High Blood Pressure in Adults: Screening
December 22, 2014
Recommendations made by the USPSTF are independent of the U.S. government. They should not be construed as an official position of the Agency for Healthcare Research and Quality or the U.S. Department of Health and Human Services.
By Margaret A. Piper, PhD, MPH; Corinne V. Evans, MPP; Brittany U. Burda, MPH; Karen L. Margolis, MD, MPH; Elizabeth O’Connor, PhD; and Evelyn P. Whitlock, MD, MPH
The information in this article is intended to help clinicians, employers, policymakers, and others make informed decisions about the provision of health care services. This article is intended as a reference and not as a substitute for clinical judgment.
This article may be used, in whole or in part, as the basis for the development of clinical practice guidelines and other quality enhancement tools, or as a basis for reimbursement and coverage policies. AHRQ or U.S. Department of Health and Human Services endorsement of such derivative products may not be stated or implied.
This article was published online first at www.annals.org on 23 December 2014.
Nearly 1 in 3 U.S. adults has high blood pressure (BP), including two thirds of those aged 60 years or older.1 Elevated BP is the largest contributing risk factor to all-cause and cardiovascular mortality.2 Despite the clear importance of accurate diagnosis of high BP, recommendations for BP measurement protocols and rescreening intervals are not based on systematic reviews of the literature,3, 4 and recommended protocols, such as repeated measurements, are rarely followed in routine health care settings.5–9 To help address these issues, newer measurement methods have been developed to reduce error, simplify performance of repeated measurements, evaluate BP throughout the 24-hour cycle, and allow use in nonmedical settings. Evidence-based measurement methods and rescreening intervals could improve the benefits and efficiency of BP screening.
In 2007, the U.S. Preventive Services Task Force (USPSTF) reaffirmed its 2003 A recommendation to screen for high BP in adults aged 18 years or older.10 In 2003, a synthesis of indirect evidence for BP screening found good-quality evidence that treatment of high BP in adults substantially decreases the incidence of cardiovascular events.11 Both reviews found that screening and treatment for high BP cause few major harms.11, 12 Given the strong evidence base for the previous recommendations and recently updated guidelines for BP control,4, 13 the USPSTF did not believe that updating the indirect evidence path was necessary. However, the previous systematic reviews did not identify a BP measurement reference standard, address diagnostic accuracy of BP measurement methods and protocols, or determine the most appropriate rescreening interval. Our evidence review was designed to address these important aspects of screening for high BP and update the direct evidence of benefits and harms of screening.
To conduct this review, we developed an analytic framework with 5 key questions (Appendix Figure 1) that examined direct evidence for the benefits and harms of screening for high BP (key questions 1 and 5, respectively), diagnostic accuracy of office BP measurement (OBPM) (key question 2), prediction of cardiovascular events by BP method and diagnostic accuracy of nonoffice measurement (key question 3), and rescreening interval (key question 4). Detailed methods are available in our full evidence report.14 The analytic framework, review questions, and methods for locating and qualifying evidence were posted on the USPSTF Web site for public comment before we started the review, and the final versions reflect public input.
Data Sources and Searches
We searched MEDLINE, PubMed, the Cochrane Central Register of Controlled Trials, and CINAHL from 2003 through 8 August 2014 to update benefits and harms of screening for high BP. We searched the same databases (excluding CINAHL) through 24 February 2014 as follows: starting in 1992 (to allow for implementation of the first guidelines for validation of BP monitoring devices15) for prediction of cardiovascular events by BP method and diagnostic accuracy of nonoffice measurement, and starting in 1966 (the beginning of MEDLINE) for rescreening interval. On the basis of the findings from these updated searches, we did not further update them because any studies we found would probably not have changed the overall conclusions. We also searched bibliographies of relevant reviews, included studies, and publication lists of highly referenced studies.
Two investigators independently reviewed abstracts and full-text articles against prespecified inclusion and exclusion criteria.14 We required all studies to have enrolled untreated adults and to have been conducted in countries rated as “very high” on the 2013 Human Development Index.16 For prediction of cardiovascular events, we allowed studies that included treated patients because a proportion of persons followed over time would inevitably begin treatment. Ambulatory BP monitoring (ABPM) and home BP monitoring (HBPM) devices were eligible for use in confirming an initially elevated OBPM result. For screening benefits and harms, cardiovascular events we analyzed included fatal or nonfatal myocardial infarction; sudden cardiac death; stroke; heart failure; atrial fibrillation; transient ischemic attack; end-stage kidney disease; or a composite of any of the aforementioned events excluding cardiovascular symptoms, angina, revascularization, carotid intima–media thickness, and left ventricular hypertrophy.
For diagnostic accuracy of OBPM, we included studies that compared different office-based devices or measurement protocols and reported sensitivity, specificity, predictive values, or concordance (for example, κ). For diagnostic accuracy of confirmatory BP measurement methods, eligible study populations had an initial elevated office BP at screening, which allowed for reporting or calculation of the positive predictive value (PPV).
For prediction of cardiovascular events, eligible studies followed a cohort of patients over time and reported the associations (hazard or risk ratios) of BP as a continuous variable, measured by at least 2 methods at baseline, with data on overall mortality or cardiovascular events collected during follow-up. For rescreening interval, we included studies that followed cohorts of initially nonhypertensive adults over time and reported hypertension incidence at rescreening intervals of up to 6 years.
Data Extraction and Quality Assessment
One investigator abstracted data from all included studies, and a second checked for accuracy. Two investigators independently assessed the quality of included studies by using predefined, design-specific criteria.17–19 We rated study quality as good, fair, or poor and excluded all poor-quality studies.17 We resolved disagreements about quality through discussion with a third investigator. Where reported, studies with various threats to internal validity were downgraded to fair-quality according to USPSTF standards.17
Data Synthesis and Analysis
We qualitatively described the results on the benefits and harms of screening. Per our protocol, we first calculated the diagnostic accuracy of OBPM by using the recommendations of the American Heart Association as the reference standard because there is no gold standard for BP measurement.3 With the subsequent identification of ABPM as the best predictor of cardiovascular events, we calculated the diagnostic accuracy of OBPM and confirmatory BP measurement methods by using ABPM as the reference standard where possible. We qualitatively described all diagnostic accuracy results because data were insufficient for quantitative synthesis.
For prediction of cardiovascular events, we combined fatal and nonfatal events within outcome categories (cardiovascular, stroke, and cardiac). Risk was most commonly reported as the hazard ratio associated with each 10–mm Hg increase in systolic BP and each 5–mm Hg increase in diastolic BP. We converted hazard ratios to these common increments if they were reported differently.14 We depicted the hazard ratios in forest plots for qualitative evaluation; because of the small numbers of studies for each outcome and heterogeneity across studies, we did not calculate summary meta-analytic estimates of risk to determine the best BP measurement method for prediction. We conducted exploratory meta-analyses to compare ABPM protocols (24-hour, daytime, and nighttime) by generating estimates of cardiovascular events or mortality risk for each protocol by using the DerSimonian–Laird random-effects method.20 In sensitivity analyses, these results were compared to estimates generated by using profile likelihood21 and Knapp–Hartung methods.22
For rescreening, we pooled reported incidence rates across all studies to generate a weighted mean incidence at yearly intervals (reported within ± 0.5 year). We qualitatively examined within-study comparisons among a priori subgroups of age, BP, sex, body mass index (BMI), smoking status, and race/ethnicity.14
When constructing the overall summary of evidence (Table 1), we evaluated included studies within the context of each review question for consistency of results for important outcomes and relevance to primary care.
Role of the Funding Source
Agency for Healthcare Research and Quality (AHRQ) staff provided oversight for the project and assisted in external review of the companion draft evidence synthesis. Liaisons for the USPSTF helped to resolve issues about the scope of the review but were not involved in the conduct of the review.
Benefits of Screening for High BP
For direct evidence of screening benefit, we included only randomized, controlled trials (RCTs) that reported changes in health outcomes as a result of screening for hypertension compared with no screening. We identified 1 good-quality cluster RCT of a community pharmacy–based BP screening program targeting adults aged 65 years or older.23 Trained volunteer health educators also provided participants with educational materials and resources to support self-management. This trial found fewer annual composite cardiovascular-related hospitalizations in the intervention group than in the control group (rate ratio, 0.91 [95% CI, 0.86 to 0.97]; P = 0.002). When the data were analyzed by the number of unique patients hospitalized, only the reduction in admissions for acute myocardial infarction was statistically significant (rate ratio, 0.89 [CI, 0.79 to 0.99]; P = 0.03). End-stage kidney disease outcomes were not reported. Summaries of the limitations, consistency, and applicability of the evidence for all key questions can be found in Table 1.
Diagnostic Accuracy of OBPM
We identified 4 good-quality24–27 and 3 fair-quality28–30 studies examining the diagnostic accuracy of OBPM methods or protocols in untreated screening populations. Four of these studies25–28 examined how well automated oscillometric OBPM (1 to 3 measurements) predicted results from manual sphygmomanometry (the reference standard). Among these, 3 studies26–28 reported sensitivities of oscillometric OBPM ranging from 51% to 68% for elevated BP (systolic BP ≥140 mm Hg or diastolic BP ≥90 mm Hg), as measured by the reference method. The fourth study25 reported a sensitivity of 91% but differed from the others in that it used a higher threshold in its definition of elevated BP (systolic BP ≥160 mm Hg or diastolic BP ≥95 mm Hg) and used a research design that minimized human error in manual BP measurement. The fair-quality study28 reported the lowest sensitivity and used 3 different oscillometric devices, with no attempt to ensure comparability or validity among them. Overall, these 4 studies reported more consistent specificities (97% to 98%) and PPVs (76% to 84%). In 3 studies31–33 that compared manual and automated OBPM with ABPM as the reference standard, neither manual nor automated systolic OBPM results were clearly favored.
Three diagnostic accuracy studies examined the effect of different aspects of recommended protocols for OBPM24, 29, 30 in untreated screening populations. For investigating the value of repeated measurements, a single manual BP measurement had a high sensitivity (95%) but a moderate PPV (76%) for the average of the second and third measurements in 1 study with a protocol that included a 5-minute premeasurement rest.24 One small study found elevated BP within the normal range among normotensive participants whose legs were crossed during measurement,29 and another found falsely elevated BP above the hypertensive threshold 40 minutes after caffeine ingestion among 17% of normotensive participants.30
Prediction of Cardiovascular Events by BP Measurement Method
We identified a reference standard for BP measurement by comparing the accuracy of ambulatory and home-based confirmatory measurement methods with office-based methods for predicting overall mortality and cardiovascular outcomes.
We evaluated the predictive value of ABPM methods for long-term cardiovascular events, after adjustment for OBPM, in 6 good-quality34–39 and 5 fair-quality40–44 studies. The ABPM devices used in the included trials are generally still available in the United States and have been validated against at least 1 recognized protocol (www.dableducational.org). Where reported, all ABPM devices were oscillometric and typically took measurements every 15 to 30 minutes during the day and every 30 to 60 minutes at night (Appendix Table 1). Eight, 10, and 9 studies reported outcomes for 24-hour, daytime, and nighttime monitoring cycles, respectively. One study that monitored BP for 48 hours was grouped with those monitoring for 24 hours.36 Results did not seem to vary by geographic region or population baseline characteristics. Each 10–mm Hg increment in 24-hour systolic ABPM, adjusted for OBPM, was consistently and statistically significantly associated with an increased risk for fatal and nonfatal stroke in 4 studies.38, 39, 41, 44 Hazard ratios ranged from 1.28 to 1.40 (Figure 1). In 6 studies, each 10–mm Hg increment in 24-hour systolic ABPM, adjusted for OBPM, was associated with an increased risk for fatal and nonfatal cardiovascular events. These results were statistically significant in 5 studies (Figure 1).34, 36, 38, 41, 43 Hazard ratios ranged from 1.11 to 1.42. One additional study42 reported only that ABPM predicted cardiovascular mortality in a model that included OBPM ( P < 0.001). Estimates of hazard ratios for each 5–mm Hg increment in diastolic 24-hour ABPM, adjusted for OBPM, were also generally statistically significant but were more attenuated (data not shown).14
We conducted an unplanned, exploratory meta-analysis to look for relative differences among ABPM protocols. This analysis showed no apparent differences in hazard ratios for each 10–mm Hg increase in systolic BP (24-hour ABPM hazard ratio, 1.24 [CI, 1.17 to 1.30]; I2 = 8.7%; daytime ABPM hazard ratio, 1.20 [CI, 1.12 to 1.28]; I2 = 33.3%; nighttime ABPM hazard ratio, 1.24 [CI, 1.17 to 1.31]; I2 = 25.6% [all controlled for OBPM]). A sensitivity analysis that used 2 additional meta-analytic methods also did not show any differences among protocols.
We also evaluated the predictive value of HBPM for long-term cardiovascular events in 5 good-quality studies,35, 45–48 4 of which adjusted for OBPM. All showed statistically significant associations with an increased risk for cardiovascular and mortality outcomes, with hazard ratios ranging from 1.17 to 1.39 (Appendix Figure 3).
Diagnostic Accuracy of Methods to Confirm Elevated Office BP
We considered confirmatory BP measurement methods separately from screening OBPM to identify persons who have an elevated BP at screening but are normotensive after confirmatory testing in a nonmedical setting (isolated clinic hypertension). Without confirmatory follow-up, this group may be harmed by misdiagnosis and unnecessary treatment.
We evaluated the diagnostic accuracy of confirmatory BP measurement methods by using ABPM as the reference standard, where available, subsequent to an elevated BP at screening in 6 good-quality32, 49–53 and 21 fair-quality31, 33, 40, 54–71 studies. Across 24 comparable studies allowing calculation, the proportion of persons with an elevated BP at screening who were hypertensive on confirmatory testing by ABPM or HBPM ranged from 35% to 95% (Figure 2). Four studies also confirmed hypertension in 58% to 96% of persons who repeated BP measurement at subsequent office visits with the same methods used at the initial screening (data not shown). Study population characteristics related to increased hypertension prevalence, such as older average age, a higher number of abnormal screening results before confirmatory testing, and a higher BP at screening, seemed to be qualitatively associated with a higher PPV for ABPM-confirmed hypertension. On the basis of screening measurement alone, the likelihood of misdiagnosis of hypertension is greater as measurements approach the threshold for a diagnosis of hypertension.
We investigated whether using different screening and confirmatory measurement methods improves diagnostic accuracy. We found 2 studies that enrolled persons with an elevated office BP and followed up with both ABPM and repeated OBPM by the same screening method at a separate visit, but the results did not consistently show improved results with confirmatory testing (data not shown).54, 61
Harms of Screening for High BP
We examined several potential harms in addition to misdiagnosis and unnecessary treatment. One good-quality72 and 3 fair-quality73–75 trials found no statistically significant differences in psychological distress or quality of life among participants who were labeled as hypertensive or prehypertensive. One fair-quality cohort study conducted among persons who were previously unaware of their hypertension status found increases in overall absenteeism from work, absenteeism due to illness, and number and duration of illness episodes after labeling that were statistically significant at 1 year 76 and 4 years of follow-up.77 Four fair-quality cohort studies reported sleep disturbances, discomfort, and restrictions in daily activities during the use of an ABPM device.78–81
Rescreening Interval and Hypertension Incidence in Screened Normotensive Persons
We identified 15 good-quality82–96 and 25 fair-quality53, 97–120 studies that reported hypertension incidence after rescreening, and 39 of these reported incidence by a priori subgroups of interest. Studies enrolled between 275 and 115,736 participants at baseline and evaluated screening intervals of up to 6 years. The largest number (16 studies) reported results for a 5-year interval, and only 2 studies provided data for more than 1 rescreening interval.88, 99 Most studies used a diagnostic threshold of at least 140/90 mm Hg and considered the use of antihypertensive medications equivalent to a BP exceeding the diagnostic threshold. Included studies were conducted in Asia (19 studies), the United States (8 studies), Europe (10 studies), the United Kingdom, and Australia. Twenty-one studies were community-based, 12 were employment-based, and 6 were conducted in clinics.
Incidence estimates varied widely at each rescreening interval (2.2% to 4.4% at 1 year and 2.1% to 28.4% at 5 years) (Figure 3). Studies that diagnosed hypertension on the basis of multiple office visits generally showed lower incidence than those that measured BP at 1 visit. In 2 studies that reported hypertension incidence both with and without repeated OBPM at confirmatory visits, about 55% of first-visit incident hypertension cases were not confirmed,53, 97 which suggests that true incident hypertension at various intervals is likely to be at the lower end of these estimates.
The substantial variation in hypertension incidence across studies is related in part to the criteria used to diagnose, and in some studies confirm, incident hypertension. Some variation probably also arises from differences in study populations, which highlights the importance of identifying subpopulations with a higher risk for incident hypertension that may benefit from targeted or more intensive rescreening.
Rescreening Interval in Subpopulations
Appendix Table 2 shows weighted mean hypertension incidence across studies at rescreening intervals of 1 to 5 years, stratified by a priori subpopulations. We focused our detailed evaluation on studies providing direct within-study comparisons.
Four studies reported incidence by age strata (Appendix Table 3).53, 87, 89, 109 Hypertension incidence was as much as 2- to 4-fold higher in older persons (aged 40 or 45 to 60 or 65 years) than in younger persons (aged 18 to 40 or 45 years). Similarly, hypertension incidence increased with increasing baseline BP (Appendix Table 4).85, 90, 91, 95, 107 Incidence consistently tripled between optimal (<120/80 mm Hg) and normal (120–129/80–84 mm Hg) BP categories and approximately doubled between normal and high-normal (130–139/85–89 mm Hg) categories. For example, persons with optimal BP had a low probability (2% to 9%) of developing hypertension over a 5-year period.
Hypertension incidence was generally higher among men than women, especially in younger populations (Appendix Table 5). Although incidence was also 2-fold higher in overweight persons and 3-fold higher in obese persons compared with normal-weight persons (Table 2),53, 111 it was not increased in smokers versus nonsmokers or former smokers (data not shown).14
Five studies conducted in the United States reported hypertension incidence at rescreening intervals by race/ethnicity (Table 3).84, 86, 88, 97, 105 In each study, the incidence for African Americans was nearly 2 or more times higher than for white persons at all intervals. Only 1 study directly compared additional racial or ethnic categories; it reported higher incidence rates for African Americans at 5 years (27.5%) than for Asian, white, or Hispanic persons (16.2% to 21.2%).86
An earlier review of indirect evidence and the resulting USPSTF recommendation found that treatment of high BP substantially decreases the incidence of cardiovascular events.10, 12 We examined direct evidence of benefits and harms of screening programs to identify adults with high BP and found a single RCT that targeted adults aged 65 years or older. Among those randomly assigned to screening, there was a small but statistically significant reduction in hospitalizations for acute myocardial infarction. Although the results do not apply to all age groups and were potentially confounded by additional management interventions, they provide supportive evidence for the effects of a BP screening program on target cardiovascular disease events.
We then focused most of our review efforts on BP screening methods and rescreening intervals to determine accurate and timely methods for identifying persons with elevated BP who are likely to benefit from treatment. We first examined BP measurement methods used for initial, office-based screening. Surprisingly, few studies provided sufficient data to compare the diagnostic accuracy of manual sphygmomanometry with that of automated methods in screening populations. Similarly, few studies of OBPM protocols were eligible, and those that were provided limited support for repeating BP measurement at a single visit, avoiding caffeine ingestion before measurement, and keeping legs uncrossed during measurement. Studies that seemed to provide support for other recommendations, such as proper arm positioning,121–123 cuff size,124–126 and cuff deflation speed127 (but not removal of clothing before cuff placement122, 128, 129), primarily reported results in terms of mean values rather than diagnostic categories or enrolled hypertensive populations. Although automated OBPM methods offer the advantages of repeated measurements in the absence of medical personnel, future evidence reviews will need to consider the applicability of the larger number of studies conducted in treated, hypertensive persons to these questions.
Blood pressure measured by office mercury sphygmomanometry is known to be associated with cardiovascular outcomes.130 We compared ABPM and HBPM with manual office methods and found that systolic ABPM consistently and statistically significantly predicted stroke and other cardiovascular outcomes independently of OBPM. In an exploratory, comparative meta-analysis (n = 13,906), we found no apparent difference among 24-hour, daytime, and nighttime ABPM protocols within our included evidence base. Our results were similar to those of a systematic review by the National Institute for Health and Care Excellence,131 which concluded that ABPM was superior for predicting clinical outcomes, with no protocol favored in a qualitative review of the data (n > 17,621). However, we did not evaluate certain outcomes (such as angina or revascularization) or populations with comorbid conditions (such as diabetes or kidney disease) and only included studies conducted in countries rated “very high” on the Human Development Index. Two other large meta-analyses (one that included 13,843 hypertensive patients132 and one that analyzed 23,856 hypertensive patients and 9641 randomly recruited persons133) reported that nighttime systolic ABPM was a stronger predictor of cardiovascular events than daytime ABPM or OPBM. Evidence gaps suggested by these conflicting meta-analyses include the influence of treatment and age133 and of composite outcomes and population composition on the predictive values of 24-hour, daytime, and nighttime ABPM. We also found that systolic HBPM predicted cardiovascular outcomes in a pattern similar to that of ABPM; however, too few studies were available to allow us to draw firm conclusions about HBPM.
On the basis of the prognostic evidence, we selected ABPM as the reference standard for BP measurement and for evaluating the diagnostic accuracy of other measurement methods. We regarded daytime, nighttime, or 24-hour ABPM protocols as acceptable. Improved prediction with ABPM also suggested the need for confirmation of OBPM. We found that OBPM variably predicted “true” hypertension, as defined by ABPM. Despite this variability, hypertension at screening with OBPM was not confirmed by non-OBPM methods in a large proportion of persons. Measurement error and regression to the mean may contribute to false-positive screening results with OBPM. However, some persons without confirmation of elevated BP at screening have isolated clinic hypertension. Studies have reported that the long-term outcomes of these persons are more similar to those of normotensive persons than to those of patients with sustained hypertension.134 An unplanned analysis of patients with isolated clinic hypertension in our included studies of cardiovascular prognosis also suggested that cardiovascular disease outcomes are more similar to those of persons who are normotensive at baseline than to those of persons with sustained hypertension (data not shown).14 Given the high variability of OBPM for predicting hypertension at confirmatory testing and the importance of identifying persons who truly require treatment, confirmatory measurement is needed to avoid misdiagnosis. Ambulatory BP monitoring provides multiple measurements over time in a nonmedical setting, which potentially avoids measurement error, regression to the mean, and misdiagnosis of isolated clinic hypertension and is best correlated with long-term outcomes.
Our evidence review shows that overdiagnosis of hypertension from unconfirmed office-based screening could result in unnecessary treatment in a substantial number of persons. Although our scope did not include reviewing evidence to determine rates of harms due to unnecessary treatment and did not directly address the proportion of persons who would have isolated clinic hypertension, these considerations will be important for future reviews. We found no evidence of other serious harms of BP screening.
Finally, we investigated the best interval for rescreening of BP after a normal screening result. Guidelines make recommendations for rescreening intervals, but none are evidence-based. We found that estimates of incident hypertension at annual intervals up to 6 years were highly variable. Qualitative analysis identified a trend toward lower estimates and less variability in studies that required confirmation (for example, by repeated measurements or visits) of elevated BP at rescreening. These findings further support the importance of confirmatory BP measurement, whether initially or at rescreening. We conclude that the wide variation in incident hypertension was at least partly driven by the different population characteristics reported in the studies. The incidence of hypertension was higher in older persons, African Americans, those with an above-normal BMI, and those with a high-normal BP.
In summary, the available evidence suggests that repeated measurements may improve the diagnostic accuracy of OBPM for screening. Initially elevated BP measured by office-based methods is best confirmed by ABPM to avoid potential overdiagnosis of isolated clinic hypertension and the potential harms of unnecessary treatment. Studies of rescreening intervals of up to 6 years found a variably high incidence of hypertension overall. Hypertension incidence at rescreening was also higher at shorter intervals for persons with BP in the high-normal range, for older persons, for those with an above-normal BMI, and for African Americans compared with those without these risk factors. These results suggest that time and resources might be better directed toward improved measurement accuracy and timely measurement in higher-risk persons rather than measurement of all persons at every office visit.
Source: This article was published online first at www.annals.org on 23 December 2014.
Acknowledgment: The authors thank the following for their contributions to this project: AHRQ staff; the USPSTF; David B. Callahan, MD, Beverly B. Green, MD, MPH, Joel Handler, MD, James A. Hodgkinson, MD, MSc, Carla I. Mercado, PhD, MS, Martin G. Myers, MD, and George S. Stergiou, MD, for providing expert review of the report; Ning Smith, PhD, for providing statistical expertise; Elizabeth Webber, MS; Leslie A. Perdue, MPH; Keshia Bigler, BS; and Kevin Lutz, MFA, and Smyth Lai, MLS, at the Kaiser Permanente Center for Health Research.
Grant Support: By contract HHSA-290-2012-00151-I, Task Order No. 2 from AHRQ.
Potential Conflicts of Interest: Dr. Piper, Ms. Evans, Ms. Burda, Dr. Margolis, Dr. O'Connor, and Dr. Whitlock report grants from AHRQ during the conduct of the study. Dr. Margolis also reports grants from the National Heart, Lung, and Blood Institute outside the submitted work. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M14-1539.
1. Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Blaha MJ, et al; American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics—2014 update: a report from the American Heart Association. Circulation. 2014;129:e28-292. [PMID: 24352519]
2. Yang Q, Cogswell ME, Flanders WD, Hong Y, Zhang Z, Loustalot F, et al. Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults. JAMA. 2012;307:1273-83. [PMID: 22427615]
3. Pickering TG, Hall JE, Appel LJ, Falkner BE, Graves JW, Hill MN, et al; Council on High Blood Pressure Research Professional and Public Education Subcommittee, American Heart Association. Recommendations for blood pressure measurement in humans: an AHA scientific statement from the Council on High Blood Pressure Research Professional and Public Education Subcommittee. J Clin Hypertens (Greenwich). 2005;7:102-9. [PMID: 15722655]
4. James PA, Oparil S, Carter BL, Cushman WC, Dennison-Himmelfarb C, Handler J, et al. 2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA. 2014;311:507-20. [PMID: 24352797]
5. Graves JW, Sheps SG. Does evidence-based medicine suggest that physicians should not be measuring blood pressure in the hypertensive patient? [Editorial]. Am J Hypertens. 2004;17:354-60. [PMID: 15062890]
6. Scherwitz LW, Evans LA, Hennrikus DJ, Vallbona C. Procedures and discrepancies of blood pressure measurements in two community health centers. Med Care. 1982;20:727-38. [PMID: 7121092]
7. Burgess SE, MacLaughlin EJ, Smith PA, Salcido A, Benton TJ. Blood pressure rising: differences between current clinical and recommended measurement techniques. J Am Soc Hypertens. 2011;5:484-8. [PMID: 22015319]
8. Minor DS, Butler KR Jr, Artman KL, Adair C, Wang W, McNair V, et al. Evaluation of blood pressure measurement and agreement in an academic health sciences center. J Clin Hypertens (Greenwich). 2012;14:222-7. [PMID: 22458743]
9. Kay LE. Accuracy of blood pressure measurement in the family practice center. J Am Board Fam Pract. 1998;11:252-8. [PMID: 9719346]
10. U.S. Preventive Services Task Force. Screening for high blood pressure: U.S. Preventive Services Task Force reaffirmation recommendation statement. Ann Intern Med. 2007;147:783-6. [PMID: 18056662]
11. Sheridan S, Pignone M, Donahue K. Screening for high blood pressure: a review of the evidence for the U.S. Preventive Services Task Force. Am J Prev Med. 2003;25:151-8. [PMID: 12880884]
12. Wolff T, Miller T. Evidence for the reaffirmation of the U.S. Preventive Services Task Force recommendation on screening for high blood pressure. Ann Intern Med. 2007;147:787-91. [PMID: 18056663]
13. Go AS, Bauman MA, Coleman King SM, Fonarow GC, Lawrence W, Williams KA, et al; American Heart Association. An effective approach to high blood pressure control: a science advisory from the American Heart Association, the American College of Cardiology, and the Centers for Disease Control and Prevention. Hypertension. 2014;63:878-85. [PMID: 24243703]
14. Piper MA, Evans CV, Burda BU, Margolis KL, O'Connor E, Smith N, et al. Screening for High Blood Pressure in Adults: A Systematic Evidence Review for the U.S. Preventive Services Task Force. Evidence Synthesis No. 121. AHRQ Publication No. 13-05194-EF-1. Rockville, MD: Agency for Healthcare Research and Quality; 2014.
15. Verberk WJ, Kroon AA, Kessels AG, de Leeuw PW. Home blood pressure measurement: a systematic review. J Am Coll Cardiol. 2005;46:743-51. [PMID: 16139119]
16. United Nations Development Programme. Human Development Report 2013. The Rise of the South: Human Progress in a Diverse World. New York: United Nations Development Programme; 2013.
17. Harris RP, Helfand M, Woolf SH, Lohr KN, Mulrow CD, Teutsch SM, et al; Methods Work Group, Third US Preventive Services Task Force. Current methods of the US Preventive Services Task Force: a review of the process. Am J Prev Med. 2001;20:21-35. [PMID: 11306229]
18. Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, et al; QUADAS-2 Group. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155:529-36. [PMID: 22007046]
19. Wells GA, Shea B, O'Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. 2014. Accessed at www.ohri.ca/programs/clinical_epidemiology/oxford.asp on 21 January 2014.
20. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7:177-88. [PMID: 3802833]
21. Hardy RJ, Thompson SG. A likelihood approach to meta-analysis with random effects. Stat Med. 1996;15:619-29. [PMID: 8731004]
22. Hartung J, Knapp G. A refined method for the meta-analysis of controlled clinical trials with binary outcome. Stat Med. 2001;20:3875-89. [PMID: 11782040]
23. Kaczorowski J, Chambers LW, Dolovich L, Paterson JM, Karwalajtys T, Gierman T, et al. Improving cardiovascular health at population level: 39 community cluster randomised trial of Cardiovascular Health Awareness Program (CHAP). BMJ. 2011;342:d442. [PMID: 21300712]
24. Handler J, Zhao Y, Egan BM. Impact of the number of blood pressure measurements on blood pressure classification in US adults: NHANES 1999–2008. J Clin Hypertens (Greenwich). 2012;14:751-9. [PMID: 23126346]
25. Kroke A, Fleischhauer W, Mieke S, Klipstein-Grobusch K, Willich SN, Boeing H. Blood pressure measurement in epidemiological studies: a comparative analysis of two methods. Data from the EPIC-Potsdam Study. European Prospective Investigation into Cancer and Nutrition. J Hypertens. 1998;16:739-46. [PMID: 9663913]
26. Lim YH, Choi SY, Oh KW, Kim Y, Cho ES, Choi BY, et al. Comparison between an automated device and a manual mercury sphygmomanometer in an epidemiological survey of hypertension prevalence. Am J Hypertens. 2014;27:537-45. [PMID: 23764377]
27. Ostchega Y, Nwankwo T, Sorlie PD, Wolz M, Zipf G. Assessing the validity of the Omron HEM-907XL oscillometric blood pressure measurement device in a National Survey environment. J Clin Hypertens (Greenwich). 2010;12:22-8. [PMID: 20047626]
28. Pavlik VN, Hyman DJ, Toronjo C. Comparison of automated and mercury column blood pressure measurements in health care settings. J Clin Hypertens (Greenwich). 2000;2:81-86. [PMID: 11416630]
29. Peters GL, Binder SK, Campbell NR. The effect of crossing legs on blood pressure: a randomized single-blind cross-over study. Blood Press Monit. 1999;4:97-101. [PMID: 10450120]
30. Pincomb GA, Lovallo WR, McKey BS, Sung BH, Passey RB, Everson SA, et al. Acute blood pressure elevations with caffeine in men with borderline systemic hypertension. Am J Cardiol. 1996;77:270-4. [PMID: 8607407]
31. Graves JW, Grossardt BR. Discarding the first of three nurse-auscultatory or oscillometric blood pressure measurements does not improve the association of office blood pressure with ABPM. Blood Press Monit. 2010;15:146-51. [PMID: 20407368]
32. Myers MG. A proposed algorithm for diagnosing hypertension using automated office blood pressure measurement. J Hypertens. 2010;28:703-8. [PMID: 20150823]
33. Zabludowski JR, Rosenfeld JB. Evaluation of clinic blood pressure measurements: assessment by daytime ambulatory blood pressure monitoring. Isr J Med Sci. 1992;28:345-8. [PMID: 1607269]
34. Clement DL, De Buyzere ML, De Bacquer DA, de Leeuw PW, Duprez DA, Fagard RH, et al; Office versus Ambulatory Pressure Study Investigators. Prognostic value of ambulatory blood-pressure recordings in patients with treated hypertension. N Engl J Med. 2003;348:2407-15. [PMID: 12802026]
35. Fagard RH, Van Den Broeke C, De Cort P. Prognostic significance of blood pressure measured in the office, at home and during ambulatory monitoring in older patients in general practice. J Hum Hypertens. 2005;19:801-7. [PMID: 15959536]
36. Hermida RC, Ayala DE, Mojón A, Fernández JR. Decreasing sleep-time blood pressure determined by ambulatory monitoring reduces cardiovascular risk. J Am Coll Cardiol. 2011;58:1165-73. [PMID: 21884956]
37. Ingelsson E, Björklund-Bodegård K, Lind L, Arnlöv J, Sundström J. Diurnal blood pressure pattern and risk of congestive heart failure. JAMA. 2006;295:2859-66. [PMID: 16804152]
38. Ohkubo T, Kikuya M, Metoki H, Asayama K, Obara T, Hashimoto J, 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. 2005;46:508-15. [PMID: 16053966]
39. 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;282:539-46. [PMID: 10450715]
40. Celis H, Staessen JA, Thijs L, Buntinx F, De Buyzere M, Den Hond E, et al; Ambulatory Blood Pressure and Treatment of Hypertension Trial Investigators. Cardiovascular risk in white-coat and sustained hypertensive patients. Blood Press. 2002;11:352-6. [PMID: 12523678]
41. 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;46:156-61. [PMID: 15939805]
42. Hansen TW, Jeppesen J, Rasmussen S, Ibsen H, Torp-Pedersen C. Ambulatory blood pressure and mortality: a population-based study. Hypertension. 2005;45:499-504. [PMID: 15753229]
43. Gasowski J, Li Y, Kuznetsova T, Richart T, Thijs L, Grodzicki T, et al. Is “usual” blood pressure a proxy for 24-h ambulatory blood pressure in predicting cardiovascular outcomes? Am J Hypertens. 2008;21:994-1000. [PMID: 18600212]
44. Mesquita-Bastos J, Bertoquini S, Polónia J. Cardiovascular prognostic value of ambulatory blood pressure monitoring in a Portuguese hypertensive population followed up for 8.2 years. Blood Press Monit. 2010;15:240-6. [PMID: 20616705]
45. Asayama K, Ohkubo T, Kikuya M, Obara T, Metoki H, Inoue R, et al. Prediction of stroke by home “morning” versus “evening” blood pressure values: the Ohasama study. Hypertension. 2006;48:737-43. [PMID: 16952977]
46. Bobrie G, Chatellier G, Genes N, Clerson P, Vaur L, Vaisse B, et al. Cardiovascular prognosis of “masked hypertension” detected by blood pressure self-measurement in elderly treated hypertensive patients. JAMA. 2004;291:1342-9. [PMID: 15026401]
47. Niiranen TJ, Hänninen MR, Johansson J, Reunanen A, Jula AM. Home-measured blood pressure is a stronger predictor of cardiovascular risk than office blood pressure: the Finn-Home study. Hypertension. 2010;55:1346-51. [PMID: 20385970]
48. Ohkubo T, Imai Y, Tsuji I, Nagai K, Kato J, Kikuchi N, et al. Home blood pressure measurement has a stronger predictive power for mortality than does screening blood pressure measurement: a population-based observation in Ohasama, Japan. J Hypertens. 1998;16:971-5. [PMID: 9794737]
49. Cuspidi C, Sala C, Valerio C, Negri F, Mancia G. Nocturnal blood pressure in untreated essential hypertensives. Blood Press. 2011;20:335-41. [PMID: 21651423]
50. Nasothimiou EG, Tzamouranis D, Rarra V, Roussias LG, Stergiou GS. Diagnostic accuracy of home vs. ambulatory blood pressure monitoring in untreated and treated hypertension. Hypertens Res. 2012;35:750-5. [PMID: 22357523]
51. Ungar A, Pepe G, Monami M, Lambertucci L, Torrini M, Baldasseroni S, et al. Isolated ambulatory hypertension is common in outpatients referred to a hypertension centre. J Hum Hypertens. 2004;18:897-903. [PMID: 15241442]
52. Andreadis EA, Angelopoulos ET, Tsakanikas AP, Agaliotis GD, Kravvariti SD, Mousoulis GP. Automated office versus home measurement of blood pressure in the assessment of morning hypertension. Blood Press Monit. 2012;17:24-34. [PMID: 22218221]
53. Radi S, Lang T, Lauwers-Cancès V, Chatellier G, Fauvel JP, Larabi L, et al; IHPAF Group. One-year hypertension incidence and its predictors in a working population: the IHPAF study. J Hum Hypertens. 2004;18:487-94. [PMID: 14961044]
54. Fogari R, Corradi L, Zoppi A, Lusardi P, Poletti L. Repeated office blood pressure controls reduce the prevalence of white-coat hypertension and detect a group of white-coat normotensive patients. Blood Press Monit. 1996;1:51-54. [PMID: 10226202]
55. Gerc V, Favrat B, Brunner HR, Burnier M. Is nurse-measured blood pressure a valid substitute for ambulatory blood pressure monitoring? Blood Press Monit. 2000;5:203-9. [PMID: 11035861]
56. Gustavsen PH, Høegholm A, Bang LE, Kristensen KS. White coat hypertension is a cardiovascular risk factor: a 10-year follow-up study. J Hum Hypertens. 2003;17:811-7. [PMID: 14704724]
57. Hond ED, Celis H, Fagard R, Keary L, Leeman M, O'Brien E, et al; THOP Investigators. Self-measured versus ambulatory blood pressure in the diagnosis of hypertension. J Hypertens. 2003;21:717-22. [PMID: 12658017]
58. Hozawa A, Ohkubo T, Kikuya M, Yamaguchi J, Ohmori K, Fujiwara T, et al. Blood pressure control assessed by home, ambulatory and conventional blood pressure measurements in the Japanese general population: the Ohasama study. Hypertens Res. 2002;25:57-63. [PMID: 11924727]
59. Inden Y, Tsuda M, Hayashi H, Takezawa H, Iino S, Kondo T, et al. Relationship between Joint National Committee-VI classification of hypertension and ambulatory blood pressure in patients with hypertension diagnosed by casual blood pressure. Clin Cardiol. 1998;21:801-6. [PMID: 9825191]
60. Kario K. Diagnosis of true uncontrolled hypertension using both home and ambulatory blood pressure monitoring. J Hum Hypertens. 2014;28:176-9. [PMID: 23924872]
61. Khoury S, Yarows SA, O'Brien TK, Sowers JR. Ambulatory blood pressure monitoring in a nonacademic setting. Effects of age and sex. Am J Hypertens. 1992;5:616-23. [PMID: 1418850]
62. Licitra R, Acconcia MC, Puddu PE, Pannarale G. Ambulatory blood pressure monitoring in prehypertensive subjects. Cardiovasc Hematol Disord Drug Targets. 2012;12:44-50. [PMID: 22524174]
63. Manning G, Rushton L, Millar-Craig MW. Clinical implications of white coat hypertension: an ambulatory blood pressure monitoring study. J Hum Hypertens. 1999;13:817-22. [PMID: 10618670]
64. Martínez MA, García-Puig J, Martín JC, Guallar-Castillón P, Aguirre de Cárcer A, Torre A, et al; Monitorización Ambulatoria de la Presión Arterial (MAPA)-Area 5 Working Group. Frequency and determinants of white coat hypertension in mild to moderate hypertension: a primary care-based study. Am J Hypertens. 1999;12:251-9. [PMID: 10192226]
65. Pierdomenico SD, Mezzetti A, Lapenna D, Guglielmi MD, Mancini M, Salvatore L, et al. "White-coat" hypertension in patients with newly diagnosed hypertension: evaluation of prevalence by ambulatory monitoring and impact on cost of health care. Eur Heart J. 1995;16:692-7. [PMID: 7588903]
66. Talleruphuus U, Bang LE, Wiinberg N, Mehlsen J, Svendsen TL, Bentzon MW. Isolated systolic hypertension in an elderly Danish population. Prevalence and daytime ambulatory blood pressure. Blood Press. 2006;15:347-53. [PMID: 17472025]
67. Tanabe P, Persell SD, Adams JG, McCormick JC, Martinovich Z, Baker DW. Increased blood pressure in the emergency department: pain, anxiety, or undiagnosed hypertension? Ann Emerg Med. 2008;51:221-9. [PMID: 18207606]
68. Toyama H, Hasegawa Y, Ejima Y, Kurosawa S, Sanada S, Hatano R, et al. Characteristics of young-onset white coat hypertension identified by targeted screening for hypertension at a university health check-up. Hypertens Res. 2008;31:1063-8. [PMID: 18716352]
69. Verdecchia P, Schillaci G, Borgioni C, Ciucci A, Zampi I, Gattobigio R, et al. White coat hypertension and white coat effect. Similarities and differences. Am J Hypertens. 1995;8:790-8. [PMID: 7576395]
70. Zawadzka A, Bird R, Casadei B, Conway J. Audit of ambulatory blood pressure monitoring in the diagnosis and management of hypertension in practice. J Hum Hypertens. 1998;12:249-52. [PMID: 9607694]
71. Pessanha P, Viana M, Ferreira P, Bertoquini S, Polónia J. Diagnostic value and cost-benefit analysis of 24 hours ambulatory blood pressure monitoring in primary care in Portugal. BMC Cardiovasc Disord. 2013;13:57. [PMID: 23937261]
72. Spruill TM, Feltheimer SD, Harlapur M, Schwartz JE, Ogedegbe G, Park Y, et al. Are there consequences of labeling patients with prehypertension? An experimental study of effects on blood pressure and quality of life. J Psychosom Res. 2013;74:433-8. [PMID: 23597332]
73. Ameling EH, de Korte DF, Man in ‘t Veld A. Impact of diagnosis and treatment of hypertension on quality of life: a double-blind, randomized, placebo-controlled, cross-over study of betaxolol. J Cardiovasc Pharmacol. 1991;18:752-60. [PMID: 1723773]
74. Mann AH. The psychological effect of a screening programme and clinical trial for hypertension upon the participants. Psychol Med. 1977;7:431-8. [PMID: 905459]
75. Viera AJ, Lingley K, Esserman D. Effects of labeling patients as prehypertensive. J Am Board Fam Med. 2010;23:571-83. [PMID: 20823351]
76. Haynes RB, Sackett DL, Taylor DW, Gibson ES, Johnson AL. Increased absenteeism from work after detection and labeling of hypertensive patients. N Engl J Med. 1978;299:741-4. [PMID: 692548]
77. Taylor DW, Haynes RB, Sackett DL, Gibson ES. Longterm follow-up of absenteeism among working men following the detection and treatment of their hypertension. Clin Invest Med. 1981;4:173-7. [PMID: 7337988]
78. Verdecchia P, Angeli F, Borgioni C, Gattobigio R, Reboldi G. Ambulatory blood pressure and cardiovascular outcome in relation to perceived sleep deprivation. Hypertension. 2007;49:777-83. [PMID: 17261645]
79. Manning G, Rushton L, Donnelly R, Millar-Craig MW. Variability of diurnal changes in ambulatory blood pressure and nocturnal dipping status in untreated hypertensive and normotensive subjects. Am J Hypertens. 2000;13:1035-8. [PMID: 10981556]
80. Viera AJ, Lingley K, Hinderliter AL. Tolerability of the Oscar 2 ambulatory blood pressure monitor among research participants: a cross-sectional repeated measures study. BMC Med Res Methodol. 2011;11:59. [PMID: 21524301]
81. Nasothimiou EG, Karpettas N, Dafni MG, Stergiou GS. Patients' preference for ambulatory versus home blood pressure monitoring. J Hum Hypertens. 2014;28:224-9. [PMID: 24152822]
82. Brantsma AH, Bakker SJ, de Zeeuw D, de Jong PE, Gansevoort RT. Urinary albumin excretion as a predictor of the development of hypertension in the general population. J Am Soc Nephrol. 2006;17:331-5. [PMID: 16434504]
83. Everson SA, Kaplan GA, Goldberg DE, Salonen JT. Hypertension incidence is predicted by high levels of hopelessness in Finnish men. Hypertension. 2000;35:561-7. [PMID: 10679498]
84. Juhaeri, Stevens J, Chambless LE, Tyroler HA, Rosamond W, Nieto FJ, et al. Associations between weight gain and incident hypertension in a bi-ethnic cohort: the Atherosclerosis Risk in Communities Study. Int J Obes Relat Metab Disord. 2002;26:58-64. [PMID: 11791147]
85. Kim J, Kim E, Yi H, Joo S, Shin K, Kim J, et al. Short-term incidence rate of hypertension in Korea middle-aged adults. J Hypertens. 2006;24:2177-82. [PMID: 17053538]
86. Lakoski SG, Cushman M, Siscovick DS, Blumenthal RS, Palmas W, Burke G, et al. The relationship between inflammation, obesity and risk for hypertension in the Multi-Ethnic Study of Atherosclerosis (MESA). J Hum Hypertens. 2011;25:73-9. [PMID: 20944659]
87. Lee DH, Ha MH, Kim KY, Jin DG, Jacobs DR Jr. Gamma-glutamyltransferase: an effect modifier in the association between age and hypertension in a 4-year follow-up study. J Hum Hypertens. 2004;18:803-7. [PMID: 15141269]
88. Levine DA, Lewis CE, Williams OD, Safford MM, Liu K, Calhoun DA, et al. Geographic and demographic variability in 20-year hypertension incidence: the CARDIA study. Hypertension. 2011;57:39-47. [PMID: 21135358]
89. Morikawa Y, Nakagawa H, Miura K, Ishizaki M, Tabata M, Nishijo M, et al. Relationship between shift work and onset of hypertension in a cohort of manual workers. Scand J Work Environ Health. 1999;25:100-4. [PMID: 10360464]
90. Nakanishi N, Suzuki K, Tatara K. Clustering of cardiovascular risk factors and risk of development of hypertension in Japanese male office workers. J Cardiovasc Risk. 2003;10:213-20. [PMID: 12775955]
91. Vasan RS, Larson MG, Leip EP, Kannel WB, Levy D. Assessment of frequency of progression to hypertension in non-hypertensive participants in the Framingham Heart Study: a cohort study. Lancet. 2001;358:1682-6. [PMID: 11728544]
92. Jung DH, Kim JY, Kim JK, Koh SB, Park JK, Ahn SV. Relative contribution of obesity and serum adiponectin to the development of hypertension. Diabetes Res Clin Pract. 2014;103:51-6. [PMID: 24398319
93. Völzke H, Fung G, Ittermann T, Yu S, Baumeister SE, Dörr M, et al. A new, accurate predictive model for incident hypertension. J Hypertens. 2013;31:2142-50. [PMID: 24077244]
94. Yamada Y, Ishizaki M, Kido T, Honda R, Tsuritani I, Ikai E, et al. Alcohol, high blood pressure, and serum gamma-glutamyl transpeptidase level. Hypertension. 1991;18:819-26. [PMID: 1683858]
95. Yambe M, Tomiyama H, Yamada J, Koji Y, Motobe K, Shiina K, et al. Arterial stiffness and progression to hypertension in Japanese male subjects with high normal blood pressure. J Hypertens. 2007;25:87-93. [PMID: 17143178]
96. Klein R, Klein BE, Moss SE, Wong TY. The relationship of retinopathy in persons without diabetes to the 15-year incidence of diabetes and hypertension: Beaver Dam Eye Study. Trans Am Ophthalmol Soc. 2006;104:98-107. [PMID: 17471330]
97. Apostolides AY, Cutter G, Daugherty SA, Detels R, Kraus J, Wassertheil-Smoller S, et al. Three-year incidence of hypertension in thirteen U.S. communities. Prev Med. 1982;11:487-99. [PMID: 7156059]
98. Arima H, Kiyohara Y, Kato I, Tanizaki Y, Kubo M, Iwamoto H, et al. Alcohol reduces insulin-hypertension relationship in a general population: the Hisayama study. J Clin Epidemiol. 2002;55:863-9. [PMID: 12393073]
99. Bakx JC, Seidell JC, Deurenberg P, van den Hoogen HJ. Development of hypertension in obese subjects seen in general practice. Fam Pract. 1987;4:11-8. [PMID: 3569720]
100. Boyko EJ, Barr EL, Zimmet PZ, Shaw JE. Two-hour glucose predicts the development of hypertension over 5 years: the AusDiab study. J Hum Hypertens. 2008;22:168-76. [PMID: 18046430]
101. Cacciolati C, Hanon O, Dufouil C, Alpérovitch A, Tzourio C. Categories of hypertension in the elderly and their 1-year evolution. The Three-City Study. J Hypertens. 2013;31:680-9. [PMID: 23412428]
102. Cheung BM, Ong KL, Tso AW, Leung RY, Xu A, Cherny SS, et al. C-reactive protein as a predictor of hypertension in the Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS) cohort. J Hum Hypertens. 2012;26:108-16. [PMID: 21270838]
103. Dernellis J, Panaretou M. Aortic stiffness is an independent predictor of progression to hypertension in nonhypertensive subjects. Hypertension. 2005;45:426-31. [PMID: 15710784]
104. Fagot-Campagna A, Balkau B, Simon D, Ducimetière P, Eschwège E. Is insulin an independent risk factor for hypertension? The Paris Prospective Study. Int J Epidemiol. 1997;26:542-50. [PMID: 9222779]
105. Fitchett G, Powell LH. Daily spiritual experiences, systolic blood pressure, and hypertension among midlife women in SWAN. Ann Behav Med. 2009;37:257-67. [PMID: 19662465]
106. Giubertoni E, Bertelli L, Bartolacelli Y, Origliani G, Modena MG. Parity as predictor of early hypertension during menopausal transition. J Hypertens. 2013;31:501-7. [PMID: 23196900]
107. Kim SJ, Lee J, Nam CM, Jee SH, Park IS, Lee KJ, et al. Progression rate from new-onset pre-hypertension to hypertension in Korean adults. Circ J. 2011;75:135-40. [PMID: 21099126]
108. Kivimäki M, Batty GD, Singh-Manoux A, Ferrie JE, Tabak AG, Jokela M, et al. Validating the Framingham Hypertension Risk Score: results from the Whitehall II study. Hypertension. 2009;54:496-501. [PMID: 19597041]
109. Lee JH, Yang DH, Park HS, Cho Y, Jun JE, Park WH, et al; Hypertension-Diabetes Daegu Initiative Study Investigators. Incidence of hypertension in Korea: 5-year follow-up study. J Korean Med Sci. 2011;26:1286-92. [PMID: 22022179]
110. Lee JS, Kawakubo K, Kashihara H, Mori K. Effect of long-term body weight change on the incidence of hypertension in Japanese men and women. Int J Obes Relat Metab Disord. 2004;28:391-5. [PMID: 14724660]
111. Matsuo T, Sairenchi T, Suzuki K, Tanaka K, Muto T. Long-term stable obesity increases risk of hypertension. Int J Obes (Lond). 2011;35:1056-62. [PMID: 21042324]
112. Okubo Y, Suwazono Y, Kobayashi E, Nogawa K. An association between smoking habits and blood pressure in normotensive Japanese men: a 5-year follow-up study. Drug Alcohol Depend. 2004;73:167-74. [PMID: 14725956]
113. Satoh H, Saijo Y, Kishi R, Tsutsui H. Brachial-ankle pulse wave velocity is an independent predictor of incident hypertension in Japanese normotensive male subjects. Environ Health Prev Med. 2011;16:217-23. [PMID: 21431793]
114. Schulz M, Liese AD, Boeing H, Cunningham JE, Moore CG, Kroke A. Associations of short-term weight changes and weight cycling with incidence of essential hypertension in the EPIC-Potsdam Study. J Hum Hypertens. 2005;19:61-7. [PMID: 15343355]
115. Shook RP, Lee DC, Sui X, Prasad V, Hooker SP, Church TS, et al. Cardiorespiratory fitness reduces the risk of incident hypertension associated with a parental history of hypertension. Hypertension. 2012;59:1220-4. [PMID: 22585947]
116. Tozawa M, Iseki K, Iseki C, Oshiro S, Higashiuesato Y, Ikemiya Y, et al. Impact of multiple risk factor clustering on the elevation of blood pressure. Hypertens Res. 2002;25:811-6. [PMID: 12484502]
117. Sung KC, Wild SH, Byrne CD. Development of new fatty liver, or resolution of existing fatty liver, over five years of follow-up, and risk of incident hypertension. J Hepatol. 2014;60:1040-5. [PMID: 24445219]
118. Kubo T, Fujino Y, Nakamura T, Kunimoto M, Tabata H, Tsuchiya T, et al. An industry-based cohort study of the association between weight gain and hypertension risk among rotating shift workers. J Occup Environ Med. 2013;55:1041-5. [PMID: 23969502]
119. Okubo Y, Sairenchi T, Irie F, Yamagishi K, Iso H, Watanabe H, et al. Association of alcohol consumption with incident hypertension among middle-aged and older Japanese population: the Ibarakai Prefectural Health Study (IPHS). Hypertension. 2014;63:41-7. [PMID: 24126168]
120. Zambrana RE, López L, Dinwiddie GY, Ray RM, Phillips LS, Trevisan M, et al. Prevalence and incident prehypertension and hypertension in postmenopausal Hispanic women: results from the Women's Health Initiative. Am J Hypertens. 2014;27:372-81. [PMID: 24480867]
121. Mourad A, Carney S, Gillies A, Jones B, Nanra R, Trevillian P. Arm position and blood pressure: a risk factor for hypertension? J Hum Hypertens. 2003;17:389-95. [PMID: 12764401]
122. Widener J, Yang C, Costello P, Allen K. Modifications to standard guidelines and changes in blood pressure readings: use of an automatic blood pressure device. AAOHN J. 1999;47:107-13. [PMID: 10347396]
123. Terént A, Breig-Asberg E. Epidemiological perspective of body position and arm level in blood pressure measurement. Blood Press. 1994;3:156-63. [PMID: 8069403]
124. Aylett M, Marples G, Jones K, Rhodes D. Evaluation of normal and large sphygmomanometer cuffs using the Omron 705CP. J Hum Hypertens. 2001;15:131-4. [PMID: 11317193]
125. Guagnano MT, Pace-Palitti V, Murri R, Marchione L, Merlitti D, Sensi S. The prevalence of hypertension in gynaecoid and android obese women. J Hum Hypertens. 1996;10:619-24. [PMID: 8953208]
126. Bakx C, Oerlemans G, van den Hoogen H, van Weel C, Thien T. The influence of cuff size on blood pressure measurement. J Hum Hypertens. 1997;11:439-45. [PMID: 9283061]
127. Zheng D, Amoore JN, Mieke S, Murray A. How important is the recommended slow cuff pressure deflation rate for blood pressure measurement? Ann Biomed Eng. 2011;39:2584-91. [PMID: 21735319]
128. Kahan E, Yaphe J, Knaani-Levinz H, Weingarten MA. Comparison of blood pressure measurements on the bare arm, below a rolled-up sleeve, or over a sleeve. Fam Pract. 2003;20:730-2. [PMID: 14701900]
129. Holleman DR Jr, Westman EC, McCrory DC, Simel DL. The effect of sleeved arms on oscillometric blood pressure measurement. J Gen Intern Med. 1993;8:325-6. [PMID: 8320577]
130. Lewington S, Clarke R, Qizilbash N, Peto R, Collins R; Prospective Studies Collaboration. Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. Lancet. 2002;360:1903-13. [PMID: 12493255]
131. National Clinical Guideline Centre (UK). Hypertension: The Clinical Management of Primary Hypertension in Adults: Update of Clinical Guidelines 18 and 34. London: National Institute for Health and Clinical Excellence; 2011. [PMID: 22855971]
132. Roush R, Fagard R, Salles G, Pierdomenico S, Reboldi G, Verdecchia P, et al. Prognostic impact of clinic, daytime, and nighttime systolic blood pressure in 9 cohorts of 13,843 patients with hypertension: systematic review and meta-analysis. J Am Soc Hypertens. 2014;8:e59.
133. Hansen TW, Li Y, Boggia J, Thijs L, Richart T, Staessen JA. Predictive role of the nighttime blood pressure. Hypertension. 2011;57:3-10. [PMID: 21079049]
134. Pierdomenico SD, Cuccurullo F. Prognostic value of white-coat and masked hypertension diagnosed by ambulatory monitoring in initially untreated subjects: an updated meta analysis. Am J Hypertens. 2011;24:52-8. [PMID: 20847724]
|Key Question||Studies, n||Overall
|Limitation||Consistency||Primary Care Applicability||Summary of Findings|
|1 (screening and cardiovascular disease and mortality)||1||Good||Evidence limited to results from 1 good-quality study||NA: 1 study||Moderate: appropriate to an elderly primary care population; screening program evaluated in the context of a universal payer||A cluster RCT (39 clusters; n = 140,642) of a BP screening program in Ontario, Canada, targeted to persons aged ≥65 y reported a statistically significant 9% relative reduction in the number of composite cardiovascular events (rate ratio, 0.91 [95% CI, 0.86 to 0.97]; P = 0.002). The intervention group had 3.02 fewer annual hospitalizations for CVD per 1000 persons than the control group. When data were analyzed by the number of unique patients hospitalized, there was a significant relative reduction only in the individual outcome of acute MI.|
|2 (diagnostic accuracy of clinic-based BP measurement methods)||4||Fair to good||Differences in study design; clinically unrealistic design in 1 study; use of different automated devices in 1 study without attempt to ensure comparability or validity||Inconsistent: sensitivity differs greatly in 1 study||High: 3 of 4 studies used clinically applicable protocols to measure the diagnostic accuracy of automated oscillometric BP devices||1 unique study that probably minimized human error more than is possible in the typical clinical setting compared manual BP measurement by sphygmomanometry (reference standard) with automated oscillometric measurement and reported a sensitivity of 91%, specificity of 96%, PPV of 88%, and NPV of 97%. 3 studies of similar comparisons but with more clinically applicable study designs reported lower sensitivities (51% to 68%) and PPVs (76% to 84%).|
|2 (diagnostic accuracy of protocol characteristic)||3||Fair to good||Different protocol characteristics addressed; populations not uniformly representative of screening populations; in 1 study, a carefully controlled protocol may limit applicability||NA: each study evaluated a different component of BP measurement||Moderate: studies addressed basic questions about BP measurement methods||1 study showed that the first of 3 BP measurements had a high sensitivity (95%) but a moderate PPV (76%) for detecting hypertension compared with the average of the second and third measurements, suggesting that the primary value of repeated measurements is in confirming initially elevated BP. In a study of normotensive persons, different leg positions, including leg crossing, did not result in reclassification to hypertensive. When BP was measured after double-blind administration of oral caffeine, 17% of persons who ingested caffeine were reclassified from normotensive to hypertensive.|
|3 (prediction of events)||15||Fair to good||No study populations based in the United States; limited data for HBPM; only 1 study compared all 3 methods||High||High: ABPM independently predicted cardiovascular outcomes compared with OBPM and can be considered the reference method for BP measurement||24-h ABPM predicted stroke and other cardiovascular fatal and nonfatal events significantly and independently of OBPM. When both were in the model, OBPM added no significant predictive capacity. Results were inconsistently significant for cardiac events, CHF, and all-cause mortality. The pattern of results was similar for nighttime and daytime ABPM compared with OBPM; no single ABPM protocol seemed best. The results of 5 studies suggested that HBPM predicts cardiovascular outcomes significantly and independently of OBPM, but too few studies are available for firm conclusions. Only 1 study compared ABPM with HBPM; the evidence was insufficient for conclusions. Limited evidence suggested that cardiovascular outcomes for the subgroup with isolated clinic hypertension at baseline were more similar to those of normotensive persons than to those of patients with sustained hypertension.|
|3 (diagnostic accuracy to confirm diagnosis)||27||Fair to good||Factors influencing variability in the proportion of persons with isolated clinic hypertension were not apparent||Limited||High: persons with unconfirmed false-positive results by OBPM (isolated clinic hypertension) could be misdiagnosed and unnecessarily treated||Initial screening by office-based methods variably predicted true hypertension, defined primarily by ABPM; the proportion of persons with an elevated BP on screening who were normotensive on confirmatory testing by ABPM or HBPM ranged from 5% to 65% across all studies; this population had isolated clinic hypertension.|
|3 (diagnostic accuracy to confirm diagnosis in subpopulations)||27||Fair to good||Factors influencing variability in the proportion of persons with isolated clinic hypertension were not apparent||Limited||High: persons with unconfirmed false-positive results by OBPM (isolated clinic hypertension) could be misdiagnosed and unnecessarily treated; no additional subpopulations identified by the available data;confirmation near threshold for hypertension most important||The subpopulation of persons with isolated clinic hypertension was identified in key question 3b. No associations among reported race/ethnicity, sex, or smoking were qualitatively detected. Increasing baseline BP was associated with increasing PPV (i.e., lower likelihood of misdiagnosis).|
|4 (shortest rescreening interval)||39||Fair to good||Only 1 study reported rescreening incidence at <1 y, and most reported it at 5 y; most studies done in Asia||Moderate||High: rescreening without confirmation may result in overestimation of hypertension incidence and misdiagnosis||In a few studies that used a separate confirmation step, a significant proportion of cases of incident hypertension were not confirmed. Thus, estimates of the weighted mean incidence of hypertension at yearly intervals >6 y derived from a few studies (except at 5 y) with highly variable results are probably overestimates because most studies did not include a confirmation step. For example, the weighted mean incidence of 14% at 5 y actually ranged from 2% to 28%. Variation resulted from criteria for diagnosis and from study population characteristics.|
|4 (shortest rescreening interval by patient characteristic)||39||Fair to good||Only 1 study reported rescreening incidence at <1 y, and most reported it at 5 y; most studies done in Asia; limited subgroup reporting||Moderate||High: higher incidence of hypertension was seen in persons with high-normal BP, older persons, those with an above-normal BMI, and African Americans; much lower incidence was seen in those without risk factors||Hypertension incidence increased as much as 2- to 4-fold between the age categories of 18 to 40 or 45 y and 40 or 45 to 60 or 65 y. Hypertension incidence consistently tripled between optimal and normal BP categories in each study and approximately doubled between normal and high-normal categories. Incidence was generally higher in men than women, especially in younger populations. Incidence was 2- and 3-fold higher in overweight and obese persons, respectively, than in normal-weight persons but did not increase in smokers compared with nonsmokers or former smokers. Black persons had a consistently higher incidence of hypertension at rescreening than white persons.|
|5 (adverse effects)||9||Fair to good||Different study designs and outcomes assessed; difficult to compare results across studies||NA: studies addressed different outcomes||Moderate: sleep disturbance and physical discomfort are associated with ABPM use||3 trials found no significant differences in psychological distress or quality of life after persons were labeled as hypertensive or prehypertensive. 1 trial reported significantly decreased mood, general physical state, sexual functioning, and sleep quality after labeling. 1 cohort study reported significantly increased absenteeism from work ≤4 y after labeling compared with the preceding year. 3 cohort studies reported significant sleep disturbances associated with ABPM use, and 2 studies reported that significant proportions of ABPM users had pain, skin irritation, and overall discomfort.|
ABPM = ambulatory blood pressure monitoring; BMI = body mass index; BP = blood pressure; CHF = congestive heart failure; CVD = cardiovascular disease; HBPM = home blood pressure monitoring; MI = myocardial infarction; NA = not applicable; NPV = negative predictive value; OBPM = office blood pressure measurement; PPV = positive predictive value; RCT = randomized, controlled trial.
Results of included studies for key question 3a. Weights are from random-effects analysis. ABPM = ambulatory blood pressure monitoring; CV = cardiovascular; HF = heart failure; HR = hazard ratio; MI = myocardial infarction; OBPM = office blood pressure measurement.
Figure 1 displays a forest plot of the hazard ratios of the risk for cardiovascular and mortality outcomes among studies that reported systolic 24-hour ambulatory blood pressure monitoring, adjusted for office blood pressure measurement.
Results of included studies for key question 3b. ABPM = ambulatory blood pressure monitoring; HBPM = home blood pressure monitoring; OBPM = office blood pressure measurement; PPV = positive predictive value.
Figure 2 plots the proportion (or positive predictive value) of elevated blood pressure screening results that are confirmed hypertensive by ambulatory or home blood pressure monitoring.
Results of included studies for key question 4a. The size of the symbol represents the number of participants in the study. HTN = hypertension.
Figure 3 is a scatterplot of hypertension incidence by rescreening interval differentiating between persons who are confirmed hypertensive with a second measurement or not; those with longer followup have higher incidence rates.
|Study, Year (Reference)||Quality||Mean Age (Range), y||Diagnostic Threshold||Mean Baseline Office BP, mm Hg||Rescreening Interval, y||Baseline BMI|
|18.5–24.9 kg/m2||25.0–29.9 kg/m2||>30.0 kg/m2|
|n||Unadjusted Incidence||n||Unadjusted Incidence||n||Unadjusted Incidence|
|Radi et al, 200453†||Fair||NR||≥140/90 mm Hg||NR||1||11,751||1.5%||4674||3.9%||1040||7.6%|
|Matsuo et al, 2011111||Fair||41.2 (30.0–59.0)||≥140/90 mm Hg or use of antihypertensive medications||121.8/73.8||3||3251||13.8%||1456||24.9%||138||32.6%|
BMI = body mass index; BP = blood pressure; NR = not reported.
* Results of studies included for key question 4b, sorted by rescreening interval. Baseline characteristics are reported for the overall study population and are not further stratified by subgroup. All studies were done in the United States.
† Measure based on >1 visit or involved an additional confirmation step.
|Study, Year (Reference)||Quality||Mean Age (Range), y||Diagnostic Threshold||Mean Baseline Office BP, mm Hg||Rescreening Interval, y||Asian||White||African American||Hispanic|
|n||Unadjusted Incidence, %||n||Unadjusted Incidence, %||n||Unadjusted Incidence, %||n||Unadjusted Incidence, %|
|Fitchett and Powell, 2009105||Fair||50.0 (42.0–52.0)||BP ≥140/90 mm Hg or use of anti-hypertensive medications||118.4/NR||2||-||-||262||17.9||739||5.7||-||-|
|Levine et al, 201188||Good||25.1 (18.0–30.0)||BP ≥140/90 mm Hg or use of antihypertensive medications||109.5/68.1||2||-||-||1582||1.8||1854||0.8||-||-|
|Juhaeri et al, 200284||Good||53.4 (46.0–65.0)||BP ≥140/90 mm Hg or use of antihypertensive medications||113.6/70.0||3||-||-||1567||16.4||7752||9.2||-||-|
|Apostolides et al, 198297||Fair||NR (30.0–69.0)||DBP >95 mm Hg or use of antihypertensive medications||NR||3||-||-||1222||24.5||1516||7.1||-||-|
|Levine et al, 201188||Good||25.1 (18.0–30.0)||BP ≥140/90 mm Hg or use of antihypertensive medications||109.5/68.1||5||-||-||1582||4.7||1854||2.0||-||-|
|Lakoski et al, 201186||Good||59.0 (45.0–84.0)||BP ≥140/90 mm Hg or history of hypertension and use of antihypertensive medications||NR||5||470||16.2||713||27.5||1552||17.5||808||21.2|
BP = blood pressure; DBP = diastolic blood pressure; NR = not reported.
* Results of studies included for key question 4b, sorted by rescreening interval. Baseline characteristics are reported for the overall study population and are not further stratified by subgroup. All studies were done in the United States.
1. Does screening for high blood pressure reduce cardiovascular disease and mortality in adults aged 18 years or older?
2. What is the best way to screen for high blood pressure in adults in the primary care setting?
a. How accurate (i.e., sensitivity, specificity, and predictive value) are clinic-based blood pressure measurement methods (e.g., manual vs. automated) in provisionally diagnosing hypertension within a single visit?
b. What screening protocol characteristics within a single encounter (e.g., sitting quietly for 5 minutes or number of readings) define the best diagnostic accuracy?
3. What is the best way to confirm hypertension in adults who initially screen positive for high blood pressure?
a. How well do home and ambulatory blood pressure monitoring methods predict cardiovascular events compared with clinic-based blood pressure measurement methods? What confirmation protocol characteristics define the best prediction of cardiovascular events? Which methods and associated protocols best predict cardiovascular events?
b. How accurate are other noninvasive blood pressure measurement methods in establishing or confirming the diagnosis of hypertension compared with these best methods and associated protocols? Does diagnostic accuracy vary by protocol characteristics (i.e., characteristics not reviewed in key question 2b, such as the number of visits)?
c. Does changing the measurement method from that used during the initial screening improve diagnostic accuracy for some specific patient subgroups (e.g., those with suspected white coat hypertension)?
4. What is the clinically appropriate rescreening interval for patients who have previously been screened and found to have normal blood pressure?
a. What is the shortest interval in which clinically significant, diagnosed hypertension may develop?
b. Does the rescreening interval vary by patient characteristics (e.g., age, sex, race/ethnicity, cardiovascular risk, blood pressure, or screening history)?
5. What are the adverse effects of screening for high blood pressure in adults?
ABPM = ambulatory blood pressure monitoring; BP = blood pressure; CHD = coronary heart disease; CVD = cardiovascular disease; ESKD = end-stage kidney disease; HBPM = home blood pressure monitoring; HF = heart failure.
* Defined as the threshold for pharmacologic treatment.
Appendix Figure 1 is an analytic framework that depicts the five key questions of the systematic evidence review. In general, it illustrates the overarching question of whether screening for high blood pressure in adults leads to improved health outcomes or potential harms. It also illustrates the intermediate steps and key questions related to methods and protocols for the initial screening encounter that identifies individuals with elevated blood pressure, methods and protocols for confirmation (or no confirmation) of the diagnosis of hypertension at a subsequent encounter, and treatment of identified hypertensive patients, leading to improved outcomes. It also identifies an interval after which individuals with normal blood pressure levels would be rescreened.
KQ = key question.
* Surveillance search results through August 2014 for trials reporting direct benefits of screening were not included; no additional trials were identified.
Appendix Figure 2 is a flow chart that summarizes the search and selection of articles. There were 28,816 citations identified through literature databases. An additional 94 citations were identified from outside sources, such as reference lists and suggestions from peer reviewers. After duplicates were removed, 19,309 unique citations were screened at the title/abstract stage. The full-text of 1,171 citations were examined for inclusion for one or more of the five key questions.
|Study, Year (Reference)||Device||Measurement Period||Time Between Measurements, min||Maximum Measurements, n||Office BP Measurements, n||Method of Office BP Determination|
|Celis et al, 200240||Spacelabs 90207 and 90239A||Day: 10:00 a.m. to 8:00 p.m.||15||40||6||Mean of 6 readings*|
|Clement et al, 200334||NR||24 h
Day: 8:00 a.m. to 8:00 p.m.
Night: midnight to 6:00 a.m.
|30 (8:00 a.m. to 8:00 p.m.); 60 (8:00 p.m. to 8:00 a.m.)
|Mean of 3 measurements|
|Dolan et al, 200541||Spacelabs 90202 or 90207||24 h
Day: 9:00 a.m. to 9:00 p.m.
Night: 1:00 to 6:00 a.m.
|Mean of 3 measurements|
|Fagard et al, 200535||Spacelabs 90202 or 90207||Day: 10:00 a.m. to 8:00 p.m.
Night: midnight to 6:00 a.m.
|Mean of 3 measurements|
|Gasowski et al, 200843||Spacelabs 90207||24 h||20 (8:00 a.m. to 10:00 p.m.); 45 (midnight to 6:00 a.m.)||50||5||Mean of 5 measurements|
|Hansen et al, 200542||Takeda TM-2421||24 h
Day: determined by diaries (defined as 6:00 a.m. to midnight if diaries were inadequate)
Night: determined by diaries (defined as midnight to 6:00 a.m. if diaries were inadequate)
|15 (7:00 a.m. to 11:00 p.m.); 30 (11:00 p.m. to 7:00 a.m.)
15 (7:00 a.m. to 11:00 p.m.)
30 (11:00 p.m. to 7:00 a.m.)
|Mean of 2 measurements|
|Hermida et al, 201136||Spacelabs 90207||48 h
Day: determined by diaries and actigraphy
Night: determined by diaries and actigraphy
|20 (7:00 a.m. to 11:00 p.m.); 30 (night†)
20 (7:00 a.m. to 11:00 p.m.)
|Ingelsson et al, 200637||Accutracker II (SunTech Medical)||24 h
Day: 10:00 a.m. to 8:00 p.m.
Night: midnight to 6:00 a.m.
|20 or 30 (6:00 a.m. to 11:00 p.m.); 20 or 60 (11:00 p.m. to 6:00 a.m.)
20 or 30
20 or 60
|41 or 72
|Mean of 2 measurements‡|
|Mesquita-Bastos et al, 201044||Spacelabs 90207||24 h
Day: 7:00 a.m. to 11:00 p.m.
Night: 11:30 p.m. to 6:30 a.m.
|20 (7:00 a.m. to 11:00 p.m.); 30 (11:30 p.m. to 6:30 a.m.)
|Mean of last 2 of 3 measurements§|
|Ohkubo et al, 200538||ABPM-630 (Nippon Colin)||24 h
Day: estimated from diaries
Night: estimated from diaries
|Mean of 2 measurements|
|Staessen et al, 199939||Spacelabs 90202 or 90207||24 h
Day: 10:00 a.m. to 8:00 p.m.
Night: midnight to 6:00 a.m.
|Mean of 6 measurementsǁ|
ABPM = ambulatory blood pressure monitoring; BP = blood pressure; NR = not reported.
* 3 measurements at each of 2 visits.
† Assumed to be 11:00 p.m. to 7:00 a.m.
‡ Rounded to nearest 2 mm Hg.
§ Clinic BP recorded at 2 visits; unclear whether reading from first, second, or both visits was used to determine BP.
ǁ 2 measurements at each of 3 visits.
Results of included studies for key question 3a. Weights are from random-effects analysis. CV = cardiovascular; HBPM = home blood pressure monitoring; HR = hazard ratio; MI = myocardial infarction; OBPM = office blood pressure measurement; TIA = transient ischemic attack.
Appendix Figure 3 displays a forest plot of the hazard ratios of the risk for cardiovascular and mortality outcomes among studies that reported systolic home blood pressure monitoring, adjusted for office blood pressure measurement.
|Subgroup||1 y||2 y||3 y||4 y||5 y|
|18 to 40 or 45 y||1†||9617||1.0||1||3436||1.2||-||-||-||1||7797||1.8||3||4568||4.1 (3.2–17.8)|
|40 or 45 to 60 or 65 y||1†||5805||4.0||1||1001||8.9||2||13,468||14.9 (10.4–24.9)||2||989||15.3 (6.7–20.4)||3||3052||7.1 (3.1–23.7)|
|≥60 or 65 y||1||275||4.4||-||-||-||-||-||-||2||2858||37.5 (35.4–40.3)||1||204||37.7|
|High-normal||-||-||-||2||5000||27.7 (26.7–31.3)||3||3323||26.7 (21.0–30.4)||2||4736||50.3 (42.8–58.0)||2||1544||46.4 (32.7–52.2)|
|Normal||-||-||-||2||50,117||7.7 (7.6–7.8)||3||4318||7.0 (4.4–9.0)||1||7443||11.8||2||2970||18.6 (16.6–18.8)|
|Male||1†||9691||3.4||4||40,519||10.6 (1.8–13.0)||7||19,447||15.4 (6.6–24.9)||5||49,283‡||34.6 (2.1–43.3)||14||31,153||13.0 (2.1–28.4)|
|Female||1†||7774||1.5||5||23,872||6.0 (0.9–11.6)||5||19,308||7.8 (1.4–19.8)||3||82,386‡||36.0 (8.7–37.3)||11||17,533||11.2 (2.5–28.8)|
|18.5 to <25.0 kg/m2||1||11,751||1.5||1||3351||5.5||1||3521||13.8||-||-||-||-||-||-|
|≥25.0 to 29.9 kg/m2||1||4674||3.9||-||-||-||1||1456||24.9||-||-||-||-||-||-|
|Current||1||5845||2.8||1||1457||5.4||1||1164||5.8||2||7194||3.4 (1.8–8.3)||6||5288||10.6 (3.0–22.0)|
|1||11,620||2.4||1||3400||8.3||1||1114||7.5||2||5611||6.0 (2.6–9.3)||6||13,222||15.1 (3.4–21.0)|
BMI = body mass index; BP = blood pressure.
* Results of studies included for key question 4b.
† Incidence based on 2 visits; incidence based on 1 visit also reported but not pooled.53
‡ The study by Okubo and colleagues119 was categorized as having a 4-y interval on the basis of an overall mean follow-up of 3.9 y; mean follow-up was 4.1 y for women and 3.4 y for men. If this study (n = 115,736) was not included in the 4-y interval category, the weighted mean incidence would be 7.3% (range, 2.1% to 35.6%) in 4 studies (n = 11,973) for men and 10.9% (range, 8.7% to 14.8%) in 2 studies (n = 3960) for women.
|Subgroup||Quality||Mean Age (Range), y||Country||Participants, n||Participants
Aged 18 to
40 or 45 y, %
BP, mm Hg
|Unadjusted Incidence, %|
|Aged 18 to 40 or 45 y||Aged 40 or 45 to 60 or 65 y||Aged ≥60 or 65 y|
|Radi et al, 200453||Fair||38.2 (15.0–69.0)||France||17,465||55.1||≥140/90 mm Hg or use of antihypertensive medications||119.5/75.3||44.5||1||1.0†||4.4†‡||NR|
|Lee et al, 200487||Good||38.7 (25.0–50.0)||Korea||8170||95.4||≥160/95 mm Hg||114.9/72.7||0.0||4||1.8||6.7||NA|
|Lee et al, 2011109||Fair||56.6 (≥20)||Korea||730||15.3||≥140/90 mm Hg or use of antihypertensive medications||119.8/75.8||63.7||5||17.9||23.7||37.7|
|Morikawa et al, 199989||Good||34.7 (18.0–49.0)||Japan||1551||65.8||≥140/90 mm Hg||117.7/69.4||0.0||5||5.5||10.0||NA|
BP = blood pressure; NA = not applicable; NR = not reported.
* Results of studies included for key question 4b, sorted by rescreening interval. Baseline characteristics are reported for the overall study population and are not further stratified by the identified subgroup.
† Includes participants aged 40 to 69 y.
‡ Based on >1 visit or involved an additional confirmation step.
|Study, Year (Reference)||Rescreening Interval, y||BP Category†||Cases, n||Participants, n||Unadjusted
|Kim et al, 200685||2||Optimal
|Kim et al, 2011107||2||Optimal
|Yambe et al, 200795||3||Optimal
|Vasan et al, 200191||4||Optimal
|Nakanishi et al, 200390||5||Optimal
BP = blood pressure.
* Results of studies included for key question 4b.
† Optimal: <120/80 mm Hg; normal: 120–129/80–84 mm Hg; high-normal: 130–139/85–89 mm Hg.
|Study, Year (Reference)||Quality||Country||Participants, n||Women, %||Mean Age (Range), y||Diagnostic Threshold||Mean
Office BP, mm Hg
|Unadjusted Incidence, %||Male–Female
|Radi et al, 200453||Fair||France||17,465||44.50||38.2 (15.0–69.0)||≥140/90 mm Hg or use of antihypertensive medications||119.5/75.3||1.0||3.4†||1.5†||2.3|
|Kim et al, 200685||Good||Korea||5869||52.40||50.8 (40.0–69.0)||≥140/90 mm Hg or use of antihypertensive medications||113.1/75.3||2.0||13.0||11.6||1.1|
|Kim et al, 2011107||Fair||Korea||49,228||32.70||37.9 (30.0–54.0)||≥140/90 mm Hg||112.4/72.8||2.0||11.0||5.4||2.0|
|Levine et al, 201188||Good||United States||3436||57.10||25.1 (18.0–30.0)||≥140/90 mm Hg or use of antihypertensive medications||109.5/68.1||2.0||1.8||0.9||2.0|
|Tozawa et al, 2002116||Fair||Japan||4857||36.00||46.0 (NR)||≥140/90 mm Hg||115.0/71.0||2.0||8.0||6.3||1.3|
|Jung et al, 201492||Good||Korea||1553||62.40||53.9 (40.0–70.0)||≥140/90 mm Hg or use of antihypertensive medications||116.9/73.8||2.6||13.5||10.2||1.3|
|Apostolides et al, 198297||Fair||United States||2738||52.70||NR (30.0–69.0)||DBP >95 mm Hg or use of antihypertensive medications||NR||3.0||14.8||15.0||1.0|
|Juhaeri et al, 200284||Good||United States||9319||55.10||53.4 (46.0–65.0)||≥140/90 mm Hg or use of antihypertensive medications||113.6/70.0||3.0||11.6||9.4||1.2|
|Okubo et al, 2014119||Fair||Japan||115,736||67.76||54.5 (40.0–79.0)||≥140/90 mm Hg or use of antihypertensive medications||120.9/73.3||3.9‡||43.3||37.3||1.2|
|Dernellis and Panaretou,
|Fair||Greece||2512||57.30||64.6 (35.0–94.0)||≥140/90 mm Hg||119.8/77.2||4.0||35.6†||14.8†||2.4|
|Brantsma et al, 200682||Good||The Netherlands||4635||54.40||45.2 (28.0–75.0)||≥140/90 mm Hg or use of antihypertensive medications||119.1/69.6||4.2||9.2†||8.7†||1.1|
|Arima et al, 200298||Fair||Japan||1133||64.30||56.0 (40.0–79.0)||≥160/95 mm Hg or use of antihypertensive medications||124.7/74.4||5.0||16.0||16.6||1.0|
|Boyko et al, 2008100||Fair||Australia||4306||57.00||47.6 (≥25.0–NR)||≥140/90 mm Hg or use of antihypertensive medications||120.2/67.0||5.0||15.6||12.7||1.2|
|Klein et al, 200696§||Good||United States||NR||56.80||57.6 (43.0–84.0)||≥140/90 mm Hg or use of antihypertensive medications||119.0/74.0||5.0||19.0||16.6||1.1|
|Lakoski et al, 201186||Good||United States||3543||51.20||59.0 (45.0–84.0)||≥140/90 mm Hg or history of hypertension and use of antihypertensive medications||NR||5.0||19.6||20.7||0.9|
|Lee et al, 2004110||Fair||Japan||5840||41.30||48.6 (30.0–69.0)||≥140/90 mm Hg or history of hypertension and use of antihypertensive medications||110.5/69.8||5.0||11.7†||8.9†||1.3|
|Lee et al, 2011109||Fair||Korea||730||63.70||56.6 (≥20.0–NR)||≥140/90 mm Hg or use of antihypertensive medications||119.8/75.8||5.0||23.0||28.8||0.8|
|Morikawa et al, 199989||Good||Japan||1551||0.0||≥140/90 mm Hg||117.7/69.4||5.0||5.5||10.0|
|Levine et al, 201188||Good||United States||3436||57.10||25.1 (18.0–30.0)||≥140/90 mm Hg or use of antihypertensive medications||109.5/68.1||5.0||4.2||2.5||1.7|
|Sung et al, 2014117||Fair||Korea||11,448||30.64||40.6 (NR)||≥140/90 mm Hg or use of antihypertensive medications||111.4/72.0||5.0||9.7||4.0||2.4|
|Cheung et al, 2012102||Fair||China (Hong
|1115||56.60||48.3 (25.0–74.0)||≥140/90 mm Hg or use of antihypertensive medications||113.9/72.2||5.3||22.5||20.1||1.1|
|Völzke et al, 201393||Good||Germany||1605||63.05||42.9 (20.0–79.0)||≥140/90 mm Hg or use of antihypertensive medications||120.5/76.8||5.3||23.9||17.9||1.3|
|Kivimäki et al, 2009108||Fair||United Kingdom||6055||31.10||44.6 (35.0–55.0)||≥140/90 mm Hg or use of antihypertensive medications||118.9/74.6||5.6||12.6||10.2||1.2|
BP = blood pressure; NA = not applicable; NR = not reported.
* Results of studies included for key question 4b, sorted by rescreening interval. Baseline characteristics are reported for the overall study population and are not further stratified by the identified subgroup.
† Measure based on >1 visit or involved an additional confirmation step.
‡ 3.4 y for men and 4.1 y for women.
§ Not included in Figure 3 because estimated from published figures; number of participants at specified interval not reported.