Research Article

Originally Published 2 September 2014

Age-Specific Differences Between Conventional and Ambulatory Daytime Blood Pressure Values

Hypertension

https://doi.org/10.1161/HYPERTENSIONAHA.114.03957

Abstract

Mean daytime ambulatory blood pressure (BP) values are considered to be lower than conventional BP values, but data on this relation among younger individuals <50 years are scarce. Conventional and 24-hour ambulatory BP were measured in 9550 individuals not taking antihypertensive treatment from 13 population-based cohorts. We compared individual differences between daytime ambulatory and conventional BP according to 10-year age categories. Age-specific prevalences of white coat and masked hypertension were calculated. Among individuals aged 18 to 30, 30 to 40, and 40 to 50 years, mean daytime BP was significantly higher than the corresponding conventional BP (6.0, 5.2, and 4.7 mm Hg for systolic; 2.5, 2.7, and 1.7 mm Hg for diastolic BP; all P<0.0001). In individuals aged 60 to 70 and ≥70 years, conventional BP was significantly higher than daytime ambulatory BP (5.0 and 13.0 mm Hg for systolic; 2.0 and 4.2 mm Hg for diastolic BP; all P<0.0001).The prevalence of white coat hypertension exponentially increased from 2.2% to 19.5% from those aged 18 to 30 years to those aged ≥70 years, with little variation between men and women (8.0% versus 6.1%; P=0.0003). Masked hypertension was more prevalent among men (21.1% versus 11.4%; P<0.0001). The age-specific prevalences of masked hypertension were 18.2%, 27.3%, 27.8%, 20.1%, 13.6%, and 10.2% among men and 9.0%, 9.9%, 12.2%, 11.9%, 14.7%, and 12.1% among women. In conclusion, this large collaborative analysis showed that the relation between daytime ambulatory and conventional BP strongly varies by age. These findings may have implications for diagnosing hypertension and its subtypes in clinical practice.

Introduction

See Editorial Commentary, pp 931–932

Elevated blood pressure (BP) is one of the strongest risk factors for morbidity and mortality worldwide.¹ BP-lowering treatment has been shown to be highly effective in preventing hypertension-related cardiovascular events.² Accordingly, an accurate diagnosis of hypertension is crucial to target treatment to those individuals at high risk for adverse events.

Conventional BP monitoring (CBPM) in the doctor’s office has been the standard of care for many decades, despite the fact that this technique has many potential limitations. Some of these limitations are minimized through the use of 24-hour ambulatory BP monitoring (ABPM). Accordingly, ABPM has been shown to be a better predictor of cardiovascular complications and death than CBPM^3,4 and may help to implement a more efficient BP-lowering treatment regimen.^5,6

ABPM values are usually considered to be lower than conventional BP (CBP) values in the same individual. Accordingly, diagnostic thresholds for hypertension based on 24-hour ABPM are lower than those for CBPM.⁷ However, most studies to determine the association between ABPM and CBPM have been performed in middle-aged to elderly individuals, and it is relatively unknown whether this relation is similar among younger individuals. Usually, younger individuals are more physically active than older individuals, which may directly affect daytime ambulatory BP (ABP) values. Evidence-based thresholds are important in younger adults, given the long-term implications of diagnosing hypertension in this population group. To address this issue, we performed a large collaborative analysis among 9550 participants not taking BP-lowering drugs and representing a wide age range.

Methods

The International Database on Ambulatory blood pressure in relation to Cardiovascular Outcomes (IDACO) was assembled from random population-based studies with available information on CBPM and ABPM, baseline cardiovascular risk factors, and fatal and nonfatal outcomes during follow-up. Details about study selection and aims of the consortium have been described previously.⁸ Currently, the IDACO database contains 12 randomly recruited population cohorts and 12 725 participants. For the purpose of this analysis, we excluded 303 participants aged <18 years, 1389 with missing CBPM, 1878 with incomplete ABPM (<10 valid daytime measurements or <5 valid nighttime measurements),⁸ and 1649 participants currently taking antihypertensive treatment, such that 7506 IDACO participants were included in this study.

To increase the number of individuals aged <40 years, data from the population-based Genetic and Phenotypic Determinants of Blood Pressure and Other Cardiovascular Risk Factors (GAPP) study were added to the IDACO data set. GAPP is an ongoing prospective cohort study among all inhabitants of the Principality of Liechtenstein aged 25 to 41 years. The study methodology has been described in detail previously.⁹ In brief, between 2010 and 2013, 2170 participants have been enrolled into GAPP. Main exclusion criteria are prevalent cardiovascular disease, a body mass index ≥35 kg/m², and current intake of antidiabetic drugs. For the purpose of this study, 2 participants with missing CBPM, 90 participants with incomplete ABPM (<10 valid daytime measurements or <5 valid nighttime measurements; details shown in Table S1 in the online-only Data Supplement), and 34 participants on antihypertensive drug treatment were excluded, leaving 2044 individuals in the GAPP database.

The combined data set for this analysis contained 9550 participants. Written informed consent was obtained from every participant. All responsible local ethics committees approved the corresponding study protocols.

Blood Pressure Monitoring

Details on CBPM and ABPM are provided in the Expanded Methods available in the online-only Data Supplement. In brief, trained observers measured CBPM with validated devices, using the appropriate cuff size, with participants in the sitting position. Observer-measured CBP was the average of 2 consecutive readings obtained either at the persons’ home or at an examination center.

ABPM was obtained by validated automated devices programmed to perform measurements every 15 to 30 minutes during daytime and every 30 to 60 minutes during nighttime. Details on time intervals between readings and numbers of programmed and recorded readings in each cohort are provided in Table S1. Daytime and nighttime BP were defined according to short fixed clock–time periods with daytime and nighttime ranging from 10.00 AM to 8.00 PM and from midnight to 6.00 AM in Europeans and South Americans and from 8.00 AM to 6.00 PM and from 10.00 PM to 4.00 AM in Asians.¹⁰ Sensitivity analyses using a diary-based definition of awake and asleep BP were performed among 7185 participants with this available information.

Normotension was defined as systolic BP <140 mm Hg and diastolic BP <90 mm Hg on CBPM and as daytime systolic BP <135 mm Hg and daytime diastolic BP <85 mm Hg on ABPM. True normotension was defined as normal CBP and normal ABP, white coat hypertension as elevated CBP and normal ABP, masked hypertension as normal CBP and elevated ABP, and sustained hypertension as elevated CBP and elevated ABP.⁷

Other Covariables

Cohort-specific questionnaires were used to obtain information on each participant’s medical history, smoking, and alcohol consumption. With regard to alcohol, participants were dichotomized as nondrinkers versus current drinkers of any amount of alcohol. Body mass index was calculated as body weight in kilograms divided by height in meters squared.

Statistical Methods

Baseline characteristics across age deciles were compared using analysis of variance or Kruskal–Wallis tests for continuous variables, as appropriate, and χ² tests for categorical variables. Within each age category, we calculated mean CBP and daytime ABP and compared the individual BP indices using paired t tests. We assessed whether our findings differed in the subgroup of individuals with hypertension on CBP, who are usually considered for ABPM according to current guidelines.⁷ To exclude an important influence of the device technology used, we repeated our main analyses in 3 cohorts, where oscillometric devices for both CBPM and ABPM were available. We also assessed whether our results were similar in those 6 cohorts where CBPM was obtained in the clinic.

We then assessed whether the age-specific differences between mean daytime ABP and CBP were independent of other baseline characteristics using multivariable linear regression analysis. Sex, age, body mass index, smoking, alcohol consumption, history of diabetes mellitus, history of cardiovascular disease, and ethnicity were prespecified covariables for these models. Because BP measurements within an individual study center may be correlated, study center was included as a random effect variable in these models. Separate models were constructed for systolic and diastolic BP. We used analyses stratified by sex to assess for sex-specific differences of our results, and we formally tested for such differences by using multiplicative interaction tests.

Finally, we calculated the prevalence of true normotension, white coat hypertension, masked hypertension, and sustained hypertension as defined by current guidelines separately within each age category.⁷ A daytime BP–based definition was used in the main analysis, and a sensitivity analysis was performed using a 24-hour BP of 130/80 mm Hg as a threshold for ambulatory hypertension. We performed another sensitivity analysis where we used awake instead of daytime ABP for the definition of BP categories. Prevalences across categories were compared using χ² tests. All analyses were performed using SAS version 9.3 (SAS Institute Inc, Cary, NC). A 2-tailed P value <0.05 was considered to indicate statistical significance.

Results

Baseline characteristics of the 9550 participants stratified by age deciles are shown in Table 1. Across categories of increasing age, there was an increasing number of male participants, an increasing prevalence of diabetes mellitus and cardiovascular disease, and a lower prevalence of white individuals. Alcohol consumption, currently smoking cigarettes, and mean body mass index showed a nonlinear distribution across age categories. By design, none of the participants was taking BP-lowering therapy.

Table 1. Baseline Characteristics Stratified by Age Categories

n=9550	Age Categories, y						P Value
n=9550	18–30	30–40	40–50	50–60	60–70	≥70	P Value
No. of participants	1543	2063	2141	1676	1408	719	…
Age, y	26±3.0	35±2.9	43±2.8	54±3.0	63±2.6	74±4.2	…
Sex (male %)	699 (45.3)	955 (46.3)	1040 (48.6)	787 (47.0)	727 (51.6)	422 (58.7)	<0.0001
BMI, kg/m²	23.3±3.6	24.5±4.0	25.3±4.0	25.8±4.2	25.7±4.2	25.1±4.1	<0.0001
Smoking status (%)							0.002
Former/never	1107 (71.8)	1511 (73.3)	1476 (69.1)	1166 (69.6)	997 (70.9)	542 (75.7)	…
Current	434 (28.2)	550 (26.7)	660 (30.9)	509 (30.4)	410 (29.1)	174 (24.3)	…
Any alcohol intake (%)	720 (46.7)	937 (45.5)	1137 (53.4)	834 (50.6)	753 (54.4)	339 (48.5)	<0.0001
Ethnicity (%)							<0.0001
White	1508 (97.7)	1946 (94.3)	1934 (90.3)	1263 (75.4)	959 (68.1)	491 (68.3)	…
Asians	34 (2.2)	116 (5.6)	207 (9.7)	347 (20.7)	326 (23.2)	120 (16.7)	…
Others	1(0.1)	1 (0.1)	0 (0.0)	66 (3.9)	123 (8.7)	108 (15.0)	…
History of CVD (%)	25 (1.6)	38 (1.8)	35 (1.6)	125 (7.5)	195 (13.9)	144 (20.0)	<0.0001
History of DM (%)	11 (0.7)	20 (1.0)	46 (2.2)	100 (6.0)	138 (9.8)	79 (11.0)	<0.0001
Office hypertension (%)*	112 (7.3)	237 (11.5)	372 (17.4)	498 (29.7)	615 (43.7)	420 (58.4)	<0.0001

Data are mean±SD or number and percentages. BMI indicates body mass index; CVD, cardiovascular disease; and DM, diabetes mellitus.

Office hypertension was defined as conventional systolic blood pressure ≥140 mm Hg or conventional diastolic blood pressure ≥90 mm Hg.

Mean systolic and diastolic CBP increased from 117 to 149 mm Hg and from 74 to 82 mm Hg, respectively, from the youngest to the oldest age category, as shown in Table 2. Daytime systolic ABP values also increased with age, although the absolute increase was smaller when compared with CBP. There was a U-shaped relationship between age categories and daytime diastolic ABP (Table 2). Among individuals aged 50 to 60 years, daytime ABP and CBP were similar (P=0.20 for the difference in systolic BP and P=0.11 for the difference in diastolic BP). Mean systolic and diastolic daytime ABP were significantly higher than the corresponding CBP among individuals <50 years (all P<0.0001). Among individuals aged ≥60 years, this relationship inversed, such that mean CBP values were significantly higher than daytime ABP values in this group (all P<0.0001). This age-dependent difference between daytime ABP and CBP is summarized in Figure 1. Similar results were obtained when individually defined awake BP was used instead of daytime ABP based on short fixed clock–time periods (Figure 2; Table S2). Among 2254 individuals with hypertension on CBP, daytime ABP was significantly lower in all age groups assessed (P<0.0001), except for systolic BP in those aged 18 to 30 years, as shown in Figure S1. Similar to the main results, the difference between CBP and daytime ABP strongly increased with age. In addition, similar BP relationships across age categories were obtained in the 3 cohorts that used only oscillometric devices (n=3625; Table S3) and in the 6 cohorts where CBP was measured in the clinic (n=7229; Table S4).

Table 2. Differences Between Conventional and Ambulatory Daytime Blood Pressures According to Age Categories

Age, y	n	Conventional SBP, mm Hg	Daytime SBP, mm Hg	Conventional DBP, mm Hg	Daytime DBP, mm Hg
18–30	1543	117.0±12.6	123.0±10.9	73.6±9.1	76.1±7.6
30–40	2063	118.6±12.9	123.8±11.3	76.8±9.3	79.5±8.1
40–50	2141	121.5±15.4	126.2±12.7	78.5±10.4	80.2±9.2
50–60	1676	128.6±19.1	129.1±14.1	80.1±11.7	79.8±9.6
60–70	1408	137.3±22.5	132.3±14.7	81.0. ± 11.9	79.0±9.1
≥70	719	148.8±27.9	135.7±15.3	81.6±12.7	77.4±9.7

Data are means±SD. DBP indicates diastolic blood pressure; and SBP, systolic blood pressure.

Figure 1. Differences between conventional and ambulatory daytime blood pressure according to age categories. Data are mean blood pressure differences (Daytime − conventional blood pressure). Error bars indicate standard errors of the mean differences. SBP indicates systolic blood pressure; and DBP, diastolic blood pressure.

Figure 2. Conventional and ambulatory daytime blood pressure according to age categories. Data are shown by age categories (in years) and represent blood pressure in mm Hg. A diary-based definition of awake blood pressure was used, an information available in 7185 participants. CBP indicates conventional blood pressure; and ABP, ambulatory blood pressure.

In multivariable linear regression analyses, age remained a significant predictor for the difference between daytime ABP and CBP. The β estimates (95% confidence interval) per 1-year increase in age were 0.31 (0.29, 0.33; P<0.0001) for systolic BP and 0.09 (0.08, 0.11; P<0.0001) for diastolic BP.

Although men had higher BP values than women across all BP types and age groups, the age-dependent relationship between daytime ABP and CBP was similar for both men and women, as shown in Table 3 and Figures S2 and S3. Accordingly, multiplicative age by sex interaction tests in the multivariable regression models were not statistically significant for either systolic (P=0.16) or diastolic (P=0.06) BP.

Table 3. Conventional and Ambulatory Daytime Blood Pressures According to Age and Sex Categories

Age, y	Sex	n	Conventional SBP, mm Hg	Daytime SBP, mm Hg	Conventional DBP, mm Hg	Daytime DBP, mm Hg
18–30	Women	844	111.6±10.8	118.6±9.3	71.9±8.3	75.2±7.3
18–30	Men	699	123.5±11.5	128.3±10.4	75.7±9.5	77.2±7.8
30–40	Women	1108	113.4±11.3	118.8±9.3	74.1±8.6	77.1±7.4
30–40	Men	955	124.7±12.0	129.5±10.7	80.1±9.1	82.3±8.1
40–50	Women	1101	117.0±14.5	121.5±11.3	75.6±9.8	77.0±8.3
40–50	Men	1040	126.3±14.9	131.0±12.2	81.6±10.2	83.5±9.0
50–60	Women	889	126.6±19.5	126.6±13.7	78.1±11.8	77.5±9.4
50–60	Men	787	130.9±18.5	132.0±13.9	82.4±11.2	82.3±9.2
60–70	Women	681	134.6±21.9	130.9±14.6	79.6±12.1	77.6±8.8
60–70	Men	727	139.8±22.9	133.6±14.7	82.3±11.6	80.4±9.2
≥70	Women	297	145.9±26.2	134.4±15.1	81.0±13.2	76.1±10.0
≥70	Men	422	150.8±29.0	136.7±15.3	82.1±12.4	78.3±9.4

Data are means±SD. DBP indicates diastolic blood pressure; and SBP, systolic blood pressure.

The prevalence of true normotension across increasing age categories was 79.6%, 70.5%, 62.9%, 54.5%, 42.2%, and 30.6% (P<0.0001). The prevalence of sustained hypertension, white coat hypertension, and masked hypertension stratified by age categories is shown in Figure S4. Sustained hypertension exponentially increased across increasing age groups from 5.1% in the youngest age group to 38.9% in those aged ≥70 years (P<0.0001). A similar relationship with age was found for white coat hypertension, which was observed in 2.2% of participants aged 18 to 30 years and 19.5% of those aged ≥70 years (P<0.0001). In contrast, the prevalence of masked hypertension showed an inverse U-shaped relationship with age. Although masked hypertension was less common in the youngest and oldest age groups (13.2% and 11.0%, respectively), it was more prevalent among those aged 30 to 50 years (18.0% and 19.8%; Figure S4). Similar results were obtained when ambulatory hypertension was defined according to 24-hour instead of daytime BP levels (Figure S5) or when awake BP was used instead of daytime ABP based on short fixed clock–time periods (Figure S6).

The overall prevalence of white coat hypertension was slightly higher in men than in women (8.0% versus 6.1%; P=0.0003), but showed a similar relationship with age in both sexes (Figure 3). Masked hypertension was more prevalent in men than in women (21.1% versus 11.4%; P<0.0001). In addition, the distribution across age categories markedly differed between men and women (Figure 3). Although in women, the prevalence of masked hypertension gradually increased from 9.0% in the youngest age category to 14.7% among those aged 60 to 70 years, there was an inverse U-shaped association among men, with the highest prevalence among men aged between 30 and 50 years (27.3% and 27.8%, respectively). The prevalence of sustained hypertension was higher in men than in women across all age groups (22.1% versus 11.3%; P<0.0001), with a similar distribution across age categories in both sexes (Figure 3).

Figure 3. Prevalence of white coat, masked, and sustained hypertension according to age and sex categories. P values given are based on a χ² test comparing the age-specific prevalences between men and women. White coat hypertension was defined as elevated conventional blood pressure (BP) and normal ambulatory BP, masked hypertension was defined as normal conventional BP and elevated ambulatory BP, sustained hypertension was defined as elevated conventional BP and elevated ambulatory BP. Numbers indicate prevalences.

Discussion

In this large collaborative study of 13 population-based cohorts, we found that the difference between daytime ABP and CBP markedly differs according to age. Although CBP was significantly higher than daytime ABP among those aged ≥60 years, as has been described in many earlier studies, this association was inverse among individuals <50 years. Our results were robust to sensitivity analyses where different definitions of ambulatory hypertension were used. The inverse relationship in younger individuals has received little attention previously,^11–13 and most available studies mainly focused on the direct relationship between age and the white coat response.^14,15 As in our work, these studies found that the white coat response increases with increasing age and that it was stronger among individuals with office hypertension. Some earlier studies found a higher prevalence of white coat hypertension among women.¹⁶ The differential findings in our study may be explained by the high number of younger individuals assessed (Figure 3).

CBPM is usually performed in a relatively standardized setting in the physician’s office, whereas daytime ABPM is obtained in the unstandardized individual real-life environment. As physical activity declines with increasing age,¹⁷ less exercise and a more sedentary behavior during ABPM may be one reason why daytime ABP is relatively higher than CBP in younger compared with older individuals. Furthermore, the observed age-dependent differences may also be partly explained by the fact that many individuals aged <60 years are part of the active workforce and many of the individuals aged ≥60 years are retired. This hypothesis is in agreement with our finding that the prevalence of masked hypertension was much higher among men <50 years, as they more often have a physically demanding profession when compared with their female counterparts.

However, if these hypotheses are true, then the prognostic relevance of masked hypertension in younger individuals is unclear, given that an increased physical activity has a favorable effect on various health outcomes.¹⁸ Several studies mostly among elderly individuals have shown that the outcome among individuals with masked hypertension is similar to those with sustained hypertension,^19,20 which is in agreement with the finding that ABP is a better predictor of cardiovascular events than CBP and that the prognostic information is partly independent of CBP.^3,4 Whether these strong associations between masked hypertension and cardiovascular events are transferable to younger, mainly male individuals, needs to be defined in prospective studies.

Taken together, we think that these findings may have important implications for the diagnosis of hypertension. Our study suggests that age-specific cut-offs for daytime ABP may be considered. Prospective studies are needed to define these cut-offs. If these studies show that the prognostic effect of masked hypertension is independent of age, then ABPM should be used more often in middle-aged men. The use of ABPM in individuals with nonhypertensive CBP is supported by recent findings showing that ABP also improves risk stratification in normotensive and prehypertensive individuals.²¹ Our data also show that, among individuals with office hypertension, a white coat effect is present in all age groups, although much higher among older individuals, such that algorithms looking for white coat hypertension proposed by current guidelines seem to be applicable independent of age.⁷

Strengths of the current analysis include the large sample size, the large number of young adults available for the study, and the population-based design of all cohorts included. Potential limitations that need to be taken into account in the interpretation of this study include the following. First, assessments of anthropometric characteristics differed across cohorts. Second, CBPM and ABPM were not standardized with regard to device used and intervals set between measurements. However, all daytime and nighttime periods in all IDACO cohorts were calculated in a homogenous fashion, as described previously.²² Third, the number of nonwhite individuals was small and heterogeneous, such that we cannot exclude a differential relationship between daytime ABP and CBP in some other populations. Finally, this was a cross-sectional study, and the prognostic significance of our findings needs to be evaluated in future studies.

Perspectives

In this large collaborative study of 9550 individuals across a wide age range, we describe important age-dependent differences in the relationship between CBP and daytime ABP. In individuals aged <50 years, daytime ABP was significantly higher than CBP, whereas the inverse was found in those aged ≥60 years. These findings may have important implications for the diagnosis of hypertension and its subtypes, although the prognostic significance of our results needs to be defined in future studies.

Novelty and Significance

What Is New?

•

This is the first large study to compare individual conventional and daytime ambulatory blood pressure (BP) values across a wide age range.

What Is Relevant?

•

Among individuals aged <50 years, mean daytime ambulatory BP was significantly higher than conventional BP.

•

Among individuals aged ≥60 years, conventional BP was significantly higher than mean daytime ambulatory BP.

•

The prevalence of white coat and masked hypertension strongly varied by age. White coat hypertension exponentially increased with age, with little variation between men and women. Masked hypertension was more prevalent among men (21.1% versus 11.4%; P<0.0001), with the highest prevalence among men aged 30 to 50 years.

Summary

We found important age-dependent differences in the relationship between conventional daytime ambulatory BP. These findings may have important implications for the diagnosis of hypertension and its subtypes.

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Hypertension

Volume 64 • Number 5 • November 2014

Pages: 1073 - 1079

PubMed: 25185130

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1 January 2014: Previous PDF (Version 1)

History

Received: 28 May 2014

Revision received: 11 June 2014

Accepted: 11 August 2014

Published online: 2 September 2014

Published in print: November 2014

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Keywords

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Hypertension

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David Conen

From the Cardiovascular Research Institut Basel and Department of Medicine, University Hospital Basel, Basel, Switzerland (D.C., S.A., T.S.); Studies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium (L.T., K.A., Y.-M.G., T.K., J.A.S.); Center for Epidemiological Studies and Clinical Trials and Center for Vascular Evaluations, Shanghai Institute of Hypertension, Shanghai Key Laboratory of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China (Y.L., J.-G.W.); Centro de Nefrologìa and Departamento de Fisiopatologìa, Hospital de Clìnicas, Universidad de la Repûblica, Montevideo, Uruguay (J.B.); Steno Diabetes Center, Gentofte and Research Center for Prevention and Health, Gentofte, Denmark (T.W.H.); Department of Planning for Drug Development and Clinical Evaluation, Tohoku University Graduate School of Pharmaceutical Sciences, Sendai, Japan (K.A., M.K., T.O., Y.I.); Division of Cardiovascular Medicine, Department of Clinical Sciences, Danderyd Hospital, Karolinska Institute, Stockholm, Sweden (K.B.-B.); Department of Hygiene and Public Health, Teikyo University School of Medicine, Tokyo, Japan (K.A., T.O.); Department of Medicine, Glostrup Hospital, University of Copenhagen, Copenhagen, Denmark (J.J.); Department of Health, Science and Technology, Aalborg University, Aalborg, Denmark (C.T.-P.); Cambridge University Hospitals, Addenbrook’s Hospital, Cambridge, United Kingdom (E.D.); First Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University Medical College, Krakòw, Poland (K.S.-S., K.K.-J.); Department of Medicine, University of Padova, Padova, Italy (V.T., E.C.); Institute of Internal Medicine, Novosibirsk, Russian Federation (S.M., Y.N.); Section of Geriatrics, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden (L.L.); Asociación Española Primera de Socorros Mutuos, Montevideo, Uruguay (E.S.); Laboratorio de Neurociencias and Instituto Cardiovascular, Universidad del Zulia, Maracaibo, Venezuela (L.M., G.E.M.); Faculty of Medicine, Charles University, Pilsen, Czech Republic (J.F.); Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland (E.O’B.); Labormedizinische Zentrum Dr.Risch, Schaan, Principality of Liechtenstein, Private University, Triesen, Principality of Liechtenstein and Department of Clinical Biochemistry, Medical University Innsbruck, Austria (L.R.); and Department of Epidemiology, Maastricht University, Maastricht, The Netherlands (J.A.S.).

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Notes

This paper was sent to Marc De Buyzere, Guest Editor, for review by expert referees, editorial decision, and final disposition.

The online-only Data Supplement is available with this article at http://hyper.ahajournals.org/lookup/suppl/doi:10.1161/HYPERTENSIONAHA.114.03957/-/DC1.

Reprint requests to David Conen, Department of Medicine, University Hospital Basel, Petersgraben 4, CH-4031 Basel, Switzerland. E-mail: [email protected]

Disclosures

None.

Sources of Funding

The Genetic and Phenotypic Determinants of Blood Pressure and Other Cardiovascular Risk Factors (GAPP) study was supported by the Liechtenstein Government, the Swiss Heart Foundation, the Swiss Society of Hypertension, the University of Basel, the University Hospital Basel, the Hanela Foundation, Schiller AG, and Novartis. David Conen was supported by a grant of the Swiss National Science Foundation (PP00P3_133681). The European Union (HEALTH-2011.2.4.2-2-EU-MASCARA, HEALTH-F7-305507 HOMAGE, and the European Research Council Advanced Researcher Grant-2011-294713-EPLORE) and the Fonds voor Wetenschappelijk Onderzoek Vlaanderen, Ministry of the Flemish Community, Brussels, Belgium (G.0881.13 and G.088013) currently support the Studies Coordinating Centre in Leuven (Belgium). The European Union (grants LSHM-CT-2006–037093 and HEALTH-F4-2007–201550) also supported the research groups in Shanghai, Kraków, Padova, and Novosibirsk. The Danish Heart Foundation (grant 01-2-9-9A-22914) and the Lundbeck Fonden (grant R32-A2740) supported the studies in Copenhagen. The Ohasama study received support via Grant-in-Aid for Scientific Research (22590767, 22790556, 23249036, 23390171, and 23790242) from the Ministry of Education, Culture, Sports, Science and Technology, Japan; Health Labour Sciences Research Grant (H23-Junkankitou [Seishuu]-Ippan-005) from the Ministry of Health, Labour and Welfare, Japan; Japan Arteriosclerosis Prevention Fund; and a Grant from the Central Miso Research Institute, Tokyo, Japan. The National Natural Science Foundation of China (grants 30871360 and 30871081), Beijing, China, and the Shanghai Commissions of Science and Technology (grant 07JC14047 and the “Rising Star” program 06QA14043), and Education (grant 07ZZ32 and the “Dawn” project) supported the JingNing study in China. The Comisión Sectorial de Investigación Científica de la Universidad de la República (Grant I+D GEFA-HT-UY) and the Agencia Nacional de Innovación e Investigación supported the research in Uruguay.

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Age-Specific Differences Between Conventional and Ambulatory Daytime Blood Pressure Values

Hypertension

Vol. 64
No. 5

Purchase access to this journal for 24 hours

Hypertension

Vol. 64
No. 5

Abstract

Introduction

Methods

Blood Pressure Monitoring

Other Covariables

Statistical Methods

Results

Discussion

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Summary

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