Abstract
The primary aim of the present study was to identify the hemodynamic correlates of both steady and pulsatile blood pressure in community-dwelling older adults. In 3,762 adults aged 70–89 years, we observed that significant hemodynamic determinants of systolic blood pressure included arterial stiffness as measured by aortic pulse wave velocity, stroke volume (via echocardiography), arterial wave reflection, left ventricular ejection time, and upstroke time. The strongest influence was exerted by arterial stiffness. The steady state component of blood pressure, mean arterial pressure, was associated with both cardiac index and total peripheral resistance (TPR), but was more strongly associated with TPR. Results were similar when participants taking antihypertensive medications were excluded from analyses. The overall findings suggest that mean arterial pressure is associated strongly with TPR and that significant hemodynamic correlates of systolic blood pressure included arterial stiffness, stroke volume, and arterial wave reflection.
Keywords: aging, hypertension, arterial compliance, systemic hemodynamics
Introduction
Arterial pressure increases progressively with advancing age, resulting in a high prevalence of essential hypertension. This rise in blood pressure with age is a major contributor to age-related increases in numerous cardiovascular disorders1. While systolic blood pressure rises continuously, diastolic blood pressure plateaus and tends to decline after 50–60 years of age2. Accordingly, pulse pressure increases markedly with advancing age, resulting in a high prevalence of isolated systolic hypertension3.
Although the trend of age-associated increases in blood pressure is well established, it remains unclear what hemodynamic factors determine blood pressure levels in older adults. Arterial blood pressure can be divided into both steady state and pulsatile primary components. The steady state component of blood pressure is represented by mean arterial pressure and is a critically important cardiovascular measure from the physiological standpoint, as it is the effective pressure that determines perfusion to the vital organs. Mean arterial pressure is determined exclusively by cardiac output and total peripheral resistance as governed by Ohm’s law. The hemodynamic factors that influence the pulsatile component on the other hand, are much more complex. Systolic blood pressure is governed by a number of hemodynamic factors, including arterial stiffness, stroke volume, and left ventricular ejection fraction, whereas the primary hemodynamic determinants of diastolic pressure include total peripheral resistance, heart rate, arterial stiffness, and systolic blood pressure. The relative contribution of each hemodynamic factor is currently unknown, especially in older adults, as most of the available evidence is derived from circulatory modeling studies or comparisons with a single hemodynamic variable4–6.
We evaluated a comprehensive number of hemodynamic determinants of blood pressure in Atherosclerosis Risk in Communities (ARIC) Study cohort. The availability of comprehensive tonometric measures in ARIC provided an added opportunity to separately interrogate correlates of both peripheral and central blood pressure. The latter approach is clinically important in light of increasing evidence that central, compared with peripheral, blood pressure may be more predictive of cardiovascular and other morbid outcomes7. Accordingly, the primary aim of the present study was to characterize the hemodynamic determinants of steady state and pulsatile blood pressure in community-dwelling older adult participants of the ARIC study.
Methods
Subjects
The ARIC Study is an ongoing, population-based longitudinal study involving four US communities (Forsyth County, NC, Jackson, MS, Minneapolis, MN, and Washington County, MD). A total of 6,533 participants (65% response rate from 10,036 eligible participants) attended ARIC study visit 5 (in years 2011 to 2013) and underwent a standardized examination8. For the present analyses, we excluded participants with missing information on blood pressure, arterial stiffness, and/or echocardiography, BMI ≥40 kg/m2, major arrhythmias (Minnesota codes 8-1-3, 8-3-1, and 8-3-2: ≥10% atrial and ventricular premature beats, atrial fibrillation or flutter), peripheral vascular disease (aortic aneurysms, abdominal aorta ≥5 cm, history of aortic or peripheral revascularization or presence of an aortic graft, aortic stenosis), other major cardiovascular disease (history of coronary artery disease, heart failure, or stroke), and moderate or greater aortic regurgitation. Participants who self-identified as Asian and African American from Minnesota and Maryland field centers were excluded due to small numbers. After exclusions, the final analytic sample included 3,762 participants. Institutional review boards approved the study protocol at each field center and participating institution, and all study participants provided written informed consent.
Measurements
Participants were asked not to consume food or drinks and to refrain from tobacco and vigorous physical activity after midnight prior to the visit or for 8 hours prior to the visit. Participants were also asked to bring all prescription and nonprescription medications taken within 2 weeks. Blood samples were obtained following a standardized venipuncture protocol and were assayed in ARIC central laboratories. Diabetes was defined as fasting glucose ≥126 mg/dl, non-fasting glucose ≥200 mg/dl, antidiabetic medication use, or self-reported diagnosis of diabetes.
Brachial blood pressure (systolic, mean, and diastolic blood pressure) was measured twice with the participants in the supine position using oscillometric automated sphygmomanometer (VP-1000 Plus, Omron Healthcare, Kyoto, Japan), and the average measurement was used for analyses. Stroke volume and cardiac output were calculated based on 2D echocardiographic measurements (IE33, Philips Healthcare, Andover, MA) performed with excellent reproducibility in our core laboratory, as previously described9. Echocardiographic measures were indexed to body surface area, where appropriate. Total peripheral resistance was calculated as mean arterial pressure divided by the cardiac index. Carotid-femoral pulse wave velocity, an index of arterial stiffness, and carotid artery pressure waveforms were obtained using an automatic vascular screening device (VP-1000 Plus, Omron Healthcare, Kyoto, Japan) as previously described10 with excellent reproducibility11. Carotid and femoral arterial pressure waveforms were acquired for 30 seconds by applanation tonometry sensors attached on the left common carotid artery (via neck collar) and left femoral artery (via elastic tape around the hip). Augmentation index, an index of arterial wave reflection, carotid systolic pressure, ejection time, and upstroke time were obtained from the carotid pressure waveform analyses5. Augmentation index measured by this machine is strongly associated with that obtained with SphygmoCor12. Vascular and cardiac measurements were performed on different days.
Statistical analyses
All statistical analyses were conducted using SAS version 9.4 (Cary, NC). Associations between blood pressure and hemodynamic variables were evaluated using multivariable linear regression and partial correlational analyses. Adjusted models included age, sex, race, body mass index, and current smoking status. Separate analyses were performed in the total sample of 3,762 participants and in the subgroup of 1,204 participants not taking antihypertensive medications at the time of the examination. A two-sided P<0.05 was considered statistically significant.
Results
The average systolic blood pressure was 137±17 mmHg and a majority of participants (68%) were taking antihypertensive medications at the time of the examination (Table 1).
Table 1.
Characteristics of the study participants
| Characteristic | Total Sample (N=3,762) |
|---|---|
| Age (year) | 75±5 |
| Women (%) | 63 |
| Black (%) | 21 |
| Body mass index (kg/m2) | 28±4 |
| Obesity (%) | 30 |
| Diabetes (%) | 23 |
| Total cholesterol (mg/dl) | 4.9±1.0 |
| LDL cholesterol (mg/dl) | 2.8±0.9 |
| HDL cholesterol (mg/dl) | 1.4±0.4 |
| Triglycerides (mg/dl) | 1.4±0.7 |
| eGFR (ml/min) | 71.7±16.1 |
| Antihypertensive medication (%) | 68 |
| Current smoker (%) | 5 |
| Heart rate (bpm) | 65±10 |
| Systolic BP (mmHg) | 137±17 |
| Diastolic BP (mmHg) | 73±9 |
| Mean BP (mmHg) | 100±13 |
| Carotid systolic BP (mmHg) | 144±22 |
| Carotid AI (%) | 19.5±16.0 |
| cfPWV (cm/sec) | 1146±295 |
| SV index (ml/m2) | 28.1±6.0 |
| CO index (ml/min/m2) | 1801±391 |
| TPR (U) | 0.03±0.01 |
| LVEF (%) | 66±10 |
| Reduced LVEF <30% (%) | 0.05 |
eGFR=estimated glomerular filtration rate, BP=blood pressure, AI= augmentation index, cfPWV=carotid-femoral pulse wave velocity, SV=stroke volume, CO=cardiac output, TPR=total peripheral resistance, LVEF=left ventricular ejection fraction.
Values are shown as mean±SD or percent frequency.
Table 2 displays multivariable-adjusted associations of both brachial and carotid systolic blood pressure measures with hemodynamic variables. All the hemodynamic variables examined were significantly associated with both brachial and carotid systolic blood pressure except for ejection fraction. For both brachial and carotid systolic pressure, the hemodynamic variables that contributed the most variation to systolic pressure (as represented by the partial R2 value) were arterial stiffness followed by augmentation index and ejection time. The results were similar when the analyses were repeated after excluding the participants taking antihypertensive medications.
Table 2.
Multivariable-adjusted hemodynamic correlates of brachial and carotid systolic pressures
| Hemodynamic | Total sample (n=3,762) | Non-medicated (n=1,204) | ||||
|---|---|---|---|---|---|---|
| Parameter | Coef. (SE) |
Partial R2 | P-value | Coef. (SE) |
Partial R2 | P-value |
| Brachial systolic pressure | ||||||
| cfPWV | 0.02 (0.0009) |
0.134 | <0.0001 | 0.02 (0.002) |
0.121 | <0.0001 |
| SV index | 1.71 (0.30) |
0.009 | <0.0001 | 1.80 (0.50) |
0.011 | 0.0004 |
| AI | 4.50 (0.29) |
0.067 | <0.0001 | 4.17 (0.49) |
0.060 | <0.0001 |
| LVEF | −0.05 (0.29) |
0.000009 | 0.86 | −0.66 (0.49) |
0.002 | 0.18 |
| ET | 3.37 (0.28) |
0.040 | <0.0001 | 2.35 (0.51) |
0.017 | <0.0001 |
| UT | −2.15 (0.28) |
0.016 | <0.0001 | −2.25 (0.50) |
0.017 | <0.0001 |
|
| ||||||
| Carotid systolic pressure | ||||||
| cfPWV | 0.02 (0.001) |
0.089 | <0.0001 | 0.02 (0.002) |
0.091 | <0.0001 |
| SV index | 2.97 (0.38) |
0.016 | <0.0001 | 2.65 (0.63) |
0.014 | <0.0001 |
| AI | 4.83 (0.37) |
0.045 | <0.0001 | 4.22 (0.62) |
0.039 | <0.0001 |
| LVEF | 0.70 (0.36) |
0.001 | 0.05 | 0.11 (0.61) |
0.00003 | 0.86 |
| ET | 5.94 (0.34) |
0.072 | <0.0001 | 4.53 (0.63) |
0.040 | <0.0001 |
| UT | −2.35 (0.36) |
0.011 | <0.0001 | −2.54 (0.62) |
0.014 | <0.0001 |
cfPWV=carotid-femoral pulse wave velocity, SV=stroke volume, LVEF=left ventricular ejection fraction, AI=augmentation index, ET=ejection time, UT=upstroke time.
All analyses were adjusted for age, sex, black race, BMI, diabetes, and current smoking status. Coefficients represent change in systolic pressure per 1-SD change in the hemodynamic parameter.
In an attempt to determine if the associations between blood pressure and hemodynamic parameters are affected by age, the study cohort was divided according to the age categories that approximate tertiles (<75 years, 75 to <80 years, and ≥80 years) (Table 3). The strength of associations between arterial stiffness and systolic BP became weaker with increasing age while associations with stroke volume and augmentation index became stronger.
Table 3.
Multivariable-adjusted hemodynamic correlates of brachial and carotid systolic pressures (total sample, N=3,762), by age group
| Age <75 years | Age 75 to <80 years | Age ≥80 years | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Parameter | Coef. (SE) | Partial R2 | P-value | Coef. (SE) | Partial R2 | P-value | Coef. (SE) | Partial R2 | P-value |
| Brachial SBP | |||||||||
| cfPWV | 0.03 (0.001) | 0.158 | <0.0001 | 0.02 (0.002) | 0.123 | <0.0001 | 0.02 (0.002) | 0.094 | <0.0001 |
| SV index | 1.32 (0.40) | 0.006 | 0.0009 | 2.04 (0.57) | 0.013 | 0.0004 | 2.55 (0.69) | 0.020 | 0.002 |
| AI | 3.82 (0.38) | 0.051 | <0.0001 | 4.73 (0.55) | 0.074 | <0.0001 | 5.93 (0.70) | 0.101 | <0.0001 |
| LVEF | −0.95 (0.40) | 0.003 | 0.02 | 0.99 (0.52) | 0.004 | 0.06 | 0.69 (0.63) | 0.002 | 0.27 |
| ET | 2.94 (0.38) | 0.029 | <0.0001 | 3.25 (0.52) | 0.038 | <0.0001 | 4.48 (0.59) | 0.075 | <0.0001 |
| UT | −1.62 (0.39) | 0.009 | <0.0001 | −2.11 (0.53) | 0.016 | <0.0001 | −3.35 (0.63) | 0.039 | <0.0001 |
| Carotid SBP | |||||||||
| cfPWV | 0.03 (0.002) | 0.106 | <0.0001 | 0.02 (0.002) | 0.080 | <0.0001 | 0.02 (0.002) | 0.071 | <0.0001 |
| SV index | 2.42 (0.51) | 0.011 | <0.0001 | 3.21 (0.72) | 0.019 | <0.0001 | 4.25 (0.81) | 0.036 | <0.0001 |
| AI | 4.03 (0.49) | 0.033 | <0.0001 | 5.07 (0.72) | 0.049 | <0.0001 | 6.35 (0.85) | 0.073 | <0.0001 |
| LVEF | −0.63 (0.52) | 0.0007 | 0.22 | 2.19 (0.66) | 0.011 | 0.0009 | 1.75 (0.75) | 0.007 | 0.02 |
| ET | 5.57 (0.48) | 0.060 | <0.0001 | 5.79 (0.66) | 0.069 | <0.0001 | 6.72 (0.70) | 0.108 | <0.0001 |
| UT | −1.63 (0.50) | 0.005 | 0.001 | −2.56 (0.67) | 0.014 | 0.0002 | −3.53 (0.77) | 0.028 | <0.0001 |
SBP=systolic blood pressure, cfPWV=carotid-femoral pulse wave velocity, SV=stroke volume, LVEF=left ventricular ejection fraction, AI=augmentation index, ET=ejection time, UT=upstroke time.
All analyses were adjusted for age, sex, black race, BMI, and current smoking status. Coefficients represent change in systolic pressure per 1-SD change in the hemodynamic parameter.
When analyses were repeated using pulse pressure, the overall results were similar to those observed for systolic blood pressure (Table 4). Ejection time was the most prominent hemodynamic determinant of variation in both brachial and systolic pulse pressure in the total study sample, followed by arterial stiffness. Stroke volume, in addition to augmentation index, was also among the hemodynamic measures that was observed to contribute significant variation to measures of pulse pressure. When the participants were divided into age tertiles, contribution of ejection time to pulse pressure became greater with increasing age (Table 5).
Table 4.
Multivariable-adjusted hemodynamic correlates of brachial and carotid pulse pressures
| Hemodynamic | Total sample (n=3,762) | Non-medicated (n=1,204) | ||||
|---|---|---|---|---|---|---|
| Parameter | Coef. (SE) |
Partial R2 | P-value | Coef. (SE) |
Partial R2 | P-value |
| Brachial pulse pressure | ||||||
| cfPWV | 0.01 (0.0006) |
0.083 | <0.0001 | 0.01 (0.001) |
0.069 | <0.0001 |
| SV index | 2.22 (0.20) |
0.030 | <0.0001 | 1.90 (0.34) |
0.024 | <0.0001 |
| AI | 2.14 (0.20) |
0.030 | <0.0001 | 1.90 (0.33) |
0.026 | <0.0001 |
| LVEF | 0.74 (0.20) |
0.004 | 0.0002 | 0.04 (0.33) |
0.00001 | 0.90 |
| ET | 4.03 (0.18) |
0.112 | <0.0001 | 3.11 (0.33) |
0.063 | <0.0001 |
| UT | −1.31 (0.19) |
0.011 | <0.0001 | −1.29 (0.34) |
0.011 | 0.0001 |
|
| ||||||
| Carotid pulse pressure | ||||||
| cfPWV | 0.01 (0.001) |
0.042 | <0.0001 | 0.014 (0.002) |
0.045 | <0.0001 |
| SV index | 3.51 (0.31) |
0.032 | <0.0001 | 2.73 (0.49) |
0.023 | <0.0001 |
| AI | 2.42 (0.31) |
0.016 | <0.0001 | 2.03 (0.48) |
0.014 | <0.0001 |
| LVEF | 1.38 (0.30) |
0.005 | <0.0001 | 0.45 (0.48) |
0.0007 | 0.36 |
| ET | 6.51 (0.27) |
0.122 | <0.0001 | 5.20 (0.48) |
0.082 | <0.0001 |
| UT | −1.46 (0.30) |
0.006 | <0.0001 | −1.30 (0.49) |
0.005 | 0.008 |
cfPWV=carotid-femoral pulse wave velocity, SV=stroke volume, LVEF=left ventricular ejection fraction, AI=augmentation index, ET=ejection time, UT=upstroke time.
All analyses were adjusted for age, sex, black race, BMI, diabetes, and current smoking status. Coefficients represent change in pulse pressure per 1-SD change in the hemodynamic parameter.
Table 5.
Multivariable-adjusted hemodynamic correlates of brachial and carotid pulse pressures (total sample, N=3762), by age group
| Age <75 years | Age 75 to <80 years | Age ≥80 years | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Parameter | Coef. (SE) | Partial R2 | P-value | Coef. (SE) | Partial R2 | P-value | Coef. (SE) | Partial R2 | P-value |
| Brachial PP | |||||||||
| cfPWV | 0.01 (0.0009) | 0.100 | <0.0001 | 0.01 (0.001) | 0.077 | <0.0001 | 0.01 (0.001) | 0.072 | <0.0001 |
| SV index | 1.78 (0.27) | 0.020 | <0.0001 | 2.62 (0.38) | 0.044 | <0.0001 | 3.03 (0.48) | 0.051 | <0.0001 |
| AI | 1.59 (0.26) | 0.018 | <0.0001 | 2.50 (0.38) | 0.043 | <0.0001 | 2.88 (0.52) | 0.044 | <0.0001 |
| LVEF | 0.21 (0.28) | 0.0003 | 0.44 | 1.43 (0.35) | 0.016 | <0.0001 | 1.24 (0.45) | 0.010 | 0.006 |
| ET | 3.66 (0.25) | 0.093 | <0.0001 | 3.72 (0.034) | 0.104 | <0.0001 | 5.06 (0.40) | 0.178 | <0.0001 |
| UT | −0.84 (0.26) | 0.005 | 0.002 | −1.68 (0.36) | 0.021 | <0.0001 | −2.03 (0.46) | 0.026 | <0.0001 |
| Carotid PP | |||||||||
| cfPWV | 0.02 (0.001) | 0.055 | <0.0001 | 0.01 (0.002) | 0.033 | <0.0001 | 0.01 (0.002) | 0.041 | <0.0001 |
| SV index | 2.88 (0.42) | 0.22 | <0.0001 | 3.94 (0.59) | 0.040 | <0.0001 | 4.73 (0.69) | 0.057 | <0.0001 |
| AI | 1.80 (0.40) | 0.010 | <0.0001 | 2.66 (0.60) | 0.019 | <0.0001 | 3.34 (0.75) | 0.027 | <0.0001 |
| LVEF | 0.47 (0.43) | 0.0005 | 0.28 | 2.60 (0.54) | 0.021 | <0.0001 | 2.04 (0.65) | 0.013 | 0.002 |
| ET | 6.16 (0.38) | 0.107 | <0.0001 | 6.18 (0.52) | 0.113 | <0.0001 | 7.26 (0.57) | 0.169 | <0.0001 |
| UT | −0.77 (0.41) | 0.002 | 0.06 | −2.21 (0.56) | 0.014 | <0.0001 | −2.14 (0.65) | 0.014 | 0.001 |
PP=pulse pressure, cfPWV=carotid-femoral pulse wave velocity, SV=stroke volume, LVEF=left ventricular ejection fraction, AI=augmentation index, ET=ejection time, UT=upstroke time.
All analyses were adjusted for age, sex, black race, BMI, and current smoking status. Coefficients represent change in pulse pressure per 1-SD change in the hemodynamic parameter.
The multivariable-adjusted hemodynamic correlates of mean blood pressure are shown in Table 6. We observed relatively small contributions of CI and TPR to variation in MBP in regression models that adjusted for all the clinical covariates. Mean blood pressure was associated with both cardiac index and total peripheral resistance; however, total peripheral resistance was the primary hemodynamic determinant of variation in mean blood pressure. The results were similar when the participants who had been taking antihypertensive medications were excluded from these analyses.
Table 6.
Multivariable-adjusted hemodynamic correlates of mean blood pressure based on Ohm’s law
| Hemodynamic | Total sample (n=3,762) | Non-medicated (n=1,204) | ||||
|---|---|---|---|---|---|---|
| Parameter | Coef. (SE) |
Partial R2 | P-value | Coef. (SE) |
Partial R2 | P-value |
| Cardiac index | 0.74 (0.21) |
0.003 | 0.0005 | 1.11 (0.38) |
0.007 | 0.003 |
| TPR | 6.29 (0.21) |
0.151 | <0.0001 | 6.29 (0.39) |
0.178 | <0.0001 |
TPR=total peripheral resistance
All analyses were adjusted for age, sex, black race, BMI, and current smoking status. Coefficients represent change in mean blood pressure per 1-SD change in the hemodynamic parameter.
Discussion
Arterial blood pressure progressively increases with advancing age, resulting in a high prevalence of essential hypertension in the population at large. Indeed, in our community-based study sample of predominantly older adults, the prevalence of hypertension was over 70%. As implied by the term “essential” hypertension, the physiological factors that contribute to the steady rise in blood pressure in aging adults remain largely unknown. Thus, in the present study, we interrogated the distinct steady state and pulsatile components of blood pressure and examined the hemodynamic correlates of these components measured both peripherally and centrally.
The steady state component of blood pressure is characterized by mean arterial blood pressure and is determined by cardiac output and peripheral resistance via the Ohm’s law. Of these two factors, total peripheral resistance displayed the more dominant influence on mean arterial pressure in the present sample of community-dwelling older adults. These results are consistent with previous small-scale cross-sectional studies showing that the elevation in mean arterial pressure with aging is related to an increase in total peripheral resistance because cardiac output typically declines5, 6. The steady state blood pressure component based on Ohm’s law is useful in gaining physiological insight. However, it may not be appropriate to apply to an aging population because mean arterial pressure does not increase much with adult aging due to age-related declines in diastolic blood pressure that offset corresponding increases in systolic blood pressure. Furthermore, in clinical practice, hypertension is typically defined in terms of systolic and diastolic blood pressure, and mean blood pressure is usually not even calculated.
In the present study, we included a variety of hemodynamic measures that have been described as physiological correlates of systolic blood pressure, and we examined the associations between potential hemodynamic determinants and noninvasively-measured systolic blood pressure. We observed that most of the hemodynamic determinants, including arterial stiffness, stroke volume, arterial wave reflection, left ventricular ejection time, and upstroke time, were significantly related to brachial systolic pressure. The only hemodynamic measure that did not display significant associations with systolic blood pressure was left ventricular ejection fraction, possibly due to attrition-related sampling bias (i.e., ARIC study participants who died prior to visit 5 were more likely to have had reduced ejection fraction).
An increase in the stiffness of the large elastic arteries located in the cardiothoracic (central) circulation (e.g., aorta and carotid artery) has been implicated as the primary mechanism underlying the age-associated increase in systolic blood pressure and pulse pressure13, 14. Indeed, the strongest relation with systolic blood pressure was observed with arterial stiffness as measured by pulse wave velocity. The increase in central artery stiffness observed with adult aging likely occurs because of changes in both functional and structural determinants within the vascular wall13, 15. However, age-related increases in arterial stiffness do not appear to be dependent on the presence of clinical atherosclerotic disease. The stiffening of arteries with advancing age has been observed in a rural Chinese population in whom the prevalence of atherosclerosis is very low16, 17 and in rigorously-screened U.S. men and women18–20, as well as in beagle dogs who are resistant to atherosclerosis21. Interestingly, when the study cohort was divided into approximate tertiles, the strength of associations between arterial stiffness and systolic BP became weaker with increasing age while associations with stroke volume and augmentation index became stronger. These results suggest that the role of arterial stiffness as a primary determinant of pulsatile blood pressure component may get diminished with advancing age.
To date, studies of the hemodynamic determinants of blood pressure have largely focused on peripheral (i.e., brachial) blood pressure. Thus, the determinants of central blood pressure have been inferred but not established. One of the strengths of the present analyses is the inclusion of central (i.e., carotid) blood pressure assessment. Central blood pressure is more directly related than peripheral blood pressure to cardiac afterload and coronary perfusion during diastole7. Accordingly, central blood pressure is considered a more accurate and robust cardiovascular prognostic marker than conventional brachial blood pressure and is differentially affected by antihypertensive medications22, 23. We observed that hemodynamic correlates of central systolic pressure included arterial stiffness, stroke volume, arterial wave reflection, left ventricular ejection time, and upstroke time. The strengths of these associations were fairly similar to those observed for peripheral (i.e., brachial) blood pressure.
Strengths of the present study include its very large sample size involving older adults as well as comprehensive measures of hemodynamic factors. However, there are also a number of limitations that should be emphasized. First, the cross-sectional nature of the present analyses cannot provide any information regarding causality or longitudinal changes. Second, a major confounding factor for the present analyses was the high prevalence of anti-hypertensive medication use. Therefore, we performed separate analyses in the subset of individuals not taking anti-hypertensive medications and observed very similar results to those from the analyses of the total sample. However, it should be noted that there are a number of co-existing conditions that we could not account for fully with statistical analyses. Conversely, we were not able to address the effects of certain anti-hypertensive medications. Third, the present sample was primarily composed of older adults; thus, the extent to which our results can be extended to younger populations is unknown. Finally, the strengths of associations between blood pressure and hemodynamic factors were modest, likely due in large part to the fact that all measurements were performed non-invasively at a single point in time in this large epidemiologic cohort; as such, our results should be interpreted with caution.
In conclusion, the findings of the present study in community-dwelling older adults indicate that mean arterial pressure is associated strongly with cardiac output and particularly with systemic vascular resistance. Significant hemodynamic determinants of systolic blood pressure included arterial stiffness, stroke volume, arterial wave reflection, left ventricular ejection time, and upstroke time with the strongest influence exerted by arterial stiffness. We also showed that these factors similarly impacted central BP. Understanding physiological factors that determine components of blood pressure should lead to better prevention and treatment strategies for the epidemics of hypertension.
Acknowledgments
The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C). This work was also supported by NIGMS grant T32 GM74905 (ELM), NHLBI cooperative agreement NHLBI-HC-11-08 (SDS), grants R00-HL-107642 (SC) and K08-HL-116792 (AMS), a grant from the Ellison Foundation (SC), and grant 14CRP20380422 from the American Heart Association (AMS).
Footnotes
Conflict of Interest
Nothing to disclose.
References
- 1.Lee ML, Rosner BA, Weiss ST. Relationship of blood pressure to cardiovascular death: the effects of pulse pressure in the elderly. Ann Epidemiol. 1999;9:101–107. doi: 10.1016/s1047-2797(98)00034-9. [DOI] [PubMed] [Google Scholar]
- 2.Kannel WB, Gordon T. Evaluation of cardiovascular risk in the elderly: the Framingham Study. Bull NY Acad Med. 1978;54:573–591. [PMC free article] [PubMed] [Google Scholar]
- 3.Benetos A, Safar M, Rudnichi A, Smulyan H, Richard JL, Ducimetiere P, Guize L. Pulse pressure: a predictor of long-term cardiovascular mortality in a French male population. Hypertension. 1997;30:1410–1415. doi: 10.1161/01.hyp.30.6.1410. [DOI] [PubMed] [Google Scholar]
- 4.Messerli FH, Frohlich ED, Suarez DH, Reisin E, Dreslinski GR, Dunn FG, Cole FE. Borderline hypertension: relationship between age, hemodynamics and circulating catecholamines. Circulation. 1981;64:760–764. doi: 10.1161/01.cir.64.4.760. [DOI] [PubMed] [Google Scholar]
- 5.Tanaka H, Dinenno FA, Hunt BE, Jones PP, DeSouza CA, Seals DR. Hemodynamic sequelae of age-related increases in arterial stiffness in healthy humans. Am J Cardiol. 1998;82:1152–1155. doi: 10.1016/s0002-9149(98)00578-5. [DOI] [PubMed] [Google Scholar]
- 6.Hunt BE, Davy KP, Jones PP, DeSouza CA, Pelt REV, Tanaka H, Seals DR. Systemic hemodynamic determinants of blood pressure in women: age, physical activity, and hormone replacement. Am J Physiol. 1997;273:H777–H785. doi: 10.1152/ajpheart.1997.273.2.H777. [DOI] [PubMed] [Google Scholar]
- 7.Agabiti-Rosei E, Mancia G, O’Rourke MF, Roman MJ, Safar ME, Smulyan H, Wang JG, Wilkinson IB, Williams B, Vlachopoulos C. Central blood pressure measurements and antihypertensive therapy: a consensus document. Hypertension. 2007;50:154–160. doi: 10.1161/HYPERTENSIONAHA.107.090068. [DOI] [PubMed] [Google Scholar]
- 8.Meyer ML, Tanaka H, Palta P, Cheng S, Gouskova N, Aguilar D, Heiss G. Correlates of Segmental Pulse Wave Velocity in Older Adults: The Atherosclerosis Risk in Communities (ARIC) Study. Am J Hypertens. 2016;29:114–22. doi: 10.1093/ajh/hpv079. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Shah AM, Cheng S, Skali H, Wu J, Mangion JR, Kitzman D, Matsushita K, Konety S, Butler KR, Fox ER, Cook N, Ni H, Coresh J, Mosley TH, Heiss G, Folsom AR, Solomon SD. Rationale and design of a multicenter echocardiographic study to assess the relationship between cardiac structure and function and heart failure risk in a biracial cohort of community-dwelling elderly persons: the Atherosclerosis Risk in Communities study. Circ Cardiovasc Imaging. 2014;7:173–81. doi: 10.1161/CIRCIMAGING.113.000736. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Tanaka H, Munakata M, Kawano Y, Ohishi M, Shoji T, Sugawara J, Tomiyama H, Yamashina A, Yasuda H, Sawayama T, Ozawa T. Comparison between carotid-femoral and brachial-ankle pulse wave velocity as measures of arterial stiffness. J Hypertens. 2009;27:2022–7. doi: 10.1097/HJH.0b013e32832e94e7. [DOI] [PubMed] [Google Scholar]
- 11.Meyer ML, Tanaka H, Palta P, Patel MD, Camplain R, Couper D, Cheng S, Al Qunaibet A, Poon AK, Heiss G. Repeatability of Central and Peripheral Pulse Wave Velocity Measures: The Atherosclerosis Risk in Communities (ARIC) Study. Am J Hypertens. 2016;29:470–5. doi: 10.1093/ajh/hpv127. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Dhindsa M, Barnes JN, Devan AE, Sugawara J, Tanaka H. Comparison of augmentation index derived from multiple devices. Artery Res. 2011;5:112–114. [Google Scholar]
- 13.O’Rourke MF. Arterial aging: pathophysiological principles. Vasc Med. 2007;12:329–341. doi: 10.1177/1358863X07083392. [DOI] [PubMed] [Google Scholar]
- 14.Arnett DK, Boland LL, Evans GW, Riley W, Barnes R, Tyroler HA, Heiss G. Hypertension and arterial stiffness: the Atherosclerosis Risk in Communities Study. Am J Hypertens. 2000;13:317–323. doi: 10.1016/s0895-7061(99)00281-2. [DOI] [PubMed] [Google Scholar]
- 15.Mitchell GF, Parise H, Benjamin EJ, Larson MG, Keyes MJ, Vita JA, Vasan RS, Levy D. Changes in arterial stiffness and wave reflection with advancing age in healthy men and women: the Framingham Heart Study. Hypertension. 2004;43:1239–1245. doi: 10.1161/01.HYP.0000128420.01881.aa. [DOI] [PubMed] [Google Scholar]
- 16.Avolio AP, Fa-Quan D, Wei-Qiang L, Yao-Fei L, Zhen-Dong H, Lian-Fen X, O’Rourke MF. Effects of aging on arterial distensibility in populations with high and low prevalence of hypertension: comparison between urban and rural communities in China. Circulation. 1985;71:202–210. doi: 10.1161/01.cir.71.2.202. [DOI] [PubMed] [Google Scholar]
- 17.Avolio AP, Chen SG, Wang RP, Zhang CL, Li MF, O’Rourke MF. Effects of aging on changing arterial compliance and left ventricular load in a northern Chinese urban community. Circulation. 1983;68:50–58. doi: 10.1161/01.cir.68.1.50. [DOI] [PubMed] [Google Scholar]
- 18.Vaitkevicious PV, Fleg JL, Engel JH, O’Connor FC, Wright JG, Lakatta LE, Yin FCP, Lakatta EG. Effects of age and aerobic capacity on arterial stiffness in healthy adults. Circulation. 1993;88:1456–1462. doi: 10.1161/01.cir.88.4.1456. [DOI] [PubMed] [Google Scholar]
- 19.Tanaka H, DeSouza CA, Seals DR. Absence of age-related increase in central arterial stiffness in physically active women. Arterioscler Thromb Vasc Biol. 1998;18:127–132. doi: 10.1161/01.atv.18.1.127. [DOI] [PubMed] [Google Scholar]
- 20.Tanaka H, Dinenno FA, Monahan KD, Clevenger CM, DeSouza CA, Seals DR. Aging, habitual exercise, and dynamic arterial compliance. Circulation. 2000;102:1270–1275. doi: 10.1161/01.cir.102.11.1270. [DOI] [PubMed] [Google Scholar]
- 21.Haidet GC, Wennberg PW, Finkelstein SM, Morgan DJ. Effects of aging per se on arterial stiffness: systemic and regional compliance in beagles. Am Heart J. 1996;132:319–327. doi: 10.1016/s0002-8703(96)90428-7. [DOI] [PubMed] [Google Scholar]
- 22.Williams B, Lacy PS, Thom SM, Cruickshank K, Stanton A, Collier D, Hughes AD, Thurston H, O’Rourke M. Differential impact of blood pressure-lowering drugs on central aortic pressure and clinical outcomes: principal results of the Conduit Artery Function Evaluation (CAFE) study. Circulation. 2006;113:1213–1225. doi: 10.1161/CIRCULATIONAHA.105.595496. [DOI] [PubMed] [Google Scholar]
- 23.de Luca N, Mallion JM, O’Rourke MF, O’Brien E, Rahn KH, Trimarco B, Romero R, De Leeuw PW, Hitzenberger G, Battegay E, Duprez D, Sever P, Safar ME. Regression of left ventricular mass in hypertensive patients treated with perindopril/indapamide as a first-line combination: the REASON echocardiography study. Am J Hypertens. 2004;17:660–667. doi: 10.1016/j.amjhyper.2004.03.681. [DOI] [PubMed] [Google Scholar]