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Heart-rate variability: A biomarker to study the influence of nutrition on physiological and psychological health?


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As the influence of diet on health may take place over a period of decades, there is a need for biomarkers that help to identify those aspects of nutrition that have either a positive or a negative influence. The evidence is considered that heart-rate variability (HRV) (the time differences between one beat and the next) can be used to indicate the potential health benefits of food items. Reduced HRV is associated with the development of numerous conditions for example, diabetes, cardiovascular disease, inflammation, obesity and psychiatric disorders. Although more systematic research is required, various aspects of diet have been shown to benefit HRV acutely and in the longer term. Examples include a Mediterranean diet, omega-3 fatty acids, B-vitamins, probiotics, polyphenols and weight loss. Aspects of diet that are viewed as undesirable, for example high intakes of saturated or trans-fat and high glycaemic carbohydrates, have been found to reduce HRV. It is argued that the consistent relationship between HRV, health and morbidity supports the view that HRV has the potential to become a widely used biomarker when considering the influence of diet on mental and physical health.
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Heart-rate variability: a biomarker to study the influence of
nutrition on physiological and psychological health?
Hayley A. Young and David Benton
As the influence of diet on health may take place over a
period of decades, there is a need for biomarkers that help to
identify those aspects of nutrition that have either a positive
or a negative influence. The evidence is considered that heart-
rate variability (HRV) (the time differences between one beat
and the next) can be used to indicate the potential health
benefits of food items. Reduced HRV is associated with the
development of numerous conditions for example, diabetes,
cardiovascular disease, inflammation, obesity and psychiatric
disorders. Although more systematic research is required,
various aspects of diet have been shown to benefit HRV
acutely and in the longer term. Examples include a
Mediterranean diet, omega-3 fatty acids, B-vitamins,
probiotics, polyphenols and weight loss. Aspects of diet that
are viewed as undesirable, for example high intakes of
saturated or trans-fat and high glycaemic carbohydrates,
have been found to reduce HRV. It is argued that the
consistent relationship between HRV, health and morbidity
supports the view that HRV has the potential to become a
widely used biomarker when considering the influence of diet
on mental and physical health. Behavioural Pharmacology
29:140151 Copyright © 2018 The Author(s). Published by
Wolters Kluwer Health, Inc.
Behavioural Pharmacology 2018, 29:140151
Keywords: diet, disease, health, heart-rate variability, nutrition
Department of Psychology, University of Wales Swansea, Swansea, Wales, UK
Correspondence to David Benton, DSc, Department of Psychology, University of
Wales Swansea, Swansea SA2 8PP, Wales, UK
Received 19 May 2017 Accepted as revised 14 January 2018
Biomarkers are important as proxy measures when
studying health or disease states that develop over long
periods. As a disease can develop over decades, this is an
area where there is a need for biomarkers that identify
aspects of life style that are potentially beneficial or
problematic. The case will be made for using heart-rate
variability (HRV) as an indicator of the physiological
response to food by those interested in the association
between diet and various health outcomes, and by
manufacturers developing functional foods with potential
health benefits. HRV is of interest as a wide range of
diseases are associated with decreased variability,
including diabetes, cardiovascular disease and psychiatric
disorders. In addition, there is an increasing literature
that reports that HRV responds to various aspects of the
diet, raising the possibility that HRV offers a convenient
measure of potential benefit.
Traditionally, heart rate (HR) has been considered a
product of emotional response or stress, but it is
becoming apparent that the interval between beats is a
marker of the capacity to regulate internal and external
demands. The intervals are not constant, but differ from
beat to beat: essentially a higher HRV indicates better
general health (Jarczok et al., 2015). In essence, the
multitude of ways in which different physiological
mechanisms modulate each other ensures that studying
one aspect of the body in isolation limits our
In 1948, the WHO defined health as a state of complete
physical, mental and social well-being and not merely the
absence of disease or infirmity. As complete well-being
is practically impossible, more recent definitions have
emphasized resilience, the capacity to cope and the
ability to maintain a sense of well-being. To assess the
level of existing health and to evaluate dietary inter-
ventions, such definitions need to be operationalized.
With this in mind, HRV may serve as a biomarker
relating to the above definition, and thus serve as an
indicator of the response to diet. In this review, the
control of HR and the measurement of HRV are first
outlined and then associations between HRV, health and
aspects of diet are considered.
Control of heart rate
Figure 1 shows an ECG trace from which the R-to-R
intervals are measured, although it is the variability in the
differences between these intervals that is of interest. In
the brain stem, the medulla oblongata controls HR
through the vagus, the tenth cranial nerve: vagal tone
reduces HR by inhibiting the sinoatrial node, the hearts
pacemaker. Although there is a tendency to view HR as
an involuntary mechanism, the medulla oblongata
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140 Review article
0955-8810 Copyright © 2018 The Author(s). Published by Wolters Kluwer Health, Inc. DOI: 10.1097/FBP.0000000000000383
receives information from the rest of the brain: including
the central autonomic network (CAN) (Benarroch, 1993),
with the prefrontal cortex playing a leading role (Thayer
and Lane, 2009). Indeed, the cortical regulation of the
CAN has been well described; there are both direct and
indirect pathways (involving the cingulate and insula
cortices, amygdala, hypothalamus and medulla oblon-
gata) linking the frontal cortex to autonomic motor cir-
cuits responsible for both the excitatory and inhibitory
effects on the heart (see Thayer and Lane, 2009 for a
review). Therefore, the moment-to-moment control of
HR reflects complex interactions between physiology,
emotion and cognition (Benarroch, 1993; Thayer and
Lane, 2009), encompassing the integration of a wide
variety of information. Thus, it has been suggested that
HRV reflects the overall capacity of the body to deal with
on-going demands (Young and Benton, 2015). HRV may
serve as a proxy for the vertical integrationof the brain
mechanisms that guide flexible control over behaviour
with peripheral physiology, and as such provides an
important window into understanding stress and health
(Thayer et al., 2012). In this way, HRV may act as a
biomarker when considering the influence of diet on
health-related mechanisms.
Indices of heart-rate variability
Three approaches are used to monitor HRV: time-
domain and frequency-domain measures are linear in
nature, whereas complexity measures offer a nonlinear
approach. The simplest approach is to summarize dif-
ferences in the interbeat interval as a mean and SD, so-
called time-domain measures (Fig. 2). Second, a spectral
analysis allows frequency domain indices to be calculated
and describes the interbeat intervals as a complex sum
of waveforms. The variance in HR is distinguished in
terms of the underlying rhythms that occur at different
frequencies. There is growing evidence that frequency-
domain indices measure the functioning of the autonomic
nervous system. The high-frequency (HF) measure
(power in the range 0.150.4 Hz) is more easily under-
stoodasitissaidtoreflectthe parasympathetic nervous
systems (PNSs) (Katona et al., 1970; Appel et al., 1989;
Billman and Hoskins 1989; Camm et al., 1996; Thayer
et al., 2010). In contrast, low-frequency (LF) (power in
the range: 0.040.15 Hz) is less readily interpreted as it
is influenced by both the PNS and also baroreceptor
activity (Houle and Billman, 1999; Billman, 2013). A
frequently considered index is the LF/HF ratio, which
is said to reflect the balance between PNS and the
sympathetic nervous system activity (Malik, 1998),
although this contention has been challenged recently
(Billman, 2013).
More recently, nonlinear indices have been developed:
as one example, approximate entropy provides an indi-
cation of the irregularity or randomness in a data set. The
time series 1, 2, 3, 1, 2, 3 has the same variability as the
time series 1, 1, 2, 2, 3, 3 and 3, 1, 2, 2, 3, 1, but different
underlying patterns. Nonlinear analysis enables the
quantification of this extra information. Essentially, the
nonlinear approach measures the complexity of the sig-
nal; how frequently do similar patterns reoccur? Although
frequency measures in particular have been studied
widely, it has become apparent that nonlinear indices of
complexity reflect different underlying mechanisms
(Young and Benton, 2015). For example, a recent study
reported that nonlinear measures of HRV were better
able to predict the performance of cognitive tests than
linear measures (Young and Benton, 2015). In addition, a
meta-analysis of the impact of depression and anti-
depressant treatment on HRV found that the effects
were most apparent with nonlinear measures of HRV
(Kemp et al., 2010). There is an impression that those
capable of generating more complex signals have a
greater ability to respond to environmental demands in a
more subtle manner (de la Torre-Luque et al., 2016).
Heart-rate variability, inflammation and
Inflammation is part of the immune response, with too
much and too little inflammation indicating, or leading to,
a wide range of diseases. Hotamisligil (2006) noted that
metabolic regulation and the immune system are highly
integrated: he suggested that this interaction reflects a
central homeostatic mechanism that, if dysfunctional,
results in chronic metabolic disorders, particularly obe-
sity, type 2 diabetes and cardiovascular disease. An
inadequate response creates immunodeficiency that can
result in infection or cancer (Mellemkjaer et al., 2002). As
the inflammatory response is in part regulated by the
autonomic nervous system, HRV is of interest.
The vagus plays a role in the inflammatory reflex that
controls innate immune responses when tissue is injured
Fig. 1
A heart-rate trace. A typical electrocardiogram trace is illustrated. R is
the peak of the QRS complex (electrocardiogram trace) and heart-rate
variability is measured by considering consecutive RR intervals. The
RR interval is not constant, but varies within a normal range of
0.61.2 s. It is the degree of this RR variability that is of interest as
greater variability is associated with better health.
HRV: a biomarker for health Young and Benton 141
or there is a pathogen invasion (Pavlov and Tracey, 2012).
The inflammatory reflex has an afferent component that
is activated by cytokines that relay information to the
hypothalamus. This input can then initiate an anti-
inflammatory response that prevents the release of
inflammatory products into the blood stream (Tracey,
2002). It is becoming increasingly clear that the nervous
system, through the vagal nerve, both monitors
Fig. 2
Linear domain - Time indices
Index Interpretation
Mean RR interval (ms) The average of NN intervals. A longer NN interval indicates a
lower heart rate.
SDNN (ms) Standard deviation of the NN intervals. Indicates total variability
with a high value is thought to associate with better health.
RMSSD (ms) The square root of the mean of the sum of the squares of
differences between adjacent NN intervals (RMSSD) is thought
to indicate parasympathetic nervous system activity.
Linear domain - Frequency indices
Index Interpretation
Total power (ms2) Variance of all inter-beat intervals ( 0.4 Hz). Indicates total
variability with a high value is thought to associate with better
ULF (ms2) Power in the ultra-low frequency range ( 0.003 Hz). Might
reflect circadian, neuroendocrine, activity, other unknown
VLF (ms2) Power in the very low frequency range (0.003–0.04 Hz). Might
reflect vasomotor changes, thermoregulatory and possibly
parasympathetic influences on heart rate.
LF (ms2) Power in the low frequency range (0.04–0.15 Hz). Thought to
reflect a combination of parasympathetic and baroreceptor
HF (ms2) Power in the HF range (0.15–0.4 Hz). Reflects parasympathetic
LF/HF Ratio LF (ms2)/HF (ms2). Frequently used index of autonomic
balance although this has been debated.
Non-linear analysis
Index Interpretation
ApEn Approximate Entropy measures irregularity or randomness in a
set of data, such that smaller values reflect a greater regularity.
Sample entropy (SampEn) is a similar measure that is more
suitable for short recordings.
DFA Detrended Fluctuation Analysis quantifies the fractal like
correlation properties of a time series and reveals short-range
(DFA1) and long-range (DFA2) correlations within a series.
Various measures of heart-rate variability. The variability in consecutive differences in the RR interval can be expressed using a number of different
approaches that are one of three types: time or frequency based or nonlinear. HF, high-frequency; LF, low-frequency.
142 Behavioural Pharmacology 2018, Vol 29 No 2&3
peripheral inflammation and dampens the immune
response (Boeckxstaens, 2013). The sympathetic arm of
the autonomic nervous system also plays a role: it releases
noradrenaline, which appears to act at sites other than the
synapse, as many immune cells, including lymphocytes
and macrophages, have adrenergic receptors (Kavelaars
et al., 1999).
HRV is associated with the levels in the blood of
C-reactive protein (CRP), a protein that is produced by
the liver as a response to inflammation, with the levels
increasing following the secretion of interleukin (IL)-6
from macrophages and T cells. The role of the protein is
to bind to lysophosphatidyl choline on the surface of
dead cells and to enhance the ability of antibodies and
phagocytic cells to remove pathogens. Higher levels of
CRP are associated with a greater risk of hypertension,
diabetes and cardiovascular disease (Dehghan et al.,
2007). Jarczok et al. (2014) reported that the HF com-
ponent of HRV predicted the level of CRP when it was
measured 4 years later; this is important as both inflam-
mation and HRV have been implicated in conditions
such as diabetes and cardiovascular disease (Kudat et al.,
2006; Thayer et al., 2010).
Madsen et al. (2007) related low-grade inflammation to
autonomic dysfunction in those with suspected coronary
heart disease. The mean SD of normal to normal RR
(SDNN) was higher in those with lower levels of CRP,
with the association being greater in those with a pre-
vious history of myocardial infarction. However, CRP
remained associated with HRV independent of disease, a
finding interpreted as a relationship occurring between
low-grade inflammation and autonomic dysfunction.
Experimental evidence is beginning to emerge and
support these associations. For example, a recent study
found that vagus nerve-stimulation in epilepsy patients
inhibited peripheral blood production of tumour necrosis
factor, IL-1βand IL-6 (Koopman et al., 2016).
Whether by influencing inflammation or by other
mechanisms, HRV has been associated with a range of
diseases, in some cases predicting subsequent problems
and in others being an index of disease progression
(RenuMadhavi and Ananth, 2012). As a generalization, a
healthy biological system tends to be both variable and
complex, characteristics that decline with disease.
Irrespective of disease, HRV declines with age, reaching,
in some older than 65 years of age, levels that are a risk
factor for mortality (Umetani et al., 1998).
The American Heart Association states that diabetes
increases the risk of heart disease or a stroke and thus
early diagnosis of complications is the key to decreasing
mortality. A systematic review of those with diabetes
concluded that HRV can help to predict cardiac mor-
bidity and mortality, and that it can be used at an early
stage to indicate the future risk of complications
(Fakhrzadeh et al., 2012). As one example, Yoshioka and
Terasaki (1994) reported that the HF component, which
indicates parasympathetic nervous activity, was lower in
diabetics rather than controls, and there were inverse
correlations between the LF and HF. It was concluded
that these measures of HRV are useful when evaluating
diabetic autonomic and peripheral neuropathies. The
Atherosclerosis Risk in Communities study (Schroeder
et al., 2005) also found that diabetics differenced in HF
power and that HF in nondiabetics was greater in those
with lower levels of fasting insulin. Thus, there was a
relationship between insulin resistance, as indicated by
higher levels of fasting insulin, and lower HRV. In
addition, after a 9-year followup, there was a general
decline in HRV. Such findings suggest that an impair-
ment of the functioning of the autonomic nervous sys-
tem, reflected in HRV, occurs during the early stages of
diabetes and becomes progressively worse over time.
A more general question is the association between HRV
and blood glucose levels. The Framingham Heart Study
(Singh et al., 2000) related HRV to fasting levels of blood
glucose: LF and HF power was reduced in those with
diabetes or impaired levels of fasting glucose. In addition,
a recent study found that resting HRV (average RR
interval, HF power, sample entropy) predicted the
increase in blood glucose following a high glycaemic load
drink (Young and Watkins, 2016). Overall, HRV appears
to be associated inversely with plasma glucose levels. It is
plausible that the links between insulin resistance, blood
glucose and HRV are attributable to deficits in the
inflammatory reflex (Pavlov and Tracey, 2012). Vinik
(2012) noted that activation of inflammatory cytokines in
newly diagnosed type 2 diabetes correlated with changes
in sympathovagal balance. As, in type 2 diabetes,
changes in the autonomic nervous system predict sudden
death, such measures offer the chance of an early
As mentioned above, a reduction in HRV predicts mac-
rovascular disease, for example carotid artery athero-
sclerosis (Gottsäter et al., 2006). Indeed, a recent study
found that insulin resistance mediated the association
between HF-HRV and carotid intimamedia thickness
(Kemp et al., 2016). In fact, it has been known for many
years that following myocardial infarction, HRV is related
to the risk of consequent morbidity and mortality (La
Rovere et al., 1998). In addition, the rate at which con-
gestive heart failure and arrhythmias occur has been
related to a reduced HRV (Sandercock and Brodie, 2006)
and lower HRV complexity is associated with a worse
outcome in cardiac patients (Souza et al., 2015). Although
fewer studies have considered those without a history of
coronary heart disease, a meta-analysis examined those
without any problem at baseline (Hillenbrand et al.,
2013). A lower HRV, measured as SDNN, was associated
with a subsequent 40% increase in the risk of suffering a
first cardiovascular event.
HRV: a biomarker for health Young and Benton 143
Heart-rate variability, obesity and weight loss
Decreased HRV is associated with a significantly
increased risk of death from cardiovascular disease
(Bigger et al., 1993; Makikallio et al., 1999). Therefore,
Kim et al. (2005) considered whether the high rate of
cardiovascular disease in obese individuals might be
associated with changes in HRV. They found that the
RMSSD (a frequently used index of parasympathetic
activity) was correlated negatively with fat mass and the
hip-to-waist ratio. Similar effects were noted for LF
power, although as noted above, this index is not easily
interpretable. Nonetheless, it seems that obesity can
alter HRV.
For example, Mouridsen et al. (2013) examined the
impact of weight loss on HR and HRV in overweight
postmenopausal women. An average weight loss of 3.9 kg
was associated with a decrease in HR and increased
HRV, as indicated by SDNN and the interbeat interval.
Previously, Karason et al. (1999) had considered obese
patients, who, after surgery, had lost 28% of their body
weight, on average 32 kg. SDNN and HF power were
attenuated in those with obesity compared with lean
patients; HRV improved with weight loss. Adachi et al.
(2011) examined the influence of obesity on autonomic
activity during sleep. Volunteers were allocated randomly
to a standard diet or one that over 8 weeks increased
weight by 4 kg. After weight gain, HF power decreased
both when awake and when asleep, changes that resolved
with weight loss. A related finding was that caloric
restriction may reverse the autonomic changes that occur
as we age. A decline in HRV with age is well described:
for example, Zulfiqar et al. (2010) compared HRV in
patients of ages ranging from 10 to 99 years. Several
measures of HRV all decreased rapidly from the second
to fifth decades, although the decline then slowed. They
concluded that a healthy long life depends on the pre-
servation of autonomic functioning, more specifically, the
influence of the PNS on HRV. Stein et al. (2012) found
that in patients who had practiced caloric restriction, for
on average 7 years, HR was lower and several measures of
HRV values were significantly higher. In fact, HRV was
comparable to the norms for those 20 years younger. The
overall impression is that weight gain adversely influ-
ences HRV, although this effect may be reversible with
weight loss and/or dietary restriction.
Heart-rate variability and eating behaviour
HR variables have also been related to dieting and eating
behaviour. A recent review concluded that most,
although not all, studies investigating HRV in those with
anorexia nervosa find parasympathetic dominance
(Mazurak et al., 2011). Similarly, those with bulimia
nervosa are characterized by higher vagal activity, parti-
cularly HF-HRV (Peschel et al., 2016). In a healthy
sample, Meule et al. (2012b) found that restrained eating,
which is the intentional restriction of food intake to
prevent weight gain or to promote weight loss, was
associated with low cardiac vagal control (Table 1). The
restraint score and the extent to which weight fluctuated
predicted HF-HRV negatively. In a further study, Meule
et al. (2012a) qualified this finding by considering suc-
cessful versus unsuccessful dieters: success was asso-
ciated positively with HF-HRV. They concluded that
vagalcardiac control reflected the strength of self-
regulation such that successful restrained eaters were
characterized by higher cardiac vagal control. These
findings are in line with two studies that found reduced
HR variability and complexity (RR interval, HF power,
sample entropy) in those with a propensity towards dis-
inhibited eating, which is a tendency to overeat in the
presence of palatable foods or other disinhibiting stimuli,
such as emotional stress (Young and Watkins, 2016;
Young et al., 2017a). Importantly, these effects remained
after controlling for the healthiness of the diet. Thus, it
appears that tonic HRV might index individual differ-
ences in the capacity to self-regulate in the face of
temptation. Indeed, Geisler et al. (2016) reported that
restrained eaters who suppressed their feelings about a
distressing film had higher vagally mediated HRV
(RMSSD) during subsequent exposure to a palatable
food (jelly beans). In an earlier study, Segerstrom and
Nes (2007) found an increase in RMSSD when partici-
pants were told to resist warm cookies and instead eat
carrots. A caveat is that caloric restriction and intermittent
fasting, behaviours commonly observed in restrained
eaters, have been shown to increase HF oscillatory
components in HR (Mager, 2006). Thus, the higher HF-
HRV observed in this population may be because of
lifestyle factors rather than differences in self-regulatory
capacity. Future research should explore this possibility.
That said, these associations between eating behaviour
and HRV offer the possibility of examining the associa-
tion between the ability of different types of food to
influence HRV and their ability to reduce or prevent
pathological eating behaviours.
Heart-rate variability and psychiatric disorders
A dysfunctional autonomic nervous system, with an
associated reduction in HRV, has been found in a wide
range of psychiatric disorders, a contention supported by
a number of recent meta-analyses. Kemp et al. (2010)
examined the association between depression and HRV
in those without cardiovascular disease. When depressed
patients and healthy controls were compared, the former
had a lower HRV; it was particularly lower in those with
more severe symptoms. Similar meta-analytic reviews
have shown HRV reductions in a range of psychiatric
disorders: bipolar disorder (Faurholt-Jepsen et al., 2017),
anxiety disorders (Chalmers et al., 2014), post-traumatic
stress disorder (Nagpal et al., 2013) and schizophrenia
(Clamor et al., 2016). Notably, such effects are most
consistently examined using HF-HRV or other vagally
mediated HRV indices (e.g. RMSSD), although on
144 Behavioural Pharmacology 2018, Vol 29 No 2&3
occasion, larger effect sizes have been noted with non-
linear indices (Kemp et al., 2010). Importantly, HRV
predicted the onset of psychological illness 10 years later
(Jandackova et al., 2016). Given the links between HRV,
emotion regulation and executive functioning (Williams
et al., 2015; Zahn et al., 2016; Holzman and Bridgett,
2017), it has been proposed that HRV is a transdiagnostic
biomarker of mental illness (Beauchaine and Thayer,
This brief overview illustrates that HRV is a risk for, or a
marker of, a wide range of disorders. As such, any inter-
vention that impacted positively on HRV has the
potential to benefit health. Evidence suggests that life-
style may be one such factor. Young et al. (2017a)
reported that smoking cigarettes and drinking alcohol
negatively influenced HRV, measured using linear (HF
power) and nonlinear (sample entropy) measures. In
addition, these aspects of the HR time series were
increased in those who took regular exercise and con-
sumed a healthy diet. Notably, diet quality at least par-
tially explained the association between mood,
disinhibition and HRV (Young et al., 2017a); thus, dietary
modification may improve HRV in those at risk of psy-
chological disorders.
The nature of the diet and heart-rate variability
In an early study, Lu et al. (1999) examined the post-
prandial changes in HRV following a 500 kcal test meal
(turkey sandwich: 32.4% fat, 17.5% protein and 50.1%
carbohydrate). HF power decreased during the first and
second 30 min following consumption, suggesting a
reduction in vagal tone. Similarly, after a mixed meal of
501.8 kcal that comprised 31% protein, 18% lipids and
51% carbohydrates, a decrease in HF power was
observed from 40 to 120 min after the meal, an effect that
correlated negatively with ghrelin concentrations (Chang
et al., 2010). In relation to specific macronutrients,
Kanaley et al. (2007) studied the influence of an acute
glucose load on HRV in obese women with and without
diabetes. Total power decreased in response to the glu-
cose challenge compared with what was observed in the
fasted state. In addition, a high-carbohydrate meal was
reported to augment HRV reactivity (in response to
mental stress) compared with a high-protein meal: HR
decreased more quickly poststress after the carbohydrate
meal (Uijtdehaage et al., 1994). Over a 2-day period,
Lima-Silva et al. (2010) examined the impact of a low-
carbohydrate diet in those who had been exercising.
Compared with a high-carbohydrate diet, the low-
carbohydrate diet increased LF and decreased HF
power. There were, however, no differences in HR or
RR interval. As this study considered those who had
been exercising, there is a need to look at those simply
going about their everyday life.
Nagai et al. (2005) reported that a high-fat meal increased
the VLF component of HRV. Although the physiological
processes underlying VLF-HRV are unclear, Nagai et al.
(2005) interpreted this as an indication of thermo-
regulatory sympathetic nervous system activity. Other
components of HRV may also be influenced by the
nature of dietary fat, at least in the longer term:
Soares-Miranda et al. (2012) reported that in two cohorts,
either 19 or 72 years of age, a greater consumption of
trans-fats was associated with a less favourable HRV;
SDNN, RMSSD and total power were lower.
Importantly, trans-fat consumption predicted lower HRV
5 years later.
When considering the influence of diet, by far the
majority of work has involved supplementation with
Table 1 The relation between heart-rate variability and eating behaviour
References Sample Design Outcome
Segerstrom and
Nes (2007)
168 students aged
19 years
Asked to resist eating palatable food and consume
less palatable. Then, they performed an anagram
task that needed persistence
Increase in RMSSD when eating cookies was resisted,
and carrots consumed. HRV seen as an index of self-
regulatory strength
Meule et al.
47 females aged
24 years
BMI 22
Compared those who were and were not retrained
A high HF associated with less weight fluctuation. Weight
fluctuation predicted LH/HF
Meule et al.
50 females aged
1840 years
BMI between
17.5 and 25
Compared those who were or were not currently
Successful dieting positively associated with HF and
negatively with LH/H F
Geisler et al.
111 students aged
23 years
Participants took on a task that did or did not require
self-control. Then,, they were exposed to palatable
food. Effortable self-control measures as H RV
Restrained eaters, who suppressed feelings, had higher
RMSSD when exposed to a palatable food, but not
when self-control had not been exercised. Suggested
dieting required self-control as indicated by HRV
Young and Watkins
66 females between
18 and 29 years
BMI 1731
Studied the relation between HRV and glucose
Disinhibited eaters had reduced HRV (HF and sample
entropy). Those with low HRV had poorer glucose
tolerance the levels remained higher for longer
Young et al.
156 healthy adults
from 18 to 34 years,
122 healthy adults
From 18 to 30 years
Cross sectional study asked whether diet mediated
the association between H RV and mood
Diet shown to mediate the relation between HRV (H F and
sample entropy) and mood
HF, high-frequency; HRV, heart-rate variability; LF, low-frequency.
HRV: a biomarker for health Young and Benton 145
omega-3 fatty acids. For example, in a secure forensic
inpatient facility, Hansen et al. (2014) randomly allocated
patients to a diet containing salmon three times a week
compared with meat in the control group. The changes in
HRV associated with fish consumption correlated nega-
tively with sleep latency and positively with a measure of
daily functioning. Table 2 lists a representative sample of
studies that show that research has been driven by an
interest in disease states, particularly heart disease, and
has typically involved the examination of older adults.
There is a general impression that omega-3 supple-
mentation resulted in greater parasympathetic activity,
although greater confidence in this conclusion comes
from a meta-analysis. Xin et al. (2013) integrated fifteen
studies. The time-domain measures, SDNN and
RMSSD, did not differ after supplementation. However,
although there was no effect on the frequency measure
LF, fish oil significantly increased HF. The authors
concluded that the enhancement of vagal tone may be
an important mechanism underlying the antiarrhythmic
and other clinical effects of fish oil. Similarly, the review
of Christensen and Schmidt (2007) concluded that: In
most (Billman et al., 1994; Christensen et al., 1999;
Christensen and Schmidt 2007; Billman and Harris, 2011;
Christensen, 2011), although not all, studies, dietary n-3
PUFA levels and n-3 PUFA supplementation are related
to improved HR variability. The findings suggested that
an increased parasympathetic regulation of cardiac func-
tioning occurred.
More generally, the Mediterranean diet, which has fish as
a component, is also associated with HRV. Dai et al.
(2010), using a food-frequency questionnaire, established
the extent to which middle-aged male twins ate a
Mediterranean diet. After adjusting for genetic con-
tributions, those who conformed to the Mediterranean
diet had higher HRV across a range of indices: SDNN,
RMSSD, ULF, VLF, HF and LF. Although it was
unclear which aspect of the diet was beneficial, it is
tempting to suggest that one factor is eating fish and in
this way increasing the intake of omega-3 fatty acids.
Billman (2013) reviewed the evidence that the intake of
omega-3 fatty acids influenced cardiac rhythms. He
concluded that supplementation with n3-PUFAs affects
ion channels and calcium-regulatory proteins, although
these depended on the route of administration.
Immediately, there is a direct effect of the fatty acids on
ion channels, although over the longer term, after the
incorporation of the fatty acids into the cell membrane,
cardiac electrical activity changes. HR is reduced and
HRV increases, reflecting alterations in the intrinsic
pacemaker rather than regulation by the activity of the
autonomic nervous system.
Other contributions to a Mediterranean diet have also
been found to influence HRV. In a randomized trial, the
influence of a multivitamin-mineral preparation on HRV
was assessed (Pomportes et al., 2015). Faster reactions in a
test of the ability to inhibit responses were associated
with a stable HF, indicative of PNS activity. In those
taking micronutrients, HF remained stable, whereas in
the placebo condition, HF decreased over time. Jaatinen
et al. (2014) studied the influence of yoghurt enriched
with α-lactalbumin, bioactive peptides and B vitamins in
individuals with high-trait anxiety. In the active group,
vagally mediated HRV (RMSSD) was higher. They
concluded that this yoghurt combination may aid coping
with stress. As nut consumption is associated with a lower
risk of cardiovascular disease, Sauder et al. (2014) studied
its influence on HRV. The pistachio diet was associated
with a higher HF and greater total variation in beat-to-
beat intervals. Similar effects have been observed in
relation to the consumption of polyphenol-rich red wine.
Intake of wine, but not of spirits or beer, is positively and
independently (after controlling for other health beha-
viours) associated with HRV (SDNN, total power, VLF
power, LF power and HF power) in women with CHD
(Janszky et al., 2005).
There is also some evidence that particular nutrients
influence HRV. Sucharita et al. (2014) considered HRV in a
healthy elderly Indian sample with either a high or a low
vitamin B
status. The LF was lower in those with a
poorer vitamin B
status, although no effects on HF power
or HR were observed. Supplementation for 3 months
increased LF to levels comparable to those with an initially
good vitamin B
status. Sodium intake is also linked to
HRV. In a randomized-controlled trial, Allen et al. (2014)
asked participants, with normal blood pressure, to consume
for 5 days a diet with low (10 mmol/day), normal
(150 mmol) or high (400 mmol) levels of sodium. The
response to low sodium was consistent with sympathetic
activation and reduced vagal activity; LFnu (normalized)
increased and SDNN, RMSSD and HFnu (normalized)
decreased compared with both normal and high sodium
In summary, although there has been limited systematic
study, there is a series of reports that relate various
indices of HRV to the intake of a range of food items. As
such, there is good reason to support the further con-
sideration of HRV as a biomarker with the potential to
indicate the potential influence of food on health.
There is growing evidence that a range of diseases are
accompanied by a decrease in HRV, including, amongst
others, diabetes (Yoshioka and Terasaki, 1994), cardio-
vascular disease (Gottsäter et al., 2006) and psychiatric
disorders (Kemp et al., 2014). Although indices of HRV
do not distinguish between types of disorder, there is a
consistent pattern of a reduced variability in HR being
associated with disease: a higher HRV is associated with
psychological flexibility and allostatic resilience. Indeed,
longitudinal studies support the view that reduced HRV
predicts psychological and physiological morbidity years
146 Behavioural Pharmacology 2018, Vol 29 No 2&3
Table 2 The influence of fish oil supplementation and eating fish on heart-rate variability
References Sample Design Intervention Outcome
Christensen et al. (1996) 49 patients with CAD aged 63 years Parallel 4.3 g EPA/DHA a day or placebo for
12 weeks
SDNN and mean RR increased from baseline in the active, but not the control
condition. No significant difference between active and control
Christensen et al. (1998) 17 patients with RF aged 52 years Parallel 4.7 g EPA/DHA a day or placebo for
12 weeks
High cell fatty acids associated with higher SDNN
Those with CRF had lower HRV
Christensen et al. (1999) 40 healthy individuals aged 38 years Parallel 1.68, 5.9 g EPA/DHA a day or
placebo for 12 weeks
Baseline positive correlation between SDN N, RMSSD and levels of DHA in cell.
Dose-dependent increase in HRV
Effects found in men, but not women
Dyerberg et al. (2004) 49 healthy individuals aged 38 years Parallel 3.2 g EPA/DHA a day or placebo for
8 weeks
SDNN, RMSSD, NN50, NN6% were not significantly
Holguin et al. (2005) 52 elderly individuals aged 77 years Parallel 1.55 EPA/DHA a day or placebo for
16 weeks
Supplementation increased LF, HF and RMSSD
OKeefe et al. (2006) 36 patients with CAD aged 68 years Cross-over 0.8 EPA/DHA a day or placebo for
16 weeks
Supplement increased HF and reduced HR at rest
SDNN and LF not effected
Hamaad et al. (2006) 38 patients with CAD aged 60 years Parallel 0.8 EPA/DHA a day or placebo for
16 weeks
No significant influence on SDNN, RMSSD, LF, HF and LF/HF
Radaelli et al. (2006) 25 patients with CAD aged 60 years Parallel 1.68 EPA/DHA a day or placebo for
16 weeks
Supplementation increased LF, HF, SDNN, RMSSD
Ninio et al. (2008) 46 overweight patients aged 50 years Parallel 0.8 EPA/DHA a day or placebo for
12 weeks
Supplement increased HF but did not affect LF or LF/HF. Resting HR decreased after
Nodari et al. (2009) 41 patients with Idiopathic dilated
cardiomyopathy aged 63 years
Parallel 1.44 g E PA/DHA a day or placebo for
24 weeks
The LF/HF ratio increased after supplement when under mental stress. VLF
decreased in the placebo group, but not in the active group
Carney et al. (2010) 72 depressed patients with CAD aged
57 years
Parallel 1.68 g E PA/DHA a day or placebo for
10 weeks
No effect on LF or HF
Sjoberg et al. (2010) 67 overweight patients aged 52 years Parallel 0.64, 1.28, and 1.92 g EPA/DHA a
day or placebo for 12 weeks
There was a dose-dependent reduction in the LF/ HF, although neither LH or HF was
significantly influenced
Valera et al. (2014) 180 French Polynesian adults Cross-
The DHA in red cells was related to
Increasing DHA concentrations were associated with lower HR and greater HF,
Fish intake
Mozaffarian et al. (2008) 4263 ECGs 1152 24 h holter Cross-
Eating tuna and other fish assessed
using FFQ
Eating fish associated with greater RMSSD and HF and lower LF. A lower Poincaré
ratio and higher short-term fractal scaling exponent suggested less erratic sinoatrial
node firing
Hansen et al. (2014) 95 male forensic inpatients Parallel Ate either fish or meat meals three
times a week for 6 months
Fish group showed a significant increase in HF.
The increased variability associated with fish consumption correlated negatively with
sleep latency and positively with a measure of daily functioning
Grung et al. (2015) 49 male forensic inpatients Parallel Ate either fish or meat meals three
times a week for 6 months
Principal component analysis of HRV parameters produced a parasympathetic factor
that increased when fish was eaten
CAD, coronary artery disease; CRF, chronic renal failure; DHA, docosahexaenoic acid; EPA, eicosapentaenoic acid; FFQ, food frequency questionnaire; HF, high-frequency; HR, heart rate; HRV, heart-rate variability; LF, low-
frequency; SDDN, SD of normal to normal RR.
HRV: a biomarker for health Young and Benton 147
later (Carnethon et al., 2003; Jandackova et al., 2016).
Thus, HRV may serve as a biomarker for future health.
Various aspects of diet have been found to be associated
with HRV. In general, the types of diet and particular
foods that have been found to be associated with a
healthy life-style are associated with higher HRV. For
example, a Mediterranean diet (Mozaffarian et al., 2008;
Soares-Miranda et al., 2012), fish consumption
(Mozaffarian et al., 2008), multivitamins (Pomportes et al.,
2015) and losing weight (Zulfiqar et al., 2010) all
increased HRV. However, aspects of diet that are com-
monly viewed as undesirable, for example a high fat or
trans-fat diet, reduced HRV (Soares-Miranda et al., 2012).
Although it is clear that diet influences HRV, the
mechanisms and pathways underlying such effects are
multifactorial. In relation to physical health, it is clear that
vagal tone is central to the regulation of a number of
allostatic systems, including the cardiovascular system,
glucose regulation, the hypothalamicpituitaryadrenal
axis function, and inflammatory processes (Thayer and
Sternberg, 2006; Young and Benton, 2015; Viljoen and
Claassen, 2017). Thus, reduced vagal tone may directly
contribute towards increased allostatic load (Koopman
et al., 2016). However, chronic diseases such as diabetes
contribute towards autonomic neuropathy (Vinik et al.,
2003), which is associated with reduced HRV
(Fakhrzadeh et al., 2012). Such bidirectional effects make
causality difficult to determine.
Similarly, it has been argued that vagal afferent signals
might mediate the influence that diet has on psycholo-
gical health (Kemp et al., 2017). Indeed, emerging evi-
dence suggests that cardiac interoceptive sensations
contribute towards ones mental health (Craig, 2003;
Critchley et al., 2004; Seth, 2013; Young et al., 2017b);
however, it is difficult to isolate diet-related effects on
afferent vagal signals. In addition, influential models such
as the neurovisceral integration model (Thayer and Lane,
2009) consider HRV to be the product of the CAN, which
guides goal-directed behaviour; the prefrontal cortex
plays a central inhibitory role (Thayer and Lane, 2000;
Smith et al., 2017). Thus, HRV may capture primarily
efferent vagal activity. With this in mind, it is plausible
that the effects of diet on HRV operate indirectly through
changes in mental health. That is, diet influences brain
functioning, cognition and mood, which is then reflected
in changes in HRV. Indeed, a study supports the view
that diet influences psychological health not only acutely
(Young and Benton, 2014, 2015) but also chronically
(Jacka et al., 2010). However, whether these effects
mediate or are meditated by HRV remains to be
Furthermore, the link between HRV and pathological
eating behaviours (Young and Watkins, 2016) points
towards the possibility of mutual causation. That is,
reduced HRV, by virtue of its connections with the
prefrontal cortex (Dietrich et al.,, 2006; Chang et al., 2013;
Jennings et al., 2016), may indicate a predisposition to
make poor dietary choices. In turn, a poor-quality diet
could exacerbate the reduction in HRV. In support of this
proposition, Young et al. (2017a) found that disinhibited
eating and poor diet quality were associated indepen-
dently with deficits in HRV. Notably, HRV is related
positively to interoceptive sensitivity (Ainley et al., 2012),
raising the possibility that diet-related reductions in vagal
tone may diminish the ability to detect interoceptive
signals, including information about ones current
homeostatic state (Attuquayefio et al., 2017, Smith et al.,
2017), and contribute towards mental illnesses (Paulus
and Stein, 2010). Irrespective of the mechanisms
involved, the association between HRV and so many
types of disease state suggests that it is a measure of
factors with a wide-spread significance. Thus, HRV may
serve as a useful biomarker for identifying potentially
beneficial or detrimental aspects of diet.
A distinction should be drawn between phasic and tonic
HRV as this will impinge upon interpretation of research
findings. In relation to emotion, demanding situations
may give rise to an increase or a decrease in phasic HRV.
The former might arise when an individual successfully
self-regulates to deal with the demands of the situation
(Park et al., 2014; Geisler et al., 2016) and the latter may
arise when the situation is perceived as threatening and
an individual shows an autonomic stress response
(Segerstrom and Nes, 2007).
The vast majority of research linking health and HRV has
focused on tonic resting-state HRV (Chalmers et al., 2014;
Kemp et al., 2014, 2016). Although tonic HRV predicts
phasic changes in vagal tone, lower tonic HRV was
associated with phasic HRV suppression and higher tonic
HRV was associated with phasic HRV enhancement
(Park et al., 2014). This is an important methodological
consideration when considering the effects of diet.
Phasic changes represent real-time adaptations to the
external or the internal environment; as such, a tempor-
ary decline in HRV need not necessarily be pathological.
An example can be considered in relation to the literature
on fluid consumption. Hypohydration necessitates a
counter-regulatory increase in HR to maintain blood
pressure: for every 1% decrease in body mass during
exercise, there is an increase in HR of 3.29 bpm (Adams
et al., 2014). Even in the absence of hypohydration, water
ingestion is followed by an increase in cardiac vagal
control (Helen et al., 2002). Under such circumstances, an
inability to flexibly alter the variability of HR may be
viewed as detrimental. Thus, whether tonic HRV influ-
ences ones ability to effectively counter regulate during
the postprandial period is an important question. Young
and Watkins (2016) provided the first evidence that this
might be the case: individual differences in tonic vagal
tone moderated the postprandial response to drinks that
148 Behavioural Pharmacology 2018, Vol 29 No 2&3
differed in glycaemic load. Whether a higher resting-state
HRV confers greater metabolic resilience during the
post-prandial period is an important question for future
Although we have argued that decreased HRV may serve
as a biomarker of future health, there are caveats that
need to be considered. For example, it has been
observed that black individuals have higher HRV, and
yet are at greater risk of future cardiovascular disease
(Hill et al., 2017). In addition, although most psychiatric
disorders are characterized by reduced HRV, those with
anorexia nervosa (Mazurak et al., 2011) or bulimia nervosa
(Peschel et al., 2016) tend to have parasympathetic
dominance (higher HF-HRV). Although both these
conundrums may be explained by dietary differences in
these populations for instance, there are clear racial
differences in nutritional behaviour the literature to
date has typically not explored this possibility. This will
be an important avenue for future research.
There are three types of approach by which HRV can be
measured: the linear time-based and frequency-based
approaches and also nonlinear methods. To date, limited
research has considered nonlinear methods when study-
ing diet, although there are reasons to believe that they
contribute additional information to that supplied by the
linear methods (Young and Benton, 2015). In addition,
there is some evidence that nonlinear HRV indices cap-
ture the influence of endogenous hormonal fluctuations
and thermoregulation (Bai et al., 2009; Young and
Benton, 2015), which may be pertinent when considering
the influence of diet. Thus, future studies should incor-
porate both linear and nonlinear approaches into their
In summary, the consistent relationship between HRV,
health and morbidity supports the view that HRV can be
considered an index of psychological and physiological
resilience. An increasing number of studies report that
particular foods, nutrients and dietary styles influence
HRV, supporting its future use when examining the
impact of what we eat. The insidious influence of diet
will be cumulative and take place over a period of many
decades (Benton, 2010). As such HRV may prove to be a
means for identifying beneficial or detrimental aspects of
Conflicts of interest
There are no conflicts of interest.
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HRV: a biomarker for health Young and Benton 151
... In the scientific discourse, some authors emphasize the value of HRV even as a "biomarker" [65,66] respectively as a "psychophysiological marker for physical and mental health" [64,67]. A current meta-analysis on HRV in patients with anxiety disorders found that especially resting-state HRV in patients with anxiety disorders, in general, was significantly lower than in healthy controls with a low to a medium effect size of Hedges' g 0.39 reflecting a "robust feature of anxiety disorders" ( [68], p. 9). ...
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Background Performance anxiety is the most frequently reported anxiety disorder among professional musicians. Typical symptoms are - on a physical level - the consequences of an increase in sympathetic tone with cardiac stress, such as acceleration of heartbeat, increase in blood pressure, increased respiratory rate and tremor up to nausea or flush reactions. These symptoms can cause emotional distress, a reduced musical and artistical performance up to an impaired functioning. While anxiety disorders are preferably treated using cognitive-behavioral therapy with exposure, this approach is rather difficult for treating music performance anxiety since the presence of a public or professional jury is required and not easily available. The use of virtual reality (VR) could therefore display an alternative. So far, no therapy studies on music performance anxiety applying virtual reality exposure therapy have investigated the therapy outcome including cardiovascular changes as outcome parameters. Methods This mono-center, prospective, randomized and controlled clinical trial has a pre-post design with a follow-up period of 6 months. 46 professional and semi-professional musicians will be recruited and allocated randomly to an VR exposure group or a control group receiving progressive muscle relaxation training. Both groups will be treated over 4 single sessions. Music performance anxiety will be diagnosed based on a clinical interview using ICD-10 and DSM-5 criteria for specific phobia or social anxiety. A behavioral assessment test is conducted three times (pre, post, follow-up) in VR through an audition in a concert hall. Primary outcomes are the changes in music performance anxiety measured by the German Bühnenangstfragebogen and the cardiovascular reactivity reflected by heart rate variability (HRV). Secondary outcomes are changes in blood pressure, stress parameters such as cortisol in the blood and saliva, neuropeptides, and DNA-methylation. Discussion The trial investigates the effect of VR exposure in musicians with performance anxiety compared to a relaxation technique on anxiety symptoms and corresponding cardiovascular parameters. We expect a reduction of anxiety but also a consecutive improvement of HRV with cardiovascular protective effects. Trial registration : This study was registered on ( Number: NCT05735860)
... Heart rate variability (HRV), which can be obtained in a simple and low-cost manner, has been proven to be a tool for the clinical monitoring of cardiac autonomic responses, in addition to being a biomarker for studying the autonomic nervous system (ANS) [1][2][3]. A study has suggested that a marked reduction in time indices and an increase in frequency domains could predict the development of cardiovascular diseases [4]. ...
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Background This study evaluates the heart rate variability (HRV), body composition parameters, physical activity level means by International Physical Activity Questionnaire (IPAQ), and sleep quality [means by Pittsburgh Sleep Quality Index (PSQI)] in non-obese, overweight, and obese individuals. Methods 51 adults were included in this study. The age of the participants ranged from 18 to 39 years old, and they underwent vital signs measurement, nutritional status classification means body mass index (BMI), and body composition through the bioelectrical impedance (BIA), questionnaires (IPAQ and PSQI), and HRV measurement. Results The most influenced body composition variables in the normal weight, overweight, and obese groups were age, body weight, BMI, resting metabolic rate, visceral fat level (VFL), skeletal muscle mass, body fat mass (BFM), body fat percentage, and minerals with p < 0.05, for all comparisons. The stress index (SI) was the HRV variable most influenced by different levels of BMI p < 0.05. The PSQI was more influenced by body water, lean mass, fat-free mass, and proteins, with p < 0.05. Furthermore, SI was the only HRV index that negatively correlated (r = − 0.395; p < 0.05) with physical activity (PA) and BFM (r = − 0.409; p < 0.05). Conclusion Obesity increases stress and sleep disturbance and is reduced with increased PA levels. In addition, PA level was negatively associated with SI and BFM.
... For instance, a Mediterranean diet, omega-3 fatty acids, B-vitamins, probiotics, polyphenols, and weight loss have all been associated with improved HRV. Conversely, dietary factors considered unfavorable, such as high intakes of saturated or trans fats and high glycemic carbohydrates, have been found to reduce HRV [31]. HRV has been found to be associated with levels of C-reactive protein (CRP) in the blood. ...
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The number of people experiencing mental stress or emotional dysfunction has increased since the onset of the COVID-19 pandemic, as many individuals have had to adapt their daily lives. Numerous studies have demonstrated that mental health disorders can pose a risk for certain diseases, and they are also closely associated with the problem of mental workload. Now, wearable devices and mobile health applications are being utilized to monitor and assess individuals’ mental health conditions on a daily basis using heart rate variability (HRV), typically measured by the R-to-R wave interval (RRI) of an electrocardiogram (ECG). However, portable or wearable ECG devices generally require two electrodes to perform bipolar limb leads, such as the Einthoven triangle. This study aims to develop a single-arm ECG measurement method, with lead I ECG serving as the gold standard. We conducted static and dynamic experiments to analyze the morphological performance and signal-to-noise ratio (SNR) of the single-arm ECG. Three morphological features were defined, RRI, the duration of the QRS complex wave, and the amplitude of the R wave. Thirty subjects participated in this study. The results indicated that RRI exhibited the highest cross-correlation (R = 0.9942) between the single-arm ECG and lead I ECG, while the duration of the QRS complex wave showed the weakest cross-correlation (R = 0.2201). The best SNR obtained was 26.1 ± 5.9 dB during the resting experiment, whereas the worst SNR was 12.5 ± 5.1 dB during the raising and lowering of the arm along the z-axis. This single-arm ECG measurement method offers easier operation compared to traditional ECG measurement techniques, making it applicable for HRV measurement and the detection of an irregular RRI.
... Heart rate variability (HRV) could reflect the regulation of the autonomic nervous system and the balance between sympathetic and parasympathetic nervous activity. Stud-ies have shown that HRV is useful for reflecting changes in autonomic nervous system tone [78]. A meta-analysis of the 717 POTS patients and 641 healthy controls showed that the time domain measures of HRV in POTS patients were lower than those in controls [79]. ...
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Postural orthostatic tachycardia syndrome (POTS) is common in children, with an excessive increment in heart rate when moving from the supine to upright position. It has significant negative impacts on the daily life of pediatric patients. The pathogenesis of POTS includes peripheral vascular dysfunction, central hypovolemia, abnormal autonomic function, a high-adrenergic state, impaired skeletal-muscle pump function, the abnormal release of vasoactive factors, and autoimmune abnormalities. Therefore, the empirical use of pharmacological treatments has limited therapeutic efficacy due to the diversity of its mechanisms. A crucial aspect of managing POTS is the selection of appropriate treatment targeting the specific pathogenesis. This review summarizes the commonly used pharmacological interventions, with a focus on their predictive indicators for treatment response. Factors such as heart rate variability, plasma biomarkers, and cardiac-function parameters are discussed as potential predictors of therapeutic efficacy, enabling the implementation of individualized treatment to improve therapeutic effectiveness. This review consolidates the current knowledge on POTS, encompassing its clinical characteristics, epidemiological patterns, underlying pathogenic mechanisms, and predictive indicators for treatment response. Further research is warranted to enhance the understanding of POTS and facilitate the development of more effective therapeutic approaches for this challenging syndrome.
... The short-term heart rate variability (HRV), i.e., oscillations of heart rate around its mean value, in humans is predominantly mediated by parasympathetic regulation. From the time series analysis tools, linear methods are traditionally used, especially the spectral power in the high frequency band (HF-HRV) reflecting the cardiovagal modulation [6][7][8][9][10][46][47][48]. In this context, symbolic dynamics -as nonlinear HRV analysis -is considered as a promising tool to study cardiac sympathetic regulation. ...
Mobile wireless communication technologies have now become an everyday part of our lives, 24 hours a day, 7 days a week. Monitoring the autonomous system under exposition to electromagnetic fields may play an important role in broading of our still limited knowledge on their effect on human body. Thus, we studied the interaction of the high frequency electromagnetic field (HF EMF) with living body and its effect on the autonomic control of heart rate using Heart Rate Variability (HRV) linear and nonlinear analyses in healthy volunteers. A group of young healthy probands (n=30, age mean: 24.2 ± 3.5 years) without any symptoms of disease was exposed to EMF with f=2400 MHz (Wi Fi), and f=2600 MHz (4G) for 5 minutes applied on the chest area. The short-term heart rate variability (HRV) metrics were used as an indicator of complex cardiac autonomic control. The evaluated HRV parameters: RR interval (ms), high frequency spectral power (HF-HRV in [ln(ms2)]) as an index of cardiovagal control, and a symbolic dynamic index of 0V %, indicating cardiac sympathetic activity. The cardiac-linked parasympathetic index HF-HRV was significantly reduced (p =0.036) and sympathetically mediated HRV index 0V % was significantly higher (p=0.002) during EMF exposure at 2400 MHz (Wi-Fi), compared to simulated 4G frequency 2600 MHz. No significant differences were found in the RR intervals. Our results revealed a shift in cardiac autonomic regulation towards sympathetic overactivity and parasympathetic underactivity indexed by HRV parameters during EMF exposure in young healthy persons. It seems that HF EMF exposure results in abnormal complex cardiac autonomic regulatory integrity which may be associated with higher risk of later cardiovascular complications already in healthy probands.
... 6 A lower HRV is generally associated with an increased risk of cardiovascular disease, including aging, obesity, hypertension, and diabetes, higher levels of stress and reduced overall resilience. 7 A recent systematic review of 33 studies found that PA interventions can have a positive effect on various outcomes, including mental health, physical fitness and quality of life, among college students and other populations during the COVID-19 pandemic. 8 However, most of these studies examined traditional forms of PA, such as aerobic exercise, strength training and yoga, rather than Tai Chi (TC). ...
Background: COVID-19 restrictions have further reduced college students’ opportunities for physical activity (PA), and problems related to physical and physiological health of college students have become increasingly serious. Studying the effect of Tai Chi (TC) on body composition and heart rate variability can provide insights into the potential benefits of TC as a form of exercise. Objectives: The aim of this study was to assess the effects of 6-week 24-forms Yang-style Tai Chi (YTC) on body composition and heart rate variability (HRV) among college students. Materials and methods: This single-arm, single-blind, pilot study enrolled 6 beginners from 25 individuals. Body composition and HRV were assessed at the beginning and end of the YTC exercise intervention. The intervention was performed twice a week for 6 weeks, each session lasting 45 minutes and consisting of warming-up, practice, and cooling-down exercises during the COVID-19 pandemic. Results: After 6-week TC exercise, BMI (21.00±2.61 to 21.20±2.62 kg/m2) barely changed (p>0.05), while body fat mass, skeletal muscle mass, and basal metabolic rate showed a significant change (p<0.05). In addition, the high frequency (6.68±0.40 to 7.05±0.50 nu) of heart rate variability had a positive significant increase (p<0.05). Conclusion: The 6-week TC practice had the benefit of improving HRV, such as high-frequency (HF), in college students, but further research is needed to identify the long-term effects of TC on body composition and HRV during the COVID-19 epidemic.
The pulse oximeter is a personal health monitoring device that measures the heart rate and the blood's oxygen saturation level. Heart rate gives useful information, but heart rate variability (HRV) offers much additional information. More and more research should be conducted to develop advanced pulse oximeter-type devices that can also provide HRV compression and exercise effect analysis for personal health monitoring. Focusing the present time needs, this research utilized a low-cost photoplethysmogram (PPG) sensor and an advanced (IoT and AI-friendly) programming language Python. It presented the methodology for comparing signals during different tasks (psychological/physical/exercises) for personal health monitoring. This methodology validated the features like HRV and fast Fourier transform (FFT), so these features could be present in future devices for advanced personal health monitoring. In the comparative analysis of different conditions/tasks/exercises, there was a visible difference in signal graphs due to the effects of psychological and/or physical tasks. The numerical results were also different for different conditions validating the reliability of the methodology. The programming language used is open source and highly advanced. This methodology will help in the development of new advanced devices and other signal analysis research, such as personal health monitoring using a comparative analysis of HRV during various mental tasks and exercises.
Background: The causal relationship between heart rate variability and cardiovascular diseases and the associated events is still unclear, and the conclusions of current studies are inconsistent. We aimed to explore the relationship between heart rate variability and cardiovascular diseases and the associated events with the Mendelian randomization study. Methods: We selected normal-to-normal inter-beat intervals (SDNN), root mean square of the successive differences of inter-beat intervals (RMSSD) and peak-valley respiratory sinus arrhythmia or high-frequency power (pvRSA/HF) as the three sets of instrumental variables for heart rate variability. The outcome for cardiovascular diseases included essential hypertension, heart failure, angina pectoris, myocardial infarction, nonischemic cardiomyopathy and arrhythmia. Cardiac arrest, cardiac death and major coronary heart disease event were defined as the related events of cardiovascular diseases. The data for exposures and outcomes were derived from publicly available genome-wide association studies. Inverse variance weighted was used for the main causal estimation. Analyses of heterogeneity and pleiotropy were conducted using the Cochran Q test of Inverse variance weighted and MR-Egger, leave-one-out analysis, and MR-Pleiotropy Residual Sum and Outlier methods. Results: The Inverse variance weighted method indicated that genetically predicted pvRSA/HF was associated with the increased risk of cardiac arrest (odds ratio 2.02, 95% confidence interval 1.25-3.28, p = .004). The results were free of heterogeneity and pleiotropy. There were no outliers and the leave-one-out analysis proved that the results were reliable. Conclusions: This study provides genetic evidence that pvRSA/HF is causally related to cardiac arrest.
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Background Performance anxiety is the most frequently reported anxiety disorder among professional musicians. Typical symptoms are - on a physical level - the consequences of an increase in sympathetic tone with cardiac stress, such as acceleration of heartbeat, increase in blood pressure, increased respiratory rate and tremor up to nausea or flush reactions. These symptoms can cause emotional distress, a reduced musical and artistical performance up to an impaired functioning. While anxiety disorders are preferably treated using cognitive-behavioral therapy with exposure, this approach is rather difficult for treating music performance anxiety since the presence of a public or professional jury is required and not easily available. The use of virtual reality could therefore display an alternative. So far, no therapy studies on music performance anxiety applying virtual reality exposure therapy have investigated the therapy outcome including cardiovascular changes as outcome parameters. Methods This mono-center, prospective, randomized and controlled clinical trial has a pre-post design with a follow-up period of 6 months. 46 professional and semi-professional musicians will be recruited and allocated randomly to an VR exposure group or a control group receiving progressive muscle relaxation training. Both groups will be treated over 4 single sessions. Music performance anxiety will be diagnosed based on a clinical interview using ICD-10 and DSM-5 criteria for specific phobia or social anxiety. A behavioral assessment test is conducted three times (pre, post, follow-up) in VR group through an audition in a concert hall. Primary outcomes are the changes in music performance anxiety measured by the German Bühnenangstfragebogen and the cardiovascular reactivity reflected by heart rate variability (HRV). Secondary outcomes are changes in blood pressure, stress parameters such as cortisol in the blood and saliva, neuropeptides, and DNA-methylation. Discussion The trial investigates the effect of VR exposure in musicians with performance anxiety compared to a relaxation technique on anxiety symptoms and corresponding cardiovascular parameters. We expect a reduction of anxiety but also a consecutive improvement of HRV with cardiovascular protective effects. Trial registration This study was registered on ( Number: NCT05735860)
Background & Aims: The role of nutrition in modulating the inflammatory response is increasingly recognized. The phytonutrient sulforaphane shows promise for clinical use due to its effect on inflammatory pathways, favorable pharmacokinetic profile, and high bioavailability. The inflammatory status has been linked to autonomic activity, which can be assessed by the study of heart rate variability (HRV). However, monitoring of HRV for assessment of inflammation in humans has hardly been used. We investigated the potential of HRV as a non-invasive tool to monitor inflammation induced by the caloric load and assessed the effects of sulforaphane on caloric load-induced inflammation in healthy participants. Methods: In this double-blind, crossover, randomized, placebo-controlled trial twelve healthy participants (26.9 (3.6) years) were administered 25 mg of sulforaphane, or placebo followed over 90 min by the standardized high-calorie drink PhenFlex given to induce an inflammatory response. Levels of high-sensitivity C-reactive protein (hs-CRP) and interleukin (IL)-6 were measured in plasma before and two hours after the PhenFlex challenge. Changes in the autonomic function were assessed by HRV on four timepoints. Results: The caloric challenge triggered a significant increase in total power (TP) (P = 0.028) and very low frequency (VLF) component (P = 0.013) 30 min after its administration. Those changes were followed by reduction of TP (P = 0.028) and low frequency (LF) component (P = 0.005), suggesting marked decrease in the sympathetic activity two hours after the caloric load. When sulforaphane was given prior to the caloric challenge, decreased parasympathetic activity was observed via a reduction of RMSSD (P = 0.007), pNN50 (P = 0.013) and HF (P = 0.047). In addition, sulforaphane elicited a pro-inflammatory response as measured by the change of hs-CRP with caloric exposure (sulforaphane 2.7 (4.2) vs. placebo -1.8 (3.1) ng/mL, P = 0.048). The pro-inflammatory effect of sulforaphane was associated with vagal withdrawal and sympathetic dominance as suggested by correlations between the changes in hs-CRP and HF (rs = -0.68, P = 0.029) as well as LF/HF (rs = 0.56, P = 0.093) components assessed before and two hours after the PhenFlex challenge. Conclusions: Monitoring of HRV might be a sensitive tool to follow activity of the inflammatory response in various clinical conditions. The standardized caloric PhenFlex challenge induced significant changes in the autonomic regulation in healthy young individuals. Administration of sulforaphane prior to the caloric challenge caused a pro-inflammatory effect which was accompanied by vagal withdrawal and sympathetic dominance. Trial registration number: NCT05146804 at
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According to estimates from Public Health England, by 2034 70% of adults are expected to be overweight or obese, therefore understanding the underpinning aetiology is a priority. Eating in response to negative affect contributes towards obesity, however, little is known about the underlying mechanisms. Evidence that visceral afferent signals contribute towards the experience of emotion is accumulating rapidly, with the emergence of new influential models of 'active inference'. No longer viewed as a 'bottom up' process, new intero-ceptive facets based on 'top down' predictions have been proposed, although at present it is unclear which aspects of interoception contribute to aberrant eating behaviour and obesity. Study one examined the link between eating behaviour, body mass index and the novel interoceptive indices; interoceptive metacognitive awareness (IAw) and interoceptive prediction error (IPE), as well as the traditional measures; interoceptive accuracy (IAc) and interoceptive sensibility (IS). The dissociation between these interoceptive indices was confirmed. Emotional eaters were characterised by a heightened interoceptive signal but reduced meta-cognitive awareness of their interoceptive abilities. In addition, emotional eating correlated with IPE; effects that could not be accounted for by differences in anxiety and depression. Study two confirmed the positive association between interoceptive accuracy and emotional eating using a novel unbiased heartbeat discrimination task based on the method of constant stimuli. Results reveal new and important mechanistic insights into the processes that may underlie problematic affect regulation in overweight populations.
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In animals, a Western style diet–high in saturated fat and added sugar–causes impairments in hippocampal-dependent learning and memory (HDLM) and perception of internal bodily state (interoception). In humans, while there is correlational support for a link between Western-style diet, HDLM, and interoception, there is as yet no causal data. Here, healthy individuals were randomly assigned to consume either a breakfast high in saturated fat and added sugar (Experimental condition) or a healthier breakfast (Control condition), over four consecutive days. Tests of HDLM, interoception and biological measures were administered before and after breakfast on the days one and four, and participants completed food diaries before and during the study. At the end of the study, the Experimental condition showed significant reductions in HDLM and reduced interoceptive sensitivity to hunger and fullness, relative to the Control condition. The Experimental condition also showed a markedly different blood glucose and triglyceride responses to their breakfast, relative to Controls, with larger changes in blood glucose across breakfast being associated with greater reductions in HDLM. The Experimental condition compensated for their energy-dense breakfast by reducing carbohydrate intake, while saturated fat intake remained consistently higher than Controls. This is the first experimental study in humans to demonstrate that a Western-style diet impacts HDLM following a relatively short exposure–just as in animals. The link between diet-induced HDLM changes and blood glucose suggests one pathway by which diet impacts HDLM in humans.
Heart rate variability (HRV) indexes functioning of the vagus nerve, arguably the most important nerve in the human body. The Neurovisceral Integration Model has provided a structural framework for understanding brain-body integration, highlighting the role of the vagus in adaptation to the environment. In the present paper, we emphasise a temporal framework in which HRV may be considered a missing, structural link between psychological moments and mortality, a proposal we label as Neurovisceral Integration Across a Continuum of Time (or NIACT). This new framework places neurovisceral integration on a dimension of time, highlighting implications for lifespan development and healthy aging, and helping to bridge the gap between clearly demarcated disciplines such as psychology and epidemiology. The NIACT provides a novel framework, which conceptualizes how everyday psychological moments both affect and are affected by the vagus in ways that have long-term effects on mortality risk. We further emphasize that a longitudinal approach to understanding change in vagal function over time may yield novel scientific insights and important public health outcomes.
Background: Uncertainty often exists about the comparability of results obtained by different health risk indicator systems. Objectives: To compare two health risk indicator systems, i.e, allostatic load and heart rate variability (HRV). Additionally, to investigate the feasibility of inclusion of HRV indicators into allostatic load assessments and which HRV indicators are best to introduce. Methods: Allostatic loads were calculated based on blood pressure, waist-to-hip ratio, BMI, cholesterol, HDL-C, LDL-C, CRP, albumin, glycosylated haemoglobin, blood glucose and cortisol excretion. Allostatic load scores were compared to HRV results obtained by frequency domain, time domain and Poincaré analyses. Results: Negative correlations were found between allostatic loads and total HRV, for all periods and all HRV analytical techniques (r=-0.67, p=0.0001 to r=-0.435, p=0.035), and between allostatic loads and vagal measures of HRV for supine (r=-0.592, p=0.001 to r=-0.584, p=0.001) and the first 5 minutes standing (r=-0.443, p=0.021 to r=-0.407, p=0.035), with all HRV techniques. Heart rate responses declined with increases in allostatic loads. Conclusion: HRV and allostatic load scores give comparable results as health risk indicators. Baseline total HRV and vagal, rather than sympathetic, measures of HRV should be introduced into allostatic load assessments. Results are in line with the concept of vagal tone as a regulator of allostatic systems. Inclusion of heart rate responses to orthostatic stress, into allostatic load assessments, warrants further investigation.
Purpose: Increased left ventricular mass (LVM) is an early precursor of target organ damage due to hypertension. Diminished parasympathetic cardiac control has been linked to both hypertension onset and left ventricular impairment; however, emerging evidence suggests that this pattern may be different in African Americans. The present study sought to determine if race impacts the relationship between parasympathetic cardiac control and LVM. Methods: LVM was assessed via echocardiography in a sample (N = 148) of African American and White adults (Mean age = 33.20 ± 5.71) with normal or mildly elevated blood pressure. Parasympathetic cardiac control was assessed by a measure of high frequency heart rate variability (HF-HRV) determined from electrocardiographic (ECG) recordings during 5 min of rest. Results: In regression analysis, greater HF-HRV was associated with greater LVM among African Americans (P = 0.002), but was not related to LVM in Whites (P = 0.919). Conclusions: These are the first data to demonstrate that race moderates the relationship between HRV and LVM and further suggest that race may be an important factor in the association between parasympathetic cardiac control and other CVD risk factors. This article is protected by copyright. All rights reserved.
Theoretical perspectives posit that heart-rate variability (HRV) reflects self-regulatory capacity and therefore can be employed as a bio-marker of top-down self-regulation (the ability to regulate behavioral, cognitive, and emotional processes). However, existing findings of relations between self-regulation and HRV-indices are mixed. To clarify the nature of such relations, we conducted a meta-analysis of 123 studies (N = 14,347) reporting relations between HRV-indices and aspects of top-down self-regulation (e.g., executive functioning, emotion regulation, effortful control). A significant, albeit small, effect was observed (r = 0.09) such that greater HRV was related to better top-down self-regulation. Differences in relations were negligible across aspects of self-regulation, self-regulation measurement methods, HRV computational techniques, at-risk compared with healthy samples, and the context of HRV measurement. Stronger relations were observed in older relative to younger samples and in published compared to unpublished studies. These findings generally support the notion that HRV-indices can tentatively be employed as bio-markers of top-down self-regulation. Conceptual and theoretical implications, and critical gaps in current knowledge to be addressed by future work, are discussed.
Background: Heart rate variability (HRV) has been suggested reduced in bipolar disorder (BD) compared with healthy individuals (HC). This meta-analysis investigated: HRV differences in BD compared with HC, major depressive disorder or schizophrenia; HRV differences between affective states; HRV changes from mania/depression to euthymia; and HRV changes following interventions. Methods: A systematic review and meta-analysis reported according to the PRISMA guidelines was conducted. MEDLINE, Embase, PsycINFO, The Cochrane Library and Scopus were searched. A total of 15 articles comprising 2534 individuals were included. Results: HRV was reduced in BD compared to HC (g=-1.77, 95% CI: -2.46; -1.09, P<0.001, 10 comparisons, n=1581). More recent publication year, larger study and higher study quality were associated with a smaller difference in HRV. Large between-study heterogeneity, low study quality, and lack of consideration of confounding factors in individual studies were observed. Conclusions: This first meta-analysis of HRV in BD suggests that HRV is reduced in BD compared to HC. Heterogeneity and methodological issues limit the evidence. Future studies employing strict methodology are warranted.
Consistently it has been reported that a depressed mood and low heart rate variability (HRV) are linked. However, studies have not considered that the association might be explained by dietary behaviour. The resting inter-beat interval data of 266 adults (Study 1: 156 (51 M), Study 2: 112 (38 M)) were recorded for six minutes and quantified using linear (HF power: 0.15–0.4 Hz) and nonlinear indices (Sample entropy). Participants also completed the Profile of Mood States and the Three Factor Eating questionnaires. The Alternative Healthy Eating Index was used to quantify diet quality. In study 1 mood was associated with HRV; an effect partially mediated by diet. Study 2 replicated the finding: disinhibited eating (the tendency to lose control over one’s eating) and diet sequentially mediated the association between mood and HRV. Diet plays a role in the link between mood and HRV and studies should consider the influence of this factor.