Abstract
Uncertainty remains regarding the association between resting heart rate (RHR) with hypertension and stroke because of limited and inconsistent data. We assessed the association between RHR, hypertension, and stroke. In this cross‐sectional study, 14 677 participants from the China Hypertension Survey study were analyzed. The history of stroke was conducted by questionnaires. RHR was measured by the standardized electronic monitors. Multivariate logistic regression analyses were performed to evaluate the association between RHR, hypertension, and stroke. Moreover, a generalized additive model (GAM) and smooth curve fitting (penalized spline method) were conducted to assess the association between RHR and stroke in different status of hypertension. Overall, each 10 beats per minute (bpm) increase in RHR was associated with an 18% increased prevalence of stroke (P = 0.017). Subjects with RHR > 80 bpm were associated with a higher prevalence of stroke (OR = 1.47; 95% CI, 1.08‐2.01) compared with those with RHR ≤ 80 bpm. Similarly, hypertensives had a higher prevalence of stroke than normotensives (OR = 3.76; 95% CI, 2.39‐5.92). Hypertensives with RHR > 80 bpm had the highest prevalence of stroke compared with their counterparts (OR = 5.47; 95% CI, 3.13‐9.56). The fully adjusted smooth curve fitting presented a linear association between RHR and stroke among participants with hypertension, but almost horizontal association among participants without hypertension. In conclusion, elevated RHR and hypertension were independently and jointly associated with the increased prevalence of stroke. These findings suggested that elevated RHR was associated with increased prevalence of stroke especially among hypertensives.
Keywords: China, hypertension, resting heart rate, stroke
1. INTRODUCTION
Stroke is the leading cause of death in China and the second leading cause of death in the world.1 Primary prevention is particularly important because about 77% of strokes are first events.2 Specifically, hypertension is a well‐recognized major modifiable risk factor for stroke.3 According to the American Heart Association and American Stroke Association's guidelines, controlling the risk factors of stroke is an effective strategies for preventing stroke.4
Resting heart rate (RHR) is an easily collected cardiovascular parameter. Previous studies have reported that elevated RHR is a risk marker for cardiovascular diseases (CVD) and all‐cause mortality.5, 6 Despite the absence of objective data, RHR was considered to be elevated when it was higher than 80‐85 bpm,8 and the threshold of RHR varies from hypertensives associated with different CVD. Although the association of RHR with stroke has also been explored, obvious conflicting results could be found among those reports.9, 10 Several epidemiological studies reported that elevated RHR was associated with an increased risk of stroke.9, 10 In contrast, some studies showed that RHR was not associated with stroke.12, 13 Nevertheless, the association between RHR and stroke remains unclear. Moreover, when combined with known risk factors for stroke, the target RHR is still less known.
Therefore, the aim of this study was to evaluate the independent and combined association of RHR and hypertension with stroke in Chinese by a population‐based cross‐sectional study.
2. METHODS
2.1. Study population
We made use of the data generated from a cross‐sectional survey conducted between November 2013 and August 2014 in Jiangxi province, China, which was a subset of the China Hypertension Survey study encompassed 31 provinces and 262 countries and was supported by the National Key R&D Program in the Twelfth Five‐Year Plan (No. 2011BAI11B01) from the Chinese Ministry of Science. Details regarding the method and design of the study have been introduced in previous publications.14, 15 Briefly, this study used a multistage, stratified random sampling method to select 15 364 representative samples. Our project was approved by the Ethical Committee of the Chinese Ministry of Science and Technology. Written informed consent was obtained from all participants before they entered this study.
As a result, out of 15 364 eligible participants, a total of 15 296 participants completed the investigation. After excluding those with missing RHR data (n = 433), as well as those having a history of atrial fibrillation (n = 130), and those taking β blockers (n = 56), finally, a total of 14 677 participants were analyzed (Figure S1).
2.2. Data collection
Participants were required to complete a standardized questionnaire which was developed by the national coordinating center of the Fuwai Hospital (Beijing, China) through face‐to‐face interviews with trained staff and physical measurements. Data on questionnaire included demographic characteristics (such as age, gender, education), family history of diseases and stroke, oral antihypertensive drugs (including angiotensin‐converting enzyme inhibitor (ACEI)/angiotensin receptor blocker (ARB), calcium channel blockers, diuretics, beta blockers), and lifestyle (such as smoking, alcohol consumption, sleep duration on workdays or non‐workdays). For each participant, self‐reported history of CVD, which was defined as hypertension, atrial fibrillation, and stroke, was collected and verified with medical or hospital records. The anthropometric examinations included weight, height, waist circumference, blood pressure (BP), and RHR.
2.2.1. Stroke
Self‐reported history of stroke was assessed if respondents answered “yes” to the question, “Have you ever been told by a doctor or other health professional that you had a stroke?” These patients were also asked for symptoms, initial dates, diagnostic units, medical records, and imaging data in order to make a reasonable assessment of the original diagnosis. Stroke included subarachnoid hemorrhage, intracerebral hemorrhage or cerebral ischemic necrosis, but did not include secondary stroke caused by transient cerebral ischemia, brain tumor, brain metastasis tumor or trauma.16
2.2.2. Hypertension and RHR
Blood pressure and resting heart rate were measured three times with 30‐second interval on the participants’ right arms using the standardized electronic monitors (HBP‐1300, Omron, Kyoto, Japan) after the participants relaxed and sitting for at least 5 minutes.17 Then systolic BP (SBP), diastolic BP (DBP), and RHR were calculated as the mean of three independent measures. Hypertension was defined as SBP ≥ 140 mm Hg and/or DBP ≥ 90 mm Hg, and also if the individual was on antihypertensive medication within 2 weeks.15, 17 RHR was analyzed as tertiles and as a dichotomized variable: T1‐T2 versus T3.
2.2.3. Covariables
The covariates included in all the analyses were sex, age (<60, ≥60 years), area (urban, rural), education status (primary school or below, middle school, high school or special school, college graduate or above), occupation status (employed, retired, unemployed), family history of cardiac‐cerebral vascular diseases (diabetes, hypertension, coronary heart disease (CHD) or stroke), cigarette smoking, alcohol consumption, sleep duration on workdays and non‐workdays,16 antihypertensive medications, body mass index (BMI) (<24, 24‐28, ≥28 kg/m2),15 and waist circumference (WC). BMI was calculated as the body weight in kilograms divided by the square of the height in meters (kg/m2).
2.3. Statistical analysis
All the analyses were performed using the statistical package R (http://www.r-project.org, the R Foundation) and Empower (R) (www.empowerstats.com; X&Y Solutions, Inc, Boston, MA). Categorical variables were reported as frequency and percentage, while continuous variables were reported as mean ± SD. Baseline characteristics of study population were described by hypertension status and tertiles of RHR. Comparisons among different RHR groups (tertiles) were performed using chi‐square tests for categorical variables and using one‐way ANOVA test for continuous variables. The association between RHR and stroke was examined as a continuous variable per 10 beats per minute (bpm) increase and also as a categorical variable using tertiles with the lower tertile as the reference group. Multivariate logistic regression analysis was performed by the stepwise procedure to assess the odds ratio (OR) and 95% confidence interval (CI) for the association between RHR, hypertension status, and stroke. Multivariable models were constructed as follows: Model I adjusted for age and sex; Model II adjusted for Model 1 covariates plus area, smoking, drinking, education status, occupation, sleep duration (workdays and non‐workdays), antihypertensive medications, family history of cardiac‐cerebral vascular diseases (CHD, stroke, diabetes, hypertension), BMI, WC, SBP, and DBP. A generalized additive model (GAM) and smooth curve fitting (penalized spline method) were conducted to assess the association between RHR and stroke in different status of hypertension. We also examined if the association between RHR and stroke varied by sex, age, BMI, smoking, and drinking. To ensure the robustness of data analysis, we did the following sensitivity analysis: (a) We converted the RHR into a categorical variable and calculated the P for trend. (b) We calculated the P for trend in the join effect of hypertension and RHR. A two‐side P value < 0.05 was considered to be statistically significant.
3. RESULTS
A total of 14 677 study participants (mean age: 52.9 ± 17.9 years; 40.8% men) were included in this final data analysis. Overall, the prevalence of stroke was 1.4% (221/14677). The baseline characteristics by hypertension status and tertiles of RHR were presented in Table 1. The ranges of RHR for tertiles 1‐3 were < 73, 73‐80, and >80 bpm, respectively. Regardless of hypertension status, participants with RHR T3 group were more likely than participants with RHR T1 and T2 groups to be females, to have a lower mean age, to have higher SBP and DBP values, and to have lower alcohol consumption (all P < 0.05). Among participants without hypertension, participants with RHR T3 group were more likely than participants with RHR T1 and T2 groups to have higher educational level and longer sleep duration on non‐workdays, and to be unemployed. Among participants with hypertension, participants with RHR T3 group were more likely to be from rural. No significant differences were found between the three groups in terms of BMI, WC, smoking status, the use of antihypertensive medications, family history of cardiac‐cerebral vascular diseases or sleep duration on workdays, regardless of hypertension status.
Table 1.
Baseline characteristics of study participants by hypertension status and RHR tertiles
| Variables* | Without hypertension | P value† | With hypertension | P value‡ | ||||
|---|---|---|---|---|---|---|---|---|
| RHR T1 (<73) | RHR T2 (73‐80) | RHR T3 (>80) | RHR T1 (<73) | RHR T2 (73‐80) | RHR T3 (>80) | |||
| N | 3427 | 3459 | 3602 | 1309 | 1336 | 1544 | ||
| Male, n (%) | 1534 (44.8) | 1316 (38.0) | 1368 (38.0) | <0.001 | 602 (46.0) | 548 (41.0) | 622 (40.3) | 0.005 |
| Age, y | 50.6 ± 16.4 | 48.2 ± 17.4 | 46.0 ± 18.4 | <0.001 | 65.9 ± 11.5 | 64.2 ± 12.9 | 63.6 ± 13.7 | <0.001 |
| BMI, kg/m2 | 22.4 ± 3.3 | 22.4 ± 3.4 | 22.5 ± 3.7 | 0.687 | 23.8 ± 3.6 | 23.9 ± 4.3 | 23.9 ± 3.9 | 0.850 |
| WC, cm | 77.5 ± 8.4 | 77.5 ± 9.0 | 77.6 ± 9.9 | 0.946 | 82.2 ± 9.5 | 81.8 ± 10.4 | 82.9 ± 10.1 | 0.009 |
| SBP, mm Hg | 116.7 ± 11.4 | 117.3 ± 10.9 | 117.8 ± 11.3 | <0.001 | 146.9 ± 18.9 | 145.8 ± 18.5 | 147.5 ± 18.5 | 0.047 |
| DBP, mm Hg | 69.7 ± 8.1 | 71.2 ± 8.0 | 71.6 ± 8.3 | <0.001 | 79.5 ± 11.3 | 82.0 ± 11.4 | 83.6 ± 12.3 | <0.001 |
| RHR, bpm | 67.0 ± 4.5 | 76.7 ± 2.4 | 89.1 ± 7.3 | <0.001 | 66.5 ± 5.0 | 77.1 ± 2.4 | 90.2 ± 7.9 | <0.001 |
| Urban, n (%) | 1599 (46.7) | 1646 (47.6) | 1781 (49.4) | 0.058 | 783 (59.8) | 866 (64.8) | 852 (55.2) | <0.001 |
| Current smokers, n (%) | 648 (19.0) | 582 (16.9) | 631 (17.6) | 0.073 | 253 (19.3) | 239 (17.9) | 297 (19.3) | 0.558 |
| Current drinkers, n (%) | 895 (26.2) | 821 (23.8) | 804 (22.4) | <0.001 | 330 (25.3) | 280 (21.1) | 360 (23.4) | 0.036 |
| Stroke, n (%) | 8 (0.2) | 21 (0.6) | 18 (0.5) | 0.057 | 48 (3.7) | 44 (3.3) | 72 (4.7) | 0.143 |
| Antihypertensive medications, n (%) | 50 (1.5) | 55 (1.6) | 54 (1.5) | 0.901 | 297 (22.7) | 307 (23.0) | 317 (20.5) | 0.218 |
| ACEI/ARB | 13 (0.4) | 16 (0.5) | 12 (0.3) | 0.678 | 80 (6.1) | 92 (6.9) | 79 (5.1) | 0.133 |
| CCB | 35 (1.0) | 42 (1.2) | 40 (1.1) | 0.747 | 209 (16.0) | 217 (16.2) | 229 (14.8) | 0.538 |
| Diuretics | 0 (0.0) | 1 (0.0) | 0 (0.0) | 0.362 | 6 (0.5) | 1 (0.1) | 7 (0.5) | 0.138 |
| Others | 8 (0.2) | 7 (0.2) | 6 (0.2) | 0.821 | 34 (2.6) | 32 (2.4) | 41 (2.7) | 0.901 |
| Family history of diseases | ||||||||
| CHD, n (%) | 118 (3.6) | 101 (3.0) | 93 (2.7) | 0.098 | 46 (3.7) | 44 (3.5) | 43 (3.0) | 0.547 |
| Stroke, n (%) | 130 (3.9) | 92 (2.8) | 102 (2.9) | 0.014 | 76 (6.1) | 69 (5.4) | 65 (4.5) | 0.164 |
| Diabetes, n (%) | 160 (4.8) | 133 (4.0) | 174 (5.0) | 0.115 | 76 (6.1) | 54 (4.3) | 76 (5.2) | 0.110 |
| Hypertension, n (%) | 650 (19.7) | 618 (18.5) | 674 (19.3) | 0.451 | 382 (30.4) | 363 (28.4) | 430 (29.3) | 0.547 |
| Education status, n (%) | <0.001 | 0.082 | ||||||
| Primary school graduate or below | 1520 (44.8) | 1504 (44.0) | 1454 (40.8) | 856 (66.4) | 893 (67.5) | 953 (63.0) | ||
| Middle school/high school/special school | 1576 (46.5) | 1578 (46.1) | 1666 (46.7) | 388 (30.1) | 395 (29.9) | 510 (33.7) | ||
| College graduate or above | 296 (8.7) | 340 (9.9) | 447 (12.5) | 45 (3.5) | 35 (2.6) | 49 (3.2) | ||
| Occupation | <0.001 | 0.050 | ||||||
| Employed | 1396 (41.1) | 1391 (40.7) | 1355 (37.9) | 284 (22.0) | 320 (24.2) | 384 (25.1) | ||
| Retired | 377 (11.1) | 291 (8.5) | 308 (8.6) | 304 (23.5) | 253 (19.2) | 294 (19.3) | ||
| Unemployed | 1624 (47.8) | 1739 (50.8) | 1910 (53.5) | 703 (54.4) | 748 (56.6) | 849 (55.6) | ||
| Sleep duration, h | ||||||||
| Workdays | 7.3 ± 1.3 | 7.4 ± 1.2 | 7.4 ± 1.2 | 0.104 | 7.2 ± 1.3 | 7.3 ± 1.3 | 7.2 ± 1.4 | 0.560 |
| Non‐workdays | 7.7 ± 1.4 | 7.8 ± 1.3 | 7.8 ± 1.4 | <0.001 | 7.4 ± 1.4 | 7.5 ± 1.3 | 7.5 ± 1.4 | 0.514 |
ACEI, angiotensin‐converting enzyme inhibitors; ARB, angiotensin II receptor blockers; BMI, body mass index; CCB, calcium channel blockers; CHD, coronary heart disease; DBP, diastolic blood pressure; RHR, rest heart rate; SBP, systolic blood pressure; WC, waist circumference.
Data are presented as number (%) or mean ± SD.
Comparisons among different RHR tertiles groups in participants without hypertension.
Comparisons among different RHR tertiles groups in participants with hypertension.
Table 2 showed the individual effect of RHR and hypertension on the prevalence of stroke. In a model adjusted for socio‐demographics and potential confounders, each 10 bpm increase in RHR was associated with a 18% increased prevalence of stroke (P = 0.017) (Table 2). Compared with those with RHR < 73 bpm, subjects with RHR > 80 bpm had an 82% increased prevalence of stroke (OR = 1.82; 95% CI, 1.23‐2.68), while no association was found between middle RHR tertile (73‐80 bpm) and the prevalence of stroke. Additionally, the effect of ORs in different RHR groups was equal, suggesting that the association between RHR and stroke was likely to be linear (P for trend = 0.003). Compared with RHR in the lower tertile (T1‐T2), the RHR T3 group was associated with a higher prevalence of stroke: The ORs were 1.38 (95% CI, 1.05‐1.82; P = 0.020) in the crude model and 1.47 (95% CI, 1.08‐2.01; P = 0.015) in the multivariate model with adjustment for sex, age, area, smoking, drinking, education status, occupation, sleep duration (workdays and non‐workdays), antihypertensive medications, family history of cardiac‐cerebral vascular diseases (CHD, stroke, diabetes, hypertension), BMI, WC, SBP, and DBP. Similarly, compared to those with no hypertension, hypertensives had a significantly increased prevalence of stroke (OR = 3.76, 95% CI, 2.39‐5.92; P < 0.001).
Table 2.
Individual effect of RHR and hypertension on stroke
| Risk factor | Events, n (%) | Stroke OR (95% CI), P value | ||
|---|---|---|---|---|
| Crude | Model I | Model II | ||
| RHR, bpm | ||||
| Per 10 bpm increase | 211 (1.4) | 1.15 (1.02, 1.30), 0.023 | 1.20 (1.07, 1.35), 0.003 | 1.18 (1.03, 1.34), 0.017 |
| Tertiles | ||||
| T1 (<73) | 56 (1.2) | Ref. | Ref. | Ref. |
| T2 (73‐80) | 65 (1.4) | 1.15 (0.80, 1.65), 0.451 | 1.26 (0.88, 1.81), 0.214 | 1.49 (0.99, 2.23), 0.055 |
| T3 (>80) | 90 (1.7) | 1.49 (1.06, 2.08), 0.021 | 1.69 (1.21, 2.38), 0.003 | 1.82 (1.23, 2.68), 0.003 |
| P for trend | 0.018 | 0.002 | 0.003 | |
| Categories | ||||
| T1‐T2 (≤80) | 121 (1.3) | Ref. | Ref. | Ref. |
| T3 (>80) | 90 (1.7) | 1.38 (1.05, 1.82), 0.020 | 1.51 (1.14, 1.99), 0.004 | 1.47 (1.08, 2.01), 0.015 |
| Hypertension | ||||
| No | 47 (0.4) | Ref. | Ref. | Ref. |
| Yes | 164 (3.9) | 9.05 (6.53, 12.54), <0.001 | 5.41 (3.83, 7.63), <0.001 | 3.76 (2.39, 5.92), <0.001 |
Model I: regression was done with adjustment for sex and age. Model II: regression was done with adjustment for sex, age, area, smoking, drinking, education status, occupation, sleep duration (workdays and non‐workdays), antihypertensive medications, family history of cardiac‐cerebral vascular diseases (CHD, stroke, diabetes, hypertension), BMI, WC, SBP, and DBP.
When RHR and hypertension were examined together, as shown in Figure 1, there was a dose‐response relationship between RHR tertile and stroke, stratified by hypertension status. The highest prevalence of stroke was in the group with RHR > 80 bpm and hypertension, with an OR of 11.59 (95% CI, 4.95‐27.13; P < 0.001) compared with normotensives with RHR < 73 bpm. To further explore the combined effect of hypertension and RHR, participants were categorized into four groups according to status of hypertension and RHR (Table 3). Compared with normotensives with RHR ≤ 80 bpm, in a multivariate‐adjusted model, the OR (95% CI) of stroke for hypertensives with RHR ≤ 80 bpm and hypertensives with RHR > 80 bpm was 3.61 (2.11, 6.17) and 5.47 (3.13, 9.56), respectively (all P < 0.001). Hypertensives with RHR > 80 bpm had the highest prevalence of stroke compared with their counterparts. However, no significant association between RHR > 80 bpm and stroke were found among normotensives.
Figure 1.
Dose‐response relationship between RHR tertiles and multivariable‐adjusted ORs and 95% confidence intervals of stroke, stratified by hypertension status. Adjustment for sex, age, area, smoking, drinking, education status, occupation, sleep duration (workdays and non‐workdays), antihypertensive medications, family history of cardiac‐cerebral vascular diseases (CHD, stroke, diabetes, hypertension), BMI, WC, SBP, and DBP
Table 3.
Joint effects of RHR levels and hypertension (Yes, No) on stroke
| Combined Groups | N |
Events n (%) |
Stroke OR (95% CI), P value | |||
|---|---|---|---|---|---|---|
| Hypertension | RHR, bpm | Crude | Model I | Model II | ||
| No | ≤80 | 6886 | 29 (0.4) | Ref. | Ref. | Ref. |
| >80 | 3602 | 18 (0.5) | 1.19 (0.66, 2.14), 0.568 | 1.33 (0.74, 2.40), 0.348 | 1.37 (0.74, 2.53), 0.316 | |
| Yes | ≤80 | 2645 | 92 (3.5) | 8.52 (5.60, 12.97), <0.001 | 5.14 (3.33, 7.93), <0.001 | 3.61 (2.11, 6.17), <0.001 |
| >80 | 1544 | 72 (4.7) | 11.57 (7.49, 17.86), <0.001 | 7.44 (4.76, 11.63), <0.001 | 5.47 (3.13, 9.56), <0.001 | |
| P for trend | <0.001 | <0.001 | <0.001 | |||
Model I: regression was done with adjustment for sex and age. Model II: regression was done with adjustment for sex, age, area, smoking, drinking, education status, occupation, sleep duration (workdays and non‐workdays), antihypertensive medications, family history of cardiac‐cerebral vascular diseases (CHD, stroke, diabetes, hypertension), BMI, WC, SBP, and DBP.
In addition, a GAM and fully adjusted smooth curve fitting (penalized spline method) were conducted to assess the association between RHR and stroke in different status of hypertension. Figure 2 presented a linear association between RHR and stroke among participants with hypertension, but almost horizontal association among participants without hypertension, which suggested that elevated RHR was associated with increased prevalence of stroke especially among hypertensives.
Figure 2.
Association between RHR and stroke stratified by hypertension status. The smooth curve fitting presented a linear association between RHR and stroke among participants with hypertension, but almost horizontal association among participants without hypertension. Adjustment factors included sex, age, area, smoking, drinking, education status, occupation, sleep duration (workdays and non‐workdays), antihypertensive medications, family history of cardiac‐cerebral vascular diseases (CHD, stroke, diabetes, hypertension), BMI, WC, SBP, and DBP
In subgroup analysis, we further explored the role of other covariables on the association between RHR (≤80 vs >80 bpm) and stroke. As shown in Figure 3, the associations between elevated RHR and stroke were consistent in the following subgroups: sex, age, BMI, smoking, and drinking (all P for interaction > 0.05).
Figure 3.
Effect size of rest heart rate on stroke in each subgroup. Adjusted, if not stratified, for Adjusted for sex, age, area, smoking, drinking, education status, occupation, sleep duration (workdays and non‐workdays), hypertension, antihypertensive medications, family history of cardiac‐cerebral vascular diseases (CHD, stroke, diabetes, hypertension), BMI, WC, SBP, and DBP
4. DISCUSSION
In this large population‐based cross‐sectional study, we investigated the independent and joint effect of RHR and hypertension on the increased prevalence of stroke in Southern China. This study indicated elevated RHR (>80 bpm), and hypertension was independently and jointly associated with the increased prevalence of stroke. The fully adjusted smooth curve fitting presented a linear association between RHR and stroke among participants with hypertension, but almost horizontal association among participants without hypertension. These findings suggested that elevated RHR was associated with increased prevalence of stroke especially among hypertensives.
Several reports have also yielded some conflicting results. The PERFORM study did not show significant increase in risk of fatal and nonfatal ischemic stroke in patients with RHR > 70 bpm or with 5‐bpm RHR increase.18 The Kailuan study predicted that elevated RHR was not associated with the risk of any stroke.19 Similarly, Martin Lindgren et al20 also found no significant association between RHR and ischemic stroke. However, some of the associations have proved significant among men only.9, 21 A prospective study conducted for 169 871 Chinese adults ≥ 40 years showed that elevated RHR increased the risks of total stroke and hemorrhagic stroke, not ischemic stroke.9 Even so, a recent large meta‐analysis showed that rise in RHR per 10 bmp increased the risk for stroke by 6%.22 Woodward et al23 found that that subjects with RHR > 80 bpm compared with those with RHR < 65 bpm had 47% greater risk for hemorrhagic stroke, 38% for ischemic stroke, and even 68% higher risk for unclassified stroke. In our study, we found that subjects with RHR > 80 bpm compared with those with RHR < 73 bpm were significantly associated with the prevalence of total stroke. These results were consistent when the analysis was stratified by age, sex, hypertension, smoking, and drinking status. Further research is needed to examine whether interventions aimed to reduce RHR decrease stroke risk.
These conflicting results might be attributed to the differences in cohort characteristics, sample size, race, subtype of stroke, RHR measurement, and adjustment of confounders. Several previous studies indicated that elevated RHR was more likely associated with hemorrhagic stroke, but not with ischemic stroke. That was why some studies concluded negative results between RHR and the risk of stroke. Furthermore, RHR was measured by electrocardiography in many epidemiologic studies and clinical trials. While in our study, RHR was measured at the end of each BP measurement by standardized electronic monitors. In 2015, the panel experts from the European Society of Hypertension remarked that electrocardiographic measurement was allowed but was not recommended even for research.8 RHR should be measured after each blood pressure reading. Because the use of electrocardiography implies an increase in costs and whether electrocardiographic measurement may actually be advantageous for research purposes is still unknown. In addition, electrocardiography is performed in the lying posture, whereas RHR measurement from standardized electronic monitors can be obtained in the sitting position together with BP.
Several mechanisms possibly explain the association between elevated RHR and stroke. Above all, elevated RHR is associated with higher levels of oxidative stress and endothelial dysfunction that lead to a higher rate of atherosclerosis.24, 25 Additionally, lower heart rates improve vascular compliance, an important determinant of blood pressure and cardiac autonomic tone.26 In aggregate, these data provide evidence that elevated heart rates predispose to several markers that are associated with the development of atherosclerotic disease, and also link high heart rates with ischemic stroke through shared risk factors (eg, atherosclerosis, hypertension). Furthermore, elevated RHR is usually related to sympathetic over‐activity, which reflects increased stress or anxiety, vascular stiffness, cardiac remodeling, atherosclerosis, metabolic changes (insulin resistance, dyslipidaemia, and obesity) and additionally has pro‐arrhythmic effect.27, 28 Recent reports have implicated RHR with the development of atrial fibrillation.29, 30 Possibly, individuals who develop atrial fibrillation and subsequent ischemic stroke have a stronger association between RHR and stroke.
As we know, hypertension is the most important and strongest modifiable risk factor for stroke.16 Previous studies have indicated that subjects with hypertension typically have faster heart rates compared with those with normal BP.31 In the Glasgow Blood Pressure Clinic Study, hypertensive patients with a HR persistently > 80 bpm had an increased risk of all‐cause mortality and cardiovascular mortality,32 which suggested that a high heart rate and hypertension may act synergistically in the development of CVD. However, few studies reported the combined effects of RHR and hypertension on the risk of stroke. Zhong et al33 reported that hypertensive patients with >80 bpm had the highest risk of stroke. Similarly, our study also found elevated RHR and hypertension were jointly associated with the increased prevalence of stroke. Compared with normotensives with RHR < 73 bpm, RHR had an independent effect on the increased prevalence of stroke; yet, compared with normotensives with RHR ≤ 80 bpm, normotensives with RHR > 80 bpm were no association with stroke.33 Moreover, the smooth curve fitting presented a linear association between RHR and stroke among participants with hypertension, but almost horizontal association among participants without hypertension. These findings suggested that elevated RHR was associated with increased prevalence of stroke especially among hypertensives.
Some limitations of this study should be noted. First, as a cross‐sectional design, it was less power to estimate the causal the association of RHR, hypertension, and stroke. Further prospective follow‐up studies are needed to verify these findings. Second, several baseline characteristics were obtained through questionnaires, and there may be recall bias. Third, we excluded the participants who were receiving β blockers when being interviewed, but did not collect other heart rate modifying drugs (such as ivabradine) or condition (such as hyperthyroidism). The last but not the least, diabetes mellitus was a major risk factor of stroke and was possibly associated with elevated RHR. However, in our questionnaire, we did not collect the history of diabetes mellitus.
In conclusion, elevated RHR and hypertension were independently and jointly associated with the increased prevalence of stroke. These findings suggested that elevated RHR was associated with increased prevalence of stroke especially among hypertensives. Further longitudinal investigations are needed to confirm our findings and to examine whether heart rate modifying therapies are able to prevent future cerebrovascular events.
DISCLOSURE
None.
AUTHOR CONTRIBUTIONS
Conceptualization and methodology: HHB and XSC. Software: LHH. Validation: LHH, XH, WZ, CJY, QL, JXL, PL, YQW, QHW, ZWW, RLG, HHB, and XSC. Formal analysis: LHH and DZ. Investigation: LHH, XH, WZ, and CJY. Data curation: HHB and XSC. Writing (original draft preparation): LHH. Writing (review and editing): HHB and XSC. Supervision: HHB and XSC. Project administration: JXL, PL, YQW, QHW, ZWW, RLG, HHB, and XSC. Funding acquisition: ZWW, RLG, and XSC.
Supporting information
ACKNOWLEDGMENTS
We acknowledge the contribution the all staff who participated in this study as well as the study participants who shared their time with us.
Hu L, Huang X, Zhou W, et al. Associations between resting heart rate, hypertension, and stroke: A population‐based cross‐sectional study. J Clin Hypertens. 2019;21:589–597. 10.1111/jch.13529
Funding information
This research was supported by the National Key R&D Program in the Twelfth Five‐Year Plan (No. 2011BAI11B01 and 2014ZX09303305) from the Chinese Ministry of Science and Technology and National Natural Science Foundation of China (No. 81560051).
Contributor Information
Huihui Bao, Email: huihui_bao77@126.com.
Xiaoshu Cheng, Email: xiaoshumenfan126@163.com.
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