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Department of Human Biology and Department of Movement Sciences, University of Limburg, 6200 MD Maastricht, The Netherlands
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
ACKNOWLEDGEMENTS
FOOTNOTES
REFERENCES
ABSTRACT 
Van Etten, Ludo M. L. A., Klaas R. Westerterp, Frans T. J. Verstappen, Bart J. B. Boon, and Wim H. M. Saris. Effect of an
18-wk weight-training program on energy expenditure and physical
activity. J. Appl. Physiol. 82(1):
298-304, 1997.
The purpose of this study was to examine the
effect of an 18-wk weight-training program on average daily metabolic
rate (ADMR). Before the intervention and in weeks
8 and 18 (T0,
T8, and
T18, respectively) data on body
composition, sleeping metabolic rate (SMR), food intake, energy cost of
the weight-training program
(EEex), and nontraining physical
activity (accelerometer) were collected in the exercise group (EXER,
n = 18 males). ADMR was determined in
a subgroup (EX12, n = 12) by using
doubly labeled water. At T0 and
T18, data (except ADMR) were also
collected in a control group (Con, n = 8). Body mass did not change in EXER or Con. Fat-free mass increased only in EXER with 2.1 ± 1.2 kg, whereas fat mass decreased in EXER
as well as Con (2.0 ± 1.8 and 1.4 ± 1.0 kg, respectively). Initial ADMR (12.4 ± 1.2 MJ/day) increased at
T8 (13.5 ± 1.3 MJ/day, P < 0.001) with no further increase
at T18 (13.5 ± 1.9 MJ/day). SMR did not change in EXER (4.8 ± 0.5, 4.9 ± 0.5, 4.8 ± 0.5 kJ/min) or Con (4.7 ± 0.4, 4.8 ± 0.4 kJ/min). Energy intake did
not change in EXER (10.1 ± 1.8, 9.7 ± 1.8, 9.2 ± 1.9 MJ/day) or Con (10.2 ± 2.6, 9.4 ± 1.8, 10.1 ± 1.5 MJ/day)
and was systematically underreported in EX12 (
21 ± 14, 28 ± 18, 34 ± 14%,
P < 0.001).
EEex (0.47 ± 0.20, 0.50 ± 0.18 MJ/day) could only explain 40% of the increase in ADMR.
Nontraining physical activity did not change in both groups. In
conclusion, although of modest energy cost, weight-training induces a
significant increase in ADMR.
doubly labeled water; accelerometer; sleeping metabolic rate; food
intake; physical exercise
INTRODUCTION EVIDENCE FOR AN IMPORTANT ROLE of increased physical
activity in the quality of life and the primary prevention of coronary heart disease and cancer has grown in recent years (1a, 2, 7). For the
majority of the people having a sedentary job, the recommended raise in
general physical activity can be achieved by exercise, sport,
recreation, and life-style activities. Depending on the field of
interest and available time, a choice can be made from an extensive
selection of different sports activities. Weight training is an example
of an individual sport that is not restricted by time of the day or
weather conditions, and most forms of weight training are reported to
be safe, even for hypertensive and cardiac patients and the elderly
(15, 16). With the introduction of the easy-to-use weight stack
machines and electronic ergometers applied during warming-up and
cooling-down exercises (treadmills, bicycles, and rower and step
machines), the popularity of weight training has increased. Research on
the effect of weight training on health and fitness determinants
revealed that weight training, like other types of exercise, positively
affects physical performance and body composition and a number of
health parameters (21, 23, 27, 30). Almost every study revealed an
increase in muscular strength, whereas the effect on aerobic power is
inconsistent and dependent on the type of weight training [e.g.,
circuit vs. heavy resistance training (28), high vs. low volume weight
training (27)]. Compared with running and cycling, the
weight-training-induced changes in body composition consist of a larger
increase in fat-free mass, whereas the decrease in fat mass seems to be
somewhat smaller. The modest effect on fat mass might be attributed to
the lower energy costs of a single weight-training workout (17). The
latter finding seems to make this kind of exercise less effective in programs of weight control and weight reduction (17). However, previous
studies suggested that the effect of physical exercise on average daily
metabolic rate (ADMR) exceeds the energy cost of the training work
itself. This finding initiated research on the effect of exercise on
other components of ADMR like the thermic effect of feeding (22) and
sleeping/resting metabolic rate (33) or on excess postexercise energy
expenditure (20). Studies that measured ADMR confirmed that the energy
demand of the added physical exercise explains only partly the increase
in ADMR (5, 11, 35). A validated method to measure ADMR in free living
subjects is the doubly labeled water method
(2H218O).
Due to the high cost, only a few studies used this technique. Until
now, no study investigated the effect of weight training on ADMR.
The purpose of this study was to investigate the effect of an 18-wk
weight-training program on ADMR and the components sleeping metabolic
rate and the energy cost of physical activity (nontraining and exercise
activity) to quantify their contribution to an ensuing change in
ADMR. A 3-day food record was used to estimate energy intake and food
composition. A triaxial accelerometer was used to register nontraining
physical activity.
METHODS The overall design of the study is presented in Fig.
1.
Fig. 1.
Overall design. Actual training program consisted of 18 wk of weight
training (
). The first 3 wk were performed at the university to
determine the relationship between energy expenditure and heart rate
(HR) in week 3 (white solid circle).
Weeks 19 and
20 were not considered as part of the
training program but were used to check whether the energy
expenditure-HR relationship was changed. During weeks
1 and 19, an
incremental cycling test was performed (white open circle). ADMR,
average daily metabolic rate; EX 12, subgroup of 12 subjects; comp,
composition; SMR, sleeping metabolic rate; EXER, exercise group; CONT,
control group.
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160 beats/min, until exhaustion.
To check whether the training program induced a change in the EE/HR
relationship (preintervention equation), the calibration protocol was
repeated after the 18 wk of training (postintervention equation).
However, three instead of four sessions were used for accommodation.
Statistical analysis.
The analysis of variance (ANOVA) for repeated measures was used to
compare means, including the two groups as a between-subject factor.
Between-group initial values were compared by using a simple factorial
ANOVA. Statistical significance was set at
P < 0.05.
RESULTS
Where appropriate, the results are presented for the entire exercise group (EXER) as well as the subgroup (EX12) in which ADMR was measured.
Changes in physical characteristics. As shown in Table 2, after 18 wk both the EXER and Con had lost a comparable amount of fat mass (2.0 ± 1.8 kg; P < 0.001 and 1.4 ± 1.0 kg; P < 0.05, respectively) whereas fat-free mass increased only in EXER [2.1 ± 1.2 kg, P < 0.001, and 0.4 ± 1.8 kg, not significant (NS), respectively]. The combined changes in fat mass and fat-free mass resulted in an unaltered body mass [0.1 ± 1.5 kg (NS) and1.0 ± 1.2 kg (NS), respectively] but a similar decrease in percentage fat of 2.6 ± 2.0%;
P < 0.001 and 1.6 ± 1.5%; P < 0.05, respectively. In
EX12, body mass increased at T8
with 1.1 ± 1.5 kg (P < 0.05)
returning to preintervention values at
T18.
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2.6 ± 1.8, 3.9 ± 2.6, 4.6 ± 2.0 MJ/day, P < 0.001). This underreporting in absolute and relative terms (21 ± 14, 28 ± 18, 34 ± 14%) increased during
the study but was only significantly different between
T0 and
T18
(P < 0.01).
Workout at the fitness club. Average training compliance, including the six training sessions in weeks 1-3, was 95 ± 7%. The average number and duration of the workouts did not differ between T8 and T18 (1.9 ± 0.5 vs. 1.9 ± 0.5 sessions/wk, 71 ± 11 vs. 73 ± 13 min/workout). To check whether the EE/HR-relationship was affected by the training program, both pre- and postintervention equations were used to predict EEex at T8 and T18. Preintervention equations always resulted in a significantly lower EEex compared with postintervention equations, revealing a change in the exercise EE/HR relationship (at T8, 28.7 ± 5.6 vs. 32.7 ± 6.5 kJ/min; at T18, 26.7 ± 5.1 vs. 30.8 ± 5.4 kJ/min, P < 0.001). Hence, the preintervention equations were used to estimate EEex at T8, whereas postintervention equations were applied at T18. Average EEex increased significantly in EXER (28.7 ± 5.6 vs. 30.8 ± 5.4 kJ/min equal to 2,014 ± 446 vs. 2,271 ± 607 kJ/session, P < 0.05) but did not change in EX12 (29.8 ± 4.9 vs. 30.9 ± 6.0 kJ/min equal to 1,952 ± 348 vs. 2,151 ± 616 kJ/session). Net daily energy cost of the workouts (EEex
SMR, MJ/day) was not different between
T8 and
T18 in EXER (0.47 ± 0.20 vs.
0.50 ± 0.18 MJ/day) or EX12 (0.43 ± 0.20 vs. 0.48 ± 0.15 MJ/day). At T8 and
T18, only 38 and 41% of the
increase in ADMR could be attributed to the net energy cost of the
workouts performed at the fitness club.
The components of ADMR.
The following components of ADMR (see Fig.
3) were calculated: 24-h SMR (MJ/day),
diet-induced thermogenesis (DIT), and the energy cost of physical
activity (ADMR SMR DIT, MJ/day). The latter was
subsequently split up into the net cost of weight training and the cost
of nontraining physical activity. The DIT was assumed be 10% of the
measured ADMR. The energy cost of physical activity increased
significantly (P < 0.01) at
T8 but showed no further increase
at T18 (4.4 ± 0.9, 5.3 ± 0.9, 5.5 ± 1.6 MJ/day, respectively). However, the energy cost of
the nontraining physical activity (ADMR DIT SMR net EEex) did not change (4.4 ± 0.9, 4.9 ± 0.8, and 5.0 ± 1.6 MJ/day, respectively)
SMR) and energy expenditure for nontraining physical activity
(EEact)
(EEact = ADMR SMR DIT EEex), before and
after 8 and 18 wk of weight training.
* P < 0.05;
** P < 0.001 compared with connected bars.
Nontraining physical activity. As depicted in Fig. 4, physical activity as measured with the triaxial accelerometer did not change between T0, T8, and T18 in the exercise group (967 ± 158, 1,052 ± 214, 1,068 ± 249 counts/min) or the control group (1,119 ± 222, 1,137 ± 311 counts/min). Also, activity time did not change in both groups (EXER: 14.0 ± 1.7, 12.9 ± 2.5, 13.3 ± 2.3 h/day; Con: 14.3 ± 1.1, 12.7 ± 2.3 h/day). Average weekly variation in accelerometer output (n = 26), expressed as coefficient of variation (individual SD/x * 100), was 14 ± 8%. The daily coefficient of variation decreased gradually during the study and was significantly different between T0 and T18 (28.0 ± 9.9 vs. 20.5 ± 10.3%, P < 0.01).
DISCUSSION
0.1 kg/wk; Ref. 38), the change in fat mass in the
control group is an indication that seasonal changes in food habits or
spontaneous activity, although not detected by the accelerometer
output, could have played a role. The increase in fat-free mass was
most likely due to the exercise, because no change was found in the
controls. Assuming an energy equivalent of 38.9 and 6.3 MJ/kg fat mass
and fat-free mass, respectively (34), it can be calculated that the
subjects in both the EXER and Con groups were in a small negative
energy balance over the total period of 18 wk (0.5 and 0.4 MJ/day,
respectively).
ADMR.
This study examined the effect of an 18-wk weight-training program on
average daily energy expenditure and found a 1.1 MJ/day (9.3%) and 1.2 MJ/day (9.5%) increase after 8 and 18 wk, respectively. To our
knowledge, only four other studies used doubly labeled water to measure
the effect of an exercise program on ADMR. The interventions, however,
consisted of endurance training instead of weight training. Meijer et
al. (19) studied the effect of 20-wk endurance training in a group of
32 untrained subjects preparing to run a half marathon. ADMR was
determined in a subgroup of four men and three women. After 8 and 20 wk, ADMR was significantly increased with ~1.6 and 2.2 MJ/day (15 and
20%, respectively). To examine the effect over a prolonged period,
Westerterp et al. (35) measured ADMR in a subgroup of 13 subjects who
continued the previously mentioned training program for another 20 wk
and found no further increase in ADMR after 40 wk (2.3 MJ/day, 21%). Bingham et al. (4) studied a group of three men and two women who
followed a 9-wk running program (60 min, 5 day/wk) and found an average
increase of 2.8 MJ/day (28%). Blaak et al. (5) found an average
increase of 1.3 MJ/day (21%) in a group of 10 obese boys, ages
10-11 yr, after a cycling program (4 wk; 5 sessions/wk, 45 min/session, 50-60% maximal O2 consumption). In
contrast with the above-mentioned studies that found an
exercise-induced increase in ADMR, a study by Goran and Poehlman (14)
revealed no change in ADMR in a group of 11 elderly subjects who
followed an 8-wk cycling program.
Campbell et al. (11) examined the effect of weight training on ADMR,
but this study did not use the doubly labeled water technique. The
required energy intake to maintain body weight was used to estimate
ADMR in a study on the effect of a 12-wk weight-training program in
older adults (n = 12). An average 1.1 MJ/day (
15%) increase in daily energy intake was required to compensate the cost of weight-training exercise and the increase in
resting metabolic rate.
Because the above-mentioned interventions not only differed in the mode
of activity but also varied widely in intensity, duration, and
frequency of the training program, additional information on the
average net energy cost of the extra exercise and changes in the
remaining components of ADMR is required to compare and interpret the
effect of the various training programs on ADMR.
Net energy cost of the training intervention.
Because the net energy cost of a training program depends on the
intensity, duration, and frequency of the training sessions, it is
evident that studies can differ considerably in exercise-induced changes in ADMR. After 18 wk of weight training, the net
EEex was 0.48 MJ/day. The net
EEex in the study of Campbell et
al. (11) as well as the increase in ADMR were similar with the present study (0.42 and 1.1 MJ/day, respectively). Although the energy cost of
the training program in the studies of Blaak et al. (5) and Goran and
Poehlman (14) was ~50% higher (± 0.63 MJ/day) compared with the
present study, ADMR only increased in the study of Blaak et al. (5)
that used a group of young boys (1.3 MJ/day). In the elderly group,
ADMR did not change. This was explained by a 60% reduction in
spontaneous and/or voluntary physical activity. The net
EEex of the added exercise in the
study of Meijer et al. (19) was almost twice as high. The increase in
ADMR in the latter study was also almost twice the increase of the
present study (0.87 and 2.2 MJ/day, respectively). In the study by
Bingham et al. (4), no values on net
EEex were presented. From
calculations based on the average time (37 min), speed (11.5 km/h), and
body mass (63 kg), net EEex was
estimated to be 1.9 MJ/day (1). This higher
EEex also induced a larger
increase in ADMR (2.8 MJ/day).
In general, interventions with higher
EEex showed a higher increase in
ADMR. The increase in ADMR, however, always exceeded the energy
expenditure due to exercise. As shown in the study by Goran and
Poehlman (14), exercise could also affect the remaining components of
ADMR (i.e., spontaneous activity). Therefore, other components of ADMR
like SMR and nontraining (spontaneous) physical activity should always
be included in the design.
SMR.
Studies on the effect of exercise on SMR are somewhat controversial
(22). The unchanged SMR in the entire exercise group (n = 18) over a period of 18 wk was in
concordance with a previous weight-training intervention that did not
reveal a change in SMR after 12 wk of weight training (33). In EX12,
however, SMR showed a small increase at
T8 (0.25 ± 0.27 kJ/min, 5%)
but returned to preintervention values after 18 wk of training. Body
mass and fat-free mass, two important determinants of SMR, also
increased at T8. The change in
SMR, however, could not be explained by the increase in body mass or
fat-free mass at T8, probably due
the small changes in SMR and the anthropometric data.
Two of the previously mentioned studies (11, 14), both using elderly
subjects, reported a change in resting metabolic rate, whereas the
present study and the three remaining studies (4, 5, 19) showed no
change in SMR. Besides differences in average age, intervention,
changes in body mass, and level of training, the protocol used to
determine resting energy expenditure (SMR vs. resting metabolic rate)
might affect the outcome of the study. In some studies that measured
both SMR and resting metabolic rate after a weight-training
intervention (31) or a bout of endurance exercise (3), resting energy
expenditure increased, whereas sleeping energy expenditure did not
change. On the other hand, Bingham et al. (4) measured also both
parameters but found no change in resting metabolic rate or SMR.
Differences in training intervention (type of exercise) are not likely
to explain the inconsistency in exercise-induced changes in SMR.
Cross-sectional (30) as well as intervention studies (10) that compared
the effect of either high-intensity resistance or endurance training
revealed no exercise-specific change in resting metabolic rate.
Although some studies reveal a substantial training-induced increase in
resting metabolic rate (up to 10%), the increasing effect on ADMR
would be at most 5%.
Dietary intake.
A 3-day food record was considered to provide information on the food
quotient (FQ). The FQ was supposed to reflect the respiratory exchange
ratio required to calculate oxygen consumption during the doubly
labeled water period. Unfortunately, the results of the 3-day food
record revealed a substantial, and gradually increasing, underreporting. Although underreporting is also found in other studies
(25, 29, 36), the increasing magnitude of the underreporting made the
data unusable for the calculation of DIT and FQ. Because the changes in
body composition revealed only a small negative energy balance, DIT was
set at 10% of the measured ADMR (26). An average FQ of 0.85 was
assumed (6, 35) during the three measurement periods, because changes
in FQ will be relatively small and therefore will not greatly affect
the calculation of ADMR (39).
Energy cost of physical activity.
The net energy cost (ADMR SMR DIT) of physical
activity increased significantly by 0.9 and 1.1 MJ/day,
equivalent to 20 and 25%. Like other studies that revealed an increase
in ADMR (5, 11, 19), the net EEex
explains only partly (±40-50%) the increase in the net energy
cost of physical activity. In the present study and the study of Meijer
et al. (19), the remaining discrepancy could not be attributed to a
change in nontraining activity as recorded by an accelerometer. The
unchanged accelerometer output in the present study is in line with the
unchanged net energy cost of physical activity at
T8 and
T18. Blaak et al. (5) also found
no change in spontaneous activity measured by HR recording. As
indicated by the large weekly and daily coefficients of variation, it
is possible, although not likely, that the accelerometer method is not
sensible enough to measure small changes in physical activity. The
decreased daily variation in physical activity at the end of the study
was probably due to seasonal and/or weather changes (study
started in winter and ended in summer).
Because the energy cost of physical activity is not directly measured
but the residue of subtracting SMR, DIT, and net
EEex from ADMR, the discrepancy
could also be due to measurement errors in one of these components.
Part of the discrepancy could be attributed to a slight underestimation
of the energy cost of EEex because it does not include the residual energy expenditure associated with
postexercise recovery or a short-term effect on SMR. However, the
magnitude of postexercise recovery is assumed to be small after both
endurance exercise [38-125 kJ per exercise bout (24)] as well as weight training [±80 kJ (20)]. This small
contribution (76-250 kJ/wk) of postexercise recovery to the net
energy cost of exercise can hardly explain the remaining part of the
increased energy expenditure (a total of 4.4 MJ/wk). On the other hand, a small underestimation of SMR due to a short-term effect (SMR was
measured >30 h postexercise), could largely explain the unaccountable increase in energy cost of physical activity and the unchanged physical
activity. Although the effect of weight training on the separate
components of ADMR remains partially unclear, for the determination of
the efficacy of weight training in weight-control programs, the
absolute change in ADMR is the main value of interest.
In summary, the unchanged accelerometer output revealed that there was
no change in (nontraining) physical activity in both the exercise as
well as the control group. Hence, we assume that the change in daily
energy expenditure could be attributed to the weight-training program.
Therefore, a weight-training program that consisted of 2 sessions/wk
resulted in an average increase in daily energy expenditure of ~10%
after 8 wk, with no further increase after 18 wk. Only 40% of the
increase could be attributed to the net energy cost of the program. The
unexplained part of the increase in ADMR could be due to an
underestimation of the net EEex or
measurement errors in other components of ADMR, although the results on
SMR revealed no significant change. Weight training did not change body
mass, and there was a 2.1 kg increase in fat-free mass in the exercise
group. The exercise group as well as the control group showed a
decrease in fat mass. From the change in daily energy expenditure, it
can be concluded that weight training, although of modest energy cost
compared with endurance training, induces a significant increase in
ADMR and, therefore, can be applied as an effective and safe adjunct to
exercise based weight-control programs.
ACKNOWLEDGEMENTS
This study was supported by a research grant from the Netherlands Heart Foundation.
FOOTNOTES
Address for reprint requests: L. M. L. A. Van Etten, Dept. of Human Biology, Univ. of Limburg, PO Box 616, 6200 MD Maastricht, The Netherlands.
Received 26 March 1996; accepted in final form 5 September 1996.
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