reproducibility of the white coat effect. However, the selection bias due to loss to follow-up may be limited since large differences in baseline BP levels between the follow-up and non-follow-up participants were not there. Fifth, we used the first value of each measurement occasion for home BP whereas the recent guidelines recommend two measurements on each occasion24,30,43,44. The reproducibility of home BP could have been underestimated in the present study. Finally, we do not have data on physical activity, which is known to affect BP levels24,30,44.
In conclusion, the long-term reproducibility of the white-coat effect is limited in the general population without antihypertensive treatment. It is difficult to capture a stable white-coat effect in the long term. The change in the white-coat effect includes the regression to the mean phenomenon, which is mainly caused by office BP variation. Since the white-coat effect is fluctuant, home and office BPs should be measured regularly.
Data availability
Because the data have a sensitive nature and are maintained based on the research participants’ agreement, the data and study materials will not be made available to other researchers to reproduce results or replicate the procedure.
References
Mancia, G. et al. Long-term risk of sustained hypertension in white-coat or masked hypertension. Hypertension 54, 226–232. https://doi.org/10.1161/HYPERTENSIONAHA.109.129882 (2009).
Ohkubo, T. et al. Prognosis of “masked” hypertension and “white-coat” hypertension detected by 24-h ambulatory blood pressure monitoring 10-year follow-up from the Ohasama study. J. Am. Coll. Cardiol. 46, 508–515. https://doi.org/10.1016/j.jacc.2005.03.070 (2005).
Cohen, J. B. et al. Cardiovascular events and mortality in white coat hypertension: A systematic review and meta-analysis. Ann. Intern. Med. 170, 853–862. https://doi.org/10.7326/M19-0223 (2019).
Huang, Q. F. et al. Ambulatory blood pressure monitoring to diagnose and manage hypertension. Hypertension 77, 254–264. https://doi.org/10.1161/HYPERTENSIONAHA.120.14591 (2021).
Mancia, G. et al. Long-term prognostic value of white coat hypertension: An insight from diagnostic use of both ambulatory and home blood pressure measurements. Hypertension 62, 168–174. https://doi.org/10.1161/HYPERTENSIONAHA.111.00690 (2013).
Satoh, M. et al. Long-term stroke risk due to partial white-coat or masked hypertension based on home and ambulatory blood pressure measurements: The Ohasama Study. Hypertension 67, 48–55. https://doi.org/10.1161/HYPERTENSIONAHA.115.06461 (2016).
Satoh, M. et al. Stroke risk due to partial white-coat or masked hypertension based on the ACC/AHA guideline’s blood pressure threshold: The Ohasama study. Hypertens. Res. 42, 120–122. https://doi.org/10.1038/s41440-018-0133-2 (2019).
Kanno, A. et al. Usefulness of assessing masked and white-coat hypertension by ambulatory blood pressure monitoring for determining prevalent risk of chronic kidney disease: The Ohasama study. Hypertens. Res. 33, 1192–1198. https://doi.org/10.1038/hr.2010.139 (2010).
Stergiou, G. S. et al. Prognosis of white-coat and masked hypertension: International database of home blood pressure in relation to cardiovascular outcome. Hypertension 63, 675–682. https://doi.org/10.1161/HYPERTENSIONAHA.113.02741 (2014).
Ugajin, T. et al. White-coat hypertension as a risk factor for the development of home hypertension: The Ohasama study. Arch. Intern. Med. 165, 1541–1546. https://doi.org/10.1001/archinte.165.13.1541 (2005).
Mancia, G. et al. Limited reproducibility of MUCH and WUCH: evidence from the ELSA study. Eur. Heart J. 41, 1565–1571. https://doi.org/10.1093/eurheartj/ehz651 (2020).
Cupisti, A. et al. Blood pressure phenotype reproducibility in CKD outpatients: A clinical practice report. Intern. Emerg. Med. 15, 87–93. https://doi.org/10.1007/s11739-019-02127-y (2020).
Ben-Dov, I. Z., Ben-Arie, L., Mekler, J. & Bursztyn, M. Reproducibility of white-coat and masked hypertension in ambulatory BP monitoring. Int. J. Cardiol. 117, 355–359. https://doi.org/10.1016/j.ijcard.2006.04.088 (2007).
Barochiner, J., Posadas Martinez, M. L., Martinez, R. & Giunta, D. Reproducibility of masked uncontrolled hypertension detected through home blood pressure monitoring. J. Clin. Hypertens. (Greenwich) 21, 877–883. https://doi.org/10.1111/jch.13596 (2019).
Viera, A. J., Hinderliter, A. L., Kshirsagar, A. V., Fine, J. & Dominik, R. Reproducibility of masked hypertension in adults with untreated borderline office blood pressure: Comparison of ambulatory and home monitoring. Am. J. Hypertens. 23, 1190–1197. https://doi.org/10.1038/ajh.2010.158 (2010).
de la Sierra, A. et al. Short-term and long-term reproducibility of hypertension phenotypes obtained by office and ambulatory blood pressure measurements. J. Clin. Hypertens. (Greenwich) 18, 927–933. https://doi.org/10.1111/jch.12792 (2016).
Ghazi, L. et al. Effect of intensive and standard clinic-based hypertension management on the concordance between clinic and ambulatory blood pressure and blood pressure variability in SPRINT. J. Am. Heart Assoc. 8, e011706. https://doi.org/10.1161/JAHA.118.011706 (2019).
Viera, A. J. et al. Reproducibility of masked hypertension among adults 30 years or older. Blood Press. Monit. 19, 208–215. https://doi.org/10.1097/MBP.0000000000000054 (2014).
Kawabe, H. & Saito, I. Reproducibility of masked hypertension determined from morning and evening home blood pressure measurements over a 6-month period. Hypertens. Res. 30, 845–851. https://doi.org/10.1291/hypres.30.845 (2007).
Muxfeldt, E. S. et al. Appropriate time interval to repeat ambulatory blood pressure monitoring in patients with white-coat resistant hypertension. Hypertension 59, 384–389. https://doi.org/10.1161/HYPERTENSIONAHA.111.185405 (2012).
Antza, C. et al. Reproducibility of masked hypertension and office-based hypertension: A systematic review and meta-analysis. J. Hypertens. 40, 1053–1059. https://doi.org/10.1097/HJH.0000000000003111 (2022).
Satoh, M. et al. Prediction models for the 5- and 10-year incidence of home morning hypertension: The Ohasama Study. Am. J. Hypertens. 35, 328–336. https://doi.org/10.1093/ajh/hpab177 (2022).
Imai, Y. et al. The Japanese Society of Hypertension guidelines for self-monitoring of blood pressure at home. Hypertens. Res. 35, 777–795. https://doi.org/10.1038/hr.2012.56 (2012).
Umemura, S. et al. The Japanese Society of Hypertension Guidelines for the Management of Hypertension (JSH 2019). Hypertens. Res. 42, 1235–1481. https://doi.org/10.1038/s41440-019-0284-9 (2019).
von Elm, E. et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. Lancet 370, 1453–1457. https://doi.org/10.1016/S0140-6736(07)61602-X (2007).
Imai, Y. et al. Characteristics of a community-based distribution of home blood pressure in Ohasama in northern Japan. J Hypertens 11, 1441–1449 (1993).
El Assaad, M. A., Topouchian, J. A. & Asmar, R. G. Evaluation of two devices for self-measurement of blood pressure according to the international protocol: The Omron M5-I and the Omron 705IT. Blood Press. Monit. 8, 127–133. https://doi.org/10.1097/01.mbp.0000087393.96145.b1 (2003).
Coleman, A., Freeman, P., Steel, S. & Shennan, A. Validation of the Omron 705IT (HEM-759-E) oscillometric blood pressure monitoring device according to the British Hypertension Society protocol. Blood Press. Monit. 11, 27–32 (2006).
White, W. B. & Anwar, Y. A. Evaluation of the overall efficacy of the Omron office digital blood pressure HEM-907 monitor in adults. Blood Press. Monit. 6, 107–110 (2001).
Williams, B. et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension: The task force for the management of arterial hypertension of the European Society of Cardiology and the European Society of Hypertension: The task force for the management of arterial hypertension of the European Society of Cardiology and the European Society of Hypertension. J. Hypertens. 36, 1953–2041. https://doi.org/10.1097/HJH.0000000000001940 (2018).
Landis, J. R. & Koch, G. G. The measurement of observer agreement for categorical data. Biometrics 33, 159–174. https://doi.org/10.2307/2529310 (1977).
Bland, J. M. & Altman, D. G. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1, 307–310 (1986).
McGraw, K. O. & Wong, S. P. Forming inferences about some intraclass correlation coefficients. Psychol. Methods 1, 30 (1996).
Koo, T. K. & Li, M. Y. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J. Chiropr. Med. 15, 155–163. https://doi.org/10.1016/j.jcm.2016.02.012 (2016).
Terwee, C. B. et al. Quality criteria were proposed for measurement properties of health status questionnaires. J. Clin. Epidemiol. 60, 34–42. https://doi.org/10.1016/j.jclinepi.2006.03.012 (2007).
Heidemann, C. H. et al. The Otitis Media-6 questionnaire: Psychometric properties with emphasis on factor structure and interpretability. Health Qual. Life Outcomes 11, 201. https://doi.org/10.1186/1477-7525-11-201 (2013).
Asayama, K. et al. Direct comparison of the reproducibility of in-office and self-measured home blood pressures. J. Hypertens. 40, 398–407. https://doi.org/10.1097/HJH.0000000000003026 (2022).
Fujiwara, T., Hoshide, S., Kanegae, H., Nishizawa, M. & Kario, K. Reliability of morning, before-dinner, and at-bedtime home blood pressure measurements in patients with hypertension. J. Clin. Hypertens. (Greenwich) 20, 315–323. https://doi.org/10.1111/jch.13165 (2018).
Stergiou, G. S. et al. Reproducibility of home, ambulatory, and clinic blood pressure: Implications for the design of trials for the assessment of antihypertensive drug efficacy. Am. J. Hypertens. 15, 101–104 (2002).
Verdecchia, P. et al. Short- and long-term incidence of stroke in white-coat hypertension. Hypertension 45, 203–208. https://doi.org/10.1161/01.HYP.0000151623.49780.89 (2005).
Hozawa, A. et al. Introversion associated with large differences between screening blood pressure and home blood pressure measurement: The Ohasama study. J. Hypertens. 24, 2183–2189. https://doi.org/10.1097/01.hjh.0000249695.81241.35 (2006).
Horikawa, T. et al. Difference between home and office blood pressures among treated hypertensive patients from the Japan Home versus Office Blood Pressure Measurement Evaluation (J-HOME) study. Hypertens. Res. 31, 1115–1123. https://doi.org/10.1291/hypres.31.1115 (2008).
Stergiou, G. S. et al. 2021 European Society of Hypertension practice guidelines for office and out-of-office blood pressure measurement. J. Hypertens. 39, 1293–1302. https://doi.org/10.1097/HJH.0000000000002843 (2021).
Whelton, P. K. et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension 71, e13–e115. https://doi.org/10.1161/HYP.0000000000000065 (2018).
Acknowledgements
We are grateful to the residents and staff members in the Ohasama town and the staff members of the Hanamaki City Government, Iwate Prefectural Central Hospital Attachment Ohasama Regional Clinical Center (former Ohasama Hospital) for their valuable support on the Ohasama study project.
Funding
This study was supported by Grants for Scientific Research, Ministry of Education, Culture, Sports, Science and Technology, Japan (18K09674, 18K09904, 18K17396, 19K19325, 19K19466, 19H03908, 19K10662, 20K08612, 20K18819, 21K10452, 21K10478, 21H04854, 21K17313, 21K19670, 22H03358, and 22K10070); The internal research grants from Keio University; the Japan Arteriosclerosis Prevention Fund; Grant–in–aid from the Ministry of Health, Labor, and Welfare, Japan (H29–Junkankitou–Ippan–003 and 20FA1002); ACRO Incubation Grants of Teikyo University; The Academic Contributions from Pfizer Japan Inc. and Bayer Yakuhin, Ltd; Scholarship donations from Daiichi Sankyo Co., Ltd.; Research Support from Astellas Pharma Inc. and Takeda Pharmaceutical Co., Ltd.; Health Science Center Research Grant; Takeda Science Foundation.
Author information
Authors and Affiliations
Contributions
M.S.: Conceptualization, data curation, formal analysis, funding acquisition, investigation, methodology, project administration, supervision, validation, visualization, and writing of the original draft. T.Y.: Conceptualization, data curation, formal analysis, methodology, validation, visualization, review, and editing. H.M.: Conceptualization, funding acquisition, investigation, methodology, project administration, supervision, visualization, review, and editing. T.M., Y.T., K.A., K.T., M.T., and Y.I.: funding acquisition, investigation, methodology, project administration, review, and editing. A.H., T.H., and A.H.: investigation, methodology, project administration, review, and editing. M.K.: data curation, funding acquisition, investigation, methodology, project administration, review, and editing. T.O.: Principal investigator of the Ohasama study, conceptualization, funding acquisition, investigation, methodology, project administration, visualization, review, and editing. All the authors contributed to this scientific work and approved the final version of the manuscript.
Corresponding author
Ethics declarations
Competing interests
M.S. received the Scholarship (Academic Contribution) from Bayer Yakuhin, Ltd. H.M., K.A., Y.I., and T.O. concurrently held the position of director of the Tohoku Institute for the Management of Blood Pressure, supported by Omron Healthcare Co., Ltd. K.A. received honoraria from Takeda Pharmaceutical Co., Ltd. K.A. and T.O. received a joint research grant from Omron Healthcare Co., Ltd. The Division of Integrative Renal Replacement Therapy was financially supported by Chugai Pharmaceutical Co., Ltd., Terumo Corporation, and JMS Co., Ltd. All other authors state no competing interest.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Satoh, M., Yoshida, T., Metoki, H. et al. The long-term reproducibility of the white-coat effect on blood pressure as a continuous variable from the Ohasama Study. Sci Rep 13, 4985 (2023). https://doi.org/10.1038/s41598-023-31861-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-023-31861-9
Comments
By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.