Correlation of Resting Heart Rate with Anthropometric Factors and Serum Biomarkers in a Population-based Study: Fasa PERSIAN Cohort Study

Abstract BackgroundThere 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 MethodsIt 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 & ConclusionA total number of 9975 persons 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 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.

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Correlation of Resting Heart Rate with Anthropometric factors and serum biomarkers in a population-based study: Fasa PERSIAN Cohort study

10.21203/rs.3.rs-20950/v2 ◽

2020 ◽

Author(s):

Yashar Goorakani ◽

Massih Sedigh Rahimabadi ◽

Azizallah Dehghan ◽

Maryam Kazemi ◽

Mahsa Rostami Chijan ◽

...

Keyword(s):

Heart Rate ◽

Cohort Study ◽

Random Sample ◽

Communicable Disease ◽

Density Lipoprotein ◽

Serum Biomarkers ◽

Baseline Survey ◽

Resting Heart Rate ◽

Absolute Deviation ◽

Males And Females

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 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 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.

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

BMC Cardiovascular Disorders ◽

10.1186/s12872-020-01594-y ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Yashar Goorakani ◽

Massih Sedigh Rahimabadi ◽

Azizallah Dehghan ◽

Maryam Kazemi ◽

Mahsa Rostami Chijan ◽

...

Keyword(s):

Heart Rate ◽

Cohort Study ◽

Population Based ◽

Serum Biomarkers ◽

Resting Heart Rate ◽

Population Based Study

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Conventional and bi-directional genetic evidence on resting heart rate and cardiometabolic traits

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/clinem/dgab847 ◽

2021 ◽

Author(s):

Tao Huang ◽

Wenxiu Wang ◽

Jingjia Wang ◽

Jun Lv ◽

Canqing Yu ◽

...

Keyword(s):

Blood Pressure ◽

Heart Rate ◽

Large Scale ◽

Low Density Lipoprotein ◽

Density Lipoprotein ◽

Heat Rate ◽

Resting Heart Rate ◽

Causal Inferences ◽

Reactive Protein ◽

Cardiometabolic Traits

Abstract Objectives To examine the direction, strength and causality of the associations of resting heart rate (RHR) with cardiometabolic traits. Methods We assessed the strength of associations between measured RHR and cardiometabolic traits in 506,211 and 372,452 participants from China Kadoorie Biobank (CKB) and UK Biobank (UKB). Mendelian randomization (MR) analyses were used to make causal inferences in 99,228 and 371,508 participants from CKB and UKB, respectively. Results We identified significant, directionally-concordant observational associations between RHR and higher total cholesterol, triglycerides (TG), low-density lipoprotein, C-reactive protein (CRP), glucose, body mass index, waist-hip ratio (WHR), systolic blood pressure (SBP) and diastolic blood pressure (DBP) after the Bonferroni correction. MR analyses showed that 10 beat/min higher genetically-predicted RHR were trans-ethnically associated with a higher DBP (beta 2.059 [95%CI 1.544, 2.574] mmHg in CKB; 2.037 [1.845, 2.229] mmHg in UKB), higher CRP (0.180 [0.057, 0.303] log mg/L in CKB; 0.154 [0.134, 0.174] log mg/L in UKB), higher TG (0.052 [-0.009, 0.113] log mmol/L in CKB; 0.020 [0.010, 0.030] log mmol/L in UKB) and higher WHR (0.218 [-0.033, 0.469] % in CKB; 0.225 [0.111, 0.339] % in UKB). In the opposite direction, higher genetically-predicted SBP, TG, glucose, WHR and lower high-density lipoprotein were associated with elevated RHR. Conclusion Our large-scale analyses provide causal evidence between RHR and cardiometabolic traits, highlighting the importance of monitoring heat rate as a means of alleviating the adverse effect of metabolic disorders.

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Relationship between resting heart rate and incident heart failure in patients with hypertension: The Kailuan Cohort Study in China

Journal of Clinical Hypertension ◽

10.1111/jch.14062 ◽

2020 ◽

Vol 22 (12) ◽

pp. 2325-2331

Author(s):

MaoXiang Zhao ◽

Yanming Chen ◽

Miao Wang ◽

Chi Wang ◽

Siyu Yao ◽

...

Keyword(s):

Heart Failure ◽

Heart Rate ◽

Cohort Study ◽

Resting Heart Rate ◽

Incident Heart Failure

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Association between resting heart rate just before starting the first dialysis session and mortality: A multicentre prospective cohort study

Nephrology ◽

10.1111/nep.13048 ◽

2018 ◽

Vol 23 (5) ◽

pp. 461-468 ◽

Cited By ~ 1

Author(s):

Daijo Inaguma ◽

Shigehisa Koide ◽

Kazuo Takahashi ◽

Hiroki Hayashi ◽

Midori Hasegawa ◽

...

Keyword(s):

Heart Rate ◽

Cohort Study ◽

Prospective Cohort Study ◽

Prospective Cohort ◽

Dialysis Session ◽

Resting Heart Rate

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Visceral Adiposity Index and Atherogenic Index of Plasma as Useful Predictor of Cardiovascular Diseases Risk: Evidence From A Cohort Study in Iran

10.21203/rs.3.rs-609029/v1 ◽

2021 ◽

Author(s):

Behrooz Hamzeh ◽

Yahya Pasdar ◽

Narmin Mirzaei ◽

Roya Safari Faramani ◽

Farid Najafi ◽

...

Keyword(s):

Cohort Study ◽

Cardiovascular Diseases ◽

Communicable Disease ◽

Density Lipoprotein ◽

Visceral Adiposity ◽

Atherogenic Index ◽

Visceral Adiposity Index ◽

Cross Sectional ◽

Atherogenic Index Of Plasma ◽

Adiposity Index

Abstract Background Visceral Adiposity index (VAI) and atherogenic index of plasma (AIP) are relatively new indicators for predicting Non-Communicable disease (NCDs). The aim of this study was to assess the association AIP and VAI with risk of cardiovascular diseases (CVDs). Methods This was a cross-sectional analysis conducted on 7362 individuals aged 35 to 65 years participated in Ravansar Non-Communicable Diseases (RaNCD) cohort study. AIP was calculated based on the value of triglyceride and high density lipoprotein cholesterol (HDL-C). VAI was calculated using Body mass index (BMI), waist circumference (WC), triglyceride, and HDL-C. All participants were stratified into three groups based on AIP and VAI tertiles. Logistic regression models were used to assess the association of AIP and VAI with CVDs. Results The mean of AIP and VAI was significantly higher in CVDs patients than in non-CVDs (P < 0.001). After adjusting for age, sex, BMI and physical activity the risk of CVDs in the second and third tertile of AIP were 1.22 (95% CI: 1.02, 1.45) and 1.40 (95% CI: 1.19, 1.66) times higher comparing to the first tertile, respectively. Risk of CVDs in the second and third tertile of VAI were 1.28 (95% CI: 1.06, 1.53) and 1.52 (95% CI: 1.25, 1.83) times higher than the first tertile, respectively; while adjusting for age, sex, hypertension and dyslipidemia and smoking. Conclusion According to the findings, AIP and VAI were positively associated with CVDs. Therefore, AIP and VAI can be useful in identifying high-risk subgroups of CVDs in general population.

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Exercise capacity and body mass index - important predictors of change in resting heart rate

BMC Cardiovascular Disorders ◽

10.1186/s12872-019-01286-2 ◽

2019 ◽

Vol 19 (1) ◽

Author(s):

Michal Ehrenwald ◽

Asaf Wasserman ◽

Shani Shenhar-Tsarfaty ◽

David Zeltser ◽

Limor Friedensohn ◽

...

Keyword(s):

Body Mass Index ◽

Heart Rate ◽

Body Mass ◽

Healthy Lifestyle ◽

Smoking Status ◽

Medical Center ◽

Linear Regression Analysis ◽

Density Lipoprotein ◽

Resting Heart Rate ◽

Metabolic Equivalents

Abstract Background Resting heart rate (RHR) is an obtainable, inexpensive, non-invasive test, readily available on any medical document. RHR has been established as a risk factor for cardiovascular morbidity, is related to other cardiovascular risk factors, and may possibly predict them. Change in RHR over time (∆RHR) has been found to be a potential predictor of mortality. Methods In this prospective study, RHR and ∆RHR were evaluated at baseline and over a period of 2.9 years during routine check-ups in 6683 subjects without known cardiovascular disease from the TAMCIS: Tel-Aviv Medical Center Inflammation Survey. Multiple linear regression analysis with three models was used to examine ∆RHR. The first model accounted for possible confounders by adjusting for age, sex and body mass index (BMI). The 2nd model included smoking status, baseline RHR, diastolic blood pressure (BP), dyslipidemia, high-density lipoprotein (HDL) and metabolic equivalents of task (MET), and in the last model the change in MET and change in BMI were added. Results RHR decreased with age, even after adjustment for sex, BMI and MET. The mean change in RHR was − 1.1 beats/min between two consecutive visits, in both men and women. This ∆RHR was strongly correlated with baseline RHR, age, initial MET, and change occurring in MET and BMI (P < 0.001). Conclusions Our results highlight the need for examining individual patients’ ∆RHR. Reinforcing that a positive ∆RHR is an indicator of poor adherence to a healthy lifestyle.

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