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Effect of Moderate- and High-Intensity Acute Exercise on Appetite in Obese Individuals

MARTINS, CATIA1,2; STENSVOLD, DORTHE3; FINLAYSON, GRAHAM4; HOLST, JENS5; WISLOFF, ULRIK3; KULSENG, BÅRD1,2; MORGAN, LINDA6; KING, NEIL A.7

Author Information
Medicine & Science in Sports & Exercise: January 2015 - Volume 47 - Issue 1 - p 40-48
doi: 10.1249/MSS.0000000000000372

Abstract

Obesity has become a global epidemic worldwide (33). This picture is undeniably linked to a decrease in physical activity (PA) levels over the past few decades, driven by dramatic changes in lifestyle (31). Although the role of PA in preventing weight gain is widely accepted (12), its effect on weight loss in the absence of energy restriction seems to be only modest (25). The ability of exercise to create a negative energy balance (EB) relies not only directly on its ability to increase energy expenditure (EE) but also indirectly on its potential to modulate energy intake (EI) and appetite (16,18). It has already been shown that the lower-than-expected weight loss experienced by some in response to an exercise intervention can be explained, at least partially, by a compensatory increase on EI (15).

Appetite is controlled by a series of complex processes in the brain and multiple hormones released peripherally (for a review, see Blundell (3). Determining how acute exercise affects appetite will provide a better understanding of its role on food intake and body weight homeostasis. Moreover, EI responses to acute exercise may also be influenced by changes in the hedonic system, with changes, for example, in food preferences (2).

The majority of the studies in normal-weight individuals indicate that acute exercise does not increase hunger or EI even at high intensities and that exercise is, therefore, able to induce a short-term negative EB (18). Acute exercise does not seem to influence total ghrelin (TG) (an orexigenic hormone) concentrations (18), and several studies have shown a significant suppression in the active component of the hormone, acylated ghrelin (AG), in response to high-intensity exercise (5,13,20) but not brisk walking (14). Moreover, exercise has been shown to increase the release of satiety hormones such as polypeptide YY (PYY) and glucagon-like peptide 1(GLP-1) in normal-weight individuals (19). Overall, the available evidence suggests that acute exercise does not induce physiological adaptations leading to increased EI in the short term (18).

However, few studies have been performed in obese individuals. Ueda et al. (29) reported no change in TG and a significant increase in PYY and GLP-1 plasma levels with moderate-intensity exercise (compared with rest) in normal-weight and obese men . Marzullo et al. (20) also showed no change in TG with maximal exercise in normal-weight and obese individuals despite a significant suppression in AG. Finally, Westerterp-Plantenga et al. (32) reported a significant suppression in hunger and EI after 2 h of cycling at 60% maximum workload in normal-weight and obese men.

Three recent reviews/meta-analyses, including obese individuals, have addressed the effect of exercise on appetite (8,23,24). They have concluded that there is little or no evidence that acute exercise affects energy or macronutrient intake, therefore being able to produce a short-term negative energy deficit (8,23). Moreover, acute exercise is associated with positive changes in appetite-related hormones, suppressing levels of AG while increasing levels of satiety peptides (PYY, GLP-1, and pancreatic polypeptide) (24).

High-intensity intermittent exercise, in which high-intensity work is interspersed with low-intensity work, has been shown to be a time-saving and sustainable exercise method even in untrained obese patients, with good results on body weight and composition, cardiovascular fitness, and insulin resistance (4). However, few studies have compared the effect of different intensities of acute bouts of exercise on appetite and they were performed in trained normal-weight men (6,7,28) and did not standardize the EE of the exercise bouts (6,28). In a recently published study, Sim et al. (26) reported a lower ad libitum EI after high-intensity intermittent cycling (HIIC) and very-HIIC compared with that in control and a significantly lower AG plasma levels after very-HIIC compared with those in other conditions in overweight inactive men. However, this study included men only, who were not obese, and exercise was performed while fasting. This has limitations concerning the applicability of the results to other populations and in conditions where exercise is performed in the postprandial state, which is the case in majority of the situations.

The primary objective of this study was to investigate the effects of acute isocaloric bouts of HIIC and moderate-intensity continuous cycling (MICC) (250 kcal) (and a short bout of HIIC (average, 9 min—125 kcal)), in comparison with a resting control condition, on the postprandial release of appetite-regulating hormones, subjective feelings of appetite, subsequent EI, and food reward in overweight/obese individuals. We hypothesized that an isocaloric session of HIIC would result in a larger reduction in AG and hunger, a larger increase in satiety peptides, and a greater reduction in subsequent EI compared with that in MICC (and that the short bout of HIIC would produce the same appetite changes as MICC).

METHODS

Subjects

Twelve healthy but sedentary overweight/obese volunteers (five males and seven females) not currently dieting to lose weight and weight stable on the previous 3 months (≤2-kg variation) were recruited for this study. Participants had an average (± SD) age of 33.4 ± 10.0 yr, an average (± SD) body mass index of 32.3 ± 2.7 kg·m−2, and an average (± SD) V˙O2max of 30.5 ± 4.9 mL·kg−1·min−1.

The exclusion criteria were as follows: a restraint score derived from the Three-Factor Eating Behavior Questionnaire >12 (30), history of CHD, type 1 or type 2 diabetes, anemia, gout, depression or other psychological disorders, eating disorders, drug or alcohol abuse within the last 2 yr, current medication known to affect appetite or induce weight loss, and hypertension.

This study was conducted according to the guidelines laid down in the Declaration of Helsinki and was approved by the regional ethics committee (Midt-Norge, Trondheim, Norway) (ref. 2010/444-1). A written informed consent was obtained from all participants before enrolling in the study.

Study Design

This was a randomized crossover study with four conditions. Participants acted as their own controls and were assigned to the four experimental conditions: control, MICC, HIIC, and S-HIIC, 1 wk apart, in a counterbalanced order.

Detailed Protocol

Participants were asked to attend the research unit five times, one preliminary familiarization session and four experimental conditions, as follows: control, MICC and HIIC isocaloric sessions designed to induce a 250-kcal energy deficit, and S-HIIC designed to induce an energy deficit of 125 kcal.

To reduce the inherent variability, participants were instructed to refrain from exercising and from drinking alcohol and caffeine 24 h before and on the day of each experimental condition. Participants were also asked to record on a food diary everything they ate and drank for dinner on the day before the first experimental condition and asked to consume exactly the same type and amount of food for dinner on the day before the other three conditions. Participants were interviewed on the morning of each experimental condition to check their compliance with these requirements.

In the preliminary session, anthropometric data were collected and cardiovascular fitness (V˙O2max) was measured on a cycle ergometer (Ergomedic 839E; Monark 2008, Sweden) using the system Oxigen Pro (Viasys Healthcare, Höchberg, Germany). The test started with a 5-min warm-up with a resistance of 50 W, and afterwards, the workload was gradually increased by 20 W every 2 min and participants were asked to maintain a cadence between 60 and 70 rpm. An RER of 1.05 or higher was set as the criterion for achieving V˙O2max. HR was continuously recorded during the test using an HR monitor (Polar type 610; Polar Electro Oy). HRmax was defined by adding five beats to the highest HR value obtained during the V˙O2max test.

For the four experimental conditions, participants were asked to arrive at approximately 8:00 a.m., having fasted for at least 10 h (water was permitted ad libitum during this time), and a cannula was inserted into an antecubital vein. A fasting blood sample was taken, and participants were instructed to consume a standard breakfast (time = 0) consisting of bread, orange juice, milk, cheese, and jam (600 kcal, 17% protein, 35% fat, and 48% CHO) within 10 min. After that, serial blood samples were taken at regular intervals for a period of 3 h (30, 60, 80, 100, 120, 150, and 180 min) and analyzed for hemoglobin, hematocrit, insulin, AG, PYY3–36, and GLP-1.

Participants were asked to rate their subjective feelings of hunger, fullness, and desire to eat using 10-cm visual analog scales throughout each study morning at different time points (right before each blood sampling), as previously described (11). The reward value of food was measured using a computer-based behavioral procedure called the Leeds Food Preference Questionnaire (10) immediately before and after each condition. The Leeds Food Preference Questionnaire provides measures of explicit liking (EL), implicit wanting (IW), and relative food preference according to the shared sensory properties of foods.

Three hours after breakfast, participants were placed in individual rooms, presented with a standardized lunch, and instructed to rate the taste and palatability of the food presented (and afterwards to eat as much or as little as they wanted from the food presented). The standardized ad libitum lunch test meal consisting of 10 1/4 (quarters) of sandwiches, 300 g of strawberry yogurt, and 60 g of crisps, in excess of expected consumption (1358 kcal, 53 g protein, 61 g fat, 133 g CHO). Participants were asked in advance to rank four sandwiches’ fillings (ham, cheese, salami, and liver paste) by order of preference. Participants were then offered their second most liked option.

Participants were then allowed to leave the research unit but were asked to use an AiperMotion 440PC accelerometer (Aipermon GmbH & Co. KG, Munich, Germany) to measure PA levels until retirement to bed. They were also asked to write down everything they ate and drank for the rest of the day in a food diary to estimate cumulative EI over that day (lunch plus subsequent EI until bedtime). Dietary analysis was performed using Mat på Data 5.0 program (Landsforeningen for kosthold og helse, Oslo, Norway).

Experimental conditions.

During the resting condition, participants remained seated but were allowed to read, write, or use a computer. During the exercise conditions, participants performed one of three exercise sessions 1 h after breakfast. Water was allowed ad libitum in all four conditions. Each exercise session started with a 5-min warm-up and finished with a 5-min cooldown. The MICC consisted of cycling at 70% HRmax. The HIIC consisted of bouts of 8-s sprinting (all out) and 12 s of turning the pedals very slowly (20–30 rpm). Participants were asked to follow a prerecorded tape, which prompted them to start and stop cycling so that the work/rest ratio was 8/12 s. The resistance used was that needed to increase the participant’s HR to 85%–90% HRmax. The S-HIIC was the same as the HIIC but for only half of the duration. The duration of each exercise session was individually designed (on the basis of data collected during the V˙O2max test) to induce a 250-kcal (MICC and HIIC) or 125-kcal (S-HIIC) energy deficit. HR was measured continuously during each exercise session using an HR monitor (Polar F1; Polar Electro Oy, Kempele, Finland). The average durations of each exercise session were 27 ± 6, 18 ± 3, and 9 ± 2 min for the MICC, HIIC, and S-HIIC sessions, respectively. The average HR during exercise were 133 ± 8 (71% ± 1% HRmax), 162 ± 11 (86% ± 2.5% HRmax), and 160 ± 9 (85% ± 3.5% HRmax) bpm for the MICC, HIIC, and S-HIIC sessions, respectively.

Hormone and metabolite measurement.

Venous blood was collected into regular EDTA tubes for the measurement of hemoglobin and hematocrit and EDTA-coated tubes containing 500 KIU aprotinin·mL−1 (Pentapharm, Basel, Switzerland) whole blood for the measurement of insulin and gut peptides. Hemoglobin and hematocrit levels were measured using standard hematological procedures. The other EDTA tubes containing aprotinin were then centrifuged at 2000g for 10 min and kept at −80°C for later analyses. For the measurement of AG, 50 μL of a 1-N hydrochloric acid solution and 10 μL of phenylmethylsulfonyl fluoride (Sigma, Schnelldorf, Germany) (10 mg·mL−1 of isopropanol) were added to each milliliter of plasma immediately after centrifugation. All samples were batch-analyzed at the end of the study to reduce interassay variability.

Insulin, AG, and PYY3–36 were quantified using human-specific radioimmunoassay (RIA) kits (Linco Research, St. Charles, MO), and GLP-1, using an in-house RIA method. GLP-1 concentrations in plasma were measured by RIA after extraction of plasma with 70% ethanol (v/v, final concentration), as previously described (20). Carboxy-terminal GLP-1 immunoreactivity was determined using antiserum 89390, which has an absolute requirement for the intact amidated carboxy-terminus of GLP-1 (7–36) amide and cross-reacts less than 0.01% with carboxy-terminally truncated fragments and 89% with GLP-1 (9–36) amide, the primary metabolite of dipeptidyl peptidase IV-mediated degradation. The sum of the two components (total GLP-1 concentration) reflects the rate of secretion of the L cell.

The sensitivity of the assays was 14 pmol·L−1 for insulin, 7.8 pg·mL−1 for AG, 1 pmol·L−1 for GLP-1, and 2 pmol·L−1 for PYY3–36. All samples were assayed in duplicate, and samples from the same participant (all four legs) were analyzed in the same batch. The intraassay coefficient of variation was of <10% for insulin and AG and <5% for GLP-1 and PYY3–36.

Statistical Analysis

Statistical analysis was carried out using SPSS version 13.0 (SPSS Inc., Chicago, IL). All the variables were checked regarding their normal distribution using the Shapiro–Wilk test, and data were expressed as mean ± SEM, unless otherwise stated.

Differences in fasting/postprandial levels of metabolites and hormones and appetite sensations between the experimental conditions were assessed by a repeated-measures ANOVA using experimental condition and time as independent variables. Because of significant differences in hemoglobin plasma levels and hematocrit (see Results section) among conditions, suggesting hemoconcentration during the exercise legs, plasma levels of the appetite hormones measured were adjusted for hematocrit (by multiplying by baseline hematocrit/hematocrit at a specific time point). The area under the curve (AUC) for plasma levels of appetite-related hormones and subjective feeling of appetite was calculated from before to 180 min after breakfast using the trapezoidal rule (baseline measurements were taken into account). Differences among experimental conditions were assessed by repeated-measures ANOVA. Post hoc analysis, with Bonferroni adjustment, was used to perform multiple comparisons.

Relative EI (REI) at the lunch test meal was calculated by subtracting the estimated EE during the exercise and rest sessions (180 min) from their respective lunch EI. EE during the 3 h at the research unit was estimated on the basis of the assumption that participants were allowed to read, write, work with the computer, etc., corresponding to an MET of 1.3 (1). EE during the MICC and HIIC was the same as that in the control condition + 250 kcal, and for the S-HIIC, EE was the same as that in the control condition + 125 kcal. Differences in absolute and REI and macronutrient intake at lunch and absolute energy and macronutrient intake throughout the day among conditions were assessed by repeated-measures ANOVA. Post hoc analysis, with Bonferroni adjustment, was used to perform multiple comparisons.

The reward value of food (EL and IW response measures and relative food preference) was analyzed using two 4 × 2 design ANOVA (experimental condition–time (pre/post)) for high-fat relative to low-fat food.

RESULTS

Hemoglobin and hematocrit.

Hemoglobin plasma levels and hematocrit changes over time in the four conditions can be seen in Figure 1. There was a significant effect of time and a condition–time interaction (P < 0.001 for both) on both hemoglobin and hematocrit. Hemoglobin plasma levels experienced a peak during exercise (quickly returning to control levels once the exercise stopped) in the three exercise conditions (Fig. 1A). A similar pattern was observed for hematocrit (Fig. 1B).

FIGURE 1
FIGURE 1:
A. Hemoglobin plasma level profiles (g·dL−1) after a 600-kcal breakfast for control (), MICC (□), HIIC (▴), and S-HIIC (X). Values represent means ± SEM for 12 subjects. Repeated-measures ANOVA showed a significant effect of time (P < 0.0001) and a significant condition–time interaction (P < 0.0001). B. Hematocrit level profiles after a 600-kcal breakfast for control (), MICC (□), HIIC (▴), and S-HIIC (X). Values represent means ± SEM for 12 subjects. Repeated-measures ANOVA showed a significant effect of time (P < 0.0001) and a significant condition–time interaction (P < 0.0001).

Appetite-related hormones.

Plasma levels of insulin, AG, PYY3–36, and GLP-1 over time in the different conditions can be seen in Figure 2.

FIGURE 2
FIGURE 2:
A. Insulin plasma level profiles (pmol·L−1) after a 600-kcal breakfast for control (), MICC (□), HIIC (▴), and S-HIIC (X). Values represent means ± SEM for 12 subjects. Repeated-measures ANOVA showed a significant effect of time (P < 0.0001) and a significant condition–time interaction (P < 0.0001). B. AG plasma level profiles (pg·mL−1) after a 600-kcal breakfast for control (), MICC (□), HIIC (▴), and S-HIIC (X). Values represent means ± SEM for 12 subjects. Repeated-measures ANOVA showed a significant effect of time (P < 0.0001) and condition (P < 0.001), but no interaction. C. PYY plasma level profiles (pmol·L−1) after a 600-kcal breakfast for control (), MICC (□), HIIC (▴), and S-HIIC (X). Values represent means ± SEM for 12 subjects. Repeated-measures ANOVA showed a significant effect of time (P < 0.0001) but no effect of condition or interaction. D. GLP-1 plasma level profile (pmol·L−1) after a 600-kcal breakfast for control (), MICC (□), HIIC (▴), and S-HIIC (X). Values represent means ± SEM for 12 subjects. Repeated-measures ANOVA showed a significant effect of time (P < 0.0001) and a significant condition–time interaction (P < 0.0001).

A significant effect of time (P < 0.001) and a condition–time interaction (P < 0.001), but no main effect of condition (P > 0.05), were observed on insulin plasma levels (Fig. 2A). Insulin plasma levels showed a peak at t = 30 min and decreased gradually afterwards in the control rest condition. In the exercise conditions, a pronounced reduction was observed during the exercise period (60–80 min), with an increase being observed shortly afterwards. No significant effect of condition was observed on insulin AUC (see Supplementary Table 1, http://links.lww.com/MSS/A400).

A significant effect of time and condition (P < 0.001 for both), but no interaction, was observed on AG plasma levels (Fig. 2B). AG plasma levels decreased after breakfast consumption with a nadir between 60 and 100 min and experienced a gradual increase afterwards. Moreover, AG plasma levels were significantly reduced in the MICC and HIIC conditions (P < 0.05) (but not S-HIIC), compared with those in control. No significant difference was observed in AG plasma levels between the MICC and HIIC conditions. A significant effect of condition was observed on AG AUC (P = 0.001), with AG AUC being significantly lower in the MIIC and HIIC compared with that in control (P = 0.02 and P = 0.037, respectively) (see Supplementary Table 1, http://links.lww.com/MSS/A400).

A significant effect of time (P < 0.001), but no effect of condition or interaction, was observed on PYY3–36 plasma levels (Fig. 2C), which increased gradually after breakfast consumption. No significant effect of condition was observed on PYY AUC (see Supplementary Table 1, http://links.lww.com/MSS/A400).

A significant effect of time (P < 0.001) and a condition–time interaction (P < 0.001), but no main effect of condition (P > 0.05), were observed on GLP-1 plasma levels. GLP-1 plasma levels peaked at around 30 min and decreased afterwards in the control rest condition. GLP-1 plasma levels were higher in the exercise conditions, compared with those in the control rest condition during and in the postexercise period. No significant effect of condition was observed on GLP-1 AUC (see Supplementary Table 1, http://links.lww.com/MSS/A400).

Subjective feelings of appetite and subsequent food intake.

Subjective feelings of appetite can be seen in Figure 3.

FIGURE 3
FIGURE 3:
A. Profiles of subjective feelings of hunger (cm) after a 600-kcal breakfast for control (), MICC (□), HIIC (▴), and S-HIIC (X). Values represent means ± SEM for 12 subjects. Repeated-measures ANOVA showed a significant effect of time (P < 0.001) but no effect of condition or interaction. B. Profiles of subjective feelings of fullness (cm) after a 600-kcal breakfast for control (), MICC (□), HIIC (▴), and S-HIIC (X). Values represent means ± SEM for 12 subjects. Repeated-measures ANOVA showed a significant effect of time (P < 0.0001) but no effect of condition or interaction. C. Profiles of subjective feelings of desire to eat (cm) after a 600-kcal breakfast for control (), MICC (□), HIIC (▴), and S-HIIC (X). Values represent means ± SEM for 12 subjects. Repeated-measures ANOVA showed a significant effect of time (P < 0.001) and a time–condition interaction (P < 0.05).

There was a significant effect of time (P < 0.0001), but no effect of condition or interaction, on hunger and fullness ratings (Fig. 3A and B). For desire to eat, there was a significant effect of time (P < 0.001) and a time–condition interaction (P < 0.05) but no main effect of condition (Fig. 3C). Desire to eat ratings decreased immediately after breakfast consumption and decreased afterwards and were lower in the exercise conditions compared with those in rest, during the exercise period. No significant effect of condition was observed for hunger, fullness, or desire to eat AUC (see Table, Supplemental Digital Content 1, AUC for subjective feelings of appetite and appetite-related hormones in the different conditions).

Energy and macronutrient intake at lunch, after each condition, and throughout the day can be seen in Table 1. There were no significant differences in absolute energy or macronutrient intake at lunch or throughout the day among conditions. There was a significant effect of condition on REI at lunch (P < 0.001). Post hoc analysis showed that REI in the control condition was significantly higher than that in the exercise conditions (P < 0.001 for MICC, P = 0.002 for HIIC, and P = 0.01 for S-HIIC). REI after MIIC was also significantly lower than that after the S-HIIC (P < 0.001).

TABLE 1
TABLE 1:
Absolute energy and macronutrient intake at lunch and throughout the day and REI at lunch during the different experimental conditions.

PA levels throughout the day after each experimental condition.

Time spent on different activities throughout the day in the different conditions can be seen in Table 2. No significant differences were observed on sedentary time or time spent in walking or fast walking among conditions. A significant effect of condition was observed on time spent active (P = 0.029). Further post hoc analysis, however, did not reveal any significant difference in active time among conditions.

TABLE 2
TABLE 2:
Time (min) spent in different activities throughout the day in the different conditions.

Food reward.

EL, IW, and relative preference scores can be seen in Table 3. Mean scores were positive in all experimental conditions, indicating that high-fat foods were, on average, more rewarding than low-fat foods. There were no significant differences in the reward value of high-fat foods between conditions or over time (and no interaction between condition and time) according to measures of EL, IW, or relative preference.

TABLE 3
TABLE 3:
Reward value of high-fat food before and after each experimental condition.

DISCUSSION

To the best of our knowledge, this is the first study to evaluate the role of exercise intensity on appetite responses to acute bouts of exercise in overweight/obese individuals. Our hypothesis that an isocaloric session of HIIC would result in a larger reduction in AG and hunger, a larger increase in satiety peptides, and a greater reduction in subsequent EI compared with those in MICC was not confirmed.

In one of the few studies performed in obese individuals, Ueda et al. (29) showed that 60 min of cycling at 50% V˙O2max leads to a significant suppression in insulin, a significant increase in PYY and GLP-1, and no changes in TG or subjective appetite feelings in obese men. It is difficult to ascertain why, in the present study, exercising at an even higher intensity was unable to increase PYY3–36 plasma levels. However, given the larger exercise-induced energy deficit in the study of Ueda et al. (29) compared with that in ours (approximately 600 kcal compared with 250 kcal), it is possible that a larger energy deficit would be needed to induce an increase in the postprandial release of PYY. Moreover, it is difficult to compare studies that measured total PYY (PYY1–36) with studies that measured its active component PYY3–36 because the conversion rate of total PYY (PYY1–36) to PYY3–36 remains unknown and only PYY3–36 has satiety properties.

In contrast to majority of the studies performed in normal-weight individuals (18), a transient suppression of hunger during exercise was not observed in the present study. However, subjective feelings of desire to eat were lower during exercise (compared with that during rest) regardless of the exercise condition. Westerterp-Plantenga et al. (32), in a study including both normal-weight and obese men, reported a significant suppression of hunger after 2 h of cycling at 60% of maximum workload (compared with a resting condition). Unfortunately, analysis was not performed separately in obese men (32). Again, it is possible that the larger exercise-induced EE in that study, compared with ours, has contributed to the differences in outcome.

Absolute energy and macronutrient intake at the lunch test meal was similar regardless of the experimental condition. However, REI was negative and significantly lower after the exercise conditions compared with that in control. No significant differences were observed in absolute energy and macronutrient intake throughout the day among conditions. However, taking into account that sedentary and active time also did not differ among conditions, a lower REI and subsequent negative EB would be expected after acute exercise. This is in accordance with the study of Ueda et al. (29), where a reduction in absolute and REI after 60 min of cycling at 50% V˙O2max was reported in obese men.

Few studies have investigated the effect of exercise intensity on appetite. Ueda et al. (28) looked at the effect of cycling at 50% or 75% V˙O2max (or rest) for 30 min on PYY3–36 and GLP-1 plasma levels in normal-weight trained men. They reported a larger increase in PYY3–36 plasma levels at higher intensity despite a similar increase in GLP-1 levels and a similar reduction in absolute EI and hunger feelings in both exercise conditions (28). Kissileff et al. (17) looked at the effect of strenuous (90 W) or moderate-intensity (30 W) cycling for 40 min (or rested) on food intake 15 min afterwards in normal-weight or overweight women. Food intake after exercise was significantly less after the strenuous than that after the moderate exercise in the normal-weight women but was similar in obese women (17). The mentioned evidence seems to suggest that a high-intensity exercise would induce not only a larger suppression in orexigenic signals (AG) but also a larger release of satiety signals (PYY3–36). However, the two last mentioned studies (17,28) used nonisocaloric bouts of exercise. Therefore, it is impossible to ascertain whether the differences are due to exercise intensity or the larger energy deficit induced by the high-intensity exercise bout. A recently published study in trained normal-weight men using isocaloric bouts of HIIC and MICC showed a significant suppression of hunger and a significant increase in PYY3–36 concentrations during/after exercise, especially during the HIIT, and no difference in ad libitum EI (7).

In the present study, in overweight/obese individuals, using isocaloric bouts of moderate- and high-intensity exercise, no significant effect of exercise intensity was observed on appetite hormones, subjective feelings of appetite, or EI. Exercise intensity by itself does not seem, at least in overweight/obese individuals, to have an effect on appetite. In a recently published study, Sim et al. (26) randomly assigned overweight sedentary men to isocaloric bouts of MICC (60% V˙O2max), HIIC (60 s at 100% V˙O2max, 240 s at 50% V˙O2max), very-HIIC (15 s at 170% V˙O2max, 60 s at 32% V˙O2max), and control in a counterbalanced order. They showed, as in our study, no differences in subjective appetite among conditions but a lower ad libitum EI after HIIC and very-HIIC compared with that in control and significantly lower AG plasma levels after very-HIIC compared with that in the other conditions (26). However, that study recruited overweight men and the exercise was performed in a fasting state. Moreover, the much higher exercise intensity used in that study, compared with ours, at levels that would be difficult to sustain in the obese population, is likely to explain the different outcomes.

Few studies on the effects of exercise on appetite have included measures of food reward. Finlayson et al. (9) reported an increase in IW for foods varying in fat content and sweet taste after moderate-intensity cycling (compared with no exercise) but only in those participants who increased their EI after exercise. Taylor and Oliver (27) reported that exercise transiently decreased cravings for chocolate (compared with rest). In the present study, we found no difference in liking, IW, or relative preference for high-fat food relative to low-fat food. These findings suggest that the overall mean pattern of food reward was stable. However, the large SD of scores indicates a broad range of between-subject variability.

Our study presents with both strengths and limitations. The main strength of our study is its design (crossover) and the fact that we measured several aspects of appetite (subjective feelings, plasma levels of several appetite-related hormones, EI, and food reward). As a limitation, we have not accounted for phase of menstrual cycle, known to affect energy and macronutrient intake (22) and food reward (21,22). However, given our design (crossover, randomized with four legs), we believe that the phase of menstrual cycle had a minor effect on our results. Even though we aimed to look at the effect of exercise intensity on appetite, the MICC and HIIC differed both in intensity and continuousness/discontinuousness. However, given that the intervals of active resting in the HIIC were so short (12 s), the HR was at 85%–90% HRmax all the time. It would be impossible to perform continuous high-intensity exercise inducing an EE of 250 kcal in this patient group (inactive overweight/obese individuals). Our protocol with exercise (or rest) being performed 1 h after breakfast and the lunch test meal being presented 3 h after breakfast was used to simulate a typical day because exercise is usually performed in the postprandial state. Several other studies looking at the effect of acute exercise on appetite have used a similar order of events (19,28,29,32).

In conclusion, our findings show that in overweight/obese individuals, acute isocaloric bouts of moderate- or high-intensity exercise lead to a similar appetite response. Both suppress insulin and AG and increase the postprandial release of GLP-1 without affecting PYY3–36 plasma levels and have no effect on hunger or fullness despite reducing desire to eat. This, together with a significant reduction in REI in all exercise conditions and no changes in activity patterns throughout the day, strengthens previous findings in normal-weight individuals that acute exercise, even at high intensity, is able to induce a negative EB without stimulating physiological compensatory adaptations at the level of the appetite control system.

We would like to thank all the participants that took part in this study for their time and enthusiasm and Mrs. Sissel Salater for her help with cannulation.

This study was funded by the liaison committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology. C. M. was supported by a postdoctoral grant from the liaison committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology.

The authors declare that there is no conflict of interest that would prejudice the impartiality of this scientific work.

The results of the present study do not constitute endorsement by the American College of Sports Medicine.

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Keywords:

GHRELIN; POLYPEPTIDE YY; GLUCAGON-LIKE PEPTIDE 1; FOOD REWARD

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