Resting Heart Rate and Incident Atrial Fibrillation in the Elderly WESLEY T. O’NEAL, M.D., M.P.H.,* MOHAMED F. ALMAHMOUD, M.D.,† and ELSAYED Z. SOLIMAN, M.D., M.SC., M.S.†,‡ From the *Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina; †Department of Internal Medicine, Section on Cardiology, Wake Forest School of Medicine, Winston-Salem, North Carolina; and ‡Department of Epidemiology and Prevention, Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Winston-Salem, North Carolina
Background: Alterations in autonomic tone and/or sinus node dysfunction are common with aging. We hypothesized that older persons with low or high heart rates represent a population with subclinical abnormalities who are more likely to develop atrial fibrillation (AF). Methods: A total of 5,226 participants aged 65 years or more (85% white; 42% male) with complete data from the Cardiovascular Health Study were used in this analysis. AF cases were identified during the yearly study electrocardiograms, participant history of a physician diagnosis, or by hospitalization data. Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (CI) for the association between resting heart rate and incident AF using clinically relevant categories (heart rate ࣘ60 beats/min, 60< heart rate beats/min ࣘ90 beats/min (reference), heart rate >90 beats/min) and as a continuous variable per 5 beats/min decrease. Results: Over a median follow-up of 12.7 years, a total of 532 (10.2%) participants developed AF. In a multivariable Cox regression analysis, heart rates ࣘ60 beats/min (HR = 1.3, 95% CI = 1.1, 1.5), but not >90 beats/min (HR = 1.1, 95% CI = 0.52, 2.3), were associated with an increased risk of AF. Additionally, heart rate per 5 beats/min decrease was associated with an increased risk of AF (HR = 1.06, 95% CI = 1.01, 1.1). The results were consistent in subgroup analyses stratified by age, sex, race, and baseline cardiovascular disease. Conclusion: In the elderly, low heart rates are associated with an increased risk of AF. Potentially, underlying alterations in autonomic tone and/or subclinical sinus node dysfunction manifested as slow heart rate predispose to AF. (PACE 2015; 00:1–7) heart rate, atrial fibrillation, epidemiology
Introduction Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice and its prevalence increases with age and among those with diabetes, hypertension, prior myocardial infarction, and heart failure.1–3 The prevalence Authors Wesley T. O’Neal and Mohamed F. Almahmoud contributed equally in the writing of this manuscript. This manuscript was prepared using CHS research materials obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center and does not necessarily reflect the opinions or views of the CHS or the NHLBI. Disclosures: The authors report no disclosures or sources of funding. Address for reprints: Wesley T. O’Neal, M.D., Department of Internal Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157. Fax: 336-7162273; e-mail: [email protected] Received October 9, 2014; revised December 3, 2014; accepted January 4, 2015. doi: 10.1111/pace.12591
of AF is projected to double by the year 2050 due to a higher predilection for older adults and the expected growth in this population.1,4 With the increased burden that AF will place on the healthcare system, the identification of AF risk factors is of paramount importance to detect and treat this arrhythmia in order to prevent complications such as stroke.5,6 Among patients who are treated for hypertension, a higher incidence of AF has been observed among individuals with higher compared with lower heart rates.7 In contrast, healthy male endurance athletes who have lower heart rates have been shown to have increased rates of AF than those who have higher heart rates.8–10 Alterations in autonomic tone and/or sinus node dysfunction, which are common with aging, possibly predispose to AF. Therefore, older persons with low or high heart rates may represent a population more likely to develop AF. To our knowledge, the association between resting heart rate and incident AF has not been examined in the elderly. The purpose of this study was to
© 2015 Wiley Periodicals, Inc. PACE, Vol. 00
2015
1
O’NEAL, ET AL.
Electronics Inc., Milwaukee, WI, USA) were used at all clinic sites, and resting, 10-second standard simultaneous 12-lead electrocardiograms were recorded for all participants. All electrocardiograms were processed in a central laboratory (initially at Dalhousie University, Halifax, Canada, and later at the EPICARE Center, Wake Forest School of Medicine, Winston-Salem, NC, USA). The electrocardiograms were first processed by the Dalhousie Electrocardiogram program and were reprocessed for the present study using the 2001 version of the GE Marquette 12-SL program (GE, Milwaukee, WI, USA). The methodology and prevalence of electrocardiogram abnormalities in CHS have been described.12 Baseline CVD was determined by self-reported history and medical record adjudication of the following diagnoses: myocardial infarction, angina pectoris without myocardial infarction, coronary revascularization procedures (angioplasty and coronary artery bypass graft surgery), and stroke.13
examine the association between resting heart rate and AF in the Cardiovascular Health Study (CHS), a population-based study of older adults. Methods Study Population Details of CHS have been previously described.11 Briefly, CHS is a prospective population-based cohort study of risk factors for cardiovascular disease (CVD) in individuals 65 years and older. A total of 5,888 participants with Medicare eligibility were recruited from four field centers located in the following U.S. locations: Forsyth County, NC; Sacramento County, CA; Washington County, MD; and Pittsburgh, PA. Participants were followed with semiannual contacts alternating between telephone calls and surveillance clinic visits. CHS clinic exams ended in June of 1999 and after that time two yearly phone calls were used to identify events and collect data. The institutional review boards at each participating site approved the study and written informed consent was obtained from each participant at enrollment. For the purpose of this analysis, participants were excluded if any of the following criteria were met: prevalent AF was reported or identified on the baseline electrocardiogram, baseline covariate data were missing, or follow-up data were missing.
Atrial Fibrillation Baseline AF cases were identified during the initial study electrocardiogram or by selfreported history of a physician diagnosis. AF cases also were identified during the annual study electrocardiograms that were performed annually until 1999. Additionally, hospitalization discharge data were used to identify AF cases using International Classification of Diseases codes 427.31 and 427.32. Hospital diagnosis codes for AF ascertainment have been shown to have a positive predictive value of 98.6%.14
Covariates Participant characteristics were collected during the initial CHS interview and questionnaire. Age, sex, race, income, and education were selfreported. Annual income was dichotomized at $25,000 and education was dichotomized at “high school or less.” Smoking was defined as “current” or “ever” versus “never” smoker. Participants’ blood samples were obtained after a 12-hour fast at the local field center. Measurements of total cholesterol, high-density lipoprotein (HDL) cholesterol, plasma glucose, and high-sensitivity C-reactive protein (hs-CRP) were used in this analysis. Diabetes was defined as a self-reported history of a physician diagnosis, a fasting glucose value ࣙ126 mg/dL, or by the current use of insulin or oral hypoglycemic medications. Blood pressure was measured for each participant in the seated position and systolic measurements were used in this analysis. Resting heart rate was recorded by measuring each participants’ pulse for 60 seconds. The use of aspirin, statin, and antihypertensive and antiarrhythmic medications were self-reported. Body mass index was computed as the weight in kilograms divided by the square of the height in meters. Identical electrocardiographs (MAC PC, Marquette
2
Statistical Analysis Categorical variables were reported as frequency and percentage while continuous variables were recorded as mean ± standard deviation. Statistical significance for categorical variables was tested using the χ 2 method and the Kruskal-Wallis procedure for continuous variables. Follow-up time was defined as the time between the initial heart rate measurement until one of the following: AF, death, loss to follow-up, or end of followup (July 1, 2008). Incidence rates for AF were calculated in units of 1,000 person-years. Cox proportional hazards regression was used to compute hazard ratios (HR) and 95% confidence intervals (CI) for the association between resting heart rate and incident AF. We examined the association by clinically relevant categories of heart rate (heart rate ࣘ60 beats/min, 60< heart rate beats/min ࣘ90, and heart rate >90 beats/min). We also examined the graphical association of heart rate and AF using a restricted cubic spline model and incorporated knots at the 5th , 50th , and
2015
PACE, Vol. 00
HEART RATE AND ATRIAL FIBRILLATION
In a multivariable Cox proportional hazards analysis, heart rates ࣘ60 beats/min (HR = 1.3, 95% CI = 1.1, 1.5), but not heart rates >90 beats/min (HR = 1.1, 95% CI = 0.52, 2.3), were associated with an increased risk of AF (Table II). Also, when we examined the association of heart rates ࣘ50 beats/min, an increased risk of AF was observed (HR = 1.4, 95% CI = 1.02, 1.8), suggesting a dose-response relationship with slow heart rates and AF. To examine whether the nonsignificant result in the high resting heart rate group was due to the small number of participants in that group, we examined the association of heart rates in the third tertile compared with the middle tertile as the reference. However, a nonsignificant result also was observed (HR = 0.96, 95% CI = 0.77, 1.2). When heart rate was examined as a continuous variable, decreases in heart rate per 5 beats/min were associated with an increased risk of AF (HR = 1.06, 95% CI = 1.01, 1.1; Table II). Similar results were obtained when the analysis was stratified by age, sex, race, and CVD (Table III). A sensitivity analysis, in which participants taking antiarrhythmic agents and/or heart rate modifying-drugs at baseline were excluded, was performed and the results were similar to the main result for the entire cohort (N = 4,253; HR = 1.06, 95% CI = 1.004, 1.1).
95th percentiles.15 Additionally, the association of heart rate as a continuous variable per 5 beats/min decrease was examined after observing an increased risk for lower values compared with higher values graphically. Multivariable models were constructed as follows: Model 1 adjusted for age, sex, race, education, and income; Model 2 adjusted for Model 1 covariates plus baseline CVD, smoking, systolic blood pressure, diabetes, body mass index, total cholesterol, HDL-cholesterol, aspirin, statins, antihypertensive and antiarrhythmic medications, and log(hs-CRP). We tested for interactions between our main effect variable and age (dichotomized at 80 years), sex, and race. We also examined if a differential association between heart rate and AF existed by baseline CVD status. Several sensitivity analyses were performed. Due to the small number of participants with heart rates >90 beats/min, we examined the association of heart rate with AF in the third (heart rate >69 beats/min) versus middle tertile (60< heart rate beats/min ࣘ69). We also examined the association of resting heart rates ࣘ50 beats/min to determine if a stronger association existed for persons with extremely low heart rates. A sensitivity analysis was performed excluding participants who were taking antiarrhythmic agents (Class I, II, III, and IV) and digoxin at baseline. The proportional hazards assumption was not violated in our analysis. Statistical significance was defined as P < 0.05. SAS Version 9.3 (Cary, NC, USA) was used for all analyses.
Discussion In this analysis from CHS, lower resting heart rates were associated with an increased risk of AF. Our results were consistent across subgroups of age, sex, race, and CVD. These findings suggest that underlying alterations in autonomic tone and/or subclinical sinus node dysfunction exist in persons with low heart rates that predispose to the development of AF. Data from the Losartan Intervention for End Point Reduction in Hypertension (LIFE) study have shown that higher in-treatment heart rates on serial electrocardiograms were associated with an increased risk of new-onset AF compared with persons who have lower heart rates.7 This association conflicts with that reported from other population-based reports mainly of healthy men. For example, a longitudinal analysis of healthy middle-aged men from Norway observed that males with low exercise heart rates have a higher risk of AF.8 Similar reports from endurance athletes have shown that low resting heart rates also carry a predisposition for AF.9,10 Our results are consistent with those that have shown an increased risk of AF for persons with lower heart rates. Several differences between the current report and prior studies that have examined the association between heart rate and AF exist. Our analysis
Results Of the 5,888 participants from the original CHS cohort, 58 participants with missing followup data were excluded. Of those who remained, 313 participants with baseline AF and 291 with missing baseline covariate data also were excluded. A total of 5,226 participants (85% white; 42% male) with complete data were used in this analysis. The study sample had a mean heart rate of 65 beats/min (median = 64 beats/min, interquartile range = 58–72 beats/min). The distribution of heart rates is shown in Figure 1. Baseline characteristics stratified by heart rate categories are shown in Table I. Over a median follow-up of 12.7 years, a total of 532 (10.2%) participants developed AF. The incidence rates for AF by heart rate categories are shown in Table II. When the association of resting heart rate was examined in a restricted cubic spline model, an increased risk of AF was observed with decreasing heart rates (Fig. 2). Although not significant, an upward trend was observed for increasing heart rate values.
PACE, Vol. 00
2015
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O’NEAL, ET AL.
Figure 1. Distribution of heart rate among study participants.
Figure 2. Risk of AF by heart rate.* *Each hazard ratio was computed with the median heart rate value of 64 beats/min as the reference. Dotted lines represent the 95% confidence interval. AF = atrial fibrillation.
was performed in a population-based cohort of older adults and was not limited to persons with hypertension or persons who were perceived to be healthy.7–10 Potentially, hypertension increases one’s sympathetic activity and subsequent risk for AF.16 However, we did not observe a significant
4
association between high heart rates and AF in this older population. Therefore, the observed association with lower heart rates and AF in the older population of CHS may be explained by an inappropriate parasympathetic response that predisposes to AF.16 Similar explanations have
2015
PACE, Vol. 00
HEART RATE AND ATRIAL FIBRILLATION
Table I. Baseline Characteristics of Study Participants (N = 5,226)
Characteristic Age, years 65–70 (%) 71–74 (%) 75–80 (%) >80 (%) Male sex (%) White (%) High school or less (%) Annual income 90 beats/min (n = 92)
844 (45) 443 (24) 425 (23) 152 (8.2) 933 (50) 1,639 (88) 990 (53) 1,083 (58) 26 (3.7) 1,038 (56) 198 (11) 139 (21) 211 (37) 54 (15) 849 (46) 74 (2.3) 629 (34) 0.75 (1.0) 446 (24)
1,372 (42) 782 (24) 763 (23) 353 (11) 1,242 (38) 2,731 (84) 1,943 (59) 2,178 (67) 27 (4.2) 1,705 (52) 589 (18) 140 (20) 213 (40) 55 (16) 1,503 (46) 36 (1.9) 1,074 (33) 1.0 (1.0) 666 (20)
36 (39) 22 (24) 23 (25) 11 (12) 32 (35) 64 (70) 65 (71) 75 (82) 28 (5.1) 52 (57) 34 (37) 142 (21) 210 (46) 54 (17) 45 (49) 3 (3.3) 33 (36) 1.7 (1.3) 25 (27)
P Value*
0.052
Background: Alterations in autonomic tone and/or sinus node dysfunction are common with aging. We hypothesized that older persons with low or high heart rates represent a population with subclinical abnormalities who are more likely to develop atrial fibrillation (AF). Methods: A total of 5,226 participants aged 65 years or more (85% white; 42% male) with complete data from the Cardiovascular Health Study were used in this analysis. AF cases were identified during the yearly study electrocardiograms, participant history of a physician diagnosis, or by hospitalization data. Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (CI) for the association between resting heart rate and incident AF using clinically relevant categories (heart rate ࣘ60 beats/min, 60< heart rate beats/min ࣘ90 beats/min (reference), heart rate >90 beats/min) and as a continuous variable per 5 beats/min decrease. Results: Over a median follow-up of 12.7 years, a total of 532 (10.2%) participants developed AF. In a multivariable Cox regression analysis, heart rates ࣘ60 beats/min (HR = 1.3, 95% CI = 1.1, 1.5), but not >90 beats/min (HR = 1.1, 95% CI = 0.52, 2.3), were associated with an increased risk of AF. Additionally, heart rate per 5 beats/min decrease was associated with an increased risk of AF (HR = 1.06, 95% CI = 1.01, 1.1). The results were consistent in subgroup analyses stratified by age, sex, race, and baseline cardiovascular disease. Conclusion: In the elderly, low heart rates are associated with an increased risk of AF. Potentially, underlying alterations in autonomic tone and/or subclinical sinus node dysfunction manifested as slow heart rate predispose to AF. (PACE 2015; 00:1–7) heart rate, atrial fibrillation, epidemiology
Introduction Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice and its prevalence increases with age and among those with diabetes, hypertension, prior myocardial infarction, and heart failure.1–3 The prevalence Authors Wesley T. O’Neal and Mohamed F. Almahmoud contributed equally in the writing of this manuscript. This manuscript was prepared using CHS research materials obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center and does not necessarily reflect the opinions or views of the CHS or the NHLBI. Disclosures: The authors report no disclosures or sources of funding. Address for reprints: Wesley T. O’Neal, M.D., Department of Internal Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157. Fax: 336-7162273; e-mail: [email protected] Received October 9, 2014; revised December 3, 2014; accepted January 4, 2015. doi: 10.1111/pace.12591
of AF is projected to double by the year 2050 due to a higher predilection for older adults and the expected growth in this population.1,4 With the increased burden that AF will place on the healthcare system, the identification of AF risk factors is of paramount importance to detect and treat this arrhythmia in order to prevent complications such as stroke.5,6 Among patients who are treated for hypertension, a higher incidence of AF has been observed among individuals with higher compared with lower heart rates.7 In contrast, healthy male endurance athletes who have lower heart rates have been shown to have increased rates of AF than those who have higher heart rates.8–10 Alterations in autonomic tone and/or sinus node dysfunction, which are common with aging, possibly predispose to AF. Therefore, older persons with low or high heart rates may represent a population more likely to develop AF. To our knowledge, the association between resting heart rate and incident AF has not been examined in the elderly. The purpose of this study was to
© 2015 Wiley Periodicals, Inc. PACE, Vol. 00
2015
1
O’NEAL, ET AL.
Electronics Inc., Milwaukee, WI, USA) were used at all clinic sites, and resting, 10-second standard simultaneous 12-lead electrocardiograms were recorded for all participants. All electrocardiograms were processed in a central laboratory (initially at Dalhousie University, Halifax, Canada, and later at the EPICARE Center, Wake Forest School of Medicine, Winston-Salem, NC, USA). The electrocardiograms were first processed by the Dalhousie Electrocardiogram program and were reprocessed for the present study using the 2001 version of the GE Marquette 12-SL program (GE, Milwaukee, WI, USA). The methodology and prevalence of electrocardiogram abnormalities in CHS have been described.12 Baseline CVD was determined by self-reported history and medical record adjudication of the following diagnoses: myocardial infarction, angina pectoris without myocardial infarction, coronary revascularization procedures (angioplasty and coronary artery bypass graft surgery), and stroke.13
examine the association between resting heart rate and AF in the Cardiovascular Health Study (CHS), a population-based study of older adults. Methods Study Population Details of CHS have been previously described.11 Briefly, CHS is a prospective population-based cohort study of risk factors for cardiovascular disease (CVD) in individuals 65 years and older. A total of 5,888 participants with Medicare eligibility were recruited from four field centers located in the following U.S. locations: Forsyth County, NC; Sacramento County, CA; Washington County, MD; and Pittsburgh, PA. Participants were followed with semiannual contacts alternating between telephone calls and surveillance clinic visits. CHS clinic exams ended in June of 1999 and after that time two yearly phone calls were used to identify events and collect data. The institutional review boards at each participating site approved the study and written informed consent was obtained from each participant at enrollment. For the purpose of this analysis, participants were excluded if any of the following criteria were met: prevalent AF was reported or identified on the baseline electrocardiogram, baseline covariate data were missing, or follow-up data were missing.
Atrial Fibrillation Baseline AF cases were identified during the initial study electrocardiogram or by selfreported history of a physician diagnosis. AF cases also were identified during the annual study electrocardiograms that were performed annually until 1999. Additionally, hospitalization discharge data were used to identify AF cases using International Classification of Diseases codes 427.31 and 427.32. Hospital diagnosis codes for AF ascertainment have been shown to have a positive predictive value of 98.6%.14
Covariates Participant characteristics were collected during the initial CHS interview and questionnaire. Age, sex, race, income, and education were selfreported. Annual income was dichotomized at $25,000 and education was dichotomized at “high school or less.” Smoking was defined as “current” or “ever” versus “never” smoker. Participants’ blood samples were obtained after a 12-hour fast at the local field center. Measurements of total cholesterol, high-density lipoprotein (HDL) cholesterol, plasma glucose, and high-sensitivity C-reactive protein (hs-CRP) were used in this analysis. Diabetes was defined as a self-reported history of a physician diagnosis, a fasting glucose value ࣙ126 mg/dL, or by the current use of insulin or oral hypoglycemic medications. Blood pressure was measured for each participant in the seated position and systolic measurements were used in this analysis. Resting heart rate was recorded by measuring each participants’ pulse for 60 seconds. The use of aspirin, statin, and antihypertensive and antiarrhythmic medications were self-reported. Body mass index was computed as the weight in kilograms divided by the square of the height in meters. Identical electrocardiographs (MAC PC, Marquette
2
Statistical Analysis Categorical variables were reported as frequency and percentage while continuous variables were recorded as mean ± standard deviation. Statistical significance for categorical variables was tested using the χ 2 method and the Kruskal-Wallis procedure for continuous variables. Follow-up time was defined as the time between the initial heart rate measurement until one of the following: AF, death, loss to follow-up, or end of followup (July 1, 2008). Incidence rates for AF were calculated in units of 1,000 person-years. Cox proportional hazards regression was used to compute hazard ratios (HR) and 95% confidence intervals (CI) for the association between resting heart rate and incident AF. We examined the association by clinically relevant categories of heart rate (heart rate ࣘ60 beats/min, 60< heart rate beats/min ࣘ90, and heart rate >90 beats/min). We also examined the graphical association of heart rate and AF using a restricted cubic spline model and incorporated knots at the 5th , 50th , and
2015
PACE, Vol. 00
HEART RATE AND ATRIAL FIBRILLATION
In a multivariable Cox proportional hazards analysis, heart rates ࣘ60 beats/min (HR = 1.3, 95% CI = 1.1, 1.5), but not heart rates >90 beats/min (HR = 1.1, 95% CI = 0.52, 2.3), were associated with an increased risk of AF (Table II). Also, when we examined the association of heart rates ࣘ50 beats/min, an increased risk of AF was observed (HR = 1.4, 95% CI = 1.02, 1.8), suggesting a dose-response relationship with slow heart rates and AF. To examine whether the nonsignificant result in the high resting heart rate group was due to the small number of participants in that group, we examined the association of heart rates in the third tertile compared with the middle tertile as the reference. However, a nonsignificant result also was observed (HR = 0.96, 95% CI = 0.77, 1.2). When heart rate was examined as a continuous variable, decreases in heart rate per 5 beats/min were associated with an increased risk of AF (HR = 1.06, 95% CI = 1.01, 1.1; Table II). Similar results were obtained when the analysis was stratified by age, sex, race, and CVD (Table III). A sensitivity analysis, in which participants taking antiarrhythmic agents and/or heart rate modifying-drugs at baseline were excluded, was performed and the results were similar to the main result for the entire cohort (N = 4,253; HR = 1.06, 95% CI = 1.004, 1.1).
95th percentiles.15 Additionally, the association of heart rate as a continuous variable per 5 beats/min decrease was examined after observing an increased risk for lower values compared with higher values graphically. Multivariable models were constructed as follows: Model 1 adjusted for age, sex, race, education, and income; Model 2 adjusted for Model 1 covariates plus baseline CVD, smoking, systolic blood pressure, diabetes, body mass index, total cholesterol, HDL-cholesterol, aspirin, statins, antihypertensive and antiarrhythmic medications, and log(hs-CRP). We tested for interactions between our main effect variable and age (dichotomized at 80 years), sex, and race. We also examined if a differential association between heart rate and AF existed by baseline CVD status. Several sensitivity analyses were performed. Due to the small number of participants with heart rates >90 beats/min, we examined the association of heart rate with AF in the third (heart rate >69 beats/min) versus middle tertile (60< heart rate beats/min ࣘ69). We also examined the association of resting heart rates ࣘ50 beats/min to determine if a stronger association existed for persons with extremely low heart rates. A sensitivity analysis was performed excluding participants who were taking antiarrhythmic agents (Class I, II, III, and IV) and digoxin at baseline. The proportional hazards assumption was not violated in our analysis. Statistical significance was defined as P < 0.05. SAS Version 9.3 (Cary, NC, USA) was used for all analyses.
Discussion In this analysis from CHS, lower resting heart rates were associated with an increased risk of AF. Our results were consistent across subgroups of age, sex, race, and CVD. These findings suggest that underlying alterations in autonomic tone and/or subclinical sinus node dysfunction exist in persons with low heart rates that predispose to the development of AF. Data from the Losartan Intervention for End Point Reduction in Hypertension (LIFE) study have shown that higher in-treatment heart rates on serial electrocardiograms were associated with an increased risk of new-onset AF compared with persons who have lower heart rates.7 This association conflicts with that reported from other population-based reports mainly of healthy men. For example, a longitudinal analysis of healthy middle-aged men from Norway observed that males with low exercise heart rates have a higher risk of AF.8 Similar reports from endurance athletes have shown that low resting heart rates also carry a predisposition for AF.9,10 Our results are consistent with those that have shown an increased risk of AF for persons with lower heart rates. Several differences between the current report and prior studies that have examined the association between heart rate and AF exist. Our analysis
Results Of the 5,888 participants from the original CHS cohort, 58 participants with missing followup data were excluded. Of those who remained, 313 participants with baseline AF and 291 with missing baseline covariate data also were excluded. A total of 5,226 participants (85% white; 42% male) with complete data were used in this analysis. The study sample had a mean heart rate of 65 beats/min (median = 64 beats/min, interquartile range = 58–72 beats/min). The distribution of heart rates is shown in Figure 1. Baseline characteristics stratified by heart rate categories are shown in Table I. Over a median follow-up of 12.7 years, a total of 532 (10.2%) participants developed AF. The incidence rates for AF by heart rate categories are shown in Table II. When the association of resting heart rate was examined in a restricted cubic spline model, an increased risk of AF was observed with decreasing heart rates (Fig. 2). Although not significant, an upward trend was observed for increasing heart rate values.
PACE, Vol. 00
2015
3
O’NEAL, ET AL.
Figure 1. Distribution of heart rate among study participants.
Figure 2. Risk of AF by heart rate.* *Each hazard ratio was computed with the median heart rate value of 64 beats/min as the reference. Dotted lines represent the 95% confidence interval. AF = atrial fibrillation.
was performed in a population-based cohort of older adults and was not limited to persons with hypertension or persons who were perceived to be healthy.7–10 Potentially, hypertension increases one’s sympathetic activity and subsequent risk for AF.16 However, we did not observe a significant
4
association between high heart rates and AF in this older population. Therefore, the observed association with lower heart rates and AF in the older population of CHS may be explained by an inappropriate parasympathetic response that predisposes to AF.16 Similar explanations have
2015
PACE, Vol. 00
HEART RATE AND ATRIAL FIBRILLATION
Table I. Baseline Characteristics of Study Participants (N = 5,226)
Characteristic Age, years 65–70 (%) 71–74 (%) 75–80 (%) >80 (%) Male sex (%) White (%) High school or less (%) Annual income 90 beats/min (n = 92)
844 (45) 443 (24) 425 (23) 152 (8.2) 933 (50) 1,639 (88) 990 (53) 1,083 (58) 26 (3.7) 1,038 (56) 198 (11) 139 (21) 211 (37) 54 (15) 849 (46) 74 (2.3) 629 (34) 0.75 (1.0) 446 (24)
1,372 (42) 782 (24) 763 (23) 353 (11) 1,242 (38) 2,731 (84) 1,943 (59) 2,178 (67) 27 (4.2) 1,705 (52) 589 (18) 140 (20) 213 (40) 55 (16) 1,503 (46) 36 (1.9) 1,074 (33) 1.0 (1.0) 666 (20)
36 (39) 22 (24) 23 (25) 11 (12) 32 (35) 64 (70) 65 (71) 75 (82) 28 (5.1) 52 (57) 34 (37) 142 (21) 210 (46) 54 (17) 45 (49) 3 (3.3) 33 (36) 1.7 (1.3) 25 (27)
P Value*
0.052
