Skip to main content
Erschienen in: BMC Cardiovascular Disorders 1/2020

Open Access 01.12.2020 | Research article

Correlation of resting heart rate with anthropometric factors and serum biomarkers in a population-based study: Fasa PERSIAN cohort study

verfasst von: Yashar Goorakani, Massih Sedigh Rahimabadi, Azizallah Dehghan, Maryam Kazemi, Mahsa Rostami Chijan, Mostafa Bijani, Hadi Raeisi Shahraki, Ali Davoodi, Mojtaba Farjam, Reza Homayounfar

Erschienen in: BMC Cardiovascular Disorders | Ausgabe 1/2020

Abstract

Background

There is a positive association between raised resting heart rate (RHR), and all causes of mortality and shorter life expectancy. Several serum biomarkers and some anthropometric factors can affect the resting heart rate. This study aimed to investigate the determinants of resting heart rate in a large random sample of the Iranian population.

Material and methods

It is a standardized, retrospective study and the subjects were chosen from the baseline survey of the Prospective Epidemiological Research Study in IrAN (PERSIAN) Fasa non-communicable disease cohort study. It was conducted from winter 2014 to summer 2019 and after obtaining informed consent from a random sample, all the eligible subjects were enrolled. All anthropometric factors and biologic laboratory factors were collected and analyzed by implement smoothly clipped absolute deviation (SCAD) linear regression and SCAD quantile regression. The comparisons between males and females were done via independent T-test.

Results & conclusion

A total number of 9975 persons from 35 to 90 years old were included. The overall median resting heart rate was 74 (interquartile range:66–80). Mean age has no important difference between males and females (P = 0.79) but, resting heart rate was significantly higher in females (76.6 versus 71.4, P < 0.001). All anthropometric factors except wrist circumference were higher in females (P < 0.05). Age has an adverse effect on resting heart rate and also, there was a direct association between resting heart rate and systolic blood pressure and blood glucose. Alpha-blockers (coefficient = 5.2) and Beta1-blockers (coefficient = − 2.2) were the most effective drugs with positive and negative effects on resting heart rate respectively. Lower hemoglobin, obesity, and more body mass index, and more low-density lipoprotein were associated with more resting heart rate.
Continuing the monitoring of this sample via our cohort study and put to action multinational prospective researches with large sample sizes and long follow-ups can lead to more precise results and better scientific judgments.
Hinweise
Yashar Goorakani and Massih Sedigh Rahimabadi contributed equally to this work.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Introduction

Elevated resting heart rate (RHR) is associated with an increased risk of cardiovascular disease and shorter life expectancy [1]. Epidemiologic studies have demonstrated that elevated RHR is strongly associated with all causes of mortality, atherosclerosis, and arterial stiffness [2, 3]. Metabolic abnormalities, left ventricular dysfunction, and ventricular Arrhythmias showed to be correlated with higher resting heart rate in general population and some subgroups including the hypertensive and those with established coronary artery disease (CAD) [4]. A few studies have shown that some biologic laboratory factors can affect the resting heart rate, particularly in non-Western populations [57]. For example, some of the previous investigators have explored the relationship between higher RHR and the increased blood pressure, and demonstrated that there is a positive correlation [8, 9]. However, there are significant controversies in the results of previous surveys [1012]. And to the best of our knowledge, all of these studies have been performed in western population and also didn’t adjust all major biomarkers of cardiovascular health. Since there are limited population-based studies that investigate factors affecting resting heart rate variations, the question arises: “which biochemical factors determine the level and variation of heart rate at the community level?”
Anthropometric factors are known as a reliable way to the measurement of the size and proportion of the human body. Body Mass Index (BMI), waist circumference (WC), waist to hip ratio (WHR), waist to height ratio (WHtR) forming classic obesity indices and A body shape index (ABSI), abdominal volume index (AVI), body adiposity index (BAI) and conicity index, formed modern obesity indices. Evidences are suggesting that abdominal obesity is related to high sympathetic nerve activity which probably mediated by elevated leptin and insulin levels [13, 14]. Also, it seems that in people with larger body mass, the blood circulation takes longer, so affects the heart rate to prevent diastolic pressure drop [15]. Recent evidence from the data of 4360 participants in French RECORD Study, showed that RHR was strongly related to BMI and body fat distribution but without a definite pattern [6]. Waist circumference has previously been shown to be associated with RHR but the exact mechanism is indistinct [16].
Unfortunately, previous studies have analyzed the association between classic anthropometric factors and RHR in adolescents, and lots of other aspects and a specific pattern are still less clear [6, 12]. Therefore, the aim of this extensive, standardized, retrospective cohort study is to review the determinants of resting heart rate in a large random sample of the Iranian population.

Method

Study population

The data used in this paper were driven from the baseline survey of the PERSIAN (Prospective Epidemiological Research Study in IrAN) cohort Study (Fasa non-communicable disease cohort study) [17]. It was conducted from Nov. 2014 to June 2019 and was the first large epidemiological study, surveying a random sample from the general population in southern Iran. The purpose, design, and method of the study have been published in detail elsewhere [17, 18]. A total number of 9975 persons from 35 to 90 years old were included. The mean and median age of the participants were 49.63 ± 9.17 and 48 years, respectively. In men, the mean age was 49.58 ± 9.49 and the median age was 47 years. The youngest man was 35 years old and the oldest was 85 years old. In women, the mean age was 49.64 ± 9.58 and the median age was 48 years. The youngest woman was 35 years old and the oldest was 90 years old. The study was approved by the research ethics committee of Fasa University of medical sciences (No. IR.FUMS.REC.1396.228) and after obtaining informed consent, all the eligible subjects were enrolled.

Measures

Resting heart rate

According to the recommendations of the International Standards for Anthropometric Assessment (ISAK), trained nurses measured RHR by electrocardiogram (Cardionics CardioPlug device) to minimize coefficients of variation [19]. The measurement was made in a quiet room after a 5 min rest period in the supine position from 9 to 11 a.m. Each measurement was made three times and the average value was calculated.

Anthropometric factors

Bodyweight was measured to the nearest 0.1 kg using an electronic scale (Seca 769 scale, Seca GMBH, Hamburg). Height was measured to the nearest 0.5 cm using a stadiometer (Seca 769 scale, Seca GMBH, Hamburg). BMI (Kg/m2) was calculated as weight (Kg) divided by squared height (m2) (thin: BMI < 18, average: 18 ≤ BMI < 25, overweight: 25 ≤ BMI < 30, obese: BMI ≥ 30). Waist and hip circumferences were measured using flexible plastic tape. Waist circumference (WC) was measured at the midpoint between the inferior border of the lowest ribs and the superior iliac crest. The measurement was done at the end of a normal expiration while the individual stood upright, with feet next together and arms hanging freely at the sides. Hip circumference was measured over no restrictive underwear at the level of the maximum extension of the buttocks in a horizontal plane, without compressing the skin. (HP < 94, 94 ≤ HP ≤ 102 and HP > 102 among men and HP < 80, 80 ≤ HP ≤ 88 and HP > 88 among women).
All anthropometric calculations were done according to the following equations:
$$A\ body\ shape\ index\ (ABSI)=\frac{WC}{BMI^{\raisebox{1ex}{$2$}\!\left/ \!\raisebox{-1ex}{$3$}\right.}\times {Height}^{\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$2$}\right.}}$$
$$Abdominal\ volume\ index\ (AVI)=\left[2{(WC)}^2+0.7{\left( waist- hip\right)}^2\right]/1000$$
$$Body\ adiposity\ index\ (BAI)=\frac{Hip}{Height^{1.5}}-18$$
$$conicity=\frac{WC(m)}{0.109\sqrt{\frac{Weight(Kg)}{Height(m)}}}$$
The percentage of body fat was obtained by the Tetrapolar Bioelectrical Impedance Analysis (BIA) system (BF-350, Tanita Corp, Tokyo, Japan). Subjects stood on the metal contacts with bare feet and their body fat mass was determined. This measurement was repeated twice, and the average value was calculated and set.

Drugs

The drugs that have been considered for use and whose role in the relationship has been modified are as follows: Tricyclic antidepressant (Imipramine, Amitriptyline, Doxepin, Nortriptyline); Beta-blockers (Propranolol, Atenolol, Carvedilol, Metoprolol); Alfa blockers (Prazosin, Terazosin); Selective serotonin reuptake inhibitor (Fleuxetin, Sertraline, Citalopram, Escitalopram, Paroxetine); Antihistamines (Hydroxyzine, Ketotifen, Loratadine, Desloratadine, Ciproheptadin, Fexofenadine); Calcium channel blockers (Amlodipine, Nefidipine, Diltiazem, Verapamil); Diuretics (Furosemide, Spfinolactone, Triamtren H, Hydrochlorothiazide, Triamterene); Beta 2 agonist (Clonidine).

Statistical methods

To consider the large number of variables in the current study, we implement smoothly clipped absolute deviation (SCAD) linear regression which is one the best in terms of variable selection in regression modeling. SCAD estimates the coefficient of unimportant variables as zero and removes them from the model, therefore it does simultaneous estimation and variable selection. Also, to assess the association between variables across the distribution of resting heart rate, we used SCAD quantile regression instead of traditional quantile regression for the same reason. In this study, RHR as a dependent variable and SBP, HDL. C, WBC, GLUC, Beta1-blockers, TG, SGPT, DBP, Age, SGOT, BUN, WC, Opium, TCA; Alpha-Blockers, HGB, Levothyroxine, Metformin, SSRI, Diuretics, LDL, Beta2-agonist, Antihistamine, ABSI, and sex entered the model as predictive variables. All the factors were compared between males and females via independent T-test in SPSS 22.0 software and figures were drawn in Prism 5.0 software. Moreover, ncvreg and rqpen packages in R 3.3.2 software were used for regression modeling.

Results

Our sample comprised of 9975 persons including 5468 (54.8%) females and 4507 (45.2%) males. The median resting heart rate was 74 (interquartile range:66–80) and 10th and 90th were 61 and 88 respectively. Although there was no significant difference between mean age of females (49.6) and males (49.5), resting heart rate was significantly higher in females (76.6 versus 71.4, P < 0.001). Comparing anthropometric factors between males and females showed that all the factors except wrist circumference were higher in females (P < 0.05). Furthermore, Table 1 shows a comparison between males and females in terms of some biological and anthropometric factors.
Table 1
Anthropometric and biological factors in males and females in Fasa PERSIAN (Prospective Epidemiological Research Study in IrAN) cohort study
Variable
Male (n = 4507)
Female (n = 5468)
P-value
Mean
SD
Mean
SD
Heart Rate (bpm)
71.40
10.13
76.59
10.46
< 0.001
Age (years)
49.52
9.69
49.57
9.59
0.79
Waist circumference (cm)
89.52
11.18
96.14
11.49
< 0.001
Hip circumference (cm)
97.54
7.67
101.25
9.41
< 0.001
Wrist circumference (cm)
17.28
1.23
16.27
1.25
< 0.001
DBP (mm Hg)
74.88
11.39
75.36
11.79
0.04
SBP (mm Hg)
111.39
17.20
112.76
18.87
< 0.001
BMI
24.20
4.41
26.86
4.81
< 0.001
ABSI
0.08
0.00
0.09
0.01
< 0.001
BAI
26.47
3.70
34.15
5.11
< 0.001
AVI
16.35
4.12
18.79
4.47
< 0.001
Conicity index
1.29
0.08
1.37
0.08
< 0.001
WHR
0.92
0.06
0.95
0.06
< 0.001
WHtR
0.53
0.07
0.62
0.07
< 0.001
WBC (10^3/μL)
6.58
1.78
6.38
1.67
< 0.001
RBC (10^6/μL)
5.19
0.56
4.78
0.50
< 0.001
HGB (g/dL)
15.66
1.58
13.88
1.47
< 0.001
HCT (%)
44.39
3.82
39.99
3.74
< 0.001
MCV (fL)
86.17
7.49
84.18
7.61
< 0.001
MCH (pg)
30.44
3.14
29.28
3.16
< 0.001
MCHC (10^3/μL)
35.31
1.19
34.74
1.21
< 0.001
PLT (%)
247.71
60.71
296.38
72.93
< 0.001
Glucose (mg/dL)
90.19
24.25
94.56
32.98
< 0.001
BUN (mg/dL)
13.74
3.94
12.29
3.85
< 0.001
Cr (mg/dL)
1.06
0.18
0.92
0.18
< 0.001
TG (mg/dL)
135.98
90.80
128.50
74.82
< 0.001
Cholesterol (mg/dL)
178.82
37.90
190.39
39.44
< 0.001
SGOT (U/L)
23.84
8.41
21.56
8.91
< 0.001
SGPT (U/L)
26.09
16.52
21.29
12.02
< 0.001
ALP (U/L)
211.06
65.62
208.30
75.65
0.052
HDL (mg/dL)
47.26
14.42
54.20
16.42
< 0.001
LDL (mg/dL)
104.44
31.44
110.57
33.43
< 0.001
GGT (U/L)
25.82
22.56
20.42
20.07
< 0.001
DBP Diastolic blood pressure, SBP Systolic blood pressure, BMI Body mass index, ABSI A body shape index, BAI Abdominal volume index, AVI Body adiposity index, WHR Waist to hip ratio, WHtR Waist to height ratio, WBC White blood cell, RBC Red blood cell, HGB Hemoglobin, HCT Hematocrit, MCV Mean cell volume, MCH Mean corpuscular hemoglobin, MCHC Mean corpuscular hemoglobin concentration, PLT Platelet, BUN Blood urea Nitrogen, Cr Creatinine, TG Triglyceride, SGOT Serum glutamic oxaloacetic transaminase, SGPT Serum glutamic pyruvic transaminase, ALP Alkaline phosphatase, HDL High-density lipoprotein, LDL Low-density lipoprotein, GGT Gamma glutamine transferase
The frequency of use of different drug groups in the study population is shown in Fig. 1.
Age has an adverse effect on resting heart rate and the female gender was directly associated with a faster resting heart rate. Also, there was a direct association between resting heart rate and SBP and blood glucose. Also, the positive association between diastolic blood pressure and resting heart rate was observed only for below 80th quantile (Fig. 2). Figure 2 shows the relationship of different quantiles of resting heart rate with the proven important variables, and aims to find the strength of this relationship in different quantiles to show whether the relationship of this variable to resting heart rate is generally established, or only in certain amounts of heart rate.
In order to investigate the simultaneous effect of different factors on resting heart rate, we proposed two models based on SCAD linear regression. In model 1, HR considered as a dependent variable, and all of the other 41 factors (aforementioned in Table 1 and drugs) were considered as independent variables. The proposed model represents 25 variables as effective factors on resting heart rate and remove the other variables from the model by estimating their coefficients equal to zero. These variables were ordered in Table 2 based on their importance.
Table 2
Results of SCAD linear regression to modeling resting heart rate in Fasa PERSIAN (Prospective Epidemiological Research Study in IrAN) cohort
Variable
Model 1a
Variable
Model 2b
β
Standard β
SE
p- Value
β
Standard β
SE
p- Value
Sex (male is ref)
4.88
0.21
0.33
<0.001
Sex (male is ref)
4.62
0.22
0.211
<0.001
SBP
0.08
0.13
.006
<0.001
SBP
0.11
0.19
0.006
0.032
HDL.C
0.06
0.10
0.026
0.137
Beta1.blockers
−2.35
−0.07
0.021
0.006
WBC
0.34
0.17
.32
.288
Age
−0.05
− 0.05
− 0.03
0.012
GLUC
0.04
0.11
0.004
<0.001
BMI
0.08
0.04
0.07
0.003
Beta1.blockers
1.12
−0.06
0.002
<0.001
Opium
−1.89
−0.04
0.28
<0.001
TG
0.01
0.06
0.001
<0.001
Levothyroxine
−1.41
−0.02
0.42
<0.001
SGPT
0.006
0.009
0.007
0.39
Alpha. blockers
5.2
0.02
1.27
<0.001
DBP
0.171
0.193
0.009
.009
TCA
2.13
0.02
1.02
<0.001
Age
−.018
−.016
.011
.111
Metformin
1.20
0.02
0.13
0.001
SGOT
−.027
− 024
.12
.028
WC
0.39
0.003
0.043
0.008
BUN
−0.21
−0.08
.027
<0.001
SSRI
−1.00
− 0.01
− 0.91
<0.001
WC
0.12
0.05f
0.008
<0.001
WHR
2.29
0.01
0.031
<0.001
Opium
−1.69
−0.13
0.004
<0.001
Antihistamine
1.55
0.01
0.178
0.003
TCA
1.94
0.02
1.12
<0.001
Beta2.agonist
2.2
0.01
0.98
.002
Alpha. blockers
4.87
0.02
1.32
<0.001
Diuretics
0.64
0.01
0.24
0.001
HGB
0.09
0.01
0.02
<0.001
     
Levothyroxine
−0.93
−0.81
− 0.71
0.471
     
Metformin
−11.78
−10.36
−3.41
0.291
     
SSRI
−1.15
−0.01
−.98
0.003
     
Diuretics
0.87
0.005
0.73
0.004
     
LDL
−0.01
−0.003
−0.02
0.006
     
Beta2.agonist
0.88
0.002
0.56
0.042
     
Antihistamine
1.46
3.11
0.74
0.639
     
ABSI
−28.04
−0.001
−19.1
0.132
     
DBP Diastolic blood pressure, SBP Systolic blood pressure, BMI Body mass index, ABSI A body shape index, WHR Waist to hip ratio, WBC White blood cell, RBC Red blood cell, HGB Hemoglobin, HCT Hematocrit, MCV Mean cell volume, MCH Mean corpuscular hemoglobin, MCHC Mean corpuscular hemoglobin concentration, PLT Platelet, BUN Blood urea Nitrogen, Cr Creatinine, TG Triglyceride, SGOT Serum glutamic oxaloacetic transaminase, SGPT Serum glutamic pyruvic transaminase, ALP Alkaline phosphatase, HDL High-density lipoprotein, LDL Low-density lipoprotein, GGT Gamma glutamine transferase
a Model 1, HR considered as dependent variable, and all of the other 41 factors (aforementioned in Table 1 and drugs) were considered as independent variables. The proposed model represents 25 variables as effective factors on resting heart rate
b Only comprised age, sex, BMI, waist circumference, WHR, SBP, and drugs because the excluded variables show a bidirectional confounding relationship with RHR
The second model (model 2) only comprised age, sex, BMI, waist circumference, WHR, SBP, and drugs because the excluded variables show a bidirectional confounding relationship with RHR (this is probably due to the same correlations that exist with other independent variables). As shown in Table 2, the female gender is the most effective factor on resting heart rate, with the mean RHR for females is 4.62 bpm higher compared to males. Meanwhile, increasing each 20 years of age leads to one decrease in resting heart rate. Considering Pharmaceutical categories, Alpha-blockers (coefficient = 5.2) and Beta1-blockers (coefficient = − 2.2) were the most effective drugs.

Discussion

The mean resting heart rate in our population was 74 bpm that is more in comparison with noted reports. In light of the evidence, previous studies report resting heart rate must be ranges 60 to 65 in a healthy population [20, 21]. This superiority leads to an increasing prevalence of the cardiovascular disease in our society [22, 23]. Also, this discrepancy may be due to some underlying diseases in the selected population.
A significant negative correlation of aging with heart rate have been described by Ogliari et al. in 2015 [24]. In this context, several studies have suggested that age could be related to RHR [9, 25, 26]. We demonstrated that there is a strong negative association between aging and RHR which is independent of other cardiovascular risk factors in both sex. Of course, the difference between men and women in the number of resting heart rate and its high rate in women is something that has been mentioned in previous studies [27, 28]. However, this increased heart rate at rest in women does not mean a higher risk of heart disease because the results of previous studies show that the power of the relationship between resting heart rate and all-cause mortality in women is weaker than men [29].
As previous studies had shown, both systolic and diastolic blood pressures were significantly related to resting heart rate in a positive way. There are some investigations that demonstrated that the relationship between RHR and SBP is stronger than DBP, such as some studies in Finland, Norway, Belgium, and the USA [12, 30]. We demonstrated that this relationship is stronger in men than women like the results of Green et al. and Cirillo et al. [31, 32]. Based on our knowledge, the interaction between aging and RHR on blood pressure still remains unexplained. The present study strongly indicated that gender had a significant effect on the relationship between aging and increased RHR. Figure 2 shows a significant positive rate-response relationship among SBP and RHR and inverse rate-response relationship with DBP above 80th quantile both in men and women for the first time. To shed new light on the mechanism of this relationship, previous data suggested that an increase in catecholamine concentration and sympathetic nervous system over-activity could be major mechanisms of this correlation [33, 34].
The Results of the present study confirm and extend the finding of the Korea National Health and Nutrition Examination Survey (KNHANES) and the Third National Health and Nutrition Survey (NHANES III) [16, 35]. We observed a significant association between waist circumference and RHR. Previous 20 years of longitudinal studies and HARVEST study demonstrated that RHR is an important predictor of overweight and obesity, and each 10 bpm increase in RHR, increases the risk of obesity by 30% [25, 36]. Our findings confirmed that central obesity constantly linked with higher RHR, which may be due to autonomic imbalance and adrenergic hyperactivity [33].
Also, the findings of this study, similar to Piwońska et al. and Cooney et al. studies, demonstrated that there is a positive association between BMI and RHR in the general population [8, 30]. Furthermore, numerous studies have reported BMI and its positive relationship with all causes of mortality and coronary artery disease, especially in patients with higher RHR [3739].
A study in Japan on 3872 individuals demonstrated that resting heart rate is a predictor of the metabolic syndrome in the middle aged Japanese population [40]. We have provided further evidence that this relation is in both sexes. The suggested mechanism explains the pathway that starts by alteration in fat accumulation neuronal signals from the liver and visceral fat to the brain, this leads to modulate autonomic tone [41, 42]. Based on our observations, we conclude that: The effect of resting heart rate as a potential predictor of metabolic syndrome is biologically plausible.
Previous findings seem to demonstrated that there is a significant relationship between HR and hsCRP as an indicator of inflammation [43]. One of the explanations is a genetic predisposition that leads to the sympathetic nervous system (SNS) dysfunction which damages the blood vessel wall. This pathway starts neurohormonal inflammatory cascade and releases some cytokines such as TNF-α and IL-6, predominantly [44]. This pathway induced a chronic systemic inflammatory and oxidative stress state which lead to arterial stiffness and generation of the atherosclerotic plaque [45, 46].
Compared to women, men had a higher level of triglyceride but this superiority has no clinical importance. On the other hand, Cholesterol, HDL, and LDL are significantly higher in women. Findings reveal that there is a weak relationship between triglyceride and RHR in both sexes. Our findings are in agreement with the results of SUN Ji Chao in china [47]. Few studies also have reported that significantly higher cholesterol and LDL levels correlate with higher levels of RHR in both genders. In contrast to these studies, our results seem to show no significant relationship between cholesterol and RHR [48]. Suggested theories propose that a higher concentration of TG is due to catecholamine action and leads to lipid metabolism alteration. This pathway catalyzes HDL synthesis and decreases the concentration of the LDL by α1 stimulation [48].
To the best of our knowledge, no previous study reported the relationship between RHR and Hb. In particular, we found a positive weak association between Hb and RHR. This relation has no definite and certain reason or explanation. It is possible that people with lower Hb, have a higher heart rate due to inadequate oxygen supply respectively. Then, our findings seem to show anemia may be considered as a minor cardiometabolic risk factor.
Our findings showed that there is a clear relationship between higher RHR and more blood glucose levels. Our result is in agreement with previous data which have been showing that increased risk of type 2 diabetes associated with increased heart rate [10, 11, 35, 37]. Similarly, Andrew Grandinetti et al. demonstrated that in the general population, a significant increase in insulin resistance titers observed in men and women with higher HR [39]. The same results were driven from analysis of the Chicago Heart Association Detection Project in Industry Study and Atherosclerosis Risk in the Communities (ARIC) [1, 38, 49]. Some other theories have been suggested about this matter, one is genetic factors that determine cardiovascular fitness and also energy expenditure [5052]. Another theory explains that increased activity of sympathetic nervous system tone can lead to an increase in HR and alter the regulation of the parasympathetic on the heart. Also, SNS overactivity stimulates hyperinsulinemia in the accompaniment of insulin resistance [53, 54]. Moreover, data reveals that patients with diabetes have increased sympathetic and decreased parasympathetic activity respectively [55]. Several studies have shown that a decrease in HR, even to a small extent, can consequently have significant public health benefits [56].

Strengths and limitations

One of the most important strengths of this study is the large multiple biological and chemical variables that have been evaluated concerning RHR, which able us to take into account the potential confounding effect of many variables. To the best of our knowledge, this is the first study that assesses the relationship between a large panel of cardiovascular risk factors and biochemical data, and RHR.
Other strengths of this study are its type and large sample size. This is a cohort study with about 10,000 participants that leads to more generalizability of the results. Also, the two-modeling analysis confirms the consistency and importance of findings.
Some limitations of the present study are 1. The cross-sectional nature of the study did not allow us to draw causal conclusions due to the lack of follow-up data. 2. We used the average of only two readings of resting heart rate, taken only a few minutes apart, to represent the resting heart rate for each participant. 3. the interfering effect of white coat syndrome and in-office stress that might influence on blood pressure and heart rate, 4. lack of measurement of heart rate variability to improve the consistency of the findings and 5. the past medical and medication history of the participants did not be considered into the analysis.

Conclusion

This study revealed that female gender, lower hemoglobin, obesity, and more BMI, more blood glucose levels, more LDL, and more systolic blood pressure are associated with more RHR. However, the investigation into this area is in progress and seems more prospective researches, especially with long periods of follow-ups and multinational sources, are needed.

Acknowledgments

This study is based on a project to achieve an M.D. degree. We thank Fasa university of medical sciences for supporting this research and Dr. Ehsan Bahramali, our cardiologist member of the cohort study, for his constructive feedback throughout the study and his comments on the interpretation of results of the study.
The authors appreciate All people that patiently contributed to this study and Fasa university of medical sciences for financial supports of this work.
The study protocol was in accordance with the Helsinki Declaration and confirmed by the Ethics Committee of Fasa University of Medical Sciences (Approval Code: IR.FUMS.REC. 1396.228). The participants were informed about the research objectives and the written informed consent was obtained from the subjects before starting the survey.
Not applicable.

Competing interests

The authors hereby affirm that the manuscript is original, that all statements asserted as facts are based on authors careful investigation and accuracy, that the manuscript has not been published in total or in part previously and has not been submitted or considered for publication in total or in part elsewhere. Each author acknowledges he/she has participated in the work in a substantive way and is prepared to take public responsibility for the work and authors have no competing interest to results of article.
Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creativecommons.​org/​licenses/​by/​4.​0/​. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Literatur
1.
Zurück zum Zitat Vazir A, Claggett B, Cheng S, et al. Association of resting heart rate and temporal changes in heart rate with outcomes in participants of the atherosclerosis risk in communities study. JAMA Cardiol. 2018;3(3):200–6. Vazir A, Claggett B, Cheng S, et al. Association of resting heart rate and temporal changes in heart rate with outcomes in participants of the atherosclerosis risk in communities study. JAMA Cardiol. 2018;3(3):200–6.
2.
Zurück zum Zitat Aladin AI, Al Rifai M, Rasool SH, et al. The association of resting heart rate and incident hypertension: the Henry Ford Hospital Exercise Testing (FIT) Project. Am J Hypertens. 2016;29(2):251–7. Aladin AI, Al Rifai M, Rasool SH, et al. The association of resting heart rate and incident hypertension: the Henry Ford Hospital Exercise Testing (FIT) Project. Am J Hypertens. 2016;29(2):251–7.
3.
Zurück zum Zitat Sharashova E, Wilsgaard T, Brenn T. Resting heart rate on the decline: the Tromsø study 1986–2007. Int J Epidemiol. 2015;44(3):1007–17.PubMed Sharashova E, Wilsgaard T, Brenn T. Resting heart rate on the decline: the Tromsø study 1986–2007. Int J Epidemiol. 2015;44(3):1007–17.PubMed
4.
Zurück zum Zitat Zhang M, Han C, Wang C, et al. Association of resting heart rate and cardiovascular disease mortality in hypertensive and normotensive rural Chinese. J Cardiol. 2017;69(5):779–84.PubMed Zhang M, Han C, Wang C, et al. Association of resting heart rate and cardiovascular disease mortality in hypertensive and normotensive rural Chinese. J Cardiol. 2017;69(5):779–84.PubMed
5.
Zurück zum Zitat Alhalabi L, Singleton MJ, Oseni AO, et al. Relation of higher resting heart rate to risk of cardiovascular versus non-cardiovascular death. Am J Cardiol. 2017;119(7):1003–7. Alhalabi L, Singleton MJ, Oseni AO, et al. Relation of higher resting heart rate to risk of cardiovascular versus non-cardiovascular death. Am J Cardiol. 2017;119(7):1003–7.
6.
Zurück zum Zitat Chaix B, Jouven X, Thomas F, et al. Why socially deprived populations have a faster resting heart rate: impact of behaviour, life course anthropometry, and biology–the RECORD cohort study. Soc Sci Med. 2011;73(10):1543–50.PubMed Chaix B, Jouven X, Thomas F, et al. Why socially deprived populations have a faster resting heart rate: impact of behaviour, life course anthropometry, and biology–the RECORD cohort study. Soc Sci Med. 2011;73(10):1543–50.PubMed
7.
Zurück zum Zitat Ji C, Zheng X, Chen S, et al. Impact of resting heart rate on the progression to hypertension in prehypertension patients. Zhonghua Xin Xue Guan Bing Za Zhi. 2014;42(10):860–5.PubMed Ji C, Zheng X, Chen S, et al. Impact of resting heart rate on the progression to hypertension in prehypertension patients. Zhonghua Xin Xue Guan Bing Za Zhi. 2014;42(10):860–5.PubMed
8.
Zurück zum Zitat Cooney MT, Vartiainen E, Laakitainen T, et al. Elevated resting heart rate is an independent risk factor for cardiovascular disease in healthy men and women. Am Heart J. 2010;159(4):612–619.e613.PubMed Cooney MT, Vartiainen E, Laakitainen T, et al. Elevated resting heart rate is an independent risk factor for cardiovascular disease in healthy men and women. Am Heart J. 2010;159(4):612–619.e613.PubMed
9.
Zurück zum Zitat Kunutsor S, Powles J. Cardiovascular risk in a rural adult west African population: is resting heart rate also relevant? Eur J Prev Cardiol. 2014;21(5):584–91.PubMed Kunutsor S, Powles J. Cardiovascular risk in a rural adult west African population: is resting heart rate also relevant? Eur J Prev Cardiol. 2014;21(5):584–91.PubMed
10.
Zurück zum Zitat Kim D-I, Yang HI, Park J-H, et al. The association between resting heart rate and type 2 diabetes and hypertension in Korean adults. Heart. 2016:heartjnl-2016;102(21):1757–62. Kim D-I, Yang HI, Park J-H, et al. The association between resting heart rate and type 2 diabetes and hypertension in Korean adults. Heart. 2016:heartjnl-2016;102(21):1757–62.
11.
Zurück zum Zitat Wu S, Liu X, Zhu C, et al. Impact of resting heart rate on new-onset diabetes in population without hypertension. Zhonghua Xin Xue Guan Bing Za Zhi. 2013;41(11):968–73.PubMed Wu S, Liu X, Zhu C, et al. Impact of resting heart rate on new-onset diabetes in population without hypertension. Zhonghua Xin Xue Guan Bing Za Zhi. 2013;41(11):968–73.PubMed
12.
Zurück zum Zitat Zhang J, Kesteloot H. Anthropometric, lifestyle and metabolic determinants of resting heart rate. A population study. Eur Heart J. 1999;20(2):103–10.PubMed Zhang J, Kesteloot H. Anthropometric, lifestyle and metabolic determinants of resting heart rate. A population study. Eur Heart J. 1999;20(2):103–10.PubMed
13.
Zurück zum Zitat Bemelmans RH, Graaf Y, Nathoe HM, et al. Increased visceral adipose tissue is associated with increased resting heart rate in patients with manifest vascular disease. Obesity. 2012;20(4):834–41.PubMed Bemelmans RH, Graaf Y, Nathoe HM, et al. Increased visceral adipose tissue is associated with increased resting heart rate in patients with manifest vascular disease. Obesity. 2012;20(4):834–41.PubMed
14.
Zurück zum Zitat Thorp AA, Schlaich MP. Relevance of sympathetic nervous system activation in obesity and metabolic syndrome. J Diabetes Res. 2015:1–11. Article ID 341583. Thorp AA, Schlaich MP. Relevance of sympathetic nervous system activation in obesity and metabolic syndrome. J Diabetes Res. 2015:1–11. Article ID 341583.
15.
Zurück zum Zitat Smulyan H, Marchais SJ, Pannier B, et al. Influence of body height on pulsatile arterial hemodynamic data. J Am Coll Cardiol. 1998;31(5):1103–9.PubMed Smulyan H, Marchais SJ, Pannier B, et al. Influence of body height on pulsatile arterial hemodynamic data. J Am Coll Cardiol. 1998;31(5):1103–9.PubMed
16.
Zurück zum Zitat Frisancho AR. Relative leg length as a biological marker to trace the developmental history of individuals and populations: growth delay and increased body fat. Am J Hum Biol. 2007;19(5):703–10.PubMed Frisancho AR. Relative leg length as a biological marker to trace the developmental history of individuals and populations: growth delay and increased body fat. Am J Hum Biol. 2007;19(5):703–10.PubMed
17.
Zurück zum Zitat Farjam M, Bahrami H, Bahramali E, et al. A cohort study protocol to analyze the predisposing factors to common chronic non-communicable diseases in rural areas: Fasa cohort study. BMC Public Health. 2016;16(1):1090.PubMedPubMedCentral Farjam M, Bahrami H, Bahramali E, et al. A cohort study protocol to analyze the predisposing factors to common chronic non-communicable diseases in rural areas: Fasa cohort study. BMC Public Health. 2016;16(1):1090.PubMedPubMedCentral
18.
Zurück zum Zitat Poustchi H, Eghtesad S, Kamangar F, et al. Prospective epidemiological research studies in Iran (the PERSIAN cohort study): rationale, objectives, and design. Am J Epidemiol. 2017;187(4):647–55.PubMedCentral Poustchi H, Eghtesad S, Kamangar F, et al. Prospective epidemiological research studies in Iran (the PERSIAN cohort study): rationale, objectives, and design. Am J Epidemiol. 2017;187(4):647–55.PubMedCentral
19.
Zurück zum Zitat Ellis KJ, Bell SJ, Chertow GM, et al. Bioelectrical impedance methods in clinical research: a follow-up to the NIH technology assessment conference. Nutrition. 1999;15(11):874–80.PubMed Ellis KJ, Bell SJ, Chertow GM, et al. Bioelectrical impedance methods in clinical research: a follow-up to the NIH technology assessment conference. Nutrition. 1999;15(11):874–80.PubMed
20.
Zurück zum Zitat Mitchell GF, Parise H, Benjamin EJ, et al. Changes in arterial stiffness and wave reflection with advancing age in healthy men and women: the Framingham heart study. Hypertension. 2004;43(6):1239–45.PubMed Mitchell GF, Parise H, Benjamin EJ, et al. Changes in arterial stiffness and wave reflection with advancing age in healthy men and women: the Framingham heart study. Hypertension. 2004;43(6):1239–45.PubMed
21.
Zurück zum Zitat Zoungas S, Ristevski S, Lightfoot P, et al. Carotid artery intima–medial thickness is increased in chronic renal failure. Clin Exp Pharmacol Physiol. 2000;27(8):639–41.PubMed Zoungas S, Ristevski S, Lightfoot P, et al. Carotid artery intima–medial thickness is increased in chronic renal failure. Clin Exp Pharmacol Physiol. 2000;27(8):639–41.PubMed
22.
Zurück zum Zitat Diaz A, Bourassa MG, Guertin M-C, et al. Long-term prognostic value of resting heart rate in patients with suspected or proven coronary artery disease. Eur Heart J. 2005;26(10):967–74.PubMed Diaz A, Bourassa MG, Guertin M-C, et al. Long-term prognostic value of resting heart rate in patients with suspected or proven coronary artery disease. Eur Heart J. 2005;26(10):967–74.PubMed
23.
Zurück zum Zitat Jouven X, Empana J-P, Schwartz PJ, et al. Heart-rate profile during exercise as a predictor of sudden death. N Engl J Med. 2005;352(19):1951–8.PubMed Jouven X, Empana J-P, Schwartz PJ, et al. Heart-rate profile during exercise as a predictor of sudden death. N Engl J Med. 2005;352(19):1951–8.PubMed
24.
Zurück zum Zitat Ogliari G, Mahinrad S, Stott DJ, et al. Resting heart rate, heart rate variability and functional decline in old age. Can Med Assoc J. 2015;187(15):E442–9. Ogliari G, Mahinrad S, Stott DJ, et al. Resting heart rate, heart rate variability and functional decline in old age. Can Med Assoc J. 2015;187(15):E442–9.
25.
Zurück zum Zitat Shigetoh Y, Adachi H, Yamagishi S-I, et al. Higher heart rate may predispose to obesity and diabetes mellitus: 20-year prospective study in a general population. Am J Hypertens. 2008;22(2):151–5.PubMed Shigetoh Y, Adachi H, Yamagishi S-I, et al. Higher heart rate may predispose to obesity and diabetes mellitus: 20-year prospective study in a general population. Am J Hypertens. 2008;22(2):151–5.PubMed
26.
Zurück zum Zitat Adachi H, Enomoto M, Fukami A, et al. Plasma renin activity and resting heart rate in a population of community-dwelling Japanese: the Tanushimaru study. Am J Hypertens. 2014;28(7):894–9.PubMed Adachi H, Enomoto M, Fukami A, et al. Plasma renin activity and resting heart rate in a population of community-dwelling Japanese: the Tanushimaru study. Am J Hypertens. 2014;28(7):894–9.PubMed
27.
Zurück zum Zitat Morcet J-F, Safar M, Thomas F, et al. Associations between heart rate and other risk factors in a large French population. J Hypertens. 1999;17(12):1671–6.PubMed Morcet J-F, Safar M, Thomas F, et al. Associations between heart rate and other risk factors in a large French population. J Hypertens. 1999;17(12):1671–6.PubMed
28.
Zurück zum Zitat Torsvik M, Häggblom A, Eide GE, et al. Cardiovascular autonomic function tests in an African population. BMC Endocr Disord. 2008;8(1):19.PubMedPubMedCentral Torsvik M, Häggblom A, Eide GE, et al. Cardiovascular autonomic function tests in an African population. BMC Endocr Disord. 2008;8(1):19.PubMedPubMedCentral
29.
Zurück zum Zitat Palatini P, Benetos A, Julius S. Impact of increased heart rate on clinical outcomes in hypertension. Drugs. 2006;66(2):133–44.PubMed Palatini P, Benetos A, Julius S. Impact of increased heart rate on clinical outcomes in hypertension. Drugs. 2006;66(2):133–44.PubMed
30.
Zurück zum Zitat Piwońska A, Piotrowski W, Broda G, et al. The relationship between resting heart rate and atherosclerosis risk factors. Kardiol Pol. 2008;66(10):1069–75.PubMed Piwońska A, Piotrowski W, Broda G, et al. The relationship between resting heart rate and atherosclerosis risk factors. Kardiol Pol. 2008;66(10):1069–75.PubMed
31.
Zurück zum Zitat Cirillo M, Laurenzi M, Trevisan M, et al. Hematocrit, blood pressure, and hypertension. The Gubbio population study. Hypertension. 1992;20(3):319–26.PubMed Cirillo M, Laurenzi M, Trevisan M, et al. Hematocrit, blood pressure, and hypertension. The Gubbio population study. Hypertension. 1992;20(3):319–26.PubMed
32.
Zurück zum Zitat Green MS, Jucha E, Luz Y. Inconsistencies in the correlates of blood pressure and heart rate. J Chronic Dis. 1986;39(4):261–70.PubMed Green MS, Jucha E, Luz Y. Inconsistencies in the correlates of blood pressure and heart rate. J Chronic Dis. 1986;39(4):261–70.PubMed
33.
Zurück zum Zitat Palatini P. Heart rate and the cardiometabolic risk. Curr Hypertens Rep. 2013;15(3):253–9.PubMed Palatini P. Heart rate and the cardiometabolic risk. Curr Hypertens Rep. 2013;15(3):253–9.PubMed
34.
Zurück zum Zitat Piwońska A, Piotrowski W, Broda G, et al. Original article the relationship between resting heart rate and atherosclerosis risk factors. Kardiologia Polska (Polish Heart J). 2008;66(10):1069–75. Piwońska A, Piotrowski W, Broda G, et al. Original article the relationship between resting heart rate and atherosclerosis risk factors. Kardiologia Polska (Polish Heart J). 2008;66(10):1069–75.
35.
Zurück zum Zitat Hong JW, Noh JH, Kim D-J. The association of resting heart rate with the presence of diabetes in Korean adults: the 2010-2013 Korea National Health and nutrition examination survey. PLoS One. 2016;11(12):e0168527.PubMedPubMedCentral Hong JW, Noh JH, Kim D-J. The association of resting heart rate with the presence of diabetes in Korean adults: the 2010-2013 Korea National Health and nutrition examination survey. PLoS One. 2016;11(12):e0168527.PubMedPubMedCentral
36.
Zurück zum Zitat Palatini P, Mos L, Santonastaso M, et al. Resting heart rate as a predictor of body weight gain in the early stage of hypertension. Obesity. 2011;19(3):618–23.PubMed Palatini P, Mos L, Santonastaso M, et al. Resting heart rate as a predictor of body weight gain in the early stage of hypertension. Obesity. 2011;19(3):618–23.PubMed
37.
Zurück zum Zitat Wulsin LR, Horn PS, Perry JL, et al. Autonomic imbalance as a predictor of metabolic risks, cardiovascular disease, diabetes, and mortality. J Clin Endocrinol Metab. 2015;100(6):2443–8.PubMed Wulsin LR, Horn PS, Perry JL, et al. Autonomic imbalance as a predictor of metabolic risks, cardiovascular disease, diabetes, and mortality. J Clin Endocrinol Metab. 2015;100(6):2443–8.PubMed
38.
Zurück zum Zitat Carnethon MR, Yan L, Greenland P, et al. Resting heart rate in middle age and diabetes development in older age. Diabetes Care. 2008;31(2):335–9.PubMed Carnethon MR, Yan L, Greenland P, et al. Resting heart rate in middle age and diabetes development in older age. Diabetes Care. 2008;31(2):335–9.PubMed
39.
Zurück zum Zitat Grandinetti A, Liu DM, Kaholokula JK. Relationship of resting heart rate and physical activity with insulin sensitivity in a population-based survey. J Diabetes Metab Disord. 2015;14(1):41.PubMedPubMedCentral Grandinetti A, Liu DM, Kaholokula JK. Relationship of resting heart rate and physical activity with insulin sensitivity in a population-based survey. J Diabetes Metab Disord. 2015;14(1):41.PubMedPubMedCentral
40.
Zurück zum Zitat Oda E, Aizawa Y. Resting heart rate predicts metabolic syndrome in apparently healthy non-obese Japanese men. Acta Diabetol. 2014;51(1):85–90.PubMed Oda E, Aizawa Y. Resting heart rate predicts metabolic syndrome in apparently healthy non-obese Japanese men. Acta Diabetol. 2014;51(1):85–90.PubMed
41.
Zurück zum Zitat Katagiri H, Yamada T, Oka Y. Adiposity and cardiovascular disorders: disturbance of the regulatory system consisting of humoral and neuronal signals. Circ Res. 2007;101(1):27–39.PubMed Katagiri H, Yamada T, Oka Y. Adiposity and cardiovascular disorders: disturbance of the regulatory system consisting of humoral and neuronal signals. Circ Res. 2007;101(1):27–39.PubMed
42.
Zurück zum Zitat Yamada T, Katagiri H, Ishigaki Y, et al. Signals from intra-abdominal fat modulate insulin and leptin sensitivity through different mechanisms: neuronal involvement in food-intake regulation. Cell Metab. 2006;3(3):223–9.PubMed Yamada T, Katagiri H, Ishigaki Y, et al. Signals from intra-abdominal fat modulate insulin and leptin sensitivity through different mechanisms: neuronal involvement in food-intake regulation. Cell Metab. 2006;3(3):223–9.PubMed
43.
Zurück zum Zitat Inoue T, Iseki K, Iseki C, et al. Elevated resting heart rate is associated with white blood cell count in middle-aged and elderly individuals without apparent cardiovascular disease. Angiology. 2012;63(7):541–6.PubMed Inoue T, Iseki K, Iseki C, et al. Elevated resting heart rate is associated with white blood cell count in middle-aged and elderly individuals without apparent cardiovascular disease. Angiology. 2012;63(7):541–6.PubMed
44.
Zurück zum Zitat Van Westerloo D, Giebelen I, Meijers J, et al. Vagus nerve stimulation inhibits activation of coagulation and fibrinolysis during endotoxemia in rats. J Thromb Haemost. 2006;4(9):1997–2002.PubMed Van Westerloo D, Giebelen I, Meijers J, et al. Vagus nerve stimulation inhibits activation of coagulation and fibrinolysis during endotoxemia in rats. J Thromb Haemost. 2006;4(9):1997–2002.PubMed
45.
Zurück zum Zitat Rogowski O, Shapira I, Shirom A, et al. Heart rate and microinflammation in men: a relevant atherothrombotic link. Heart. 2007;93(8):940–4.PubMedPubMedCentral Rogowski O, Shapira I, Shirom A, et al. Heart rate and microinflammation in men: a relevant atherothrombotic link. Heart. 2007;93(8):940–4.PubMedPubMedCentral
46.
Zurück zum Zitat Lee Y-J, Lee J-W, Kim J-K, et al. Elevated white blood cell count is associated with arterial stiffness. Nutr Metab Cardiovasc Dis. 2009;19(1):3–7.PubMed Lee Y-J, Lee J-W, Kim J-K, et al. Elevated white blood cell count is associated with arterial stiffness. Nutr Metab Cardiovasc Dis. 2009;19(1):3–7.PubMed
47.
Zurück zum Zitat Sun JC, Huang XL, Deng XR, et al. Elevated resting heart rate is associated with dyslipidemia in middle-aged and elderly Chinese. Biomed Environ Sci. 2014;27(8):601–5.PubMed Sun JC, Huang XL, Deng XR, et al. Elevated resting heart rate is associated with dyslipidemia in middle-aged and elderly Chinese. Biomed Environ Sci. 2014;27(8):601–5.PubMed
48.
Zurück zum Zitat Bønaa KH, Arnesen E. Association between heart rate and atherogenic blood lipid fractions in a population. The Tromsø study. Circulation. 1992;86(2):394–405.PubMed Bønaa KH, Arnesen E. Association between heart rate and atherogenic blood lipid fractions in a population. The Tromsø study. Circulation. 1992;86(2):394–405.PubMed
49.
Zurück zum Zitat Beddhu S, Nigwekar SU, Ma X, et al. Associations of resting heart rate with insulin resistance, cardiovascular events and mortality in chronic kidney disease. Nephrol Dial Transplant. 2009;24(8):2482–8.PubMedPubMedCentral Beddhu S, Nigwekar SU, Ma X, et al. Associations of resting heart rate with insulin resistance, cardiovascular events and mortality in chronic kidney disease. Nephrol Dial Transplant. 2009;24(8):2482–8.PubMedPubMedCentral
50.
Zurück zum Zitat Lammers G, van Duijnhoven NT, Hoenderop JG, et al. The identification of genetic pathways involved in vascular adaptations after physical deconditioning versus exercise training in humans. Exp Physiol. 2013;98(3):710–21.PubMed Lammers G, van Duijnhoven NT, Hoenderop JG, et al. The identification of genetic pathways involved in vascular adaptations after physical deconditioning versus exercise training in humans. Exp Physiol. 2013;98(3):710–21.PubMed
51.
Zurück zum Zitat Rampersaud E, Nathanson L, Farmer J, et al. Genomic signatures of a global fitness index in a multi-ethnic cohort of women. Ann Hum Genet. 2013;77(2):147–57.PubMed Rampersaud E, Nathanson L, Farmer J, et al. Genomic signatures of a global fitness index in a multi-ethnic cohort of women. Ann Hum Genet. 2013;77(2):147–57.PubMed
52.
Zurück zum Zitat Thomaes T, Thomis M, Onkelinx S, et al. A genetic predisposition score for muscular endophenotypes predicts the increase in aerobic power after training: the CAREGENE study. BMC Genet. 2011;12(1):84.PubMedPubMedCentral Thomaes T, Thomis M, Onkelinx S, et al. A genetic predisposition score for muscular endophenotypes predicts the increase in aerobic power after training: the CAREGENE study. BMC Genet. 2011;12(1):84.PubMedPubMedCentral
53.
Zurück zum Zitat Anselmino M, Öhrvik J, Ryden L. Resting heart rate in patients with stable coronary artery disease and diabetes: a report from the euro heart survey on diabetes and the heart. Eur Heart J. 2010;31(24):3040–5.PubMed Anselmino M, Öhrvik J, Ryden L. Resting heart rate in patients with stable coronary artery disease and diabetes: a report from the euro heart survey on diabetes and the heart. Eur Heart J. 2010;31(24):3040–5.PubMed
54.
Zurück zum Zitat Grassi G, Arenare F, Quarti-Trevano F, et al. Heart rate, sympathetic cardiovascular influences, and the metabolic syndrome. Prog Cardiovasc Dis. 2009;52(1):31–7.PubMed Grassi G, Arenare F, Quarti-Trevano F, et al. Heart rate, sympathetic cardiovascular influences, and the metabolic syndrome. Prog Cardiovasc Dis. 2009;52(1):31–7.PubMed
55.
Zurück zum Zitat Palatini P. Sympathetic overactivity in hypertension: a risk factor for cardiovascular disease. Curr Hypertens Rep. 2001;3(1):S3–9.PubMed Palatini P. Sympathetic overactivity in hypertension: a risk factor for cardiovascular disease. Curr Hypertens Rep. 2001;3(1):S3–9.PubMed
56.
Zurück zum Zitat Bo H, LIU XY, ZHENG Y, et al. High physical activity is associated with an improved lipid profile and resting heart rate among healthy middle-aged Chinese people. Biomed Environ Sci. 2015;28(4):263–71. Bo H, LIU XY, ZHENG Y, et al. High physical activity is associated with an improved lipid profile and resting heart rate among healthy middle-aged Chinese people. Biomed Environ Sci. 2015;28(4):263–71.
Metadaten
Titel
Correlation of resting heart rate with anthropometric factors and serum biomarkers in a population-based study: Fasa PERSIAN cohort study
verfasst von
Yashar Goorakani
Massih Sedigh Rahimabadi
Azizallah Dehghan
Maryam Kazemi
Mahsa Rostami Chijan
Mostafa Bijani
Hadi Raeisi Shahraki
Ali Davoodi
Mojtaba Farjam
Reza Homayounfar
Publikationsdatum
01.12.2020
Verlag
BioMed Central
Erschienen in
BMC Cardiovascular Disorders / Ausgabe 1/2020
Elektronische ISSN: 1471-2261
DOI
https://doi.org/10.1186/s12872-020-01594-y

Weitere Artikel der Ausgabe 1/2020

BMC Cardiovascular Disorders 1/2020 Zur Ausgabe

Update Kardiologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.