Original Article
Arterial stiffness and SBP variability in children and adolescents Stella Stabouli a,b, Sofia Papakatsika b, George Kotronis b, Kyriaki Papadopoulou-Legbelou c, Zoe Rizos d, and Vasilios Kotsis b Background: The aim of this study was to explore the impact of ambulatory blood pressure (ABP) parameters on arterial stiffness measured by carotid–femoral pulse wave velocity (cf-PWV) in children and adolescents. Method: The study population consisted of 138 consecutive young patients (age range 4–20 years) referred to our hypertension center. Office blood pressure (BP), 24-h ABP monitoring and cf-PWV measurements were performed in all patients. Family history and smoking habits were also recorded. Results: Among the study population, 10.6% had cf-PWV values equal to or higher than the 95th percentile of the study population. cf-PWV was higher in the hypertensive compared to the normotensive patients, classified by ABP levels even after adjustment for age and sex. Significant correlations were found between cf-PWV and age, weight, height, estimated central pulse pressure (PP), office SBP and DBP, and ABP parameters including 24-h SBP and DBP, weighted 24-h SBP variability, 24-h SBP and DBP load, 24-h mean arterial pressure (MAP), daytime and night-time SBP, daytime and night-time SBP variability, but not with office and 24-h heart rate, 24-h heart rate variability, 24-h daytime and night-time PP, DBP variability, ambulatory arterial stiffeness index and BMI z-score. In analysis of covariance, only weighted 24-h SBP variability (b ¼ 0.28, P < 0.05) and daytime SBP variability (b ¼ 0.15, P < 0.05) were the independent determinants of cf-PWV in children and adolescents. Conclusion: These data may suggest that increased SBP variability is closely associated with arterial stiffness in children and adolescents. Keywords: 24-h ambulatory blood pressure, adolescents, arterial stiffness, blood pressure variability, children, early vascular ageing, hypertension, obesity, pulse wave velocity Abbreviations: AASI, ambulatory arterial stiffness index; ABP, ambulatory blood pressure; BP, blood pressure; cf-PWV, carotid–femoral pulse wave velocity; WCH, white-coat hypertension
INTRODUCTION
H
ypertension has been recognized as a risk factor for cardiovascular disease that acts from early childhood [1]. Accumulating evidence shows that subclinical target organ damage may be present even in the 88
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early stages of mild hypertension in children and adolescents [2–4]. This is quite alarming in the context of the trend of increasing prevalence of hypertension in the young worldwide [5]. Current guidelines have pointed out the importance of diagnosing hypertension in children and adolescents and the importance of using ambulatory blood pressure monitoring (ABPM) for the diagnosis of hypertension in this population [6,7]. Blood pressure (BP) presents significant variability in children and adolescents, and the diagnosis of hypertension is based on multiple BP measurements on different occasions [6]. ABPM offers numerous BP measurements, out of the office environment, and allows a more rigorous assessment of BP phenotype in the pediatric population [7]. In recent years, ABPM has been utilized in many clinical studies in children and adolescents, showing not only a significant superiority in indentifying young patients with increased cardiovascular risk, but also a better control of BP levels during treatment [2,7,8]. Early vascular alterations have been described in children and adolescents with BP pressure elevations, both for primary and secondary hypertension [9]. Noninvasive assessment of atherosclerosis in young populations has become a significant challenge under the notion of increasing future ability to improve cardiovascular outcomes. The measurement of pulse wave velocity (PWV) has been accepted as a simple, reproducible, noninvasive method to assess arterial stiffness as a surrogate measure of atherosclerosis [10]. PWV is the speed at which the pressure waveforms travel along the aorta and large arteries during each cardiac cycle. Recent data show that PWV is increased in children and adolescents with BP elevations, as well as in those with diabetes mellitus and other cardiovascular risk factors [11–14]. However, only limited studies have performed both measurements of PWV and ABPM [15,16]. Most investigations have been based on office BP measurements, Journal of Hypertension 2015, 33:88–95 a 1st Department of Pediatrics, Aristotle University of Thessaloniki, Hippokratio Hospital, bHypertension-24 h ABPM ESH Center of Excellence, 3rd Department of Medicine, c4th Department of Pediatrics, Aristotle University of Thessaloniki, Papageorgiou Hospital, Thessaloniki, Greece and dUniversity of Toronto, Ontario, Canada
Correspondence to Associate Professor Stella Stabouli, MD, PhD, 39 Zaka STR, Panorama, Thessaloniki 55236, Greece. Tel: +30 6976433767; fax: +30 2310452429; e-mail: [email protected] Received 28 December 2013 Revised 4 August 2014 Accepted 5 August 2014 J Hypertens 33:88– 95 ß 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. DOI:10.1097/HJH.0000000000000369
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Arterial stiffness in youth
whereas data on the association between ambulatory blood pressure (ABP) parameters and PWV are scarce. The aim of the present study was to investigate possible associations of ABP parameters with PWV in children and adolescents. We studied the effect of average ABP and other parameters such as BP variability, daytime-to-night-time BP ratio, and 24-h pulse pressure (PP) on carotid–femoral PWV (cf-PWV) in young patients. We also studied the relationship between ambulatory arterial stiffness index (AASI) and cf-PWV. Moreover, we examined the possible effect of hypertension and obesity on cf-PWV.
METHODS Study population The study population consisted of 138 consecutive children and adolescents with an age range of 4–20 years. None of the participants were taking any medication or had evidence of systemic disease that causes hypertension. Body weight and height were measured at the closest 0.1 kg and 0.1 cm, respectively, with the participants in light clothing without shoes. BMI was calculated as weight (kg)/height (m2). BMI z-score was calculated using Cole’s lambda-mu-sigma method [17]. Patients were characterized as normal-weight if their BMI was lower than the 85th percentile, overweight if their BMI was equal to or higher than the 85th percentile and lower than the 95th percentile, and obese if their BMI was equal to or higher than the 95th percentile [18]. Fasting serum glucose and lipids were measured in all patients. Family history of hypertension was recorded. Smoking and alcohol use were also recorded. Informed consent to participate in the study was obtained by the children’s parents and in the case of patients older than 8 years by both the parent and the child or adolescent. The institutional review board approved the human research protocol.
Clinic blood pressure measurements A trained physician measured office BP three times in each patient using a mercury sphygmomanometer with the appropriate size cuff before the fitting of the ABP monitors. During the measurements the participant remained seated for 10 min with the arm comfortably placed at the level of the heart. Three additional sphygmomanometric sitting BP measurements were performed after the removal of the ABP device. Office BP was calculated as the average of the six BP measurements. Hypertension was defined according to the previously published guidelines [6,19]. BP index was calculated by dividing the average office BP by the 95th BP percentile specific for each patient.
Ambulatory blood pressure monitoring All patients underwent 24-h ABPM on a usual school day. They were instructed to act normally. The Spacelabs 90217 ambulatory BP monitor (Spacelabs Inc., Snoqualmie, Washington, USA) was used. The appropriate size cuff was placed around the nondominant arm and three BP determinations were made, along with sphygmomanometric measurements, to verify that the average of the two sets of values did not differ by more than 5 mmHg. Reading and analyzing the ABP data has been previously described Journal of Hypertension
[20,21]. All patients were instructed to rest or sleep between midnight and 0600 h (night-time) and to maintain their usual activities between 0800 and 2200 h (daytime). Patients were instructed to keep their arm still and relaxed at their side during measurements. They were requested to avoid strenuous exercise and sleeping during daytime and to rise from bed after 6 : 00 a.m., even if they were awake earlier than this time of the day. Those who stated that they had not rested or slept during the night-time (n ¼ 2) were excluded from the study. All 24-h ABPM sessions had at least 72 valid BP measurements (average measurements 80.9 6.5). BP variability was measured using the weighted 24-h BP SD, computed as the weighted average of daytime and nighttime BP SD [22]. AASI was calculated as 1 minus the regression slope of DBP on SBP [23]. Daytime BP index was calculated by dividing the average daytime BP by the 95th BP percentile specific for each patient. BP load was calculated as the percentage of BP readings above the 95th BP percentile specific for each patient. The 24-h BP load was calculated as a weighted sum of the daytime and nighttime BP loads. ABP percentiles according to sex and height were used for the evaluation of ABP in patients aged 16 years or less, whereas adult ABP limits were used for older patients [6,19]. Using the combination of both office BP and ABP measurements, the patients were divided into four BP phenotypes. Patients who showed normotension or hypertension on the basis of both office BP and ABP measurements were characterized as having sustained normotension or hypertension, respectively. White-coat hypertension (WCH) was defined as office hypertension with ambulatory normotension, and masked hypertension as office normotension with ambulatory hypertension [24].
Carotid–femoral pulse wave velocity measurement The investigation took place in a quiet, semi-darkened, temperature-controlled room (218C). Before the examination, all participants rested in the recumbent position for about 15 min. The participants were instructed to refrain from eating, smoking and drinking beverages containing caffeine 3 h and also from drinking alcohol 10 h before measurement. cf-PWV estimation, according to the European Expert Consensus on Arterial Stiffness, was used to determine arterial stiffness [10]. cf-PWV was calculated according to the equation cf-PWV ¼ D(m)/t (s), where t denotes the transit time of the arterial pulse along the distance, and D the distance assimilated to the surface between the recording sites. D was measured directly using a centimeter tape, whereas t was obtained by the Complior System (Colson, Les Lilas, France) automatically. The transit time was quantified as the time delay between the feet of the two waveforms that were recorded simultaneously at the right common carotid artery and the right femoral artery (‘foot-to-foot’ method) using mechano-transducers directly applied on the skin. Subtracted cf-PWV was also calculated by using the 0.8 of D [10]. Central PP was calculated by pulse wave analysis. Complior device measures directly central (carotid) pressure waveforms. There is neither any mathematical model nor any transfer function. Complior uses the calibration method recognized by the scientific www.jhypertension.com
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Stabouli et al.
experts using mean and diastolic pressure to calibrate the carotid signal [25,26]. Patients remained in the supine position and were advised neither to speak nor to sleep during the measurements. The same doctor, who was unaware of the BP measurements, conducted all the measurements under the previously described conditions. Reproducibility of the measurements from our group has been reported previously [21]. Spurious systolic hypertension was defined as brachial SBP higher than or equal to the 95th percentile for age, sex and height, brachial DBP lower than the 95th percentile for age, sex and height, and central PP lower than the 90th percentile of the study population [27].
Statistical analysis The IBM SPSS 21.0 (SPSS Inc., Chicago, Illinois, USA) statistical package was used to analyze the data. Standard descriptive statistics, two-tailed Student’s t test, bivariate correlation analysis, linear regression analysis (stepwise criteria: probability of F to enter 0.050, probability of F to remove 0.100) and analysis of covariance (ANCOVA) were used. A P value less than 0.05 was considered statistically significant. The collinearity statistics tolerance (tolerance ¼ 1 Ri2, where Ri is the square multiple correlation of one variable with the other independent variables) was used for collinearity diagnostics. The default value for tolerance was 0.0001. All variables were necessary to pass this criterion in order to be included in an equation, regardless of the selection method used. The general linear model (GLM) univariate procedure provides regression analysis and analysis of variance for one dependent variable by one or more independent factors or covariates. The factor variables divide the population into groups. GLM is a general model that encompasses both analysis of variance (ANOVA) and regression. In GLM you can estimate random and mixed-effects models, perform post-hoc tests on estimated marginal means, and analyze ANCOVA and regression models (SPSS Base Applications Guide, SPSS Inc., Chicago, Illinois, USA).
RESULTS Demographic data, cf-PWV, office BP and ABP levels of the population are listed in Tables 1 and 2. ABP levels were TABLE 1. Patients’ characteristics and carotid–femoral pulse wave velocity values Variable
Mean SD
Age (years) Sex (male %) BMI (kg/m2) Total cholesterol (mg/dl) Triglycerides (mg/dl) Glucose (mg/dl) Current smokers (%) Family history hypertension (%) Alcohol (yes%) Dyslipidemia (%) Diabetes (%) cf-PWV (m/s) Subtracted cf-PWV (m/s)
12.0 5.0 61.7 24.3 6.0 167.9 31.5 89.2 42.8 90.2 36.6 7.6 29.4 8.2 7 4.5 7.1 1.7 5.7 1.4
cf-PWV, carotid–femoral pulse wave velocity.
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lower to normal-weight children and adolescents compared to overweight (112.92 11.22 vs. 118.45 10.62 mmHg; P < 0.05) and obese ones (112.92 11.22 vs. 119.99 10.99 mmHg; P < 0.001). Isolated systolic hypertension was found in 29.8% of the children and adolescents, and 11.5% of the population could be characterized as having ‘spurious’ systolic hypertension. Patients with ‘spurious’ systolic hypertension were 58.3% men and had increased BMI percentile (83.3% had BMI 97th percentile). With regard to BP classification, 72.7% of these patients had WCH and 27.3% had sustained hypertension. Carotid–femoral pulse wave velocity was higher in hypertensive compared with normotensive patients identified by ABP levels (Table 3). The differences in cf-PWV remained significant after adjustment for age and sex. Among the patients, 10.6% had cf-PWV values higher than the 95th percentile of the study population. PWV values adjusted for age, sex and BMI z-score did not differ between patients with and without family history of hypertension (6.99 0.31 versus 6.85 0.19; P ¼ 0.70), current smokers and nonsmokers (6.73 0.85 versus 6.70 0.16; P ¼ 0.97). In Pearson’s bivariate correlations analysis, cf-PWV showed significant correlations with age, height, weight, TABLE 2. Office blood pressure and ambulatory blood pressure levels Variable
Mean SD
Office SBP (mmHg) Office DBP mmHg Office heart rate (beats/min) Office PP (mmHg) SBP index SBP index Average 24-h SBP (mmHg) Average 24-h DBP (mmHg) Average 24-h heart rate (beats/min) Average 24-h PP (mmHg) 24-h SBP load (%) 24-h DBP load (%) Weighted 24-h SBP SD (mmHg) Weighted 24-h DBP SD (mmHg) 24-h heart rate SD (beats/min) Average daytime SBP (mmHg) Average daytime DBP (mmHg) Average daytime heart rate (beats/min) Average daytime PP (mmHg) Daytime SBP load (%) Daytime DBP load (%) Daytime SBP index Daytime SBP index Daytime SD SBP (mmHg) Daytime SD DBP (mmHg) Daytime SD Heart rate (beats/min) Average night-time SBP (mmHg) Average night-time DBP (mmHg) Average night-time heart rate (beats/min) Average night-time PP (mmHg) Night-time SD SBP (mmHg) Night-time SBP load (%) Night-time DBP load (%) Night-time SD DBP (mmHg) Night-time SD Heart rate (beats/min) Daytime-to-night-time SBP
126.4 16.1 75.8 12.7 89.7 17.7 49.5 12.0 0.99 0.12 0.84 0.21 117.4 12.1 68.5 7.8 86.9 13.3 48.9 8.5 16.0 19.5 8.0 12.5 12.1 2.9 11.2 2.3 12.8 3.0 119.5 12.3 70.7 8.1 90.0 14.1 48.8 8.5 17.6 19.9 10.0 14.7 0.93 0.08 0.86 0.09 11.3 2.8 10.5 2.4 11.9 3.2 111.8 12.7 62.8 8.6 78.8 12.9 48.9 9.2 10.6 3.5 29.0 29.7 9.8 15.3 9.3 2.7 9.1 3.4 1.07 0.07
PP, pulse pressure.
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Arterial stiffness in youth TABLE 3. Carotid–femoral pulse wave velocity by blood pressure classification Variable a
cf-PWV SE Subtracted cf-PWVa SE
Normotension
White-coat hypertension
6.696 0.262 5.390 0.213
Hypertension
Spurious hypertension
7.860 0.476 6.315 0.386
7.231 0.261 5.819 0.212
7.282 0.414 5.857 0.336
ABP, ambulatory blood pressure; BP, blood pressure; cf-PWV, carotid–femoral pulse wave velocity; SE, standard error. a Based on estimated marginal means, adjusted for age, weighted least-squares regression by sex and adjustment for Bonferroni’s multiple comparisons. P < 0.05 vs. normotension.
office SBP and DBP, 24-h SBP and DBP, weighted 24-h SBP SD, 24-h SBP and DBP load, 24-h MAP, 24-h MAP SD, daytime SBP, SD of daytime SBP, night-time SBP and DBP, SD of night-time SBP, night-time PP, and estimated central PP. No relationship was found between cf-PWV and any heart rate measurements (office, 24 h, 24-h heart rate variability) (Tables 4 and 5). No relationship was found between cf-PWV and AASI (Table 5). Linear regression analysis for weighted 24-h SBP variability and cf-PWV is shown in Fig. 1.
Carotid–femoral pulse wave velocity in different blood pressure phenotypes The 95% confidence interval (CI) of cf-PWV was 6.4–7.1 m/s in sustained normotensive patients (n ¼ 56), 6.4–7.9 m/s in WCH patients (n ¼ 48), 5.8–8.1 m/s in masked hypertension patients (n ¼ 5), and 6.1–8.0 m/s in sustained hypertensive patients (n ¼ 27). There were no statistically significant differences in cf-PWV among the above groups after adjustment for age and sex (WCH vs. normotensive patients; P ¼ 0.38, masked hypertension vs. normotensive patients; P ¼ 0.74, sustained hypertensive vs. sustained normotensive patients; P ¼ 0.63, Bonferroni’s adjustment for multiple comparisons). The results for masked hypertension and sustained hypertension were underpowered because of the small number of patients in these groups.
TABLE 4. Pearson’s correlations of carotid–femoral pulse wave velocity with anthropometric measures, office blood pressure levels and laboratory values cf-PWV (m/s) Variable Age (years) Height (cm) Weight (kg) BMI z-score Office SBP (mmHg) Office SBP z-score Office SBP index Office DBP (mmHg) Office DBP z-score Office DBP index Office heart rate (beats/min) Heart rate measured by Complior (beats/min) Glucose (mg%) Total cholesterol (mg%) Triglycerides (mg%)
r
P
0.233 0.263 0.229 0.106 0.197 0.05 0.061 0.23 0.09 0.11 0.004 0.077 0.016 0.212 0.023
0.0001 0.0001 0.0001 0.09 0.05 0.57 0.55 0.01 0.28 0.287 0.93 0.23 0.88 0.06 0.84
BP, blood pressure; cf-PWV, carotid–femoral pulse wave velocity. Statistically significant values are highlighted in bold.
Journal of Hypertension
Analysis of covariance for the relationship of carotid–femoral pulse wave velocity with blood pressure variability after adjustment for demographics and other risk factors In ANCOVA, cf-PWV was significantly associated with weighted 24-h SBP variability (b ¼ 0.28, 95% CI of b 0.037–0.536, P < 0.05). Age (b ¼ 0.117, P ¼ 0.78), sex (b ¼ 0.083, P ¼ 0.83), office SBP (b ¼ 1.297, P ¼ 0.56) and office DBP indices (b ¼ 1.184, P ¼ 0.35), 24-h SBP (b ¼ 2.405, P ¼ 0.51) and DBP (b ¼ 0.555, P ¼ 0.86) indices, and BMI z-score (b ¼ 0.063, P ¼ 0.71) were not significant determinants of cf-PWV in the model (model’s R2 ¼ 0.144). The ratio of daytime to night-time SBP was not associated with cf-PWV (b ¼ 2.165, P ¼ 0.25). The role of obesity was further investigated in another model where cf-PWV was significantly associated with age (b ¼ 0.675, P < 0.05) and weighted 24-h SBP variability (b ¼ 0.114, P < 0.05), but not with overweight versus obesity status (b ¼ 0.030, P ¼ 0.94) or normal-weight versus obesity TABLE 5. Pearson’s correlations of carotid–femoral pulse wave velocity with ambulatory blood pressure parameters and estimated central pulse pressure cf-PWV (m/s) Variable 24-h SBP (mmHg) Weighted 24-h SBP SD (mmHg) 24-h SBP load (%) 24-h DBP (mmHg) Weighted 24-h DBP SD (mmHg) 24-h DBP load (%) 24-h MAP (mmHg) 24-h MAP SD (mmHg) 24-h PP (mmHg) Average 24-h heart rate (beats/min) SD 24-h heart rate (beats/min) Daytime SBP (mmHg) SD daytime SBP (mmHg) Daytime DBP (mmHg) SD daytime DBP (mmHg) Daytime PP (mmHg) Daytime SBP index Daytime DBP index Night-time SBP (mmHg) SD night-time SBP (mmHg) Night-time DBP (mmHg) SD night-time DBP (mmHg) Night-time PP (mmHg) Daytime-to-night-time SBP AASI Estimated central PP (mmHg)
r
P
0.239 0.251 0.216 0.196 0.106 0.517 0.22 0.21 0.163 0.131 0.061 0.221 0.273 0.167 0.069 0.164 0.153 0.139 0.266 0.181 0.232 0.88 0.214 0.818 0.167 0.223
0.01 0.001 0.012 0.05 0.22 0.067 0.001 0.01 0.06 0.13 0.48 0.01 0.001 0.053 0.422 0.056 0.075 0.107 0.005 0.05 0.01 0.31 0.024 0.256 0.058 0.001
AASI, ambulatory arterial stiffness index; ABP, ambulatory blood pressure; cf-PWV, carotid–femoral pulse wave velocity; MAP, mean arterial pressure; PP, pulse pressure. Statistically significant values are highlighted in bold.
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Stabouli et al. R2 linear = 0.063
12 000
y = 5.23-0.13*x
cf-PWV (m/s)
b
P value
R2
0.020 0.036 0.014 0.006 0.153 0.005 0.140 0.049 0.088
0.199 0.078 0.550 0.870 0.044 0.956 0.669 0.175 0.420
0.176
0.016 0.020 0.014 0.021 0.042 0.008 0.147 0.069 0.009
0.266 0.305 0.509 0.533 0.459 0.917 0.660 0.046 0.936
0.149
by office
0.841
0.441
0.196
by ABP
0.157
0.886
0.16 0.018 1.235 0.048 0.105
0.037 0.830 0.194 0.149 0.312
by office
0.539
0.639
by ABP
0.227
0.845
0.048 0.003 1.056 0.068 0.064
0.398 0.969 0.285 0.037 0.534
cf-PWV (m/s)
10 000 8 000 6 000 4 000 2 000 000
5.0
10.0
15.0
20.0
25.0
Weighted 24-h SBP SD (mmHg) FIGURE 1 Linear regression analysis between carotid–femoral pulse wave velocity and weighted 24-h SBP variability.
status (b ¼ 0.371, P ¼ 0.20). cf-PWV was 6.98 1.56 m/s in patients clasified as obese, compared with 7.17 2.06 m/s in overweight and 7.26 1.74 m/s in normal-weight patients, but the differences between the groups did not reach statistical significance. Fasting serum glucose, total cholesterol and triglycerides were not significant determinants of cf-PWV (b ¼ 0.001, P ¼ 0.81; b ¼ 0.011, P ¼ 0.11; b ¼ 0.003, P ¼ 0.61, respectively). Finally, AASI (b ¼ 0.796, P ¼ 0.48), 24-h PP (b ¼ 0.006, P ¼ 0.77), 24-h SBP and DBP loads (b ¼ 0.884, P ¼ 0.34; b ¼ 0.797, P ¼ 0.64, respectively) and office SBP and DBP z-scores (b ¼ 0.18, P ¼ 0.213; b ¼ 0.13, P ¼ 0.294, respectively) were also not significantly associated with cf-PWV (Supplementary Table 7, http:// links.lww.com/HJH/A405). The role of daytime and night-time SBP and DBP variability and the presence of office or ambulatory hypertension were further investigated (Table 6). There was a strong relationship between daytime SBP variability and weighted 24-h SBP variability (r ¼ 0.88, P < 0.0001). Both variables are related to cf-PWV (r ¼ 0.25 and 0.27, P < 0.01). When we forced the daytime SBP variability in the same model with weighted 24-h SBP variability, then the model’s R2 decreased and both variables lost the significance, suggesting that daytime SBP variability is neither stronger nor a better determinant of cf-PWV compared to weighted 24-h SBP variability.
DISCUSSION The present study showed significant correlations between cf-PWV and ABP parameters in children and adolescents. The main finding was that weighted 24-h and daytime SBP variability exhibited an independent association with cf-PWV. Hypertension was accompanied with increased cf-PWV. Obesity was not a significant determinant of cf-PWV in this study, as BMI z-score did not correlate with cf-PWV in any model. These findings suggest that short-term BP fluctuations may have an impact on structural and functional vascular properties in young patients independent of absolute BP levels and adiposity. Several studies in adults have shown a relationship between short-term BP variability and target organ damage 92
TABLE 6. Analysis of covariance for the relationship of carotid– femoral pulse wave velocity with daytime and nighttime SBP variability
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Model 1a Office SBP Office DBP Daytime SBP Daytime DBP SD daytime SBP SD daytime DBP Sex (male vs. female) Age (years) BMI z-score Model 2a Office SBP Office DBP Night-time SBP Night-time DBP SD daytime SBP SD daytime DBP Sex (male vs. female) Age (years) BMI z-score Model 1b Presence of hypertension BP (yes–no) Presence of hypertension (yes–no) SD daytime SBP SD daytime DBP Sex (male vs. female) Age (years) BMI z-score Model 2b Presence of hypertension BP (yes–no) Presence of hypertension (yes–no) SD night-time SBP SD night-time DBP Sex (male vs. female) Age (years) BMI z-score
0.152
ABP, ambulatory blood pressure; PP, pulse pressure. Statistically significant values are highlighted in bold.
or cardiovascular outcomes using different methods for the quantification of BP variability [28–30]. In the present study, BP variability was defined as weighted 24-h SD of BP, which is considered a better index of BP variability. Analysis of daytime and night-time BP variability in our population suggested that daytime compared to night-time BP variability exerts a more important effect in arterial stiffness in youth. Night-time variability maybe less reproducible in the young and maybe more than one ABPM studies are needed. On the contrary, weighted 24-h BP SD that has been introduced by Bilo et al. [22] is more reproducible as a method of estimation of BP variability. Weighted 24-h SD overcomes the interference of night-time BP fall, offering assessment of BP variability all over the 24-h period and has been suggested to be a better predictor of organ damage and cardiovascular risk [22]. BP variability in children and adolescents has been associated with low birth weight, obesity, BP levels and age [31,32]. The changes in BP variability with age were studied in a diverse ethnic population over a 15-year period and demonstrated that BP Volume 33 Number 1 January 2015
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Arterial stiffness in youth
variability increased with age. Other determinants of BP variability were mean ABP values, male sex, obesity, and socioeconomic status [32]. Impaired baroreflex sensitivity has been suggested in children with elevated BP levels [33]. Other possible mechanisms may include enhanced activation of the sympathetic nervous system or inflammatory factors promoting vasoconstriction and facilitating acute BP increases. The effect of BP variability on cf-PWV may have an early origin as suggested by the young age of the study population consisting of either normotensive patients or newly diagnosed hypertensive patients. In a previous study by our group in healthy young volunteers, we have shown that weighted 24-h SBP variability is a predictor of increased cf-PWV and early vascular aging [21]. Increased weighted 24-h BP variability may result in repetitive fluctuations of shear stress on arterial wall that results in morphological changes and arterial stiffening. The independent association between weighted 24-h SBP variability and cf-PWV may alternatively imply a common pathogenetic mechanism in youth. Determinants of PWV have been reported to be age, sex and absolute BP values, which, as mentioned above, are also predictors of BP variability [34,35]. Thus, the question of whether SBP variability has a causative role in or it is a result of arterial stiffening needs to be clarified by further studies. Carotid–femoral pulse wave velocity is accepted as the most reliable method for the measurement of arterial stiffness in adults with prognostic significance for cardiovascular morbidity and mortality for coronary events and fatal strokes [36–39]. However, its predictive value remains yet to be established in young patients. In the current study, we aimed to detect early vascular changes in children and adolescents in the absence of any known clinical manifestation of cardiovascular disease. The population was at an increased risk for future cardiovascular events in the context that they have been referred to a hypertension center for suspected hypertension. Despite referral from primary care practitioners, the majority of patients were found to be normotensive both in office BP and ABP measurements. Normotensive patients had lower cf-PWV compared to those with hypertension by ABP levels. Increased PWV in youth has been associated with conditions that confer increased cardiovascular risk such as diabetes and hypertension [11,14–16,40,41]. The parameters 24-h PP and AASI, which are derived from 24-h ABPM, have been proposed as surrogate markers of arterial stiffness [42–47]. In children and adolescents, PP and AASI are not very well studied. We have previously reported that 24-h PP could predict left ventricular mass index, and it presents significant correlations with carotid intima-media thickness in children and adolescents referred to a hypertension clinic [48,20]. In another study of 82 referred children and adolescents, a close association of 24-h PP was demonstrated with left ventricular mass index and cf-PWV, but not with AASI [15]. In the present study, AASI also did not correlate with cf-PWV. PP was associated with cf-PWV in simple bivariate correlations, but only weighted 24-h and daytime SBP variability were independent determinants in the ANCOVA analysis. The potential explanation of these findings may lie in the different Journal of Hypertension
mechanisms of BP-induced arterial stiffening. In young patients with more elastic arteries, the SBP elevation and the increase in 24-h PP may be mediated by the exaggeration of the amplification phenomenon. On the contrary, BP fluctuations interfering to cyclic stress on the arterial wall may have a more significant contribution to arterial stiffening. The majority of the patients in the study had systolic hypertension by office BP levels and 29.8% had isolated systolic hypertension. About one-third of these patients had estimated central aortic PP in the normal range of the study population and could be characterized as having ‘spurious’ hypertension. Interestingly, in our population, children and adolescents with ‘spurious’ hypertension were more likely to have WCH, which has been associated with an increased cardiovascular risk in children and adolescents [24,49]. Further studies may evaluate the importance of this finding. In this cross-sectional study, we were unable to determine the causative effect or mechanism underlying the relationship among BP variability and cf-PWV. Another limitation of the study is that the patients were not randomly selected as they were referred to a hypertension center. However, a large proportion of the children and adolescents were diagnosed as sustained normotensive patients after the evaluation. Larger longitudinal studies are needed to assess the effect of BP variability on progression of arterial stiffness in young populations. Another limitation of the study is that cf-PWV was explained from BP variability only in a small percentage in the models (14.4–19.6%), suggesting that other important factors can influence arterial stiffness beyond BP fluctuations. In the current study we hypothesized that newer parameters of ABPM such as weighted 24-h and daytime SBP variability could have an impact on arterial stiffness independent of the classical BP measurements. This study provides evidence that arterial stiffness is an ongoing process starting early in life, advancing with age and modified from different factors. In this pediatric and adolescent population, 10.6% had cf-PWV values higher than the 95th percentile of the population, suggesting an early onset of arteriosclerosis [50]. These extreme values of stiffness may be followed up for the possibility of early and aggressive interventions, especially as far as the lifestyle of these young patients is concerned.
ACKNOWLEDGEMENTS Conflicts of interest There are no conflicts of interest.
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Arterial stiffness in youth 46. Jerrard-Dunne P, Mahmud A, Feely J. Ambulatory arterial stiffness index, pulse wave velocity and augmentation index–interchangeable or mutually exclusive measures? J Hypertens 2008; 26:529–534. 47. Muxfeldt ES, Fiszman R, Castelpoggi CH, Salles GF. Ambulatory arterial stiffness index or pulse pressure: which correlates better with arterial stiffness in resistant hypertension? Hypertens Res 2008; 31:607–613.
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Reviewers’ Summary Evaluations
Reviewer 2
Reviewer 1 A novel finding provided by the authors is the existence of a correlation between blood pressure variability, assessed by 24 h monitoring, and pulse wave velocity in a population of children and adolescents. This information is useful in understanding the pathophysiology of vascular compliance in this age range. Among the limitations of the study are the heterogeneity and wide age range of the study population, spanning from paediatric age subjects to young adults. Additional studies will be necessary, possibly performed in a higher number of subjects with more homogeneous characteristics, in order to confirm and validate the present results.
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The strengths of the study are the relatively large group of children included and the detailed description of the hemodynamic phenotype. It was found that in childhood PWV does not differ significantly across BP status from normotension to sustained hypertension. However, significant relationships between BP variability and increased PWV were observed. This finding suggest that increased BP variability may precede early vascular damage. A limitation of the study is lack of data on relations between PWV and other markers of hypertensive damage such as left ventricular hypertrophy and increased intima–media thickness.
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Arterial stiffness and SBP variability in children and adolescents Stella Stabouli a,b, Sofia Papakatsika b, George Kotronis b, Kyriaki Papadopoulou-Legbelou c, Zoe Rizos d, and Vasilios Kotsis b Background: The aim of this study was to explore the impact of ambulatory blood pressure (ABP) parameters on arterial stiffness measured by carotid–femoral pulse wave velocity (cf-PWV) in children and adolescents. Method: The study population consisted of 138 consecutive young patients (age range 4–20 years) referred to our hypertension center. Office blood pressure (BP), 24-h ABP monitoring and cf-PWV measurements were performed in all patients. Family history and smoking habits were also recorded. Results: Among the study population, 10.6% had cf-PWV values equal to or higher than the 95th percentile of the study population. cf-PWV was higher in the hypertensive compared to the normotensive patients, classified by ABP levels even after adjustment for age and sex. Significant correlations were found between cf-PWV and age, weight, height, estimated central pulse pressure (PP), office SBP and DBP, and ABP parameters including 24-h SBP and DBP, weighted 24-h SBP variability, 24-h SBP and DBP load, 24-h mean arterial pressure (MAP), daytime and night-time SBP, daytime and night-time SBP variability, but not with office and 24-h heart rate, 24-h heart rate variability, 24-h daytime and night-time PP, DBP variability, ambulatory arterial stiffeness index and BMI z-score. In analysis of covariance, only weighted 24-h SBP variability (b ¼ 0.28, P < 0.05) and daytime SBP variability (b ¼ 0.15, P < 0.05) were the independent determinants of cf-PWV in children and adolescents. Conclusion: These data may suggest that increased SBP variability is closely associated with arterial stiffness in children and adolescents. Keywords: 24-h ambulatory blood pressure, adolescents, arterial stiffness, blood pressure variability, children, early vascular ageing, hypertension, obesity, pulse wave velocity Abbreviations: AASI, ambulatory arterial stiffness index; ABP, ambulatory blood pressure; BP, blood pressure; cf-PWV, carotid–femoral pulse wave velocity; WCH, white-coat hypertension
INTRODUCTION
H
ypertension has been recognized as a risk factor for cardiovascular disease that acts from early childhood [1]. Accumulating evidence shows that subclinical target organ damage may be present even in the 88
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early stages of mild hypertension in children and adolescents [2–4]. This is quite alarming in the context of the trend of increasing prevalence of hypertension in the young worldwide [5]. Current guidelines have pointed out the importance of diagnosing hypertension in children and adolescents and the importance of using ambulatory blood pressure monitoring (ABPM) for the diagnosis of hypertension in this population [6,7]. Blood pressure (BP) presents significant variability in children and adolescents, and the diagnosis of hypertension is based on multiple BP measurements on different occasions [6]. ABPM offers numerous BP measurements, out of the office environment, and allows a more rigorous assessment of BP phenotype in the pediatric population [7]. In recent years, ABPM has been utilized in many clinical studies in children and adolescents, showing not only a significant superiority in indentifying young patients with increased cardiovascular risk, but also a better control of BP levels during treatment [2,7,8]. Early vascular alterations have been described in children and adolescents with BP pressure elevations, both for primary and secondary hypertension [9]. Noninvasive assessment of atherosclerosis in young populations has become a significant challenge under the notion of increasing future ability to improve cardiovascular outcomes. The measurement of pulse wave velocity (PWV) has been accepted as a simple, reproducible, noninvasive method to assess arterial stiffness as a surrogate measure of atherosclerosis [10]. PWV is the speed at which the pressure waveforms travel along the aorta and large arteries during each cardiac cycle. Recent data show that PWV is increased in children and adolescents with BP elevations, as well as in those with diabetes mellitus and other cardiovascular risk factors [11–14]. However, only limited studies have performed both measurements of PWV and ABPM [15,16]. Most investigations have been based on office BP measurements, Journal of Hypertension 2015, 33:88–95 a 1st Department of Pediatrics, Aristotle University of Thessaloniki, Hippokratio Hospital, bHypertension-24 h ABPM ESH Center of Excellence, 3rd Department of Medicine, c4th Department of Pediatrics, Aristotle University of Thessaloniki, Papageorgiou Hospital, Thessaloniki, Greece and dUniversity of Toronto, Ontario, Canada
Correspondence to Associate Professor Stella Stabouli, MD, PhD, 39 Zaka STR, Panorama, Thessaloniki 55236, Greece. Tel: +30 6976433767; fax: +30 2310452429; e-mail: [email protected] Received 28 December 2013 Revised 4 August 2014 Accepted 5 August 2014 J Hypertens 33:88– 95 ß 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. DOI:10.1097/HJH.0000000000000369
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Arterial stiffness in youth
whereas data on the association between ambulatory blood pressure (ABP) parameters and PWV are scarce. The aim of the present study was to investigate possible associations of ABP parameters with PWV in children and adolescents. We studied the effect of average ABP and other parameters such as BP variability, daytime-to-night-time BP ratio, and 24-h pulse pressure (PP) on carotid–femoral PWV (cf-PWV) in young patients. We also studied the relationship between ambulatory arterial stiffness index (AASI) and cf-PWV. Moreover, we examined the possible effect of hypertension and obesity on cf-PWV.
METHODS Study population The study population consisted of 138 consecutive children and adolescents with an age range of 4–20 years. None of the participants were taking any medication or had evidence of systemic disease that causes hypertension. Body weight and height were measured at the closest 0.1 kg and 0.1 cm, respectively, with the participants in light clothing without shoes. BMI was calculated as weight (kg)/height (m2). BMI z-score was calculated using Cole’s lambda-mu-sigma method [17]. Patients were characterized as normal-weight if their BMI was lower than the 85th percentile, overweight if their BMI was equal to or higher than the 85th percentile and lower than the 95th percentile, and obese if their BMI was equal to or higher than the 95th percentile [18]. Fasting serum glucose and lipids were measured in all patients. Family history of hypertension was recorded. Smoking and alcohol use were also recorded. Informed consent to participate in the study was obtained by the children’s parents and in the case of patients older than 8 years by both the parent and the child or adolescent. The institutional review board approved the human research protocol.
Clinic blood pressure measurements A trained physician measured office BP three times in each patient using a mercury sphygmomanometer with the appropriate size cuff before the fitting of the ABP monitors. During the measurements the participant remained seated for 10 min with the arm comfortably placed at the level of the heart. Three additional sphygmomanometric sitting BP measurements were performed after the removal of the ABP device. Office BP was calculated as the average of the six BP measurements. Hypertension was defined according to the previously published guidelines [6,19]. BP index was calculated by dividing the average office BP by the 95th BP percentile specific for each patient.
Ambulatory blood pressure monitoring All patients underwent 24-h ABPM on a usual school day. They were instructed to act normally. The Spacelabs 90217 ambulatory BP monitor (Spacelabs Inc., Snoqualmie, Washington, USA) was used. The appropriate size cuff was placed around the nondominant arm and three BP determinations were made, along with sphygmomanometric measurements, to verify that the average of the two sets of values did not differ by more than 5 mmHg. Reading and analyzing the ABP data has been previously described Journal of Hypertension
[20,21]. All patients were instructed to rest or sleep between midnight and 0600 h (night-time) and to maintain their usual activities between 0800 and 2200 h (daytime). Patients were instructed to keep their arm still and relaxed at their side during measurements. They were requested to avoid strenuous exercise and sleeping during daytime and to rise from bed after 6 : 00 a.m., even if they were awake earlier than this time of the day. Those who stated that they had not rested or slept during the night-time (n ¼ 2) were excluded from the study. All 24-h ABPM sessions had at least 72 valid BP measurements (average measurements 80.9 6.5). BP variability was measured using the weighted 24-h BP SD, computed as the weighted average of daytime and nighttime BP SD [22]. AASI was calculated as 1 minus the regression slope of DBP on SBP [23]. Daytime BP index was calculated by dividing the average daytime BP by the 95th BP percentile specific for each patient. BP load was calculated as the percentage of BP readings above the 95th BP percentile specific for each patient. The 24-h BP load was calculated as a weighted sum of the daytime and nighttime BP loads. ABP percentiles according to sex and height were used for the evaluation of ABP in patients aged 16 years or less, whereas adult ABP limits were used for older patients [6,19]. Using the combination of both office BP and ABP measurements, the patients were divided into four BP phenotypes. Patients who showed normotension or hypertension on the basis of both office BP and ABP measurements were characterized as having sustained normotension or hypertension, respectively. White-coat hypertension (WCH) was defined as office hypertension with ambulatory normotension, and masked hypertension as office normotension with ambulatory hypertension [24].
Carotid–femoral pulse wave velocity measurement The investigation took place in a quiet, semi-darkened, temperature-controlled room (218C). Before the examination, all participants rested in the recumbent position for about 15 min. The participants were instructed to refrain from eating, smoking and drinking beverages containing caffeine 3 h and also from drinking alcohol 10 h before measurement. cf-PWV estimation, according to the European Expert Consensus on Arterial Stiffness, was used to determine arterial stiffness [10]. cf-PWV was calculated according to the equation cf-PWV ¼ D(m)/t (s), where t denotes the transit time of the arterial pulse along the distance, and D the distance assimilated to the surface between the recording sites. D was measured directly using a centimeter tape, whereas t was obtained by the Complior System (Colson, Les Lilas, France) automatically. The transit time was quantified as the time delay between the feet of the two waveforms that were recorded simultaneously at the right common carotid artery and the right femoral artery (‘foot-to-foot’ method) using mechano-transducers directly applied on the skin. Subtracted cf-PWV was also calculated by using the 0.8 of D [10]. Central PP was calculated by pulse wave analysis. Complior device measures directly central (carotid) pressure waveforms. There is neither any mathematical model nor any transfer function. Complior uses the calibration method recognized by the scientific www.jhypertension.com
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experts using mean and diastolic pressure to calibrate the carotid signal [25,26]. Patients remained in the supine position and were advised neither to speak nor to sleep during the measurements. The same doctor, who was unaware of the BP measurements, conducted all the measurements under the previously described conditions. Reproducibility of the measurements from our group has been reported previously [21]. Spurious systolic hypertension was defined as brachial SBP higher than or equal to the 95th percentile for age, sex and height, brachial DBP lower than the 95th percentile for age, sex and height, and central PP lower than the 90th percentile of the study population [27].
Statistical analysis The IBM SPSS 21.0 (SPSS Inc., Chicago, Illinois, USA) statistical package was used to analyze the data. Standard descriptive statistics, two-tailed Student’s t test, bivariate correlation analysis, linear regression analysis (stepwise criteria: probability of F to enter 0.050, probability of F to remove 0.100) and analysis of covariance (ANCOVA) were used. A P value less than 0.05 was considered statistically significant. The collinearity statistics tolerance (tolerance ¼ 1 Ri2, where Ri is the square multiple correlation of one variable with the other independent variables) was used for collinearity diagnostics. The default value for tolerance was 0.0001. All variables were necessary to pass this criterion in order to be included in an equation, regardless of the selection method used. The general linear model (GLM) univariate procedure provides regression analysis and analysis of variance for one dependent variable by one or more independent factors or covariates. The factor variables divide the population into groups. GLM is a general model that encompasses both analysis of variance (ANOVA) and regression. In GLM you can estimate random and mixed-effects models, perform post-hoc tests on estimated marginal means, and analyze ANCOVA and regression models (SPSS Base Applications Guide, SPSS Inc., Chicago, Illinois, USA).
RESULTS Demographic data, cf-PWV, office BP and ABP levels of the population are listed in Tables 1 and 2. ABP levels were TABLE 1. Patients’ characteristics and carotid–femoral pulse wave velocity values Variable
Mean SD
Age (years) Sex (male %) BMI (kg/m2) Total cholesterol (mg/dl) Triglycerides (mg/dl) Glucose (mg/dl) Current smokers (%) Family history hypertension (%) Alcohol (yes%) Dyslipidemia (%) Diabetes (%) cf-PWV (m/s) Subtracted cf-PWV (m/s)
12.0 5.0 61.7 24.3 6.0 167.9 31.5 89.2 42.8 90.2 36.6 7.6 29.4 8.2 7 4.5 7.1 1.7 5.7 1.4
cf-PWV, carotid–femoral pulse wave velocity.
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lower to normal-weight children and adolescents compared to overweight (112.92 11.22 vs. 118.45 10.62 mmHg; P < 0.05) and obese ones (112.92 11.22 vs. 119.99 10.99 mmHg; P < 0.001). Isolated systolic hypertension was found in 29.8% of the children and adolescents, and 11.5% of the population could be characterized as having ‘spurious’ systolic hypertension. Patients with ‘spurious’ systolic hypertension were 58.3% men and had increased BMI percentile (83.3% had BMI 97th percentile). With regard to BP classification, 72.7% of these patients had WCH and 27.3% had sustained hypertension. Carotid–femoral pulse wave velocity was higher in hypertensive compared with normotensive patients identified by ABP levels (Table 3). The differences in cf-PWV remained significant after adjustment for age and sex. Among the patients, 10.6% had cf-PWV values higher than the 95th percentile of the study population. PWV values adjusted for age, sex and BMI z-score did not differ between patients with and without family history of hypertension (6.99 0.31 versus 6.85 0.19; P ¼ 0.70), current smokers and nonsmokers (6.73 0.85 versus 6.70 0.16; P ¼ 0.97). In Pearson’s bivariate correlations analysis, cf-PWV showed significant correlations with age, height, weight, TABLE 2. Office blood pressure and ambulatory blood pressure levels Variable
Mean SD
Office SBP (mmHg) Office DBP mmHg Office heart rate (beats/min) Office PP (mmHg) SBP index SBP index Average 24-h SBP (mmHg) Average 24-h DBP (mmHg) Average 24-h heart rate (beats/min) Average 24-h PP (mmHg) 24-h SBP load (%) 24-h DBP load (%) Weighted 24-h SBP SD (mmHg) Weighted 24-h DBP SD (mmHg) 24-h heart rate SD (beats/min) Average daytime SBP (mmHg) Average daytime DBP (mmHg) Average daytime heart rate (beats/min) Average daytime PP (mmHg) Daytime SBP load (%) Daytime DBP load (%) Daytime SBP index Daytime SBP index Daytime SD SBP (mmHg) Daytime SD DBP (mmHg) Daytime SD Heart rate (beats/min) Average night-time SBP (mmHg) Average night-time DBP (mmHg) Average night-time heart rate (beats/min) Average night-time PP (mmHg) Night-time SD SBP (mmHg) Night-time SBP load (%) Night-time DBP load (%) Night-time SD DBP (mmHg) Night-time SD Heart rate (beats/min) Daytime-to-night-time SBP
126.4 16.1 75.8 12.7 89.7 17.7 49.5 12.0 0.99 0.12 0.84 0.21 117.4 12.1 68.5 7.8 86.9 13.3 48.9 8.5 16.0 19.5 8.0 12.5 12.1 2.9 11.2 2.3 12.8 3.0 119.5 12.3 70.7 8.1 90.0 14.1 48.8 8.5 17.6 19.9 10.0 14.7 0.93 0.08 0.86 0.09 11.3 2.8 10.5 2.4 11.9 3.2 111.8 12.7 62.8 8.6 78.8 12.9 48.9 9.2 10.6 3.5 29.0 29.7 9.8 15.3 9.3 2.7 9.1 3.4 1.07 0.07
PP, pulse pressure.
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Arterial stiffness in youth TABLE 3. Carotid–femoral pulse wave velocity by blood pressure classification Variable a
cf-PWV SE Subtracted cf-PWVa SE
Normotension
White-coat hypertension
6.696 0.262 5.390 0.213
Hypertension
Spurious hypertension
7.860 0.476 6.315 0.386
7.231 0.261 5.819 0.212
7.282 0.414 5.857 0.336
ABP, ambulatory blood pressure; BP, blood pressure; cf-PWV, carotid–femoral pulse wave velocity; SE, standard error. a Based on estimated marginal means, adjusted for age, weighted least-squares regression by sex and adjustment for Bonferroni’s multiple comparisons. P < 0.05 vs. normotension.
office SBP and DBP, 24-h SBP and DBP, weighted 24-h SBP SD, 24-h SBP and DBP load, 24-h MAP, 24-h MAP SD, daytime SBP, SD of daytime SBP, night-time SBP and DBP, SD of night-time SBP, night-time PP, and estimated central PP. No relationship was found between cf-PWV and any heart rate measurements (office, 24 h, 24-h heart rate variability) (Tables 4 and 5). No relationship was found between cf-PWV and AASI (Table 5). Linear regression analysis for weighted 24-h SBP variability and cf-PWV is shown in Fig. 1.
Carotid–femoral pulse wave velocity in different blood pressure phenotypes The 95% confidence interval (CI) of cf-PWV was 6.4–7.1 m/s in sustained normotensive patients (n ¼ 56), 6.4–7.9 m/s in WCH patients (n ¼ 48), 5.8–8.1 m/s in masked hypertension patients (n ¼ 5), and 6.1–8.0 m/s in sustained hypertensive patients (n ¼ 27). There were no statistically significant differences in cf-PWV among the above groups after adjustment for age and sex (WCH vs. normotensive patients; P ¼ 0.38, masked hypertension vs. normotensive patients; P ¼ 0.74, sustained hypertensive vs. sustained normotensive patients; P ¼ 0.63, Bonferroni’s adjustment for multiple comparisons). The results for masked hypertension and sustained hypertension were underpowered because of the small number of patients in these groups.
TABLE 4. Pearson’s correlations of carotid–femoral pulse wave velocity with anthropometric measures, office blood pressure levels and laboratory values cf-PWV (m/s) Variable Age (years) Height (cm) Weight (kg) BMI z-score Office SBP (mmHg) Office SBP z-score Office SBP index Office DBP (mmHg) Office DBP z-score Office DBP index Office heart rate (beats/min) Heart rate measured by Complior (beats/min) Glucose (mg%) Total cholesterol (mg%) Triglycerides (mg%)
r
P
0.233 0.263 0.229 0.106 0.197 0.05 0.061 0.23 0.09 0.11 0.004 0.077 0.016 0.212 0.023
0.0001 0.0001 0.0001 0.09 0.05 0.57 0.55 0.01 0.28 0.287 0.93 0.23 0.88 0.06 0.84
BP, blood pressure; cf-PWV, carotid–femoral pulse wave velocity. Statistically significant values are highlighted in bold.
Journal of Hypertension
Analysis of covariance for the relationship of carotid–femoral pulse wave velocity with blood pressure variability after adjustment for demographics and other risk factors In ANCOVA, cf-PWV was significantly associated with weighted 24-h SBP variability (b ¼ 0.28, 95% CI of b 0.037–0.536, P < 0.05). Age (b ¼ 0.117, P ¼ 0.78), sex (b ¼ 0.083, P ¼ 0.83), office SBP (b ¼ 1.297, P ¼ 0.56) and office DBP indices (b ¼ 1.184, P ¼ 0.35), 24-h SBP (b ¼ 2.405, P ¼ 0.51) and DBP (b ¼ 0.555, P ¼ 0.86) indices, and BMI z-score (b ¼ 0.063, P ¼ 0.71) were not significant determinants of cf-PWV in the model (model’s R2 ¼ 0.144). The ratio of daytime to night-time SBP was not associated with cf-PWV (b ¼ 2.165, P ¼ 0.25). The role of obesity was further investigated in another model where cf-PWV was significantly associated with age (b ¼ 0.675, P < 0.05) and weighted 24-h SBP variability (b ¼ 0.114, P < 0.05), but not with overweight versus obesity status (b ¼ 0.030, P ¼ 0.94) or normal-weight versus obesity TABLE 5. Pearson’s correlations of carotid–femoral pulse wave velocity with ambulatory blood pressure parameters and estimated central pulse pressure cf-PWV (m/s) Variable 24-h SBP (mmHg) Weighted 24-h SBP SD (mmHg) 24-h SBP load (%) 24-h DBP (mmHg) Weighted 24-h DBP SD (mmHg) 24-h DBP load (%) 24-h MAP (mmHg) 24-h MAP SD (mmHg) 24-h PP (mmHg) Average 24-h heart rate (beats/min) SD 24-h heart rate (beats/min) Daytime SBP (mmHg) SD daytime SBP (mmHg) Daytime DBP (mmHg) SD daytime DBP (mmHg) Daytime PP (mmHg) Daytime SBP index Daytime DBP index Night-time SBP (mmHg) SD night-time SBP (mmHg) Night-time DBP (mmHg) SD night-time DBP (mmHg) Night-time PP (mmHg) Daytime-to-night-time SBP AASI Estimated central PP (mmHg)
r
P
0.239 0.251 0.216 0.196 0.106 0.517 0.22 0.21 0.163 0.131 0.061 0.221 0.273 0.167 0.069 0.164 0.153 0.139 0.266 0.181 0.232 0.88 0.214 0.818 0.167 0.223
0.01 0.001 0.012 0.05 0.22 0.067 0.001 0.01 0.06 0.13 0.48 0.01 0.001 0.053 0.422 0.056 0.075 0.107 0.005 0.05 0.01 0.31 0.024 0.256 0.058 0.001
AASI, ambulatory arterial stiffness index; ABP, ambulatory blood pressure; cf-PWV, carotid–femoral pulse wave velocity; MAP, mean arterial pressure; PP, pulse pressure. Statistically significant values are highlighted in bold.
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Stabouli et al. R2 linear = 0.063
12 000
y = 5.23-0.13*x
cf-PWV (m/s)
b
P value
R2
0.020 0.036 0.014 0.006 0.153 0.005 0.140 0.049 0.088
0.199 0.078 0.550 0.870 0.044 0.956 0.669 0.175 0.420
0.176
0.016 0.020 0.014 0.021 0.042 0.008 0.147 0.069 0.009
0.266 0.305 0.509 0.533 0.459 0.917 0.660 0.046 0.936
0.149
by office
0.841
0.441
0.196
by ABP
0.157
0.886
0.16 0.018 1.235 0.048 0.105
0.037 0.830 0.194 0.149 0.312
by office
0.539
0.639
by ABP
0.227
0.845
0.048 0.003 1.056 0.068 0.064
0.398 0.969 0.285 0.037 0.534
cf-PWV (m/s)
10 000 8 000 6 000 4 000 2 000 000
5.0
10.0
15.0
20.0
25.0
Weighted 24-h SBP SD (mmHg) FIGURE 1 Linear regression analysis between carotid–femoral pulse wave velocity and weighted 24-h SBP variability.
status (b ¼ 0.371, P ¼ 0.20). cf-PWV was 6.98 1.56 m/s in patients clasified as obese, compared with 7.17 2.06 m/s in overweight and 7.26 1.74 m/s in normal-weight patients, but the differences between the groups did not reach statistical significance. Fasting serum glucose, total cholesterol and triglycerides were not significant determinants of cf-PWV (b ¼ 0.001, P ¼ 0.81; b ¼ 0.011, P ¼ 0.11; b ¼ 0.003, P ¼ 0.61, respectively). Finally, AASI (b ¼ 0.796, P ¼ 0.48), 24-h PP (b ¼ 0.006, P ¼ 0.77), 24-h SBP and DBP loads (b ¼ 0.884, P ¼ 0.34; b ¼ 0.797, P ¼ 0.64, respectively) and office SBP and DBP z-scores (b ¼ 0.18, P ¼ 0.213; b ¼ 0.13, P ¼ 0.294, respectively) were also not significantly associated with cf-PWV (Supplementary Table 7, http:// links.lww.com/HJH/A405). The role of daytime and night-time SBP and DBP variability and the presence of office or ambulatory hypertension were further investigated (Table 6). There was a strong relationship between daytime SBP variability and weighted 24-h SBP variability (r ¼ 0.88, P < 0.0001). Both variables are related to cf-PWV (r ¼ 0.25 and 0.27, P < 0.01). When we forced the daytime SBP variability in the same model with weighted 24-h SBP variability, then the model’s R2 decreased and both variables lost the significance, suggesting that daytime SBP variability is neither stronger nor a better determinant of cf-PWV compared to weighted 24-h SBP variability.
DISCUSSION The present study showed significant correlations between cf-PWV and ABP parameters in children and adolescents. The main finding was that weighted 24-h and daytime SBP variability exhibited an independent association with cf-PWV. Hypertension was accompanied with increased cf-PWV. Obesity was not a significant determinant of cf-PWV in this study, as BMI z-score did not correlate with cf-PWV in any model. These findings suggest that short-term BP fluctuations may have an impact on structural and functional vascular properties in young patients independent of absolute BP levels and adiposity. Several studies in adults have shown a relationship between short-term BP variability and target organ damage 92
TABLE 6. Analysis of covariance for the relationship of carotid– femoral pulse wave velocity with daytime and nighttime SBP variability
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Model 1a Office SBP Office DBP Daytime SBP Daytime DBP SD daytime SBP SD daytime DBP Sex (male vs. female) Age (years) BMI z-score Model 2a Office SBP Office DBP Night-time SBP Night-time DBP SD daytime SBP SD daytime DBP Sex (male vs. female) Age (years) BMI z-score Model 1b Presence of hypertension BP (yes–no) Presence of hypertension (yes–no) SD daytime SBP SD daytime DBP Sex (male vs. female) Age (years) BMI z-score Model 2b Presence of hypertension BP (yes–no) Presence of hypertension (yes–no) SD night-time SBP SD night-time DBP Sex (male vs. female) Age (years) BMI z-score
0.152
ABP, ambulatory blood pressure; PP, pulse pressure. Statistically significant values are highlighted in bold.
or cardiovascular outcomes using different methods for the quantification of BP variability [28–30]. In the present study, BP variability was defined as weighted 24-h SD of BP, which is considered a better index of BP variability. Analysis of daytime and night-time BP variability in our population suggested that daytime compared to night-time BP variability exerts a more important effect in arterial stiffness in youth. Night-time variability maybe less reproducible in the young and maybe more than one ABPM studies are needed. On the contrary, weighted 24-h BP SD that has been introduced by Bilo et al. [22] is more reproducible as a method of estimation of BP variability. Weighted 24-h SD overcomes the interference of night-time BP fall, offering assessment of BP variability all over the 24-h period and has been suggested to be a better predictor of organ damage and cardiovascular risk [22]. BP variability in children and adolescents has been associated with low birth weight, obesity, BP levels and age [31,32]. The changes in BP variability with age were studied in a diverse ethnic population over a 15-year period and demonstrated that BP Volume 33 Number 1 January 2015
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Arterial stiffness in youth
variability increased with age. Other determinants of BP variability were mean ABP values, male sex, obesity, and socioeconomic status [32]. Impaired baroreflex sensitivity has been suggested in children with elevated BP levels [33]. Other possible mechanisms may include enhanced activation of the sympathetic nervous system or inflammatory factors promoting vasoconstriction and facilitating acute BP increases. The effect of BP variability on cf-PWV may have an early origin as suggested by the young age of the study population consisting of either normotensive patients or newly diagnosed hypertensive patients. In a previous study by our group in healthy young volunteers, we have shown that weighted 24-h SBP variability is a predictor of increased cf-PWV and early vascular aging [21]. Increased weighted 24-h BP variability may result in repetitive fluctuations of shear stress on arterial wall that results in morphological changes and arterial stiffening. The independent association between weighted 24-h SBP variability and cf-PWV may alternatively imply a common pathogenetic mechanism in youth. Determinants of PWV have been reported to be age, sex and absolute BP values, which, as mentioned above, are also predictors of BP variability [34,35]. Thus, the question of whether SBP variability has a causative role in or it is a result of arterial stiffening needs to be clarified by further studies. Carotid–femoral pulse wave velocity is accepted as the most reliable method for the measurement of arterial stiffness in adults with prognostic significance for cardiovascular morbidity and mortality for coronary events and fatal strokes [36–39]. However, its predictive value remains yet to be established in young patients. In the current study, we aimed to detect early vascular changes in children and adolescents in the absence of any known clinical manifestation of cardiovascular disease. The population was at an increased risk for future cardiovascular events in the context that they have been referred to a hypertension center for suspected hypertension. Despite referral from primary care practitioners, the majority of patients were found to be normotensive both in office BP and ABP measurements. Normotensive patients had lower cf-PWV compared to those with hypertension by ABP levels. Increased PWV in youth has been associated with conditions that confer increased cardiovascular risk such as diabetes and hypertension [11,14–16,40,41]. The parameters 24-h PP and AASI, which are derived from 24-h ABPM, have been proposed as surrogate markers of arterial stiffness [42–47]. In children and adolescents, PP and AASI are not very well studied. We have previously reported that 24-h PP could predict left ventricular mass index, and it presents significant correlations with carotid intima-media thickness in children and adolescents referred to a hypertension clinic [48,20]. In another study of 82 referred children and adolescents, a close association of 24-h PP was demonstrated with left ventricular mass index and cf-PWV, but not with AASI [15]. In the present study, AASI also did not correlate with cf-PWV. PP was associated with cf-PWV in simple bivariate correlations, but only weighted 24-h and daytime SBP variability were independent determinants in the ANCOVA analysis. The potential explanation of these findings may lie in the different Journal of Hypertension
mechanisms of BP-induced arterial stiffening. In young patients with more elastic arteries, the SBP elevation and the increase in 24-h PP may be mediated by the exaggeration of the amplification phenomenon. On the contrary, BP fluctuations interfering to cyclic stress on the arterial wall may have a more significant contribution to arterial stiffening. The majority of the patients in the study had systolic hypertension by office BP levels and 29.8% had isolated systolic hypertension. About one-third of these patients had estimated central aortic PP in the normal range of the study population and could be characterized as having ‘spurious’ hypertension. Interestingly, in our population, children and adolescents with ‘spurious’ hypertension were more likely to have WCH, which has been associated with an increased cardiovascular risk in children and adolescents [24,49]. Further studies may evaluate the importance of this finding. In this cross-sectional study, we were unable to determine the causative effect or mechanism underlying the relationship among BP variability and cf-PWV. Another limitation of the study is that the patients were not randomly selected as they were referred to a hypertension center. However, a large proportion of the children and adolescents were diagnosed as sustained normotensive patients after the evaluation. Larger longitudinal studies are needed to assess the effect of BP variability on progression of arterial stiffness in young populations. Another limitation of the study is that cf-PWV was explained from BP variability only in a small percentage in the models (14.4–19.6%), suggesting that other important factors can influence arterial stiffness beyond BP fluctuations. In the current study we hypothesized that newer parameters of ABPM such as weighted 24-h and daytime SBP variability could have an impact on arterial stiffness independent of the classical BP measurements. This study provides evidence that arterial stiffness is an ongoing process starting early in life, advancing with age and modified from different factors. In this pediatric and adolescent population, 10.6% had cf-PWV values higher than the 95th percentile of the population, suggesting an early onset of arteriosclerosis [50]. These extreme values of stiffness may be followed up for the possibility of early and aggressive interventions, especially as far as the lifestyle of these young patients is concerned.
ACKNOWLEDGEMENTS Conflicts of interest There are no conflicts of interest.
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Reviewers’ Summary Evaluations
Reviewer 2
Reviewer 1 A novel finding provided by the authors is the existence of a correlation between blood pressure variability, assessed by 24 h monitoring, and pulse wave velocity in a population of children and adolescents. This information is useful in understanding the pathophysiology of vascular compliance in this age range. Among the limitations of the study are the heterogeneity and wide age range of the study population, spanning from paediatric age subjects to young adults. Additional studies will be necessary, possibly performed in a higher number of subjects with more homogeneous characteristics, in order to confirm and validate the present results.
Journal of Hypertension
The strengths of the study are the relatively large group of children included and the detailed description of the hemodynamic phenotype. It was found that in childhood PWV does not differ significantly across BP status from normotension to sustained hypertension. However, significant relationships between BP variability and increased PWV were observed. This finding suggest that increased BP variability may precede early vascular damage. A limitation of the study is lack of data on relations between PWV and other markers of hypertensive damage such as left ventricular hypertrophy and increased intima–media thickness.
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