Exercise and the Cortisol Awakening Response: A Systematic Review
Anderson and Wideman Sports Medicine - Open
Exercise and the Cortisol Awakening Response: A Systematic Review
Travis Anderson 0
Key Points 0
0 University of North Carolina at Greensboro , Greensboro, NC 27412 , USA
Background: The cortisol awakening response (CAR) has been used as a biomarker of stress response in a multitude of psychological investigations. While a myriad of biochemical responses have been proposed to monitor responses to exercise training, the use of CAR within the exercise and sports sciences is currently limited and is a potentially underutilized variable. Therefore, the purpose of this review was to collate studies that incorporate both exercise and CAR, in an effort to better understand (a) whether CAR is a useful marker for monitoring exercise stress and (b) how CAR may be most appropriately used in future research. Methods: A systematic review of the literature was conducted, following PRISMA guidelines. Searches were conducted using PubMed, SportDISCUS, Scopus, and PsychInfo databases, using search terms related toCAR and exercise and physical activity. Results: 10,292 articles were identified in the initial search, with 32 studies included in the final analysis. No studies investigated the effects of laboratory-controlled exercise on CAR. Variable effects were observed, possibly due to inconsistencies in study design, methodology, population, and CAR analysis. The available literature suggests a threshold of exercise may be required to alter the HPA axis and affect CAR. Moreover, CAR may represent a combination of previous exercise load and upcoming stress, making current interpretation of field-based observational research challenging. Conclusions: More research is needed to fully elucidate the influence of exercise on CAR and address a number of gaps in the literature, including controlling exercise load, consistent sample collection, and CAR calculation and analysis.
Biomarker; Stress; Athletes; Monitoring; Overtraining
There is sufficient evidence for the continued
investigation of CAR as a potential biomarker for
exercise-related monitoring, both in athletes and the
Currently, the discrepancies observed in the literature
make interpretation of the findings and future
To confirm CAR as an appropriate biomarker for use
in exercise response or overtraining monitoring, it is
essential that future studies follow recommended
guidelines for utilizing and reporting CAR, as
discussed in this review.
Monitoring the physiological responses to exercise is critical
for exercise scientists in all facets of the discipline. While
numerous physiological responses (e.g., resting heart rate [
], HR variability [
], and inflammatory markers ) have
been investigated for their potential use as a monitoring tool
of physical stress in exercise or as indicators of
overreaching/overtraining, a single variable capable of acting as an
indicator of exercise-induced physical stress has remained
elusive. Although the search for a single marker that
captures an athlete’s stress or recovery continues, the likelihood
of such a marker being identified is low. Therefore, many
researchers have increased interest in a composite marker
of stress that may represent, in a more comprehensive
manner, the degree of physical stress experienced by an athlete
or exercising individual. Even so, each component of such a
composite marker must be individually studied and assessed
for potential inclusion in the model.
The hypothalamic-pituitary-adrenal (HPA) axis is
principally controlled through corticotropin-releasing hormone
(CRH) secretion from the hypothalamus. AVP (arginine
vasopressin) may also act synergistically with CRH to
stimulate adrenocorticotropin hormone (ACTH) synthesis
and secretion from the anterior pituitary. The increased
ACTH concentration then activates adrenocorticotropic
receptors on the adrenal cortex to stimulate secretion of the
steroid hormone cortisol. Circulating cortisol consists of
primarily the bound, inactive form of the hormone, while
5–10% is unbound and biologically active and plays a
prominent role in a variety of functions, including
metabolic, immune responses and psychological effects through
binding to cytoplasmic glucocorticoid receptors.
Due to this hormonal cascade, cortisol concentrations
are controlled by the secretion and synchrony of CRH
and AVP, which, during periods of low stress, are
secreted in a pulsatile manner approximately 2–3 times
per hour. As the hormonal end product, cortisol acts in
a negative feedback manner, suppressing activity at the
hippocampus, hypothalamus, and pituitary glands [
Cortisol shows strong diurnal variation, peaking
following quiescence (i.e., shortly after waking) [
diurnal pattern is controlled by a complex set of
interactions initiated by the so-called biological clock in the
suprachiasmatic nucleus (SCN) of the hypothalamus. In
brief, there exists a self-oscillating transcriptional loop in
the nucleus of SCN cells. A circadian locomotor output
cycle kaput (CLOCK) and brain-muscle-arnt-like protein
1 (Bmal-1) heterodimer binds to DNA response elements
to stimulate the expression of periods and cryptochromes,
which phosphorylate and negatively feedback on CLOCK
and Bmal-1 to prevent further gene expression [
cycle which takes approximately 24 h [
]. The SCN also
incorporates external feedback, such as light exposure via
the optic nerves. Although the HPA axis and circadian
rhythmicity are intricately linked, a complete review of the
interactions between the HPA axis and the master
circadian CLOCK systems are well beyond the scope of this
exercise and CAR-related review. Interested readers are
encouraged to consult several comprehensive reviews
available on this topic (see Nadar et al. [
], Nicolaides et
], and Wiley et al. [
During acute stress, a dramatic increase in CRH and
AVP pulsatility will ultimately increase circulating
cortisol concentrations. Exercise serves as such a stressor,
resulting in the aforementioned higher-order brain
centers recognizing a threat to homeostasis and
responding accordingly. As such, cortisol is a common
biomarker that is used in the analysis of exercise
responses in both elite athletes and clinical populations.
Interestingly, elevations in acute and basal cortisol
concentrations in response to stress are believed to be
detrimental to health, while elevations in acute and basal
cortisol levels in response to chronic exercise are
thought to be beneficial. The mechanism related to this
exercise-cortisol paradox has been speculated to be
partially linked to medial prefrontal cortex dopamine levels
and glucocorticoid receptors, but most of this evidence
is limited to animal studies (see Chen et al. [
review). While it is well known that cortisol
concentrations will increase in response to acute exercise, it is
important to note that this occurs only when appropriate
intensity thresholds have been achieved [
The primary function of cortisol secretion in response
to exercise is to increase the availability of substrates for
metabolism, both during the activity [
] and into
]. It has been shown that cortisol may then
exhibit a “rebound” effect and remain depressed for 24–
48 h after exhaustive exercise [
]. This disruption to
the HPA axis has implicated cortisol as a potential
biomarker for diagnosing overtraining, although this effort
has yet to yield consistent findings [
exercise training may influence acute HPA responses to
exercise, decreasing pituitary sensitivity to negative feedback
] or increasing peripheral tissue-level sensitivity to
]. There is also significant research on the role
of cortisol in obesity (see Rodriguez et al. [
] for review).
Somewhat paradoxically and despite the role of cortisol as
a primary lipolytic hormone, elevations in cortisol can
result from an elevated body fat content (see McMurray
and Hackney [
] for review), thus suggesting that
changes in resting cortisol concentrations may be of
interest in monitoring effectiveness of exercise and weight loss
programs, especially in individuals who are obese.
In addition to the diurnal pattern of cortisol secretion,
a distinct rise in cortisol has been observed immediately
after waking [
], typically peaking 30–45 min after
], and has been appropriately termed the cortisol
awakening response (CAR). This response is a
neuroendocrine manifestation of the HPA axis, considered to be
superimposed over the regular diurnal cortisol rhythm
], and has been demonstrated to be sensitive to a host
of psychological conditions and stressors. CAR is
believed to act as a “boosting” mechanism, to aid in
physiologically preparing one for waking somatic tasks
]. This rationale is primarily due to CAR being
present independent of postural condition [
] and use
of an alarm clock [
]. While light does appear to affect
the response [
], the absence of optical stimuli does
not seem to eliminate the response entirely. Thus, the
act of waking may be considered to be an event that
disrupts homeostasis [
], resulting in increased pulsatile
frequency at the hypothalamus and culminating with
increased cortisol secretion. The hippocampus has been
touted as playing a “central role” in regulating CAR [
while several other brain regions have been implicated
in the fine-tuning of CAR, including the limbic system.
There have been a number of methods developed for
assessing CAR that are worth briefly discussing. As is
standard in a range of endocrine research areas,
especially those that include a specific time series,
researchers often calculate the area under the curve of the
cortisol awakening response (AUC), typically over 1–4
measures taken after the initial awakening event. This
can be calculated using two predominate AUC methods
]: the AUC can be represented relative to a 0
concentration point (termed AUC relative to the ground
[AUCg]) and/or AUC that reflects only the increase in
concentration observed (AUCi). Thus, AUCg represents
the total hormonal exposure, while AUCi is the total
increase in exposure following waking.
Although it is currently unknown whether CAR and
AUCg or AUCi reflect dissimilar physiological
phenomena, these markers can show disparate responses to the
same intervention. In addition to exposure measures,
there are several other approaches to examining CAR,
including the relative increase in cortisol, calculated as a
percent increase above the first sample concentration
(CAR%). Researchers may also calculate the mean
increase (MnInc) by averaging the increased cortisol
concentrations above the first sample concentration, the
morning cortisol peak (CMP), or mean morning cortisol
(i.e., the mean of serial morning samples in the
awakening period; CARμ). Also frequently assessed is the
calculated slope of the CAR response, typically between
the first sample and peak (CARslope). Lastly, contrast
effects (e.g., linear or quadratic) can be used to assess
the shape, or change in shape, of CAR. As is often the
case when hormones are investigated, there appears to
be significant inter-individual variability in both the
cortisol profile and CAR in response to physical stress.
However, the CAR response within a given individual
seems to be consistent [
], as long as confounding
variables are properly controlled, such as time of waking,
sex, and age (see Clow et al. [
] for detailed review of
Until recently, a vast majority of CAR research has
occurred in the psychobiological literature, where CAR has
been related to burnout [
], chronic fatigue, and stress
]; depression ; and post-traumatic stress
]. Although normative ranges have been
developed for several populations [
], it is still unclear
what may constitute a “healthy” CAR, as both elevated
and depressed responses have been related to
dysfunctional psychosocial health status [
These changes in CAR in relation to psychological
stress raises the possibility of CAR also being an
appropriate measure to monitor responses to physiological
stressors (i.e., exercise). The benefits of a biomarker such
as CAR are severalfold. Firstly, measures can be obtained
via saliva which is less invasive to obtain as compared to
biomarkers obtained from plasma or serum. Secondly,
and in contrast to other assessments of overstrain which
require an athlete to complete multiple exercise sessions
], the measures can be obtained at rest, greatly
reducing subject burden. Lastly, the multitude of factors that
are thought to affect CAR could confer a potential
marker of global stress (e.g., allostatic load), which may
be more important for monitoring health or potential of
burnout or overtraining in athletes. Since the
symptomology of the overtraining syndrome includes
psychosocial disturbances which accompany the depreciation of
physiological factors, CAR may be useful in monitoring
both components simultaneously.
Presently, the use of CAR in the exercise science
literature has been limited and variable. Therefore, the
purpose of this review was to collate the results of
studies that have investigated the impact of exercise or
physical activity on CAR, in an effort to understand how
this biomarker could be better utilized in the exercise
and sports science fields.
A systematic review of the literature was conducted with
the collection of articles concluding on November 4,
2016. The PRISMA guidelines for systematic reviews
and meta-analyses were followed [
], except where not
applicable. Searches were completed via the electronic
search databases PubMed, SPORTDiscus, PsychINFO,
and Scopus to identify publications that included
markers of CAR and physical activity, exercise, and/or
physical fitness. The search terms utilized were all
possible combinations of terms from List 1 and List 2
(Table 1). In addition, previous review articles and
relevant publications were also analyzed for any citations
which may meet inclusion criteria. Due to the novelty of
CAR within the exercise science literature, no
restrictions in the search terms were used, such as date ranges
or place of publication; however, only articles written in
English were included in analysis. All searches were
completed November 4–5, 2016.
The first screening of the articles excluded studies based
on the relevance of the title of the publication, the second
screening excluded studies based on a reading of the
abstract, and the third screening excluded studies based on a
reading of the full text. To be eligible for inclusion, studies
needed to be primary, peer-reviewed research. In addition,
studies must have had at least one marker of CAR and an
objective measure of physical activity, exercise, or physical
fitness. In the event that data was not available in the
manuscript, efforts were made to contact the
corresponding author to acquire the necessary data. Inclusion in the
study was not limited by study design, length of
intervention, or CAR methodology.
This review had two primary aims: (1) to summarize
the current state of CAR in regards to exercise and
physical activity and its potential use as an
exerciserelated biomarker and (2) to provide recommendations
to researchers for future exercise and CAR studies. It is
important to note that the authors originally intended
this review to result in a meta-analysis of alterations in
CAR in response to both acute and prolonged exercise
protocols. However, due to the limited number of
studies, disparate protocols, and outcome variables;
range of populations studied; and variable statistical
analyses used, it was determined that attempts to
summarize the findings in these studies would not result
in any further clarification of the influence of exercise
on CAR. Therefore, no aggregated data were used in any
statistical analyses, nor were any inter-study composite
measures reported in the present study.
A total of 10,292 articles were identified in the initial
search. Following the subsequent screenings, 32 articles
were included in the review (Fig. 1).
Of the articles included, 11 articles concerned athletic
populations, and a single article addressed a military
population. The remaining studies included a variety of
populations, including psychiatric illness (n = 3),
children and adolescents (n = 5), older adults (n = 6),
and obese populations (n = 2).
Articles included in this analysis showed four distinct
types of exercise and physical activity measures: (a)
responses to exercise intervention ≥ 1 week (Table 2,
n = 13); (b) response to a single exercise bout (Table 3,
n = 2); (c) relationships to physical activity (Table 4,
n = 12); and (d) response to upcoming exercise stress
(Table 5, n = 5).
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Response to a Prolonged Exercise Intervention
Studies observing prolonged exercise interventions
included a number of populations and exercise
interventions. In an attempt to more clearly understand the
responses observed, we discuss the impact on athletes
and non-athletes separately.
In the five studies identified as monitoring the
response of the CAR to an exercise intervention in
athletes, the variables of interest included CAR,
CAR%, and AUCg, and the interventions ranged from
a 7-day intensive soccer training period [
] to a
9month global boat race [
]. Clearly, the variability in
the populations assessed, the techniques for assessing
the awakening response, and the statistical techniques
used make the aggregation of the data nonsensical.
However, some patterns did become evident. For
example, Gouarne et al. [
], Minetto et al. [
Park et al. [
], all showed an increase in CAR
following training (triathlon, soccer, and mountain
climbing, respectively). More specifically, Gouarne et
] demonstrated that elite-level triathletes will
exhibit an increase in CAR% following the onset of
training but will stabilize at a higher level even as the
season progresses, which appears to mirror the
findings in mountain climbers [
]. It is important to
note here that although Park et al. framed this
particular study in terms of altitude exposure, it is
reasonable to include mountain climbing as a form of
prolonged exercise. Even so, the interpretation of the
results of this study is more difficult due to the
additional impact of altitude on cortisol responses
]. Nonetheless, there was a clear increase in the
CAR of mountain climbers after climbing to 4800 m
in 8 days, compared to only a single day of climbing
to 1100 m. The lack of a similar response by Sherpas
to the same intervention was suggested by the
authors to be a result of acclimatization to the
altitude, although this may also be viewed as the
response of a well-trained and adapted individual for
this specific exercise stress. Thus, one could interpret
the study as being the same exercise load applied to
well-trained and lesser-trained individuals, with the
latter group showing larger increases in CAR. Again,
this suggested initial increase in CAR could be
expected following a significant exercise intervention,
which may then level off as participants become
accustomed to the exercise load.
These findings seem contrary to Filaire et al. [
demonstrated that a 4-month tennis training period in
players aged 14.8 years with an average of 7+ years of
training, resulted in a decrease in AUCg and CAR. As a
potential explanation of this discrepancy, it was reported
that subjects also exhibited a disturbance in REST-Q
subscales indicating a decreased affective state; a
significant relationship between CAR and these psychological
affects was present. These findings suggest that CAR will
be altered differentially, contingent on the physiologic
response of the athlete to the training load imposed on
them. That is, if the training load is too great for an
individual’s fitness level, they may present an inverse
response (decreases in CAR), relative to another athlete
who responds to the same training load in the opposing
direction (increases in CAR). In support of this
rationalization, Gouarne et al. [
] observed that two
triathletes developed the overtraining syndrome across the
course of the triathlon season, as determined both by a
decrease in athletic performance, as well as decreases in
subjective fatigue scores [
]. In those overtrained
athletes, and juxtaposed with the non-overtrained athletes,
CAR% showed a decline in response to the training,
eventually stabilizing in one of the athletes, but not the
other. Although it is difficult to compare the results
directly, a global boat race appears to have blunted the
awakening response as the race progressed over
9 months [
]. The authors likened this response of the
sailors to that observed in burnout patients, whom have
been shown to also present a blunted CAR [
In contrast, and challenging the idea of blunted CAR
to elevated training load in athletes, Minetto et al. [
showed an increase in CAR and AUCg in response to
training, while showing a positive relationship between
these responses and performance. It is possible however
that due to the short training period employed in this
study (7 days), these athletes were exhibiting only local
muscular fatigue that affected their physical
performance, but that did not reach the threshold required to
negatively affect neuroendocrine function during
In summary, these studies posit the possibility that
shifts in CAR may not be consistent across all training
loads, potentially increasing as training is first imposed
and stabilizing after an acclimatization period, before
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decreasing if training load becomes too extreme and
overloads the athlete. Of course, these are speculative
claims and must be investigated directly by designing
longitudinal studies that investigate this specific
response. Moreover, as has been done previously, intensity
or load thresholds should be investigated relative to
disruption of the HPA axis and a subsequent effect on the
CAR in athletes. This potential non-linear relationship
with training load may be reflective of a similar
phenomenon observed in the chronic fatigue and
burnout literature, which suggest CAR may increase [
], or be unchanged [
Although the separation of athletic and military physical
interventions could be considered arbitrary, we believed
that some military personal may have had very little
exposure to physical conditioning prior to their enrollment
in military service, a belief that was reflected in the high
proportion of subject “dropout” [
]. This lack of
extended or even lifelong exposure to physical training
may result in disparate CAR responses relative to
athletes and is therefore discussed independently.
In the singular study that examined military physical
training on CAR, Clow et al. [
] tracked military
recruits across an 11-week basic training program,
involving significant physical training components. The
researchers used a cortisol awakening response variable
termed the mean increase (MnInc), calculated as the
difference of the average of the second and third sample
above the first sample (MnInc = ((s2 + s3)/2) − s1). The
authors found no change in MnInc, but AUCg decreased
significantly at weeks 3 and 6, before returning to
baseline levels by week 11. Interestingly, the authors also
analyzed the shape of the curves across the time period,
showing linear increases at weeks 0 and 3, compared to
quadratic contrasts at week 0 and week 12, again
suggesting a leveling off after the initial cortisol increase.
Evidently, the observed function and degree of change
over time should be considered in analyses. This
observation has implications for the desired sampling
frequency and methodology (i.e., at least 3 samples to
test for quadratic relationships, 4 for cubic relationships,
and so forth).
In studies of exercise interventions in non-athletic or
untrained populations, exercise paradigms used tended
to be either aerobic (i.e., cycling) or low-impact practices
such as yoga. Since these intervention types likely affect
the HPA axis dissimilarly, the results of these studies are
Yoga Interventions In the two studies observing
changes in CAR in response to yoga practice,
populations studied included those patients diagnosed with
] and a non-clinical sample of female
]. Inconsistent findings are therefore
somewhat expected given that CAR has been shown to be
altered in clinical populations, likely because these
individuals are often under severe chronic physical,
emotional, financial, and psychological stress. Cutis et al.
] studied changes in CAR following 8 weeks of yoga
training in a clinical fibromyalgia population. The area
under the cortisol curve was reported to significantly
increase following yoga training; however, the authors
included an evening cortisol sample in this AUC
calculation, as opposed to analyzing only the awakening
response. Even so, the data presented shows that the
area was mostly influenced by the first two measures
(i.e., the CAR). Therefore, the yoga program appears to
have increased AUC, with no change in the slope of the
response. In a non-clinical population, Daubenmier et al.
] observed no change in CAR following a 9-week
mindfulness intervention, which included a component
of yoga training, relative to a control group. The details
of this program were significantly lacking, so it is
difficult to interpret this result relative to those of
From the limited number of studies, it is likely that
low-intensity, low-impact physical activity has little
impact on CAR, unless the subject is under severe
chronic stress from a clinical condition. In this case,
low-intensity exercise may have a positive effect on
CAR moving it toward a “normal healthy” response
and away from either an over-responsive or
underresponsive CAR. More studies are required to fully
elucidate these effects, in both clinical and
Aerobic Exercise The impact of aerobic exercise on
CAR in non-athletes was assessed in five studies. In four
of the five studies, no statistically significant change was
reported, although the details of these investigations are
interesting to consider. For example, Foley et al. [
showed aerobic training non-significantly decreased
CAR after 6 and 12 weeks. The decrease observed at
week 12 (week 12 1.89 ± 1.30 ng/ml vs. week 0
3.59 ± 2.63 ng/ml) certainly implies a decrease in CAR,
but the results are impeded by a small sample size
(n = 8) and large inter-individual variability. Similarly, in
a sample of subjects presenting a BMI > 35 (i.e., obese),
a lifestyle intervention (including an aerobic exercise
program) resulted in morning cortisol being greater than
that observed in matched controls at both 0 h and +
0.5 h, although neither the treatment nor control group
showed a significant change from their respective
preintervention values [
]. In this instance, it is likely that
utilizing AUC (or associated AUC-related variables) may
have conferred more information than simple cortisol
values taken at individual time points. Interestingly, the
morning increase was greater in the intervention group
at 6 months of follow-up compared to the control group,
suggesting there are residual effects on CAR following
exercise interventions, although it is unclear why this
would not also be observed immediately following the
exercise intervention. Indeed, the lack of details of
subject activities during this period makes any inferences to
this point problematic. Comparably, Tortosa-Martinez et
] showed no statistical difference between control
and intervention groups in CAR post-intervention,
although an increased peak at +0.5 h and the magnitude
of the increase was nearly significant (p = .068).
Finally, in a study in participants suffering from
jobrelated exhaustion (and therefore a suspected impaired
CAR), there did not appear to be any change in CAR
following the 12-week aerobic exercise intervention [
As with the clinical populations discussed above, in
those populations that likely have a chronic shift in their
CAR, any additional or consistent alteration in CAR
seems doubtful. This null finding may in fact be
considered a positive effect of exercise in these
chronically fatigued individuals. It is possible that exercise
prevented any further shift in CAR in these subjects (i.e.,
perhaps a basement effect was observed). Of course,
longitudinal analysis of this population should be
conducted to test these hypotheses.
In the single study that observed a change in the CAR, a
“green-exercise” intervention in which office workers were
prescribed exercise either in an indoor or an outdoor
setting was investigated [
]. Figures included in this study
suggest that both indoor and outdoor exercise changed
the shape of the CAR. That is, the indoor group moved
from a “regular” CAR, with a peak occurring at + 0.25 h,
to a decreased cortisol concentration at the same time
following the intervention. The outdoor group on the
other hand showed only a small increase at + 0.25 h
pre-intervention but moved to a more regular response
postintervention. In this case, reporting linear or quadratic
contrasts may have been beneficial in fully explaining the
shift in CAR. Moreover, the outdoor exercise appeared to
have a much smaller AUCi than the indoor exercise
following the intervention. This was, however, likely due
to the relative decrease at + 0.25 and + 0.5 h
postawakening cortisol observed in the outdoor group
following exercise. This inverted awakening response is indeed
curious but may be an artifact of the small sample size
(n = 6) and the inherent variability in cortisol responses.
Response to a Single Exercise Session Intervention
Compared to more prolonged interventions, two studies
observed possible changes in CAR following a single
exercise bout. While small in number, these investigations
are crucial if CAR is to be considered as an appropriate
measure for monitoring day-to-day responses to exercise
In one of the studies observing CAR response to a
single exercise session, the researchers found no
differences in the awakening response the morning after
an exercise bout, consisting of a resistance exercise,
circuit-training-type exercise protocol [
]. It must be
noted that the circuit training was approximately
20 min, followed by a 15-min period of “fitness
training.” No reference was made to what this may
have included, but it was presumably some type of
aerobic training. Therefore, approximately 35 min of
physical exercise was completed, with no reference to
the intensity or participant exertion during the
session. Previous literature on the acute exercise-induced
response of cortisol indicates that an intensity
threshold exists [
]. Thus, if we are to understand CAR to
reflect the cumulative stress over time, a relatively
short bout of exercise that is not particularly intense
may not produce any alteration in CAR, since it is
unlikely to illicit acute HPA responses.
Similarly, in response to a late-night exercise bout,
Ucar et al. [
] observed CAR responses to a soccer
match in college-aged participants. The serial
sampling protocol showed no differences in any of the
morning time points following an evening soccer
match compared to a control condition, although it
appears as if the initial peak may have been greater
following the match, thus making the AUCi variable
non-significantly greater. Again, the variability in
these responses (1 h AUCi range 439–70,003 a.u.)
makes analyses difficult, and therefore,
intraindividual responses, even within a given population,
may be more beneficial.
Response to Daily Activity Monitoring
Studies observing the CAR in relation to physical activity
were numerous; however, few directly assessed the
impact on CAR and instead included physical activity as a
component in a multivariate model. For example, Bogg
and Slatcher [
] assessed the impact of physical activity
on CAR via multi-level growth curves, thereby making
extracting data and possible relationships difficult.
Nonetheless, in this particular study, no significant
intercepts were observed for general physical activity in any
of the models. Of note, moderate-vigorous activity
approached a significant correlation (p = 0.088),
although such an effect would have been small and
Similarly, another study found a significant
relationship with Swedish Occupational Fatigue Inventory
]. CAR was positively related with a lack of
energy (r = .11), lack of motivation (r = .10), and lack of
physical exertion (r = .11). Noticeably, these are only
weak or very weak relationships, likely observed to be
statistically significant because of the large sample size
(n = 581) included in the analysis. Nonetheless, and
quite interestingly, when analyzed by sex, these
relationships held only in females and no significant
relationships were observed in males. Even though there were
fewer males in this study, the authors state definitively
that the lack of relationships in males were not due to
lack of statistical power; rather, there may be a true
difference in responses between males and females. It
must be noted however that this study did not control
for any objective marker of exercise or physical activity,
and thus the impact of non-work related physical activity
A study by Vreeburg et al. [
] showed significant
relationships between AUCg and AUCi and physical
activity in depressive subjects. Interestingly, these
relationships were inverted relative to each other, such
that physical activity was a positive predictor of AUCg
and a negative predictor of AUCi, suggesting an overall
greater magnitude of cortisol output, yet a blunted
cortisol response in those individuals who are more
active. Since depressive patients have been shown to have
blunted responses (i.e., lowered AUCi) relative to healthy
], this finding may indicate that physical
activity was beneficial in moving the CAR to a more
Also assessing physical activity via multivariate
models, Martikainen et al. [
] found partial correlations
between the awakening AUC and overall and vigorous
physical activity. However, the modeling techniques also
adjusted for a number of variables, including the timing
of a dexamethasone suppression test. The results are
therefore difficult to interpret and generalize; however,
there does seem to be evidence present that AUCg
shows a negative relationship with both vigorous and
overall physical activity. Even though 272 adolescents
were included in the study, these significant models were
observed only in girls, as observed by Eek et al. [
follows then that not only should sex be considered
when assessing CAR in adolescents but also pubertal
development. Furthermore, Ozgocer and colleagues
recently showed CAR to be affected by menstrual cycle
] and should therefore be controlled for in
future CAR research designs.
Compared to survey-based assessments of physical
activity and exercise, DuBose and McKune [
Actigraph technology to monitor the activity levels in 23
children and demonstrated a relationship between AUCg
and vigorous activity. This suggests those children who
participate in a greater amount of intense physical
activity also tend to show a greater awakening response. This
of course must be understood in the context of a
correlational analysis, as there are numerous factors that could
contribute to the difference in activity level and cortisol
response, especially in an adolescent population [
Interestingly, while there was no difference in the
cortisol concentration immediately after waking, there was a
relationship between the 0.5 h cortisol and both vigorous
and moderate-to-vigorous activity. These findings do
indicate that CAR represents a separate construct than a
simple measure of basal cortisol level. In contrast, AUCi
was found to be significantly negatively related to
walking speed (r = − 0.223) in older adults [
], suggesting a
lower cortisol response is related to greater physical
function. In addition, AUCi contributed an additional 5%
to the second step of a regression model predicting
walking speed from a number of demographic- and
health-related variables [
In comparison to these findings, other studies found no
relationships between CAR and physical activity in
adolescents in sporting clubs [
], an ethnic minority group
], or young or old dancers [
] and no CAR differences
in older adults who completed 1 or more hours per week
of physical activity compared to those who did not [
In addition to those studies assessing the relationship
between CAR and physical activity, one study was
included that measured physical and functional ability. In
this investigation, Gardner et al. [
] studied 962
middle-aged and older men. No relationship was found
between CAR and the “get up and go” or “flamingo”
functional tasks; although after adjusting for other
covariates and similarly to Pulopulos et al. [
], there was a
weak relationship with CAR and walking speed only in
those subjects identified in the highest CAR. AUC did
not elucidate anything any further in this study.
Upcoming Exercise Stress Intervention
Lastly, five studies assessed changes in CAR as a
response to an upcoming exercise stress. This
anticipated stress reaction is considered to be psychological in
nature, but it is nonetheless important to consider that
any CAR variable is a result of both psychological
reactivity to upcoming events and previous exercise
training or stress.
Three studies found no change in CAR in response to
an upcoming laboratory exercise session [
], or martial arts competition [
Balthazar et al. [
] found that there was a significant
increase in both awakening and + 0.5 h cortisol, but this
was not accompanied by a change in CAR. The authors
noted that this lack of difference was due to the large
variability in the awakening response on the morning of
the competition. This suggests that some athletes were
perhaps more psychologically aroused by the upcoming
competition than others. Similarly, since Labsy et al. [
utilized a laboratory-based exercise session with little
competitive incentive, it is likely that the psychological
impact was rather low. As an alternate explanation,
Strahler et al. [
] suggests that their lack of significant
findings may be due to some degree of endocrine
habituation in high-level athletes. In comparison, a study
in competitive swimmers demonstrated a significantly
greater AUCg on competition days compared to control
]. In further support of the psychological impact
on CAR, these researchers collected data on 2 days prior
to the event and showed that the response appears to be
much greater on day 2, which was closer to the time of
competition and presumably a time of greater
Also evaluating swimmers, Meggs et al. [
that AUCg contributed significantly to a linear regression
model predicting athletic performance in a swimming
competition. There was also an interaction between
psychological resilience, as measured by the Academic
Resilience Scale [
] and AUCg with performance, with the
greatest performance occurring in those with low AUCg
and high psychological resilience. This implies that CAR
may actually be beneficial in monitoring overall stress
load in the athletes and may be predictive of
performance in competitive events.
The aims of this systematic review were to firstly
summarize the alterations in CAR in response to
exercise and determine whether there was sufficient support
for its use as an exercise-related biomarker and secondly
to provide future recommendations, where warranted,
for improving CAR research. We acknowledge that
many of the studies included in this review include
confounding variables that may influence the cortisol
response above and beyond exercise alone (i.e., hypoxia
due to altitude or psychological stress). However, had we
limited our review to studies that investigated only the
influence of exercise on alterations in CAR without any
confounding variables, the number of studies included
in the systematic review would have been zero. The
original intent of this review was to conduct a
metaanalysis and establish potential effect sizes across
exercise contexts. However, as has been discussed, there are
significant variations in research methodology, data
reduction, populations, and statistics. Therefore, any
meta-analyses presented would be inconclusive, if not
entirely erroneous. As such, we aim to discuss the
current state of CAR in exercise research and provide
recommendations for augmenting our current
knowledge of this biomarker.
From the findings presented above, it is reasonable to
suggest that a threshold of exercise must be surpassed to
illicit and measure a response in the CAR. Although
available evidence suggests this may be
intensitydependent, future research should confirm this. The
necessity of an exercise intensity threshold is not unheard
of in the exercise endocrinology literature, especially in
reference to cortisol [
]. The lack of change in CAR in
those studies focused on low-intensity exercise or
workplace stress, therefore, may in fact represent a
sub-threshold effect. If true, the lack of sensitivity to
lowimpact exercise may be considered a potential strength
of CAR, especially when considering the utility of CAR
to monitor exercise training stress and thereby modulate
training intensity. For example, during periods of regular
exercise training, CAR may present very little variability,
but overload periods of increased intensity or volume
may impair the CAR, thus acting as an early predictor of
Studies that included CAR as a physiological marker
of readiness on the morning of a competition showed a
degree of consistency in CAR predicting performance
outcomes, leading to the suggestion that CAR
potentially acts as an indicator of the psychological status of
the athlete. This more positive affective state then
presumably leads to improved athletic performances.
However, it is also possible that the observed CAR was a
function of, or affected by, the preceding chronic
training load undertaken by the athletes. That is, athletes
with a greater chronic training load also had more
favorable physical adaptations that lead to improved
performances, and that greater training load was also
reflected in the CAR. Being unable to distinguish this
point, there is a clear need for laboratory-controlled
exercise programs that also monitor CAR.
Many studies in the present review were excluded due
to their lack of a CAR measure. Of these, a significant
number stated that awakening responses were collected;
however, these measures were either not reported (i.e.,
only included concentration values at individual time
points) or were reported as a composition score of
“diurnal cortisol,” which included a number of cortisol
measures outside of the waking period. Although there are
certainly uses for monitoring the entire diurnal period, it
is recommended that the awakening-period cortisol be
analyzed as a separate variable, as described below, in
addition to the diurnal rhythm. This small addition to
the calculations and analysis may lead to relationships or
changes that have been otherwise unidentified.
A clear issue in the literature is related to the most
appropriate way to present CAR variables. It is evident that
CAR and AUC measures may both be valuable for
evaluating responses to exercise, yet it remains unclear
whether AUCi or AUCg should be more consistently
used. Even more concerning is the lack of agreement in
the number or timing of sample collections. While most
studies include samples immediately after waking and a
second sample after 30 min, the variability in studies
including a third, fourth, or fifth measure, or researchers
that prefer a 20- and 40-min capture period, leads to
difficulties in assessing overall effect sizes. After
reviewing the literature, we suggest sampling at least every
15 min following an initial waking sample, for at least
1 h after waking. This allows for the following: (1) an
increased confidence in capturing the peak change; (2) an
increased resolution in the shape of the response; (3)
more meaningful statements in regards to total cortisol
exposure (i.e., area under the curve); (4) more
sophisticated statistical analyses to be completed, such as
nonlinear metrics; and (5) the potential to elucidate
intra-individual variability in the measure across the course of
an exercise training or intervention period. Of
particular importance, a recent study by Smyth et al.
] suggests there is a non-linear rise over the initial
waking period, which is subsequently followed by a
more linear increase, again emphasizing the need for
Moreover, we recommend the reporting of at least:
CAR, CAR%, AUCg, and AUCi, and contrast analysis.
These variables allow for analysis of both the relative
and absolute increases and exposure observed, as well as
general shapes of the CAR curve. Since research on
CAR within the exercise literature is still in its infancy,
the reporting of these variables, even if not significant
will (1) more fully explain the response to the
intervention and (2) allow researchers to more efficiently
focus on CAR variables which may be most relevant
Field-based and observational studies are undoubtedly
important for establishing the effect of exercise and
CAR in real-world scenarios and outlining potential uses
for this biomarker, although there is currently a lack of
control over the exercise interventions, as well as
potential confounding factors in the literature. As such,
although CAR has routinely been obtained via saliva
samples produced in the subject’s regular sleeping
environment, researchers should also consider conducting
studies in which subjects use sleep-in facilities so that
saliva collection procedures could be more closely
monitored for adherence. Although self-reports of wake-time,
or activity and sleep monitors may provide evidence of
waking, they do not denote the actual timing of saliva
samples post-waking. As demonstrated above, the cubic
or quadratic contrasts are highly time-dependent, and
short delays in sampling have been shown to impact
].The use of a sleep-in laboratory facility may
also allow for serum collection in conjunction with
salivary measures. Previous research on salivary and serum
cortisol markers have shown consistent reliability, with
correlation coefficients ranging from r = 0.71 to 0.96
], depending on the population being analyzed. It is
important to recognize the salivary cortisol represents
only the free concentration of the hormone, and the
increased activity of 11β-hydroxysteroid [
] in saliva leads
to lower cortisol levels in saliva. Due to this, as well as
the potential delays in free cortisol excretion through
salivary glands, serum monitoring may prove to provide
a more complete picture of cortisol responses during
awakening. Moreover, cortisol concentrations prior to
the conscious awakening point may elucidate further
physiological mechanisms underlying CAR, which would
be ostensibly achievable only through IV catheterization.
There are occasional references in the literature to the
possibility of responders and non-responders in regards
to CAR [
]. It is the opinion of the authors that the
lack of an increase in cortisol following awakening or
the decrease in cortisol with wakening should not be
excluded from analysis on the basis of being a
“non-responder.” This variability in the response is critical to
further understanding its nature. In the event of
individual responses that do not follow the expected cortisol
rise, these subjects should instead be identified and
individually discussed and perhaps included in a secondary
post hoc analysis.
As discussed elsewhere [
], CAR should be analyzed
in regards to other possible awakening responses. These
may include either the alpha-amylase or
dihydroepiandrosterone awakening responses, as well as other
interdependent physiological systems such as heart rate
variability. It is likely that the relationships between
these markers, as opposed to any individual biomarker,
will permit more complete information regarding the
response to exercise. In addition to relating CAR with
other biomarkers, one should also be cognizant of the
relationships that the CAR has already demonstrated
with subjective markers of stress and recovery.
Specifically within the exercise sciences, CAR has been studied
in reference to the Profile of Mood States [
Analogue Scale to Measure Fatigue , and an adapted
Academic Resilience Scale [
]. Given the clear link
between psychological stress and hypothalamic function,
the inclusion of these questionnaire-based measures and
monitoring of the affective state of the athlete in
response to exercise training is necessary.
The use of CAR in the current exercise and physical
activity literature is sporadic and inconsistent. However,
from the limited evidence presented, CAR appears to be
a viable biomarker to monitor both exercise training
responses and health-related outcomes. In particular, it
appears that CAR may be influenced by an intensity
threshold, since changes in CAR seem to occur in higher
load interventions or those subjects which presumably
have a reduced training tolerance. Moreover, CAR
appears to represent physical activity in some
populations and may be useful in monitoring physiology in
large scale physical activity observational research.
Future research should focus on addressing the
methodological inconsistencies discussed above, establishing a
potential exercise threshold required to illicit an acute
response and determining the extent to which CAR
represents past physiological disruption and upcoming
+xh: Cortisol concentration x hours after waking; 0 h: Cortisol concentration
immediately after waking; AUCg: The area under the curve relative to a 0 cortisol
concentration; AUCi: The area under the curve relative to the increase in cortisol,
typically immediately after waking; AVP: Arginine vasopressin; CAR: The absolute
increase in cortisol from immediately after waking to peak; CAR%: The relative
increase in cortisol from immediately after waking to peak; CARμ: The mean
increase in cortisol, typically taken as an average of two measures following the
initial measure; CMP: The peak cortisol concentration following awakening;
CRH: Corticotropin-releasing hormone; MnInc: The average cortisol
concentration greater than the initial value (MnInc = ((s2 + s3)/
2) − s1); SCN: Suprachiasmatic nucleus
The authors would like to thank Dr. Jennifer L. Etnier for her guidance and
assistance throughout this process.
This project was not funded.
Availability of Data and Materials
Authors TA and LW were responsible for authorship of this manuscript and article
review and were required to reach consensus in the event of disagreement on
article inclusion. TA conducted all database searches and completed all data
extraction and production of summary tables, where necessary. Both authors
read and approved the final manuscript.
Ethics Approval and Consent to Participate
Consent for Publication
Authors Travis Anderson and Laurie Wideman both grant permission for
publication of this manuscript.
Authors Travis Anderson and Laurie Wideman have no competing interests
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
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