Resting Heart Rate Research Paper



The objective was to examine the association of physical activity and resting heart rate (RHR) with hospital-diagnosed atrial fibrillation (AF) in a Norwegian cohort.

Methods and results

This prospective study included 20 484 adults (50.3% men) who participated in the third Tromsø Study survey in 1986–87. At baseline, physical activity was assessed by a validated questionnaire, and RHR was objectively measured. Participants were followed from baseline through 2010 with respect to incident cases of hospital-diagnosed AF documented on an electrocardiogram. During a mean follow-up period of 20 years (409 045 person-years), 750 participants (70.5% men) were diagnosed with AF. Compared with the low physical activity group, moderately active individuals had a 19% lower risk of any AF [adjusted hazard ratio (HR) 0.81, 95% confidence interval (CI) 0.68–0.97], whereas highly active had similar risk of AF. Vigorously active individuals showed a non-significantly higher risk of AF (adjusted HR 1.37, 95% CI 0.77–2.43). Risk of AF increased with decreasing RHR (adjusted HR 0.92, 95% CI 0.86–0.98 for each 10 b.p.m. increase in RHR), and RHR < 50 b.p.m. was a risk factor for AF (P < 0.05).


In this prospective cohort study, leisure time physical activity was associated with AF in a J-shaped pattern. Moderate physical activity was associated with a reduced risk of AF, whereas higher activity levels attenuated the benefits of moderate activity. Low RHR was a risk factor for AF. Our results support the hypothesis that moderate and vigorous physical activity may affect AF risk via different pathophysiological mechanisms.

Exercise, Physical activity, Atrial fibrillation, Resting heart rate, Arrhythmia


Atrial fibrillation (AF) is a cardiac arrhythmia with a prevalence of 0.5–1% at age 40–50 years, increasing to 5–15% at age 70–80 years.1 Typically, AF progresses from short, infrequent to longer, more frequent episodes, and eventually the patient may develop permanent AF.1 AF is most commonly associated with cardiovascular disease (CVD) or other medical conditions, but may also occur in individuals without any underlying medical condition,1 and factors such as alcohol consumption and endurance training have been linked to development of AF.2

In recent decades, studies have demonstrated high prevalences of AF in male endurance athletes.2–7 However, these studies are mainly conducted among men with a history of sport practice and demanding competitions at rather high level. Only recently, studies embracing a wider range of the physical activity continuum have addressed the issue, and the findings vary from increased risk8,9 or a gradually decreasing risk of AF with increasing physical activity level10–13 to a U-shaped relationship between physical activity and risk of AF.14,15 Very few studies have examined risk of AF in relation to occupational activity.16

Therefore, we aimed to examine the associations between leisure time and occupational physical activity, resting heart rate (RHR), and hospital-diagnosed AF in a community-based cohort of Norwegian men and women.


Study population

The Tromsø Study is a prospective, community-based cohort study with repeated surveys, conducted in the municipality of Tromsø, Norway. The study is described in detail elsewhere.17 The present study consists of participants from the survey in 1986–87 (Tromsø 3), which comprised 21 733 men and women aged 12–67 years (participation rate 75%). Follow-up data on AF were derived from medical hospital records at the University Hospital of North Norway, by linking the participants to the hospital's diagnosis registry using their national 11-digit identification number.

Participants who also had reported physical activity level 7 years prior to Tromsø 3 (data from the second Tromsø Study in 1979–80) were included in a subcohort in order to study AF in relation to change in physical activity.

The Tromsø Study has been approved by the Norwegian Data Inspectorate and recommended by the Regional Committee of Research Ethics. Participants were informed that data would be treated in strict confidence.

Analytical sample

After excluding participants younger than 20 years (n = 1054), participants with missing baseline data (n = 83), AF diagnosed prior to baseline (n = 25), migrating during the study (n = 35), or before participating in the baseline examination (n = 52), the present study includes 20 484 men and women (Figure 1). Of these, 12 121 persons also participated in the second Tromsø Study survey in 1979–80, generating a subcohort with two assessments of physical activity.

Baseline data collection

At baseline in 1986–87, data were collected by questionnaire and physical examinations. From the questionnaire, we extracted self-reported data on current smoking (yes/no), CVD, i.e. heart attack, stroke, and/or angina (yes/no), diabetes (yes/no), educational level (years), use of heart medicine or hypertension treatment during the last 14 days (yes/no), teetotaller (yes/no), and physical activity. Physical activity was assessed with separate questions on leisure time and occupational physical activity, which have both been used in several other health surveys.8,16,18–20 Leisure time physical activity was graded from 1 to 4 with the following categories: (i) reading, watching TV, or other sedentary activities (‘low activity’); (ii) walking, cycling, or other forms of exercise at least 4 h a week (‘moderate activity’ ); (iii) participation in recreational sports, heavy gardening, etc. at least 4 h a week (‘high activity’); and (iv) participation in hard training or sports competitions regularly several times a week (‘vigorous activity’). The occupational activity question was also graded from 1 to 4, using the following response options: (i) mostly sedentary work; (ii) work requiring a lot of walking; (iii) work requiring a lot of walking and lifting; and (iv) heavy manual labour.

Physical activity was measured with similar questions in Tromsø 2. In a subsample comprising participants with physical activity data from both the second and third surveys, we categorized the participants into four categories according to change in leisure time physical activity from 1979–80 to 1986–87: (i) low physical activity (low at both examinations); (ii) reduced activity (from moderate/high/vigorous to low); (iii) increased activity (from low to moderate/high/vigorous); and finally (iv) active (moderate/high/vigorous at both examinations).

Height and weight were measured to the nearest centimetre and half-kilogram, with subjects wearing light clothing and no shoes. Body mass index (BMI) was calculated as weight (kg)/height2 (m2). Blood pressure was measured using standard procedures (Dinamap, Criticon, Tampa, FL, USA), and RHR was derived during the time of the blood pressure measurement after 2 min rest. Three recordings of heart rate were made with 2 min interval, and the lowest recorded measurement was used.

Follow-up and detection of AF

The participants were followed from the date of examination in 1986–87 (Tromsø 3) until the date of first documented AF, or date of censoring due to migration or death, or end of follow-up at 31 December 2010, whichever came first. Deaths and migration from Tromsø during follow-up were identified through the Population Register of Norway.

Incident cases of AF documented on an electrocardiogram (ECG) were retrieved from medical hospital records at the University Hospital North Norway, which is the only hospital within a radius of 250 km. For participants without arrhythmia, but with diagnoses of cerebrovascular or cardiovascular events, text search in electronic records was performed, along with a manual search in paper versions of hospital records, aiming at documenting further AF events. Adjudication of AF events was performed by an independent endpoint committee.21

AF type was categorized into any, paroxysmal/persistent, and permanent. Subjects with transient AF occurring only during an acute myocardial infarction or cardiac surgery and persons with AF documented only in the last week of life were classified as non-cases.

Statistical analyses

Cox proportional hazard regression was used to assess the association between AF and leisure time and occupational physical activity and RHR. Proportional hazard assumptions were tested by inspecting log minus log plots. The lowest physical activity level was used as the reference group. RHR was treated as both a continuous and a categorical variable [<50, 50–59, 60–69, 70–79, 80–89, ≥90 b.p.m., with the lowest RHR group (<50 b.p.m., n = 286) as the reference group]. All analyses were adjusted for baseline age, sex, daily smoking, BMI, height, CVD, systolic and diastolic blood pressures, diabetes, and hypertension treatment. Secondary analyses were conducted in a subcohort (n = 12 121), using change in physical activity with four categories as exposure.

Sensitivity analyses were performed to assess the robustness of the leisure time physical activity model, with the following additional adjustments: (i) RHR was added to the model; (ii) alcohol consumption, education, and use of heart medication were added to the model (n = 15 685); (iii) exclusion of participants using heart medication and participants with baseline CVD; and (iv) interim myocardial infarction was added to the model. Finally, use of heart medication was added to the RHR model.

Possible interactions were assessed by adding multiplicative interaction terms to the main multivariable model. No significant interactions were indicated between sex and physical activity, age and physical activity, or physical activity and RHR (P > 0.2).

Two-sided P < 0.05 was considered statistically significant. All analyses were performed using SPSS (Statistical Package for Social Sciences, Chicago, IL, USA), version 22.


Baseline characteristics

In total, 10 300 men (mean age 39.1 years at baseline) and 10 184 women (mean age 36.9 years at baseline) were included in the analyses. Further baseline characteristics of the participants are given in Table 1. During a mean follow-up period of 20.0 years (409 045 person-years), 750 participants (529 men and 221 women) were diagnosed with AF, of which 408 were paroxysmal/persistent and 342 permanent. Incidence of AF was 1.83/1000 person-years (2.62/1000 person-years in men and 1.07/1000 person-years in women).

Table 1

Baseline characteristics by physical activity levels

Men (n = 10 300)
Women (n = 10 184)
Low activity Moderate activity High activity Vigorous activity Low activity Moderate activity High/vigorous activitya
N2371 5110 2358 461 2420 6708 1056 
Age (years) 39.0 (11.0) 40.8 (11.2) 37.4 (10.3) 30.1 (8.5) 36.8 (9.8) 37.3 (9.9) 34.5 (9.7) 
Body height (cm) 177.0 (6.9) 177.1 (6.8) 178.1 (6.6) 178.6 (7.0) 164.0 (6.3) 164.4 (6.1) 165.6 (5.9) 
Body weight (kg) 78.1 (12.2) 77.5 (10.8) 77.2 (9.7) 75.6 (9.0) 62.7 (11.0) 62.6 (9.8) 62.1 (8.5) 
BMI (kg/m224.9 (3.4) 24.7 (3.1) 24.3 (2.6) 23.7 (2.3) 23.3 (3.9) 23.2 (3.4) 22.6 (2.9) 
Systolic blood pressure (mmHg) 130 (15) 130 (14) 129 (13) 129 (13) 120 (15) 120 (14) 118 (13) 
Diastolic blood pressure (mmHg) 77 (11) 77 (11) 74 (11) 69 (10) 73 (11) 72 (10) 70 (10) 
RHR (b.p.m.) 75 (13) 73 (13) 68 (12) 63 (12) 78 (12) 77 (13) 72 (12) 
Education (years)b11.1 (4.0) 11.2 (3.9) 12.1 (3.9) 12.6 (3.4) 10.8 (3.6) 11.2 (3.7) 12.2 (3.8) 
 <50 0.8 (18) 1.4 (72) 3.9 (92) 11.7 (54) 0.4 (10) 0.4 (28) 1.1 (12) 
 50–59 8.2 (194) 11.8 (603) 20.3 (479) 32.3 (149) 4.3 (104) 5.6 (377) 9.7 (102) 
 60–69 27.0 (641) 30.4 (1553) 33.7 (794) 30.8 (142) 19.2 (464) 23.1 (1549) 30.9 (326) 
 70–79 33.7 (798) 30.9 (1578) 25.4 (598) 15.4 (71) 35.0 (846) 34.6 (2320) 33.4 (353) 
 80–89 18.7 (444) 16.0 (819) 11.7 (275) 6.7 (31) 24.5 (592) 21.2 (1424) 17.5 (185) 
 ≥90 11.6 (276) 9.5 (485) 5.1 (120) 3.0 (14) 16.7 (404) 15.1 (1010) 7.4 (78) 
Smokers 59.8 (1418) 47.8 (2442) 37.4 (883) 21.3 (98) 56.7 (1372) 43.8 (2937) 37.5 (396) 
CVD 3.7 (88) 3.5 (181) 1.6 (38) 0.0 (0) 1.2 (29) 0.6 (39) 0.0 (0) 
Diabetes 1.1 (25) 0.9 (48) 0.3 (8) 0.2 (1) 0.4 (10) 0.4% (25) 0.3 (3) 
Mostly sedentary work 50.7 (1203) 42.1 (2152) 37.5 (884) 36.4 (168) 45.0 (1088) 34.1 (2289) 34.3 (362) 
Teetotallerb5.9 (108) 6.8 (275) 4.8 (91) 5.2 (20) 9.2 (158) 9.8 (488) 7.4 (60) 
Heart medicine useb2.1 (39) 2.2 (91) 0.7 (14) 0.3 (1) 1.2 (21) 0.5 (27) 0.0 (0) 
Treatment for hypertension 3.3 (78) 3.4 (172) 1.9 (45) 0.7 (3) 2.3 (56) 2.1 (138) 0.9 (9) 
Men (n = 10 300)
Women (n = 10 184)
Low activity Moderate activity High activity Vigorous activity Low activity Moderate activity High/vigorous activitya
N2371 5110 2358 461 2420 


Elevated resting heart rate has been shown to be associated with mortality across several general population studies1–3 and in patient populations.4,5

In healthy subjects, the main question is whether a high resting heart rate is an independent risk factor, a surrogate marker of subclinical disease states, or a marker of poor physical fitness. A number of studies have shown that resting heart rate is associated with circulating levels of inflammatory markers related to subclinical chronic disease states.6–8 Resting heart rate is determined by the activity of the autonomic nervous system, levels of circulating hormones and cardiorespiratory fitness.9,10 The association between a high level of cardiorespiratory fitness (physical fitness) and a low resting heart rate is well known11 and physical fitness may therefore be an important confounding factor. Most general population studies have included information about self-reported physical activity.12,13 However, the correlation between self-reported physical activity and objectively measured physical fitness is only poor to moderate.14 The lack of objectively measured physical fitness in the current literature may have resulted in residual confounding and may have influenced the interpretation of previous findings.

In the present study, we investigated whether resting heart rate was predictive of mortality in a population of employed apparently healthy middle-aged men who previously had physical fitness determined by a bicycle ergometer test and were followed for 16 years.


A total of 2798 subjects were included in the current study; 1082 men (38.7%) died during the 16 years of follow-up.

Table 1 shows baseline characteristics according to categories of resting heart rate. As shown, high resting heart rate was associated with lower physical fitness, and higher BP, total cholesterol, TGs and BMI. There was no difference in age or social class. Interestingly, subjects in the lowest resting heart rate categories were more likely to be smokers than in the higher resting heart rate categories.

Resting heart rate and physical fitness (VO2Max)

There was a highly significant correlation between VO2Max and resting heart rate (R=−0.34, p<0.001) (figure 2). Subjects with higher levels of physical fitness were more likely to have lower resting heart rates.

Figure 2

Relationship between physical fitness (VO2Max) and resting heart rate (bpm).

Resting heart rate and mortality

Overall, a high resting heart rate was a significant predictor of mortality. As shown in table 2, subjects with elevated resting heart rate were at significantly greater risk of mortality in all models (1–5). In the fully adjusted model, resting heart rate in the range 51–80 bpm was associated with about a 40–50% increase in risk, a resting heart rate in the range 81–90 bpm conferred a twofold increase in risk, and resting heart rates above 90 bpm risk conferred a threefold increase in risk compared to subjects in the lowest heart rate category (<50 bpm).

In a fully adjusted model with heart rate as a continuous variable, elevated heart rate was associated with an increased risk of 16% (10–22) per 10 bpm increase in resting heart rate.

There was a borderline significant interaction between resting heart rate, smoking status and mortality (p=0.07). In the fully adjusted model and with resting heart rate as a continuous variable, risk increased with 20% (12–27) in smokers, and 14% (4–24) in non-smokers per 10 bpm increase in resting heart rate.

Table 2

HRs (95% confidence limits) for all-cause mortality according levels of resting heart rate


In the present study of healthy middle-aged men, the main finding was that resting heart rate was a risk factor for mortality independent of physical fitness (VO2Max) and other major potential confounders.

Resting heart rate as a risk factor for mortality has received considerable attention in recent years. However, a concern has been whether elevated resting heart rate is merely a surrogate marker of poor physical fitness, which in turn is associated with poor prognosis. A high level of physical fitness is a strong predictor of longevity11 and is associated with lower heart rate, as also demonstrated in the present study. Level of physical fitness therefore plays a pivotal role in the study of resting heart rate. In a study from the Paris Prospective Study, resting heart rate was predictive of mortality and especially sudden death after adjusting for duration of exercise.24 However, the main body of studies use self-reported levels of physical activity22,25 or, in some cases, include no information.26 In the current study, all subjects underwent a physical exercise test and estimation of VO2Max as well as an assessment of leisure-time physical activity; we found that irrespective of level of physical fitness subjects with high resting heart rates fare worse than subjects with lower heart rates. This suggests that a high resting heart rate is not a mere marker of poor physical fitness but is an independent risk factor.

There were more smokers in the low heart rate categories than in the higher heart rate categories. Although the acute effects of smoking are tachycardia and increase in BP, healthy smokers are more likely to have lower BP than non-smokers; this has been shown in numerous studies,27–29 and the same mechanisms may explain the observation in the present study. The possible mechanisms are at least twofold and probably pertinent to heart rate as well: first, it represents a counter-regulatory physiological response to the acute rise in BP and heart rate following smoking; and second, the healthy worker effect probably plays a role—smokers in the present study are healthier, leaner and more fit than non-smokers; they can ‘endure’ the smoking.

Interestingly, we found a borderline significant interaction between resting heart rate, smoking and mortality, which suggests that high heart rate at any given resting heart rate level is associated with greater risk in smokers than in non-smokers. In a study from the Copenhagen City Heart Study,23 resting heart rate was a stronger predictor of all-cause mortality among smokers than among non-smokers, which is in line with results from the present study. That this relationship can be found in two different large cohorts adds to the evidence that a true relationship may exist and not simply be a random association. Considering that the number of smokers globally is about 1 billion,30 this is yet another argument for preventive measures against tobacco consumption and might have therapeutic implications in terms of heart rate monitoring and perhaps modification in smokers.

Several pathophysiological mechanisms have been proposed to explain the relationship between high resting heart rate and mortality.31,32 Resting heart rate has been found to correlate with longevity in mammals. Levine33 showed that the number of heart beats per lifetime is the same across different mammal species, indicating that basal metabolic effects may explain the effect of high resting heart rate on mortality. Smoking is known to promote inflammatory pathways and induce alterations in metabolism, vessel walls, haemostatics and impaired blood flow34,35; also, high heart rate may promote the development of atherosclerosis and plaque rupture through increase in cardiac work, decreased artery compliance and increase in arterial wall stress.36 Altogether, these mechanisms could be related to the findings of this study. Studies investigating cause-specific mortality, be it mainly mortality from cardiovascular reasons, cancer or other disease entities, may further elucidate the relationship between elevated resting heart rate and longevity.

Methodological considerations

Possible study limitations should be considered. Since all subjects were employed and recruited from work places, there may have been a ‘healthy worker’ effect, resulting in the study population being healthier than would be seen in the general population. Also, there may have been a survivor selection bias. Since resting heart rate and VO2Max were measured at different examinations, only subjects who survived to attend both examinations were included in the study. This may have biased the results towards the null hypothesis, making the observed HRs smaller than the true HRs.

Also, physical fitness may have changed between the first and the second examination. However, subjects were free of overt disease and survived to participate in the second examination; this makes it more likely that the subjects were healthier than the background population as a whole; second, all subjects with cardiovascular disease, diabetes or absence of sinus rhythm were excluded, suggesting that no major health-related event would have occurred to change general fitness levels substantially; third, a normal deterioration in general fitness over time would be the same in the entire study population and would therefore not affect the findings; and fourth, the correlation between physical fitness measured at the first examination and resting heart rate measured at the second examination supports that cardiorespiratory physical fitness was in general maintained between the two examinations. This is supported by the finding that the correlation between resting heart rate and physical fitness (r=−0.34) found in the present study was identical with the correlation between resting heart rate and physical fitness measured at the same point in time in a male population in the Tromsø Study.14

Heart rate shows diurnal variation, which may give some imprecision in the estimate of resting heart rate; however, misclassification of heart rate due to a single assessment would bias the results towards the null hypothesis and can therefore not explain our findings.

Finally, it should be mentioned that since the results presented here are based only on findings among healthy, middle-aged and elderly Caucasian men, our results may not necessarily apply to other population groups.


In the present study of 2798 healthy, middle-aged and elderly Caucasian men followed for 16 years, resting heart was a risk factor for mortality independent of physical fitness (VO2Max) assessed by a bicycle ergometer, leisure-time physical activity and other conventional risk factors. These results suggest that in healthy subjects, elevated resting heart rate is not merely a marker of poor general fitness but an independent risk factor.


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