Daily hassles and eating behaviour: The role of cortisol reactivity status
Emily Newman,* Daryl B. O’Connor, Mark Conner
Institute of Psychological Sciences, University of Leeds, Leeds, LS2 9JT
*Corresponding author:
School of Health in Social Sciences, Old Medical School, Teviot Place, University of
Edinburgh, EH8 9AG
Tel: +44 (0)131 65413945
Fax: +44 (0)131 651 3971
Email: Emily.newman@ed.ac.uk
Running title: Cortisol and snacking
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Summary
Previous research has shown high cortisol reactors to consume a greater
amount of snack foods than low reactors following a laboratory stressor. The current
study tested whether high cortisol reactors also consume more snacks than low
reactors in response to field stressors. Fifty pre-menopausal women completed a
laboratory stressor, provided saliva samples to assess cortisol reactor status and then
completed daily hassles and snack intake diaries over the next fourteen days.
Hierarchical multivariate linear modelling showed a significant association between
daily hassles and snack intake within the overall sample, where an increased number
of hassles was associated with increased snack intake. This significant positive
association between number of hassles and snack intake was only observed within the
high cortisol reactors and not within the low cortisol reactors. These findings suggest
that high cortisol reactivity to stress promotes food intake. Furthermore, the eating
style variables of restraint, emotional eating, external eating and disinhibition were
more strongly associated with snack intake in high reactors than in low reactors. This
suggests that cortisol reactivity may in part account for the moderating role of eating
style on stress-induced eating. The results are discussed within the context of future
health risk.
Keywords: Stress; cortisol; hassles; snacking; obesity; mood; metabolic syndrome
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Introduction
It is becoming more apparent that stress and negative affect not only have
direct effects on health but also indirect effects through behavioural changes,
including changes in the type and amount of food consumed (e.g. Macht and Simons,
2000; O’Connor et al., 2000; O’Connor and O’Connor, 2004). Laboratory and selfreport studies demonstrate that individuals respond differently in their eating response
to stress with gender, bodyweight and the eating style variables of restraint, emotional
eating, external eating and disinhibition acting as significant moderators of the stresseating relationship (McKenna, 1972; Herman and Polivy, 1975; Grunberg and Straub,
1992; Greeno and Wing, 1994; Conner et al., 1999; Oliver et al., 2000; Van Strien et
al., 2000; O’Connor et al., 2005;). Although, while research has identified a number
of important moderators of stress-induced eating, relatively little is known about the
underlying mechanisms.
One possible mechanism for stress-induced eating concerns the activity of the
hypothalamic-pituitary-adrenal axis during stress, particularly the release of
glucocorticoids from the adrenal cortex. Sapolsky (1998) proposed that corticotropic
releasing hormone (CRH) and glucocorticoids (GC) have opposing effects on
appetite, such that food intake is inhibited by CRH and promoted by GC production.
Direct manipulations of GC levels support their association with appetite and food
intake. Adrenalectomised rats unable to secrete GC have been shown to consume
smaller amounts of carbohydrate relative to other macronutrients (Laugero, 2001),
and GC appears to protect against the hypophagic effects of leptin (Zakrzewska et al.,
1997). In humans, the administration of glucocorticoids in humans has been shown to
increase energy consumption, especially carbohydrates and proteins (Tataranni et al.,
1996).
3
Furthermore, the release of GC during stress has been associated with
increased snack intake. In a laboratory investigation of snack intake in women after
stress exposure, Epel et al. (2001) reported that during stress recovery high cortisol
reactors consumed more than low reactors, especially of high fat, sweet foods.
Therefore individual differences in the stress-eating response could be dependent on
GC reactivity to stress, such that high cortisol reactors consume a greater amount
when stressed than do low reactors. As yet, this cortisol reactivity theory of stressinduced eating has only been tested in the laboratory and not in the field. To test
whether the effect is limited to the laboratory it is essential to replicate and extend
Epel et al.’s (2001) findings in a more natural setting.
Field studies of stress-induced eating usually require individuals to complete
diary records of workload, hassles and food intake (e.g. Steptoe et al., 1998; Conner et
al., 1999), allowing the researcher to measure natural eating behaviour in response to
real-life stressors. Previously, diary studies of stress-induced eating have compared
overall snack intake across high and low stress weeks (e.g. Steptoe et al., 1998).
However, by averaging intake across days and weeks subtle daily variations in stress
and intake may be lost. Multivariate linear modelling enables researchers to test
between-person associations and within-person daily variations in measures (Affleck
et al., 1999), and would therefore facilitate an investigation of the relationship
between daily stress and snack intake. Despite this advantage, only one previous
study has employed this method of analysis to examine fluctuations in intake with
daily stress (O’Connor et al., 2005).
The present study aimed to test whether the relationship between hassles and
snacks outside the laboratory differs between high and low cortisol reactors as an
extension of Epel et al.’s (2001) study and a test of whether GC release could account
4
for variations in stress-induced eating. The study also aimed to test whether the
relationship between eating style and snacking differed according to cortisol reactivity
status. Following the procedure of Epel et al. (2001), pre-menopausal women were
exposed to laboratory stressors to establish cortisol reactivity status and required to
report daily hassles and snack intake in diaries over two weeks. Because of reported
gender differences in cortisol reactivity to stress (e.g. Kudielka and Kirschbaum,
2005) and a greater prevalence of stress-induced food intake in females (e.g.
Grunberg and Straub, 1992), only females were included in the current study. It was
predicted that high cortisol reactors would show a stronger positive association
between daily hassles and snack intake than low reactors.
Methods
Participants
Fifty-five pre-menopausal women completed the laboratory tasks. Of these,
four did not return both diaries and one woman did not produce sufficient saliva for
analysis. Therefore complete data were obtained and is reported from fifty women.
The participants had a mean age of 33.96 years (SD=6.18) and mean body mass index
(BMI) of 23.34 (SD=3.62). Participants were recruited using a County Council
Bulletin in an advert to take part in a ‘Women and Eating Study’. Exclusion criteria
were based on factors previously shown to affect baseline or reactive cortisol levels.
Participants were not included in the study if they had been diagnosed with a
neuroendocrine or metabolic disorder, had a history of eating disorders or depression
(Ellenbogen et al., 2002), were postmenopausal or taking oral contraceptives
(Kirschbaum and Hellhammer, 1989; Pruessner et al., 1997). Menstrual cycle phase
was left random, although cortisol levels are reportedly higher around the luteal phase
5
(Kirschbaum et al., 1999). Participants were paid twenty pounds (approximately $36)
for completing all parts of the study.
Procedure
Participants cortisol reactivity was individually tested in the laboratory in the
afternoon, to control for the waking response (Pruessner et al., 1997) and because
cortisol stress reactivity is greater in the afternoon (Kirschbaum and Hellhammer,
1989). Moreover, time of day has also been found to influence levels of anxiety
during stressful encounters (Willis, O’Connor and Smith, 2005). They were asked not
to smoke during the hour before testing due to the associated rise in cortisol (Morgan
et al., 2004), nor to exercise or drink alcohol on the test day. On arrival at the
laboratory, the participant was given an information sheet about the study before
providing written consent. She was measured and weighed, and asked to provide a
first saliva sample (baseline measure one). The participant then relaxed for fifteen
minutes with a selection of magazines while listening to a ‘Classical Chillout’
compact disc (Circa Records Ltd, 2001), before providing a second baseline saliva
sample. The 15-minute stress induction procedure was then conducted. The stress
manipulation was based on the Trier Social Stress Test (Kirschbaum et al., 1993). For
the first five minutes, each participant was asked to prepare a five-minute presentation
of their opinion on a controversial topic from a list (topics included abortion, sexual
equality and cannabis legalisation), for later assessment by psychologists who were
experts in body language. The participant then performed the presentation for five
minutes in front of the experimenter and a videocamera; although, the performance
was not actually recorded or assessed. The participant was prompted to continue if
the presentation stopped for any length of time, until a total of five minutes had
passed. For the subsequent five minutes, the participant was required to count
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backwards serially in thirteens from the number 1022 as quickly and accurately as
possible. If an incorrect response was made, the participant was required to restart the
subtraction from 1022. Such stress protocols involving both an assessment and
mathematical component have been shown to be most effective in inducing cortisol
reactivity (Dickerson and Kemeny, 2004).
After the stress procedure, a third saliva sample was taken. The participant
was asked to complete a questionnaire battery for forty minutes. During this time,
four more saliva samples were taken, at ten-minute intervals. The participant was
then led into a different room, and asked to relax again for twenty minutes before an
eighth saliva sample was taken. The participant was then provided with the two
weekly diaries in freepost envelopes. Diaries contained brief instructions on how they
should be completed; however the participant was also given an explanation of how to
complete each daily entry on receipt of the diaries. Participants were contacted for
debriefing after receipt of the second diary.
Measures
State anxiety was measured before and after the stress manipulation using the
Shortened State Anxiety Inventory (STAI; Marteau and Bekker, 1992). The
participants also recorded how stressful they had found the manipulation, using a
seven-point anchored scale from ‘not at all’ to ‘extremely’. The questionnaire battery
consisted of the Dutch Eating Behavior Questionnaire (DEBQ; Van Strien et al.,
1986) and disinhibition scale of the Three Factor Eating Questionnaire (TFEQ;
Stunkard and Messick, 1985). The DEBQ contains 33 items designed to measure
dietary restraint (10 items, e.g. ‘Do you deliberately eat foods that are slimming?’),
emotional eating (13 items, e.g. ‘Do you have a desire to eat when you are upset?’)
and external eating (10 items, e.g. ‘If you see others eating, do you also have a desire
7
to eat?’) and has previously been validated in a British sample by Wardle (1987). The
disinhibition scale of TFEQ contains sixteen items (e.g. ‘Sometimes when I start
eating, I just can’t seem to stop’) designed to measure tendency to disinhibit food
intake. The reliability of the TFEQ has been previously validated by Stunkard and
Messick (1985). In the current sample, each of the scales exhibited very good internal
reliability (range  = .84 - .92). In the field, participants completed two weekly diaries
over two consecutive weeks. Daily mood was recorded using the shortened Positive
and Negative Affect Scale (PANAS; MacKinnon et al., 1999). Participants reported
their daily hassles, rating the intensity of each on four-point anchored scale from ‘not
at all’ to ‘very much’ (scored 0-4). Previous research suggests that snack intake is
more susceptible to change with daily hassles than is meal intake (Conner et al., 1999;
Crowther et al., 2001; O’Connor and O’Connor, 2004) and so participants were only
required to record snack intake. Snacks were defined within the diaries as foods
consumed between meals and thus discriminated from meals. The participants were
asked to complete their daily entries at the end of each day, and to return each weekly
diary by post as soon as it was completed, using the pre-addressed freepost envelopes.
Cortisol measurements
The participants provided salivary samples of cortisol, using salivette tubes
(Sarstedt, UK). Salivary samples provide a non-invasive measure of free, bioavailable cortisol levels (Kirschbaum and Hellhammer, 1989; DeWeerth et al., 2003).
The salivette contains a cotton dental roll inside a plastic tube, which the participant is
required to place in the mouth for 30 to 45 seconds before replacing in the tube.
Salivettes were frozen at –20oC on the same day, to preserve sample stability as well
as possible (Groschl et al., 2001). After defrosting and spinning, the saliva samples
were tested using a fluorescence immunoassay with an autodelfia kit. Assays were
8
performed over three days with samples from each participant tested on the same
immunoassay plate to minimise inter-assay variation. Boxplots revealed that three
women had outlying high cortisol reactivity levels; however, given that reactivity was
not treated as a continuous variable as participants were divided into high and low
reactor groups, this did not impact on the statistical analysis (c.f. Epel et al., 2001).
Data analysis
Cortisol reactivity was determined using the difference between mean baseline
cortisol level and maximum level after the stressor. Those individuals who increased
in cortisol levels were classified as high reactors, while those who showed no change
or decreased in levels from baseline were classified as low reactors. Hierarchical
multivariate linear modelling was conducted to test the relationship between daily
hassles and snack intake and the relationship between eating style and snack intake in
the field, using the program HLM6 (Raudenbush et al., 2004). The data contained a
two level hierarchical structure, Level 1 being the within-person variation (e.g., daily
patterns in the number snacks consumed, the number of hassles experienced), and
Level 2 being the between-person variability (e.g., eating style). The fifty participants
with usable datasets provided a total of 700 days of data.
Results
Stress ratings
The stressfulness ratings of the stress procedure ranged from 1 (not at all
stressful) to 7 (extremely stressful) on the 7 point scale, with a mean of 4.78
(SD=1.43), indicating that the stressor was moderately, but not extremely, stressful.
The mean state anxiety level was 13.94 (SD=3.32) before the stress manipulation, and
16.76 (3.68) after the manipulation. A repeated measures t-test indicated that this
9
difference was significant (t(49)= 4.96, p<0.001), indicating that the stress
manipulation was successful in increasing anxiety.
Cortisol reactivity
Cortisol reactivity was measured by taking the difference between the average
of the two baseline samples and the peak response (between ten and forty minutes
following the start of the stress protocol). There was an average cortisol increase of
1.36nmol/l (SD=3.77). A previous study has shown an average cortisol increase of
approximately 7.00nmol/l in women after forty minutes (Kirschbaum et al., 1992),
therefore average reactivity was lower in the current study. Reactivity ranged from –
3.39 to +13.43nmol/l, indicating that some participants showed a decline in cortisol
levels following baseline. Twenty-six women showed an increase in cortisol levels,
and were classified as high reactors (mean reactivity=3.69nmol/l). Twenty-three
women who showed a decrease in levels and one participant who showed no change
were classified as low reactors (mean reactivity=-1.18nmol/l). Figure 1 shows the
cortisol reactivity profiles for high and low reactors. High and low reactors
significantly differed in reactivity from baseline (t(48)=-6.18, p<0.001), but not in
average baseline values (t(48)=0.08, n.s.). There was no difference in stress ratings of
the manipulation between the reactor groups (t(48)=-0.93, n.s.), but there was a
significant difference in state anxiety post-manipulation (t(48)=-3.11, p<0.01),
indicating that high reactors had a greater anxiety rating following the stress
manipulation than did low reactors.
<Figure 1>
Relationship between daily hassles and snack intake
The number of reported daily hassles ranged from zero to five, with a mode of
one. The number of daily hassles was positively skewed so this variable was
10
dichotomised: No hassles or one hassle experienced per day was coded as low, and 2
or more coded as high, to provide the most even division of low and high numbers of
hassles (65.7% days coded as low hassle days, and 34.3% coded as high hassle days).
The rated intensities of each hassle were summed for each day to give a total daily
hassle intensity score. These hassle intensity scores ranged from 0 to 16 and were
also positively skewed. The variable was dichotomised into high and low hassle
intensity days, with intensity scores of 0 to 2 coded as low, and 3 to 16 as high (47.1%
days were coded as low intensity and 52.9% as high intensity). Because the number
and intensity of hassles were dichotomised, both these variables were entered as
uncentred variables in the multivariate models. The number of daily snacks
consumed ranged from 0 to 6, with a mean of 1.84 snacks per day.
The effect of the number and intensity of daily hassles on overall snack intake
was tested using a level one model, with the number and intensity of hassles as
predictors. This model is expressed in the equation:
Yi = β0 + β1+εi
where Yi=the outcome variable of the number of daily snacks, β0=the intercept, β1=the
slope for the level one predictor variable and εi=the random error term.
Each level one predictor variable (number of hassles, intensity of hassles,
negative affect and positive affect) was entered individually into the equation, rather
than all being entered simultaneously. Table 1 shows the association between each
predictor variable and snack intake.
<Table 1>
Table 1 shows that across the sample snack intake was significantly associated
with the number of hassles, intensity of hassles and negative affect. An increase in
11
hassle intensity, number and negative affect was associated with increased snack
intake. Daily positive affect score was unrelated to snack intake.
Daily hassles and intake in high and low cortisol reactors
To test whether the relationship between hassles and snack intake differed
between the low and high peak cortisol reactors, the same hierarchical modelling was
also conducted separately for the two groups (shown in Table 1). Within the low
reactors, snack intake was not significantly associated with the number of daily
hassles (β=0.01, t=0.14, n.s.) or the intensity of hassles (β=-0.14, t=-1.84, n.s.). In
high peak reactors, there were significant positive associations between hassle number
and snack intake (β=0.39, t=3.96, p<0.01), and hassle intensity and snack number
(β=0.51, t=6.30, p<0.001), indicating that snack intake increased with a greater
number and intensity of hassles in the high reactor group. Beta coefficients were
significantly different between the high and low reactor groups for number of hassles
(t(46)=2.83, p<0.01) and numbers of hassles (t(46)=5.81, p<0.01). With regards to
daily mood, snack intake was significantly positively associated with negative affect
(β=0.04, t=2.75, p<0.05) and negatively associated with positive affect (β=-0.01, t=2.61, p<0.05) in the low reactors only indicating that snack intake increased with
negative mood and decreased with positive mood in low and not in high peak reactors.
Effect of eating style on snack consumption
To test whether snack consumption was predicted by the eating style variables
and if this relationship differed according to cortisol reactivity status, each eating style
variable was added individually to the equation:
Yi=β0 + β1 + εij
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where Yi=the outcome variable of the number of daily snacks, β0=the intercept,
β1=the slope for the level two eating style predictor variable and εij=the random error
term.
Table 2 shows the relationship between each of the eating style measures and
daily snack intake in the overall sample and within the high and low cortisol reactor
groups separately.
<Table 2>
Snack intake was significantly associated with dietary restraint (β=0.08, t=6.83,
p<0.01), emotional eating (β=0.04, t=4.16, p<0.01), disinhibition (β=0.10, t=4.08,
p<0.01) and external eating (β=0.04, t=2.47, p<0.01) in the overall sample. In each
case, an increase in the eating style variable was associated with an increase in the
number of snacks consumed. Table 2 also shows that all the eating style variables
were significantly associated with snack intake in both the high and low cortisol
reactors, but that the associations were stronger within the high reactors. A
comparison of the beta coefficients between the groups showed that associations were
significantly stronger within the high reactors for restraint (t(46)=3.97, p<0.01),
emotional eating (t(46)=2.16, p<0.01) and disinhibition (t(46)=2.42, p<0.01), but not
external eating style (t(46)=0.83, n.s.).
Discussion
The aim of the current study was to test whether the relationship between
stress and food intake would differ between high and low cortisol reactors when tested
in the field. The results of a previous study indicated that eating response to stress in
the laboratory differed between high and low cortisol reactor groups, such that high
cortisol reactors consumed a greater amount of food, especially high fat, sweet foods
13
(Epel et al., 2001). The results of the current study support Epel et al.’s findings. A
greater number and intensity of daily hassles was associated with increased snack
intake across the sample. However, this positive association only remained
significant among the high cortisol reactor group when participants were tested
separately according to reactivity status. The findings therefore suggest that a
difference in eating response to stress between high and low reactors can also be
observed outside of the laboratory.
The results from the current study provide further support for the role of GC
activity in appetite (e.g. Tataranni et al., 1996). Furthermore, the findings suggest that
not only does the administration of GC increase food intake, but that the release of
GC during the physiological stress response also promotes increased intake. Sapolsky
(1998) proposed that CRH and GC have opposing effects on appetite, so that the
release of CRH at the start of the HPA axis response has an anorectic effect, but the
later release of GC promotes food intake during the recovery stage for the
replenishment of energy required during the ‘fight or flight’ response. While this
mechanism may have been adaptive in our evolutionary past, the effects of GC may
be less beneficial in response to the modern day psychological stressors. In fact,
continuous exposure to stressors could contribute to obesity. The release of GC
appears to promote the release of insulin (Dallman et al., 1994). This combination of
insulin release and food consumption increases the likelihood that consumed energy
will be stored as fat, and particularly around the abdominal region where GC
receptors are abundant (Strack et al., 1995; Laugero, 2001). Therefore, the appetite
stimulating effects of GC may have adverse consequences for obesity and health.
Moreover, it has been suggested that the effects of stress on food intake may
also contribute to increased risk of metabolic syndrome (Epel et al., 2004). The
14
characteristics of which include obesity, insulin resistance (or type II diabetes), high
blood pressure, high blood triglyceride levels and low HDL cholesterol levels.
Recently, Epel et al (2004) in a longitudinal study examined the effects of selfreported stress-eating tendencies (more-eaters vs. less-eaters) on changes in cortisol,
insulin, adiposity, lipid levels and food intake from baseline to exam-stress periods in
medical students. These authors found that increases in weight, cortisol, insulin, and
lipid profile in response to stress were only observed in stress ‘more-eaters’ and not in
the ‘less-eaters’. Taken together with the current findings, these results indicate that
stress-related changes in food intake, if maintained overtime, may be a risk factor for
the development of metabolic syndrome. Larger and more comprehensive
longitudinal investigations are required in order to determine the causal pathways.
It is as yet unclear exactly how GC affects food intake. One possibility is that
they initiate the release of neuropeptide Y, a known appetite stimulant (Sainsbury et
al., 1997). It is also possible that GC protects against the hypophagic effects of leptin.
Early tests have revealed that leptin is only effective in promoting weight loss in
adrenalectomised animals (Zakrzewska et al., 1997), suggesting that GC counteract its
effects. It is also unclear why certain individuals are more reactive to stress in terms
of cortisol output. It is likely that psychological factors are involved, since the results
of the present study reported that self-report anxiety after the stressor was greater in
high reactors. Moreover, these results also point to diathesis-stress mechanisms that
suggest that psychological vulnerabilities, when activated by stress, may result in
negative outcomes. For example, coping styles, the behavioural and cognitive
responses individuals use when they encounter stress, in particular, have been shown
to have well-established moderating effects on an individual’s response to a stressful
encounter (cf., O’Connor and O’Connor, 2003). It would therefore be beneficial for
15
future research to address the psychological factors (such as coping) associated with
the cortisol response to stress and whether this differs according to stressor type (e.g.,
ego-threatening, interpersonal, work-related).
Previous research has highlighted that eating style variables are significant
moderators of stress-induced eating, such that restrained, emotional and external
eaters and those with a high tendency to disinhibit food intake are more likely to
increase food intake during stress (e.g. Conner et al., 1999; Oliver et al., 2000; Van
Strien et al., 2000; O’Connor et al., 2005). The results of the present study indicated
that the positive associations between snack intake and restrained, emotional and
disinhibited eating style variables were greater among the high cortisol reactors than
within the low reactors. One possible explanation for this finding is that individuals
high in these eating style variables produce high levels of cortisol, which then has an
appetitive effect. Previous research has reported that high dietary restraint individuals
have greater salivary and urinary cortisol levels than low restraint individuals (e.g.
McLean et al., 2001; Anderson et al., 2002), which may be due to the stress caused by
diet monitoring. However the relationship between cortisol output and other eating
style variables has not been investigated. Therefore individual differences in cortisol
reactivity to stress may contribute to an understanding of the moderating effect of
these eating style measures on eating response to stress, though further investigations
of the relationship between eating style and cortisol output are needed to further
elucidate this finding.
We also found fluctuations in daily mood only impacted on snack intake in the
low cortisol reactors: negative affect was associated with a hyperphagic snacking
response, whereas, positive affect was associated with a hypophagic snacking
response. These findings are important and indicate that the mechanisms associated
16
with between-meal snacking are different in the high and low cortisol reactors with
mood being an important driver in the low reactors and cortisol in the high reactors.
To the best of our knowledge, this is also the first study to show the differential
effects of positive and negative mood on food intake within a naturalistic setting. The
role of mood in understanding food intake within the context of cortisol reactivity
status requires further examination.
The present study used a modified version of the Trier Social Stress Test
(Kirschbaum et al., 1999), where participants were asked to present their opinion
about a controversial topic for five minutes to the experimenter. This first part of the
test differed from the original, which requires participants to convince a three-person
panel of male and female confederates that they are the right person for a specified
job. Although the modified version combined an assessment task with a mathematical
task to maximise cortisol reactivity (Dickerson and Kemeny, 2004), it is likely that the
changes to the presentation task account for the lower cortisol reactivity levels
compared with previous research (Kirschbaum et al., 1992). Therefore it would be
useful to replicate the study using the original version of the Trier Social Stress Test.
As a result of the lower cortisol reactivity in the current study, the reactor groups may
be more accurately described as reactors and non-reactors, rather than high and low
reactors. However, the cortisol profiles of the reactor groups are similar to those
reported by Epel et al. (2001), therefore the terms high and low reactors have been
used to maintain consistency with this previous study. It should also be noted that
menstrual phase was not identified in the present study, although evidence has
suggested that cortisol reactivity can vary over the cycle (Kirschbaum et al., 1999). It
would therefore be useful for future research to include some measure of menstrual
cycle phase. In addition, this study only examined the effects of cortisol reactivity in
17
women; consequently, it remains unknown whether these effects will generalise to a
male sample. Recent research, using a diary methodology, has found similar effects of
daily hassles on between-meal snacking in men and women, although, this study did
not assess cortisol reactivity to stress (O’Connor et al., 2005). Therefore, it would be
useful if further research examined the effects of stress and cortisol on eating
behaviour in a sample of men and considered utilising alternatives to the self-report
diary methodology (e.g., electronic techniques) assessing these variables at random
time points throughout day.
In conclusion, the results of this study suggest that the association between
stress and snack intake is greater in high cortisol reactors than low reactors, when
investigated in the field. This suggests that the release of glucocorticoids during the
HPA axis stress response promotes the intake of food. However, this may have
adverse consequences for the development of central obesity and metabolic syndrome.
Future research ought to explore further the psychological factors that predict cortisol
reactivity to stress.
18
Acknowledgements
We would like to thank Duncan Talbot at Unilever in Colworth, UK for conducting
the cortisol analysis.
19
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