Stress Induced Eating and Food
Preference in Humans:
A Pilot Study
Mark L. Willenbring, M.D.
Allan S. Levine, Ph.D.
John E. Morley, M.D.
Psychological stress has been shown to produce feeding behavior in both
humans and animals. In our animal studies, it appears that the texture of
the food may determine how well a food alleviates stress. We studied the
food preferences of 80 stress-eating and nonstress-eating adults and examined the relationships of them with current stress, sex, age, and weight.
Preference for high caloric density foods is predicted by being a stress-eater
and lower current stress and is associated with a concern over feeding
behavior and normal weight. Preference for low caloric density foods is
predicted by high stress and stress-eating, as well as obesity, being older
and not smoking. Food preference was associated also with food texture.
A preference for salty foods (as opposed to sweets) was associated with
being younger, stressed, nonobese, and eating less when stressed.
The relationship of oral behaviors to stress has long been recognized
both in humans and in wild animals (Morley, Levine & Rowland,
1983). Psychological stress can produce multiple behavioral abnormali-
Mark 1. Willenbring, M.D. is Assistant Professor, Neuroendocrine Research Laboratory, Departments of Psychiatry, University of Minnesota and VA Medical Center, Minneapolis. Allan
S. Levine, Ph.D. is Associate Professor, Neuroendocrine Research Laboratory, Departments
of Food Science and Nutrition, University of Minnesota and Medicine Service, VA Medical
Center, Minneapolis. John E. Morley, M.D. is Professor, Department of Medicine, University
of California, Los Angeles, and Director, Geriatric Research, Education and Clinical Center,
VA Medical Center, Sepulveda. Please address correspondence to: Mark 1. Willenbring,
M.D., Psychiatry Service ( 1 16A), VA Medical Center, Minneapolis, MN 55417.
lnternational lournal of Eating Disorders, Vol. 5, NO. 5, 855-864 (1 986)
CCC 0276-3478/86/050855-10$04.00
0 1986 by John Wiley & Sons, Inc.
856
Willenbring, Levine, and Morley
ties, including overeating. Robbins and Fray (1980) have suggested that
many different stressors may produce inner sensations, sufficiently
similar to each other so as to produce responses that may appear irrelevant to the particular motivational state present. Since the classic article by Stunkard et al. (1955) describing the night eating syndrome in
stressed individuals, a number of formal psychological studies have
confirmed the presence of stress-induced feeding in humans (Meyer &
Pudel, 1977; Schachter, Goldman & Gordon, 1968).
A laboratory model of stress induced eating has been developed in
rats and mice (Antelman & Caggiula, 1977; Levine & Morley, 1981;
Levine, Morley, Wilcox, Brown & Handwerger, 1982; Rowland & Antelman, 1976). Sustained mild tail-pinch in these animals induces a variety of oral behaviors including gnawing, eating, and licking in almost
every animal tested. Utilizing this model, it has been shown that
stress-induced eating involves both dopaminergic and opioid mechanisms (Lowy, Maickel & Yim, 1980; Morley & Levine, 1980; Morley,
Levine, Murray, Kneip & Grace, 1982). Studies in our laboratory have
shown that during pinch stress the predominant behavior is chewing
rather than eating (Levine & Morley, 1982). It also appears that the
texture of the food is associated with the degree of stress reduction that
the chewing behavior will produce. For this reason we decided to
study the preference for two different food textures in stress-eating and
nonstress-eating (or stress-fasting) humans. In addition, we attempted
to define the food preferences of stress eaters.
METHODS AND SUBJECTS
Subjects were recruited from three groups: obese patients seen in
Medicine Clinic (6%), people in TOPS (an organization for people who
want to lose weight) (19%), and normal and overweight co-workers of
the investigators at the Veterans Administration Medical Center, Minneapolis, MN (75%). They were asked to participate in a study of
stress, eating, and food preference; informed consent was obtained
prior to their participation. A total of 20 males and 60 females, all Caucasian, with an average age of 42.0 years (range 20-71) participated.
Using height-weight tables of the Society of Actuaries and Association
of Life Insurance Medical Directors of America (1980), we determined
that 51 subjects were less than 14% overweight, 10 were 15-29%
overweight, and 17 were 30% or more overweight (weight data
were missing on 2 subjects). No subjects were significantly underweight.
All subjects filled out a questionnaire concerning their eating habits
and a Symptom Checklist-90 (SCL-90) (Derogatis, Lipman & Rickels,
Stress Induced Eating
857
1974). On the questionnaire, subjects were asked if they ate more, less,
or the same when stressed; more, less, or the same when bored;
whether they preferred sweet or salty foods; whether they were unhappy, somewhat unhappy, or not unhappy with their weight;
whether or not they were dieting; and whether or not they currently
smoked tobacco. The SCL-90 is a 90-item checklist where subjects rate
the degree of being bothered by each symptom item in the previous
week. Each item is rated from zero (not at all) to five (a great deal).
The SCL-90 is a well-validated instrument that produces scores on five
factor scales (somatization, interpersonal sensitivity, depression, anxiety, and hostility), as well as an overall rating, the GSI. We used nonpsychiatric patient norms for our sample. The GSI was used as an overall measure of ”stress.” They were then given four diet bars and
asked to rate them in terms of texture and overall response, on a scale
of one (like) to ten (dislike). All bars had similar appearance, but differed with respect to water activity (Aw). Aw is a term reflecting the
relative amount of water in a given food. Water has an Aw = 1. Bars
1-3 had an Aw = 0.25, giving them a crunchy texture. Bar 4 had an
Aw = 0.60, and is more chewy. All bars were a high fiber, flavor6d
bar with 30 Ca1/15 g. They were sweetened with aspartame, and constituted with washed orange peel and polydextrose. Bars 1,2, and 4 were
apple-flavored, while bar 3 was lemodgrape. All subjects were asked
whether they preferred sweet or salty foods, and then ranked each of
five foods in seven groups according to preference (Table 1).Each food
was grouped according to its caloric density, and a score assigned to it
on that basis. The highest and lowest ranked foods were taken as most
liked and most disliked, and these two density scores for that item
were recorded for each grouping. These scores were summed for
total ”density liking” and “density disliking” scores. We were interested in the relationship between “sweet preference” and ”densityliking”, because most “sweets” are high in both carbohydrates and
fat (e.g., donuts and ice cream) and thus have a high caloric density.
Table 1. Food preference scales given to patients. Rank each of the foods
listed i n order of preference: 1 = best, 5 = worst.
Apples -;
Bananas -;
Butter -;
Sugar -;
Butter -;
F. Bread -;
G. Licorice -;
A.
B.
C.
D.
E.
oatmeal -;
tomatoes -;
broccoli -; cottage cheese __
doughnuts -;
potato chips -;
chocolate -;
butter __
walnuts -;
peanut butter -; swiss cheese -;
cottage cheese apples -;
doughnuts -;
ice cream -;
almonds
cream -;
cashews -;
milk -; buttermilk doughnuts -; ice cream -; chocolate -; avocado banana -;
bread -; coke -; rice __
~
Willenbring, Levine, and Morley
858
RESULTS
Responses to the eating behavior questionnaire indicated that 44%
increased eating when stressed, 48% decreased eating, and 8% did not
change eating when stressed. Boredom caused 46% to increase eating
and 52% had no response. Sweets were preferred over salty foods by
46%, salty foods were preferred by 29%, and 21% expressed no preference. Many subjects (75%) were at least somewhat unhappy about
their weight and 73% were currently dieting.
Means (and ranges) for the standardized scores for the SCL-90 scales
were: somatization 51.9 (33-79), interpersonal sensitivity 56.1 (37-85),
depression 54.1 (32-77), anxiety 50.9 (35-72), hostility 52.6 (38-83), and
GSI 54.0 (30-80). A standardized score of 50 indicates that 50% of the
comparison population (nonpsychiatric patients) scored higher on a
particular dimension than did that individual or group. Thus, this was
not a highly stressed sample overall, although there was a good range
of scores. The GSI, a measure of overall scale elevation, was used as
our indicator of stress in further analysis.
Table 2 shows simple correlations (Pearson’s Y) among several key
variables. In general, while there are numerous statistically significant
associations, correlations are not particularly high. This suggests a fair
amount of independence among the variables. On the other hand, the
presence of the small but significant association among the different
eating variables is consistent with the idea that people may tend to
exhibit several “problem” eating behaviors, but in a variety of patterns.
The underlying patterns of association were explored with multivariate
analysis (see below). However, there are several specific correlations
that deserve mention. Smoking is not highly correlated with any of the
eating variables, which suggests that these ”oral behaviors” are not
more likely to occur together. High density preference was significantly
associated only with current stress (GSI). The low correlation of high
density preference and sweet preference suggests that caloric density
per se is not the primary factor in the reinforcing quality of sweets. On
the other hand, high density preference and GSI correlate at a significant level, suggesting that food preference (in terms of caloric density)
may vary with stress levels. Another important relationship is that between obesity and stress levels (GSI).
In order to further explore the relationships among variables we
used factor analysis with oblique rotation. Seven factors were identified
with eigenvalues greater than one. However, using the scree test, we
selected five factors as significant, accounting for 63% of the variance.
The five factors, with the factor loading of each variable, are shown in
Table 3. The variables that loaded significantly on each factor are identified in Table 4. Preference ratings for bars 1-3 loaded on factor 1,
indicating that subjects tended to dislike all three if they disliked one.
*p<.05.
+*p< .01.
tp<.Ool.
Stress eating
Boredom
eating
Sweet
preference
Smoking
Unhappy
with
weight
Obesity
Dieting
High density
preference
Current
stress
(GSI)
- .13
- .05
.17
.07
.08
.22'
.05
- .07
.31**
.43t
.15
.25"
.22*
.34t
.17
.22'
- .07
- .13
.04
.14
1.00
.26**
Smohng
.26**
- .13
1.00
.21
.28**
Sweet
Preference
1.00
Boredom
Eating
1.00
.29**
Stress
Eating
.06
.15
.46t
.04
1.00
Unhappy
With
Weight
Table 2. Simple correlations among several key variables.
.41t
1.00
.16
- .20
Obesity
.06
1.00
.ll
Dieting
.29*'
1.00
High
Density
Preference
1.00
Current
Stress
(GSI)
m
%.
rn
Willenbring, Levine, and Morley
860
Table 3. Factor loadings of variables on five factors identified
through factor analysis with oblique rotation.
Factor 1
Factor 2
- .03
- .52
.01
-.ll
- .04
- .09
- .01
- .02
- .21
- .16
- .83
- .75
- .90
- .25
- .29
- .23
- .17
.33
- .26
- .04
.77
.54
.41
-.17
-.39
.77
.23
.16
.12
- .01
.00
Age
Sex
Boredom-eating
Stress-eating
Sweet preference
Smoking
Happy with weight
Dieting
Obesity
GSI
Likes bar 1
Likes bar 2
Likes bar 3
Likes bar 4
Density-like
Density-dislike
-
Factor 3
.oo
- .18
.37
- .19
.14
- .12
-.36
-.18
.05
.67
.63
- .15
.24
.01
.15
- .78
.18
Factor 4
Factor 5
.21
.25
.02
- .20
- .09
-.02
- .55
.22
-.01
- .26
- .14
- .32
- .08
-.79
.02
.60
- .72
.23
.17
- .37
- .41
.23
.20
.ll
- .01
.44
.00
.08
.00
- .17
.01
- .23
Table 4. Variables loading significantly on 5 factors identified through factor
analysis. Numbers in parentheses are factor loadings. Obesity is included in
factors 2 and 5 in order to show relative loading of this variable, even though
this was not significant on those factors.
Factor 1
Factor 2
Factor 3
Factor 4
Factor 5
Female sex
(.52)
Dislikes bar 1
(33)
Dislikes bar 2
Boredom eating
(.77)
Stress eating
(.54)
Sweet preference
(.4U
Unhappy with
weight (.39)
Likes high
density (.37)
[Obesity (.23)]
Increased age
(.33)
Nonsmoker
(.36)
Obese (.67)
Current stress
(.63)
Lack of high
density
preference
(.78)
Unhappy
with
weight
(.55)
Dislikes bar
4 (. 79)
Dislikes high
density
(.60)
Decreased age
(. 72)
Stress fasting
(.37)
Salt preference
(.41)
Current stress
(.44)
[Obesity
( - .Ol)l
(.75)
Dislikes bar 3
(.90)
Female sex also was associated with this factor. Interestingly, bar 4
preference loads on a separate factor (factor 4), along with happiness
with weight and disliking high density foods. The caloric density may
thus be related to water activity (Aw). These data support the notion
that Aw is important in determining preference, since bars 1-3 differed
from bar 4 primarily in Aw. Factor 2 appears to be a “problem eating
factor.” Eating when bored or stressed, preferring sweets and higher
density foods, and dieting and being unhappy with weight all load at
least moderately on this factor. However, obesity does not load signif-
Stress Induced Eating
861
icantly on this factor which might suggest that people who are aware
of their food cravings and dysfunctional eating patterns may be the
ones who are now more successful at preventing or reversing weight
gain. Factor 3 loads primarily with obesity, stress, and a lack of highdensity preference, and less so with increasing age and not smoking.
Older subjects may thus have less sweet-craving, but may simply eat
more of everything as a response to stress. Although we do not have
data regarding previous smoking habits, it may be that at least some
subjects experienced weight gain associated with smoking cessation, a
pattern not uncommon in middle-age. Factor 5 has loadings on age
(lower), stress-eating (less), sweet preference (less), and GSI (higher).
This suggests that younger individuals, while more stressed, tended to
eat less when stressed, and had a preference for salty foods over
sweets.
The factor analysis solution suggested a complex interaction of age,
stress-eating, sweet preference, density preference, and stress. Bar
preference was related to sex, happiness with weight, and density
Preference. Density preference and sweet preference tended not to
load on the same factors, again suggesting that high caloric density
preference was not similar to sweet preference. Density liking and density disliking were not highly correlated either ( Y = .26), and loaded
on separate factors, suggesting that an absence of liking these foods is
not the same as actively disliking them, and vice-versa. This solution
also suggests that density preference and sweet preference are related
to stress-eating and stress (Factors 2, 3, and 5).
In order to further test the hypothesis that food preference is affected
by stress, we used stepwise multiple regression analysis. It was predicted that sweet preference, density liking, and bar preference would
be predicted by being a stress-eater, by being currently stressed (GSI),
and by an interaction of stress-eating and stress. (For example, we predicted that stressed stress-eaters would prefer sweets, high-density
foods and some bars more than nonstressed stress-eaters.) Other variables known to correlate with the criterion variables, such as obesity,
currently dieting, unhappiness with weight, being a boredom-eater,
age and sex were entered first in order to isolate the effects of the
criterion variables. The interaction term was entered last. Summary results from the regressions are shown in Table 5. Density liking was
predicted significantly by both stress-eating and GSI but in opposite
directions. Age approached sigificance; thus, stress-eaters and younger
subjects were more likely to like high-density foods, but current stress
predicted a rating preference of low-density foods. Bar preference was
also predicted to Bar 4 (but not Bars 1-3), with both stress-eating and
current stress predicting lower preference. Sweet preference was not
predicted by any variable. The interaction terms were also not signifi-
862
Willenbring, Levine, and Morley
Table 5. Results of stepwise multiple regression
of eight variables on density-liking (A) and bar
4 preference (B). Variables 1-5 were entered
first, followed by 6 and 7, and variable 8 was
entered last.
F to
enter
P
Simple r
3.78
2.07
1.75
1.88
.41
7.15
7.01
0.03
0.56
,154
,191
.175
,523
,010
.010
.860
- .23
3.90
2.28
1.22
1.33
0.21
13.23
8.85
0.16
.153
.136
,274
,252
.649
,001
,004
,900
(A) Density-liking
1.
2.
3.
4.
5.
6.
7.
8.
~
Age
Sex
Dieting
Obesity
Happy with weight
GSI
Stress eating
Stress eating x GSI
.17
.16
- .18
- .03
- .28
.16
.25
~~
(B) Bar 4 preference
1.
2.
3.
4.
5.
6.
7.
8.
Happy with weight
Sex
Age
Dieting
Obesity
Stress eating
GSI
Stress eating x GSI
.23
- .17
- .07
.03
- .08
- .37
- .37
- .23
cant on any analysis. Regressions done in a similar fashion assessing
interaction effects between obesity, happiness with weight, and dieting
also showed no effects.
DISCUSSION
Our results suggest that food preference, as measured by both ratings of different foods and actual tasting of different snack bars, is associated with self-perception of being a stress-eater and current stress
level, but not by any simple interaction between the two. Preference
for high caloric density foods is predicted by being a stress eater, but
also by a lower level of current stress. This supports the idea that eating may alleviate stress. A lower preference for one of four test food
bars containing more water activity (and therefore a chewier texture)
was predicted by both being a stress eater and high stress. This finding
is in keeping with animal studies suggesting that stress-induced eating
is associated with a preference for crunchy textures (Levine & Morley,
1982). If confirmed by further research, it raises the possibility of de-
Stress Induced Eating
863
veloping low calorie, low Aw (crunchy) bars as an adjunct in the therapy of stress eating. Preference for sweet over salty foods was not
predicted by stress eating or current stress level.
Exploratory factor analysis provided a further delineation of potential
relationships among food preference and other variables. Preference
for high caloric density foods was associated with several indications
of concern over regulating eating, including stress eating and boredom
eating, but not with obesity. On the other hand, the lack of such a
preference was associated with obesity, older age, current stress, and
non-smoking. Actively disliking high density foods also was associated
with disliking a test bar with a higher water activity and chewier texture. Bar preference seemed to be based primarily'on water activity
(texture). Finally, preferring salty foods over sweets was associated
with younger age, higher stress, fasting when stressed, and normal
weight.
Thus, it is possible that there may be several different dynamics operating in different groups of people. People who are conscious of their
food preference and are concerned about their eating may do well at
controlling their weight. There might be different dynamics operatiig
at different times in the life span. An interesting question is whether
there are two different groups of individuals or whether eating dynamics change over time. Finally, these findings support studies in animals
that texture (or water activity) is the primary variable in determining
food preference betwee similar appearing and tasting foods. It would
therefore be more likely that a cruchy diet bar might be received better
by stress-eaters while younger stress-fasters might like salty foods better.
While these findings must be regarded as tentative pending a more
refined and complete study, they help point the way to further research in this area.
The authors wish to thank Donna Kulakowski, Ph.D. and Steven Gangestad,
Ph.D. for their help with this project. This work was supported, in part, by
the Veterans Administration.
REFERENCES
Antelman, S. M., & Caggiula, A. R. (1977). Tails of stress-related behavior: A neuropharmacological approach. In I. Hanin & E. Usdin (Eds.), Animal Models in Psychiatry
and Neurology. Oxford: Pergamon Press.
Derogatis, L., Lipman, R., & Rickels, K. (1974). The Hopkins Symptom Checklist
(HSCL)-A self report symptom inventory. Behavioral Science, 19, 1-16.
Levine, A. S., & Morley, J. E. (1981). Stress induced eating in man. American journal of
Physiology, 241, R72-R76.
Levine, A. S., & Morley, J. E. (1982). Gnawing is the preferred consummatory behavior
initially induced by tail pinch. Appetite, 3 , 135-138.
864
Willenbring, Levine, and Morley
Levine, A. S., Morley, J. E., Wilcox, G. L., Brown, D. M., & Handwerger, B. S. (1982).
Tail pinch behavior and analgesia in diabetic mice. Physiology and Behavior, 28, 3943.
Lowy, M. T., Maickel, R. P., & Yim, G. K. W. (1980). Naloxone reduction of stress
related feeding. Life Sciences, 26, 2113-2118.
Meyer, J. E., & Pudel, V. E. (1977). Experimental feeding in man: A behavioral approach
to obesity. Psychosomatic Medicine, 39, 153-159.
Morley, J. E., & Levine, A. S. (1980). Stress induced eating is mediated through endogenous opiates. Science, 209, 1259-1261.
Morley, J. E., Levine, A. S., Murray, S. S., Kneip, J., & Grace, M. (1982). Peptidergic
regulation of stress-induced eating. American journal of Physiology, 243, R159-R163.
Morley, J. E., Levine, A. S., & Rowland, N. E. (1983). Stress induced eating. Life Sciences,
32, 2169-2182.
Robbins, T. W., & Fray, P. J. (1980). Stress-induced eating: Fact, fiction or misunderstanding? Appetite, 1, 103-133.
Rowland, N. E., & Antelman, S. M. (1976). Stress-induced hyperphagia and obesity in
rats: A possible model for the understanding of human obesity. Science, 191, 310-312.
Schachter, S., Goldman, R., & Gordon, A. (1968). Effects of fear, food deprivation and
obesity on eating. Journal of Personality and Social Psychology, 10, 91-97.
Stunkard, A. J., Grace, W. J., & Wolff, H. G. (1955). The night eating syndrome: A
pattern of food intake among certain obese patients. American journal of Medicine, 19,
78-83.