J Appl Physiol 103: 1613–1621, 2007.
First published August 16, 2007; doi:10.1152/japplphysiol.00179.2007.
Energy flux, more so than energy balance, protein intake, or fitness level,
influences insulin-like growth factor-I system responses during 7 days of
increased physical activity
Kevin R. Rarick,1 Matthew A. Pikosky,2 Ann Grediagin,2 Tracey J. Smith,2 Ellen L. Glickman,2
Joseph A. Alemany,1 Jeffery S. Staab,1 Andrew J. Young,2 and Bradley C. Nindl1
1
Military Performance Division and 2Military Nutrition Division, U. S. Army Research Institute of Environmental Medicine,
Natick, Massachusetts
Submitted 19 February 2007; accepted in final form 13 August 2007
INSULIN-LIKE GROWTH FACTOR-I (IGF-I) can be produced both
systemically in an endocrine fashion and locally in an autocrine/paracrine fashion. In terms of exercise responses, the
literature has firmly established that local IGF-I expression is
upregulated following exercise. However, the literature is
equivocal with regard to systemic (i.e., circulating) IGF-I in
that studies have shown increases (21, 25), decreases (27, 29,
33), and no changes (5, 22, 31) following both acute and
chronic exercise studies. These findings are consistent with the
idea that locally synthesized IGF-I plays a predominant role in
body growth and has led some to question the physiological
relevance of circulating IGF-I and its role in tissue remodeling.
However, recent studies suggested that circulating IGF-I concentrations may be related to the development or progression
of pathological conditions such as cancer (20), heart disease
(17), diabetes (34), and neural disease (7). Additionally,
definitive data were published illustrating the importance of
circulating IGF-I in the direct regulation of bone growth and
density (38).
Recently, our laboratory demonstrated that circulating IGF-I
has greater prognostic utility than other conventional nutritional biomarkers when assessing weight change during metabolic strain (28). Thus the physiological significance of circulating IGF-I may reside in its ability as a biomarker to reflect
changes in health and fitness profiles. However, the unclear
association between exercise and circulating IGF-I emphasizes
the need to further investigate the IGF-I response during
periods of physical activity and altered energy states. Such
information may provide greater insight with regard to the
relative role of circulating vs. local IGF-I as well as the
pleiotropic effects that IGF-I exerts in mediating the beneficial
outcomes of exercise.
The disparate effects of exercise on circulating IGF-I might
be attributable to effects of fitness level and/or dietary intake
variations, since most studies have not adequately controlled
for these coincident effects. With respect to fitness level per se,
Rosendal et al. (33) reported that untrained individuals showed
more extensive changes in the IGF-I system during an 11-wk
physical training program than trained individuals. Variations
in total energy availability regulate IGF-I and the family of
insulin-like growth factor binding proteins (IGFBPs; Refs. 8,
19, 37) and may influence the circulating IGF-I responses to
exercise. Smith et al. (35) demonstrated that negative energy
balance induced by caloric restriction without exercise decreased IGF-I to the same extent as an equivalent exerciseinduced negative energy balance. Dietary macronutrient composition also can influence the IGF-I system (15). For example,
dietary protein restriction has been shown to decrease IGF-I
and IGFBP-3, as well as increase IGFBP-2, even when total
caloric content of the diet remains constant (36). Similarly,
among subjects participating in a 6-mo strength and conditioning program, those who consumed a diet supplemented with
Address for reprint requests and other correspondence: B. C. Nindl, Military
Performance Division, U. S. Army Research Institute of Environmental Medicine, Natick, MA 01760 (e-mail: [email protected]).
The costs of publication of this article were defrayed in part by the payment
of page charges. The article must therefore be hereby marked “advertisement”
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
insulin-like growth factor binding proteins; exercise; nutritional factors
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Rarick KR, Pikosky MA, Grediagin A, Smith TJ, Glickman
EL, Alemany JA, Staab JS, Young AJ, Nindl BC. Energy flux,
more so than energy balance, protein intake, or fitness level, influences insulin-like growth factor-I system responses during 7 days of
increased physical activity. J Appl Physiol 103: 1613–1621, 2007. First
published August 16, 2007; doi:10.1152/japplphysiol.00179.2007.—The
purpose of this study was to determine the impact of dietary factors
and exercise-associated factors on the response of IGF-I and its
binding proteins (IGFBPs) during a period of increased physical
activity. Twenty-nine men completed a 4-day (days 1– 4) baseline
period of a controlled energy balanced diet while maintaining their
normal physical activity level followed by 7 days (days 5–11) of a
1,000 kcal/day increase in physical activity above their normal activity levels. Two subject groups, one sedentary (Sed, mean V̇O2peak: 39
ml 䡠 kg⫺1 䡠 min⫺1, n ⫽ 7) and one fit (FIT1, mean V̇O2peak: 56
ml 䡠 kg⫺1 䡠 min⫺1, n ⫽ 8) increased energy intake to maintain energy
balance throughout the 7-day intervention. In two other fit subject
groups (FIT2, n ⫽ 7 and FIT3, n ⫽ 7), energy intake remained at
baseline resulting in a 1,000 kcal/day exercise-induced energy deficit.
Of these, FIT2 received an adequate protein diet (0.9 g/kg), and FIT3
received a high-protein diet (1.8 g/kg). For all four groups, IGF-I,
IGFBP-3, and the acid labile subunit (ALS) were significantly decreased by day 11 (27 ⫾ 4%, 10 ⫾ 2%, and 19 ⫾ 4%, respectively)
and IGFBP-2 significantly increased by 49 ⫾ 21% following day 3.
IGFBP-1 significantly increased only in the two negative energy
balance groups, FIT2 (38 ⫾ 6%) and FIT3 (46 ⫾ 8%). Differences in
initial fitness level and dietary protein intake did not alter the IGF-I
system response to an acute increase in physical activity. Decreases in
IGF-I were observed during a moderate increase in physical activity
despite maintaining energy balance, suggesting that currently unexplained exercise-associated mechanisms, such as increased energy
flux, regulate IGF-I independent of energy deficit.
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ENERGY BALANCE AND IGF-I
METHODS
Subjects. Twenty-nine healthy men gave informed consent to
complete the study after an oral and written explanation of all study
procedures and risks. All subjects were medically cleared for participation in accordance with United States Army Research Institute of
Environmental Medicine guidelines for human use. The study followed the policies for protection of human subjects as prescribed in
Army Regulation 70 –25, and the research was conducted in adherence with the provisions of 32 CFR Part 219. As part of the initial
screening, each subject’s V̇O2peak was assessed with a continuous
cycle ergometer test. The V̇O2peak value was used to classify the
subjects as fit (cut point V̇O2peak value ⬎ 52–54 ml 䡠 kg⫺1 䡠 min⫺1) or
sedentary (cut point V̇O2peak value ⬍ 41– 43 ml 䡠 kg⫺1 䡠 min⫺1). Subjects were divided into four separate experimental groups (refer to
Fig. 1): one sedentary (Sed) and via random selection into three fit
(FIT1, FIT2, and FIT3). Subjects were housed in the Doriot Climatic
Chambers Metabolic laboratory at the Natick Soldier Systems Command in Natick, MA, for the duration of the study to ensure dietary
compliance and to tightly control and measure energy expenditure.
Diet and activity intervention. Refer to Table 1. Baseline period
(days 1– 4): for the 4-day baseline period, all subjects were given a
controlled diet that replicated their normal energy intake and they also
maintained their normal physical activity level. Throughout the study,
dietary protein intake was held constant at 0.9 g protein 䡠 kg body
wt⫺1 䡠 day⫺1 (Sed, FIT1, FIT2) or 1.8 g protein 䡠 kg body wt⫺1 䡠 day⫺1
(FIT3). To determine normal energy intake and activity, each subject
kept a 3-day diet and activity record the week preceding the study. All
subjects were interviewed to ensure the accuracy of the 3-day records.
During the interview, each subject was asked to describe in detail
(type, duration, and intensity) their typical weekly exercise habits and
to quantify their exercise training history for the 6 mo leading up to
the study. Energy intake and expenditure values were compared and
used collectively to determine each subject’s energy requirements and
activity prescription during the 4-day baseline period to maintain
energy balance. The actual total daily energy expenditure (TDEE) for
each subject was verified using indirect calorimetry during each
activity (as described below) on day 1 of the 4-day baseline period to
ensure that energy balance was maintained. The type, intensity, and
duration of all activities (normal daily and physical) throughout the
baseline period were tightly controlled by dividing each 24-h period
into prescribed 15-min blocks at a specific metabolic equivalent
(MET) level to duplicate the subjects’ normal daily caloric expendi-
Fig. 1. Experimental design displaying the subject inclusion criteria, the intervention description for the 4 experimental groups, and the comparisons and research
questions being investigated.
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additional dietary protein (2.2 g/kg) exhibited higher circulating IGF-I concentrations than subjects who consumed
an isocaloric diet with a normal (1.1 g/kg) dietary protein
intake (1).
While it is clearly established that circulating IGF-I declines
during caloric restriction, recent work suggested that IGF-I
may also decline in response to an increase in physical activity
even during energy balance (26). This suggests that, rather than
the overall energy balance, the IGF-I system may be responding to the energy flux of the metabolic system, defined as the
absolute level of energy intake and expenditure under conditions of energy balance (4). Furthermore, it is not known
whether manipulating dietary protein content of an energydeficient diet will influence IGF-I responses to exercise. Therefore, the purpose of the current study was to further characterize the relationship between dietary factors and exercise-associated factors and their impact on the IGF-I system by strictly
controlling for energy and protein intake and energy expenditure. Specifically we tested three hypotheses: 1) an increase in
physical activity would significantly decrease circulating IGF-I
to a greater extent when in energy deficit vs. when in energy
balance, 2) a protein-supplemented diet would attenuate a
decrease in circulating IGF-I during an energy deficit, and 3)
there would be a greater decrease in circulating IGF-I in
sedentary vs. fit individuals following an increase in physical
activity matched with energy intake. As IGF-I binding proteins
regulate IGF-I bioavailability, we also measured the circulating
concentrations of IGFBP-1, -2, -3, and the ALS.
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ENERGY BALANCE AND IGF-I
Table 1. Timeline of study for all four groups
Baseline Period
Study Period Day
Prescreening
V̇O2peak determination
3-day diet record
Activity record
Controlled diet
Normal daily activity
Additional 1,000 kcal exercise
TDEE verification
Fasting blood draw
X
X
X
Exercise/ Caloric Intervention
1
2
3
4
5
6
7
8
9
10
11
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
12
X
X denotes what day(s) intervention was performed. TDEE, total daily energy expenditure.
J Appl Physiol • VOL
in the USARIEM metabolic kitchen by a registered dietitian.
Throughout the study, the protein content of the diet was held constant
at 0.9 (Sed, FIT1, and FIT2) or 1.8 (FIT3) g 䡠 kg body wt⫺1 䡠 day⫺1.
Total energy content was adjusted by adding or subtracting fat- and
carbohydrate-containing foods so that the caloric ratio of these nutrients in the diet remained ⬃1:2, respectively. The dietary composition
of the total daily energy intake was ⬃8 to 12.6% protein, 32–37% fat,
and 55% carbohydrate and contained at least 80% of the recommended daily allowance for vitamins and minerals. Meals were served
according to a fixed schedule, but water and sugar-free noncaffeinated
drinks were taken ad libitum.
Blood collection. Fasting blood samples were collected in the
morning on days 3, 5, 6, 11, and 12 by venipuncture. The blood
samples were immediately delivered to the lab, allowed to clot at
room temperature and then centrifuged. The serum was then aliquoted
and stored at ⫺80°C until assays were performed.
Body composition. Body weight was measured at baseline and on
day 11 of the intervention using a calibrated electronic batterypowered scale accurate to 0.1 kg. Body composition was determined
by whole body dual energy X-ray absorptiometry (DEXA). Total
body estimates of percent fat and non-bone lean tissue were determined using manufacturer-described procedures and supplied algorithms (Lunar, Madison, WI). DEXA measurements were done at
baseline and on day 11 of the intervention.
IGF-I system assays. Total IGF-I, IGFBP-1, and IGFBP-3 concentrations were determined by two-site immunoradiometric assays
(IRMA). IGFBP-2 was measured using a RIA. Total ALS was
measured by ELISA. All immunoassays were products of Diagnostic
System Laboratories (Webster, TX). IRMA and RIA were performed
on a Cobra gamma counter (Packard Instruments, Downers Grove,
IL). ELISA were performed using a 96-well plate washer and microplate absorbance reader (Microtiter plate washer, MRX Revelation
reader, Dynex Technologies, Chantilly, VA). All samples for a given
subject were run in the same assay batch to eliminate interassay
variance. Immunoassay sensitivities for IGF-I, IGFBP-1, -2, -3, and
ALS were 2.06, 0.33, 0.5, 0.5, and 0.7 ng/ml, respectively. Interassay
variances for IGF-I, IGFBP-1, -2, -3, and ALS were 1.7%, 7.3%,
4.5%, 2.4%, and 5.6%, respectively. Intra-assay variances for IGF-I,
IGFBP-1, -2, -3, and ALS were 2.8%, and 7.5%, 4.8%, 3.0%, 7.3%,
respectively.
Statistical analysis. The analyses were divided into three groups:
Sed vs. FIT1, FIT1 vs. FIT2, and FIT2 vs. FIT3. This allowed us to
independently investigate the effects of fitness level, energy balance, and protein intake while controlling for the other variables.
All results are reported as means (SD). A repeated-measures
ANOVA (Statistica, StatSoft, Tulsa, OK) was used to compare the
IGF-I system concentrations between and within groups on days 3,
5, 6, 11, and 12. A P value of (P ⬍ 0.05) was accepted as
indicating significant differences.
103 • NOVEMBER 2007 •
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ture and simulate their normal activity level. Exercise/caloric intervention period (days 5–11): during days 5–11, subjects increased their
daily energy expenditure by 1,000 kcal/day by performing additional
exercise at 50 – 65% of their V̇O2peak. For subject comfort and to
reduce injuries, exercise was divided among different modes (bike,
treadmill, elliptical) and performed in 15-min bouts spaced throughout
the day. As during the baseline period, the type, intensity, and
duration of all activities (normal daily and physical) throughout the
intervention period were tightly controlled by dividing each 24 h
period into prescribed 15-min blocks at a specific MET level. On the
first day of the 7-day exercise intervention (day 5), Sed and FIT1
increased their energy expenditure and caloric intake (the groups were
in energy balance), while FIT2 and FIT3 increased energy expenditure
but did not increase caloric intake (the groups were in an energy
deficit). For days 6 – 8, subjects replicated the activity of day 5. On
day 9, energy expenditure was again verified and duration was
adjusted to obtain the desired expenditure. Days 10 –11 replicated the
activity of day 9. On day 12, fasting blood samples were obtained in
the morning, after which there was no further activity.
Description of TDEE verification. TDEE was measured on baseline
period day 1 and on exercise intervention period days 5 and 9. While
still in bed, each subject was awoken enough to attach a noseclip and
a two-way rebreathing valve to collect samples of expired air and
calculate V̇O2 and V̇CO2 (Parvo Medics, Sandy, UT) to determine
resting metabolic rate. The measured resting metabolic rate was used
to estimate the energy expended while the subjects slept (EEsleep).
During each different exercise session throughout the day, once steady
state was reached (⬃5 min), the subjects’ expired air was collected for
10 min using the same computer-based metabolic system. The energy
expenditure from each exercise session was used to determine the
total energy cost of all physical activities (EEphysical activity). The same
procedure was used to determine the energy cost of non-exercise
activities [i.e., watching TV, playing video games, reading (EEother)].
TDEE was determined by adding the total energy cost of all
activity and exercise sessions to the estimated energy expenditure
of sleep (EEtotal ⫽ EEsleep ⫹ EEphysical activity ⫹ EEother). For the
purpose of this study we are considering our subjects to be in a
state of increased energy flux when they have an increase in TDEE,
resulting from increased physical activity, matched with an increase in energy intake to maintain energy balance. This working
definition of energy flux has previously been published in the
literature (4, 6, 13).
Study diet. Three to five days prior to starting the baseline period,
subjects were asked to consume a diet that contained the same amount
of protein as the study diet to help habituate hepatic enzymes to a
specific protein level. Subjects were instructed by dietitians on how to
do this during the prescreening evaluation of their 3-day diet record.
The controlled diet consumed throughout the experimental phase of
the study, when the subjects were residing in the metabolic laboratory,
consisted of whole foods and liquid supplements provided to each
subject in individually prescribed amounts. All meals were prepared
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ENERGY BALANCE AND IGF-I
Table 2. Anthropometric data
Weight, kg
Sed
FIT1
FIT2
FIT3
LBM, kg
Fat mass, kg
Pre
Post
Pre
Post
Pre
Post
74.4 (7.3)
73.4 (7.4)
73.3 (7.2)
85.7 (9.1)
73.6 (7.2)
72.5 (8.1)
70.9 (7.4)*
83.0 (9.1)*
59.3 (4.6)
62.1 (5.0)
63.3 (5.2)
73.1 (7.5)
59.4 (4.8)
61.6 (5.0)
61.8 (5.0)*
71.8 (7.7)*
15.1 (3.9)
11.2 (3.0)
10.0 (6.1)
12.5 (4.3)
14.2 (4.5)
11.0 (3.5)
9.0 (6.3)*
11.2 (4.6)*
Values are mean (SD). LBM, lean body mass; Sed, sedentary groups; FIT, fit groups. * Denotes significant decrease from the Pre value (P ⬍ 0.05).
RESULTS
DISCUSSION
The purpose of this study was to further characterize the
relationship between diet and exercise and their influence on
the IGF-I system by isolating the singular effects of variations
in energy balance, dietary protein intake, and fitness level on
circulating concentrations of IGF-I and IGF binding proteins.
Studying circulating IGF-I remains important due to its utility
as a biomarker reflecting health and fitness status as well as to
the fact that the relationship between systemic and local IGF-I
remains obscure. Because of the effect of nutritional intake on
the IGF-I system, we tightly controlled the daily caloric intake
and total energy expenditure for each individual subject during
the 11-day study period. Our data clearly demonstrate that
alterations in the circulating IGF-I system occur with increased
daily physical activity over a 7-day period. The IGF-I system
changes observed during the 7 days of increased activity were
similar despite: 1) differences in energy balance, 2) differences
in dietary protein intake, and 3) differences in fitness level. As
the increase in physical activity was the common factor inherent to the observed IGF-I alterations, our data suggest that the
Table 3. Average caloric intake and expenditure
Days 1– 4
Sed
FIT 1
FIT 2
FIT 3
Days 5–11
Intake
Expenditure
Intake
Expenditure
2,861 (351)1,2,3
3,538 (725)S
3,470 (375)S
3,919 (953)S
2,891 (370)1,2,3
3,558 (734)S
3,491 (398)S
3,932 (942)S
3,825 (374)1
4,486 (720)S,2
3,429 (377)2
3,914 (954)
3,876 (371)1,2,3
4,553 (730)S
4,447 (415)S,*
4,934 (941)S,*
Values are mean (SD) in kcal. Days 1– 4 was the baseline period. The intervention occurred on days 5–11, with activity being increased 1,000 kcal/day for
all groups. For the intervention period, groups Sed and FIT1 were given extra calories to account for the increased activity while groups FIT2 and FIT3 were
not given extra calories, resulting in a caloric deficit. Superscripts denote that value is significantly different from specified group (SSED, 1FIT1, 2FIT2, 3FIT3);
*significantly different from the intake value (P ⬍ 0.05).
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Body composition. Table 2 displays the body composition
changes for the study. Sed and FIT1 did not experience any
significant changes in body weight, lean body mass (LBM), or
fat mass. FIT2 and FIT3 showed significant decreases in body
weight (3.5 and 3.2%, respectively), LBM (2.5 and 2.0%,
respectively), and fat mass (11 and 13.5%, respectively).
Energy balance. Table 3 displays the caloric intake and
expenditure data for the study. During the baseline period
(days 1– 4), all subjects were in energy balance and maintained
their normal daily intake and expenditure as calculated from
their individual diet and activity records. For the 7-day exercise
intervention period (days 5–11), all subjects increased their
daily energy expenditure by ⬃1,000 kcal/day. Energy intake
was increased to match expenditure or remained unchanged
depending on the intervention group.
IGF-I system responses: impact of energy balance on IGF-I
(FIT1 vs. FIT2). No interaction or group effects were demonstrated. We observed similar changes in IGF-I, IGFBP-1–2–3,
and ALS for both FIT1 (maintained energy balance) and FIT2
(energy deficit of 1,000 kcal/day) in response to the 7-day
increase in physical activity (see Fig. 2). IGF-I was similar
across days 3– 6, but decreased significantly by days 11 and 12.
IGFBP-1 exhibited no significant differences. IGFBP-2 was
increased on day 5 and remained elevated throughout the
study. IGFBP-3 and ALS decreased on days 6 and 11, respectively, and remained lower throughout the study.
Impact of dietary protein intake on IGF-I (FIT2 vs. FIT3).
No interaction or group effects were demonstrated. We observed similar changes in IGF-I, IGFBP-1–2–3, and ALS for
both FIT2 (adequate protein diet, 0.9 g/kg) and FIT3 (highprotein diet, 1.8 g/kg) in response to the 7-day increase in
physical activity (see Fig. 3). IGF-I was similar across days
3– 6, but decreased significantly by days 11 and 12. IGFBP-1
increased at day 6 and remained elevated. IGFBP-2 increased
on day 5 and showed an additional increase by day 11.
IGFBP-3 and ALS decreased by days 11 and 12, respectively.
Impact of fitness level on IGF-I (Sed vs. FIT1). No interaction effects were demonstrated, however, a main group effect
was demonstrated for IGFBP-1 (P ⫽ 0.01) and IGFBP-2 (P ⫽
0.02). We observed similar changes in IGF-I, IGFBP-1–2-3,
and ALS for both Sed (V̇O2peak: 39 ml䡠kg⫺1 䡠min⫺1) and FIT1
(V̇O2peak: 56 ml䡠kg⫺1 䡠min⫺1) in response to the 7-day increase
in physical activity (see Fig. 4). IGF-I decreased at days 6 and
was significantly lower throughout the remainder of the study.
IGFBP-1 exhibited no significant differences. IGFBP-2 was
increased on days 5 and continued to increase thereafter.
IGFBP-3 and ALS decreased by days 6 and continued to
decrease thereafter.
ENERGY BALANCE AND IGF-I
1617
Fig. 2. Graphs A-E display the mean concentrations of insulin-like growth
factor (IGF)-I, IGF binding protein (IGFBP)-1, IGFBP-2, IGFBP-3, and the
acid labile subunit (ALS), respectively, for 1 and 2 groups of fit subjects (FIT1
and FIT2) over the 7-day intervention. The FIT1 (caloric balance) vs. FIT2
(caloric deficit) comparison addressed the question of energy balance on IGF-I
system responses. Graphs F-J combine the mean concentrations of both groups
to show the observed time effect of the 7-day intervention on the IGF-I system.
The dotted line divides the graphs into the baseline period [days 1– 4 (D1-D4)]
and the intervention period (D5-D11). Mean concentrations with different
superscripts are significantly different (P ⬍ 0.05).
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circulating IGF-I system is influenced by yet unidentified
exercise-associated mechanisms that are stimulated during periods of increased energy flux (periods of increased energy
intake and expenditure under conditions of energy balance) and
not necessarily solely dependent on an energy deficit.
Impact of energy balance on IGF-I (FIT1 vs. FIT2). Surprisingly, this study observed an ⬃30% decline in circulating
IGF-I over a 7-day period of increased physical activity, which
was a similar response regardless of whether subjects were in
an energy balance or in a 1,000 kcal/day energy deficit. The
belief that energy restriction is the principal regulator causing
IGF-I decrements during a negative energy balance has been
supported by numerous studies (11, 12, 16, 18, 26, 29, 35, 36).
For example, Smith et al. (35) previously demonstrated similar
IGF-I declines during an energy deficit whether the deficit was
created by exercise or caloric restriction and concluded that the
IGF-I decline was mainly the result of a mismatch between
energy intake/expenditure. Our data challenge this well-established concept by reporting a decline in IGF-I during a 7-day
period of energy balance (FIT1 group). In essence, we demonstrated that the well known IGF-I decline normally observed
during a catabolic, negative energy balance can also be observed with increased physical activity while maintaining energy balance.
The current study contributes to a growing body of evidence
that the “normal” response pattern of IGF-I during short-term,
acute physical activity is that of a reduction. Declines in IGF-I
have also been demonstrated in exercise training studies ranging from 5 to 12 wk in such diverse populations as male and
female adolescents (9, 10) and end-stage renal disease patients
(30). Although these previous training studies did not control
energy intake and expenditure to the extent implemented in the
current study, the subjects in those studies did maintain body
mass and/or increase muscle thigh volume, indicating that the
subjects trained in an overall state of energy balance. In
addition, we are confident that the results observed for the
current study are the effects from the 7-day intervention and
not the effect from the last bout of exercise, as we previously
demonstrated no changes in 12-h circulating total IGF-I concentrations after an acute bout of exercise (31).
Of further interest are the findings from Nemet et al. (26)
who examined IGF-I responses during 7 day of strenuous
exercise in two groups that were either underfed or overfed. In
this study, the daily exercise-associated energy expenditure for
both the overfed and underfed groups was similar to the current
study (⬃1,000 kcal/day). The overfed group had a positive
energy balance of 393 kcal/day, a 1% increase in body mass
and did not experience any change in IGF-I, whereas the
underfed group had a negative energy balance of 2,052 kcal/
day, a 1.5% decrease in body mass, and reported a similar
IGF-I decline as observed in the current study (⬃30%). Nemet
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ENERGY BALANCE AND IGF-I
Fig. 3. Graphs A-E display the mean concentrations of IGF-I, IGFBP-1,
IGFBP-2, IGFBP-3, and the ALS, respectively, for FIT2 and FIT3 over the
7-day intervention. The FIT2 (0.9 k/kg protein) vs. FIT3 (1.8 g/kg protein)
comparison addressed the question of dietary protein intake on IGF-I system
responses. Graphs F-J combine the mean concentrations of both groups to
show the observed time effect of the 7-day intervention on the IGF-I system.
The dashed line divides the graphs into the baseline period (D1–D4) and the
intervention period (D5–D11). Mean concentrations with different superscripts
are significantly different (P ⬍ 0.05).
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et al. (26) suggested that exercise prevented the overfed group
from demonstrating an increase in IGF-I and with the use of
regression analyses, further illustrated that under conditions of
energy balance, exercise may induce declines in IGF-I concentrations.
In contrast to the decline in circulating IGF-I over 7 days of
exercise observed in the current study and reported by Nemet
et al. (26), Ormsbee et al. (32) reported no changes in circulating IGF-I during 5 days of physical activity (500 kcal/day)
in energy balance, negative energy (approximately ⫺500 kcal/
day), or positive energy balance (⬃500 kcal/day). Taken together, the collective findings to date suggest that circulating
IGF-I declines during both large increases in energy flux (level
of high energy intake and high expenditure under conditions of
energy balance) as well as during a negative energy balance.
Impact of dietary protein intake on IGF-I (FIT2 vs. FIT3).
Our results demonstrate that increasing dietary protein intake
(1.8 g/kg body wt) did not attenuate the decline in circulating
IGF-I concentrations compared with a normal dietary protein
intake (0.9 g/kg body wt) in fit individuals subjected to a 1,000
kcal/day exercise-induced energy deficit over a 7-day period.
Previous research has shown an increase in circulating IGF-I
following prolonged strength and conditioning training with
protein supplementation compared with carbohydrate supplementation (1). Cross-sectional analysis has also shown a positive association between dietary protein intake and circulating
IGF-I concentrations (14). It is possible that the acute increase
in activity resulting in an exercise-induced negative energy
balance in our subjects could not be corrected by increasing
dietary protein intake without a concomitant increase in caloric
intake. Isley et al. (15) demonstrated the existence of a threshold of energy intake that is necessary to return circulating
IGF-I concentrations to prefasting concentrations and suggested that overall energy intake may be of greater importance
than the macronutrient content of the diet. Our results provide
additional support to this idea by suggesting that when adequate energy is not available (i.e., during a 7-day period of an
exercise-induced caloric deficit), similar decreases in IGF-I
concentrations are observed with both adequate (0.9 g/kg body
wt) and high (1.8 g/kg body wt) dietary protein intake. When
adequate energy is available, a positive correlation has been
shown between protein intake and IGF-I (16). Therefore it is
possible that increasing dietary protein intake could have
modulated IGF-I concentrations if our subjects had been in
energy balance.
Our data also suggest that macronutrient content of the diet
may not be as important as total energy availability in maintaining lean body mass during periods of increased physical
activity. It was suggested that increasing dietary protein intake
while decreasing total energy intake with or without exercise
can result in decreases in body weight while sparing lean body
ENERGY BALANCE AND IGF-I
1619
Fig. 4. Graphs A-E display the mean concentrations of IGF-I, IGFBP-1,
IGFBP-2, IGFBP-3, and the ALS, respectively, for sedentary (Sed) and FIT1
over the 7-day intervention. The Sed (low fitness) vs. FIT1 (high fitness)
comparison addressed the question of fitness level on IGF-I system responses.
Graphs F-J combine the mean concentrations of both groups to show the
observed time effect of the 7-day intervention on the IGF-I system. The dashed
line divides the graphs into the baseline period (D1–D4) and the intervention
period (D5–D11). Mean concentrations with different superscripts are significantly different (P ⬍ 0.05).
J Appl Physiol • VOL
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mass (24). In the current study, we demonstrated that increasing dietary protein intake, 0.9 (FIT2) vs. 1.8 g/kg body wt
(FIT3), did not conserve lean body mass when normal daily
activity was increased to induce an energy deficit. Layman et
al. (23) showed that overweight females on a high-protein diet
tended to lose less lean mass than those on a normal protein,
high-carbohydrate diet; however, lean mass was still lost,
except in subjects that exercised in addition to increasing
protein intake. The discrepancy in these findings is most likely
due to the fact that our subjects experienced a relatively greater
daily energy deficit due to a greater exercise stress.
Impact of fitness level on IGF-I (Sed vs. FIT1). Both the Sed
and FIT1 groups experienced similar declines in IGF-I during
the 7-day period of increased energy flux. Also observed was
a significant increase for IGFBP-2 and a decrease for IGFBP-3
and ALS, but no alterations for IGFBP-1. The magnitudes of
these changes were similar for both the sedentary and fit
subjects. Our results suggest that initial fitness level does not
alter the circulating IGF-I response to an acute increase in 7
days of physical activity. These findings are in contrast to
Manetta et al. (25), who demonstrated a differential response of
IGF-I in trained vs. sedentary subjects to a single bout of
endurance exercise. Furthermore, Rosendal et al. (33) showed
a differential effect of an 11-wk strength and conditioning
program on the circulating IGF-I system when comparing
untrained vs. trained individuals. They demonstrated that only
the untrained group experienced a significant perturbation in
total and free IGF-I, IGFBP-2, and IGFBP-3 proteolysis that
persisted throughout the entire 11 wk and suggested that
untrained vs. well-trained individuals have a lower threshold of
physiological stress that is needed to impact the IGF-I system.
However, they noted that at the start of the training, IGF-I
decreased in both untrained and well-trained subjects. It is
likely that the increase in metabolic activity, rate of energy
flux, associated with an acute increase in exercise results in an
alteration in the IGF-I system regardless of training status.
IGF binding protein responses. Our results suggest that 7
days of increasing normal daily activity by 1,000 kcal/day not
only decreases circulating concentrations of IGF-I but can also
impact the bioavailability of IGF-I by altering the concentrations of regulatory binding proteins such as IGFBP-1 (increased), -2 (increased), -3 (decreased), and ALS (decreased).
The increase that we observed in IGFBP-1 was only significant
in the two groups that were in a 1,000 kcal/day exerciseinduced caloric deficit and this increase likely contributes to
the maintenance of glucose homeostasis. Nutritional status is
considered a major regulator of IGF binding proteins (3).
Caloric restriction has been shown to increase concentrations
of IGFBP-1 and -2 and to decrease IGFBP-3 and ALS (2, 8,
29). IGFBP-1 is affected by acute dietary manipulations,
whereas IGFBP-2 and -3 are thought to be impacted only after
1620
ENERGY BALANCE AND IGF-I
DISCLAIMER
The opinions or assertions contained herein are the private views of the
author(s) and are not to be construed as official or reflecting the views of the
Army or the Department of Defense. Any citations of commercial organizations and trade names in this report do not constitute an official Department of
the Army endorsement of approval of the products or services of these
organizations.
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