African Americans (AA) have the highest prevalence of hypertension in the world and develop hypertension and higher rate of other heart diseases at an earlier age compared with Caucasians (CA) (15,20). Pathophysiological factors of the increased cardiovascular disease burden even in young AA adults include increased vascular resistance, reduced microvascular vasodilatory capacity (38), increased arterial stiffness (14), increased carotid intima-media thickness (IMT) (35), and decreased endothelial-dependent and -independent vasodilatation (9). This may contribute or cause the higher blood pressure (BP) reported even in young AA adults (47). Furthermore, young otherwise healthy AA men exhibit higher central BP compared with their CA peers even though brachial BP were similar (24). This is important because central BP is a better predictor of clinical outcomes and target organ damage (36). Young AA men have higher aortic stiffness compared with age- and fitness-matched CA men (46). Conversely, Arena et al. found that differences in the aortic stiffness between AA and Caucasian participants were partially related to differences in aerobic fitness (2). Thus, whether improving aerobic fitness may help attenuate these racial differences in vascular function in young men and women is still not clear.
Endurance exercise can reduce both BP and arterial stiffness coupled with an increase in endothelial function in healthy CA adults (8,13). Short-term (3 months or less) regular aerobic exercise can increase endothelial function by 30% (13) and central arterial compliance by 25% while producing an approximately 20% decrease in the carotid β-stiffness index (39) in healthy previously sedentary CA adults. In addition, recent studies have reported an improvement in both arterial stiffness and endothelial function after endurance exercise training in young healthy adults (3,4,12,33,37). Hence, there is general agreement that aerobic training is beneficial for arterial health in young, middle-age and older CA; however, AA young adults may exhibit differential responses. Information on the effect of endurance exercise training is notably lacking in the AA population, and data regarding exercise training in younger AA women are particularly sparse in existing literature because of small sample sizes and a lack of control groups or control periods (6,7,21). Nevertheless, there is also no information suggesting that AA women would exhibit differential changes in response to training compared with AA men.
Hence, our aim was to examine the effect of 8 wk of moderate- to high-intensity aerobic training on young healthy sedentary AA men and women compared with their CA peers. We hypothesized that AA would show significantly greater improvement in BP, arterial stiffness, resting forearm blood flow (FBF), reactive hyperemia, and IMT measures compared with CA.
Healthy volunteers (men and women) between 18 and 35 yr of age (mean age, 24 yr) were recruited and screened via phone interview. Sixty-two participants completed the study (Fig. 1, CONSORT diagram). All subjects were free of acute cardiovascular or respiratory disease and do not smoke. Exclusion criteria included participants with hypertension, stroke, or myocardial infarction, metabolic disease (diabetes mellitus), inflammatory diseases (rheumatoid arthritis and systemic lupus erythematosus), bleeding disorders, or intake of any medication on a regular basis other than oral contraceptives. Participants taking allergy medications and participants who were taking over-the-counter pain/anti-inflammatory medications were asked to come in for testing only 72 h after their last dose. Participants who had experienced the common cold, influenza or upper respiratory tract infection 2 months preceding enrolment were also excluded. All subjects were recruited from the local community and provided a written informed consent before participation. This study was approved by the institutional review board of the University of Illinois at Urbana-Champaign. The clinical trials identifier for the study is NCT01024634.
We used a longitudinal experimental design, with all subjects undergoing all the conditions. The first 4 wk of the study after the baseline visit (T1) served as a reference/control period for each participant. During this control period, all the participants were asked to continue their regular lifestyle and refrain from making changes to their diet. They were also asked to refrain from starting any exercise protocols on their own. After the 4-wk control period, subjects visited the laboratory for a follow-up visit (T2). After that visit, all subjects were enroled in an 8-wk endurance exercise program. They then returned for a final visit after completion of the 8-wk exercise program (T3). Subjects were asked to maintain their normal lifestyle and diet during the entire study period. All participants underwent three testing sessions and 24 exercise training sessions. The study design and visit details are presented in Figure 2.
To control for diurnal variation, all the measurements were performed during the same time of the day for each participant, with the exception of fasting blood draws, which were obtained on a separate day. Women were tested during the early follicular phase of their menstrual cycle or during the placebo phase if they were taking oral contraceptives. Before each testing session, all participants were asked to fast for minimum of 4 h. They were also asked to refrain from heavy physical activity for 24 h before the testing session and anti-inflammatory medication for at least 3 d.
Height and weight were measured using a stadiometer and a beam balance platform scale, respectively. Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared.
Assessment of hemodynamics and vascular structure and function
Resting BP was measured in the supine position using an automated oscillometric cuff (HEM-907XL; Omron Corporation, Japan) after 15 min of rest. The coefficient of variation (CV) for BP measurements in our laboratory is between 2% and 3.3%.
Pulse wave analysis
Radial artery pressure waveforms were attained in the supine position from a 10-s epoch using applanation tonometry, and using a generalized validated transfer function (10), the augmentation index (AIx) and AIx normalized to an HR of 75 bpm (AIx@75) were calculated. The AIx, which is typically expressed in percentage and used as an index of systemic arterial stiffness, was calculated as the ratio of amplitude of the pressure wave above its systolic shoulder (i.e., the difference between the early and late systolic peaks of the arterial waveform), to the total pulse pressure (PP). Because AIx is influenced by HR, AIx values were normalized to an HR of 75 bpm (AIx@75). Only high-quality recordings i.e., recordings with a quality index >80%, were included in the analysis (44). All measurements were made in duplicate, and the mean value was used for subsequent analysis. Reproducibility of measures attained from this technique has previously been shown to be high (45). The CV for AIx is <5.5% in our laboratory.
Pulse wave velocity
A high-fidelity strain gauge transducer (Millar Instruments, Houston, TX) was used to obtain the pressure waveform from the following: 1) the left common carotid artery and the left femoral artery and 2) the left femoral artery and the ipsilateral superior dorsalis pedis artery. All measurements were conducted following guidelines of the Clinical Application of Arterial Stiffness Task Force III (42). This value was used as an index of central stiffness. Only those pulse wave velocity (PWV) values with SD <10% as assessed by the integral software (SphygmoCor; AtCor Medical, Sydney, Australia) are included in subsequent analysis. All measurements were made in duplicate, and the mean value was used for subsequent analysis. This technique is highly reproducible (45). The CV for PWV is 3.2% in our laboratory.
Carotid artery compliance and β-stiffness
The cephalic portion of carotid artery was imaged in longitudinal section, 1–2 cm proximal to the bifurcation, via ultrasonography (Aloka alpha-10; Tokyo, Japan) using a high-frequency (7.5 MHz) linear array probe. Simultaneous BP of the contralateral carotid artery was determined using applanation tonometry. Image analysis and calculation of arterial compliance (AC) and β-stiffness index (β) were carried out using an automated wall detection echo-tracking software system. The CV for β-stiffness in our laboratory is approximately 5%.
Carotid artery IMT
All measurements were made at end-diastole measured via ultrasonography (Aloka alpha-10, Tokyo, Japan). The IMT of the common carotid artery was determined from an average of five measurements obtained 20 mm proximal to the carotid bifurcation. The CV for IMT in our laboratory is approximately 1.4%.
Forearm resistance artery vasodilatory capacity
With participants in supine position, the vasodilatory function of forearm resistance arteries was assessed using reactive hyperemia (RH) and strain-gauge plethysmography (EC-6; DE Hokonson, Inc., Bellevue, WA). A wrist cuff was placed right at the wrist level to exclude hand circulation. Upper arm cuff was placed above the elbow on the upper arm, whereas strain gauge was placed on the widest area of the forearm. FBF was measured using strain-gauge plethysmography (EC-4; D.D. Hokanson, Inc., Bellevue, WA). RH of the forearm vessels was evaluated immediately after FBF. After 5 min of upper arm occlusion and last minute of wrist cuff occlusion, changes in the forearm volume was measured using rapid release of the upper arm cuff. Thirteen readings (3 min) were taken with a 15-s cycle. Peak FBF was recorded as the highest reading. Area under the curve (AUC) was used as a measure of total RH by plotting all 13 measurements against time. The CV for RH in our laboratory is approximately 9%. FBF was expressed as milliliters per minute per 100 mL of forearm tissue and also as flow per unit pressure (conductance) using the following equation:
Forearm vascular resistance was calculated using the equation:
Peak oxygen consumption was evaluated using cycle ergometry to exhaustion as we have previously described (23). We used a graded protocol, starting at 50 W followed by 30-W increments every 2 min until exhaustion. The test was terminated when the subject could no longer continue, and peak effort was determined on the basis of meeting three of the following criteria: 1) inability to maintain a 60-rpm pedal rate, 2) a respiratory exchange ratio of 1.1, 3) achievement of ± 10 bpm of predicted HRmax, 4) a plateau in HR with an increase in work rate, 5) a plateau in aerobic capacity (V˙O2) with increase in work rate (an increase of less than 150 mL·min−1), and 6) a final RPE of ≥17 on the Borg scale (6–20).
Endurance training intervention
Both groups underwent a supervised endurance training program in accordance with established guidelines (1). Sessions were carried out three times per week. During each session, participants completed a 5-min warm-up followed by 30–45 min of endurance exercise. During the first 2 wk, exercise was performed at an initial intensity equivalent to 65%–75% of V˙O2peak measured from the peak cycle ergometry test. After the initial 2 wk, intensity was increased to 75%–85% of V˙O2peak to increase the training stimulus. This intensity range is considered moderate to high intensity and is designed to improve V˙O2peak and produce changes in arterial function. Intensity was monitored using HR monitors during each exercise session, and each participant received an exercise prescription with a heart range equivalent to 65%–85% of their V˙O2peak. Participants were asked to complete 30 min of exercise during each session in week 1, 35 min in week 2, and 40–45 min from week 3 through week 8. Each exercise session was concluded with a 5-min cooldown period.
After an overnight fast on a separate day, venous blood samples were collected and analyzed for plasma concentrations of C-reactive protein (CRP) and interleukin-6 (IL-6). Samples were collected into 10-mL tubes containing EDTA (anticoagulant and chelating agent). Samples were separated by centrifugation at 4°C for 15 min at 1100g and were stored at −80°C until analyzed and were measured to assess systemic inflammation. Separate Quantikine enzyme-linked immunosorbent assay kits (R&D Systems, Minneapolis, MN) were used to measure plasma IL-6 and CRP. Sensitivities for the enzyme-linked immunosorbent assay kits were 0.010 ng·mL−1 and 0.039 pg·mL−1 for CRP and IL-6, respectively.
All inferential statistics were conducted using Stata IC (12.0) statistical software and used two-tailed alpha to reject the null hypothesis of no effect at 0.05. Each of our dependent variables was analyzed separately. All analyses were conducted in concert with our mixed-effects experimental design consisting of one independent measures factor (race, AA vs not AA) and one longitudinal/repeated-measures factor (time, before control, after control, and after training). We analyzed our outcomes with mixed-effects linear regression models, also known as multilevel modeling. These are recent extensions of ordinary least squares (OLS) regression/ANOVA methods that are particularly favorable for repeated-measures studies like ours because they enable us to incorporate each subjects’ unique Y-intercept term (random effect for subject) to accommodate the within-subject correlation structure yet not having the strict ANOVA requirement that all subjects have all data from all time points. That is, each subject contributes data from all available periods for which they remained a participant, but occasionally missed data acquisitions will not eliminate the participant from the entire analysis. Because of unplanned attrition, some subjects dropped out from the study before some data acquisitions; however their available observations remain in our analyses and helped inform our statistical models where possible. Each of our models included dummy-coded time indicators comparing times 2 and 3 to the precontrol period and thus forced no assumptions of linearity or nonlinear change over time.
All the values are reported as means ± SEM. AA had a significantly higher BMI (P < 0.05) as compared with CA at all the three time points (Table 1). There was no significant difference between V˙O2peak at baseline (T1) and the end of the control period (T2) for either group. There was a significant increase in V˙O2peak (P < 0.05) from the end of the control period (T2) to end of exercise training (T3).
There was no significant difference in brachial systolic BP (SBP), diastolic BP (DBP), and mean arterial pressure (MAP) between CA and AA at baseline (Table 2). PP was significantly higher in CA as compared with that in AA (P < 0.05). However, aortic and carotid SBP, DBP, MAP or PP, and aortic DBP or PP were not significantly different between CA and AA at baseline.
Control period (T2)
There was a decrease in brachial SBP (P < 0.05) but no change in DBP after the control period in both groups (Table 2). There were also no significant changes in carotid SBP, DBP, and aortic SBP and DBP during the control period. There was a significant group–time interaction (P < 0.05) in aortic PP at T2 (4-wk control period). This was attributed to the rise in aortic PP in AA by approximately 2 mm Hg at T2 whereas it decreased by approximately 2 mm Hg in CA. Similarly, there was a significant interaction (P < 0.05) in carotid PP at T2 (4-wk control period). Again, this is due to a drop in carotid PP by approximately 3 mm Hg in CA whereas there was no change in the AA group.
Posttraining period (T3)
There was a significant decrease in brachial SBP (P < 0.05) after the aerobic exercise training period, compared with baseline, across groups (Table 2). In addition, carotid PP decreased significantly after exercise training compared with that in baseline across groups. There was no exercise effect on any of the other BP variables.
There were no differences in the levels of IL-6 and CRP between the two groups. There were no exercise effects for IL-6 or CRP in CA or AA.
AA had significantly lower baseline FBF (P < 0.05) compared with CA. In addition, AA had significantly lower RH and AUC than CA (Table 3). However, there was no main effect of exercise training and no interaction effects on resting FBF, RH, or AUC. In addition, there were no differences at baseline, main effect of exercise training, and no interaction effects in forearm vascular conductance or resistance between AA and CA groups.
Arterial function and structure
There was no significant baseline difference in central arterial stiffness (cPWV), wave reflection (AIx), or carotid β-stiffness between the two groups (Table 3). Exercise training had no effect of cPWV, AIx, or β-stiffness in either group. AA had a higher IMT at baseline (P < 0.05) compared with CA (Fig. 3). While both groups decreased IMT from T2 to T3, we observed a significant race–time interaction effect, with greater decreases in the AA group. In addition, there was no significant difference in the carotid diastolic diameter (D-min) at baseline between CA and AA; however, exercise training increased carotid diameter in CA but not in AA (P = 0.048). Because changes in IMT can be influenced by changes in arterial lumen diameter, we also conducted a follow-up mixed-effects analysis controlling for the change in arterial diameter. This analysis showed a significant race–training interaction, where AA exhibited a significant decrease in IMT after controlling for changes in arterial diameter, whereas CA did not (adjusted means ± SE of 0.421 ± 0.011 to 0.401 ± 0.011 mm for AA vs 0.407 ± 0.01 to 0.400 ± 0.01 mm for CA).
This is the first study to examine the effects of race on vascular and hemodynamic adaptations after aerobic training in young men and women. Our primary finding was that 8 wk of aerobic exercise training improved IMT profile in AA and BP changes do not explain the changes in IMT. Although endurance exercise training did not influence FBF and RH in AA or CA, our findings corroborate previous data (28) that even healthy young AA have lower FBF and RH as compared with their CA counterparts. Interestingly, carotid PP decreased with exercise training across groups, suggesting that exercise training affected carotid PP similarly in both AA and CA. Although brachial SBP decreased after the control period and remained lower than baseline after exercise training, exercise training did not significantly affect SBP in either group, consistent with previous findings in young healthy adults (18,19).
Similar to previous works, we found AA have an increased carotid IMT as compared with that in their CA peers (14,35). Even a 0.1-mm increase in the carotid-IMT has been associated with increased risk of myocardial infarction after adjusting for age and sex (30). In addition, carotid IMT provided risk stratification similar to that of Framingham risk score (31), and low physical fitness independently correlates with increased carotid IMT in middle-age and older adults (34). In contrast to our study in younger (18–35 yr) adults, longitudinal studies evaluating the effects of aerobic exercise training (8–12 wk) on IMT in middle-age and older adults found that training was unable to alter the carotid artery IMT (40). Conversely, Thijssen et al. (41) observed a significant reduction in wall thickness in the carotid and femoral artery after 8 wk of exercise training in healthy young adults, consistent with our findings. Others have also found structural changes after a brief intervention period (8–12 wk) in peripheral arteries (17). To our knowledge, the present study is the first to show a reduction in IMT with exercise training in young healthy AA. Furthermore, our time-control study design ascertained that our findings were not a result of potential preexisting differences between groups. One of the potential reasons for this beneficial change in carotid artery IMT in AA may be due to the positive effect of exercise training on carotid PP. Increased PP has been associated with increased carotid artery wall thickness (16). In addition, increased pressure also causes a shift in arterial endothelial cell phenotype by reducing endothelial nitric oxide synthase and increasing VCAM-1, ICAM-1 and ET-1, which promote atherosclerotic process (29). In addition, vascular wall hypertrophy may depend more on the PP rather than mean pressure or wall tension (26). Hence, the reduction in PP seems to be consistent with the reduction in carotid artery IMT in AA, although similar changes in PP in CA had no effect on IMT when controlled for changes in carotid artery diameter. Thus, endurance exercise training seems to affect carotid artery remodeling differently in AA and CA young healthy adults.
Interestingly, internal carotid artery diameter increased significantly in CA but not in AA after exercise training, even though there was no significant difference in the carotid diastolic diameter (D-min) at baseline between CA and AA. It is possible that a decrease in wall thickness is accompanied by lumen dilation; thus, the change in IMT may simply be a function of changes in lumen diameter. Our data support this notion in CA, as the change in IMT was not significant when controlled for changes in carotid diameter, whereas the training-induced change in IMT was unaffected by carotid diameter changes in AA. Because reductions in IMT with exercise training has more commonly been observed in obese populations (32,43), it is possible that the higher BMI in our AA participants may have contributed to the greater reduction in IMT controlled for changes in arterial size in our AA group.
Blood flow and vascular responsiveness
Young healthy normotensive AA have lower vascular responsiveness to nitric oxide (NO) compared with that of CA (9). Our current findings suggest that AA not only have a reduced baseline blood flow in the forearm microvasculature but also exhibit significantly reduced reactivity of this vasculature compared with CA. Contrary to our hypothesis, 8 wk of aerobic training did not abolish the difference in microvascular circulation between AA and CA.
AA have a higher minimum forearm vascular resistance compared with age-, BMI-, sex-, and BP-matched CA (25). This reinforces our finding that the baseline measures of FBF and RH were significantly lower in AA. This is of particular importance because the increase in forearm resistance can be a precursor for hypertension because of its effect on vascular remodeling and metabolic factors (25). However, in the present study, we did not find any significant difference in baseline forearm vascular resistance or conductance in AA as compared with those in CA.
Brachial, carotid, and aortic SBP, DBP, and mean BP were not significant different between groups at baseline, nor was there a significant change after exercise training. However, it should be noted that systolic brachial pressure was significantly higher in CA as compared with that in AA. Importantly, average BP was in the normal range and both groups had almost similar baseline pressures. Unexpectedly, there was a decrease in brachial SBP (P < 0.05) after the period in both groups. The decrease was approximately 2 mm Hg in both groups, and it is difficult to determine the exact reason for the change during the control period as opposed to after exercise training. Even though there was a significant reduction after exercise training compared with that in baseline, there was no change in brachial SBP at T3 as compared with that in the control period (T2). The lack of change in BP after exercise training could be attributed to the fact that both the groups recruited were young healthy normotensive participants. Previous literature suggests that even patients with average fitness and mild hypertension fail to show significant reduction in BP after endurance exercise training without dietary changes (5).
Ceiling effect with vascular function
In the present study, we did not find any significant changes in the measures of vascular function despite an effect of exercise training on arterial structure (IMT). Interestingly, Green et al. (22) have reported that in world-class athletes, there was an inverse relation between the diameter and flow-mediated dilation in both femoral and brachial arteries. This suggests that adaptation of arterial function and arterial structure may not always coexist. One of the primary reasons for this lack of change could be that the values at baseline and pretraining period in our younger healthy cohort were normal and hence there was a little scope for improvement with 8 wk of exercise training. This ceiling effect may be challenged by either increasing the intensity of exercise or changing the mode or duration of exercise.
One of the limitations of the study was that we did not control the mode of aerobic training (bike, treadmill, or elliptical machine) and allowed participants to self-select intensity from the range normally used to induce exercise training effects (65%–85% HRmax). Although we address this as a limitation, we also believe this improves the applicability of our study to real-world scenarios. Secondly, we did not control for the regular activity of an individual by maintaining activity records. In addition, AA have higher BMI as compared with that of the CA group and there was no significant decrease in BMI after the training period. Hence, one of the limitations is that BMI could have been a confounding variable for differences in IMT at baseline. However, as BMI did not change but there were changes seen in IMT, it is plausible that these vascular changes were not due to weight loss. Third, we acknowledge that NO has been shown to play limited role in peak vasodilation during RH and other factors (endothelial dependent or independent) may be playing a role. Lastly, the study included only young healthy individuals from both ethnicities and hence there was a lack of differences at baseline in vascular function and BP. Therefore, these results cannot necessarily be extrapolated to clinical populations. However, as we reported in this study, even young healthy AA have a significantly higher carotid-IMT and lower microvascular function as compared with CA.
This is the first study to show that 8 wk of aerobic training significantly improves arterial structure (carotid artery IMT) in young healthy AA. In addition, the study shows that young healthy AA have lower FBF and RH as compared with those in their CA counterparts, which were not improved by 8 wk of aerobic training.
The present study was funded by National Institute of Health (NHLBI 1R01HL093249-01A1).
The authors declare no conflicts of interest.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
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