Editorial
Exercise, Heart Rate Variability, and Longevity
The Cocoon Mystery?
Paul Poirier, MD, PhD, FRCPC
H
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umans are increasingly approaching an era where cardiovascular health seems to be one of the major upper
limits on achievable life span. An increasing body of scientific
research and observational evidence indicates that resting heart
rate (HR) is inversely related to the life span among homeothermic mammals and within individual species. HR not only
reflects the status of the cardiovascular system but also serves
as an indicator of cardiac autonomic nervous (sympathetic and
parasympathetic) system activity and metabolic rate. There is
a remarkable amount of variation in HR among species; it can
be as low as 30 to 35 beats per minute (bpm) in large animals like whales and elephants or as high as 600 to 700 bpm
in mice (Figure 1). Mammals that have a slower average HR
tend to live much longer than those that have a faster HR.1,2
Although some variability inevitably exists and is observed in
humans, estimations yield a mean value of ≈1 × 109 (1 billion)
heartbeats in a lifetime across almost all homeothermic mammals (Figure 2).
Thus, the parasympathetic influences will generate more rapid
changes in the beat-to-beat regulation of the heart. There is
extensive literature documenting a number of determinants of
autonomic tone.6,7 Human HR is not regular and varies in time,
and such variability, also known as HRV, is not representing
background noise or a random phenomenon.8 These variations
are thought to be the result of complex interactions between
extrinsic environmental and behavioral factors and intrinsic
cardiovascular regulatory mechanisms (neural central, neural reflex, and humoral influences) that are not yet completely
understood.9 Nevertheless, HRV is a surrogate index of cardiac
autonomic nerve function and a marker of imbalanced sympathetic/vagal activities (sympathetic tone enhancement or vagal
tone depression). HRV also independently predicts cardiovascular disease mortality not only in patients with coronary artery
disease or chronic heart failure but also in apparently healthy
populations.10–12 Many different HRV measures exist. Most
clinicians are unfamiliar with HRV indices, and the nonelectrophysiologists are invited to look at Table 1 of the article of
Soares-Miranda et al13 for a better description of HRV indices.
Succinctly, using linear algorithms, HRV is usually clinically
analyzed in the time or frequency domain. Time domain indices
are the first to be used and the simplest way to calculate HRV.
They are mathematical calculations of consecutive RR intervals,
and they correlate with each other (standard deviation of NN
intervals, measure of changes in heart rate attributed to cycles
>5 minutes, the proportion of interval differences of successive
NN intervals greater than 50 ms, etc). Frequency domain indices are more elaborated and based on spectral analysis, mostly
used to evaluate the autonomic nervous system contribution to
HRV (very low frequency [LF], LF, high frequency [HF], and
HF/LF ratio). Spectral analysis of HR signals provides their
power spectrum density and displays in a plot the relative contribution (amplitude) of each frequency after application of a
Fast Fourier transformation to the raw signal. The area under
the power spectral curve in a particular frequency band (power)
is considered to be a measure of HRV at that frequency.14–16
Spectral analysis can be used to analyze the sequence of RR
intervals of short-term recordings (2–5 minutes) or an entire
24-hour period (Holter monitoring).14 Hence, HRV indices represent the final outcome of complex systems. Ultra LF power
correlates with standard deviation of NN intervals and measure
of changes in heart rate attributed to cycles >5 minutes index,
very LF power and LF power with standard deviation of NN
intervals index, and HF power with root mean square of the
successive differences and the proportion of interval differences
of successive NN intervals greater than 50 ms.17
Soares-Miranda et al13 evaluated cross-sectionally and
longitudinally measures of both physical activity (PA) and
24-hour Holter HRV over 5 years among 985 older US adults
Article see p 2100
Regularly engaging in moderate-to-vigorous physical activity has been shown to reduce the risk of all-cause mortality,
cardiovascular mortality, cancer mortality, stroke, heart disease, breast cancer, and colon cancer, as well as numerous
other undesirable health outcomes.3 Endurance physical exercise can reduce HR and promote the overall health profile. It is
well known that endurance athletes tend to have higher parasympathetic tone and lower resting HR than the general public. Although exercise itself elevates HR significantly, resting
HR is significantly reduced, and overall total heartbeats over
24 hours are reduced as well. There is also a powerful association between functional capacity and cardiovascular risk.4,5
Autonomic nervous system function is assessed clinically
by measuring resting HR, HR variability (HRV), or HR recovery after exercise. HRV is modulated by many physiologic or
pathologic states. Adjustments from the sympathetic modulations are slow, on the time scale of seconds, whereas those from
the parasympathetic are fast, on the time scale of milliseconds.
The opinions expressed in this article are not necessarily those of the
editors or of the American Heart Association.
From the Institut Universitaire de Cardiologie et de Pneumologie
de Québec and Faculté de Pharmacie, Université Laval, Québec City,
Québec, Canada.
Correspondence to Paul Poirier, MD, PhD, FRCPC, Faculté de
Pharmacie, Institut Universitaire de Cardiologie et de Pneumologie de
Québec, 2725 Chemin Ste-Foy, Sainte-Foy, Québec, G1V 4G5, Canada.
E-mail [email protected]
(Circulation. 2014;129:2085-2087.)
© 2014 American Heart Association, Inc.
Circulation is available at http://circ.ahajournals.org
DOI: 10.1161/CIRCULATIONAHA.114.009778
2085
2086 Circulation May 27, 2014
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Figure 1. Semilogarithmic relation between resting heart rate and
life expectancy in 15 mammal species. Excluding humans, heart
rate (HR) is inversely correlated with life span. Adapted from
Levine1 with permission of the publisher.
in the community-based Cardiovascular Health Study. They
reported that greater total leisure time activity, as well as
walking alone, were prospectively associated with healthier
cardiac autonomic function (assessed with HRV). Greater
total leisure time activity, walking distance, and walking pace
were each prospectively associated with specific, more favorable HRV indices, and over 5 years, those who increased their
walking pace or walking distance had more favorable HRV
indices when compared with those who decreased their walking pace or walking distance. The authors evaluated PA in prespecified categories, including leisure time activity (quintiles),
exercise intensity (none/low or medium/high), blocks walked
(quintiles), and usual pace walked (<2 or ≥2 mph). Usual
Figure 2. Relation between life expectancy and total heartbeats
over a lifetime of 15 mammal species. Data fall in a relatively narrow range, ≈1 billion beats. Adapted from Levine1 with permission of the publisher.
leisure time activity was assessed at baseline (1989–1990)
and at 1992–1993 using a modified Minnesota L
­ eisure-Time
Activities questionnaire. As pointed out by the authors,
the modified Minnesota PA questionnaire has been validated against the full version. Although it is recognized that
­self-reported measures of PA may be susceptible to bias, measures of PA may be sufficient for ranking individuals within
an epidemiologic data set for analysis.18 Strength of the study
is the use of 24-hour measurements that assess both ­short-term
and long-term HRV indices, where short-term ECGs, which
have been reported in numerous other epidemiologic studies,
assess only short-term HRV indices. Surprisingly, PA variables were not significantly associated with other HRV indices, including root mean square of the successive differences,
LF, HF, LF/HF ratio, or very LF power, whereas faster walking
pace was associated with higher nighttime LF/HF ratio only.
It is important to emphasize that root mean square of the successive differences, LF, HF, and LF/HF ratio were evaluated
among individuals (n=493) with lower erratic HRV. Lower
statistical power attributed to the smaller numbers of subjects may explain the lack of statistical association, because
regular PA is generally associated with more favorable HRV
indices, especially those reflecting increased vagal modulation and reduced sympathetic activity. On the other hand,
the participants in the highest quintile of changes in walking
distance had significantly higher ULF power compared with
the lowest quintile. Similarly, those who increased walking
pace had significantly higher HRV indices when compared
with those who decreased or maintained their walking pace.
Although the biological interpretation of some indices is complex, the meaning of ULF is uncertain. Mean daytime HR was
78±10 bpm, ranging from 71 to 85 bpm. One may assume that
these older participants were not very physically active during daytime, especially with the use of only 13% β-blocker
in the population studied. One must remember that intrinsic
(denervated heart) HR is higher than the normal resting HR,
because the heart is under tonic inhibitory control by parasympathetic influences. Indeed, the intrinsic HR of healthy
individuals, as reflected by the HR observed during complete
autonomic blockade, is ≈100 bpm. With advancing age, the
intrinsic rate decreases, particularly in the latter decades of
life. More detailed studies have investigated the pattern of loss
of autonomic function during aging and have demonstrated
that HRV parasympathetic activity decreases faster until the
age of 80 years and then starts to increase again.19 Even if a
range of covariates were available and evaluated as potential
confounders (body mass index, systolic blood pressure, use
of β-blockers, calcium channel blockers, or digitalis, as well
as presence or absence of coronary heart disease, congestive
heart failure, hypertension, diabetes mellitus, or left ventricular hypertrophy) and findings were similar in several sensitivity analyses, residual confounders attributed to unknown
or incompletely measured factors cannot be excluded. Body
mass index is certainly not a good reflection of adiposity and
fat distribution in an older population.20 Indeed, body fat distribution, independent of body mass index, may modulate
HRV.21,22 This may be of clinical importance, because sarcopenic obesity and physical disability are encountered in the aging
older population and are characterized by decreased muscle
Poirier Heart Rate Variability and Exercise 2087
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mass and increased fat mass, particularly visceral fat. Also,
the rate of patients with diabetes mellitus was low (15%). This
is important because abnormal HRV has been associated with
the severity of left ventricular diastolic dysfunction,23 which
has been associated with lower exercise capacity in subjects
with well-controlled type 2 diabetes mellitus.24
The study of Soares-Miranda et al13 is an interesting prospective valuable study and shows the independent link
between PA and preserved autonomic function in older
patients. Although several studies have reported on the clinical and prognostic values of HRV analysis in the assessment
of patients with cardiovascular diseases, this technique has
not been incorporated into clinical practice. To welcome
HRV analysis as part of the cardiovascular risk assessment,
prospective, randomized studies focusing on the clinical use
of HRV as a cardiovascular risk marker in primary or secondary prevention or as a tool to assess treatment efficacy are
required.25 Meanwhile, the findings of Soares-Miranda et al13
may be used for knowledge transfer to older people to reinforce the positive impact of habitual PA later in life.
Disclosures
None.
References
1.Levine HJ. Rest heart rate and life expectancy. J Am Coll Cardiol.
1997;30:1104–1106.
2. Dawson TH. Similitude in the cardiovascular system of mammals. J Exp
Biol. 2001;204(pt 3):395–407.
3.U.S. Department of Health and Human Services. Physical Activity
Guidelines for Americans: Be Active, Healthy and Happy. Washington,
DC: US Department of Health and Human Services; 2008.
4.Myers J, Prakash M, Froelicher V, Do D, Partington S, Atwood JE.
Exercise capacity and mortality among men referred for exercise testing.
N Engl J Med. 2002;346:793–801.
5.Gulati M, Black HR, Shaw LJ, Arnsdorf MF, Merz CN, Lauer MS,
Marwick TH, Pandey DK, Wicklund RH, Thisted RA. The prognostic
value of a nomogram for exercise capacity in women. N Engl J Med.
2005;353:468–475.
6. Curtis BM, O’Keefe JH Jr. Autonomic tone as a cardiovascular risk factor:
the dangers of chronic fight or flight. Mayo Clin Proc. 2002;77:45–54.
7. Thayer JF, Lane RD. The role of vagal function in the risk for cardiovascular disease and mortality. Biol Psychol. 2007;74:224–242.
8. Jarrin DC, McGrath JJ, Giovanniello S, Poirier P, Lambert M. Measurement
fidelity of heart rate variability signal processing: the devil is in the details.
Int J Psychophysiol. 2012;86:88–97.
9. Valera B, Dewailly E, Poirier P. Impact of mercury exposure on blood
pressure and cardiac autonomic activity among Cree adults (James Bay,
Quebec, Canada). Environ Res. 2011;111:1265–1270.
10. Kleiger RE, Stein PK, Bigger JT Jr. Heart rate variability: measurement
and clinical utility. Ann Noninvasive Electrocardiol. 2005;10:88–101.
11.Dekker JM, Crow RS, Folsom AR, Hannan PJ, Liao D, Swenne CA,
Schouten EG. Low heart rate variability in a 2-minute rhythm strip predicts risk of coronary heart disease and mortality from several causes:
the ARIC Study--Atherosclerosis Risk in Communities. Circulation.
2000;102:1239–1244.
12.Galinier M, Pathak A, Fourcade J, Androdias C, Curnier D, Varnous
S, Boveda S, Massabuau P, Fauvel M, Senard JM, Bounhoure JP.
Depressed low frequency power of heart rate variability as an independent predictor of sudden death in chronic heart failure. Eur Heart J.
2000;21:475–482.
13. Soares-Miranda L, Sattelmair J, Chaves P, Duncan GE, Siscovick DS, Stein
PK, Mozaffarian D. Physical activity and heart rate variability in older
adults: the Cardiovascular Health Study. Circulation. 2014;129:2100–2110.
14. Task Force of the European Society of Cardiology and the North American
Society of Pacing and Electrophysiology. Heart rate variability: standards
of measurement, physiological interpretation and clinical use. Circulation.
1996;93:1043–1065.
15. Akselrod S, Gordon D, Ubel FA, Shannon DC, Berger AC, Cohen RJ.
Power spectrum analysis of heart rate fluctuation: a quantitative probe of
beat-to-beat cardiovascular control. Science. 1981;213:220–222.
16. Malik M, Camm AJ. Components of heart rate variability–what they really
mean and what we really measure. Am J Cardiol. 1993;72:821–822.
17.Bigger JT Jr, Fleiss JL, Steinman RC, Rolnitzky LM, Kleiger RE,
Rottman JN. Correlations among time and frequency domain measures of
heart period variability two weeks after acute myocardial infarction. Am J
Cardiol. 1992;69:891–898.
18. Atkin AJ, Gorely T, Clemes SA, Yates T, Edwardson C, Brage S, Salmon
J, Marshall SJ, Biddle SJ. Methods of measurement in epidemiology: sedentary behaviour. Int J Epidemiol. 2012;41:1460–1471.
19. Reardon M, Malik M. Changes in heart rate variability with age. Pacing
Clin Electrophysiol. 1996;19(11 pt 2):1863–1866.
20. Cornier MA, Després JP, Davis N, Grossniklaus DA, Klein S, Lamarche
B, Lopez-Jimenez F, Rao G, St-Onge MP, Towfighi A, Poirier P;
American Heart Association Obesity Committee of the Council on
Nutrition; Physical Activity and Metabolism; Council on Arteriosclerosis;
Thrombosis and Vascular Biology; Council on Cardiovascular Disease
in the Young; Council on Cardiovascular Radiology and Intervention;
Council on Cardiovascular Nursing, Council on Epidemiology and
Prevention; Council on the Kidney in Cardiovascular Disease, and Stroke
Council. Assessing adiposity: a scientific statement from the American
Heart Association. Circulation. 2011;124:1996–2019.
21. Poliakova N, Després JP, Bergeron J, Alméras N, Tremblay A, Poirier
P. Influence of obesity indices, metabolic parameters and age on cardiac autonomic function in abdominally obese men. Metabolism.
2012;61:1270–1279.
22. Salamin G, Pelletier C, Poirier P, Després JP, Bertrand O, Alméras N,
Costerousse O, Brassard P. Impact of visceral obesity on cardiac parasympathetic activity in type 2 diabetics after coronary artery bypass graft
surgery. Obesity (Silver Spring). 2013;21:1578–1585.
23.Poirier P, Bogaty P, Philippon F, Garneau C, Fortin C, Dumesnil JG.
Preclinical diabetic cardiomyopathy: relation of left ventricular diastolic
dysfunction to cardiac autonomic neuropathy in men with uncomplicated
well-controlled type 2 diabetes. Metabolism. 2003;52:1056–1061.
24. Poirier P, Garneau C, Bogaty P, Nadeau A, Marois L, Brochu C, Gingras
C, Fortin C, Jobin J, Dumesnil JG. Impact of left ventricular diastolic dysfunction on maximal treadmill performance in normotensive subjects with
well-controlled type 2 diabetes mellitus. Am J Cardiol. 2000;85:473–477.
25. Goldberger JJ, Cain ME, Hohnloser SH, Kadish AH, Knight BP, Lauer
MS, Maron BJ, Page RL, Passman RS, Siscovick D, Siscovick D,
Stevenson WG, Zipes DP. American Heart Association/American College
of Cardiology Foundation/Heart Rhythm Society scientific statement
on noninvasive risk stratification techniques for identifying patients at
risk for sudden cardiac death: a scientific statement from the American
Heart Association Council on Clinical Cardiology Committee on
Electrocardiography and Arrhythmias and Council on Epidemiology and
Prevention. Circulation. 2008;118:1497–1518.
Key Words: Editorials ◼ aging ◼ exercise ◼ heart rate ◼ obesity
Exercise, Heart Rate Variability, and Longevity: The Cocoon Mystery?
Paul Poirier
Circulation. 2014;129:2085-2087; originally published online May 5, 2014;
doi: 10.1161/CIRCULATIONAHA.114.009778
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