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Garthe, I. G., Raastad, T., Refsnes, P. E., Koivisto, A., Sundgot-Borgen, J.
(2011). Effect of Two Different Weight-Loss Rates on Body
Composition and Strength and Power-Related Performance in Elite
Athletes. International Journal of Sport Nutrition & Exercise
Metabolism, 21, 97-104.
97
International Journal of Sport Nutrition and Exercise Metabolism, 2011, 97-104
© 2011 Human Kinetics, Inc.
Effect of Two Different Weight-Loss Rates
on Body Composition and Strength
and Power-Related Performance in Elite Athletes
Ina Garthe, Truls Raastad, Per Egil Refsnes, Anu Koivisto, and Jorunn Sundgot-Borgen
When weight loss (WL) is necessary, athletes are advised to accomplish it gradually, at a rate of 0.5–1 kg/
wk. However, it is possible that losing 0.5 kg/wk is better than 1 kg/wk in terms of preserving lean body mass
(LBM) and performance. The aim of this study was to compare changes in body composition, strength, and
power during a weekly body-weight (BW) loss of 0.7% slow reduction (SR) vs. 1.4% fast reduction (FR).
We hypothesized that the faster WL regimen would result in more detrimental effects on both LBM and
strength-related performance. Twenty-four athletes were randomized to SR (n = 13, 24 ± 3 yr, 71.9 ± 12.7 kg)
or FR (n = 11, 22 ± 5 yr, 74.8 ± 11.7 kg). They followed energy-restricted diets promoting the predetermined
weekly WL. All athletes included 4 resistance-training sessions/wk in their usual training regimen. The mean
times spent in intervention for SR and FR were 8.5 ± 2.2 and 5.3 ± 0.9 wk, respectively (p < .001). BW, body
composition (DEXA), 1-repetition-maximum (1RM) tests, 40-m sprint, and countermovement jump were
measured before and after intervention. Energy intake was reduced by 19% ± 2% and 30% ± 4% in SR and
FR, respectively (p = .003). BW and fat mass decreased in both SR and FR by 5.6% ± 0.8% and 5.5% ± 0.7%
(0.7% ± 0.8% vs. 1.0% ± 0.4%/wk) and 31% ± 3% and 21 ± 4%, respectively. LBM increased in SR by 2.1%
± 0.4% (p < .001), whereas it was unchanged in FR (–0.2% ± 0.7%), with signicant differences between
groups (p < .01). In conclusion, data from this study suggest that athletes who want to gain LBM and increase
1RM strength during a WL period combined with strength training should aim for a weekly BW loss of 0.7%.
Keywords: energy restriction, strength training, hypertrophy
Weight loss in athletes is generally motivated by a
desire to optimize performance by improving power-
to-weight ratio, making weight to compete in a certain
weight category, or for aesthetic reasons in leanness
sports. Because of the negative effects of rapid weight
loss and long periods of restricted energy intake (Hall &
Lane, 2001; Koral & Dosseville, 2009; Umeda, Nakaji,
Shimoyama,Yamamoto, & Sugawara, 2004), existing
literature recommends a gradual weight loss through
moderate energy restriction, promoting a weekly weight
loss of 0.5–1 kg (Fogelholm, 1994; Rankin, 2002). To
induce a weight loss of 0.5–1 kg/wk, an energy decit
corresponding to 500–1,000 kcal/day is needed. This can
be achieved by reduced energy intake, increased energy
expenditure, or a combination of the two.
However, a decrease in body mass resulting from
energy restriction can lead to loss of lean body mass
(LBM; Koral & Dosseville, 2009; Koutedakis et al.,
1994) and thereby impair performance (Degoutte et al.,
Garthe, Raastad, and Sundgot-Borgen are with the Norwegian
School of Sport Sciences, Oslo, Norway. Garthe, Refsnes,
and Koivisto are with the Norwegian Olympic Sports Centre,
Oslo, Norway.
2006; Koral & Dosseville, 2009). Strength training in
combination with mild energy restriction can preserve
LBM during weight-loss periods in overweight seden-
tary subjects (Kraemer et al., 1999). Therefore, to make
weight-loss interventions as effective as possible, we
combined energy restriction with strength training to
alleviate the expected negative consequences on LBM
and performance.
Finally, when the weight-loss goal is xed, most
athletes choose to use the shortest amount of time to reach
the goal to avoid extended periods of fatigue. There are
probably different implications of reducing daily energy
intake by 500 or 1,000 kcal, and a reduction of 1,000 kcal
can compromise recovery and impair training adaptations
in athletes, especially in those with an already low energy
intake (American College of Sports Medicine [ACSM],
2009; Nattiv et al., 2007).
Consequently, the aim of this study was to compare
two practical approaches to the recommended weight-
loss regimen in the literature. We compared weekly BW
losses of 0.7% and 1.4% (i.e., twice the relative weight),
which corresponds to weekly weight losses of 0.5 and
1 kg, respectively, in a 70-kg athlete. We hypothesized
that the faster weight-loss regimen would result in more
detrimental effects on both LBM and strength- and power-
related performance.
98 Garthe et al.
Methods
Subjects
Thirty-six elite male and female athletes, age 18–35 years,
were recruited, and 30 completed the study. The athletes
were recruited by invitation from the Norwegian Olympic
Sport Center when they contacted the center to get assis-
tance with weight loss, or by invitation letters to sport
federations. The following sports were represented in the
study: football, volleyball, cross-country skiing, judo,
jujitsu, tae kwon do, waterskiing, motocross, cycling,
track and eld, kickboxing, gymnastics, alpine skiing,
ski jumping, freestyle sports dancing, skating, biathlon,
and ice hockey. There were 43% versus 57% and 31%
versus 69% men and women in the slow-reduction group
(SR) and the fast-reduction group (FR), respectively.
The physical and anthropometrical characteristics of the
athletes are shown in Table 1.
Six female athletes with repeated weight uctua-
tions during the last season reported a low energy intake
at baseline and therefore had to accomplish their weight
goal with an intervention that included increased energy
expenditure in addition to the reduced energy intake. They
were included in the study because this is a daily practical
challenge when working with athletes. However, because
of the different intervention with additional energy expen-
diture included for this subgroup, the statistical analysis,
results, and discussion are presented without this subgroup.
The athletes were informed about the purpose and
experimental procedures before written consent was
obtained. The study was conducted according to the
Declaration of Helsinki and approved by the Data Inspec-
torate and the Regional Ethics Committee of Southern
Norway. Permission to conduct the study was provided by
the Norwegian Olympic Committee and the Norwegian
Confederation of Sports.
Experimental Design
The athletes were screened and block-randomized to the
SR and FR groups. All athletes followed a 4- to 12-week
energy-restriction and strength-training period. The
length of the intervention was determined by the rate
of weight loss (SR or FR) and the desired weight loss
(minimum 4% of BW). The nal weight goal was set by
a nutritionist and exercise physiologist based on results
from the body-composition measurements that provided
the information needed to calculate minimum percentage
fat for each athlete and the athlete’s desired weight loss.
The length of the intervention period for each subject
depended on the athlete’s weight-loss goal and the weekly
weight-loss rate. For example, a 70-kg athlete who
wanted to reduce body weight by 5 kg (and the amount of
weight loss was appropriate for the calculated minimum
percentage fat) would have either a 5- (FR) or 10-week
(SR) intervention depending on which intervention group
he or she was randomly allocated to.
Preparticipation Screening
Screening included the Eating Disorder Inventory (EDI-
2; Garner, 1991), followed by an interview and medical
examination according to the standard for preseason
health evaluation at the Norwegian Olympic Sports
Center. The exclusion criteria were as follows: diseases
and conditions known to affect metabolic functions in
muscle, use of pharmaceuticals that might affect any of
the measurements, and presence of one or more of the
triad components—disordered eating/eating disorder,
menstrual dysfunction, or low bone-mineral density
(Nattiv et al., 2007). For possible diagnoses, DSM-IV
criteria were used for anorexia nervosa, bulimia nervosa,
and eating disorder not otherwise specied (American
Psychiatric Association, 1994); clinically evident peri-
menopausal or postmenopausal condition; pregnancy;
and fat mass corresponding to a predicted postinterven-
tion body-fat value of less than 5% for men and 12% for
women (Fogelholm, 1994; Heyward & Wagner, 2004).
Intervention
Diet. Diet registrations were obtained by a 4-day (3
weekdays + 1 weekend day) weighed-food record that
was analyzed by a national food database, “Mat Paa
Data” (version 5.0, LKH, Mattilsynet, Norway). The
athletes were instructed to make sure they were weight
stable during the diet registration. The record served as
Table 1 Baseline Data, M ± SD
Slow-Rate Weight Loss Fast-Rate Weight Loss
Men (
n
= 6) Women (
n
= 7) Men (
n
= 5) Women (
n
= 6)
Age (years) 24.9 ± 3.5 22.4 ± 3.1 20.9 ± 4.5 20.7 ± 6.4
Height (cm) 177 ± 11 169 ± 8 179 ± 4 167 ± 1
Body weight (kg) 78.5 ± 14.1 66.4 ± 8.8 81.9 ± 11.5 68.9 ± 6.7
Fat mass (kg) 13.3 ± 5.0 17.3 ± 4.4 13.3 ± 6.5 21.2 ± 5.2
Total body fat (%) 17 ± 5 27 ± 5 16 ± 3 30 ± 5
Lean body mass (kg) 62.3 ± 10.3 46.3 ± 5.5 65.5 ± 3.3 44.6 ± 3.6
Experience as athletes (years) 13 ± 6.4 10.7 ± 4.7 12.6 ± 4.5 13.1 ± 5.1
Training per week (hr) 15.6 ± 4.5 15.2 ± 3.1 15.2 ± 3.1 13.9 ± 5.3
Strength training last season (hr/week) 2.8 ± 1.6 2.7 ± 1.6 3.4 ± 1.1 2.1 ± 1.5
Weight Loss in Elite Athletes 99
a basis for developing each athlete’s individualized diet
plan promoting weekly BW loss of 0.7% or 1.4%. This
was calculated from the assumption that 1 g of mixed
tissue gives 7 kcal. For example, a 60-kg athlete in SR
had to reduce energy intake by ~420 kcal/day to achieve
the weekly weight-loss goal of 0.4 kg (60,000 × 0.7%/7
days × 7 kcal). In the diet plans, the aim was to have a
daily protein intake corresponding to 1.2–1.8 g/kg, a daily
carbohydrate intake corresponding to 4–6 g/kg and ≥20%
fat, with low-energy/high-nutrient foods that provided
satiety, as well as food variety. There were 5–7 daily
meals and snacks and no meal plan below 1,500 kcal/day.
All athletes ingested a milk-protein-based recovery meal
containing carbohydrates (20–40 g) and protein (6–20
g) within 30 min after training sessions and a balanced
meal within 1–2 hr, in an attempt to optimize recovery.
During implementation of the dietary plan, the athletes
were encouraged to use a food scale to ensure correct
portion sizes. They were encouraged to drink a minimum
of 0.5 L/hr of water during training sessions and ~2 L of
uids during the day. If the athletes were unable to follow
the dietary plan during the week, they were instructed to
write down any deviations from it.
Supplementation. The athletes were not allowed
to have used creatine supplementation during the 6
weeks before the intervention, and they did not take any
supplements other than those given by the nutritionist
during the intervention. A multivitamin–mineral
supplement (Nycomed, Asker, Norway) and a cod
liver oil supplement (Møller’s tran, Oslo, Norway)
were prescribed to ensure sufficient micronutrient
intake and essential fat intake during the intervention.
Furthermore, if blood samples indicated any other
specic micronutrient needs (e.g., iron, vitamin B12),
these vitamins were provided to the athletes and blood
levels were thereafter monitored.
Nutritional Counseling. The athletes received nutri-
tional counseling once a week during intervention. The
counseling included basic nutrition, sports physiology,
and possible adjustments in the dietary plan or weight
regimen, depending on progress.
Training. The intervention period started off-season
for all athletes to be able to add additional training to
their schedule and for practical reasons (e.g., traveling
and competitions). All athletes continued their sport-
specic training schedule (14.6 ± 3.5 hr/week, presented
as a mean of the training during the previous year).
They included four strength-training sessions per week
to emphasize muscle strength and hypertrophy. The
strength-training program was a two-split periodized
program. Each muscle group was exercised twice a
week with two exercises in each session, one main
exercise attacking multiple muscle groups (e.g., squat)
and one working on a specic muscle group (e.g., knee
extension). Main exercises for leg muscles were clean
(whole body), squat, hack squat, and dead lift, and main
exercises for upper body muscles were bench press, bench
pull, rowing, chins, shoulder press, and core exercises.
In the rst 4 weeks the athletes trained with a 3 × 8–12
repetition-maximum (RM) regimen, the next period with
4 × 6–12RM, and the last 4 weeks with 5 × 6–10RM.
For the athletes who participated for less than 12 weeks,
the program was adjusted with shorter periods. The rest
period between sets was 1–3 min long. Once a week,
athletes were supervised during training at the Olympic
Sports Center to ensure correct training technique and
adequate progress. A computerized exercise diary was
recorded during the entire intervention period.
Experimental Assessments
All tests were conducted by the same test team before and
after the intervention, and the test day was standardized.
Athletes were not allowed to perform heavy training 48
hr before testing.
BW. BW was measured in a fasted state with a balance
scale (Seca Model 708, Seca Ltd., Birmingham, UK) to
the nearest 100 g on the test day in the morning between
8 and 9 a.m. During the intervention period, athletes
used their own scales to monitor BW because their
weekly meetings with the nutritionist were at different
times during the day, and their weight would uctuate
depending on food and liquid intake. They were instructed
to weigh themselves without clothes and with an empty
bladder immediately after awaking and before breakfast.
Body Composition. Fat mass, percent body fat,
and LBM were measured with dual-energy X-ray
absorptiometry (DEXA; GE Medical Systems, Lunar
Prodigy, WI) by a trained technician. The DEXA system
was calibrated every day before testing, and the test was
conducted with the participant in a fasted state between
8:30 and 10:00 a.m. For DEXA reproducibility, 10
athletes did two repeated measurements within 24 hr, and
the coefcient of variation in the DEXA Lunar Prodigy
total-body scan for repeated measurements was 3% for
fat mass and 0.7% for LBM.
Performance. Performance was measured by 40-m
sprint, countermovement jump (CMJ), and 1RM of bench
press, bench pull, and squat. Before the sprint, CMJ, and
1RM strength tests, the athletes performed a standardized
warm-up consisting of 15 min of low-intensity running or
cycling. After the general warm-up they performed a more
sprint-specic warm-up, followed by three maximal 40-m
sprints, and the best result was used in the data analysis.
CMJ was performed on an AMTI force platform (SG 9,
Advanced Mechanical Technology Inc., Newton, MA),
and the best jump of three was used in the data analysis.
In the 1RM tests the weight was progressively increased
until the athlete could not move it through the full range
of motion on at least two attempts.
EDI-2. The EDI-2 is a self-report measure with 91
items, a 6-point forced-choice inventory assessing several
behavioral and psychological traits common in anorexia
nervosa and bulimia (Garner, 1991). The EDI-2 consists
of the following 11 subscales: drive for thinness, bulimia,
body dissatisfaction, ineffectiveness, perfectionism,
100 Garthe et al.
interpersonal distrust, interceptive awareness, maturity
fears, asceticism, impulse regulation, and social
insecurity. The athletes lled out the EDI before and
after testing to assess behavioral and psychological traits.
Statistical Analyses
Data are presented as M ± SD for pre- and post- measure-
ments and M ± SE for changes within and between groups.
The computer software programs Graphpad Prism 5.0 (CA,
SA) and SPSS 15 (Chicago, IL) were used for statistical
analysis. The pre- to post- changes within groups were
analyzed with paired-samples two-tailed Student’s t test
or Wilcoxon’s paired-rank test when appropriate. Between
groups, independent two-tailed Student’s t test and the
Mann–Whitney test were used when appropriate. Pearson’s
R or Spearman’s rho was performed when appropriate to
study correlations between variables. Values of p below
.05 were considered statistically signicant.
Results
A history of dieting and weight cycling was reported
by 53% of the athletes in SR and 45% of the athletes in
FR. The mean lengths of time spent in intervention for
SR and FR were 8.5 ± 2.2 and 5.3 ± 0.9 weeks, respec-
tively. There were no signicant differences between
groups in any of the baseline measurements (Tables 1, 2
and 3).
Diet
Baseline energy intakes were 2,409 ± 622 and 2,514 ±
518 kcal/day for SR and FR, respectively. Energy intake
was reduced more in FR (30% ± 4%) than in SR (19%
± 2%; p = .003; Table 2), with the aim of faster weight
loss. Although intake of most of the macronutrients was
signicantly reduced, none of the variables differed
between groups (Table 2).
Table 2 Energy and Nutrition Variables Presented as M ± SD for Diet Registration and Meal Plan
and M ± SE for Change
Slow-Rate Weight Loss (
n
= 13) Fast-Rate Weight Loss (
n
= 11)
Diet
registration Meal plan Change
Diet
registration Meal plan Change
Energy intake (kcal) 2,409 ± 622 1,940 ± 482 –469 ± 61* 2,514 ± 518 1,723 ± 234 –791 ± 113*
Energy (kcal/LBM) 45.6 ± 9.6 36.5 ± 6.5 –9.1 ± 4.2*# 47.8 ± 11.3 33.0 ± 5.2 –15.0 ± 2.2*#
Protein (g/kg BW) 1.6 ± 0.4 1.6 ± 0.4 0.1 ± 0.1* 1.6 ± 0.5 1.4 ± 0.2 –0.2 ± 0.1
Protein (E%) 19.6 ± 6.3 25.2 ± 3.7 7.0 ± 1.3* 18.2 ± 2.9 24.2 ± 3.3 4,5 ± 1.6*
CHO (g/kg BW) 4.1 ± 0.9 3.6 ± 0.7 –0.5 ± 0.2* 4.1 ± 1.1 3.2 ± 0.6 –1.0 ± 0.2*
CHO (E%) 51.0 ± 6.5 54.0 ± 3.3 3.1 ± 1.6 49.3 ± 6.3 55.5 ± 4.4 6.2 ± 1.5*
Fat (E%) 30.0 ± 6.9 20.8 ± 1.1 –9.2 ± 2.1* 31.1 ± 4.0 20.6 ± 2.0 –10.5 ± 1.4*
Note. LBM = lean body mass; BW = body weight; CHO = carbohydrate; E% = percent of total energy intake.
*p < .05 signicantly different from pre. #p < .05 signicant difference between groups.
Table 3 Body Composition and Performance Variables Presented as M ± SD for Pre- and Post-
and M ± SE for Change
Slow-Rate Weight Loss (
n
= 13) Fast-Rate Weight Loss (
n
= 11)
Pre- Post- Change Pre- Post- Change
Body weight (kg) 71.9 ± 12.7 67.8 ± 11.4 –4.2 ± 0.6* 74.8 ± 11.7 70.6 ± 10.6 –4.2 ± 0.6*
Lean body mass (kg) 53.7 ± 11.3 54.7 ± 11.2 1.0 ± 0.2* 54.1 ± 12.1 53.8 ± 11.1 –0.3 ± 0.4#
Fat mass (kg) 15.5 ± 4.9 10.5 ± 3.6 –4.9 ± 0.7* 17.6 ± 6.9 14.4 ± 6.8 –3.2 ± 0.5#*
Countermovement jump (cm) 32.3 ± 6.4 34.3 ± 5.5 2.0 ± 0.7* 31.3 ± 7.6 31.6 ± 7.7 0.3 ± 0.8
40-m sprint (s) 5.76 ± 0.61 5.80 ± 0.65 0.04 ± 0.05 5.99 ± 0.49 5.99 ± 0.44 0.00 ± 0.04
1RM press (kg) 59.2 ± 21.2 66.7 ± 22.3 7.5 ± 0.5* 73.2 ± 33.3 75.5 ± 29.1 2.3 ± 1.7#
1RM pull (kg) 63.5 ± 16.5 69.2 ± 15.8 5.8 ± 1.5* 69.5 ± 19.8 71.4 ± 17.2 1.8 ± 1.7
1RM squat (kg) 97.5 ± 38.3 106.5 ± 34.7 9.0 ± 2.1* 90.0 ± 25.6 97.0 ± 23.9 7.0 ± 1.7*
Note. 1RM = one-repetition-maximum.
*p < .05 signicantly different from pre. #p < .05 signicant difference between groups.
Weight Loss in Elite Athletes 101
Body Composition
BW was reduced by 5.6% ± 0.8% in SR (p < .001) and
5.5% ± 0.7% in FR (p < .001; Figure 1). The average
weekly rates of weight loss for the SR and FR were
0.7% ± 0.4% and 1.0% ± 0.4%, respectively. In accor-
dance with the aim of the study, the rate of weight loss
in FR was signicantly faster than in SR (p = .02). Fat
mass decreased more in SR than in FR (31% ± 3% vs.
21% ± 0%, respectively, p = .02; Figure 1). Total LBM
increased signicantly in SR by 2.1% ± 0.4% (p < .001),
whereas it was unchanged in FR (–0.2% ± 0.7%), with
signicant differences between groups (p < .01; Figure 1).
The increase in total LBM in SR was mainly caused by a
3.1% ± 0.8% increase in upper body LBM. The weekly
gains in LBM were 0.3% ± 0.0% and 0.0 ± 0.1% (p =
.02) for SR and FR, respectively.
Body Composition and Gender
Women gained LBM during the intervention, whereas
men did not (1.8% ± 0.4% vs. 0.0% ± 0.7%, respectively,
p < .01). In men, LBM was gained during the interven-
tion in SR (1.7% ± 0.4%, p < .01), whereas men in FR
tended to reduce LBM (–2.0% ± 1.0%, p = .1), with a
signicant difference between groups (p < .01). There
were no signicant differences between women in SR
and FR in any of the body-composition variables.
Performance
Performance in CMJ was improved by 7% ± 3% (p <
.01) in SR, whereas no signicant change was observed
in FR (Figure 2). There was no change in 40-m-sprint
performance in any of the groups. 1RM squat improved
similarly by 11.9% ± 3.4% (p < .01) in SR and 8.9% ±
2.3% (p < .01) in FR (Figure 2). Bench-press performance
increased more in SR than in FR (13.6% ± 1.1% vs. 6.4%
± 3.3%, respectively, p = .01; Figure 2). The performance
in bench pull improved by 10.3% ± 3.0% (p = .001) in
the SR and 4.0% ± 2.6% in the FR. Overall change in
1RM for the upper body exercises was higher in SR than
in FR (11.4% ± 2.6% vs. 5.2% ± 2.4%, respectively, p
= .03). The weekly gains in mean relative changes in all
1RM measurements were 1.4% ± 0.7% and 1.3% ± 0.5%
for SR and FR, respectively. There were no signicant
correlations between changes in any of the performance
variables, strength-training experience, weight-loss
experience, or weekly weight-loss rate and changes in
body composition.
Performance and Gender
The increase in 1RM squat was higher in women (16.2%
± 2.7%) than in men (4.7% ± 1.5%, p = .002). No other
signicant gender differences were observed for changes
in performance tests.
EDI
There were no signicant differences between groups at
baseline in any of the EDI subscale scores, and there were
no signicant changes from pre- to posttest in either SR
or FR (35.2% ± 16.5% to 26.2% ± 13.7% and 26.5% ±
11.5% to 27.6% ± 9.6%, respectively).
Compliers Versus Noncompliers
The dened weekly weight-loss goals for SR and FR
were 0.7% and 1.4% of BW, respectively. All athletes
are included in the current results according to the
intention-to-treat principle. The mean weekly weight-loss
rates and standard deviations were 0.7% ± 0.3% of
Figure 1 — Changes in body weight, fat mass, and lean
body mass (LBM) in the slow-rate weight-loss group (SR)
and the fast-rate weight-loss group (FR), M ± SE. *p < .05
signicantly different from pre. #p < .05 signicant difference
between groups.
Figure 2 — Changes in one-repetition-maximum (1RM)
bench press, bench pull, and squat; 40-m-sprint performance;
and countermovement jump (CMJ) in the slow-rate weight-loss
group (SR) and the fast-rate weight-loss group (FR), M ± SE.
*p < .05 signicantly different from pre. #p < .05 signicant
difference between groups.
102 Garthe et al.
BW per week in SR and 1.0% ± 0.5% in FR. Three
athletes in SR (cutoff values in weekly weight-loss rate:
0.5–0.9%) and 5 athletes in FR (cutoff values in weekly
weight-loss rate: 1.0–1.6%) did not accomplish their
weight-loss goals. When noncompliers were removed
there were no signicant changes in results, but dif-
ferences between the SR and FR were generally more
pronounced. No statistically signicant differences in
any of the variables were found between compliers and
noncompliers.
Discussion
The aim of this study was to compare the effects of 5–6%
BW loss at slow and fast rates on changes in body com-
position and strength- and power-related performance in
elite athletes. We hypothesized that the faster weight loss
would result in more detrimental effects on both LBM
and performance. Surprisingly, LBM increased by 2.1% ±
0.4% in SR, accompanied with improved performance in
CMJ and all the 1RM parameters, whereas there was no
signicant change in LBM or improvements in strength-
and power-related performance, except 1RM squat, in
FR. Total LBM increased more in SR than in FR, with
weekly gains in LBM of 0.3% ± 0.0% and 0.0% ± 0.1%
(p = .02) for SR and FR, respectively. Consequently, the
slower weight-loss intervention had more positive effects
on LBM and performance than the faster weight-loss
intervention.
Diet
Compared with their high activity level the reported base-
line energy intake was relatively low, and this may be a
result of underreporting, undereating, or both, which is
common in self-reported dietary intake (Magkos & Yan-
nakoulia, 2003). We chose a 4-day weighed-food registra-
tion to minimize the burden, improve compliance, and
avoid alteration of the subject’s usual intake. The possible
underreporting during the intervention was controlled for
by weekly measurements of BW and sum of skinfolds.
The calculated energy decits for the SR and FR were
469 ± 61 and 845 ± 113 kcal/day, respectively. Because
of daily training sessions, no meal plan was set below
1,500 kcal/day. The diet in both groups was a low-fat diet
(~20% of total energy intake), and the mean carbohydrate
intakes were 3.5 ± 0.7 g/kg (SR) and 3.2 ± 0.6 g/kg (FR),
which is less than recommended (ACSM, 2009). The
mean protein intakes were 1.6 ± 0.47 and 1.4 ± 0.27 g/
kg in SR and FR, respectively, within the recommended
protein intake for athletes (ACSM, 2009). Adequate pro-
tein intake was considered important to ensure sufcient
amino acid supply to muscles and to enhance the anabolic
response to strength training, in addition to thermogenic
and satiety-inducing effects (ACSM, 2009; Karst, Stei-
niger, Noack, & Steglich, 1984). The meal plans were
based on the dietary registrations and general guidelines
for each nutrient, and the athletes took part in making
the meal plans. This included choice of foods and drinks
and timing of intake. We consider the individual planning
crucial for compliance and motivation for the athletes.
Body Composition
LBM increased signicantly in SR from pre- to postint-
ervention and increased signicantly more in SR than
in FR. There were also highly signicant differences
for men between SR and FR in LBM, even though the
sample size was somewhat low (6 vs. 5 athletes). There
was no signicant difference in weekly hours of strength
training the season before entering the study between SR
and FR or the men in SR and FR, which could have been
a plausible explanation for different changes in LBM.
The rst assumption for this difference in LBM
changes is the fact that SR spent a signicantly longer
time in the intervention than FR. The mean amounts
of time spent in intervention for SR and FR were 8.5 ±
2.2 and 5.3 ± 0.9 weeks, respectively (p < .001). Con-
sequently, athletes in SR performed strength training
for ~3 weeks longer than FR. This is likely the most
important explanation for the differences in changes in
LBM. However, although the athletes in SR had a longer
period with energy decit, they had a smaller restriction in
energy intake, and this may also be a contributing factor
to the larger increase in LBM. This is supported by the
fact that the weekly gain in LBM was signicantly higher
in the SR group than in the FR group. Consequently, the
rate of weight loss seems to be important in addition to
the time spent in the intervention.
Note that increased upper body LBM was the major
contributor to the increase in total LBM in the SR group.
There may be several explanations for this nding, but it
seems like upper body muscles generally respond better
to strength-training stimuli than leg muscles (Wernbom,
Augustsson, & Thomee, 2007). Furthermore, all athletes
already had a heavy load on leg muscle in their sport-
specic training, which may have reduced the training
potential in these muscles. This is also supported by the
performance results showing more gain in upper body
strength in SR than FR. The increased LBM in SR and
maintained LBM in FR during a 5–6% reduction in BW
is a controversial result (Koutedakis et al., 1994; Smith et
al., 2001; Umeda et al., 2004), because the subjects were
normal-weight athletes with a history of high training
volume, including strength training.
Studies on gradual weight loss in athletes are sparse,
and the methodology is limited because of small sample
sizes and different nutritional strategies and measure-
ments of performance and body composition. However, it
has been reported that loss of LBM accounts for 30–85%
of total weight loss after reducing BW by 4–8% (Kout-
edakis et al., 1994; Slater, Rice, Jenkins, Gulbin, & Hahn,
2006; Umeda et al., 2004). Furthermore, a curvilinear
relationship between initial body-fat content and the
proportion of weight loss consisting of LBM is reported
(Forbes, 2000). Consequently, weight loss in already
lean people will normally compromise LBM even when
Weight Loss in Elite Athletes 103
exercise is incorporated in the weight-loss intervention
(Forbes, 2000). Although some studies support this,
especially studies that include endurance exercise as the
intervention (Kraemer et al., 1999), other studies report a
different weight-loss composition in favor of preserving
LBM when heavy strength training is added (Kraemer
et al., 1999; Stiegler & Cunliffe, 2006). Although the
composition of the weight loss varies between studies,
most studies report loss of LBM during energy restric-
tion even in obese subjects (Forbes, 2000; Stiegler &
Cunliffe, 2006).
In contrast to the suggested curvilinear relationship
between initial body-fat content and the proportion of
weight loss consisting of LBM, we found no correlations
between initial fat mass and changes in LBM. The reason
for this may be that the heavy strength training during
the intervention stimulated muscle growth and thereby
overrode the catabolic effect of negative energy balance
on LBM. In a study by Umeda et al. (2004), 38 athletes
participated in a 20-day intense training regimen (21 hr/
week exercise, including 2 hr/week of strength training)
combined with energy restriction. The athletes reduced
their BW by 2.8 kg, and loss of fat-free mass contributed
to 61% of the total weight loss. Although the intervention
was of shorter duration, the weekly weight-loss rate cor-
responded to 1.2% of BW and thus is comparable with
the result in the current study. These results suggest that
a certain amount of heavy strength training is critical to
preserve or increase LBM during energy restriction in
elite athletes.
The relative increase in LBM was significantly
greater in women than men. There were no signicant
differences in total training hours or weekly hours of
strength training between men and women the season
before entering the study. The fact that women had a
higher baseline percent body fat may have contributed to
a greater potential for LBM increase in women, as well
as other factors such as type of previous strength training.
Strength- and Power-Related Performance
The results of the performance tests support the fact that
the duration of the intervention was important for changes
in strength- and power-related performance. Study results
are equivocal when it comes to performance. Some stud-
ies report unchanged or improved performance in certain
tests after weight loss in athletes, despite loss of LBM
(Smith et al., 2001), whereas other studies report impaired
performance (Degoutte at al., 2006; Koral & Dosseville,
2009; Umeda et al., 2004). It is a challenge to measure
sport-specic performance and interpret the results, espe-
cially if athletes from more than one sport are included.
We included athletes from several sports in this study
for several reasons. Adequate sample size is one of the
limiting factors when elite athletes are included in more
challenging intervention studies. Furthermore, it was
important for us to include all the athletes that requested
weight-loss assistance. Because of the heterogeneous
group of athletes in this study, we included more general
tests of strength- and power-related performance. Nev-
ertheless, the more general impact on physical capacity
measured in this study provides important information
on how function is affected by the interventions.
EDI
Because dieting has been considered a risk factor for
development of eating disorders (Nattiv et al., 2007;
Sundgot-Borgen, 1994), it was expected that the athletes
might increase their scores on the drive-for-thinness test
(the higher the score, the more symptomatic). Neither SR
nor FR increased any of the subscale scores during the
intervention period. The lack of increased scores in EDI
subscales can probably be explained by the fact that none
of the athletes had symptoms of eating disorders at base-
line. Furthermore, these athletes were all closely guided
during the weight-loss period. It has been stated that in
terms of developing eating disorders, it is not necessarily
dieting, per se, that triggers an eating disorder but whether
or not the athlete is guided during the weight-loss period
(Sundgot-Borgen, 1994).
Compliance
Three athletes in SR and 5 in FR did not accomplish their
weight-loss goals. Although every athlete was closely
followed to reach their nal weight goal, we did not put
pressure on them in favor of study compliance for ethical
reasons. One might also consider whether the noncom-
pliers actually were nonresponders to the intervention
because of counterregulatory mechanisms (i.e., reduced
metabolism or other mechanisms increasing food ef-
ciency; Brownell, Steen, & Wilmore, 1987).
Experimental Design
To be able to do a controlled weight-loss intervention in
elite athletes’ off-season, we had to accept some limiting
factors in the study design and therefore interpret the results
with caution. Studies and practical experience indicated
that weight loss in normal-weight athletes would com-
promise LBM and thereby performance. Because many
of the athletes were to participate in major competitions
a short time after the intervention, we had to include
strength training during the intervention to prevent decline
in performance. A cleaner approach would be to look at
weight-loss rate with standardized habitual training with no
additional stimuli for muscle growth. Different amounts of
weight lost during the intervention may also be a limiting
factor. A cleaner approach would be to standardize amount
of weight loss for all athletes (e.g., 5% of BW), but for
ethical and health reasons this was not feasible.
Conclusion
The initial aim of twofold difference in weight-loss rate
was not achieved in all the athletes in FR, resulting in
a weekly weight-loss rate corresponding to 1.0% of
104 Garthe et al.
BW rather than 1.4%. However, total LBM increased
signicantly more in SR, accompanied by signicantly
improved performance in CMJ and all the 1RM tests,
whereas there was no signicant increase in LBM or
improvements in performance except in 1RM squat in
FR. Separating weekly gains in LBM and improvements
in strength- and power-related performance, there was
a signicant difference between groups in favor of SR.
This leads to a general suggestion that athletes who want
to gain LBM and increase strength- and power-related
performance during a weight-loss period combined with
strength training should aim for a weekly weight loss of
0.7% of BW, whereas athletes who only want to keep
LBM might increase their weekly weight-loss rate to
1.0–1.4% of BW.
Acknowledgments
The authors would like to thank the athletes who participated in
the study for their time and dedication. We also want to thank
Elisabet Børsheim for proofreading the manuscript and Ron
Maughan and Kevin Tipton for valuable contributions during
the writing process. This article is dedicated to Per Egil Refsnes
(co-author), who passed away in a bicycle accident during the
work on the current article. Thank you for your inspiration and
for being a great friend and colleague.
Disclosure statement of funding: Norwegian Olympic Sports
Center and Norwegian School of Sport Sciences.
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