Heart rate variability (HRV) refers to the beat-to-beat
alterations in heart rate. Under resting conditions, the ECG of healthy individuals
exhibits periodic variation in R-R intervals. This rhythmic phenomenon, known as
respiratory sinus arrhythmia (RSA), fluctuates with the phase of respiration --
cardio-acceleration during inspiration, and cardio-deceleration during expiration. RSA is
predominantly mediated by respiratory gating of parasymphathetic efferent activity to the
heart: vagal efferent traffic to the sinus node occurs primarily in phase with expiration
and is absent or attenuated during inspiration. Atropine abolishes RSA.
Reduced HRV has thus been used as a marker of reduced vagal activity. However, because
HRV is a cardiac measure derived from the ECG, it is not possible to distinguish reduced central
vagal activity (in the vagal centers of the brain) from reduced peripheral activity (the
contribution of the target organ -- the sinus node -- or the afferent/efferent pathways
conducting the neural impulses to/from the brain).
What aspect of allostasis does HRV potentially measure?
Although our understanding of the meaning of HRV is far from complete, it seems to be a
marker of both dynamic and cumulative load. As a dynamic marker of load, HRV
appears to be sensitive and responsive to acute stress. Under laboratory conditions,
mental load -- including making complex decisions, and public speech tasks -- have been
shown to lower HRV. As a marker of cumulative wear and tear, HRV has also been
shown to decline with the aging process. Although resting heart rate does not change
significantly with advancing age, there is a decline in HRV, which has been attributed to
a decrease in efferent vagal tone and reduced beta-adrenergic responsiveness. By contrast,
regular physical activity (which slows down the aging process) has been shown to raise
HRV, presumably by increasing vagal tone.
In short, HRV appears to be a marker of two processes, relevant to the
conceptualization of allostatic load: (1) frequent activation (short term dips in
HRV in response to acute stress); and (b) inadequate response (long-term vagal
withdrawal, resulting in the over-activity of the counter-regulatory system -- in this
case, the sympathetic control of cardiac rhythm).
How is HRV measured?
Originally, HRV was assessed manually from calculation of the mean R-R interval and its
standard deviation measured on short-term (e.g., 5 minute) electrocardiograms. The smaller
the standard deviation in R-R intervals, the lower is the HRV. To date, over 26 different
types of arithmetic manipulations of R-R intervals have been used in the literature to
represent HRV. Examples include: the standard deviations of the normal mean R-R interval
obtained from successive 5-minute periods over 24-hour Holter recordings (called the SDANN
index); the number of instances per hour in which two consecutive R-R intervals differ by
more than 50 msec over 24-hours (called the pNN50 index); the root-mean square of the
difference of successive R-R intervals (the rMSSD index); the difference between the
shortest R-R interval during inspiration and the longest during expiration (called the
MAX-MIN, or peak-valley quantification of HRV); and the base of the triangular area under
the main peak of the R-R interval frequency distribution diagram obtained from 24-hour
recording; and so on. So far, experimental and simulation data appear to indicate that the
various methods of expressing HRV are largely equivalent, and there is no evidence that
any one method is superior to another, provided measurement windows are 5 minutes or
longer.

The approach uses Fourier transforms. The HRV spectrum
contains two major components: the high frequency (0.18-0.4 Hz) component, which is
synchronous with respiration and is identical to RSA. The second is a low frequency (0.04
to 0.15 Hz) component that appears to be mediated by both the vagus and cardiac
sympathetic nerves. The power of spectral components is the area below the relevant
frequencies presented in absolute units (square milliseconds). The total power of a
signal, integrated over all frequencies, is equal to the variance of the entire signal.
Some investigators have used the ratio of the low-to-high frequency spectra as an index of
parasympathetic-sympathetic balance; however, this remains controversial because of our
lack of complete understanding of the low frequency component (which seems to be affected
by centrally generated brainstem rhythms, baroreceptor feedback influences, as well as
both sympathetic and vagal input).
As a measure of vagal activity, spectral analysis of the high-frequency component
probably offers no additional information over time-domain measures of RSA. On the other
hand, the meaning and utility of the low frequency component deserves further
investigation.
In sum, the analysis of HRV (whether by time-domain or spectral approaches) offers a
non-invasive method of evaluating vagal input into cardiac rhythm. The measurement of HRV
is becoming increasingly standardized (e.g., see report of the Task Force of the European
Society of Cardiology, 1996). Although, the assessment of HRV requires electrophysiologic
expertise, the equipment is not prohibitively expensive, requiring only ECG equipment,
microprocessors, and relevant software for carrying out Fourier analyses.
Does HRV predict disease?
The major reason for the interest in measuring HRV stems from its ability to predict
survival after heart attack. Over half a dozen prospective studies have shown that reduced
HRV predicts sudden death in patients with MI, independent of other prognostic indicators
such as ejection fraction. Reduced HRV appears to be a marker of fatal ventricular
arrhythmia. Moreover, a small number of studies have begun to suggest that reduced HRV may
predict risk of survival even among individuals free of CHD.
Does HRV vary with psychosocial factors?
Several studies have now suggested a link between negative emotions (such as anxiety
and hostility) and reduced HRV. Kawachi et al (1995) reported a cross-sectional
association between anxiety and reduced HRV (as assessed by two time-domain measures) in
581 men. Offerhaus (1980) observed lower HRV in individuals who were "highly
anxious" according to the Minnesota Multiphasic Personality Inventory. Yeragani et
al. (e.g., 1990; 1993) have published a series of reports indicating reduced HRV (using
both time domain and spectral measures) among DSM-III diagnosed panic disorder patients.
In turn, at least three prospective epidemiologic studies (Haines et al, 1987; Kawachi et
al, 1994a; Kawachi et al, 1994b), and one case-crossover study (Mittleman et al, 1995)
have suggested a relationship between high levels of anxiety and risk of CHD.
Sloan et al (1994) reported reduced high-frequency power among 33 healthy volunteers
who scored high on the Cooke-Medley Hostility scale. The association between negative
affect and reduced HRV may thus provide a potential mechanism linking chronic stress to
disease outcomes (e.g., risk of CHD).
Further Readings
Grossman P. Respiratory and cardiac rhythms as windows to central and autonomic
biobehavioral regulation: Selection of window frames, keeping the panes clean and viewing
neural topography. Biological Psychology 1992; 34: 131-161.
Haines AP, Imeson JD, Meade TW. Phobic anxiety and ischaemic heart disease. Br Med J
1987; 295: 297-299.
Kawachi I, Colditz GA, Ascherio A, Rimm EB, Giovannucci E, Stampfer MJ, Willett WC.
Prospective study of phobic anxiety and risk of coronary heart disease. Circulation 1994a;
89: 1992-1997.
Kawachi I, Sparrow D. Vokonas PS, Weiss ST. Symptoms of anxiety and risk of coronary
heart disease: The Normative Aging Study. Circulation 1994b; 90: 2225-2229.
Kawachi I, Sparrow D, Vokonas PS, Weiss ST. Decreased heart rate variability in men
with phobic anxiety. Am J Cardiol 1995; 75: 882-885.
Kristal-Boneh E, Raifel M, Froom P, Ribak J. Heart rate variability in health and
disease. Scan J Work Environ Health 1995; 21: 85-95.
Mittleman MA, Maclure M, Sherwood JB, Mulry RP, Tofler GH, Jacobs SC, Friedman R,
Benson H, Muller JE. Triggering of acute myocardial infarction onset by episodes of anger.
Circulation 1995; 92: 1720-1725.
Offerhaus RE. Heart rate variability in psychiatry. In: RJ Kitney, Rompelman O (eds). The
Study of Heart Rate Variability. Oxford: Oxford University Press, 1980: 225-238.
Sloan RP, Shapiro PA, Bigger T Jr, Bagiella E, Steinman RC, Gorman JM. Cardiac
autonomic control and hostility in healthy subjects. Am J Cardiol 1994; 74:
298-300.
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: 1043-65.
Yeragani VK, Balon R, Pohl R, Ramesh C, Glitz D, Weinberg P, Merlos B. Decreased R-R
variance in panic disorder patients. Acta Psychiatr Scand 1990; 81: 554-559.
Yeragani VK, Pohl R, Berger R, Balon R, Ramesh C, Glitz D, Srinivasan K, Weinberg P.
Decreased heart rate variability in panic disorder patients: a study of power-spectral
analysis of heart rate. Psychiatry Res 1993; 46: 89-103.