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The link between elevated long-term resting heart rate and SBP variability for all-cause mortality

Yang, Xiaoleia,*; Hidru, Tesfaldet H.a,d,*; Wang, Binhaoc,*; Han, Xua; Li, Huihuaa,d; Wu, Shoulingb; Xia, Yunlonga

doi: 10.1097/HJH.0000000000001857
ORIGINAL PAPERS: Heart and vessels
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Background: Resting heart rate (RHR) and SBP are important risk markers for all-cause mortality. However, the link between increased RHR and SBP for all causes of death remained unclear. We investigated the link between an increased visit-to-visit variation of RHR and SBP for risk of all-cause mortality in the general population.

Methods: We examined long-term visit-to-visit variation of RHR and blood pressure among 46 751 residents of Tangshan city, China (mean age: 52.58 ± 11.64 years; 78% men). Cox proportional hazard model was used to estimate the hazard ratios and 95% confidence interval (CI) adjusting for clinical characteristics assessed at the last examination (2010–2011).

Results: A total of 1667 deaths were recorded over 4.97 ± 0.69 years follow-up. A rise in 1 SD of heart rate (4 bpm) was associated with an increased risk of death among the participants in third and fourth quartile of SBP-SD in the subgroups of general population [hazard ratio (95% CI) = 1.10 (1.03–1.67) and 1.16 (1.03–1.30), respectively], men [hazard ratio (95% CI) = 1.10 (1.02–1.17) and 1.16 (1.03–1.30), respectively], and participants under 65 years of age [hazard ratio (95% CI) = 1.16 (1.02–1.33) and 1.20 (1.03–1.39), respectively]. Similarly, 1-SD increase of SBP (7 mmHg) was associated with an increased risk of death among the participants in the highest quartiles of RHR-SD in the subgroups of the general population, men, and under 65 years of age.

Conclusion: An elevated long-term SBP variability combined with an increased RHR variability or vice versa may amplify the risk of all-cause mortality in general population, as well as in men and middle-age group.

aDepartment of Cardiology, Institute of Cardiovascular Diseases, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning

bDepartment of Cardiology, Kailuan General Hospital, Tangshan, Hebei

cArrhythmia Center, Ningbo First Hospital, Ningbo, Zhejiang

dSchool of Public Health, Dalian Medical University, Dalian, Liaoning, China

Correspondence to Yunlong Xia, PhD, Department of Cardiology, Institute of Cardiovascular Diseases, First Affiliated Hospital of Dalian Medical University, Dalian 116011, Liaoning, China. Tel: +86 0411 83635963; e-mail: yunlong_xia@126.com

Abbreviations: CI, confidence interval; CRP, C-reactive protein; CVD, cardiovascular disease; FPG, fasting plasma glucose; KCS, Kailuan cohort study; RHR, resting heart rate; TC, total cholesterol; VVV, visit to visit variation

Received 31 March, 2018

Revised 2 June, 2018

Accepted 14 June, 2018

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INTRODUCTION

Heart rate (HR) and blood pressure (BP) are two separate measurements, but both are interrelated components of the cardiovascular system. Any irregularities in one parameter may associate with fluctuations of another one. Furthermore, the presence of an uncontrolled HR or BP in general population is associated with an increased risk for adverse cardiovascular diseases (CVDs) effects. Although previously misunderstood, the importance of SBP and resting heart rate (RHR) [1,2] variability is becoming increasingly clear as important risk markers for CVD events and all-cause mortality. Several population-based epidemiological studies have been conducted in China, but the results were not consistent.

In the past few years, epidemiologic studies have revealed that SBP variability is an independent predictor of stroke, coronary heart disease, cognitive dysfunction, and all-cause mortality [3–5]. Also, SBP variability has been associated with poor outcomes in individuals with diabetes mellitus, coronary heart disease, heart failure, and renal disease, independent of mean BP or medication adherence [4,6,7]. Despite these findings in the previous studies, many in the field have been disinclined to recognize the adverse effect of SBP variation in a population with CVD [8,9]. On the other hand, elevated RHR is associated with increased risk for all-cause mortality in a population with and without CVD [1,2]. The Systolic Heart Failure Treatment trial reported that RHR variability has been associated with all-cause of death in heart failure patients [10].

In the past few years, it is clear that previous studies investigated the independent association between visit-to-visit RHR and SBP variations in the risk of all-causes of death in the general population [11,12]. Also, the Atrial Fibrillation Follow-Up Investigation of Rhythm Management Study reported that day-by-day variability of BP positively correlates with that of HR [13]. However, the threshold that could estimate the risk for all-cause mortality due to an increase in these parameters (SBP and RHR) is still uncertain. Hence, we examined the link between an increased RHR visit-to-visit variability (VVV) and SBP-VVV for all-cause mortality based on an increase in 1 SD of HR or SBP in the Chinese population.

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METHODS

Study design and population

We conducted a large contemporary population-based prospective cohort study based on the Kailuan cohort study (KCS) data to assess elevated long-term RHR variation and the risk of all-cause mortality in general population (ChiCTR-TNRC-11001489). The cohort consists of 101 510 ethnic Chinese participants enrolled in the KCS registries of Tangshan City, Hebei Province of China. All coal workers above the age of 18 years, regardless their sex status, were invited to participate in KCS, and those who had no history stroke, transient ischemic attack, and/or coronary heart disease at baseline were selected in KCS. RHR and SBP variability were assessed during the first 6 years (2006–2011) of the study, and outcomes were analyzed from the end of the third examination to the end of the follow-up period (December 2016). Clinical characteristics were assessed at the end of repeated ECG and BP examinations (third examination, 2010–2011) and adjusted to RHR-SD and SBP-SD to prove that RHR and SBP variability assessed over the long period of time was not a consequence of deteriorating health and/or appearance of diseases. Participants who received at least three consecutive examinations with complete ECG and SBP recordings were eligible for this study. A total of 46 751 participants were included in the data analysis after excluding those with cardiovascular events (prior history of myocardial infarction/stroke or coronary artery disease, unstable angina and any coronary revascularization procedure, congestive heart failure), had atrial fibrillation or flutter on their ECG readings at examination 1, 2, or 3, had received pacemaker before examination 3, had less than 6-years follow-up period or died during the first 6 years, and were under the use of β blockers and nondihydropyridines medication through the entire period of BP and RHR assessment. A detailed description of the assessment follow-up is given in Fig. 1. The study was approved by the Ethics Committee of Kailuan General Hospital and First Affiliated Hospital of Dalian Medical University.

FIGURE 1

FIGURE 1

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Assessment of long-term variation in resting heart rate

RHR was obtained using a 10-s 12-lead resting supine ECG from every participant between 0600 and 0900 h. The SD of the RHR (RHR-SD) over the first three examinations was calculated as described previously [14].

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Assessment of long-term blood pressure variability

During the study period, SBP and DBP were measured twice from the upper right arm after 5 min of rest in the seated position by a trained health professional, using a calibrated mercury sphygmomanometer with the cuff appropriate for a participant's arm measurements, and the mean of these two measurements were recorded as the DBP and SBP values. Additional measurements were made if the first two results were quite different. The mean of the two closest readings (including the last reading) was calculated to determine the reported BP for each participant. Pulse pressure (PP) readings were calculated by subtracting DBP from SBP. The SD of the SBP (SBP-SD) over the first three examinations was calculated by the following formulae:

where SBPi is the SBP of the participant at the examination, and

is the average SBP of the participant across examinations. The SD of the DBP (DBP-SD) and the SD of the PP (PP-SD) over the first three examinations were calculated similar to SD of the SBP.

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Collection and definitions of potential covariates

A standardized interview was conducted during each examination to collect data on health-related lifestyle, disease history, family history, and use of antihypertensive drugs including angiotensin-converting-enzyme inhibitor, AT1 blocker, calcium channel blockers, only dihydropyridines, diuretics, and others (such as α blockers and traditional Chinese medicine, etc.). BMI was calculated as the weight (kg) divided by height squared (m2). Fasting (>8 h) blood specimens were collected and were biochemically examined for the concentration of fasting plasma glucose (FPG) and C-reactive protein (CRP). Elevated CRP was defined as the level at least 2 mg/l. Standard enzymatic methods were used to measure serum total cholesterol (TC) and HDL. Smoking status was grouped into three categories: current smoker (history of cigarette smoking during the past year), former smoker (history of ever smoking), and never smoker (participants who had never smoke in their lifetime). Physical exercise was divided into two categories: sedentary/moderate activity for less than 4 h/week and high/intense activity for at least 4 h/week. Diabetes mellitus was defined as FPG at least 7.0 mmol/l or random plasma glucose at least 11.1 mmol/l or a self-reported diabetes history with the current use of antidiabetes medication. Hypertension was defined as SBP at least 140 mmHg and/or DBP at least 90 mmHg, or a self-reported history of hypertension and currently undergoing a treatment with antihypertensive medication.

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Outcome of mortality

The primary outcome was all-cause mortality occurring beyond the first three examinations following registration in the KCS. All participants were investigated for death occurrence through the hospital records, providing all available clinical details. In addition, to improve the quality of the data on death event, death certificates were regularly screened from state vital statistics offices annually for the sites included under the KCS. All deaths were evaluated by an independent committee.

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Statistical analysis

Participants were stratified into quartiles based on the SBP-SD (first, <5.8 mmHg; second, 5.8–9.7 mmHg; third, 9.7–13.9 mmHg; and fourth, >13.5 mmHg) and RHR-SD (first, <3.6 bpm; second, 3.7–5.8 bpm; third, 5.9–8.5 bpm; and fourth, RHR-SD >8.5 bpm). All continuous variables were expressed as mean ± SD, and categorical variables were expressed as counts and percentiles. Quartiles were tested for differences using χ2 test and analysis of variance for categorical and continuous data, respectively. Kaplan–Meier method was used to estimate survivor functions for quartiles. Log-rank test for trend was considered to compare the survival distributions. Participants were grouped based on age (≤65 and >65 years) and sex.

In this study, we first calculated the cumulative mortality and hazards ratios for all-cause mortality associated with quartiles of SD of RHR and SBP to confirm the relationship between RHR or SBP variation over years and all-cause mortality. Later, we calculated hazard ratios and corresponding 95% confidence intervals (CI) for the occurrence of all-cause mortality associated with 1-SD increase in RHR and SBP. For primary outcomes (all-cause mortality), we drafted two distinct Cox models for RHR and SBP quartiles and continuous SD of RHR and SBP. The first Cox proportional hazard model was performed to establish the association of RHR-SD quartiles with an increase in 1 SD in SBP, modeled as a continuous variable, for the occurrence of all-cause mortality. The second Cox model was considered to establish the association of SBP-SD quartiles with an increase in 1 SD in RHR, modeled as a continuous variable, for the occurrence of all-cause mortality. The Cox models were adjusted for age, sex, BMI, high/intensive activity, mean HR, mean SBP, FPG, TC, HDL, elevated CRP, and antihypertensive medication. All statistical analyses were conducted using SAS 9.3 (SAS Institute, Cary, North Carolina, USA). A P value of less than 0.05 was considered statistically significant.

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RESULTS

Baseline characteristics of the participants

The current study includes 46 751 participants. Baseline characteristics of the participants by quartiles of SD of RHR and SBP are given in Table 1. Mean age was 52.58 ± 11.64 years, 78% were men. Mean ± SD of the average RHR over the examination period (6 years) was 73.71 ± 7.88 bpm, and the mean of the average SBP was 129.62 ± 16.72 mmHg. Participants in higher quartiles of SD of RHR and SBP had higher mean DBP, HR, and FPG than in lower quartiles. In addition, participants in higher quartiles of SD of RHR and SBP were older, more likely to have hypertension, and a higher proportion of elevated CRP. The values of the mean BMI and TC over the examination period (6 years) of the study were lower in the lowest quartiles of SD of SBP. Also, participants in higher quartiles of SD of SBP were more likely to have diabetes mellitus, and less likely to be current smokers unlike the participants in higher quartiles of SD of RHR. The participants in the highest quartiles of SBP-SD and RHR-SD received more antihypertensive drugs. Baseline characteristics of the participants by quartiles of SD of DBP and PP are supplemented in Table S1, http://links.lww.com/HJH/A975.

TABLE 1

TABLE 1

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Relationship between visit-to-visit variability in resting heart rate/SBP/DBP/pulse pressure and all-cause mortality

Table 2 presents the hazard ratios of death among participants grouped by quartile of RHR-SD and SBP-SD. The mortality rates in the first quartile through the fourth quartile were 2.3, 2.9, 3.3, and 5.9%, respectively, for SBP, and 2.4, 3.2, 4.0, and 4.6%, respectively, for RHR-SD. In the entire cohort, compared with participants of the first quartile of RHR-SD, the age and sex-adjusted hazard ratios and 95% CI of all causes of death were 1.32 (1.13–1.54), 1.59 (1.37–1.85), and 1.72 (1.49–1.99) in participants of the second, third, and fourth quartiles, respectively. Likewise, participants of the second, third, and fourth quartiles of SBP-SD showed increased age and sex-adjusted hazard ratios of all causes of death [Q2 = 1.15 (0.98–1.35), Q3 = 1.18 (1.02–1.38), and Q4 = 1.65 (1.44–1.90)] compared with those in the first quartile. The subsequent analysis considered age, sex, BMI, current smoker, mean SBP, mean resting HR, FPG, TC, HDL, elevated CRP, and ACE inhibitor. The results showed that the effects of RHR-SD and SBP-SD were slightly attenuated, but remained statistically significant for the fourth versus the first quartile of RHR-SD and SBP-SD. The hazard ratio of death for the fourth versus the first quartile of RHR-SD was 1.43 (1.23–1.67), whereas that for the fourth versus the first quartile of SBP-SD was 1.45 (1.26–1.68). The trends of hazard ratios of all causes of death across the four quartiles were linear for both RHR-SD and SBP-SD (P for trend <0.001). Cumulative incidence of all-cause mortality shows a progressively higher risk of death across quartiles of SBP-SD and RHR-SD (Fig. 2; log-rank test, all P < 0.001).

TABLE 2

TABLE 2

FIGURE 2

FIGURE 2

The hazard ratios of all-cause mortality were similar across quartiles of DBP-SD (Table S2, http://links.lww.com/HJH/A975). Compared with participants of the first quartile of DBP-SD, the multivariate adjusted hazard ratios and 95% CI of all causes of death were 0.88 (0.75–1.04), 0.95 (0.82–1.08), and 1.13 (0.99–1.30) for the second, third, and fourth quartiles, respectively. No association between variability in DBP and mortality was present after adjustment for the potential confounders.

The participants in the highest PP-SD quartile had a significantly increased risk of death. This association persisted even after adjusting for potential confounding factors, including age, sex, BMI, current smoker, mean PP, mean resting HR, FPG, TC, HDL, elevated CRP, and ACE inhibitor. Compared with participants in the first quartile, the hazard ratios (95% CI) for the subjects in Q2, Q3, and Q4 were 1.09 (0.92–1.29), 1.27 (1.08–1.49), and 1.48 (1.27–1.72), respectively (P for trend <0.001). The association between PP-SD and the risk of death is presented in Table S3, http://links.lww.com/HJH/A975.

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The effect of resting heart rate and SBP/pulse pressure interaction in all cause of death

The effect of an increase in 1 SD (4 bpm) in resting heart rate

Table 3 presents the hazard ratios associated with an increase in 1 SD (4 bpm) in RHR among participants grouped by quartiles of SBP-SD. The participants in third and fourth quartile had an independent increase in risk for all-cause mortality [hazard ratio (95% CI) = 1.10 (1.03–1.67) and 1.16 (1.03–1.30), respectively) in the general population. We observed a similar independent increase in risk for all-cause mortality among male participants in third and fourth quartile [hazard ratio (95% CI) = 1.10 (1.02–1.17) and 1.16 (1.03–1.31), respectively] after adjusting for potential confounders. Moreover, the Cox regression confirmed that participants less than the age of 65 years in the second, third, and fourth quartiles of SBP-SD had an independent increase in risk for all-cause mortality [hazard ratio (95% CI) = 1.15 (1.05–1.26), 1.16 (1.02–1.33), and 1.20 (1.03–1.39), respectively].

TABLE 3

TABLE 3

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The effect of an increase in 1 SD (7 mmHg) SBP

Table 3 presents the hazard ratio associated with an increase in 1 SD (7 mmHg) in SBP among participants grouped by quartiles of RHR-SD. Among the general population, an increased risk for all-cause mortality was confirmed for SBP-SD quartiles 2, 3, and 4 [hazard ratio (95% CI) = 1.11 (1.01–1.23), 1.14 (1.07–1.21), and 1.21 (1.12–1.30)]. Similarly, the risk of all-cause mortality increased across male participants in RHR-SD quartiles 2, 3, and 4 [hazard ratio (95% CI) = 1.12 (1.01–1.25), 1.14 (1.07–1.22), and 1.20 (1.10–1.30), respectively]. Also, an increased risk of all-causes of mortality was observed across RHR-SD quartiles 3 and 4 among participants less than 65 years old [hazard ratio (95% CI) = 1.10 (1.01–1.19) and 1.18 (1.07–1.30), respectively]. In addition, with an increase in 1 SD of SBP, participants greater than 65 years of age had a higher risk for all-cause of mortality across quartiles of RHR-SD.

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The effect of resting heart rate and pulse pressure interaction in all cause of death

Table S4, http://links.lww.com/HJH/A975 presents the hazard ratios associated with an increase in 1 SD (4 bpm) in RHR among participants grouped by quartiles of PP-SD. Participants in the highest PP-SD quartile had a significantly increased risk of death after controlling for potential confounders across study visits.

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Absolute risk of mortality

We calculated 5 years absolute risk of mortality using Cox proportional hazard model (Fig. 3). Adjusted hazard ratio for 5 years absolute risk of mortality was increased in each group of quartiles of RHR-SD and SBP-SD.

FIGURE 3

FIGURE 3

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Sensitivity analyses

We investigated the hazard ratio for SDs of BP and HR with the aim to exclude the BP influence on mortality. We investigated the hazard ratio and 95% CI for 1-SD increase in SBP-SD and RHR-SD for participants without history of hypertension (based on the reported history; n = 40 098) and for participants whose BP was within the normal range defined as SBP less than 140 mmHg and DBP less than 90 mmHg (either free of hypertension or controlled their BP during the third examination; n = 32 061). The fourth quartile of SBP-SD and RHR-SD was associated with the highest risk of all-cause death. We included a linear trend line to show whether the hazard ratio is increasing at a steady rate (Fig. S1, http://links.lww.com/HJH/A975). A linear trend line clearly shows that hazard ratios have consistently risen through quartiles of RHR-SD/SBP-SD in both groups (no history of hypertension and controlled BP), suggesting that hypertension status was not influenced the outcome of the data.

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DISCUSSION

In this study conducted in 46 751 participants from the Kailuan study, RHR and SBP variability were independently associated with an increased risk of all-cause of death. This association of the RHR-SD and SBP-SD with death occurrence remains consistent after multiple adjustments for potential confounders. Participants with the highest quartile of RHR-SD and SBP-SD (RHR-SD > 8.5 bpm and SBP-SD ≥ 13.9 mmHg) had the highest risk of death compared with the participants in the lowest quartiles of RHR-SD and SBP-SD variability. Also, the current study found a significant association between VVV in PP and all-causes of death. However, there was no association for VVV in DBP.

Variabilities of RHR and SBP are usually dismissed as random fluctuations or obstacles to accurate HR and BP. However, variabilities of SBP and RHR are important risk markers for CVD events and all-cause mortality [15,16], alongside other risk factors such as diabetes, smoking, hyperlipidemia, and obesity [17,18]. Nevertheless, for many years, variations of RHR and SBP have not been included among the main cardiovascular and mortality risk factors due to the potential of interdependence with other risk factors and incomplete understanding of the mechanisms linking them to CVD and all-cause mortality. Significantly, our study has revealed that a rate control strategy is not inferior to a CVD control strategy in preventing risk of all-cause of death.

Previous SBP variability studies demonstrate an association with multiple CVD events. According to NHANES III [5] and ALLHAT [4] longitudinal studies, SBP was independently associated with the risk of all-cause of mortality and CVD events. Also, the current study found that visit-to-visit variability in SBP is independently associated with all-cause of death among the general population, even after adjustment for the confounding variables, which confirmed that SBP variability predicts the subsequent occurrence of all-cause mortality. The risk of death was higher among those with SBP-SD in the top quartile compared with those with SBP variability in the lowest quartile. The findings regarding associations between SBP-SD and all-cause mortality remain consistent after multivariate adjustment for the potential confounding factors; hence, SBP variability could be a potential marker of all-cause mortality in the general population. These results provide insights into the development of comprehensive public health strategy to increase quality and years of healthy life.

In the general population, greater HR variability, defined as RHR–visit-to-visit variability, is associated with a higher risk for all-cause mortality. Recently, Wang et al.[14] reported that elevated RHR (RHR-SD) variability is a potential predictor of long-term mortality among aged population without an established CVD in a study that entertained extensive adjustment for potential confounding factors in the general population. Also, our findings support that RHR variability is predictive of all-cause mortality, even after multiple adjustments for potential confounders. Importantly, we observed an increased risk of all-cause of death with an increase in 1 SD in RHR among the participants in the SBP quartiles. Similarly, the SD of RHR was also increasingly associated with a risk of all-cause of death in men after adjusting for potential confounders, but not in women. This discrepancy could be explained by the sex differences in the prevalence of hypertension, which is higher in men [19], and its associated adverse cardiovascular outcomes [20]. Also, these discrepancies could be due to the relatively small sample size of the women. The SD of HR was also significantly associated with risk of death in participants younger than 65 years of age, whereas this association was weakened to a nonsignificant level when we censored deaths within 6 years of enrollment in age group greater than 65 years. Beat-by-beat HR variability is known to be negatively associated with age [21], which may mitigate the effect of RHR variability for all-cause mortality in the group age at least 65. The RHR-mediated arterial stress has gained attention among the potential mechanisms underlying CVD progression and clinical manifestations as RHR relate to sympathetic overactivity, atherosclerosis, and plaque vulnerability [22]. However, the attenuated predictive power of RHR could be attributed to the difference in the intensity of physical activity. A period of 15–30 min of daily moderate exercise could prevent RHR associated all-cause of death by 40% [23].

The SD of SBP was significantly associated with risk of death in the general population. In this study, SBP variability was significantly increased with age. Arterial stiffness associated with hypertension and aging can amplify random BP changes and intensify variability. Also, some studies had previously confirmed an association between SBP variability and the risk of microvascular complications in the diabetic population [24].

In the current study, no association was found between visit-to-visit variability in DBP and all-cause mortality. This finding is consistent with a previous report [5]. For example, higher visit-to-visit variability in DBP was not associated with all-cause of mortality in general population enrolled in the Third National Health and Nutrition Examination Survey (NHANES III) [5].

The visit-to-visit variability in PP was associated with all-cause of mortality. The risk of death was higher among those with PP-SD in the top quartile compared with those with PP variability in the lowest quartile. Significantly, the findings regarding associations between PP-SD and all-cause mortality remain consistent even after controlling for potential confounding factors. Therefore, further study is needed to confirm these results, and identify the putative mechanisms involved in this association.

The current study has a large sample size and addresses the prognostic implications of long-term SBP and RHR variability. However, as with all observational studies, this study has several limitations. First, the link between variability and death outcome may not necessarily imply a cause–effect relationship. Second, there is still no consensus on the best way to define visit-to-visit RHR and SBP variability. Third, variations in participant activities before measurement may still represent a source of hemodynamic variability. Fourth, RHR and SBP show variations over more prolonged periods; our definitions of variability were based upon annual measurements of RHR and SBP, more frequent assessments could have improved the phenotyping of variability that could result from age-related physiological changes. Fifth, a more reliable method to calculate RHR and SBP variability could be obtained by excluding the influence of physiological variation. Although we recorded RHR and BP in the same season annually to define RHR and SBP variability at the same time, physiological cause and/or pathological variation cannot be clearly defined as autonomic dysfunction can cause swings in hemodynamic variables. Sixth, arterial stiffness caused by aging and hypertension can magnify random BP changes and increase variability to strengthen the validity of our associations. Seventh, our data may likely underestimate the true association between the RHR and the risk of all-causes of death in women population. Elevated variability may, thus, only offer a marker of the above-mentioned conditions rather than an independent risk factor.

In conclusion, elevated long-term RHR and SBP variations are independent risk markers for all-cause mortality in the general population. An elevated long-term SBP variability combined with an increased RHR variability may amplify the risk of all-cause mortality among men and middle-age group.

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ACKNOWLEDGEMENTS

Reprint request: reprints are not to be made available.

Previous presentations: this work has not presented in any conference or journal as a whole or in part.

The work was supported by the grants from National Natural Science Foundation of China (grant number: 81570313).

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Conflicts of interest

There are no conflicts of interest.

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* Xiaolei Yang, Tesfaldet H. Hidru, and Binhao Wang contributed equally to the article.

Keywords:

all-cause mortality; blood pressure; heart rate; Kailuan study; resting heart rate; SBP

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