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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Note: This article will be published in a forthcoming issue of
the International Journal of Sport Nutrition and Exercise
Metabolism. This article appears here in its accepted, peer-
reviewed form; it has not been copyedited, proofed, or
formatted by the publisher.
Section: Original Research
Article Title: Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance
Athletes
Authors: Monica K. Torstveit1, Ida Fahrenholtz2, Thomas B. Stenqvist1, Øystein Sylta1, and
Anna Melin2
Affiliations: 1Faculty of Health and Sport Science, Institute of Public Health, Sport &
Nutrition, University of Agder, Kristiansand, Norway. 2Department of Nutrition, Exercise
and Sports, University of Copenhagen, Frederiksberg, Denmark.
Running Head: Within-day energy deficiency in male athletes
Journal: International Journal of Sport Nutrition and Exercise
Acceptance Date: January 5, 2018
©2018 Human Kinetics, Inc.
DOI: https://doi.org/10.1123/ijsnem.2017-0337
“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Within-day energy deficiency and metabolic perturbation in male
endurance athletes
Torstveit MK.,1 Fahrenholtz I.2, Stenqvist TB.,1 Sylta Ø.,1 Melin A.2
1Faculty of Health and Sport Science, Institute of Public Health, Sport & Nutrition,
University of Agder, Kristiansand, Norway.
2 Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg,
Denmark
Running head: Within-day energy deficiency in male athletes
Corresponding author:
Monica Klungland Torstveit,
University of Agder,
Faculty of Health and Sport Science PO. Box 422
4604 Kristiansand Norway
E-mail: [email protected]
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Abstract
Endurance athletes are at increased risk of relative energy deficiency associated with metabolic
perturbation and impaired health. We aimed to estimate and compare within-day energy
balance (WDEB) in male athletes with suppressed and normal resting metabolic rate (RMR)
and explore if within-day energy deficiency (WDED) is associated with endocrine markers of
energy deficiency. Thirty-one male cyclists, triathletes, and long-distance runners recruited
from regional competitive sports clubs were included. The protocol comprised measurements
of RMR by ventilated hood, and energy intake and energy expenditure to predict RMRratio
(measured RMR/predicted RMR), energy availability (EA), 24-hour energy balance (EB) and
WDEB in 1-hour intervals, assessment of body-composition by dual-energy X-ray
absorptiometry, and blood plasma analysis. Subjects were categorized as having suppressed
(RMRratio < 0.90, n=20) or normal RMR (RMRratio > 0.90, n=11). Despite no observed
differences in 24-hour EB or EA between the groups, subjects with suppressed RMR spent
more time in an energy deficit exceeding 400 kcal (20.9 [18.8 – 21.8] hours vs. 10.8 [2.5 –
16.4], P=0.023), and had larger single-hour energy deficits compared to subjects with normal
RMR (3265 ± 1963 kcal vs. -1340 ± 2439, P=0.023). Larger single-hour energy deficits were
associated with higher cortisol levels (r = -0.499, P=0.004) and a lower testosterone:cortisol
ratio (r = 0.431, P=0.015), but no associations with T3 or fasting blood glucose were observed.
In conclusion, WDED was associated with suppressed RMR and catabolic markers in male
endurance athletes.
Keywords: Energy availability, within-day energy balance, resting metabolic rate
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Introduction
A balanced diet with an appropriate energy intake supports optimal body function
(Thomas et al., 2016) and is, together with regular physical activity, the cornerstone of a healthy
lifestyle. However, exercising women and female athletes focusing on leanness, such as
endurance athletes, are reported to be at increased risk for restricted eating behavior and relative
energy deficiency related to serious health conditions that include eating disorders, premature
osteoporosis, and increased cardiovascular risk factors (De Souza et al., 2014; Mountjoy et al.,
2014; Nattiv et al., 2007). There is scientific evidence concerning the causality between relative
energy deficiency and the metabolic and endocrine perturbations related to suppressed resting
metabolic rate (RMR), subclinical and clinical menstrual dysfunction in women, and poor bone
health (Loucks et al., 1998; Loucks & Thuma, 2003). Furthermore, a growing body of evidence
suggests that energy deficiency results in an altered endocrine profile, loss of bone mass, and
suppressed RMR in male athletes (Dolan et al. 2012; Hagmar et al. 2013; Koehler et al., 2016;
Wilson et al., 2015). Nonetheless, recent position papers and reviews call for more knowledge
regarding energy deficiency and associated health- and performance variables among male
athletes (Mountjoy et al., 2014; Tenforde et al., 2016).
RMR represents the energy cost of basic physiological functions, including immunity,
reproductive function, growth, and thermoregulation (Fuqua & Rogol, 2013), which all appear
to be affected by relative energy deficiency (Mountjoy et al., 2014). When energy intake is
inadequate, energy allocation is prioritized to physiological processes essential for immediate
survival (Wade & Jones, 2004). Therefore, bodyweight and body composition may remain
within the normal range despite insufficient energy intake (Goldsmith et al., 2010; Redman et
al., 2009; Redman & Loucks, 2005). In female athletes, an RMRratio < 0.90 is widely accepted
as a surrogate marker for relative energy deficiency (De Souza et al. 2008; Gibbs et al. 2013;
Melin et al., 2015).
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Traditionally, energy status is evaluated in blocks of 24-hours as either energy balance
(EB = energy intake – total energy expenditure) or energy availability (EA) (EA = energy
intake – exercise energy expenditure (EEE) relative to fat free mass (FFM)). However, these
24-hour views of human thermodynamics have been criticized for failing to account for the
endocrine responses that act on real-time changes in energy intake and expenditure (Benardot,
2013). Within-day EB (WDEB), where energy intake and energy expenditure are assessed in
1-hour intervals may, therefore, be more appropriate (Benardot, 2013; Deutz et al., 2000).
Indeed, it has been suggested that failure to find associations between field determinations of
low EA and objective measures of energy conservation may be explained by a failure to
account for within-day energy deficiency (WDED) as a possible contributor to the metabolic
and endocrine alterations associated with relative energy deficiency
(Mountjoy et al., 2014). Published studies investigating WDED have thus so far only
assessed female athletes, where WDED has been associated with menstrual dysfunction, lower
estradiol and RMRratio and higher cortisol levels (Fahrenholtz, et al., 2017) and an unfavorable
body composition (Deutz et al., 2000).
Therefore, the aim of this study was to estimate and compare WDED, where EB is
assessed in 1-hour intervals, in male endurance athletes with suppressed and normal RMR, and
to investigate whether these comparisons deviate from the traditional 24-hour assessments.
Finally, it was of interest to explore if WDED is associated with endocrine markers of energy
deficiency in this male athletic group.
Methods
Forty-six male cyclists, triathletes, and long-distance runners were recruited to the
study through local clubs and social media in two phases (Figure 1). All subjects were
categorized as trained or well-trained (Jeukendrup et al., 2000), and at performance level 3-4
(De Pauw et al., 2013). Inclusion criteria were male, 18-50 years old, absence of disease or
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
injury, maximal oxygen uptake (�̇�O2max) >55 mL.kg-1.min-1, training frequency ≥4
sessions/week during the previous year, and competing in an endurance sport at a regional or
national level. Two subjects dropped out due to personal reasons and 13 subjects were
excluded; 5 were under the age of 18, 5 were excluded due to missing data, and 3 did not follow
protocol (Figure 1). No subjects were excluded due to underreporting of energy intake
according to Black (2000). Thus, 31 subjects (67.4%) were included in the final data analysis.
The study was approved by the University Faculty Ethics Committee and registered with the
Norwegian Centre for Research Data. All subjects signed a written informed consent before
study participation.
Measurement methods
Performance and health were assessed during three non-consecutive days, followed by
four consecutive days (three weekdays and one weekend-day) of recording food consumption,
non-exercise activity thermogenesis (NEAT) and training in the subjects’ normal environment.
The test protocol was standardized for each athlete.
On the first day, determination of �̇�O2max and anthropometric measurements were
performed. On the second day, RMR and resting heart rate (HR) were assessed, a questionnaire
was completed, and the subjects received detailed instructions on how to record their energy
intake and expenditure. On the third day, blood samples were drawn and whole-body
composition was assessed. All subjects were asked to arrive in a fasted state on days two and
three, refrain from using products containing tobacco, alcohol and caffeine, and to not exceed
1 hour of low intensity exercise the day before.
Anthropometry
Height measurement was completed without shoes to the nearest 0.1 cm using a
centimeter scale affixed to the wall (Seca Optima, Seca, UK), and body weight was measured
in light clothing to the nearest 0.01 kg (InBody 720, Biospace, Seoul, Korea). Body mass index
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
(BMI) was calculated as measured weight in kilograms (kg) divided by height squared in meter
(kg/m2). Body composition was measured using Dual-energy X-ray absorptiometry (DXA)
(Lunar Prodigy, EnCore v. 15, GE Medical Systems, 3030 Ohmeda Drive, Madison, Wi 53718,
USA). All measurements were completed in a fasted state between 6 and 9 a.m.
Maximal oxygen uptake
VO2max was predicted by asking the subjects to perform an incremental test until
exhaustion: cyclists and triathletes on a stationary bike (Excalibur Sport, Lode B.V.,
Groningen, the Netherlands) and runners on a treadmill (Katana Sport, Lode B.V., Groningen,
the Netherlands). Cyclists started with one minute of cycling at a power output corresponding
to 3 W/kg, and increased by 25 W/min until voluntary exhaustion or failure to maintain a
cadence ≥70 RPM. Runners started at 12 km.h-1 on a constant incline of 3°. Speed was
increased by 1 km.h-1.min-1 until exhaustion. �̇�O2max was measured using Oxycon Pro™ with
mixing chamber and 30-s sampling time (Oxycon Pro, Jaeger GmbH, Hoechberg, Germany),
using a two-way T-shape non-rebreathing valve and a nose clip (series 9015, Hans Rudolph,
Kansas, MO, USA). All systems were calibrated according to standards.
Resting metabolic rate and resting heart rate
For RMR assessment, subjects arrived at the laboratory in a fasted state by motorized
transport between 6 and 9 a.m. Subjects were instructed to minimize movement after
awakening, and rested lying down for 15 minutes before the measurements began. For a
detailed description of measurement of RMR, see table 1. The lowest obtained heart rate (HR)
during the RMR measurement was registered using a Polar V800 HR monitor (Polar Elektro
Oy, Kempele, Finland).
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Blood sampling
Fasted blood samples were drawn from a cephalic vein between 7 and 9 a.m. by a
qualified bio-technician. One 10 mL BD Vacutainer CAT (BD, Plymouth, United Kingdom)
was filled and centrifuged after at least 30 min and within 60 min. Two 1.8 mL Cryotube Vials
(Termo Fischer Science, Roskilde, Denmark) were filled with serum and frozen to -75ºC.
Blood samples were analyzed for glucose, cortisol, testosterone, and triiodothyronin (T3) at
Sorlandets Hospital in Kristiansand and Aker Hormonlab in Oslo, Norway. Reference values
based on the Norwegian laboratories standards were used: glucose (4-6 mmol.L-1); cortisol
(138-690 mmol.L-1); testosterone (18-40 y, 7.2-24 nmol.L-1; >41 y, 4.6-24 nmol.L-1); and T3
(1.2-2.7 nmol.L-1).
Energy status
Energy availability (EA) was calculated by subtracting EEE from the subjects’ daily
energy intake, relative to FFM (Nattiv et al., 2007). In order not to underestimate EA, EEE
only represented the energy attributable to training, and RMR was subtracted from EEE before
used in the EA-calculation.
An overview of the components for the WDEB calculation is presented in Table 1 and
an example of WDEB calculation is provided in Table 2, illustrating 18 hours in EB < 0 kcal,
6 hours in EB <-400 kcal, and a largest single hour deficit of 1070 kcal.
Statistics
Statistical calculations were performed using RStudio version 0.99.879 (Boston, MA,
USA) with a two-tailed significance level of < 0.05. All data sets were tested for normality and
homogeneity of variance before statistical hypothesis tests were performed. Normally
distributed data were summarized as means and standard deviations (SD), and non-normally
distributed data as median and interquartile range (IQ 25 and IQ 75 percentiles). Differences
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
between subjects with suppressed RMR (RMRratio < 0.90) vs. normal RMR (RMRratio > 0.90)
were investigated using unpaired Student’s t-test for normally distributed data and the
Wilcoxon rank-sum test for non-parametric data. Pearson’s correlation coefficient and
Spearman’s rank correlation coefficient were calculated to investigate associations between
WDED variables and continuous outcomes for normally and non-normally distributed data,
respectively.
Results
Sixty-five percent of the subjects had suppressed RMR. Subjects with suppressed RMR
were older compared to subjects with normal RMR, but no differences in anthropometry,
exercise capacity, training volume (Table 3), or energy expenditure data (Table 4) between the
groups were found.
No difference in 24-hour EB or EA between the groups was observed, but subjects with
suppressed RMR spent more time in energy deficits exceeding 400 kcal (P=0.023) and had
larger single-hour energy deficits (P=0.023) compared to subjects with normal RMR (Table 4).
No difference in protein intake between subjects with normal RMR (1.8 ±0.4 g/kg/day) and
subjects with suppressed RMR (1.7 ±0.4 g/kg/day) was observed.
All subjects had fasting blood glucose, cortisol, testosterone, and T3 within the normal
range. There were no associations between WDED and glucose or T3 (Table 5). Larger single-
hour energy deficit was associated with higher cortisol (r= 0.499, P=0.004) and a lower
testesterone:cortisol ratio (r= 0.431, P=0.015). The more time spent in WDEB < 0 kcal, and
the larger the single-hour energy deficit, the lower body fat percentage (r= -0.366, P=0.043 and
r= 0.359, P=0.047, respectively). There were no associations between protein intake and any
body composition measures, although there was a tendency towards a lower fat free mass with
lower protein intake (r= -0.333, P=0.067).
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Discussion
In this group of well-trained men, 65% had suppressed RMR and, despite similar EA
and 24 hour EB compared to subjects with normal RMR, they spent more time in severe energy
deficit and had larger single-hour energy deficit, which were associated with higher cortisol
levels and a lower testosterone:cortisol ratio.
In order to account for the endocrine responses, it has been suggested that calculating
WDEB is more physiologically relevant compared to the traditional 24-hour assessment
(Benardot, 2013). The WDEB method assesses time and magnitude deviations from the
predicted EB, where ±400 kcal represent the hypothetical limits for staying in a desirable EB,
based on the predicted amount of liver glycogen, although the limits may be smaller or larger,
depending on individual factors (Benardot, 2007; Benardot 2013; Deutz et al., 2000).
Exceeding the threshold of EB below -400 kcal, could potentially accelerate catabolic
processes and compromise brain glucose availability (Benardot, 2007; Benardot 2013). This
may be reflected in endocrine alterations, such as higher cortisol levels and lower
testosterone:cortisol ratio as observed in our study, which may reduce the ability to recover
and increase the risk of overreaching and overtraining, thereby compromising athletic
performance (Banfi & Dolci, 2006). WDEB is an accumulating value that does not reset
calculations every day at midnight, thus, it is possible that a traditional 24-hour assessment of
EB or EA may mask multi-day periods with energy deficits. For instance, light training days
may have a compensatory effect on the mean 24-hour EB. Such “hidden” periods of energy
deficits may, over time, lead to serious health- and performance consequences, such as
unfavorable endocrine profile, bone loss, and suppressed RMR (Dolan et al., 2012; Koehler et
al., 2016; Wilson et al., 2015).
In an earlier study, number of hours in EB < -300 kcal was positively associated with
body fat percentage in female middle- and long-distance runners (Deutz et al., 2000),
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
presumably related to both an adaptive reduction in RMR and endocrine responses that favor
muscle breakdown and fat gain (Benardot, 2007; Benardot 2013). Therefore, a restrictive
eating behavior may have the opposite of the desired effect on athletes’ body composition. This
is in contrast with our findings, where WDED (number of hours in EB < 0 kcal and largest
energy deficit) was associated with a lower body fat percentage in male athletes, and as recently
reported we found no association between WDEB and body composition in female elite
endurance athletes (Fahrenholtz et al. 2017). One explanation for conservation of fat free mass
despite hypocaloric conditions may be attributed to protein intake (Fahrenholtz et al., 2017,
Phillips & Van Loon, 2011). This could, however, not explain the findings of the present study.
The ability to compare our results with those reported by Deutz et al. (2000) is, however,
limited due to several methodological differences. For instance, Deutz et al. (2000) used 24-
hour recall to assess energy intake and energy expenditure with only one assessment day, in
contrast to our four-consecutive days of recording food- and beverage consumption as well as
objectively measured energy expenditure.
Regarding energy expenditure, some of our athletes had a considerably high NEAT,
and although not significant different, there was a trend towards a higher NEAT in the group
with suppressed RMR compared to those with normal RMR. The large NEAT may be due to
that some of the athletes were deliberately looking for ways to expend calories to maintain
leanness. Another explanation may be the fact that some of the athletes had physically active
jobs such as firefighters, carpenters, plumbers, mason workers, and ironworkers. In addition,
some athletes self-reported a physically active leisure time such as active play with their
children, which to some degree could have increased their NEAT. This information was,
however, not registered in the questionnaire, only obtained when talking to the athletes. Hence,
we can only speculate whether these factors may explain the trend towards a higher NEAT in
the group with suppressed RMR. Whether some athletes may not consider their leisure- or
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
employment activities as considerably energy-demanding could be an item for future
consideration in education programs concerning how to balance energy expenditure with
adequate energy intake.
One methodological challenge may be how one distinguish between “exercise” and
“activities that contributed to NEAT”. In our study, detailed information and instructions about
the different terms were provided individually to each participant. Exercise was defined as the
athletes’ planned exercise-bouts with the aim of improving fitness/performance, while
activities that contributed to NEAT were defined as all physical activity, besides exercise.
Activities such as riding a bike to and from work (if not regarded as an exercise-bout by the
athletes), walking to the store/in the neighborhood, playing with children, and active at work
(such as working as a plumber or fireman) counted as activities that contributed to NEAT. All
athletes were instructed not to use their accelerometer (remove it physically from the body)
during their planned exercise-bouts, and to use their heart rate monitor during every exercise
bout. It is, however, complicated to control (e.g. whether athletes use their accelerometer
immediately after exercise), and we recognize that this can have a potential effect on the total
NEAT. Detailed information given to each participant in advance and during data collection
was provided to minimize such errors in the present study.
When calculating pRMR, a prediction error of 10% is expected (Cunningham, 1980),
and therefore an expected normal range of RMRratio is 0.9-1.1 (Sterling et al., 2009). A
RMRratio < 0.90 has been used as a recognized surrogate marker for energy deficiency in
females (De Souza et al., 2008; Gibbs et al., 2013; Melin et al., 2015; Scheid et al., 2009), but
more studies are needed to further investigate this relationship in males. Experimental studies
indicate that males’ reproductive system may be more resistant to energy deficiency than
females’ (Koehler et al., 2016), which may suggest a lower cut-off for RMRratio when assessing
male athletes. However, whether males’ sports performance and health consequences other
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
than those related to the reproductive system are similarly sensitive to relative energy
deficiency has not yet been investigated. Additionally, both the Cunningham and the Harris-
Benedict equation have been found to significantly underestimate RMR in heavyweight male
national team rower and canoe racers (Carlsohn et al., 2011), suggesting an overestimation of
RMRratio in some athletes and an increased risk of false classification of normal RMR with a
lower RMRratio cut-off.
Strengths and limitations
To our knowledge, this is the first study analyzing WDED and associated endocrine
markers of energy deficiency in males. Other strengths of this study were inclusion of a
relatively high number of male athletes compared to previous research (Carlsohn et al., 2011;
Wilson et al., 2015), the use of valid outcome measures and that all tests followed best practice
protocols for measurements.
The results of this study should be interpreted with consideration of certain
methodological limitations. First, the data are based on a cross sectional study design, limiting
assertions of causality. Second, the WDED variables adapted from the literature leads to a high
number of correlation analysis, which may increase the risk of type 1 error. Third, a limitation
of the current study design was that the collection of data related to food consumption, NEAT,
and training occurred after the physiological assessment. Hence, we cannot be sure that these
behaviors were the cause of the results seen in the study. The reason for assessing dietary intake
and energy expenditure after the physiological testing, and not before, was exclusively
practical. Due to the fact that assessment of dietary intake and energy expenditure is
methodologically difficult, we needed to give detailed instructions to each participant and
ensure that they were all familiar with the measurement equipment and best practice
procedures. In addition, with regard to the participants total load of being a part of this project,
in combination their daily life, we chose not to invite them to the laboratory also before the
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
physiological testing. Thus, we decided that the best practical solution was to include the
dietary intake and energy expenditure testing after the physiological testing was completed. It
should be noted, however, that all athletes were instructed to eat, drink and exercise “as usual”,
and the software of Dietist Net was chosen due to that it was not possible for the participants
to see any caloric calculations of their registrations neither during registration, nor afterwards.
This may have reduced the risk of under- or over reporting of food items or portions.
Based on our experiences, we recommend future research to measure dietary intake and
energy expenditure immediately before the laboratory testing in order to possibly capture a
closer correlation between dietary intake and energy expenditure and the physiological
variables of interest. Furthermore, there is a need of data that investigate the reasonable period
of time over which WBEB calculations should be conducted. We also recommend using
objective, validated methods to measure both energy intake and energy expenditure, and to
standardize when and how the equipment, such as accelerometers or heart rate monitors, should
be used. Finally, to use a registration system that identifies low compliance to the measurement
equipment, such as an accelerometer, may be of help to exclude participants not following the
test procedures from the analysis. For analysis of energy intake, we recommend the use of
Goldberg’s cut off (Black, 2000) to reduce the risk of including under-reporters.
In conclusion, we found that male endurance athletes with suppressed RMR, despite
similar 24-hour EB and EA, spent more time in energy deficits exceeding 400 kcal and had
larger single-hour energy deficits compared to those with normal RMR. WDED was associated
with higher cortisol levels and a lower testosterone:cortisol ratio. The results suggest that
assessing energy status in intervals of 24 hours may not be sufficient for detecting athletes at
risk for health-related consequences caused by energy deficiency. A continuous view on energy
status evaluated in smaller time blocks may therefore be more appropriate.
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Acknowledgements
The authors would like to thank the subjects participating in the study. We also thank the master
students in sports science at the University of Agder for assisting in the data collection.
Author contributions
The study was designed, and data was collected by MKT, ØS, and TBS; the data was analyzed
by AKM and IF, data interpretation and manuscript preparation were undertaken by TBS,
AKM, IF, and MKT. All authors approved the final version of the paper.
Declaration of funding
The study was funded by the University of Agder, Faculty of Health and Sport Sciences,
Kristiansand, Norway.
Conflicts of interest
The authors have no conflicts of interest in this study.
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© 2018 Human Kinetics, Inc.
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Figure 1. Flowchart showing the recruitment process, dropouts and exclusion of subjects
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International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Table 1. Overview of methods used to calculate WDEB and RMRratio
COMPONENTS OF WITHIN-DAY ENERGY BALANCE
Component Summary of method Comments/reference
Energy intake
(EI)
Prospective weighed food and beverage record for 4 consecutive days in the
subjects’ normal environment
Digital kitchen scale: OBH Nordica 9843 Kitchen Scale Color, Taastrup,
Demark
Software program: Dietist Net, Kost och Näringsdata, Bromma, Sweden
In depth oral and written instructions
were given to the subjects
Diet induced
thermogenesis
(DIT)
Defined as 10% of EI and distributed in the hours after each meal or snack by
using the equation: 175.9·T·e-T/1.3 where T=Time and e=the base of the natural
logarithm
Reed & Hill, 1996
Non-exercise
activity
thermogenesis
(NEAT)
Subjects wore a Sensewear accelerometer (BodyMedia, Inc., Pittsburgh, PA,
175 USA) or Actigraph accelerometer (Actigraph GT3X®, Pensacola, FL,
USA) the same days as dietary intake recording
All logging was performed from the
time subjects woke up in the morning
until bedtime
Only allowed to take the logging
device off during showering,
swimming, and training
Exercise
energy
expenditure
(EEE)
Subjects recorded all training sessions with HR- monitor (Polar M400/V800)
during the same days as they recorded dietary intake as epochs of five seconds
during every training session
EEE (kcal/kg/min) = ((5.95*HRaS) + (0.23·age) + (84·1)-134)/4186.8 where
HRaS=HR above sleeping HR (beats/min) (HRaS)
Sleeping HR was estimated from a resting supine measurement during the
RMR measurement (sleep HR=0.83 * supine HR)
Crouter et al., 2008
Brage et al., 2005
Excess post-
exercise
Defined as 5% of EEE the first hour post-exercise plus 3% of EEE the second
hour post-exercise
Phelain et al., 1997
Fahrenholtz et al., 2017
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
oxygen
consumption
(EPOC)
Resting
metabolic rate
(RMR)
The predicted RMR used to calculate WDEB was calculated using the
Cunningham equation
Cunningham, 1980
Sleeping
metabolic rate
(SMR)
Defined as 90% of pRMR Used instead of RMR during sleeping
hours
Within-day
energy
balance
(WDEB)
The hourly energy balance was calculated as EB = energy intake – total
energy expenditure; predicted DIT + EEE + EPOC + NEAT + RMR
In order to control for the problem of
potential underestimation of energy
requirements, the unadapted (pRMR),
instead of (mRMR) was used when
calculating total energy expenditure
The starting point for the calculation
of WDEB was at midnight on the first
day of food recording and was
calculated as follows; the mean EI of
the last daily meal/snack minus mean
total energy expenditure in the time
interval following the mean
meal/snack consumption
WDEB was calculated continuously
for the four days of registration
WDED
variables
Total hours with energy deficit (unadapted EB < 0 kcal)
Hours spent in energy deficit exceeding 400 kcal (unadapted EB < -400 kcal)
Largest single-hour energy deficit
Benardot, 2007
Benardot, 2013
COMPONENTS OF RMRratio
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Component Summary of method Comments/reference
Measured
RMR
(mRMR)
Calorimetry using a ventilated canopy hood system (Oxycon Pro, Jaeger
GmbH, Hoechberg, Germany)
Calibrated before each test according to standards
Oxygen consumption and carbon dioxide production were assessed over a 30-
min period
A 5-min steady state period defined as a coefficient of variation (CV) of less
than 10% to assess RMR was identified
Measured RMR (mRMR) was assessed using the Weir equation
Compher et al., 2006
Weir, 1990
Predicted
RMR
(pRMR)
pRMR = 500 + 22 · FFM (kg) Cunningham, 1980
Resting
metabolic rate
ratio
(RMRratio)
RMRratio = mRMR/pRMR
Suppressed RMR was defined as a RMRratio <0.90 and normal RMR as a
RMRratio >0.90
De Souza et al., 2008
Melin et al., 2015
The Cunningham equation was
chosen, since this equation has been
found to be the best predictive
equation for RMR in endurance
athletes (Thompson & Manore, 1996)
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Table 2. Example of WDEB calculation of one day for one subject.
Kcal in Kcal out
Time EI DIT EEE EPOC NEAT
SEE REE
TEE
h to h EB
00:00-01:00 0 0 0 0 0 66 0 66 40
01:00-02:00 0 0 0 0 0 66 0 1323 -26
02:00-03:00 0 0 0 0 0 66 0 199 -92
03:00-04:00 0 0 0 0 0 66 0 266 -158
04:00-05:00 0 0 0 0 0 66 0 332 -224
05:00-06:00 0 0 0 0 0 66 0 399 -290
06:00-07:00 0 0 0 0 0 66 0 465 -356
07:00-08:00 0 0 0 0 24 0 74 563 -454
08:00-09:00 242 7 0 0 169 0 74 812 -462
09:00-10:00 0 7 0 0 94 0 74 987 -637
10:00-11:00 654 24 0 0 91 0 74 1176 -172
11:00-12:00 13 22 0 0 113 0 74 1384 -369
12:00-13:00 792 38 0 0 163 0 74 1660 148
13:00-14:00 0 31 0 0 201 0 74 1966 -158
14:00-15:00 575 37 0 0 101 0 74 2178 205
15:00-16:00 0 28 0 0 162 0 74 2442 -59
16:00-17:00 0 17 721 0 0 0 74 3253 -871
17:00-18:00 278 18 0 36 99 0 74 3481 -820
18:00-19:00 0 12 0 22 142 0 74 3730 -1070
19:00-20:00 1570 55 0 0 88 0 74 3946 283
20:00-21:00 0 47 0 0 73 0 74 4140 89
21:00-22:00 259 40 0 0 79 0 74 4333 155
22:00-23:00 0 27 0 0 79 0 74 4513 -25
23:00-00:00 0 16 0 0 75 0 74 4678 -190
24-h Total 4383 426 721 58 1753 462 1258 4678 -295
Abbreviations: EI: energy intake, DIT: diet induced thermogenesis, EEE: exercise energy
expenditure, EPOC: excess post-exercise oxygen consumption, NEAT: non-exercise activity
thermogenesis, SEE: sleeping energy expenditure, REE: resting energy expenditure, TEE:
total energy expenditure, EB: energy balance.
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Table 3. Description of subjects characterized by RMRratio
All
(n=31)
Normal RMR
(n=11)
Suppressed RMR
(n=20)
P-value1
Age (years) 34.7 ± 8.1 30.8 ± 7.2 36.9 ± 7.9 0.045
Height (cm) 179.5 ± 5.3 180.4 ±
5.
2
179.1 ± 5.4 0.516
Body weight (kg) 72.0 ± 6.1 73.7 ± 6.2 71.1 ± 6.0 0.267
BMI (kg/m2) 22.3 ± 1.8 22.7 ± 2.1 22.1 ± 1.7 0.501
Body fat (kg) 8.4 (4.5 – 11.2)
11.0 (6.0 – 12.7) 8.2 (4.2 – 10.6)
0.302
Body fat (%) 11.7 ± 5.7 12.8 ± 6.1 11.1 ± 5.5 0.427
Fat free mass (kg) 63.4 ± 5.1 64.0 ± 4.7 63.1 ± 5.4 0.634
Exercise
(hours/week)
8.7 ± 3.2 9.2 ± 3.3 8.4 ± 3.2 0.515
VO2peak
(ml/kg/min)
66.4 ± 6.2 66.7 ± 8.2 66.2 ± 5.0 0.807
Data are presented as mean ± SD for normally distributed data and as median and interquartile range
(25-75) for non-normally distributed data. Abbreviations: BMI: body mass index, VO2peak: maximal
oxygen uptake. 1) Difference between subjects with normal (RMRratio> 0.9) vs. suppressed RMR
(RMRratio< 0.9).
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Table 4. Energy expenditure and within-day energy deficiency characterized by RMRratio.
All
(n=31)
Normal RMR
(n=11)
Suppressed RMR
(n=20)
P-value1
Exercise EE
(kcal/day)
678 ± 250 662 ± 283 675 ± 238 0.942
DIT (kcal/day)
228 ± 52 243 ± 66 220 ± 42 0.250
EPOC (kcal/day) 54 ± 20 55 ± 23 54 ± 19 0.920
NEAT (kcal/day) 819 (482 – 1648) 580 (374 – 1094) 1548 (557 – 1744) 0.087
pRMR (kcal/hour) 79 ± 4 79 ± 4 79 ± 5 0.741
mRMR
(kcal/hour)
69 ± 8 76 ± 8 66 ± 5 <0.001
RMRratio 0.88 ± 0.07 0.96 ± 0.05 0.83 ± 0.04 <0.001
24-hour EB*
(kcal)
-698 ± 928 -402 ± 1056 -861 ± 832 0.192
24-hour EB**
(kcal)
-914 ± 966 -463 ± 1059 -1162 ± 837 0.052
24-hour EA
(kcal/kg FFM)
39 ± 12 41 ± 11 37 ± 12 0.393
WDEB < 0 kcal
(hours/day)
22.0 (14.1 –
22.8)
14.3 (3.9 – 20.9) 22.1 (20.4 -22.8) 0.059
WDEB <-400 kcal
(hours/day)
18.8 (10.5 –
21.6)
10.8 (2.5 – 16.4) 20.9 (18.8 – 21.8) 0.023
Largest hourly
deficit (kcal)
-2582 ± 2302 -1340 ± 2439 -3265 ± 1962.9
0.023
Data are presented as mean ± SD for normally distributed data and as median and interquartile range
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
(25-75) for non-normally distributed data. Abbreviations: DIT: diet induced thermogenesis, EB:
energy balance, EE: energy expenditure, EPOC: excess post-exercise oxygen consumption, mRMR:
measured resting metabolic rate, pRMR: predicted resting metabolic rate, WDEB: within-day energy
balance. 1) Difference between subjects with normal (RMRratio> 0.9) vs. suppressed RMR (RMRratio<
0.9). *using mRMR **using pRMR
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“Within-day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes” by Torstveit et al.
International Journal of Sport Nutrition and Exercise Metabolism
© 2018 Human Kinetics, Inc.
Table 5. Associations between within-day energy deficiency and markers for catabolic state
Hours with WDEB < 0
kcal
Hours with WDEB <-400
kcal
Largest hourly deficit1
r P-value
r P-value
r P-value
RMRratio -0.231 0.212 -0.242
0.190
0.335 0.065
Body fat (%) -0.366 0.043 -0.311 0.090 0.359 0.047
Cortisol
0.167 0.377
0.294 0.108 -0.499 0.004
Testosterone -0.277 0.132 -0.315 0.085
0.268 0.145
Test:cortisol -0.117 0.532 -0.235 0.204
0.413 0.016
T3
-0.104 0.577 0.032 0.864 -0.058 0.753
Glucose -0.064 0.731 -0.151 0.415 0.247 0.180
All subjects (n=31) were included in the correlation analysis. Abbreviations: BP: Blood pressure,
RMR: resting metabolic rate, Test:cortisol: the ratio between testosterone and cortisol, WDEB:
within-day energy balance. 1)Values recorded as negative numbers.
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