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RAPID COMMUNICATIONS IN MASS SPECTROMETRY
Rapid Commun. Mass Spectrom. 2006; 20: 3367–3373
) DOI: 10.1002/rcm.2740
Published online in Wiley InterScience (www.interscience.wiley.comAn objective means of diagnosing anorexia nervosa
and bulimia nervosa using 15N/14N and 13C/12C
ratios in hair
Kent A. Hatch1*, Morgan A. Crawford1, Amanda W. Kunz1, Steven R. Thomsen2,
Dennis L. Eggett3, Stephen T. Nelson4 and Beverly L. Roeder1
1Department of Integrative Biology, Brigham Young University, Provo, UT 84602, USA2Department of Communications, Brigham Young University, Provo, UT 84602, USA3Department of Statistics, Brigham Young University, Provo, UT 84602, USA4Department of Geology, Brigham Young University, Provo, UT 84602, USA
Received 10 June 2006; Revised 8 September 2006; Accepted 12 September 2006
*CorrespoBiology,84602, USE-mail: kContract/ties (ORC
An objective means based on the carbon and nitrogen stable isotope analysis of five hairs per
individual is presented for distinguishing between individuals with anorexia nervosa and/or
bulimia nervosa from non-clinical individuals (i.e. clinically normal controls). Using discriminant
analysis, an algorithm has been developed that provides both sensitivity and specificity of 80% in
making diagnoses of individuals with these eating disorders. With further refinements, the results
suggest that it may be also possible to distinguish between individuals with anorexia or bulimia.
Finally, the study shows the value of conducting blind tests and using larger sample sizes of both
control and treatment groups. Both groups are needed to validate the diagnostic value of a method
and to provide measures of sensitivity and specificity of any diagnostic test. Copyright # 2006
John Wiley & Sons, Ltd.
Conservative estimates suggest that as many as 1–5% of all
high school and college-age women in the United States, as
well as increasing numbers throughout the developed world,
are affected in some way by pathological dietary practices.1,2
The two most prevalent forms of disordered eating are
anorexia nervosa, characterized by an extreme fear of weight
gain and a severe concomitant restriction of calories, and
bulimia nervosa, manifested in excessive binging and
purging cycles.3–5
Common to both anorexia and bulimia is the element of
denial. Those who suffer from these illnesses are often
unwilling or unable to recognize and admit to the
psychopathology of their behaviors.3,6,7 This problem raises
specific concerns and challenges for researchers and medical
professionals seeking to obtain accurate dietary information
for diagnostic and evaluative purposes when working with
eating disorder patients. In most cases, doctors and
researchers must rely on potentially unreliable self-reported
data.6,7 This problem underscores the need for and the
usefulness of a clinical test to determine diet and condition
independent of subjective criteria and self-reporting, both to
accurately diagnose and to effectively treat eating disorder
patients.
The measurement of stable isotope ratios in hair has the
potential to provide a unique method for objectively
ndence to: K. A. Hatch, Department of IntegrativeBrigham Young University, 401 WIDB, Provo, UTA.
hatch@byu.edugrant sponsor: Office of Research and Creative Activi-A) of Brigham Young University.
diagnosing individuals with eating disorders.8 When the
body is in an anabolic state, it incorporates dietary proteins
into growing hair. Although the mechanism is unclear, it
appears that 14N is excreted by the organism at a slightly
higher rate than 15N. As a result, 15N concentrates in body
tissues9 (but see also Ref. 10). Thus, as one moves up the food
chain, d15N increases on average at 3% with each step or
trophic level11 (but see also Ref. 12). Because of these trophic
level effects,11–15 the 15N/14N ratios of herbivores (or
vegetarians and vegans) are less than those of predators
(or humans who eat more meat). Likewise, when the body
becomes catabolic, the 15N/14N ratio of the individual’s
tissues increases further due to something functionally
similar to an increase in trophic level.12,16,17 As the individual
loses weight, the individual’s body consumes its own energy
and protein stores. The remaining proteins are 15N enriched
and their amino acids are recycled. Some of these amino
acids are incorporated into new hair growth, providing a
signal of the change in diet.8,15,18,19 Research has long
suggested that the progression of anorexic pathology is
accompanied by changing patterns in dietary habits.20–22
These patterns include periods of low or no carbohydrate
intake and an avoidance of dietary fats.20 They can also
include patterns in which the primary foods consumed are
fruits and vegetables. During this period, meat is often
avoided.21 In one study of anorexic women, for example, 47%
of the participants reported they had become vegetarians.23
Copyright # 2006 John Wiley & Sons, Ltd.
3368 K. A. Hatch et al.
Changes in relative amounts of heavy to light isotopes in the
hair indicate changes in the body’s metabolic state and
dietary intake. Since hair is produced sequentially and is
inert after production by the body, the serial sections of hair
record these changes over time.8 d15N values should decrease
over time as the eating disorder progresses and the
individual eliminates animal products from the diet, thereby
reducing the amount of protein in the diet17,24 (i.e. older
segments of hair would have higher d15N values than newer
segments). Finally, the newest segments of hair would show
an increase in d15N values in individuals who have become
highly catabolic, because they are eating a high fiber diet
providing little protein, they are losing weight rapidly, and
they are metabolizing their own proteins for energy. Since
the d15N values of hairs of normal individuals should follow
no such pattern, we predicted that it would be possible to
distinguish individuals with anorexia or bulimia (or both)
from normal individuals (non-clinical controls) based on
stable isotope analysis of the hairs alone.
The focus of much stable isotope research, to date, has been
to reconstruct dietary histories. Much of this work has been
done by anthropologists, paleontologists, and archeologists
who initially focused on bone collagen.25,26 Nitrogen was
shown to correlate well with diet, but to be approximately
3% more positive than the diet.13,27–29 Carbon in well-
preserved hairs was also found to correlate well with
diet.27,30–34 Schoeninger and DeNiro25 also suggested that
d15N values might be useful in determining the degree of
carnivory in consumers.
Surprisingly, it was not until the late 1990s that researchers
provided experimental evidence suggesting hair as a
superior material for establishing the dietary history of
archeological humans.35 Meanwhile, because of its accessi-
bility and because its sampling was not invasive, the
usefulness of hair in understanding the dietary habits of
living humans was also explored.11,36–38 Stable isotope ratios
in hair were found to closely reflect the diet of living
humans,36,38,39 and to be able to indicate a diet change in 6–
12 days.36 Shampooing and graying were shown not to affect
the stable isotope ratios in hair, but dying and bleaching may
affect them.39,40 Studies of living humans also provided solid
evidence that increasing the proportion of meat in a diet
increases the d15N of the hairs of the individual.19,35,39
Several studies demonstrated the potential that stable
isotope analysis has for providing information on an
individual’s dietary history as well as her/his body
condition over time. By using stable nitrogen isotopic ratios,
researchers have been able to distinguish people eating diets
containing animal protein (such as meat, eggs, and milk)
from people eating vegan diets.19,41 Those individuals eating
diets higher in animal proteins are naturally labeled with
elevated ratios of 15N/14N.15,42,43 Animals that go through
periods of fasting have also been shown to have tissues
enriched in 15N as a result.16,44 Other studies indicated that
the stable isotope ratio analysis of hair serial sections can
determine anabolic and catabolic states in humans.8,18,45
Nevertheless, few attempts have been made to apply
stable isotope analysis of hairs to the diagnosis and treatment
of medical conditions in humans. The use of stable isotope
analysis of hairs has been explored to detect the use of illegal
Copyright # 2006 John Wiley & Sons, Ltd.
drugs,46 to determine adequate zinc intake in infants,47 to
determine the diet of elderly people with senile dementia,43
and to understand the effects of pregnancy.45 A study of
Ross’s geese first suggested that stable isotope analyses
might be used to indicate nutritional stress16,48 (but see also
Ref. 49). Fuller et al.18 were the first to show that nutritional
stress, by affecting the nitrogen balance in pregnant women,
can change the d15N ratios in hairs, although not the d13C
ratios. Most recently, Mekota et al.8 presented evidence that
the dietary changes of women with eating disorders are
recorded in the d15N and d13C of the hairs of these women.
While several studies have demonstrated that nitrogen
isotope ratios of hairs in humans are influenced by diet and
nutritional stress, they were not designed to demonstrate
how to apply stable isotope analysis of hairs to the diagnosis
or treatment of these conditions.
The goal of our study was to determine if stable isotope
analysis of hairs from a sample of young adult women could
provide an objective measure of whether or not they have an
eating disorder. The d13C and d15N values were measured of
the hairs of non-clinical volunteers (i.e. clinically normal
controls) and individuals diagnosed with anorexia nervosa,
bulimia, or both anorexia and bulimia. Individuals diag-
nosed with eating disorders had had these eating disorders
for an average of 4.6 years (standard deviation (SD)¼3.1 years) before the study and first sought treatment after, on
average, 35.5 months (SD¼ 29.2 months). A discriminant
analysis of the d13C and d15N values of the hairs was then
conducted to determine how successfully these data could be
used to separate individuals with eating disorders from
those without. Simple variables were used that avoided any
need for a subjective evaluation of the hairs. Our results
strongly suggest that stable isotope analysis of hairs can
provide an effective, objective diagnosis of whether an
individual has either or both anorexia and bulimia or
whether that individual is clinically normal.
EXPERIMENTAL
Sample collectionHair samples were collected from two groups of female
subjects: inpatients diagnosed as having anorexia, anorexia
and bulimia, or bulimia (20 individuals), and non-clinical
volunteers (23 individuals). The treatment group consisted of
inpatients at an eating disorder treatment facility (The Center
for Change, Orem, UT, USA). All patients were diagnosed by
therapists at the facility as having either anorexia nervosa,
bulimia nervosa, or both anorexia and bulimia, based on the
criteria established in the Diagnostic and Statistical Manual
for Mental Disorders, fourth edition (DSM-IV). While the
diagnoses were made based on the factors listed in the
description of anorexia and bulimia in the DSM-IV, we were
not privy to these data, including the weight and height of
the individuals. The non-clinical volunteers were recruited
from communication classes at Brigham Young University.
Each subject filled out a survey indicating dietary habits and
eating disorder history, and then pulled five hairs from her
own head. The hairs were wrapped in aluminum foil for later
stable isotope analysis. The patients were asked to pull rather
than to cut hairs because cutting hairs can cause loss of
Rapid Commun. Mass Spectrom. 2006; 20: 3367–3373
DOI: 10.1002/rcm
Diagnosing eating disorders using stable isotopes in hair 3369
information. Cutting hairs also makes it difficult to align the
hairs such that when hair sections are combined those
sections of hair were grown during the same period of time.50
The patients were also asked to extract their longest hairs, but
the location from which the hairs should come was not
specified.
The hair samples and surveys of the subjects were assigned
numbers to preserve anonymity. The surveys were kept by
one of the authors (SRT). The hair samples were again
assigned a random identification code to ensure that analysts
did not know the original categories of the subjects. All
participants were given a $10 gift certificate for a local
shopping mall in exchange for their participation in the
study. All procedures were approved by the Institutional
Review Board of Brigham Young University and were in
compliance with federal requirements for the use of human
subjects. In addition, permission was obtained from the
eating disorder treatment facility to collect data from the
inpatients there.
Sample preparation and cleaningThe hair samples were prepared as follows: the five strands
were removed from the foil and the proximal (root) ends
were lined up and glued to a piece of surgical wire with
Super GlueTM (Super Glue, Rancho Cucamonga, CA, USA).
The samples were then sonicated for 15 min in distilled water
and for an additional 15 min in petroleum ether to remove
contaminants from the hair’s surface. The samples were
allowed to dry for 1 h and then all five hairs in a sample were
cut into 1 cm segments, starting with the root end. Each 1 cm
segment (including all five hairs from that segment) was
placed in a separate tin capsule and weighed. The sample
weights ranged from 0.3 to 0.6 mg. Occasionally, a 1 cm
segment of an individual’s hairs did not weigh 0.3 mg. In that
case, a second 1 cm segment was added to the same capsule
to bring it within the proper weight range.
Mass spectrometric analysisTin capsules containing 1–2 cm of hair from five hairs were
combusted using a elemental analyzer (Costech, Valencia,
CA USA) coupled to a Deltaplus mass spectrometer
(Finnigan, Bremen, Germany) for d15N and d13C analysis
of the hair samples. All ratios were expressed as d values
relative to Pee Dee Belemnite51 in the case of carbon and
atmospheric nitrogen52 for nitrogen isotopic ratios. Samples
were corrected using UCLA Carrera (a working standard
from Ian Kaplan’s laboratory, UCLA, d13C¼ 2.52) and
LSVEC (NIST, d13C¼�47) as external standards for carbon,
and USGS 25 (NIST, d15N¼�30.4) and USGS 26 (NIST,
d15N¼ 53.5) as external standards for nitrogen. These
standards were chosen because they bounded the expected
d values of the hair allowing the d values to be corrected via
interpolation.
Statistical analysisAnalysis of variance (ANOVA) and stepwise (forward)
multiple regression analysis were used to determine which
factors would most likely be predictive of an individual
having an eating disorder. These variables were chosen
because visual inspection of the data suggested that they
Copyright # 2006 John Wiley & Sons, Ltd.
might be useful in distinguishing between anorexic, bulimic,
and non-clinical individuals. The variables considered were
as follows:
1. T
he average d15N values of the whole length of hair;2. T
he average d15N values of the length of hair grown beforethe individual entered treatment (subjects had had the
eating disorder for an average of 35.5 months, with a
standard deviation of 29 months, before seeking treat-
ment);
3. T
he average d15N values of the length of hair grown by theindividual after entering treatment. (Since all the subjects
were inpatients at The Center for Change, staff in the
center were able to monitor them and to ensure they were
getting adequate nutrition.);
4. T
he d15N values of the oldest (most distal) section of hair;5. T
he d15N values of the youngest (most proximal) section ofhair;
6. T
he difference in d15N values between the oldest andyoungest sections of hair (i.e. D15N);
7. T
he maximum and minimum d15N values found along thelength of the hair;
8. T
he slopes of the d15N values of hair sampled before andafter the subjects entered treatment; and
9. T
he standard deviation of the d15N values along an indi-vidual’s hair.
The same variables were considered for carbon. These
values were regressed against the following factors: months
since eating disorder was diagnosed, months in treatment,
months working with a nutritionist, age, how frequently the
individual ate meat, and how frequently the individual ate
less than 1200 calories per day. The F-to-enter was 4.00 and
the F-to-remove was 3.99. The variables that were predictive
of any one of these factors were included in the stepwise
discriminant analysis.
The ability of the equations developed by discriminant
analysis to correctly categorize individuals as either having
an eating disorder or as being clinically normal was tested.
The binomial distribution of the normal approximation of the
lower 95% confidence intervals (CIs) for both sensitivity and
specificity of these results was calculated. Only the lower
95% CI was used, since we were primarily concerned with
the degree to which a test might perform worse than, not
better than, the predicted outcome.
ANOVA (type III sums of squares) was used to determine
which of the above variables appeared to be useful in
distinguishing between individuals with anorexia, bulimia,
both anorexia and bulimia, and non-clinical volunteers. Post
hoc analyses were carried out using Fisher’s probable least-
squares difference (PLSD, p< 0.05). Variables that appeared
useful in this regard were also included in the stepwise
discriminant analysis.
RESULTS
ANOVA showed that several factors could be useful in
distinguishing between non-clinical individuals, individuals
with eating disorders and between different eating disorders.
When the d15N values of the oldest sections of hair were
compared with those of the youngest sections of hairs for all
Rapid Commun. Mass Spectrom. 2006; 20: 3367–3373
DOI: 10.1002/rcm
Figure 1. The d15N of the oldest (the 1 cm section at tip)–the
youngest section of hair (the 1 cm section at the base). ‘Both’
indicates individuals with both anorexia and bulimia. Error
bars indicate standard error. Groups that do not share letters
above the bar differ significantly at p< 0.05.
Figure 3. Comparison of the variance in d15N along the
length of hairs between those diagnosed with an eating
disorder and the controls. ‘Both’ indicates individuals with
both anorexia and bulimia. Error bars indicate standard error.
3370 K. A. Hatch et al.
four groups (anorexia, bulimia, both anorexia and bulimia,
and normal volunteers), the differences were significant
(F3,39 ¼ 5.688, p¼ 0.0025). Patients who described themselves
as anorexic showed the greatest difference from the controls.
Patients with both anorexia and bulimia showed less
difference. There was no significant difference between
bulimic patients and controls or between anorexic patients
and patients with both anorexia and bulimia. However,
anorexic patients were significantly different from bulimic
patients (Fig. 1).
The youngest hair growth of patients with either anorexia
or both anorexia and bulimia had significantly lower d15N
values than non-clinical controls while there was no
difference between individuals with bulimia and the non-
clinical controls (F3,39¼ 4.916, p¼ 0.005; Fig. 2). However,
there was no statistical difference between the mean d15N
values of the oldest segments of hair (the 1 cm nearest the tip
of the hair) of any of the groups. Finally, the degree of
variance in d15N along the length of an individual’s hair was
examined and compared with the hair variance between the
groups. Here there was weak evidence (F3,38¼ 2.647,
Figure 2. Comparison of the d15N values of the youngest
section of hair (the 1 cm section at the base) between those
diagnosed with an eating disorder and the controls. ‘Both’
indicates individuals with both anorexia and bulimia. Error
bars indicate standard error. Groups that do not share letters
above the bar differ significantly at p< 0.05.
Copyright # 2006 John Wiley & Sons, Ltd.
p¼ 0.0624) that the hairs of individuals with anorexia were
more variable in d15N along their length than were those
either from individuals with bulimia or from the normal
volunteers and that individuals with both anorexia and
bulimia showed a similar trend (Fig. 3).
Stepwise (forward) multiple regression analyses showed
that the d15N values of the newest sections of hair were
correlated with an individual’s age (t40¼ 2.124, p< 0.04) and
with the amount of meat that an individual consumed each
day (t40 ¼ 4.341, p< 0.0001; R2¼ 0.371). The standard devi-
ation of the d15N values along the length of the hair was
found to correlate with how frequently an individual ate less
than 1200 calories per day (t41¼ 2.803, p¼ 0.008; R2¼ 0.161).
The difference between the d15N values of the oldest and the
youngest sections of hair (distal and proximal ends of the
hair) was found to correlate both with the frequency of eating
less than 1200 calories per day (t40¼ 2.185, p¼ 0.035) and
with the frequency of eating meat (t40¼�1.872, p¼ 0.07;
R2¼ 0.56).
The d13C values of the hairs appeared to be less useful in
distinguishing among individuals with eating disorders and
the non-clinical controls. Nevertheless, the d13C of the oldest–
the d13C of the youngest 1 cm sections of hair differed
significantly between individuals with and without eating
disorders (F1,40¼ 11.237, p¼ 0.002; Fig. 4). Forward stepwise
Figure 4. The d13C of the oldest–the d13C of the newest
sections of hair (i.e. the D13C) was significantly different
(p< 0.05). Error bars indicate standard error.
Rapid Commun. Mass Spectrom. 2006; 20: 3367–3373
DOI: 10.1002/rcm
Table 1. The correct and incorrect diagnosis of individuals as
either having an eating disorder or as being clinically normal
by the discriminant analysis algorithm
Subject group (n)
Subjects assignedto control group
(% of total)
Subjects assignedto eating disordergroup (% of total)
Control (22) 18 (81.8) 4 (18.2)Eating disorder (20) 4 (20) 16 (80)
Diagnosing eating disorders using stable isotopes in hair 3371
multiple regression found that the d13C of the youngest 1 cm
of hair was correlated with the number of months since the
eating disorder began (p¼ 0.04; R2¼ 0.10). The average d13C
value of an individual’s hair after entering treatment was
significantly correlated with the frequency of eating meat
(t36¼ 3.161, p¼ 0.003; R2¼ 0.22).
Thus, through the use of ANOVA and stepwise multiple
regression, the list of variables to include in a stepwise
discriminant analysis was narrowed down to the following:
1. S
Co
tandard deviation in d15N values along the length of an
individuals hair;
2. T
he d15N values of the youngest (most proximal) section ofhair;
3. T
he average d15N value of an individual’s hair afterentering treatment;
4. T
he difference in d13C values between the oldest andyoungest sections of hair; and
5. T
he d13C values of the oldest sections of hair.Other comparisons were not significant and therefore were
not included in the above list.
The forward stepwise discriminant analysis further
reduced the list of useful variables. Variables were added
if p< 0.15 and dropped if their p values increased above 0.15
after other variables were added. The difference between the
d15N values of the oldest and youngest sections of hair was
added first, followed by the standard deviation in d15N
values along the length of the hair. When, however, the
difference in the d13C values of the oldest and the youngest
sections was added, the difference in d15N values between
them was dropped. Finally, the d15N values of the youngest
section of hair were added to the model.
The discriminant analysis procedure used three of the
above variables to produce two equations: one for individ-
uals with normal eating habits (Eqn. (1)) and one for
individuals with eating disorders (Eqn. (2)):
Control ¼ �143:7 þ 14:1S þ 35:0Y � 5:57O (1)
Eating disorder ¼ �125:6 þ 20:1S þ 32:5Y � 3:42O (2)
where S is the standard deviation of the d15N values along the
length of the hairs, Y is the d15N value of the youngest hair
section, and O is the difference in the d13C value of the oldest–
the youngest hair section. The values for the individual are
entered into each equation. If the resulting value is larger for
Eqn. (1), it is inferred that the individual is clinically normal.
If, however, the larger of the two results belongs to Eqn. (2), it
is then inferred that the individual has an eating disorder.
Based on this algorithm, the computer assigned each
individual to either the control group or the eating disorder
group. The algorithm was correct approximately 80% of the
time in both cases (see Table 1).
DISCUSSION
Our study suggests that a statistically sound and objective
measure can be triangulated with the current objective
and subjective measures to improve the diagnosis of
eating disorders. While previous studies have shown that
eating habits,8,15,18,19,35,41–43,45 weight loss or gain,8,18,45 or
pyright # 2006 John Wiley & Sons, Ltd.
eating disorders8 can affect the ratios of stable isotopes in
hair, this study is the first to establish an objective and
statistically sound means, based on stable isotope ratios of
hairs, for diagnosing eating disorders. The diagnosis of an
eating disorder is a triangulation of multiple facts, including
both objective measures (e.g. weight, amenorrhea, body mass
index, change in weight over time) and subjective assess-
ments based on qualitative interviews and self-reporting by
the patient. The accuracy of the subjective assessments is
based on the honesty of the information reported by the
patient, and it can be difficult for a clinician seeing a patient
for the first time to get a clear idea of the true history of the
patient’s disorder. Researchers, clinicians and patients
would therefore greatly benefit from an objective, biological
measure that could aid in diagnosing eating disorders.
While Mekota et al.8 were the first to attempt to analyze
isotope ratios of hair as a means of diagnosing eating
disorders, their study was not designed to establish the
validity of using stable isotope analysis to diagnose eating
disorders. To establish the validity of a method or test to
diagnose a condition, three points need to be considered.
First, the study should be a blind and independent
comparison with a reference standard. Secondly, the study
should include an appropriate spectrum of individuals,
including both those with and those without the condition so
that the sensitivity and specificity of the method can be
evaluated. Thirdly, the results should not influence the
outcome.53,54
Similarly to previous authors, we initially used a visual
examination of the data to evaluate the individual’s eating
disorder. However, this new approach differed in that the
tests were blind so that previous knowledge of the
individuals could not influence the outcome. In addition,
we included non-clinical individuals in our study. This had
not been done previously when studying the effects of eating
disorders8 or nutritional stress18,45 on the carbon and
nitrogen isotope ratios in human hairs.
A blind pilot test was carried out in which one of the
authors (KAH) was given the d15N and d13C values from the
serial analyses of the hairs of six individuals. KAH was told
only that three individuals were normal and three had eating
disorders. By visually examining graphs of the stable isotope
ratios of the hairs down their lengths, KAH was able to
correctly assign all six individuals to their correct group.
This procedure was repeated with all the individuals in the
study. However, this time not only did KAH not know who
had an eating disorder and who did not, but he did not know
how many had an eating disorder and how many did not. On
this occasion, the overall success was only 70%. This
represents only a fair ability to discriminate.55
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DOI: 10.1002/rcm
3372 K. A. Hatch et al.
Typically, when establishing the diagnostic performance
of a test, one should establish the sensitivity and specificity of
the test. The sensitivity is the probability that the test is
positive for an individual who actually has the disease, while
the specificity is the probability that the test is negative for an
individual who does not have the disease.56 The sensitivity of
the subjective, visual method was 75% with a 95% lower
confidence interval (CI) of 59%. The specificity was 65% with
a 95% lower CI of 49%.
Discriminant analysis, however, offered a means by which
one could determine which measures were most important
and predictive. It is also completely objective, since the
algorithms on which the diagnoses are based cannot be
influenced by previous knowledge or biases. Both the
sensitivity and the specificity of this method were better
than that of subjective, visual analysis. The sensitivity using
the algorithms was 80% (95% lower CI¼ 65%) as was the
specificity. Thus the overall ability to discriminate was 80%
(95% lower CI¼ 66%), which indicates good discrimi-
nation.55
While these results are promising, there are several other
potential problems that should be considered. First, it is
important to recognize that the above equations were
established using a North American population. North
Americans differ in their diets from other populations
primarily in that they eat more corn.36,57 Corn is a C4 plant
that has a different carbon isotope ratio from the C3 plants
(e.g. wheat and rice) typical of other industrial societies.58–61
Thus, the above algorithms may not be appropriate for
diagnosing individuals with eating disorders who are
residents of Europe or Japan, for example. However, this
study suggests that if the above algorithms are not universal
in their applicability, algorithms can be developed specific to
the eating habits of other societies.
Secondly, variation in the stable isotope ratios of hairs can
be caused by other factors such as seasonal variations in
diets,62 travel between locations with differing diets,36,37 or
other conditions that affect metabolism.18,45 Incorporating
this kind of information into the above algorithms or
evaluating the results of the algorithms may improve their
accuracy.
Thirdly, the small number of hairs sampled may have
introduced some error. Only five hairs per individual were
sampled, and these hairs occasionally may not have been
representative, particularly if several of the hairs sampled
were in the quiescent stage.50 Previous authors have
suggested using 25 or more hairs to avoid this.8 However,
as the results were 80% correct with regard to both sensitivity
and specificity, this suggests that the small sample size of
hairs was not a major problem. While cutting 25 hairs does
not cause a patient great stress, the most recent information is
lost when hair is cut and it is difficult to properly align the cut
hairs for analysis.50 If one wants to avoid this problem by
pulling hairs, the use of a small sample size reduces the stress
experienced by the patient.
Fourthly, it may also be possible to gain greater accuracy
by sequentially analyzing segments of hair shorter than the 1
cm length used in this study and by avoiding combining
consecutive sections of hair for analysis. Occasionally, 1 cm
segments (for a total of 2 cm) had to be combined in order to
Copyright # 2006 John Wiley & Sons, Ltd.
obtain sufficient mass of hair for analysis. This may also have
introduced some error. However, the study by Schwertl
et al.50 suggests that this is unlikely to cause significant errors
because of the buffering effect that the body’s amino acid
pool has. In addition, the algorithms did not include the
sequence of hairs as a factor, except for comparing the first
and the last sequences. Rather, it included the variance of the
signal along the length of the hair. Order is not important
here nor is the occasional combining of two 1 cm segments
likely to greatly affect the variance along the length of the
hair.
Despite these potential problems, Figs. 1–3 suggest that it
may be possible to develop an algorithm that distinguishes,
not just between individuals with eating disorders and non-
clinical individuals, but also among four different groups:
individuals with anorexia, individuals with bulimia, indi-
viduals with both anorexia and bulimia, and non-clinical
controls. In the above-mentioned figures, individuals with
either anorexia or both anorexia and bulimia were consist-
ently similar, while individuals with only bulimia were
consistently similar to non-clinical volunteers. By definition,
individuals with anorexia or anorexia and bulimia are losing
weight and do not get adequate nutrition.3,63 These
individuals either get their nitrogen largely from plants,
and/or do not get sufficient nitrogen in their diet and are in
nitrogen imbalance. Consequently, the individuals in our
study with either anorexia or anorexia and bulimia differed
from non-clinical volunteers. By contrast, individuals diag-
nosed with only bulimia are maintaining their weight,3,63
and therefore get adequate nutrition, and are likely not to be
in nitrogen imbalance. These individuals may get much of
their nitrogen from meat or milk products in their diets64 and
were therefore similar to normal volunteers. These results do
suggest that further distinctions may be possible.
In conclusion, the fact that students from across the USA
were being compared with patients, that the hairs of these
students included seasonal variation and variation from
travel, that only five hairs from each individual were used,
and that it was still possible to obtain 80% or better accuracy
suggest that we were able to capture the majority of the
information needed for diagnosis and that the above
problems are not overwhelming. Accounting for problems
may refine the above algorithms further, thereby improving
the accuracy of the resulting diagnoses, but our study
suggests that the method is already quite robust.
AcknowledgementsWe would like to acknowledge the help of all the individuals
who volunteered in this study. We are especially thankful to
The Center for Change in Orem, Utah, for its assistance in this
study. We appreciate Vanessa Dewey’s help in editing the
manuscript. All funding for this study was provided by the
Office of Research and Creative Activities (ORCA) of Brig-
ham Young University as part of its effort to support under-
graduate mentored research. Funding was in the form of a
Mentoring Environment Grant to KAH and an Undergradu-
ate Research Scholarship to MAC. The $10 gift certificates
were paid for by a grant from the Wendell J. Ashton Fund,
which provides support for research in the Brigham Young
University Department of Communication.
Rapid Commun. Mass Spectrom. 2006; 20: 3367–3373
DOI: 10.1002/rcm
Diagnosing eating disorders using stable isotopes in hair 3373
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DOI: 10.1002/rcm