Article

Study protocol: prevalence of low energy availability and its relation to health and performance among female football players

Abstract and Figures

Enduring low energy availability (LEA) is associated with several potentially serious physiological and mental conditions. LEA has been found highly prevalent among female elite athletes within endurance sports, thus hampering athletes’ health and performance. The prevalence and the underpinning risk factors of LEA among female elite football players are less studied. One reason is that the existing self-report measures and technological devices to monitor energy intake and expenditure are inadequately adapted to capture the nature of the physical activity and energy expenditure among football players and are thus inaccurate. The present paper outlines a study protocol addressing the prevalence of LEA, the measurement of LEA and the correlations of LEA in terms of health and performance in female football players. Four studies will be conducted with the following aims (1) to evaluate the accuracy of global positioning systems (GPS)-based devices to monitor energy expenditure with indirect calorimetry as the gold standard, (2) to assess energy intake, quantify energy expenditure and investigate energy availability through self-report instruments, double labelled water (DLW) and GPS monitoring devices, (3) to determine the point prevalence of LEA using self-report instruments, DLW, dual-X-ray-absorptiometry (DXA) to quantify muscle and bone mass distribution and density, and a battery of hormonal analyses, and (4) to explore whether the prevalence of LEA varies across a full football season. Measures covering mental symptoms and psychological resources will be included, and a selection of biological measures derived from study 3. Measurements of DXA and DLW are resource-demanding and will be collected from one professional club (N~20 women). In contrast, the remaining data will be collected from four professional clubs (N~60 women) located in Bergen, the largest city within the Western region of Norway. Overall procedures and biobank storage procedures have been approved for data collection that will end in December 2024.
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RosenvingeJH, etal. BMJ Open Sp Ex Med 2022;8:e001219. doi:10.1136/bmjsem-2021-001219 1
Open access Protocol
Study protocol: prevalence of low
energy availability and its relation to
health and performance among female
football players
Jan H Rosenvinge ,1 Marcus Smavik Dasa,2 Morten Kristoffersen,3
Gunn Pettersen,2 Jorunn Sundgot- Borgen ,4 Jørn Vegard Sagen,5,6
Oddgeir Friborg1
To cite: RosenvingeJH,
DasaMS, KristoffersenM, etal.
Study protocol: prevalence
of low energy availability
and its relation to health and
performance among female
football players. BMJ Open
Sport & Exercise Medicine
2022;8:e001219. doi:10.1136/
bmjsem-2021-001219
Accepted 23 December 2021
1UiT The Arctic University
of Norway, Department of
Psychology, Tromsø, Norway
2UiT The Arctic University of
Norway, Department of Health
and Care Sciences, Tromsø,
Norway
3Western Norway University
of Applied Sciences, Bergen,
Norway
4The Norwegian School of Sport
Sciences, Department of Sports
Medicine, Oslo, Norway
5University of Bergen, Faculty of
Medicine, Department of Clinical
Science, Bergen, Norway
6Haukeland University Hospital,
Department of Medical
Biochemistry and Pharmacology,
Bergen, Norway
Correspondence to
Professor Jan H Rosenvinge;
jan. rosenvinge@ uit. no
© Author(s) (or their
employer(s)) 2022. Re- use
permitted under CC BY- NC. No
commercial re- use. See rights
and permissions. Published by
BMJ.
ABSTRACT
Enduring low energy availability (LEA) is associated with several
potentially serious physiological and mental conditions. LEA
has been found highly prevalent among female elite athletes
within endurance sports, thus hampering athletes’ health and
performance. The prevalence and the underpinning risk factors
of LEA among female elite football players are less studied.
One reason is that the existing self- report measures and
technological devices to monitor energy intake and expenditure
are inadequately adapted to capture the nature of the physical
activity and energy expenditure among football players and are
thus inaccurate.
The present paper outlines a study protocol addressing
the prevalence of LEA, the measurement of LEA and the
correlations of LEA in terms of health and performance in
female football players. Four studies will be conducted with
the following aims (1) to evaluate the accuracy of global
positioning systems (GPS)- based devices to monitor energy
expenditure with indirect calorimetry as the gold standard,
(2) to assess energy intake, quantify energy expenditure and
investigate energy availability through self- report instruments,
double labelled water (DLW) and GPS monitoring devices, (3)
to determine the point prevalence of LEA using self- report
instruments, DLW, dual- X- ray- absorptiometry (DXA) to
quantify muscle and bone mass distribution and density, and
a battery of hormonal analyses, and (4) to explore whether
the prevalence of LEA varies across a full football season.
Measures covering mental symptoms and psychological
resources will be included, and a selection of biological
measures derived from study 3.
Measurements of DXA and DLW are resource- demanding and
will be collected from one professional club (N~20 women).
In contrast, the remaining data will be collected from four
professional clubs (N~60 women) located in Bergen, the largest
city within the Western region of Norway. Overall procedures
and biobank storage procedures have been approved for data
collection that will end in December 2024.
INTRODUCTION
Energy availability and energy expenditure
An enduring imbalance between energy
intake (EI) and exercise energy expenditure
(EEE) may result in low energy availability
(LEA). LEA is associated with a cluster of
endocrine, cardiovascular, inflammatory,
gastrointestinal and mental features. This has
been labelled a ‘relative energy deficiency in
sports’ (RED- S) within sports medicine. LEA
can lead to the manifestation of RED- S, a
condition that can result in irreversible health
and performance impairments.1–3 The preva-
lence and covariates of LEA have been heavily
explored among female athletes representing
weight- sensitive sports, but not among female
football players on an elite level.
Some studies among female football players
have reported a prevalence of LEA from 23%
to 64%,4–6 and elite players are in the upper
range. Most of these studies have used the
Low Energy Available in Females Question-
naire (LEAF- Q).7 The LEAF- Q determines
LEA risk from symptoms and is validated
based on endurance sports. It might prob-
ably yield biased prevalence figures because
it does not fully capture the football- specific
characteristics such as the intermittent nature
of the physical activity and the type and loca-
tion of injuries.
A generic methodological problem is the
measurement of EEE and EI (EA/EI).8 Valid
biological measures are quite reliable but
costly, such as dual- energy X- ray absorpti-
ometry (DXA) to quantify muscle and bone
mass distribution and density and free fat
mass (FFM), and the use of doubly labelled
Key messages
The current protocol outlines studies that explore the
point and 1- year prevalence of LEA among female
elite football players using an extensive battery of
technical, biological, and psychological measures.
A critical point is the number of participants, and
actions will be taken to limit drop- out and missing
data.
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Open access
water (DLW) to quantify the rate of energy elimination.
High costs connected with logistic demands make such
procedures unfeasible during matches, especially in
larger study populations. Questionnaire- based methods
are feasible alternatives, that is, procedures like food
diaries, remote food photographic methods and 24 hours
recalls in quantifying EI—but at the expense of more
measurement errors. Yet, high reliability of self- reporting
procedures against DLW has been found only for male
football players.9
Another approach in measuring EEE is the use of
microtechnological positioning devices. Activity moni-
tors that combine accelerometry and measurement of
heat production and skin conductivity show promising
findings among ball game athletes with indirect calo-
rimetry as the gold standard.10 Still, the commercial
sale of such devices has been terminated. Other devices
used in the literature include heart rate, power metres
and global positioning systems (GPS). Recent quality
improvements11 of GPS- based devices make them a
feasible alternative to monitor player load.12 However, in
exploring the prevalence of LEA and RED- S, GPS and
other microtechnological devices may fall short consid-
ering the intermittent nature of physical expenditure in
football, which the GPS algorithms cover more poorly.13
The theoretical concept of metabolic power has been
proposed14 to better account for the energetic cost of
accelerations and decelerations. Still, metabolic power-
based methods seem to underestimate the energetic cost
of football- specific actions compared with the reference
standard of indirect calorimetry.13 Indeed, there is a
need to investigate the accuracy of different devices in
measuring EEE during intermittent activity to assess the
EA among football players more accurately.
Psychosocial correlates
While previous research has focused on the ‘triad’
between menstrual dysfunction, poor bone health and
disordered eating as a marker of LEA, recent studies
show a wide range of psychosocial correlates in terms
of both indicators and consequences, like depression,
irritability, impaired judgement and decreased concen-
tration.1 These factors may even outperform the triad
factors in predicting LEA.15 Other studies indicate an
uncertain relation among subjects with a higher preva-
lence of depression and LEA, particularly among younger
players in secondary divisions.16–18 Moreover, this casts
some uncertainty about the link between LEA and disor-
dered eating as it is not depression but rather, anxiety
disorders that stand out as a likely understanding of the
spectrum of eating disorders19–21 and the nature of exces-
sive physical activity.22 Furthermore, undereating and
insufficient EI may arise from non- pathological reasons
like poor awareness of appropriate sport- specific fuel-
ling, lack of interest or time to prepare meals meeting
refuelling requirements.1 23–25 Athletes are in general also
characterised by positive attributes like resilience and
well- being that may facilitate self- care and protect against
an inner or external drive to undereat.26–31 Whether such
attributes may lower the risk of LEA and RED- S remains
uninvestigated.
The present protocol consists of four studies exploring
the prevalence and correlations of LEA among female
elite football players. Table 1 provides an overview of
study- specific aims, including information about the
timeframe of the project and data collection related to
self- report instruments, microtechnological devices,
a gynaecological clinical assessment and biological
measures of saliva, urine, blood and bone.
METHODS
Participants
For all studies (1–4), female players (age 16–34) are
recruited from four high- level female football clubs,
competing in the Norwegian first or second division. The
four included teams are located in Bergen, the largest
city in the Western region of Norway.
Overall procedures
For all studies, information will be collected about age,
educational/occupational status, training history, dura-
tion of team membership, training/competition volume,
height, weight, FFM and position in the team, respec-
tively. Data collection for study 1 will occur at the teams’
training facilities. Here, players will perform a football-
specific circuit, mimicking the physiological demands in
elite female football based on existing data from inter-
national games32 and collecting GPS performance data.
Additional data collection will primarily take place at
outpatient healthcare facilities and certified physiolog-
ical laboratories
Measures of energy expenditure and intake
Table 1 provides an overview of the microtechnological
devices used in studies 1, 2 and 3, respectively. In study
1, these measures will be post- hoc compared against indi-
rect calorimetry.33 Oxygen uptake (VO2) will be measured
continually throughout the test, using a portable gas
analyzer (VO2 Master Health Sensors). Due to oxygen
deficit at exercise onset, the post- exercise oxygen
consumption will be added to the overall oxygen cost
of the physical exercise protocol, following rest periods
within the protocol.34 The results of study 1 will serve as
a reference for measuring EEE during the data collec-
tion of the remaining studies, necessary to calculate EA.
The data collection for studies 2 and 3 will be completed
simultaneously for approximately 6 months. In study 2,
total energy expenditure will be measured via DLW to
quantify the total energy expenditure of this population,
following the Maastricht protocol.35 In studies 3 and 4,
players will, during training and matches, wear a GPS
device (based on study 1) for analysis of duration of the
activity, total distance covered, average speed, time in
different speed zones. For study 3, GPS measures using
metabolic power will also aid to quantify EA through
EEE, in addition to general EE provided by DLW, as the
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Open access
latter cannot specify the EE of single training sessions or
matches. Measurement of EE through GPS devices will
also be used during study 4 to quantify EA. A 24- hour diet
recalls distributed randomly throughout the data collec-
tion will quantify EI for studies 2,3 and 4, respectively.
Biological data collection and storage
Blood samples for all hormonal data will be collected
after an overnight fasting period (8–10 hours). A trans-
vaginal ultrasound will be performed and examined in
conjunction with the serum testosterone where neces-
sary to screen for potential polycystic ovarial symptoms.
The gynaecological examination will be conducted at an
outpatient clinic if required. Other biochemical param-
eters that will be measured are presented in table 1.
Moreover, serum and plasma samples for biobanking
will be obtained. Using the Maastrict Protocol,35 urine
from the DLW- samples will be stored in airtight vitals
and frozen until analysis to determine the isotopic disap-
pearance rate and thus energy expenditure. Data from
DXA and resting metabolic rate (RMR) based on DLW
and physical performance will be completed at a certified
physiological laboratory at Western Norway University of
Applied Science. Serum and plasma blood samples will
be collected and stored in an existing biological bank. All
Table 1 Overview of study specic aims, samples and data sources
Studies, samples, and
purposes Time frame
Self- report
instruments
Microtecnological
devices Biological measures
Study 1 (n=13)
Aim: To evaluate the
accuracy of methods
measuring exercise energy
expenditure (EE) against
the gold standard of
indirect calorimetry.
March–April 2021.
Baseline+7 days
consequtively
RPE GPS- tracking,
foot mounted
accelerometer/
gyroscope
Vo2 (indirect
calorimetry)
Blood lactate (mmol/L)
Study 2 (n=20)
Aim: To quantify energy
intake (EI), EE and its
implications for nutritional
recommendations
.
September 2021–April
2022. Baseline+14
days consequtively
24 hours diet recall
× 3.
Weekly weight
measurement.
GPS tracking
Activity monitor
with integrated
accelerometer
DLW and DXA
Study 3 (n=50)
Aim: To identify the point
prevalence of LEA and
validity of subjective
measure of LEA through
objective physiological
markers
September 2021–April
2022.
Baseline+30 days
LEAF- Q+additional
items
EDE- Q core items.
EI (food registration)
and training intensity
on food registration
days
DLW
RMR
DXA
Analysis of the following
biochemical markers:
TSH, free T3 free T4,
glucose, insulin, C-
peptide, cortisol, S-
CTX- 1 (collagen I), PINP,
leptin, adiponectin,
IGF- 1, IGFBP3, estradiol,
testosterone and SHBG.
Serum and plasma
collection for biobanking.
Transvaginal Ultrasound
(If indicated by
testosterone levels)
Study 4 (n=50)
Aim: To explore whether
the prevalence of LEA
varies across a full
football season and its
possible biological and
psychological covariates
January 2022–January
2023.
1 year (four measure
points during 3–5
testing days at
baseline, in season,
and post- season,
respectively)
LEAF- Q+additional
items
EDE- Q core items
CFQ (fatigue)
GHQ- 12 (mental
distress)
BIS (insomnia)
SoC- 13 (resilience)
QoL- BREF (well- being)
See study 3. A selection
will be made based on
study 3- ndings for a
subsample (N=20).
Physical performance
(baseline and post
season).
BIS, Bergen Insomnia Scale; CFQ, Chalder Fatigue Scale; CTX- 1, type I collagen cross- linked C- telopeptide; DLW, double labelled water;
DXA, dual- X- ray- absorptiometry; EDE- Q, Eating Disorder Examination Questionnaire; GHQ- 12, General Health Questionnaire- 12; LEA, low
energy availability; LEAF- Q, Low Energy Availability in Females Questionnaire; PINP, Procollagen type I N- terminal propeptide; RMR, resting
metabolic rate; RPE, Rated Perceived Exertion; SoC- 13, Sense of Coherence Scale; TSH, thyroid stimulating hormone; VO2, oxygen uptake.
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Open access
hormonal contraceptive agents used by participants will
also be registered for analytical purposes.
Self-Report Questionnaires
The set of self- report questionnaires (table 1) includes
a measure of LEA7 with additional football- related items
inspired by previous work36 to capture football- specific
injuries (studies 2–4). Also, we will measure mental and
physical fatigue (study 4),37 a brief version38 of a measure
of eating problems (Eating Disorder Examination Ques-
tionnaire)39 to capture weight and shape concerns
(studies 3 and 4). In study 4, we also measure psycho-
logical distress,40 insomnia and sleeping difficulties,41
resiliency and sense of coherence42 as well as the overall
quality of life and well- being.43
Statistical approach
Using a within- study design with unevenly spaced- out
repeated measures, a linear mixed modelling approach
is preferred as it supports the use of time- variant predic-
tors, variations in the repeated time codings, including
superior flexibility in adjusting the fixed coefficients for
complex error correlation structures related to repeat
measures or within team dependencies. The restricted
maximum likelihood method ensures the use of all avail-
able information, thus being more lenient toward missing
data in estimating marginal mean changes over time.
Power calculations
The use of double labelled water (DLW) and full- body
DXA scans are highly resource- demanding; hence, these
data are collected from a single team consisting of at
least 20 women. Despite numerous studies on the use
of DLW, we only located a single study examining the
relationship between DLW- based RMR (representing
chronic energy unbalance) and the LEAF- Q question-
naire, which indicates a Pearson r of approx. 0.45. As
football is physiologically more intensive, we consider a
stronger association, likely between 0.45 and 0.60. Using
an alpha=0.05, r=0.50, and a lower 95% CI of r>0.30,
requires ~50 independent observations. Assuming
an intraclass correlation of 0.25 requires 5 repeated
measures from 20 women to achieve an effective sample
size of N=50, given a statistical power of 0.80. For study 3
(prevalence), assuming a prevalence of ~0.35 (reported
between 0.15 and 0.55 in the literature), power of 0.80,
alpha of 0.05 and a finite population (max 200 elite
players in Norway), requires a minimum of approx. 60
or 120 observations for a precision of ±0.10 and ±0.05,
respectively. We, therefore, recruit a minimum of 60
women from 3 elite clubs. Adding 4 repeated measures
throughout the full football season (assuming ICC=0.25)
yields an effective sample size of approximately 137
independent observations that we regard as adequately
sensitive to study point precision and variation in prev-
alence.
User involvement and participation
User involvement enhances the relevance and quality of
research.44 Hence, 3–5 elite female football players from
clubs that do not participate in the study will cooperate
with the research group, notably in the implementation
of the protocol and the dissemination of the results.
DISCUSSION
Previous studies have indicated that LEA is present among
ball game female athletes. Yet, methodological issues and
limited accuracy of measurements may underpin the huge
range in prevalence figures across studies. The main purpose
of the present protocol is to establish the technological
and psychometric basis for exploring the prevalence and
correlates of LEA among female elite football players, and
hence, contribute to the existing literature within this area
which is quite limited for female football players.
With the heavy logistics connected with data collection,
storage and analysis of biological data, the number of foot-
ball clubs involved had to be restricted to a particular region
in Norway. The statistical power may thus be a critical issue
in this study. The COVID- 19 pandemic restrictions and
the nature of the finite population provide few options to
enlarge the project to other national regions, which could
entail an increased risk concerning lowering feasibility
related to non- participation drop- out or missing data. In
this project, feasibility was weighted highly due to the alle-
giance, commitment and adherence to the overall aims
and the procedures for data collection among the female
players, the club leaders and the overall supporting teams.
Moreover, to ensure compliance, a research team member
will be present to respond to queries and secure optimal data
quality during the data collection procedures. In the present
COVID- 19 situation with heavy travel restrictions, a similar
allegiance and commitment might not have been possible
with a national, multisite implementation approach. Given
that we consider the effect size estimations as fair and the
compensation that repeated measures offer in terms of statis-
tical power and offering future interesting study possibilities,
the current project may yield new and high- quality knowl-
edge to this emerging research field.
User involvement may enhance the relevance and quality
of research.44 Hence, a group of end- users (2- 3) /elite female
football players (who are not participating in the project) will
cooperate with the research group, notably in implementing
the protocol and disseminating the results. Another asset of
user involvement is related to the development of items in
addition to the LEAF- Q to capture football- related injuries.
It takes a considerable amount of time and access to a large
group of project- independent players to develop and validate
a football- specific new instrument to capture the proxies of
LEA. However, the present user engagement procedure is,
in our opinion, satisfactory and will provide a basis for future
validation studies.
Contributors The rst author provided the rst drafts, and all authors have equally
contributed to nalise the manuscript, and all authors thus meet the Vancouver
criteria for authorship.
Funding The project is fully funded by the UiT The arctic university of Tromsø
Norway.
Competing interests None declared.
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Open access
Patient and public involvement Patients and/or the public were involved in the
design, or conduct, or reporting, or dissemination plans of this research. Refer to
the Methods section for further details.
Patient consent for publication Not applicable.
Ethics approval The protocol has in July 2021 been approved by the Norwegian
Centre for Research Data (ref. no. 807592). The Regional Committee for Medical
and Health Research (REK) judged that while the study did not fall under to the
Norwegian Health Research Act (ref. no. 257695), ethical approval was needed
for the biobank storage of serum and plasma blood samples. A REK- approval was
given in July 2021 (ref. no 29081) for storage in previously approved biobank
(2016/787).
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement No data are available. This is a study protocol article
and hence, no data are available at present.
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
Jan HRosenvinge http://orcid.org/0000-0003-3485-9641
JorunnSundgot- Borgen http://orcid.org/0000-0002-5291-5486
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