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A Quantitative Systematic Review of Normal Values for Short-Term Heart Rate Variability in Healthy Adults

Authors:

Abstract

Heart rate variability (HRV) is a known risk factor for mortality in both healthy and patient populations. There are currently no normative data for short-term measures of HRV. A thorough review of short-term HRV data published since 1996 was therefore performed. Data from studies published after the 1996 Task Force report (i.e., between January 1997 and September 2008) and reporting short-term measures of HRV obtained in normally healthy individuals were collated and factors underlying discrepant values were identified. Forty-four studies met the pre-set inclusion criteria involving 21,438 participants. Values for short-term HRV measures from the literature were lower than Task Force norms. A degree of homogeneity for common measures of HRV in healthy adults was shown across studies. A number of studies demonstrate large interindividual variations (up to 260,000%), particularly for spectral measures. A number of methodological discrepancies underlined disparate values. These include a systematic failure within the literature (a) to recognize the importance of RR data recognition/editing procedures and (b) to question disparate HRV values observed in normally healthy individuals. A need for large-scale population studies and a review of the Task Force recommendations for short-term HRV that covers the full-age spectrum were identified. Data presented should be used to quantify reference ranges for short-term measures of HRV in healthy adult populations but should be undertaken with reference to methodological factors underlying disparate values. Recommendations for the measurement of HRV require updating to include current technologies.
A Quantitative Systematic Review of Normal Values for
Short-Term Heart Rate Variability in Healthy Adults
DAVID NUNAN, PH.D.,*,‡ GAVIN R. H. SANDERCOCK, PH.D.,† and DAVID A. BRODIE, PH.D.‡
From the *Division of Public Health and Primary Health Care, University of Oxford, Oxford, UK; †Centre for Sports
and Exercise Science, University of Essex, Colchester, UK; and ‡Research Centre for Society and Health,
Buckinghamshire New University, Chalfont St Giles, UK
Heart rate variability (HRV) is a known risk factor for mortality in both healthy and patient populations.
There are currently no normative data for short-term measures of HRV. A thorough review of short-term
HRV data published since 1996 was therefore performed. Data from studies published after the 1996
Task Force report (i.e., between January 1997 and September 2008) and reporting short-term measures
of HRV obtained in normally healthy individuals were collated and factors underlying discrepant values
were identified. Forty-four studies met the pre-set inclusion criteria involving 21,438 participants. Values
for short-term HRV measures from the literature were lower than Task Force norms. A degree of
homogeneity for common measures of HRV in healthy adults was shown across studies. A number of
studies demonstrate large interindividual variations (up to 260,000%), particularly for spectral measures.
A number of methodological discrepancies underlined disparate values. These include a systematic
failure within the literature (a) to recognize the importance of RR data recognition/editing procedures
and (b) to question disparate HRV values observed in normally healthy individuals. A need for large-
scale population studies and a review of the Task Force recommendations for short-term HRV that
covers the full-age spectrum were identified. Data presented should be used to quantify reference ranges
for short-term measures of HRV in healthy adult populations but should be undertaken with reference
to methodological factors underlying disparate values. Recommendations for the measurement of HRV
require updating to include current technologies. (PACE 2010; 33:1407–1417)
autonomic nervous system,risk factors,norms,homogeneity,populations
Introduction
In 1996, the European Society for Cardiology
and the North American Society of Pacing and
Electrophysiology supported a Task Force which
issued a seminal paper: “Heart rate variability:
Standards of measurement, physiological inter-
pretation and clinical use” (Circulation, 1996; 93,
1043–1065). Reference normal values for short-
term measures of heart rate variability (HRV) in
healthy adults were published as an appendix
to the paper. Some of these values, however,
were approximated from studies involving small
sample sizes. As a result, these data are considered
as “unsuitable for definite clinical conclusions to
be drawn from.”1The Task Force stressed the
need for large prospective population studies to
Disclosures: The authors have no conflicts of interest to
disclose.
Address for reprints: David Nunan, Ph.D., MaDOx Group, Uni-
versity of Oxford, Rosemary Rue Building, Old Road Campus,
Roosevelt Drive, Headington, Oxford, United Kingdom. Fax:
441865-289287; e-mail: david.nunan@dphpc.ox.ac.uk
Received February 26, 2010; revised May 17, 2010; accepted
June 9, 2010.
doi: 10.1111/j.1540-8159.2010.02841.x
establish normal HRV standards including age and
sex subsets. This need was considered greatest for
HRV values obtained from short-term recordings.
The interest in HRV as a measurement of
autonomic function lies in its clinical importance.
A reduced HRV is a powerful and independent
predictor of an adverse prognosis in patients with
heart disease2–4 and in the general population.5,6
Despite the important prognostic power of HRV, it
is still not a widely used tool in clinical settings.
Key issues relating to this fact include the most
appropriate analysis method(s), the recommended
length of electrocardiogram recordings, and the
conditions in which they should be assessed.7
Arguably an additional key factor is the lack of
agreed normative values for HRV, without which
classifying “abnormal” HRV remains difficult.
In the majority of other clinically health-related
measures (e.g., blood pressure, heart rate, forced
vital capacity), established norms are routinely
compared to provide an indication of current
health status. There is no clear explanation why
this is not the case for HRV.
Since 1996, publications assessing and re-
porting both 24-hour and short-term HRV in
healthy and clinical populations have increased.
Pinna and colleagues8report an increase in the
C
2010, The Authors. Journal compilation C
2010 Wiley Periodicals, Inc.
PACE, Vol. 33 November 2010 1407
NUNAN, ET AL.
number of yearly publications from 391 to 584
in the period 2000 to 2006, respectively. Taylor
and Studinger9reported an average of 10 articles
related to HRV published weekly during 2005.
These “newer” studies provide a potential source
of normative data for common HRV measures
in healthy populations. Moreover, by comparing
values between publications, it may be possible
to identify factors contributing to discrepancies in
HRV values.
Methods
Search Strategy
The PubMed and Ovid databases were
searched using the mesh term “heart rate variabil-
ity” and: “short” “term” “short-term” and “five.” A
second search using 13 terms in conjunction with
the previous search terms was then performed.
Full text articles were then obtained and their
bibliographies searched for further studies not
identified electronically. The full set of search
strategy terms are illustrated in Figure 1.
Selection Criteria and Review Process
Only English language publications involving
healthy adults of at least 18 years were included.
As this study was only interested in short-term
HRV, publications reporting 24-hour measures
of HRV were excluded. A sample size greater
than 50 was originally an inclusion criterion but
was later lowered to 30. The requirement for all
publications to present the mean RR interval was
also an original criterion later revoked. These
two actions were performed as only 22 papers
were eligible for inclusion when the original
criteria were applied. Publications were rejected
if they presented HRV values other than in Task
Force-recommended formats (i.e., absolute, log-
transformed, or back-transformed units).
Data Analysis and Synthesis
The nature of the data (i.e., analysis of group
means) does not support inferential analysis.
Descriptive statistics are presented including:
mean, standard deviation (SD), median, and range.
Measures such as the coefficient of variation
(CV =SD/mean ×100) provide an index of
the dispersion of mean values between studies.
To identify factors underlying between-study
differences, values for measures equating to
greater than 1.5 SD from the mean publication
value were considered discrepant. A value of
1.5 SD was chosen to provide a more conservative
reference range for consideration of discrepant
values. Assessment of possible factors underlying
discrepant values was then made on a study-by-
study and measure-by-measure basis. Percentage
differences were used to assess between-group
differences based on sex, spectral decomposition
technique, and the use of paced versus free
breathing protocols.
Data are presented for time and frequency
measures of HRV most commonly reported within
the literature. Measures of HRV often demonstrate
skewed distributions and are reported as natural
logarithms. Absolute and log-transformed units
are presented for the following measures:
1. Standard deviation of normal-to-normal
(NN) intervals (SDNN);
2. Root mean square of successive differences
between NN intervals (rMSSD);
3. Proportion of successive NN intervals
greater than 50 ms (pNN50%);
4. Very low-frequency spectral power (VLF);
and
5. Total spectral power (TP), low-frequency
power (LF), and high-frequency power (HF) in
both ms2and normalized units and the ratio of
LF power to HF power (LF:HF).
Measures of TP and VLF from short RR
recordings are physiologically ambiguous and for
this reason their use is not recommended by
the Task Force.1The Task Force also prefers the
use of rMSSD to pNN50 due to its mathematical
robustness. Data from studies reporting TP, VLF,
and pNN50 were included in the initial review
stages but were not entered into the final analysis
of means. These measures were included to
allow the reviewer a complete assessment of the
discrepancy between studies in adherence to the
Task Force recommendations.
Results
Database searches retrieved a total of 3,141
citations (Fig. 1). Shortlisted citations were
retrieved and checked at the title/abstract level
excluding 2,765 papers. Complete articles for the
remaining 376 studies were checked for com-
pliance to inclusion/exclusion criteria. Reasons
for exclusion included measurement of longer-
term HRV (e.g., 24 hours), a sample size <30,
assessment of nonhealthy participants, failure to
present values for, or to measure, traditional time-
and/or frequency-domain HRV, or the paper was
a review article. Therefore, only 44 (12%) eligible
trials were identified. The total sample size from
these 44 papers was 21,438 participants.
Data from the present study are presented as
follows:
Table SI—Participant demographics and
details of the methodologies employed for all
publications that met the inclusion criteria;
1408 November 2010 PACE,Vol.33
REVIEW OF SHORT-TERM HRV VALUES
1. ‘Heart rate variability’ –
limited to human studies
involving adults aged 18+
published in English from
Jan ’97 – Sept ’08
2. ‘Short,’ ‘Term,’
‘Short-term’
3. ‘Five’
4. ‘Normal’
5. ‘Healthy’
6. ‘Control’
7. ‘Sedentary’
8. ‘Population’
9. ‘Heritability’
10. ‘Genetic’
11. ‘Ethnic’
12. ‘Environment’
13. ‘Longitudinal’
14. ‘Athlete’
15. ‘Tr ained’
16. ‘Untrained’
3141 citations with ‘heart
rate variability’ in title or
abstract
376 Potentially
relevant citations
2765 Citations excluded
because of irrelevance to
the systematic review
44 Citations finally
included in
systematic review
332 Citations excluded due
to:
90 long-term HRV measured
134 sample size <30
78 unhealthy participants
29 non-traditional measures
1 review article
Phase 1 Phase 2 Phase 3
Figure 1. Schematic of search “strings” added to the PubMed and Ovid databases for retrieval of
citations assessing short-term measures of HRV in healthy adults. Also indicated are the inclusion
and exclusion processes.
Table SII—Values for the HRV measures
corresponding to each study in Table SI;
Table I—Summary data including the
overall mean, SD, CV, and range in values for each
of the HRV measures in Table SII;
Table II—Summates data in Table SII based
on sex;
Table III—Summates data in Table SII
based on breathing protocol and spectral method;
Table IV—Summates data from studies
displaying interindividual range in a number of
HRV measures.
Data from Rajendra Acharya et al.10 listed in
Table SI are not included in Table SII. This study
only presented the range in values for measures of
HRV without providing a mean value. These data
are included in Table IV.
Analysis of Short-Term HRV Data
from the Literature
Descriptive statistics for data from all the in-
cluded studies are presented in Table I. There was
a large range in values between studies. Compared
with frequency-domain measures, time-domain
measures of HRV demonstrated less variation be-
tween studies. For measures reported in absolute
units, the largest variation was observed for HF
(CV =118%) with a range in values across studies
of 3,548 ms2. Mean RR interval demonstrated the
smallest variation (CV =10%; range =375 ms).
In log-transformed units, HF again demonstrated
the largest variation between studies (CV =37%,
range =6.87 ln units). The SDNN demonstrated
the smallest variation (CV =6%, range 0.50 ln
units).
Compared with males, females demonstrated
slightly lower values (8–11%) for all time-domain
measures of HRV expressed in absolute units
(Table II). In the frequency domain, males demon-
strated lower values for LF (14%) and HF (8%)
power. Males showed substantially higher values
for LFnu (17%) but HFnu was similar between
sexes. Values for LF (20%) and HF (18%) were
substantially lower in females when expressed
in log units. Females also demonstrated a lower
LF:HF ratio regardless of the unit of expression.
PACE,Vol.33 November 2010 1409
NUNAN, ET AL.
Tab le I .
Summary of Data from Table SII: Cross Study Overall Mean and Range in Values for Approved Task Force Measures of
Short-Term HRV
Absolute Values Log-Transformed Values
HRV No. of CV No. of CV
Measure Studies Mean SD (%) Median Range Studies Mean SD (%) Median Range
mRR (ms) 30 926 90 10 933 785–1,160 n/a n/a n/a n/a n/a n/a
SDNN (ms) 27 50 16 32 51 32–93 4 3.82 0.23 6 3.71 3.57–4.07
rMSSD (ms) 15 42 15 37 42 19–75 4 3.49 0.26 7 3.26 3.26–3.41
LF (ms2) 35 519 291 56 458 193–1,009 18 5.01 1.76 35 5.02 2.05–7.31
LFnu 29 52 10 19 54 30–65 n/a n/a n/a n/a n/a n/a
HF (ms2) 36 657 777 118 385 82–3,630 18 4.76 1.78 37 4.96 0.08–6.95
HFnu 30 40 10 25 38 16–60 n/a n/a n/a n/a n/a n/a
LF:HF 25 2.8 2.6 93 2.1 1.1–11.6 7 0.69 0.73 106 0.58 0.16–1.98
n/a =nonapplicable; SD =standard deviation; CV =coefficient of variation (SD/mean ×100); mRR =mean RR interval; SDNN =
standard deviation of normal-to-normal intervals; rMSSD =root mean square of successive differences; LF =low-frequency spectral
power; HF =high-frequency spectral power; LF:HF =ratio of low-frequency power to high-frequency power; nu =normalized units; ln =
natural logarithm.
When compared with data derived using
autoregressive methods, spectral measures of
HRV derived using the fast Fourier transform
(FFT) method were markedly different (Table III).
Studies utilizing the FFT method demonstrate
lower LF power, a higher HF power (absolute and
log-transformed units), and, therefore, a higher
LF:HF ratio.
Table II.
Comparison of Absolute and Log-Transformed HRV Values from Included Publications According to Sex
Mean Absolute Values from Mean Log-Transformed Values from
All Studies According to Sex*All Studies According to Sex
No. of Studies Measure Value No. of Studies Measure Value
HRV Difference Difference
Measure M F M F (%) M F M F (%)
mRR (ms) 9 7 922 885 8 No data§No data No data
SDNN (ms) 3 4 40369 No data No data No data
rMSSD (ms) 2 1 211911 No data No data No data
LF (ms2) 9 8 356 414 14 8 4 5.04 4.19 20
LFnu 6 9 53 46 17 No data No data No data
HF (ms2) 10 8 475 516 8 8 4 4.86 4.10 18
HFnu 7 7 39 38 3 No data No data No data
LF:HF 3 6 2.3 1.2 91 2 1 0.360.15140
*Data are means regardless of spectral method; Data from AR studies only; Data from FFT studies only. §Refers to the fact that no
comparable data between males and females were available from any of the included studies; mRR =mean RR interval; SDNN =
standard deviation of normal-to-normal intervals; rMSSD =root mean square of successive differences; LF =low-frequency spectral
power; HF =high-frequency spectral power; LF:HF =ratio of low-frequency power to high-frequency power; nu =normalized units.
There were large discrepancies in values
for HRV measures when obtained under paced
versus free breathing conditions (Table III). When
conducted under paced breathing conditions,
values were higher for all measures of HRV
except LF power which was higher during free
breathing. Finally, a number of studies revealed
large interindividual variation for the majority
1410 November 2010 PACE,Vol.33
REVIEW OF SHORT-TERM HRV VALUES
Table III.
Comparison of Absolute HRV Values from Included Publications According to Breathing Protocol and Spectral
Decomposition Methods
Mean Absolute Values According to Mean Absolute Values According to
Free or Paced Breathing Pattern*Spectral Decomposition Method
No. of Studies Measure Value No. of Studies Measure Value
HRV Difference Difference
Measure NB PB NB PB (%) AR FFT AR FFT (%)
mRR (ms) 20 6 928 948 2 12 14 881 943 7
SDNN (ms) 20 5 49 59 17 11 14 42 59 29
rMSSD (ms) 8 4 43 55 22 5 10 26 44 40
LF (ms2) 26 15 500 440 12 17 13 484 441 10
LFnu 25 3 51 58 12 13 13 55 47 18
HF (ms2) 27 16 434 963 54 17 14 348 647 45
HFnu 27 2 39 43 9 13 16 36 40 10
LF:HF 21 6 2.72 2.76 0.01 12 12 2.9 1.7 71
*Values are means from all studies using free breathing (NB) and paced breathing (PB) protocols without accounting for sex or spectral
decomposition method; Data are means from all AR or FFT studies without accounting for sex. mRR =mean RR interval; SDNN =
standard deviation of normal-to-normal intervals; rMSSD =root mean square of successive differences; LF =low-frequency spectral
power; HF =high-frequency spectral power; LF:HF =ratio of low-frequency power to high-frequency power; nu =normalized units.
of HRV measures, with values for one measure
(HF) differing by as much as 260,000% between
individuals within the same study (Fagard et al.11;
Table IV).
Discussion
Results of Literature Retrieval for Normal
Values of Short-Term HRV
From over some 3,100 citations, only 44
reported short-term measures of HRV in healthy
adult participants (n 30) and were in ac-
cordance with Task Force methodological stan-
dards/recommendations. The number of studies
was limited by the following factors:
Many studies of HRV assessed longer term
24-hour monitoring;
Studies were powered for the use of small
sample sizes;
Studies often include clinical populations
without the inclusion of a healthy cohort and/or
reference to healthy values;
Adherence to the Task Force methodologi-
cal recommendations was poor.
Some of the factors pertaining to the above
findings can be more easily explained than others.
A preferred use of 24-hour measurements to that
of short-term measurements could lie in their
greater prognostic power,3,52–54 or the additional
information such as night:day ratios that can
only be determined from 24-hour monitoring.
A more plausible explanation lies in the fact
that many studies of HRV are retrospective
in nature, reporting data from 24-hour Holter
monitoring carried out as part of standard cardiac
assessment.
The fact that studies utilize only a small
sample size may be explained by the nature of
the study, limitations in resources, and/or the
calculations of statistical power.55 Other factors,
such as the failure to report the actual values
for measures of HRV, were found to occur when
studies were interested in change scores56 or
preferred to present results graphically.57
The failure to report mean RR interval
by 54% of the studies is a concern. Because
of the reciprocal nature of HR and mean RR
interval, studies reporting measures of HRV often
choose to report only mean HR36,43 or in some
cases, neither.25,41 This error can be likened
to assessing the suspension behavior of a car
without acknowledging the car’s speed. Such
errors also reflect, on the part of both author and
publishing editor, failures in understanding of the
fundaments of HRV data and their analysis.
Thirty-six percent of included studies re-
ported TP and VLF which are not recommended
from short RR recordings due to their ambiguous
physiological meaning under such conditions.1
The use of units that differ from standard units
(e.g., beats per minute/Hz58) further limited
the number of eligible studies. When such
studies are published, they reflect a weakness in
PACE,Vol.33 November 2010 1411
NUNAN, ET AL.
Tab le I V.
Publications Presenting Interindividual Variation in Approved Task Force Short-Term Measures of HRV
Author Number of mRR SDNN rMSSD LF HF
and Date Participants (ms) (ms) (ms) (ms2) LFnu (ms2) HFnu LF:HF
Agelink et al.13 (1998) 69 NR NR 6.9–99.4 NR NR NR NR 0.29–11.00
Fagard et al.11 (1998) 587 NR NR NR 4–6,397*NR 4–10,751*NR NR
1–6,924*2–7,513*
Sinnreich et al.16 (1998) 293 NR 3.39–4.05 ln2.88–3.57 ln4.63–6.24 lnNR 4.07–5.49 lnNR NR
Pikkuj¨
ams¨
aetal.
23 (2001) 392 573–1,402 13–168 NR 35–5,941 11–98 10–7,231 3–72 0.24–17.10
3.56–8.69 ln 2.30–8.89 ln
Sucharita et al.25 (2002) 93 NR NR NR NR NR 13- 6,830 19–93 NR
Rajendra Acharya10 et al. 125 NR 41–67 53.6–70.4 NR NR NR NR 1.6–1.9
(2004) (mean lower and upper
values from three age groups)
Kurosawa et al.45 (2007) 66 NR NR NR 86–1,874NR 98–3,938NR NR
*Value is geometric; Values are 25th –75th percentile; Values are 5 and 95 percentiles; NR =not reported; mRR =mean RR interval; SDNN =standard deviation of
normal-to-normal intervals; rMSSD =root mean square of successive differences; LF =low-frequency spectral power; HF =high-frequency spectral power; LF:HF =ratio of
low-frequency power to high-frequency power; nu =normalized units; ln =natural logarithm.
1412 November 2010 PACE,Vol.33
REVIEW OF SHORT-TERM HRV VALUES
adherence to Task Force recommendations. This
also demonstrates a lack of coherence between
authors and editors as to how and what to present
when reporting short-term measures of HRV.
Comparisons between Literature and Task
Force Values
The Task Force does not provide norm values
for short-term time-domain measures of HRV and
therefore comparisons can only be made between
spectral measures. The Task Force figures are as
follows: 1,170 ms2for LF power, 975 ms2for
HF power, 54 and 29 for normalized LF and HF,
and 1.5–2.0 for the LF:HF ratio. The Task Force
LF value is more than 1.5 SD above the mean
literature value (519 ms2). The Task Force HF
value is also higher compared with that from the
literature (657 ms2). Task Force and literature-
normalized measures of LF and HF power are
more homogenous but the Task Force value for
LF:HF (1.5–2.0) is considerably lower than the
value gained from the literature (2.8).
Reasons for these discrepancies could be
due a number of factors including differing
characteristics of participants and differences in
spectral decomposition methods. The studies from
which the norms were obtained were not cited by
the Task Force authors so comparisons in terms
of participants are not possible. The Task Force
report does provide details as to the frequency
bandwidths used for determining LF and HF
power distributions. Oscillations in RR intervals
occurring at LF were assessed between 0.04 and
0.15 Hz and at HF between 0.15 and 0.4 Hz. Forty-
seven percent of the studies presented here report
values for LF and HF power obtained at frequency
bandwidths differing from those recommended by
the Task Force. Some considered oscillations in
heart periods at frequencies as low as zero to
0.003 as part of the LF component.19,40 Others
utilized much lower cutoff values (0.3 Hz) for
the HF component.21 Discrepancies in LF and HF
frequency bands could lead to the inclusion and/or
exclusion of oscillations of differing physiological
origins and would certainly result in varying
values for LF, HF, and/or both. It is both interesting
and somewhat telling then that these studies
report some of the largest discrepancies for
spectral measures of HRV.
From Table SI, it can be seen that the
following population-based studies report values
for short-term HRV measurements from large
samples (1,000): Rennie et al.,6Kuo et al.18
Dekker et al.,20 Liao et al.,32 Hemingway et al.,36
Britton et al.43 On closer examination, a number
of these studies were based upon ongoing
longitudinal and/or cross-sectional assessments
of the same participant populations. While these
studies present different sized samples and were
testing different hypotheses, there is a potential
for significant overlap between their respective
samples. This may explain the similarity in values
between Dekker et al.20 and Liao et al.32 and
among Rennie et al.,6Hemingway et al.,36 and
Britton et al.43 (Table SII). For these reasons, it
could be argued that only three large populations
have been assessed since the 1996 Task Force
report.6,18,43 Moreover, the lowest participant age
across these three populations was 40 years. This
means that there are currently no published data
for short-term HRV measures obtained in a large
population including adults aged less than 40. The
negative relationship between HRV and age may
also explain the relatively low values for HRV
measures observed by these studies. The impact
these large samples have on the mean publication
values presented here is also noteworthy.
Studies Reporting Discrepant Absolute
HRV Values
Approximately 85% of studies demonstrated
values within 1.5 SD of the mean publications
value for one or more short-term HRV measure.
Closer scrutiny of the 15% of studies demon-
strating values greater than 1.5 SD can help
identify conditions leading to disparate values
for short-term measures of HRV. Discussion of
the following studies demonstrating discrepant
values will adopt a measure-by-measure approach:
Melanson21 (mRR, SDNN, rMSSD, LF, HF),
Sandercock et al.34 (LF), Evrengul et al.40 (SDNN),
Mehlsen et al.48 (SDNN), Sandercock et al.50
(SDNN, rMSSD), Nunan et al.51 (LF).
A closer look at the characteristics of the
above studies revealed a number of similarities
and differences related to study participants,
RR interval data recording, artifact identification,
and interpolation and spectral decomposition
protocols. As these factors can have differing
effects depending on the measure, they will be
discussed separately for time- and frequency-
domain measures, respectively.
Time-Domain Measures
The high RR values reported by Melanson21
and the high SDNN values reported by both
Melanson21 and Sandercock et al.50 might be
explained by their use of young and moderate-
to-well trained participants. There is a well-
established link between age and HRV, with a
decrease in HR for increasing age with younger
individuals demonstrating higher values.1,16,18,59
SDNN is also a function of the recording
length, with longer analyzed recordings producing
larger values.60 For this reason, the Task Force
recommends a standardized duration of 5 minutes
PACE,Vol.33 November 2010 1413
NUNAN, ET AL.
for short-term SDNN (and other measures of
HRV). These factors most likely explains the larger
values observed by Evrengul and colleagues40 who
determined the SDNN of RR interval data recorded
over a 1-hour period. No justification for such a
recording length was given by the authors.
Parasympathetic nerve traffic enacts its effects
at a much faster (<1 second) rate than sympa-
thetic outflow (>5 seconds); therefore, beat-to-beat
changes in RR intervals (rMSSD) are considered
a reflection of vagal outlfow.52,54 Measures of
rMSSD are highly variable under conditions of
enhanced vagal outflow.61 One such condition
is paced breathing, particularly in the supine
position. In addition, the bradycardia observed
for more highly trained individuals is commonly
accompanied by augmented markers of cardiac
vagal modulation,62,63 although this relationship is
not always observed.64 The discrepant values for
rMSSD reported by Melanson21 and Sandercock
et al.50 are likely to result from the combined
effect of young, trained individuals with higher
baseline vagal tone and the use of supine and
paced breathing protocols.
Frequency-Domain Measures
A number of human and animal studies have
demonstrated findings of both sympathetic65–67
and parasympathetic68 origins for LF oscilla-
tions and spectral power. An augmented and
diminished LF power under parasympathetic
blockade has implications for studies where
vagal conditions are enhanced, such as during
paced breathing conditions.68 The higher values
observed by Melanson21 may be the consequence
of a vagally mediated augmentation of LF power
resulting from the paced breathing condition.
In healthy normotensive controls, a value of
82 ms2was reported by Piccirillo et al.33 Moreover,
this value was used to determine “abnormal” HF
power in chronic heart failure (CHF) patients.
Inclusion of these values in the present study
may explain the lower overall mean value for
HF power. An important observation is that these
values are considerably lower than the Task Force
norm value for HF and the mean studies value
presented here. As is common throughout the
literature, consideration as to the “normality” of
the so-called “healthy” values is ignored.
Spectral measures are highly sensitive to tech-
nical errors within RR data such as artifacts, mis-
placement of missing data, poor pre-processing,
and nonstationarity. Information regarding error
detection methods for 1-hour Holter RR interval
data was not provided by Evrengul et al.40 and
no indication as to the number of errors observed
and/or removed was given. The fact that Mehlsen
et al.48 do not report the performance of any
error identification, removal, and/or correction
procedures suggest a failure to understand the
importance of correct RR interval data in the
analysis of its variation. RR intervals were also
considered to be “within normal range,” yet the
authors provide no reference for this so-called
“normal” range.
The Task Force1recommendations stress
the need for manual editing of RR interval
data. Evidence of a strong prognostic value for
fully automated measures of HRV12 and their
accurate and reliable determination compared to
traditional methods34,51 suggests that the Task
Force1recommendations may be outdated. At the
very least, they require updating to account for
the computational power of current automated RR
recording and HRV analysis devices.
Studies Reporting Discrepant Log-Transformed
HRV Values
Of the studies reporting log-transformed mea-
sures of HRV, only one demonstrated discrepant
values for HRV measures.12 In the study by Ho
et al.12 data for spectral measures of HRV were
obtained in a healthy control group matched for
age and sex to a group of patients suffering from
CHF. The participants in the control group were
44% female, with a mean age of 72 years and a
resting HR of 76 beats/min. There is a well-known
age-related decline in HRV that particularly affects
measures related to vagal modulations of HR in
females.18 Data presented elsewhere demonstrate
a negative correlation between HR and spectral
measures of HRV.69 These two factors alone may
explain the low values for LF (2.05 ln ms2)and
particularly for HF power (0.08 ln ms2) observed
by Ho et al.12 As with the majority of studies
utilizing a control “reference” group, the values
presented in the control group are not questioned
by the authors as to their normality/abnormality.
Summary of Main Factors Underlining
Discrepant Values in Short-Term HRV
from Healthy Individuals
The measure-by-measure analysis performed
for those studies reporting discrepant values
revealed a number of underlying factors including:
1. Moderate to high level of participant
habitual physical activity;
2. The use of paced breathing protocols,
particularly when performed in participants with
moderate to high physical activity levels;
3. Where younger participants are measured,
values for HRV are typically higher;
1414 November 2010 PACE,Vol.33
REVIEW OF SHORT-TERM HRV VALUES
4. Poor reporting and/or performance of
RR interval error recognition, removal, and/or
correction procedures;
5. The use of differing frequency bandwidths
and normalization methods for LF and HF spectral
measures;
6. Wide variation in HRV measures between
healthy participants of the same study;
7. The misclassification of participants as
healthy;
8. A failure of studies to recognize the nor-
mality/abnormality of values obtained in healthy
participants.
Some of the points above (1, 2, 3, and 6)
were not unexpected. Of some surprise was the
failure to perform error correction procedures by a
number of studies and the poor reporting of these
procedures by others. The last three summary
points are particularly important and highlight the
inherent problem of defining a so-called “normal”
HRV.
These points are also inter-related in that
the failure to question the normality of data
when obtained in healthy participants possibly
stems from the fact that even in homogonous
healthy groups, measures of HRV can display wide
interindividual variations (as high as 260,000%,
Fagard et al.11; Table IV).
It is important, however, to recognize other
factors could influence discrepancies between
studies. Measures of HRV are influenced by diet
(caffeine and alcohol intake) and physical and
mental stress. Very few of the studies included
here include information on these factors and their
impact on values presented cannot be determined.
When assessing studies reporting so-called normal
HRV, readers should employ close scrutiny of the
factors outlined above as well as potential other
factors (e.g., diet, stress) related to the individual
aspects of each study. With consideration of these
factors, the data presented in this study may
provide users of HRV with reference ranges by
which to determine disparate values for common
measures of short-term HRV.
Study Limitations
It is possible that some papers meeting the
inclusion criteria for the present study would have
been missed by the search strategy employed.
Arbitrary selection of the selected search terms
may have meant that some studies reporting short-
term HRV in healthy adults may have been missed.
Alternatively, it could be argued that studies
missed despite the comprehensive list of search
terms may be too ambiguous in terms of the
context in which short-term measures of HRV were
used.
Study Recommendations
To facilitate between-study comparisons and
aid standardization of measurements, studies need
to report the outcomes of RR interval data editing
procedures. In addition, measures of stationarity
or measures taken to address nonstationary
signals should be provided. Moreover, editors
and reviewers need to adopt greater diligence in
ensuring that papers using HRV provide details
of data treatment before accepting the paper(s) for
publication.
Despite the call for large population-based
studies to determine normal HRV standards by the
1996 Task Force paper, there are no studies with
participants from the full age spectrum. There is
still a need for a population-based study assessing
short-term HRV measurements and involving the
full age spectrum. A multicenter approach may be
the most feasible approach. Such a study would
require stringent methodological standards and
participant inclusion criteria and awareness of
methodological and participant factors known to
affect HRV.
There is a need for a revision of current recom-
mendations and standards for the measurement of
short-term HRV. These should be made in light
of significant developments in the computational
power and accuracy of automated RR interval
and HRV analysis systems. There is a particular
need to stress clarity and transparency by the
manufacturers as to the QRS, RR interval, and HRV
analysis procedures of new technologies.
Conclusions
Data presented here should be used to
quantify reference ranges for short-term measures
of HRV in healthy adult populations but should
be undertaken with reference to methodological
factors underlying disparate values. These include
but are not limited to: participant demographic
characteristics, including age, sex, and habitual
physical activity levels; poor RR interval data
editing procedures; poor classification of healthy
participants; and a failure to recognize values as
disparate. Studies reporting HRV need to recog-
nize the normality of data even when obtained
in individuals considered as healthy. The need
for large-scale population studies assessing short-
term HRV in normally healthy adults still remains.
Current recommendations require updating to
account for the era of completely automated HRV
analysis. Clarification of measurement standards
in light of the discrepancies observed between
studies is also needed.
PACE,Vol.33 November 2010 1415
NUNAN, ET AL.
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Supporting Information
The following supporting information is available for this article:
Table SI. Publications Reporting Short-Term Measures of HRV in Normally Healthy Adults from 1996
to September 2008: Comparison of Methodologies.
Table SII. Publications Reporting Short-Term Measures of HRV in Normally Healthy Adults from 1996
to September 2008: HRV Measurement Values.
Supporting Information may be found in the online version of this article.
(This link will take you to the article abstract).
Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting
information supplied by the authors. Any queries (other than missing material) should be directed to
the corresponding author for the article.
PACE,Vol.33 November 2010 1417
... Spectral analysis allows the intensity of the HRV spectral components [i.e., the high-frequency band (HF), lowfrequency band (LF), and very low-frequency band (VLF)] to be determined. The HF component is believed to be mediated primarily by cardiac parasympathetic outflows and thus may provide a direct index of vagal activity; whereas the LF is commonly viewed as a product of both sympathetic and parasympathetic activity (Gianaros et al., 2004;Jennings & McKnight, 1994;Malliani et al., 1991;Nunan et al., 2010;Pumprla et al., 2002;Task Force, 1996). ...
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The Task Force was established by the Board of the European Society of Cardiology and co-sponsored by the North American Society of Facing and Electrophysiology. It was organised jointly by the Working Groups on Arrhythmias arzd on Computers of Cardiology of the European Society of Cardiology. After exchanges of written views on the subject, the main meeting of a writing core of the Task Force took place on May 8-10. 1994, on Necker Island. Following external reviews, the tent of this report was approved by the Board of the European Society of Cardiology on August 19,1995, and by the Board of the North American Society of Facing and Electrophysiology on October 3, 1995.
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Background —Low heart rate variability (HRV) is associated with a higher risk of death in patients with heart disease and in elderly subjects and with a higher incidence of coronary heart disease (CHD) in the general population. Methods and Results —We studied the predictive value of HRV for CHD and death from several causes in a population study of 14 672 men and women without CHD, aged 45 to 65, by using the case-cohort design. At baseline, in 1987 to 1989, 2-minute rhythm strips were recorded. Time-domain measures of HRV were determined in a random sample of 900 subjects, for all subjects with incident CHD (395 subjects), and for all deaths (443 subjects) that occurred through 1993. Relative rates of incident CHD and cause-specific death in tertiles of HRV were computed with Poisson regression for the case-cohort design. Subjects with low HRV had an adverse cardiovascular risk profile and an elevated risk of incident CHD and death. The increased risk of death could not be attributed to a specific cause and could not be explained by other risk factors. Conclusions —Low HRV was associated with increased risk of CHD and death from several causes. It is hypothesized that low HRV is a marker of less favorable health.