Available via license: CC BY-NC 4.0
Content may be subject to copyright.
HaliouaR, etal. BMJ Open Sp Ex Med 2024;10:e002035. doi:10.1136/bmjsem-2024-002035 1
Open access Original research
Exploring the relationship between low
energy availability, depression and
eating disorders in female athletes: a
cross- sectional study
Robin Halioua ,1,2 Paulina Wasserfurth,3 Désirée Toepffer,3
Malte Christian Claussen,1,4 Karsten Koehler 3
To cite: HaliouaR,
WasserfurthP, ToepfferD,
etal. Exploring the relationship
between low energy availability,
depression and eating disorders
in female athletes: a cross-
sectional study. BMJ Open
Sport & Exercise Medicine
2024;10:e002035. doi:10.1136/
bmjsem-2024-002035
Accepted 18 July 2024
1Research Group Sports
Psychiatry, Center for Psychiatric
Research, Department of Adult
Psychiatry and Psychotherapy,
Psychiatric University Clinic
Zurich, University of Zurich,
Zurich, Switzerland
2Praxis Liebestrasse, Winterthur,
Switzerland
3Department Health and Sport
Sciences, TUM School of
Medicine and Health, Technical
University of Munich, Munich,
Germany
4Clinic for Depression and
Anxiety, Psychiatric Centre
Muensingen, Muensingen,
Switzerland
Correspondence to
Dr Robin Halioua;
robin. halioua@ hin. ch
© Author(s) (or their
employer(s)) 2024. Re- use
permitted under CC BY- NC. No
commercial re- use. See rights
and permissions. Published by
BMJ.
ABSTRACT
Objective This cross- sectional study aimed to
investigate the role of low energy availability (LEA) in
the interplay between depression and disordered eating/
eating disorders (DE/EDs) among female athletes. The
International Olympic Committee consensus statement
on Relative Energy Deciency in Sport (REDs) identied
depression as both an outcome of LEA and a secondary
risk factor for REDs. However, the direct link between LEA
and depression has yet to be fully established.
Methods We assessed 57 female athletes participating
in weight- sensitive sports at different levels of competition
training at least four times a week. Assessment was
conducted using laboratory analyses, clinical interviews
and the Patient Health Questionnaire- 9 questionnaire.
Participants were recruited through various channels,
including German sports clubs, Olympic training centres,
social media platforms and the distribution of yers at
competitions. Indicators of LEA were dened if at least
two of the following three physiological indicators were
present: menstrual disturbances, suppressed resting
metabolic rate and suppressed thyroid hormones. Logistic
and linear regression analysis were used to examine the
relationship between LEA, depression and DE/ED.
Results The lifetime prevalence of depressive disorders
was 29.6%. 19% of the participants were diagnosed with
an ED, and an additional 22.6% exhibited DE.
LEA was not signicantly associated with either lifetime
prevalence of depressive disorders or current depressive
symptoms. However, a signicant association was found
between depression and DE/ED in terms of both lifetime
prevalence and current depressive symptoms. DE/
ED increased the probability of lifetime prevalence of
depressive disorders by 34% (19%–49%) compared with
normal eating behaviour.
Conclusion We found no evidence that LEA is an
independent factor for depression in female athletes. Its
association with LEA and REDs appears to occur primarily
in the presence of DE/ED.
INTRODUCTION
Low energy availability (LEA) refers to a state
where energy intake is inadequate to sustain
optimal functioning of all physiological
systems after accounting for exercise- related
energy expenditure.1 Problematic LEA
represents a maladaptive response to severe
and/or prolonged LEA that disrupts various
body systems1 and is understood as the under-
lying cause of Relative Energy Deficit in
Sports (REDs), a syndrome of impaired phys-
iological and/or psychological functioning
experienced by female and male athletes.2–4
The impact of problematic LEA on mental
health and the influence of psychological
factors are not as well understood as the
physiological consequences. Eating disorders
(EDs) and disordered eating (DE) behaviour
are considered significant risk factors for
LEA and REDs, as they can be both a cause
and consequence and, thus, are considered
a primary indicator of REDs.4 5 The Interna-
tional Olympic Committee (IOC) consensus
statement also identifies depressive symptoms
WHAT IS ALREADY KNOWN ON THIS TOPIC
⇒Depression is recognised as both a mental health
outcome and a secondary risk factor of Relative
Energy Deciency in Sport (REDs). However, the re-
lationship between low energy availability (LEA) and
depression has not been fully established, as exist-
ing research on depression has neither been based
on clinical data nor accounted for potential comorbid
eating disorders (EDs).
WHAT THIS STUDY ADDS
⇒We found no evidence that LEA is associated with
the lifetime prevalence of depressive disorders or
current depressive symptoms in participants with or
without disordered eating/EDs (DE/EDs).
HOW THIS STUDY MIGHT AFFECT RESEARCH,
PRACTICE OR POLICY
⇒The association between LEA and depression ap-
pears to occur primarily in the presence of DE/ED.
Therefore, further investigation is needed before
conclusively classifying depression as a mental
health outcome and a secondary risk factor of REDs.
copyright. on August 29, 2024 by guest. Protected byhttp://bmjopensem.bmj.com/BMJ Open Sport Exerc Med: first published as 10.1136/bmjsem-2024-002035 on 28 August 2024. Downloaded from
2HaliouaR, etal. BMJ Open Sp Ex Med 2024;10:e002035. doi:10.1136/bmjsem-2024-002035
Open access
and affective disorders as adverse mental health outcomes
associated with problematic LEA and REDs, considering
clinically diagnosed depression a secondary indicator
of REDs.4 A narrative review by a subgroup of the IOC
consensus on REDs discussed the temporal relationship
between exposure to LEA and mental health outcomes.5
It was suggested that mood changes, fatigue and psycho-
logical conflict may be expected within days and weeks,
whereas the development of depressive symptoms may
require longer exposure to LEA.5
However, the current literature on the association
between LEA and depressive symptoms and/or clinically
diagnosed depression is limited. To our knowledge, only
three studies have investigated the relationship between
LEA and depressive symptoms.6–8 Although these studies
provide valuable insights, their findings may be subject
to interpretation due to methodological limitations.
Ackerman et al (2019) reported a positive association
between LEA and depressive symptoms in a large- scale
(n=1000) cross- sectional study. However, LEA assess-
ment relied on DE/ED screening questionnaires, which
may have primarily captured the association between
DE/ED and depressive symptoms. Furthermore, diag-
noses of ED and depression were based solely on
questionnaires without clinical confirmation from diag-
nostic interviews. In the study by Rogers et al (2021),
LEA was established through objective laboratory anal-
yses and defined as a low resting metabolic rate (RMR).
And although clinical interviews were conducted, find-
ings from these were not included in the final analysis,
which instead solely relied on questionnaire responses
that considered depressive symptoms only. Mathisen
et al (2019) conducted a longitudinal study and found
an increase in depressive symptoms in female fitness
athletes preparing for a competition.8 However, the
relationship between LEA and depressive symptoms was
not directly evaluated, and the assessment of depressive
symptoms relied solely on questionnaires. Furthermore,
the increased depressive symptoms remained well below
clinical significance. Neither study accounted for poten-
tial comorbid DE/ED, which could have influenced the
observed relationship.
Investigating the association between LEA and
depression requires consideration of comorbid DE/
ED, which are both a possible cause of LEA and share
a well- established comorbidity with depression in non-
athletic populations.9 Preliminary findings suggest this
comorbidity may also exist in the athletic context.10 In
response to the IOC’s call for more studies to explore
the reciprocal function of psychological variables with
LEA,2 5 we aimed to examine the role of LEA in the inter-
play between DE/ED and depression more closely. As the
study was exploratory in nature, no specific hypotheses
were formulated. This allowed for an open investiga-
tion into the association between LEA and depression in
athletes accounting for DE/ED, as well as an exploration
of whether LEA increases the risk of depression in those
with ED/DE.
METHODS
Study design, setting and participants
This cross- sectional study examined physiological indi-
cators of problematic LEA, depression and DE/ED in
female athletes using state- of- the- art assessments: labo-
ratory analyses, clinical interviews and questionnaires.
Laboratory analyses were performed at our core facility
at the Technical University of Munich, and clinical inter-
views were conducted via telemedicine by a trained
psychiatrist. Participants were recruited through various
channels, including German sports clubs, Olympic
training centres, social media platforms and the distribu-
tion of flyers at competitions. The study was approved by
the Technical University Munich’s Ethical Review Board
(registration number: 347/21 S) and adhered to the
Declaration of Helsinki. All participants provided written
informed consent. Recruitment and data collection
lasted from November 2021 until April 2023.
Eligibility criteria
The eligibility criteria required participants to be female
athletes aged 18–39 years engaged in weight- sensitive
sports (cycling, triathlon, long- distance running, swim-
ming, cross- country skiing, biathlon and ballet) who
trained ≥4 times weekly. Exclusion criteria encompassed
the use of hormonal contraceptives, pregnancy, breast-
feeding or chronic illness or acute injury at the time of
potential inclusion.
Clinical assessment of depression and eating disorders
The clinical assessment comprised clinical interviews
conducted by a board- certified psychiatrist via a secure
online video platform, along with the completion of
questionnaires. All interviews were conducted following
the laboratory analysis and lasted approximately 45 min.
Depression
The clinical interview was conducted using Module A
of the Structured Clinical Interview for Diagnostic and
Statistical Manual of Mental Disorders, Fifth Edition
(DSM- 5), Clinician Version (SCID- 5- CV). The SCID-
5- CV is a semistructured interview for diagnosing mental
disorders according to DSM- 5. Each DSM- 5 criterion is
associated with specific interview questions to assist the
interviewer in assessing the criterion. Both current and
past depressive symptoms were assessed. This allowed for
an evaluation of both current depressive symptomatology
and the lifetime prevalence of depressive disorder.
The Patient Health Questionnaire- 9 (PHQ- 9) ques-
tionnaire was administered in addition to the clinical
interview. The PHQ- 9 corresponds to the Depression
Module of PHQ (PHQ- D) and consists of nine ques-
tions related to depressive symptoms. It was developed
as a screening instrument for diagnosing depression for
routine use in somatic medical settings. To minimise
potential bias, the interviewer was kept blinded to the
participants’ questionnaire outcomes throughout the
data collection process.
copyright. on August 29, 2024 by guest. Protected byhttp://bmjopensem.bmj.com/BMJ Open Sport Exerc Med: first published as 10.1136/bmjsem-2024-002035 on 28 August 2024. Downloaded from
3
HaliouaR, etal. BMJ Open Sp Ex Med 2024;10:e002035. doi:10.1136/bmjsem-2024-002035
Open access
Eating disorders and disordered eating
The clinical interview was conducted using the German
version of the Eating Disorder Examination by Fair-
burn and Cooper, a structured interview for assessing
the specific psychopathology of ED.11 12 It assesses
eating behaviour across four scales: ‘Restraint’, ‘Eating
Concern’, ‘Weight Concern’ and ‘Shape Concern’. In
addition to these scales, 14 additional diagnostic items
enable clinical diagnosis of ED.
DE was only identified in cases where clear pathological
behaviours and/or distorted body image were present,
without meeting the diagnostic criteria for an ED. The
assessment took into account the context of sports and
the resulting demands on eating behaviour.10 The study
set a high threshold for DE, placing it closer to ED than
to normal, functional eating behaviour.
Assessment of LEA
Classication of menstrual status
Participant menstrual status was determined retrospec-
tively via phone interviews, with information collected
on menstruation within the last 3 months. Based on their
cycle lengths, participants were classified as eumenor-
rheic (28±7 days), oligomenorrheic (cycle length >35
days), primary amenorrheic (no menarche after 15 years
of age) or secondary amenorrheic (absence of ≥3 consec-
utive periods or no menses for ≥90 days).13
Laboratory examinations
For participants with regular or irregular periods, labo-
ratory examinations were scheduled during the early
follicular phase (days 3–5 after period onset), while for
those with amenorrhoea, the examination was conducted
at the earliest opportunity. Prior to measurement, partic-
ipants refrained from exercise, caffeine and alcohol for
24 hours and arrived at the laboratory after a 12- hour
overnight fast in a rested state.
Anthropometry and body composition
Participants wore only underwear or tightly fitting swim-
wear for measurements. Height was measured to the
nearest 0.1 cm using a stadiometer (seca 217, SECA,
Hamburg, Germany). Body composition was assessed
using air displacement plethysmography (ADP; BOD
POD, COSMED, Rome, Italy), with body mass being
measured using a built- in scale. The device was calibrated
before each measurement session. Participants wore a
swim cap and remained still during the measurement.
Fat mass and fat- free mass were determined using the Siri
equation based on ADP- measured body density.14
Resting metabolic rate
RMR was assessed using open- circuit indirect calorimetry
with a canopy (Q- NRG, COSMED, Rome, Italy) at room
temperature (20–25 °C).15 The device was calibrated with
external gas and room air prior to each measurement,
and ethanol burning tests were conducted monthly.
Participants rested supine for ~10 min before data collec-
tion, which lasted at least 30 min. RMR (kcal/day) was
calculated using the Weir equation from steady- state
data, which was defined as a coefficient of variation ≤10%
in steady- state oxygen consumption and carbon dioxide
production.16
Blood samples
Blood samples were drawn from the antecubital vein and
free triiodothyronine (fT3) was analysed by an external
laboratory (Labor Becker MVZ GbR, Munich, Germany).
Classication of LEA
Following the 2023 IOC REDs consensus statement,4
cases of LEA were operationally defined if at least two of
the following three physiological indicators were present:
menstrual disturbances (amenorrhoea and oligomen-
orrhoea), suppressed RMR (<30 kcal/kg/fat- free mass
(FFM)) and suppressed thyroid hormones (fT3 below
the IOC- recommended laboratory reference ranges:
within or below the lowest quartile). Suppressed RMR
was selected as an indicator due to its association with
LEA,17 without being directly related to DE/ED.
Statistical analysis
Sample size
Based on the existing literature on LEA prevalence,7
a sample size of 50 was determined, allowing for
approximately 30% of LEA cases. To account for a
15%–20% dropout rate between measurements, we
aimed for a total of 60 participants.
Descriptive analysis
We calculated frequencies, means and 95% CIs for demo-
graphic data and assessment instruments.
Main analysis
To examine the role of LEA in the interplay between
depression and DE/ED, logistic regression and linear
regression analyses were conducted. The lifetime prev-
alence of diagnosed depressive disorder was chosen as
the outcome for logistic regression, while the outcome
for linear regression was current depressive symptoms
according to PHQ- 9 scores. In both analyses, LEA was
used as a predictor variable, with DE/ED serving as a
control variable. Given the high threshold applied for DE
in this study, DE and ED were examined as a combined
variable. In both regression analyses, DE and ED were
also inserted as separately coded variables, aiming to
explore the potential differences in outcomes compared
with analyses combining DE/ED. Interactions between
LEA and DE/ED were examined by the likelihood ratio
test.
The OR and Average Marginal Effects (AME) were
calculated to interpret the effect of LEA and DE/ED. In
this case, AMEs reflect the average change in predicted
probability for each observation in factorial variables
while holding the other variable constant.18 Predicted
probabilities for lifetime depressive disorder and
predicted margins for depressive symptoms were also
calculated.
copyright. on August 29, 2024 by guest. Protected byhttp://bmjopensem.bmj.com/BMJ Open Sport Exerc Med: first published as 10.1136/bmjsem-2024-002035 on 28 August 2024. Downloaded from
4HaliouaR, etal. BMJ Open Sp Ex Med 2024;10:e002035. doi:10.1136/bmjsem-2024-002035
Open access
Missing data
We conducted Multiple Imputation by Chained Equa-
tions to analyse 10 multiply- imputed datasets, addressing
incomplete variables using the mi impute command in
Stata. Rubin’s combination rules were applied to adjust
estimates and their standard errors for imputation
uncertainty. Additionally, we performed a complete case
analysis for comparison.
Statistical software
Stata Statistical Software: Release V.16.1. College Station,
Texas was used to analyse the data.
Patient and public involvement
As our study focuses on female athletes in weight- sensitive
sports, no patients were involved. Participants were first
engaged in the study during the recruitment phase.
Some participants subsequently recruited additional
participants from their own circles. Results of laboratory
measurements and clinical interviews were shared with
participants. Assistance was provided to one participant
in arranging therapy for her ED. Results and new insights
will be provided to the participants.
Equity, diversity and inclusion statement
Our study is on female athletes in weight- sensitive sports.
The author group consists of junior, mid- career and
senior researchers from different disciplines in Switzer-
land and Germany. Participants were recruited through
various channels to ensure a broad spectrum of socio-
economic backgrounds. Nevertheless, our patient cohort
predominantly represents the middle to upper socio-
economic strata. Clinical interviews were conducted via
telemedicine to enhance accessibility.
RESULTS
Participants
A total of 93 athletes provided written informed consent
to participate in the study, with 57 completing on- site
measurements. Demographics, laboratory assessments
and clinical diagnoses of depressive disorder and ED are
presented in table 1.
Missing data
The assessment and clinical diagnosis of depression and
DE/ED were completed for 53 (92.9%) participants.
Four participants did not participate in the clinical inter-
views, one of whom did not provide a blood sample.
Three participants reported taking thyroid medication,
which was treated as missing values for low fT3 and RMR
<30 kcal/kg/FFM. Non- participation in clinical inter-
views was treated as missing values for lifetime depressive
disorder and DE/ED. The missing blood analysis was
treated as a missing value for low fT3. There were a total
of five missing values for LEA/Controls, four for lifetime
depressive disorders and four for DE/ED. Multiple impu-
tation and complete case analysis lead to similar results;
therefore, we present only the former.
Main results
Logistic and linear regressions
Table 2 summarises the results of the logistic regression
analysis on lifetime prevalence of depressive disorders
and the linear regression analysis on current depres-
sive symptoms according to the PHQ- 9. LEA was not
statistically associated with either lifetime prevalence of
depressive disorders or current depressive symptoms.
DE/ED showed statistical significance in both regression
analyses. There was no significant interaction between
LEA and DE/ED.
DE/ED increased the probability of lifetime prevalence
of depressive disorders by 34% (19%–49%) compared
with normal eating behaviour. The predicted probabili-
ties for female athletes with DE/ED and concurrent LEA
were 57.9% (25.3%–90.5%) and 51.5% (27.7%–75.3%)
for those without concurrent LEA. The difference of
6.4% was statistically not significant (p=0.73). Those
with a DE/ED and concurrent LEA yielded a predicted
PHQ- 9 score of 7.5 (5.5–9.4), and those without concur-
rent LEA yielded a score of 7.7 (6.2–9.2). The difference
was statistically not significant (p=0.71). Figure 1 pres-
ents the predicted probabilities for lifetime prevalence of
depressive disorders, while figure 2 displays the predicted
scores of the PHQ- 9.
DISCUSSION
The aim of this study was to examine the role of LEA
in the interplay between depression and DE/ED in an
exploratory investigation. Our findings indicate that
the previously established association between LEA and
depression may be mediated by comorbid DE/ED. We
found no evidence that indicators of LEA are associated
with the lifetime prevalence of depressive disorders or
current depressive symptoms in participants regardless of
DE/ED status. However, a strong association was found
between DE/ED and depression, in terms of both life-
time prevalence and current symptoms.
Energy availability
LEA alone did not increase the prevalence of lifetime
depressive disorder or current depressive symptoms in
those with or without DE/ED. Our results indicate that
DE/ED as an underlying cause of LEA has a more signif-
icant impact on depression than LEA itself. LEA may
result from intentional or unintentional undereating.19
In the case of intentional undereating, it is important to
distinguish DE/ED from controlled eating for perfor-
mance enhancement and other functional reasons.
Although both can result in LEA, they are driven by
different motivational factors and seem to play a deci-
sive role in whether LEA is associated with depression or
not. Given that DE/EDs typically have a long course and
that LEA was not associated with depression in those with
DE/EDs, it seems unlikely that there is a temporal rela-
tionship between prolonged exposure to LEAs and the
development of depressive symptoms. Taken together,
depression as a direct mental health outcome resulting
copyright. on August 29, 2024 by guest. Protected byhttp://bmjopensem.bmj.com/BMJ Open Sport Exerc Med: first published as 10.1136/bmjsem-2024-002035 on 28 August 2024. Downloaded from
5
HaliouaR, etal. BMJ Open Sp Ex Med 2024;10:e002035. doi:10.1136/bmjsem-2024-002035
Open access
from a physiological causal chain involving exposure to
LEA seems unlikely.
This contradicts the findings of previous studies by
Ackermann6 and Rogers,7 who found a positive associ-
ation between LEA and depression. The difference in
results with Ackermann’s study can be attributed to their
use of the DE/ED screens as a marker for LEA, essen-
tially confirming the association between LEA and DE/
ED observed in our study. Our study’s more precise
operationalisation of LEA, which incorporates several
Table 1 Descriptive characteristics of the study sample
Variables Controls (39) LEA (14) Total (57)
Age (years), mean±SD 28.4±5.7 27.3±4.2 27.9±5.3
Height (cm), mean±SD 168.7±5.8 169.5±5.5 168.8±5.5
Weight (kg), mean±SD 62.0±6.5 55.8±5.3 60.5±7.1
BMI (kg/m²), mean±SD 21.7±1.7 19.4±1.3 21.2±2.1
Education (%)
Academic 61.5 100 70.2
High school 25.6 0 21.1
Non- academic 2.6 0 1.8
Secondary school 10.3 0 7
Training level (%)
National team 7.7 0 5.3
Professional 5.1 14.3 7
Club 41.0 21.4 36.8
Individual with competition 38.5 57.1 43.9
Individual without competition 7.7 7.1 7
Menstrual status (%)
Amenorrhoea 7.7 64.3 21.1
Oligomenorrhoea 20.5 21.4 21.1
Eumenorrhoea 71.8 14.3 57.9
RMR (kcal/kg FFM), mean±SD 30.9±2.6 27.4±1.7 30.0±2.8
fT3 (ng/L), mean±SD 2.7±0.3 2.2±0.5 2.6±0.4
Depressive disorder (%)
No depressive disorder 71.1 61.5 68.5
Mild depressive episode m m 1.9
History of one depressive episode in the past 10.5 15.4 11.1
Recurrent depressive disorder, current episode in remission 15.8 15.4 14.8
Recurrent depressive disorder, current episode mild 2.6 7.7 3.7
Lifetime prevalence 28.9 38.5 29.6
PHQ- 9 (0–28), mean±SD 5.8±3.6 5.8±3.6 5.8±3.5
Eating disorder (%)
Normal eating behaviour 60.5 46.2 58.5
Disordered eating 23.7 23.1 22.6
Bulimia nervosa 2.6 7.7 3.8
Anorexia nervosa 0.0 7.7 1.9
Bulimia nervosa of low frequency/limited duration 7.9 0.0 5.7
Atypical anorexia nervosa 2.6 7.7 3.8
Purging disorder 2.6 7.7 3.8
Eating disorder or disordered eating (%) 39.5 53.8 41.5
Unless otherwise specied, mean and SD are reported for continuous variables, and proportions are reported for categorical data.
*Depression Module of the Patient Health Questionnaire.
BMI, body mass index; fT3, free triiodothyronine; LEA, Low energy availability; m, missing; PHQ- 9, Patient Health Questionnaire- 9;
RMR, resting metabolic rate.
copyright. on August 29, 2024 by guest. Protected byhttp://bmjopensem.bmj.com/BMJ Open Sport Exerc Med: first published as 10.1136/bmjsem-2024-002035 on 28 August 2024. Downloaded from
6HaliouaR, etal. BMJ Open Sp Ex Med 2024;10:e002035. doi:10.1136/bmjsem-2024-002035
Open access
physiological indicators such as low RMR, low T3, and
menstrual dysfunction, may explain the difference from
Rogers’ findings, which identified LEA only using low
RMR. Furthermore, Rogers’ study did not consider poten-
tial comorbid DE/ED in their analysis. Our results are in
line with those in the non- athletic context, which found
no correlation between nutritional status and depressive
symptoms in individuals with anorexia nervosa.20 21
Depression
When compared with the general population, partic-
ipants in the present study showed higher levels of
depression, both in terms of lifetime prevalence and
current symptoms. The overall lifetime prevalence was
29.6%, surpassing the 10%–15% range observed in the
general population.22 23 Additionally, the average PHQ- 9
score was elevated at 5.8, exceeding the normative value
of 3.624 and aligning with scores observed in representa-
tive patient samples from general hospitals in Germany.25
The findings are consistent with Schaal et al (2001),26 who
found a lifetime prevalence of 30% in women who partic-
ipate in aesthetic sports. Only 5.6% of the participants
in our sample exhibited clinically diagnosed depression
during the clinical interviews. Therefore, the score from
the PHQ- 9 should be interpreted as mainly subclinical.
However, in light of the higher lifetime prevalence, it
may have clinical significance as it may indicate a higher
overall burden of depressive symptoms.
DE/ED
The prevalence of ED (19%) and DE (22.6%) in our
sample was higher than that of the general popula-
tion,27 which is consistent with the findings of similar
studies.28 29 The majority (13.3%) classified as Other
Specified Feeding and Eating Disorder. Participants
with LEA primarily displayed atypical anorexia nervosa
and purging disorder, whereas those with adequate EA
showed bulimia of low frequency/limited duration.
Notably, individuals with LEA were twice as likely to
have an ED (30.8%) when compared with those with
Table 2 Results from the logistic and linear regressions
Logistic regression on lifetime prevalence of depressive
disorders
Variable OR (95% CI) SE P value
LEA* 1.3 (0.29 to 5.75) 0.99 0.73
DE/ED† 7.59 (1.93 to 29.82) 5.29 <0.01
Constant 0.14 (0.05 to 0.43) 0.08 <0.01
Linear regression on current depressive symptoms
according to the PHQ- 9
Variable β(95% CI) SE P value
LEA* −0.23 (−2.33 to 1.87) 1.04 0.83
DE/ED† 3.09 (1.33 to 4.85) 0.88 <0.01
Intercept 4.62 (3.42 to 5.82) 0.6 <0.001
*Low energy availability.
†Disordered Eating / Eating disorder.
DE/ED, disordered eating/eating disorder; LEA, low energy
availability; PHQ- 9, Patient Health Questionnaire- 9.
Figure 1 Predicted probabilities for lifetime prevalence of depressive disorders. For those without LEA (controls), the
predicted probabilities for lifetime prevalence of depressive disorders were 12.4% (0.2%–24.5%) with normal eating behaviour
and 51.5% (27.7%–75.3%) with DE/ED. For those with LEA and normal eating behaviour, the probability was 14.3% (0%–29%)
compared with 57.9% (25.3%–90.5%) with concurrent DE/ED. Whiskers represent the 95% CI. DE/ED, disordered eating/eating
disorder; LEA, low energy availability.
copyright. on August 29, 2024 by guest. Protected byhttp://bmjopensem.bmj.com/BMJ Open Sport Exerc Med: first published as 10.1136/bmjsem-2024-002035 on 28 August 2024. Downloaded from
7
HaliouaR, etal. BMJ Open Sp Ex Med 2024;10:e002035. doi:10.1136/bmjsem-2024-002035
Open access
adequate EA (15.7%); however, DE occurred at the
same frequency (23 %) in both groups. This under-
scores the necessity to consider LEA and DE/ED as
distinct entities. While DE/ED is a prevalent under-
lying cause of LEA, a notable proportion (46.2%) of
those with LEA did not exhibit an associated DE/ED.
Furthermore, 40% of individuals without LEA still
exhibited a DE/ED.
Interplay between depression and DE/ED
A strong association was found between DE/ED and
depression, in terms of both lifetime prevalence and
current depressive symptoms. The presence of DE/ED
increased the likelihood of experiencing depression at
least once in one’s lifetime by 35% and current depres-
sive symptoms by three points on the PHQ- 9 scale.
Participants with DE/ED had a lifetime prevalence
of depressive disorder ranging from 51.5% (without
concurrent LEA) to 57.9% (with concurrent LEA).
This is in line with findings in the general and athletic
population, which indicate a high rate of comorbidity
between depression and ED, suggesting a bidirec-
tional relationship.10 27 30 Our findings indicate that
the previously established association between LEA
and depression may be mediated by comorbid DE/ED.
Additionally, this comorbidity may explain the higher
prevalence of depression in weight- sensitive samples
compared with other sports.26 31
Clinical implications and future research
REDs is conceptualised as an etiological syndrome
based on problematic LEA. Within this framework,
depression is both considered a mental health outcome
and a secondary risk factor of REDs.4 From a theoretical
perspective, there is insufficient evidence to conclude
that LEA is in fact a causative factor for depression. Our
data demonstrate that the association between LEA and
depression appears to occur primarily in the presence
of DE/ED. Therefore, further investigation is needed
before conclusively classifying depression as a mental
health outcome and a secondary risk factor of REDs.
Limitations
First, while ensuring that participants represented the
primary target audience of REDs, our inclusion criteria
of a minimum of four training sessions per week may
have excluded participants with severe depressive symp-
toms, as they may not have been able to maintain such
a sports regimen at this frequency. Second, despite
our efforts to represent a broad socioeconomic spec-
trum, the generalisability is limited by the fact that the
participants are predominantly from middle to upper
socioeconomic strata with educational backgrounds.
Third, the use of state- of- the- art methodology involving
lab measurements and clinical interviews resulted in a
relatively small sample size. As such, caution is neces-
sary when interpreting effect sizes as they may be
susceptible to inflation. Fourth, by using cross- sectional
data, we are precluded from drawing causal conclu-
sions from the associations we found.
Figure 2 Predicted scores of the PHQ- 9. For those without LEA (controls), the predicted PHQ- 9 score was 4.6 (3.4–5.8) with
normal eating behaviour and 7.7 (6.2–9.2) with DE/ED. For those with LEA and normal eating behaviour, the predicted score
was 4.4 (2.4–6.4) compared with 7.5 (5.5–9.4) with concurrent DE/ED. Whiskers represent 95% CI. DE/ED, disordered eating/
eating disorder; LEA, low energy availability; PHQ- 9, Patient Health Questionnaire- 9.
copyright. on August 29, 2024 by guest. Protected byhttp://bmjopensem.bmj.com/BMJ Open Sport Exerc Med: first published as 10.1136/bmjsem-2024-002035 on 28 August 2024. Downloaded from
8HaliouaR, etal. BMJ Open Sp Ex Med 2024;10:e002035. doi:10.1136/bmjsem-2024-002035
Open access
Acknowledgements We would like to thank Mona Saller, Lena Fladerer,
Josephine Ruf and Vanessa Corrêa Mascarenhas for their assistance. We would
further like to thank all volunteers who participated in the study.
Contributors Conceptualisation: KK and RH. Methodology: KK, RH and PW.
Investigation: RH, PW and DT. Formal analysis: RH. Data curation: RH, PW and DT.
Writing—original draft preparation: RH. Writing—review and editing: PW, KK, MCC
and DT. Funding acquisition: KK, RH and MC. Resources: MCC and KK. Supervision:
KK and MCC. RH is the guarantor. Since English is not the rst author’s rst
language, AI was used to make linguistic corrections. The use of AI was strictly
conned to correcting language errors. No content interpretations or statistical
analyses were conducted using AI.
Funding This study was funded by the Robert- Enke- Foundation. PW is supported
by a fellowship by the Bavarian Equal Opportunity Scholarship Program.
Disclaimer AI use statement: since English is not the rst author's rst language,
AI was used to make linguistic corrections. The use of AI was strictly conned to
correcting language errors. No content interpretations or statistical analyses were
conducted using AI.
Competing interests None declared.
Patient and public involvement Patients and/or the public were involved in the
design, conduct, reporting or dissemination plans of this research. Refer to the
Methods section for further details.
Patient consent for publication Consent obtained directly from patient(s).
Ethics approval This study involves human participants and was approved by
the Ethical Review Board of the Technical University Munich (registration number:
347/21 S). Participants gave informed consent to participate in the study before
taking part.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available upon reasonable request. The
datasets used and/or analysed during the current study are available from the rst
author on reasonable request.
Open access This is an open access article distributed in accordance with the
Creative Commons Attribution Non Commercial (CC BY- NC 4.0) license, which
permits others to distribute, remix, adapt, build upon this work non- commercially,
and license their derivative works on different terms, provided the original work is
properly cited, appropriate credit is given, any changes made indicated, and the
use is non- commercial. See:http://creativecommons.org/licenses/by-nc/4.0/.
ORCID iDs
RobinHalioua http://orcid.org/0000-0002-1334-4916
KarstenKoehler http://orcid.org/0000-0002-9618-2069
REFERENCES
1 Redman LM, Loucks AB. Menstrual disorders in athletes. Sports
Med 2005;35:747–55.
2 Mountjoy M, Sundgot- Borgen J, Burke L, etal. The IOC consensus
statement: beyond the Female Athlete Triad--Relative Energy
Deciency in Sport (RED- S). Br J Sports Med 2014;48:491–7.
3 Mountjoy M, Sundgot- Borgen J, Burke L, etal. International
Olympic Committee (IOC) Consensus Statement on Relative Energy
Deciency in Sport (RED- S): 2018 Update. Int J Sport Nutr Exerc
Metab 2018;28:316–31.
4 Mountjoy M, Ackerman KE, Bailey DM, etal. 2023 International
Olympic Committee’s (IOC) consensus statement on Relative Energy
Deciency in Sport (REDs). Br J Sports Med 2023;57:1073–98.
5 Pensgaard AM, Sundgot- Borgen J, Edwards C, etal. Intersection of
mental health issues and Relative Energy Deciency in Sport (REDs):
a narrative review by a subgroup of the IOC consensus on REDs. Br
J Sports Med 2023;57:1127–35.
6 Ackerman KE, Holtzman B, Cooper KM, etal. Low energy availability
surrogates correlate with health and performance consequences
of Relative Energy Deciency in Sport. Br J Sports Med
2019;53:628–33.
7 Rogers MA, Appaneal RN, Hughes D, etal. Prevalence of impaired
physiological function consistent with Relative Energy Deciency in
Sport (RED- S): an Australian elite and pre- elite cohort. Br J Sports
Med 2021;55:38–45.
8 Mathisen TF, Heia J, Raustøl M, etal. Physical health and symptoms
of relative energy deciency in female tness athletes. Scand J Med
Sci Sports 2020;30:135–47.
9 Godart NT, Perdereau F, Rein Z, etal. Comorbidity studies of eating
disorders and mood disorders. Critical review of the literature. J
Affect Disord 2007;97:37–49.
10 Tan JOA, Calitri R, Bloodworth A, etal. Understanding Eating
Disorders in Elite Gymnastics. Clin Sports Med 2016;35:275–92.
11 Fairburn C, Wilson G. Binge eating: nature, assessment, and
treatment. J Nerv Ment Dis 1993;183.
12 Hilbert A, Tuschen- Cafer B, Karwautz A, etal. Eating Disorder
Examination- Questionnaire. Diagn 2007;53:144–54.
13 Elliott- Sale KJ, Minahan CL, de Jonge XAKJ, etal. Methodological
Considerations for Studies in Sport and Exercise Science with
Women as Participants: A Working Guide for Standards of Practice
for Research on Women. Sports Med 2021;51:843–61.
14 Siri WE. Body composition from uid spaces and density: analysis of
methods. 1961. Nutrition 1993;9:480–91.
15 Compher C, Frankeneld D, Keim N, etal. Best practice methods
to apply to measurement of resting metabolic rate in adults: A
systematic review. J Am Diet Assoc 2006;106:881–903.
16 Weir JBDB. New methods for calculating metabolic rate with special
reference to protein metabolism. J Physiol 1949;109:1–9.
17 Melin A, Tornberg ÅB, Skouby S, etal. Energy availability and the
female athlete triad in elite endurance athletes. Scand J Med Sci
Sports 2015;25:610–22.
18 Long JS, Freese J. Regression Models for Categorical Dependent
Variables Using Stata, 3rd Edn. College Station, Texas: Stata Press,
2014.
19 Wasserfurth P, Palmowski J, Hahn A, etal. Reasons for and
Consequences of Low Energy Availability in Female and Male
Athletes: Social Environment, Adaptations, and Prevention. Sports
Med Open 2020;6:44.
20 Mattar L, Huas C, Godart N, etal. Relationship between affective
symptoms and malnutrition severity in severe Anorexia Nervosa.
PLoS ONE 2012;7:e49380.
21 Mattar L, Thiébaud M- R, Huas C, etal. Depression, anxiety
and obsessive- compulsive symptoms in relation to nutritional
status and outcome in severe anorexia nervosa. Psychiatry Res
2012;200:513–7.
22 Streit F, Zillich L, Frank J, etal. Lifetime and current depression
in the German National Cohort (NAKO). World J Biol Psychiatry
2023;24:865–80.
23 Nixdorf I, Frank R, Hautzinger M, etal. Prevalence of Depressive
Symptoms and Correlating Variables Among German Elite Athletes.
J Clin Sport Psychol 2013;7:313–26.
24 Gräfe K, Zipfel S, Herzog W, etal. Screening psychischer Störungen
mit dem «Gesundheitsfragebogen für Patienten (PHQ- D)»:
Ergebnisse der deutschen Validierungsstudie. [Screening for
psychiatric disorders with the Patient Health Questionnaire (PHQ)
Results from the German validation study.]. Diagn 2004;50:171–81.
25 Rief W, Nanke A, Klaiberg A, etal. Base rates for panic and
depression according to the Brief Patient Health Questionnaire: a
population- based study. J Affect Disord 2004;82:271–6.
26 Schaal K, Tafet M, Nassif H, etal. Psychological balance in high
level athletes: gender- based differences and sport- specic patterns.
PLoS One 2011;6:e19007.
27 Keski- Rahkonen A, Mustelin L. Epidemiology of eating disorders in
Europe: prevalence, incidence, comorbidity, course, consequences,
and risk factors. Curr Opin Psychiatry 2016;29:340–5.
28 Sundgot- Borgen J, Torstveit MK. Prevalence of eating disorders in
elite athletes is higher than in the general population. Clin J Sport
Med 2004;14:25–32.
29 Byrne S, McLean N. Elite athletes: effects of the pressure to be thin.
J Sci Med Sport 2002;5:80–94.
30 Puccio F, Fuller- Tyszkiewicz M, Ong D, etal. A systematic review
and meta- analysis on the longitudinal relationship between eating
pathology and depression. Int J Eat Disord 2016;49:439–54.
31 Gorczynski PF, Coyle M, Gibson K. Depressive symptoms in
high- performance athletes and non- athletes: a comparative meta-
analysis. Br J Sports Med 2017;51:1348–54.
copyright. on August 29, 2024 by guest. Protected byhttp://bmjopensem.bmj.com/BMJ Open Sport Exerc Med: first published as 10.1136/bmjsem-2024-002035 on 28 August 2024. Downloaded from
