Articles in PresS. J Appl Physiol (November 14, 2013). doi:10.1152/japplphysiol.00956.2013
1
Determinants of resting lipid oxidation in response to a prior bout of endurance exercise
2 3
By:
Gregory C. Henderson1,2 and Brandon L. Alderman1
4 5 6
1
Department of Exercise Science and Sport Studies, Rutgers University, New Brunswick, NJ 08901
2
Rutgers Center for Lipid Research, Rutgers University, New Brunswick, NJ 08901
7 8 9 10 11 12
AUTHOR CONTRIBUTIONS G.C.H. conceived of and designed the experiment, performed calculations, interpreted findings, and wrote the manuscript. B.L.A. designed the experiment, performed calculations, analyzed results, interpreted findings, and wrote the manuscript.
13
14 15
Corresponding author:
16
Gregory C. Henderson, Ph.D.
17
Rutgers University
18
70 Lipman Drive
19
Loree Building
20
New Brunswick, NJ 08901
21
Email: [email protected]
22
Phone: 732-932-7564
23
Fax: 732-932-9151
24 25 26
Running Title: Postexercise lipid oxidation
27 28 1
Copyright © 2013 by the American Physiological Society.
29
ABSTRACT
30
A single bout of exercise can alter subsequent resting metabolism for many hours and into the next day.
31
However, differences between men and women, effects of nutritional state, and relative effects of resting
32
metabolic rate (RMR) and respiratory exchange ratio (RER) in controlling the increase in lipid oxidation
33
(Lox) after exercise are not yet clear. Effects of aerobic capacity (VO2peak) and exercise bout
34
parameters (intensity and volume) also remain to be clearly elucidated as does the time course of
35
changes after exercise. We performed a meta-analysis to assess these potential moderators of the impact
36
of endurance exercise (effect sizes, ESs) on subsequent Lox at rest (ES=0.91; 95% CI: 0.69–1.12) on the
37
day of exercise (ES=1.22; 95% CI: 0.89–1.55) and on the following day (ES=0.60; 95% CI: 0.35–0.85).
38
ES for the exercise-related increase in resting Lox was significantly greater in men than women in the
39
postabsorptive state but similar in the postprandial state. The ES for depression of RER after exercise
40
was similar between men and women, while the ES for RMR in the postabsorptive state tended to be
41
higher in men than women. Finally, VO2peak and energy expenditure of exercise (EEE), but not
42
intensity, were predictive of postexercise Lox. The findings indicate importance of EEE and fitness for
43
ability to achieve robust enhancement of Lox after exercise. The results additionally indicate a gender
44
difference in postexercise Lox that is dependent on nutritional state, as the ES for Lox was lower in
45
women only in the postabsorptive state.
46 47 48 49
Key words: Meta-analysis, fuel metabolism, substrate oxidation, sex, sex-based differences
50
2
51
INTRODUCTION
52
Maintenance of body composition over time, or prevention of fat gain, requires that individuals
53
oxidize at least as much fat as they consume. Thus, not surprisingly, a reduced relative contribution of
54
lipid oxidation (Lox) to energy metabolism is associated with increased risk of gaining weight over time
55
(59, 70). Along with the contribution of a positive energy balance, poor ability to oxidize lipids in
56
certain individuals could contribute to their propensity toward gain and retention of body fat. A
57
physically active lifestyle prevents age-related weight gain over time (33), and this effect could be
58
related to energy expenditure and to energy substrate selection.
59
Even in individuals who successfully meet current physical activity guidelines for total exercise
60
volume (33) and for whom exercise energy expenditure (EEE) thus significantly adds to total energy
61
expenditure (TEE), weight management through exercise alone can still be difficult. The non-substantial
62
impact of exercise on body weight may be because most of the TEE is still from the resting metabolic
63
rate (RMR); in individuals characterized as active, likely RMR is in the vicinity of 75% of TEE (33).
64
EEE remains a minor contributor to TEE, and so in attempts to monitor and manipulate energy substrate
65
metabolism, resting metabolism is a logical and important focus. Although energy substrate metabolism
66
is altered during exercise, the majority of the 24-hour period in individuals in Western society is spent at
67
rest. Exercise, however, can be a strategy to alter resting metabolism, as the effects of each individual
68
exercise bout on energy substrate utilization continue many hours into subsequent rest, with Lox
69
remaining elevated above that observed under sedentary conditions for many hours (25). That is to say,
70
resting lipid metabolism is altered by a recent exercise bout.
71
Previous work has modeled the relationship between exercise intensity and fuel partitioning
72
during exercise (7, 9, 10), but to our knowledge no model exists for the postexercise recovery period.
73
Extensive work has led to the conclusion that women rely upon lipid as a fuel to a relatively greater 3
74
extent than do men during an endurance exercise bout (13, 15, 16, 21, 22, 25, 26, 30, 56, 60, 62), and
75
this conclusion was reinforced by a meta-analysis on the topic (61). Additionally, some initial
76
observations indicate that there may be differences between men and women during the postexercise
77
recovery period (25, 30). As resting metabolism makes up the vast majority of TEE in most people, even
78
in those engaged in formal exercise training programs, we undertook an attempt to further explore the
79
determinants of postexercise Lox, including the effects of gender, physical fitness, nutritional state,
80
timing of assessment (immediately after, next day), exercise intensity, and EEE. Additionally, we
81
explored the components of the enhancement of Lox after exercise which can include an increase in
82
RMR and a relative shift away from carbohydrate and toward lipid for energy (i.e., reduced respiratory
83
exchange ratio, RER).
84
A variety of study designs have been used to investigate the effects of exercise on subsequent
85
substrate oxidation at rest. Investigations have been performed on both men and women, employing a
86
variety of exercise volumes and intensities, and subjects of a wide variety of fitness levels have been
87
studied after exercise in the postabsorptive (fasted) and postprandial (fed) states. Each individual study
88
may have some degree of statistical power limitation, and each pool of study participants represent only
89
a subset of variations in phenotype within society. Based on the limited statistical power inherent to any
90
one individual study, the ability to study important moderators of Lox or substrate utilization during the
91
postexercise window is limited. Therefore, we set out to harness these variabilities in study designs and
92
to provide a statistically powerful test beyond that of any individual study by employing meta-analytic
93
and meta-regression approaches to identify the determinants of postexercise Lox.
94 95 96
METHODS 4
97
Study aim. We performed a systematic quantitative analysis of published results on energy substrate
98
utilization data derived from pulmonary gas exchange. Specifically, we explored the impact of each
99
single endurance exercise bout in humans, and the moderating influence of gender, physical fitness,
100
nutritional state, timing of assessment (immediately after, next day), exercise intensity, and EEE.
101 102
Identification of data for the analysis. Relevant papers were identified by searching the PubMed
103
database using various combinations of the following terms: prior exercise, postexercise, post-exercise,
104
lipid oxidation, fat oxidation, substrate oxidation, substrate utilization, RER, and RQ. Additional papers
105
that might have been relevant for inclusion were identified from reference lists from all articles
106
identified from the PubMed search. Studies in which endurance exercise was performed at a steady
107
intensity were included (i.e., not interval exercise or resistance exercise). Because energy substrate
108
metabolism changes with the time of day and time elapsed since the prior meal (25, 30, 53), we only
109
included studies that utilized a time-matched sedentary control condition performed on a separate
110
occasion from that of exercise in the same subjects (i.e., cross-over design). In studies where
111
postexercise nutrition was provided, only those that fed the same energy and macronutrient content
112
under both exercise and sedentary conditions were included. There were not a sufficient number of
113
studies to allow for a separate meta-analysis of those in which energy intake was different between
114
exercise and sedentary conditions, but these individual studies are discussed separately from the main
115
findings in this report. The minimum duration of postexercise recovery was chosen to be two hours in
116
order to observe persistent changes in resting metabolism. Based upon knowledge that men and women
117
can respond differently to exercise (25), and to address a primary aim of investigating gender differences
118
in substrate oxidation, we excluded any papers that pooled men and women into one single group. In
119
the one study in which women were studied in both the follicular and luteal phases of the menstrual 5
120
cycle (20), data from the follicular phase were used in the analysis because this phase is often chosen
121
when standardizing cycle phase in exercise and substrate utilization research. Mean and variance values
122
for postexercise Lox and for Lox in sedentary control trials were obtained from published papers. When
123
data were displayed graphically but not numerically, authors were contacted to request the mean and
124
variance values, and these data were included in the analysis when authors agreed to provide the results.
125
Mean and variance for RMR and RER, because they are the components in derivation of Lox values,
126
were also obtained as available. Data were categorized as those collected on the day of exercise (on the
127
same calendar day), or on the day after exercise (after an overnight period had passed after exercise).
128
Data were also categorized into those collected in the postprandial (a meal taken immediately before
129
indirect calorimetry assessments) or the postabsorptive state.
130 131
Calculations. Exercise duration and relative exercise intensity (% VO2peak) were recorded for each
132
study, as well as energy expenditure of exercise (EEE). When EEE was not reported, it was estimated
133
from published oxygen consumption (VO2) rate and exercise duration, estimating 5 kcal energy per liter
134
of VO2 (8). If exercise VO2 was not reported, from the published mechanical power output (watts), the
135
energy requirement of exercise was estimated from a published table to convert power output to
136
metabolic equivalents (METS) (1). As needed, percentage of energy from fat and carbohydrate
137
(assuming negligible protein oxidation) was calculated from published equations (43). When not
138
provided, RMR was calculated using these percentages of fat and carbohydrate, published VO2, and the
139
assumption of 5.05 kcal/LO2 for carbohydrate and 4.7 kcal/LO2 for fat (8). When standard error (SE)
140
but not standard deviation (SD) were available, SD was calculated by multiplying SE by the square root
141
of the reported sample size. Effect sizes (ESs) for postexercise Lox were calculated as followed:
142
[(postexercise mean) – (sedentary mean)] / (sedentary SD)]. 6
143 144 145
Statistical analysis. Descriptive statistics were generated using SPSS v. 19 and are expressed as mean ± SE. ESs
146
were calculated and meta-analyses were conducted using Comprehensive Meta-Analysis v. 2.0. Cohen’s
147
d was used as the measure of the overall effect and evidence suggests that Type I error rates for tests of
148
heterogeneity are well controlled using this metric (32). Given that sample size impacts the precision of
149
the ES estimate, each ES was weighted by the inverse of its variance prior to conducting further
150
analyses. A random effects model was used to pool effects and compare results across studies to address
151
potential concerns regarding the lack of independence of data points when multiple effects are derived
152
from a single study (41). Overall ESs for Lox, RER, and for RMR were conducted independently to
153
examine subject and exercise characteristics on these outcomes.
154
Heterogeneity in meta-analysis refers to the variation in outcomes between studies included in
155
the review. The extent of heterogeneity partly determines the difficulty in drawing overall conclusions
156
from the literature. Understanding the cause of heterogeneity, in part through the use of moderating
157
variable analyses, can increase both the scientific and clinical value of the meta-analysis (64). Detecting
158
heterogeneity among ESs supports the necessity of follow-up moderating analyses. Heterogeneity was
159
examined using Cochran’s Q and I2 statistics. The traditional approach for assessing heterogeneity in
160
meta-analyses has been through the use of Cochran’s Q statistic (32, 55). Cochran’s Q is computed by
161
summing the squared deviation of each study ES from the overall ES estimate, weighting the
162
contribution of each ES by the inverse of its variance. The alpha value for statistical significance for Q
163
was set at P ≤ 0.10 because this statistic tends to suffer from low power (24, 34). More recently
164
Cochran's Q has been shown to be heavily influenced by the number of studies in a review such that it
165
has low power with a small number of studies and excessive power with a large number of studies (28). 7
166
Thus, the Q index provides a test of the presence of heterogeneity among ESs along with a
167
corresponding P statistic, but not the exact extent of heterogeneity within the meta-analysis (28). The I2
168
statistic, which expresses the ratio of the observed variance between outcomes to the total observed
169
variance in ESs (32), has been recommended along with Q to describe the extent of between-studies
170
variability, and was calculated as (Q - df)/Q x 100, where df equals the degrees of freedom. The I2
171
statistic was interpreted as small (25% to 0.10. Women
217
in the postabsorptive state exhibited an ES of 0.50±0.20 while in the postprandial state the ES for Lox
218
was 1.04±.36, a difference that was not statistically significant, Q(1)=1.8, P = 0.18. Additionally, a
219
general time course was observed in which a greater ES for Lox occurred immediately following
220
exercise (1.22±.17) when compared to that observed the day following exercise (0.60±0.13), Q(1)=8.51,
221
P < 0.05.
222
Respiratory exchange ratio. The overall ES for RER was 0.82±0.10, which was significantly
223
different from zero. The Q and I2 statistics revealed a lack of heterogeneity across effects, Q(27)=23.96,
224
I2=0, P > 0.10. Despite this lack of heterogeneity among the ESs, we examined potential moderators
225
based on a priori study hypotheses and to determine the relative role of RER in postexercise substrate
226
oxidation. No significant difference in RER was observed between men (ES = 0.83±0.12) and women
227
(ES = 0.80±0.16). There was also no significant difference in ESs as a function of
228
postprandial/postabsorptive state of the sample. RER effects for men did not differ from women in either
229
the postabsorptive (ES = 0.84 ±.13 vs 0.82±0.21) or postprandial (ES = 0.81±0.43 vs 0.85±0.35) state,
230
respectively. Notably, postprandial state RER data were only attained for men (20, 66) and for women
231
(14, 20) in two studies each, whereas a far more extensive RER data set was analyzed for the
232
postabsorptive state. A trend emerged indicating larger RER effects in the immediate recovery period
10
233
following exercise (ES = 0.99±0.15) relative to those observed the next day (ES = 0.65±0.15),
234
Q(1)=2.54, P = 0.11. Resting metabolic rate. ESs for metabolic rate were derived from 12 studies. The overall
235 236
observed ES was 0.26±0.10, which was significantly different from zero. The Q and I2 statistics revealed
237
a lack of heterogeneity across effects, Q(22)=12.13, I2=0, P > 0.10. However, similar to RER, follow-up
238
tests were conducted to assess the relative role of RMR in postexercise substrate utilization. Women had
239
less accentuation of metabolic rate postexercise (ES = 0.06±0.16) relative to men (ES = 0.38±0.13), and
240
this trend approached but did not reach statistical significance, Q(1)=2.51, P = 0.11. In terms of the
241
effects of feeding, overall average ES for the postabsorptive state was 0.29±0.11 while in the
242
postprandial state the impact of exercise on RMR was smaller with an ES of 0.05±0.26, Q(1)=0.73, P >
243
0.10. In the postabsorptive state, men exhibited a significantly larger ES for RMR (ES = 0.51±0.15) than
244
women (ES = 0.05±0.17), Q(1)=3.94, P < 0.10. No significant sex difference was found in the
245
postprandial state, Q(1)=0.02, P > 0.10. However, only three effects emerged from samples in the
246
postprandial state with one of the observations taken immediately after exercise in overweight women
247
(14) while the other two were assessed on the following day in men (23, 66). When analyzing RMR
248
data with postprandial and postabsorptive states pooled together immediately postexercise, men
249
expressed a larger effect for metabolic rate (0.59±0.19) than women (0.11±0.19), Q(1)=3.0, P < 0.10.
250
This effect was not statistically different the following day, although the trend remained with men
251
(0.29±0.20) retaining higher rates than women (-0.07±0.29), Q(1)=1.0, P > 0.10. No statistically
252
significant effects were observed for exercise on RMR during the immediate postexercise recovery
253
period (ES = 0.39±0.15) relative to values measured the following day (ES = 0.17±0.16), Q(1)=0.96, P
254
> 0.10.
255
Regression Analyses 11
256
Separate regression analyses were conducted using Lox ESs as the dependent variable with
257
exercise intensity (% VO2peak) and EEE (kcal) as predictors in meta-regression analyses to determine
258
the impact of these exercise characteristics on postexercise Lox. No evidence of ES moderation was
259
found for exercise intensity (QR= 0.79; P>0.05; R2 = 0.05; QE = 33.47; P>0.05). However, the overall
260
meta-regression model was found to be significant for EEE (QR= 8.89; P0.05). Thus, overall EEE (β = 0.42; z = 2.98; P < 0.01) but not exercise intensity (β = 0.22; z = 0.89;
262
P>0.05), accounted for significant variation in the overall effect of endurance exercise on subsequent
263
Lox. We also ran these meta-regression analyses by gender to determine whether this moderation of
264
EEE on postexercise Lox exists for both men and women. EEE was a significant predictor of
265
postexercise Lox for men (QR= 6.20; P0.05) but not for women (QR=
266
0.32; P>0.05; R2 = 0.001; QE = 16.12; P>0.05). Similar to the overall model, exercise intensity did not
267
significantly moderate postexercise Lox in men (QR= 1.51; P>0.05; R2 = 0.14; QE = 19.82; P>0.05) or
268
women (QR= 0.01; P>0.05; R2 = 0.01; QE = 11.38; P>0.05). However, these gender-specific analyses
269
were underpowered and thus results should be interpreted with caution.
270
Separate meta-regression analyses were conducted using Lox ESs as the dependent variable with
271
VO2peak as a predictor to determine whether postexercise Lox is greater among more aerobically fit
272
subjects. For total VO2peak, expressed in L/min, the test for linear regression with Lox was significant,
273
QR= 3.86; P
1
Determinants of resting lipid oxidation in response to a prior bout of endurance exercise
2 3
By:
Gregory C. Henderson1,2 and Brandon L. Alderman1
4 5 6
1
Department of Exercise Science and Sport Studies, Rutgers University, New Brunswick, NJ 08901
2
Rutgers Center for Lipid Research, Rutgers University, New Brunswick, NJ 08901
7 8 9 10 11 12
AUTHOR CONTRIBUTIONS G.C.H. conceived of and designed the experiment, performed calculations, interpreted findings, and wrote the manuscript. B.L.A. designed the experiment, performed calculations, analyzed results, interpreted findings, and wrote the manuscript.
13
14 15
Corresponding author:
16
Gregory C. Henderson, Ph.D.
17
Rutgers University
18
70 Lipman Drive
19
Loree Building
20
New Brunswick, NJ 08901
21
Email: [email protected]
22
Phone: 732-932-7564
23
Fax: 732-932-9151
24 25 26
Running Title: Postexercise lipid oxidation
27 28 1
Copyright © 2013 by the American Physiological Society.
29
ABSTRACT
30
A single bout of exercise can alter subsequent resting metabolism for many hours and into the next day.
31
However, differences between men and women, effects of nutritional state, and relative effects of resting
32
metabolic rate (RMR) and respiratory exchange ratio (RER) in controlling the increase in lipid oxidation
33
(Lox) after exercise are not yet clear. Effects of aerobic capacity (VO2peak) and exercise bout
34
parameters (intensity and volume) also remain to be clearly elucidated as does the time course of
35
changes after exercise. We performed a meta-analysis to assess these potential moderators of the impact
36
of endurance exercise (effect sizes, ESs) on subsequent Lox at rest (ES=0.91; 95% CI: 0.69–1.12) on the
37
day of exercise (ES=1.22; 95% CI: 0.89–1.55) and on the following day (ES=0.60; 95% CI: 0.35–0.85).
38
ES for the exercise-related increase in resting Lox was significantly greater in men than women in the
39
postabsorptive state but similar in the postprandial state. The ES for depression of RER after exercise
40
was similar between men and women, while the ES for RMR in the postabsorptive state tended to be
41
higher in men than women. Finally, VO2peak and energy expenditure of exercise (EEE), but not
42
intensity, were predictive of postexercise Lox. The findings indicate importance of EEE and fitness for
43
ability to achieve robust enhancement of Lox after exercise. The results additionally indicate a gender
44
difference in postexercise Lox that is dependent on nutritional state, as the ES for Lox was lower in
45
women only in the postabsorptive state.
46 47 48 49
Key words: Meta-analysis, fuel metabolism, substrate oxidation, sex, sex-based differences
50
2
51
INTRODUCTION
52
Maintenance of body composition over time, or prevention of fat gain, requires that individuals
53
oxidize at least as much fat as they consume. Thus, not surprisingly, a reduced relative contribution of
54
lipid oxidation (Lox) to energy metabolism is associated with increased risk of gaining weight over time
55
(59, 70). Along with the contribution of a positive energy balance, poor ability to oxidize lipids in
56
certain individuals could contribute to their propensity toward gain and retention of body fat. A
57
physically active lifestyle prevents age-related weight gain over time (33), and this effect could be
58
related to energy expenditure and to energy substrate selection.
59
Even in individuals who successfully meet current physical activity guidelines for total exercise
60
volume (33) and for whom exercise energy expenditure (EEE) thus significantly adds to total energy
61
expenditure (TEE), weight management through exercise alone can still be difficult. The non-substantial
62
impact of exercise on body weight may be because most of the TEE is still from the resting metabolic
63
rate (RMR); in individuals characterized as active, likely RMR is in the vicinity of 75% of TEE (33).
64
EEE remains a minor contributor to TEE, and so in attempts to monitor and manipulate energy substrate
65
metabolism, resting metabolism is a logical and important focus. Although energy substrate metabolism
66
is altered during exercise, the majority of the 24-hour period in individuals in Western society is spent at
67
rest. Exercise, however, can be a strategy to alter resting metabolism, as the effects of each individual
68
exercise bout on energy substrate utilization continue many hours into subsequent rest, with Lox
69
remaining elevated above that observed under sedentary conditions for many hours (25). That is to say,
70
resting lipid metabolism is altered by a recent exercise bout.
71
Previous work has modeled the relationship between exercise intensity and fuel partitioning
72
during exercise (7, 9, 10), but to our knowledge no model exists for the postexercise recovery period.
73
Extensive work has led to the conclusion that women rely upon lipid as a fuel to a relatively greater 3
74
extent than do men during an endurance exercise bout (13, 15, 16, 21, 22, 25, 26, 30, 56, 60, 62), and
75
this conclusion was reinforced by a meta-analysis on the topic (61). Additionally, some initial
76
observations indicate that there may be differences between men and women during the postexercise
77
recovery period (25, 30). As resting metabolism makes up the vast majority of TEE in most people, even
78
in those engaged in formal exercise training programs, we undertook an attempt to further explore the
79
determinants of postexercise Lox, including the effects of gender, physical fitness, nutritional state,
80
timing of assessment (immediately after, next day), exercise intensity, and EEE. Additionally, we
81
explored the components of the enhancement of Lox after exercise which can include an increase in
82
RMR and a relative shift away from carbohydrate and toward lipid for energy (i.e., reduced respiratory
83
exchange ratio, RER).
84
A variety of study designs have been used to investigate the effects of exercise on subsequent
85
substrate oxidation at rest. Investigations have been performed on both men and women, employing a
86
variety of exercise volumes and intensities, and subjects of a wide variety of fitness levels have been
87
studied after exercise in the postabsorptive (fasted) and postprandial (fed) states. Each individual study
88
may have some degree of statistical power limitation, and each pool of study participants represent only
89
a subset of variations in phenotype within society. Based on the limited statistical power inherent to any
90
one individual study, the ability to study important moderators of Lox or substrate utilization during the
91
postexercise window is limited. Therefore, we set out to harness these variabilities in study designs and
92
to provide a statistically powerful test beyond that of any individual study by employing meta-analytic
93
and meta-regression approaches to identify the determinants of postexercise Lox.
94 95 96
METHODS 4
97
Study aim. We performed a systematic quantitative analysis of published results on energy substrate
98
utilization data derived from pulmonary gas exchange. Specifically, we explored the impact of each
99
single endurance exercise bout in humans, and the moderating influence of gender, physical fitness,
100
nutritional state, timing of assessment (immediately after, next day), exercise intensity, and EEE.
101 102
Identification of data for the analysis. Relevant papers were identified by searching the PubMed
103
database using various combinations of the following terms: prior exercise, postexercise, post-exercise,
104
lipid oxidation, fat oxidation, substrate oxidation, substrate utilization, RER, and RQ. Additional papers
105
that might have been relevant for inclusion were identified from reference lists from all articles
106
identified from the PubMed search. Studies in which endurance exercise was performed at a steady
107
intensity were included (i.e., not interval exercise or resistance exercise). Because energy substrate
108
metabolism changes with the time of day and time elapsed since the prior meal (25, 30, 53), we only
109
included studies that utilized a time-matched sedentary control condition performed on a separate
110
occasion from that of exercise in the same subjects (i.e., cross-over design). In studies where
111
postexercise nutrition was provided, only those that fed the same energy and macronutrient content
112
under both exercise and sedentary conditions were included. There were not a sufficient number of
113
studies to allow for a separate meta-analysis of those in which energy intake was different between
114
exercise and sedentary conditions, but these individual studies are discussed separately from the main
115
findings in this report. The minimum duration of postexercise recovery was chosen to be two hours in
116
order to observe persistent changes in resting metabolism. Based upon knowledge that men and women
117
can respond differently to exercise (25), and to address a primary aim of investigating gender differences
118
in substrate oxidation, we excluded any papers that pooled men and women into one single group. In
119
the one study in which women were studied in both the follicular and luteal phases of the menstrual 5
120
cycle (20), data from the follicular phase were used in the analysis because this phase is often chosen
121
when standardizing cycle phase in exercise and substrate utilization research. Mean and variance values
122
for postexercise Lox and for Lox in sedentary control trials were obtained from published papers. When
123
data were displayed graphically but not numerically, authors were contacted to request the mean and
124
variance values, and these data were included in the analysis when authors agreed to provide the results.
125
Mean and variance for RMR and RER, because they are the components in derivation of Lox values,
126
were also obtained as available. Data were categorized as those collected on the day of exercise (on the
127
same calendar day), or on the day after exercise (after an overnight period had passed after exercise).
128
Data were also categorized into those collected in the postprandial (a meal taken immediately before
129
indirect calorimetry assessments) or the postabsorptive state.
130 131
Calculations. Exercise duration and relative exercise intensity (% VO2peak) were recorded for each
132
study, as well as energy expenditure of exercise (EEE). When EEE was not reported, it was estimated
133
from published oxygen consumption (VO2) rate and exercise duration, estimating 5 kcal energy per liter
134
of VO2 (8). If exercise VO2 was not reported, from the published mechanical power output (watts), the
135
energy requirement of exercise was estimated from a published table to convert power output to
136
metabolic equivalents (METS) (1). As needed, percentage of energy from fat and carbohydrate
137
(assuming negligible protein oxidation) was calculated from published equations (43). When not
138
provided, RMR was calculated using these percentages of fat and carbohydrate, published VO2, and the
139
assumption of 5.05 kcal/LO2 for carbohydrate and 4.7 kcal/LO2 for fat (8). When standard error (SE)
140
but not standard deviation (SD) were available, SD was calculated by multiplying SE by the square root
141
of the reported sample size. Effect sizes (ESs) for postexercise Lox were calculated as followed:
142
[(postexercise mean) – (sedentary mean)] / (sedentary SD)]. 6
143 144 145
Statistical analysis. Descriptive statistics were generated using SPSS v. 19 and are expressed as mean ± SE. ESs
146
were calculated and meta-analyses were conducted using Comprehensive Meta-Analysis v. 2.0. Cohen’s
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d was used as the measure of the overall effect and evidence suggests that Type I error rates for tests of
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heterogeneity are well controlled using this metric (32). Given that sample size impacts the precision of
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the ES estimate, each ES was weighted by the inverse of its variance prior to conducting further
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analyses. A random effects model was used to pool effects and compare results across studies to address
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potential concerns regarding the lack of independence of data points when multiple effects are derived
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from a single study (41). Overall ESs for Lox, RER, and for RMR were conducted independently to
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examine subject and exercise characteristics on these outcomes.
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Heterogeneity in meta-analysis refers to the variation in outcomes between studies included in
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the review. The extent of heterogeneity partly determines the difficulty in drawing overall conclusions
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from the literature. Understanding the cause of heterogeneity, in part through the use of moderating
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variable analyses, can increase both the scientific and clinical value of the meta-analysis (64). Detecting
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heterogeneity among ESs supports the necessity of follow-up moderating analyses. Heterogeneity was
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examined using Cochran’s Q and I2 statistics. The traditional approach for assessing heterogeneity in
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meta-analyses has been through the use of Cochran’s Q statistic (32, 55). Cochran’s Q is computed by
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summing the squared deviation of each study ES from the overall ES estimate, weighting the
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contribution of each ES by the inverse of its variance. The alpha value for statistical significance for Q
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was set at P ≤ 0.10 because this statistic tends to suffer from low power (24, 34). More recently
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Cochran's Q has been shown to be heavily influenced by the number of studies in a review such that it
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has low power with a small number of studies and excessive power with a large number of studies (28). 7
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Thus, the Q index provides a test of the presence of heterogeneity among ESs along with a
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corresponding P statistic, but not the exact extent of heterogeneity within the meta-analysis (28). The I2
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statistic, which expresses the ratio of the observed variance between outcomes to the total observed
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variance in ESs (32), has been recommended along with Q to describe the extent of between-studies
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variability, and was calculated as (Q - df)/Q x 100, where df equals the degrees of freedom. The I2
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statistic was interpreted as small (25% to 0.10. Women
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in the postabsorptive state exhibited an ES of 0.50±0.20 while in the postprandial state the ES for Lox
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was 1.04±.36, a difference that was not statistically significant, Q(1)=1.8, P = 0.18. Additionally, a
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general time course was observed in which a greater ES for Lox occurred immediately following
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exercise (1.22±.17) when compared to that observed the day following exercise (0.60±0.13), Q(1)=8.51,
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P < 0.05.
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Respiratory exchange ratio. The overall ES for RER was 0.82±0.10, which was significantly
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different from zero. The Q and I2 statistics revealed a lack of heterogeneity across effects, Q(27)=23.96,
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I2=0, P > 0.10. Despite this lack of heterogeneity among the ESs, we examined potential moderators
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based on a priori study hypotheses and to determine the relative role of RER in postexercise substrate
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oxidation. No significant difference in RER was observed between men (ES = 0.83±0.12) and women
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(ES = 0.80±0.16). There was also no significant difference in ESs as a function of
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postprandial/postabsorptive state of the sample. RER effects for men did not differ from women in either
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the postabsorptive (ES = 0.84 ±.13 vs 0.82±0.21) or postprandial (ES = 0.81±0.43 vs 0.85±0.35) state,
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respectively. Notably, postprandial state RER data were only attained for men (20, 66) and for women
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(14, 20) in two studies each, whereas a far more extensive RER data set was analyzed for the
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postabsorptive state. A trend emerged indicating larger RER effects in the immediate recovery period
10
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following exercise (ES = 0.99±0.15) relative to those observed the next day (ES = 0.65±0.15),
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Q(1)=2.54, P = 0.11. Resting metabolic rate. ESs for metabolic rate were derived from 12 studies. The overall
235 236
observed ES was 0.26±0.10, which was significantly different from zero. The Q and I2 statistics revealed
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a lack of heterogeneity across effects, Q(22)=12.13, I2=0, P > 0.10. However, similar to RER, follow-up
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tests were conducted to assess the relative role of RMR in postexercise substrate utilization. Women had
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less accentuation of metabolic rate postexercise (ES = 0.06±0.16) relative to men (ES = 0.38±0.13), and
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this trend approached but did not reach statistical significance, Q(1)=2.51, P = 0.11. In terms of the
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effects of feeding, overall average ES for the postabsorptive state was 0.29±0.11 while in the
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postprandial state the impact of exercise on RMR was smaller with an ES of 0.05±0.26, Q(1)=0.73, P >
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0.10. In the postabsorptive state, men exhibited a significantly larger ES for RMR (ES = 0.51±0.15) than
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women (ES = 0.05±0.17), Q(1)=3.94, P < 0.10. No significant sex difference was found in the
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postprandial state, Q(1)=0.02, P > 0.10. However, only three effects emerged from samples in the
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postprandial state with one of the observations taken immediately after exercise in overweight women
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(14) while the other two were assessed on the following day in men (23, 66). When analyzing RMR
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data with postprandial and postabsorptive states pooled together immediately postexercise, men
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expressed a larger effect for metabolic rate (0.59±0.19) than women (0.11±0.19), Q(1)=3.0, P < 0.10.
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This effect was not statistically different the following day, although the trend remained with men
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(0.29±0.20) retaining higher rates than women (-0.07±0.29), Q(1)=1.0, P > 0.10. No statistically
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significant effects were observed for exercise on RMR during the immediate postexercise recovery
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period (ES = 0.39±0.15) relative to values measured the following day (ES = 0.17±0.16), Q(1)=0.96, P
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> 0.10.
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Regression Analyses 11
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Separate regression analyses were conducted using Lox ESs as the dependent variable with
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exercise intensity (% VO2peak) and EEE (kcal) as predictors in meta-regression analyses to determine
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the impact of these exercise characteristics on postexercise Lox. No evidence of ES moderation was
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found for exercise intensity (QR= 0.79; P>0.05; R2 = 0.05; QE = 33.47; P>0.05). However, the overall
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meta-regression model was found to be significant for EEE (QR= 8.89; P0.05). Thus, overall EEE (β = 0.42; z = 2.98; P < 0.01) but not exercise intensity (β = 0.22; z = 0.89;
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P>0.05), accounted for significant variation in the overall effect of endurance exercise on subsequent
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Lox. We also ran these meta-regression analyses by gender to determine whether this moderation of
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EEE on postexercise Lox exists for both men and women. EEE was a significant predictor of
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postexercise Lox for men (QR= 6.20; P0.05) but not for women (QR=
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0.32; P>0.05; R2 = 0.001; QE = 16.12; P>0.05). Similar to the overall model, exercise intensity did not
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significantly moderate postexercise Lox in men (QR= 1.51; P>0.05; R2 = 0.14; QE = 19.82; P>0.05) or
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women (QR= 0.01; P>0.05; R2 = 0.01; QE = 11.38; P>0.05). However, these gender-specific analyses
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were underpowered and thus results should be interpreted with caution.
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Separate meta-regression analyses were conducted using Lox ESs as the dependent variable with
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VO2peak as a predictor to determine whether postexercise Lox is greater among more aerobically fit
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subjects. For total VO2peak, expressed in L/min, the test for linear regression with Lox was significant,
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QR= 3.86; P
