Journal Logo

APPLIED SCIENCES

High-Intensity Interval Training, Appetite, and Reward Value of Food in the Obese

MARTINS, CATIA1,2; ASCHEHOUG, IRINA1; LUDVIKSEN, MARIT1; HOLST, JENS3; FINLAYSON, GRAHAM4; WISLOFF, ULRIK5,6; MORGAN, LINDA7; KING, NEIL8; KULSENG, BÅRD1,2

Author Information
Medicine & Science in Sports & Exercise: September 2017 - Volume 49 - Issue 9 - p 1851-1858
doi: 10.1249/MSS.0000000000001296
  • Free

Abstract

Exercise is frequently used as a weight loss strategy because it has the ability to increase energy expenditure and, therefore, theoretically to create a negative energy balance. However, weight loss response to exercise is known to be highly variable, even when exercise is supervised (14). Several compensatory mechanisms have been identified that can undermine the ability of exercise to promote the predicted weight loss (12,14).

We have previously reported that those who have a suboptimal response to exercise, in terms of weight/fat mass loss, show an immediate postexercise increase in liking and wanting and a preference for high-fat sweet foods (4). Low responders also experience a compensatory increase in energy intake and an increase in hunger feelings (14). Evaluating the effect of chronic exercise on appetite is, therefore, of vital importance if we want to improve our understanding on the role of exercise in weight management. Collectively, our research groups have previously shown that 12 wk of moderate-intensity exercise (five times per week) is associated with increased levels of acylated ghrelin (AG) (4) and hunger feelings in the fasting state (13,18), despite an improved satiety response to a meal (4,5) and improved sensitivity of the appetite control system (18,19). However, a study by Guelfi et al. (7) reported no change in either fasting hunger or AG after 12 wk of aerobic (moderate intensity) or resistance exercise (three times per week). Differences in the magnitude of weight and fat mass losses, volume of exercise, and gender may contribute to the discrepancies between studies.

People usually claim lack of time as a barrier for not exercising (29), and this is likely to contribute to the high dropout rates from exercise programs observed particularly in the obese (6,24). High-intensity exercise offers a more time-efficient option and possibly a more enjoyable than moderate-intensity continuous training (MICT) (15). High-intensity interval training (HIIT), where bouts of high-intensity exercise alternate with bouts of low-intensity exercise, has been proposed as an effective alternative (2). Studies on the effect of chronic HIIT on appetite in the obese population are scarce, and the available single study is limited by the fact that the authors included overweight men only (26).

Therefore, the aim of this study was to compare the effect of 12 wk of isocaloric HIIT, MICT, and short-duration HIIT (1/2-HIIT) on subjective appetite sensations, appetite-related hormones, and liking and wanting in obese individuals.

METHODS

Subjects

Forty-six obese, but otherwise healthy, individuals (30 females and 16 males), with a sedentary lifestyle, mean body mass index (BMI) of 33.3 ± 2.9 kg·m−2, and mean age of 34.4 ± 8.8 yr were recruited for this study, through web and paper advertisement posted at the Norwegian University of Science and Technology (Trondheim, Norway) and surrounding community.

Sedentary lifestyle was defined as not engaged in strenuous work or in regular brisk leisure physical activity more than once a week or in light exercise for more than 20 min·d−1 on more than three times per week. This was assessed through an exercise history (interview) of the 3 months before the study. Those dieting to lose weight, with weight unstable on the last 3 months (≤2 kg variation), taking any medication known to affect appetite or induce weight loss, or with a restraint score derived from the Three Factor Eating Behavior Questionnaire (27) >12 were not included in the study.

This study was conducted according to the guidelines laid down in the Declaration of Helsinki and was approved by the regional Ethics Committee for Medical Research (REK no. 2010/447). Written informed consent was obtained from all participants before enrolling in the study. The study reported here is a component of a larger metabolic study of which portions have been published earlier (17).

Study design

This was a randomized study where participants were randomly allocated to either MICT (n = 14), HIIT (n = 16), or 1/2-HIIT (n = 16) for 12 wk. There were no significant differences between the three groups in age, male/female ratio, BMI, or cardiovascular fitness (V˙O2max) before the training programs.

Detailed description of the study

Participants underwent a 12-wk supervised exercise program and were asked to maintain their habitual diet during the study. Compliance was assessed using 3-d self-reported food diaries at baseline and on the last week of training (two weekdays and one weekend day). Food diary data were analyzed using the program Mat på Data (version 5.1). Several measurements were performed before and after the intervention, at least 48 h after the last exercise session, including anthropometric measurements, body composition, maximal oxygen consumption (V˙O2max), fasting and postprandial subjective feelings of appetite and plasma concentrations of appetite-related hormones, and food reward, among others (for a full description of all the measurements, see Martins et al. [17]). Participants completed the appetite measurements individually in separate rooms.

There was a significant overall reduction in body weight (−1.2 ± 2.5 kg, P < 0.01) and increase in V˙O2max (P < 0.001), when expressed in absolute values (L·min−1, +9%) and when normalized for body weight (mL·kg−1·min−1, +10%), with the exercise intervention, but no significant main effect of group or interaction. Also, significant improvements were seen in body composition and no changes in insulin sensitivity, energy, or macronutrient intake, despite no differences between groups (for more details, see Martins et al. [16]).

Exercise intervention

All participants exercised three times per week for 12 wk, and all sessions were supervised. Exercise was carried out on a Monark cycle ergometer (Ergomedic 839E; Monark 2008, Varberg, Sweden). All participants started the exercise session with 5 min warm-up and finished with a 5-min cooldown. HR was recorded during each exercise session using Polar F6M HR monitor (Polar type 610, Polar Electro Oy, Finland).

The MICT consisted of continuous cycling at 70% of HRmax. The duration of the exercise sessions was estimated for each participant individually to induce a 250-kcal energy deficit, using HR/V˙O2 data obtained during the V˙O2max test. The HIIT protocol consisted of 8 s of sprint, working at 85%–90% of HRmax and 12 s of recovery phase, during which participants cycled as slowly as possible (28). Participants were instructed when to start and stop each phase using a recorded audio message. The resistance was ramped during the 12 wk to accommodate increased aerobic capacity. The HIIT protocol was designed to induce a 250-kcal energy deficit, and the duration of the exercise session was calculated for each participant individually. Participants in the 1/2-HIIT group followed the same protocol as the HIIT group, but only for the duration needed to induce a 125-kcal energy deficit (using the same approach as for MICT).

To account for changes in aerobic capacity and body weight, submaximal V˙O2max tests were performed at weeks 4 and 8, and exercise prescription was adjusted to maintain exercise-induced energy expenditure constant overtime. Therefore, exercise-induced energy expenditure, at all time points, was estimated from V˙O2 data, not directly measured.

Subjective sensations of appetite and blood sampling

Participants visited the research unit in the fasting state (at least a 12-h fast), before and after the 12-wk exercise intervention. On each occasion, an intravenous cannula was inserted into an antecubital vein. A fasting blood sample was taken, and participants were asked to rate their baseline appetite using a 10-cm visual analog scale, as previously described (9). Participants were then instructed to consume a standard breakfast (time [t] = 0) consisting of bread, orange juice, milk, cheese, and jam (600 kcal, 17% protein, 35% fat, and 48% carbohydrate) within 10 min. Blood samples were taken every 30 min for a period of 3 h, and subjective feelings of hunger, fullness, desire to eat, and prospective food consumption (PFC) were assessed throughout the morning using visual analog scale.

Hormone measurement

Venous blood was collected into ethylenediaminetetraacetic acid–coated tubes containing 500 KIU aprotinin (Pentapharm, Basel, Switzerland) per milliliters of whole blood for the measurement of gut peptides. Samples were then centrifuged at 2000g for 10 min and plasma kept at −80°C for later analyses. For the measurement of AG, 50 μL of 1 N hydrochloric acid 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.

AG and polypeptide YY3–36 (PYY3–36) were quantified using human-specific RIA kits (Linco Research, St. Charles, MO) and glucagon-like peptide 1 (GLP-1) with an “in-house” RIA method (22). The sensitivity of the assays was 7.8 pg·mL−1 for AG, 1 pmol·L−1 for GLP-1, and 20 pg·mL−1 for PYY3–36. All samples were assayed in duplicate, and baseline and end samples of the same individual were analyzed in the same batch. The intra-assay coefficient of variation was less than 10% for AG and PYY3–36 and less than 5% for GLP-1.

Measurement of food preferences and reward

Fat and sweet taste preference and the reward value of food were measured using a computer-based behavioral procedure called the Leeds Food Preference Questionnaire (5). The Leeds Food Preference Questionnaire provides measures of explicit liking, implicit wanting, and relative food preference according to the shared sensory properties of foods. Participants were presented with an array of pictures of individual food items common in the diet. A database with food items either predominantly high (>50% energy) or low (<20% energy) in fat, but similar in familiarity, protein content, sweet or nonsweet taste, and palatability and adapted to Norwegian culture, was used for this purpose. For more details about the procedure, see Finlayson et al. (5).

Power calculation

This study was powered to determine differences between the MICT and the HIIT groups, in terms of changes in subjective feelings of appetite in fasting. For a difference of 2.4 cm in changes in subjective hunger in fasting between groups, given an SD of the outcome variable of 2 cm, at a power of 80% and a significance level of 0.05, 12 participants per group would be needed (18). We assumed that the 1/2-HIIT would produce the same results as the HIIT.

Statistical analysis

Statistical analysis was conducted using SPSS 20.0 (SPSS Inc., Chicago, IL). All variables were checked regarding normality of distribution using the Kolmogorov–Smirnov test. Statistical significance was assumed at P < 0.05, unless otherwise stated. A three-way mixed-model ANOVA was used to examine the effect of intervention (pre- vs postintervention), blood sampling time (0, 30, 60, 90, 120, 150, and 180 min postprandially), exercise group (HIIT, 1/2-HIIT, and MICT), and interactions on subjective feelings of appetite and appetite-related hormones. A two-way mixed-model ANOVA was used to examine the effect of intervention (pre- vs postintervention), exercise group (MICT, HIIT, and 1/2-HIIT), and interactions on the total area under the curve (tAUC) for subjective feelings of appetite and appetite-related hormones. tAUC for appetite hormones and subjective feelings of appetite was calculated from immediately before to 180 min after breakfast, using the trapezoidal rule. The reward value of food (explicit liking and implicit wanting 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

Compliance with the Intervention

For various reasons, one participant from the MICT (due to family reasons), three from the HIIT (one due to muscle discomfort and two due to lack of time), and seven from the 1/2-HIIT group (three due to muscle discomfort, three due to lack of time, and one for family reasons) withdrew from the study. There were no significant differences in age, BMI, or any of the variables measured between those who withdrew and those who completed the intervention.

All the participants who finished the intervention performed all the planned exercise sessions (36 sessions for 12 wk). The average exercise duration/session was 32, 20, and 10 min for the MICT, HIIT, and 1/2-HIIT, respectively.

Subjective Sensations of Appetite

Fasting state

Changes in subjective feelings of appetite, in the fasting state, in the different exercise interventions can be seen in Table 1. There was a significant increase in fasting subjective feelings of hunger with exercise (P = 0.01) but no main effect of group or interaction.

No significant effect of exercise, group, or interaction was observed for subjective feelings of fullness, desire to eat, or PFC in fasting.

TABLE 1
TABLE 1:
Fasting subjective appetite sensations before and after each exercise intervention.

Postprandial state

A significant effect of assessment time (P < 0.001) was observed on subjective feelings of hunger, fullness, desire to eat, and PFC, which either decreased or increased after breakfast intake and increased (or decreased) afterward. No significant effect of intervention (pre- vs postexercise), group (MICT, HIIT, or 1/2-HIIT), or interactions were found for any of the appetite feelings studied.

tAUC for hunger increased significantly after the 12-wk exercise program (P = 0.048), but there was no significant effect of group or interaction (Fig. 1A). No significant effect of exercise, group, or interaction was found for the tAUC for fullness, desire to eat, and PFC (Figs. 1B–1D).

FIGURE 1
FIGURE 1:
A–D, tAUC (0–180 min) for hunger, fullness, desire to eat, and PFC before and after the 12-wk exercise intervention. Results are expressed as mean ± SD. A main effect of exercise (P = 0.048) but no effect of group or interaction was found for AUC hunger. No main effect of exercise, group, or interaction was found regarding AUC for the other appetite ratings.

Plasma Concentration of Appetite-Related Hormones

Fasting concentrations

The fasting plasma concentrations of the appetite-related hormones measured before and after the three exercise interventions are shown in Table 2. There was no significant effect of exercise (before vs after the 12-wk exercise program), group (MICT, HIIT, or 1/2-HIIT), or interaction for any of the appetite-related hormones measured.

TABLE 2
TABLE 2:
Fasting plasma levels of AG, PYY3–36, and GLP-1 before and after each exercise intervention.

Postprandial concentrations

A significant effect of sampling time (P < 0.001) was observed on AG plasma levels, which decreased up to 60 min and increased afterward until 180 min postprandially. No significant effect of exercise intervention (pre- vs postexercise) or group was found on AG plasma levels (data not shown). A significant effect of sampling time (P < 0.001) was observed for GLP-1 plasma levels, which increased up to 90 min and decreased afterward until 180 min postprandially. No significant effect of intervention or group was found on GLP-1 plasma levels (data not shown). A significant effect of sampling time (P < 0.001) was also observed for PYY3–36 plasma levels, which gradually increased over time up to 180 min postprandially. No significant effect of intervention or group was found on PYY3–36 plasma levels.

No significant effect of exercise, group, or interaction, was found on tAUC for AG, GLP-1, or PYY3–36 (Figs. 2A–2C).

FIGURE 2
FIGURE 2:
A–C, tAUC (0–180 min) for AG (A), GLP-1 (B), and PYY3–36 before and after the 12-wk exercise intervention. Results are expressed as mean ± SD. No main effect of exercise, group, or interaction was found regarding AUC for any of the appetite hormones.

When the data from the three groups were pooled, there was a significant correlation between magnitude of weight loss and changes in ghrelin concentration in fasting (r = −0.538, n = 34, P = 0.001), but not for changes in ghrelin concentration after the test meal (AUC) (r = −0.308, n = 34, P = 0.076), denoting greater increases in ghrelin fasting concentrations with larger weight losses.

Food Preference and Reward

Breakfast intake significantly decreased explicit liking, implicit wanting, and relative preference for high-fat relative to low-fat foods (all P < 0.001) and savory relative to sweet foods (all P < 0.001). No effects of intervention (pre- vs postexercise), group (MICT, HIIT, or 1/2-HIIT), or interactions were found (Table 3).

TABLE 3
TABLE 3:
Food preference and food reward pre- and postbreakfast, before and after each exercise intervention.

DISCUSSION

The main findings of this study were that no significant differences between exercise groups (MICT, HIIT, and 1/2-HIIT) were found for any of the variables measured. Moreover, there were no significant main effects of time, except fasting and postprandial subjective sensations of hunger, which increased significantly. These findings may indicate that at this low level of exercise-induced energy expenditure, exercise intensity has no major effect on appetite.

Only a handful of studies have addressed the effect of chronic exercise on subjective feelings of appetite and appetite-related hormones (7,13,18,23) in overweight or obese individuals. King et al. (13) were the first to demonstrate that chronic exercise (12 wk duration at moderate intensity, inducing an average 3.2-kg weight reduction, mainly fat mass) has a dual effect on appetite in obese individuals; it increases the orexigenic drive to eat (hunger feelings), both in fasting and throughout the day, while also improving meal-induced satiety, i.e., inducing a stronger suppression of hunger after a mixed meal. Martins et al. (18) later showed, using the same exercise intervention, that exercise-induced weight loss (average 3.5 kg) leads to an increase in AG levels and hunger feelings in fasting, despite an improved satiety response to a meal (tendency toward increased release of PYY and GLP-1 in the late postprandial period).

In the study of Guelfi et al. (7), overweight and obese men exercised at moderate intensity (70%–80% HRmax, three times per week for 12 wk. They reported no change in either fasting hunger or AG after the exercise intervention, despite an average weight loss of 2 kg. It is possible that a minimum threshold of weight loss and/or exercise-induced energy expenditure is needed to induce not only an increase in hunger and AG but also an improvement in the satiety response with exercise. This is strengthened by previous findings showing that it is weight loss, not exercise, that leads to increased ghrelin plasma levels (17) and by our findings that greater increases in ghrelin fasting concentrations are seen with larger weight loss. However, Rosenkilde et al. (23) showed that despite significant weight reduction (3.5 vs 2.5 kg, respectively), neither moderate (30 min·d−1) nor high doses of MICT (60 min·d−1) increase fasting or postprandial measures of appetite (hunger feelings or total ghrelin). Moreover, they reported that a high dose of exercise (double that used in the present study) was associated with an increase in fasting and meal-related ratings of fullness and a tendency toward increased postprandial release of PYY. However, this study was run in overweight, nonobese individuals, and differences in BMI as well as the measurement of total versus active ghrelin may modulate the results.

Studies on the effect of chronic HIIT on appetite are however lacking. A recent study by Sim et al. (26), where overweight men were randomized to isocaloric programs of HIIT (15 s at a power output equivalent to approximately 170% V˙O2peak, with an active recovery period, 60 s at a power output approximately 32% V˙O2peak, between efforts) or MICT (60% V˙O2peak), or a no-intervention control group, for 12 wk, reported no change in either subjective feelings of appetite or appetite-related hormones (AG, PYY, and pancreatic polypeptide) (in fasting or postprandially) or differences between groups. This is consistent with our findings in obese men and women. The only difference was that in our study, we report an overall increase in subjective feelings of hunger in fasting and postprandially. This may be due to differences in the amount of weight loss between the two studies (average −0.7 vs −1.2 kg). The changes in subjective feelings of appetite, in the absence of significant changes in the plasma concentration of appetite-related hormones, described in the present study, are not unexpected and have been previously reported (3). This discrepancy may be related with changes in the sensitivity to the appetite-related hormones.

Blood flow redistribution and lactate production have been proposed as two potential mechanisms mediating the effect of acute exercise on appetite, in particular the transitory appetite suppression seen after high-intensity exercise, characterized by hypoxia and lactate accumulation (8). Given that postintervention appetite measurements were completed at least 48 h after the last exercise session, it is unlikely that hypoxia and lactate accumulation are involved in appetite changes in response to chronic exercise. However, more studies are needed in this area.

A decrease in the relative preference for high- versus low-fat foods has been reported after an acute bout of MICT in normal weight individuals (21). However, no changes in the reward value of food were seen after isocaloric bouts of MICT or HIIT (20) or one session of MICT and HIIT in obese individuals (1), or differences between exercise modalities (10,20). However, studies on the effect of chronic exercise, including MICT and/or HIIT, on food hedonics are lacking, and to the best of our knowledge, the present study is the first to show that chronic MICT or HIIT have no significant effect on the reward value of food.

Our research group (20) and others (25) have shown that an acute session of HIIT leads to similar appetite responses as MICT in obese individuals, both in terms of subjective appetite feelings and appetite-related hormones. The present findings and the available literature (26) suggest that the effect of chronic HIIT on appetite may also not differ from MICT. A review by Kessler et al. (11) concluded that HIIT has the potential to induce a similar weight loss, and similar or larger improvements in aerobic fitness in the obese, compared with MICT. Later studies in obese individuals, using HIIT, have shown similar improvements in aerobic fitness as isocaloric protocols of MICT (17,26). This has important practical implications. The time saving component associated with performing HIIT, and the fact that it may be more enjoyable (15), gives HIIT an advantage. However, at the end, exercise needs to be individualized, and overweight and obese individuals should potentially choose the exercise program that best fits them and that has the best chance of compliance and long-term commitment. The current study benefits from a robust design (a randomized, controlled study) and the methodology used tackled several aspects of appetite: subjective feelings, objective measures (levels of appetite-related hormones in the plasma), and food hedonics. However, we are also aware of several limitations: first, a larger sample size would be preferable, particularly given the known large interindividual variation in compensatory responses to exercise (12). Second, this was an efficacy study and, as such, our analysis was restricted to completers, which may distort the results and practical implication of our findings. Third, the volume of exercise used, and as a result the attained weight loss, might not have been enough to activate the expected changes in appetite (13,18). Fourth, we did not account for changes in bicarbonate pool/buffering, which were likely larger after HIIT compared with MICT and might have distorted the calculations of energy expenditure. Fifth, the estimation of energy expenditure during HIIT was based on the HR/V˙O2 relationship obtained during continuous exercise. Although this is a common procedure (25,26), the validity and the accuracy of this approach have never been tested. Lastly, we did not measure excess postexercise oxygen consumption, which has been shown to be larger after HIIT compared with isocaloric MICT (16). Given the approach used to estimate energy expenditure during HIIT and the fact that excess postexercise oxygen consumption was not measured, the isocaloric nature of the MICT and HIIT protocols cannot be guaranteed.

We can conclude that the effect of chronic MICT versus HIIT on appetite, in obese previously sedentary individuals, does not seem to differ. Neither exercise modality seems to induce meaningful changes in either subjective or objective appetite measures or food hedonics, at least when weight loss is minimal. More and larger studies are needed to confirm the present findings.

Catia Martins 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 thank all the participants that took part in this study for their time and enthusiasm and Mrs. Sissel Salater and Hege Bjøru for their help with cannulation. The results of the present study do not constitute endorsement by the American College of Sports Medicine.

The authors declare that there is no conflict of interest that would prejudice the impartiality of this scientific work. Moreover, the authors also declare that the results of the present study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.

REFERENCES

1. Alkahtani SA, Byrne NM, Hills AP, King NA. Interval training intensity affects energy intake compensation in obese men. Int J Sport Nutr Exerc Metab. 2014;24(6):595–604.
2. Boutcher SH. High-intensity intermittent exercise and fat loss. J Obes. 2011;2011:868305.
3. Doucet E, Laviolette M, Imbeault P, Strychar I, Rabasa-Lhoret R, Prud'homme D. Total peptide YY is a correlate of postprandial energy expenditure but not of appetite or energy intake in healthy women. Metabolism. 2008;57(10):1458–64.
4. Finlayson G, Caudwell P, Gibbons C, Hopkins M, King N, Blundell J. Low fat loss response after medium-term supervised exercise in obese is associated with exercise-induced increase in food reward. J Obes. 2011;2011: pii: 615624.
5. Finlayson G, King N, Blundell J. The role of implicit wanting in relation to explicit liking and wanting for food: implications for appetite control. Appetite. 2008;50(1):120–7.
6. Fox AM, Mann DM, Ramos MA, Kleinman LC, Horowitz CR. Barriers to physical activity in East harlem, new york. J Obes. 2012;2012:719140.
7. Guelfi KJ, Donges CE, Duffield R. Beneficial effects of 12 weeks of aerobic compared with resistance exercise training on perceived appetite in previously sedentary overweight and obese men. Metabolism. 2013;62(235):243.
8. Hazell TJ, Islam H, Townsend LK, Schmale MS, Copeland JL. Effects of exercise intensity on plasma concentrations of appetite-regulating hormones: potential mechanisms. Appetite. 2016;98:80–8.
9. Hill AJ, Leathwood PD, Blundell JE. Some evidence for short-term caloric compensation in normal weight human subjects: the effects of high- and low-energy meals on hunger, food preference and food intake. Hum Nutr Appl Nutr. 1987;41(4):244–57.
10. Kalarchian MA, Marcus MD, Courcoulas AP, Cheng Y, Levine MD, Josbeno D. Optimizing long-term weight control after bariatric surgery: a pilot study. Surg Obes Relat Dis. 2012;8(6):710–5.
11. Kessler HS, Sisson SB, Short KR. The potential for high-intensity interval training to reduce cardiometabolic disease risk. Sports Med. 2012;42(6):489–509.
12. King NA, Caudwell P, Hopkins M, et al. Metabolic and behavioral compensatory responses to exercise interventions: barriers to weight loss. Obesity (Silver Spring). 2007;15(6):1373–83.
13. King NA, Caudwell PP, Hopkins M, Stubbs JR, Naslund E, Blundell JE. Dual-process action of exercise on appetite control: increase in orexigenic drive but improvement in meal-induced satiety. Am J Clin Nutr. 2009;90(4):921–7.
14. King NA, Hopkins M, Caudwell P, Stubbs RJ, Blundell JE. Individual variability following 12 weeks of supervised exercise: identification and characterization of compensation for exercise-induced weight loss. Int J Obes (Lond). 2008;32(1):177–84.
15. Kong Z, Fan X, Sun S, Song L, Shi Q, Nie J. Comparison of high-intensity interval training and moderate-to-vigorous continuous training for cardiometabolic health and exercise enjoyment in obese young women: a randomized controlled trial. PLoS One. 2016;11(7):e0158589.
16. Laforgia J, Withers RT, Gore CJ. Effects of exercise intensity and duration on the excess post-exercise oxygen consumption. J Sports Sci. 2006;24(12):1247–64.
17. Martins C, Kazakova I, Ludviksen M, et al. High-intensity interval training and isocaloric moderate-intensity continuous training result in similar improvements in body composition and fitness in obese individuals. Int J Sport Nutr Exerc Metab. 2016;26(3): 197–204.
18. Martins C, Kulseng B, King NA, Holst JJ, Blundell JE. The effects of exercise-induced weight loss on appetite-related peptides and motivation to eat. J Clin Endocrinol Metab. 2010;95(4):1609–16.
19. Martins C, Kulseng B, Rehfeld JF, King NA, Blundell JE. Effect of chronic exercise on appetite control in overweight and obese individuals. Med Sci Sports Exerc. 2013;45(5):805–12.
20. Martins C, Stensvold D, Finlayson G, et al. Effect of moderate- and high-intensity acute exercise on appetite in obese individuals. Med Sci Sports Exerc. 2015;47(1):40–8.
21. McNeil J, Cadieux S, Finlayson G, Blundell JE, Doucet E. The effects of a single bout of aerobic or resistance exercise on food reward. Appetite. 2015;84:264–70.
22. Orskov C, Rabenhoj L, Wettergren A, Kofod H, Holst JJ. Tissue and plasma concentrations of amidated and glycine- extended glucagon-like peptide I in humans. Diabetes. 1994;43:535–9.
23. Rosenkilde M, Reichkendler MH, Auerbach P, et al. Appetite regulation in overweight, sedentary men after different amounts of endurance exercise: a randomized controlled trial. J Appl Physiol (1985). 2013;115(11):1599–609.
24. Rye JA, Rye SL, Tessaro I, Coffindaffer J. Perceived barriers to physical activity according to stage of change and body mass index in the west virginia wisewoman population. Womens Health Issues. 2009;19(2):126–34.
25. Sim AY, Wallman KE, Fairchild TJ, Guelfi KJ. High-intensity intermittent exercise attenuates ad-libitum energy intake. Int J Obes (Lond). 2014;38(3):417–22.
26. Sim AY, Wallman KE, Fairchild TJ, Guelfi KJ. Effects of high-intensity intermittent exercise training on appetite regulation. Med Sci Sports Exerc. 2015;47(11):2441–9.
27. Stunkard AJ, Messick S. The Three-Factor Eating Questionnaire to measure dietary restraint, desinhibition and hunger. J Psychosom Res. 1985;29(1):71–83.
28. Trapp EG, Chisholm DJ, Freundl J, Boutcherl SH. The effects of high-intensity intermittent exercise training on fat loss and fasting insulin levels of young women. Int J Obes (Lond). 2008;32(4): 684–91.
29. Trost SG, Owen N, Bauman AE, Sallis JF, Brown W. Correlates of adults' participation in physical activity: review and update. Med Sci Sports Exerc. 2002;34(12):1996–2001.
Keywords:

HUNGER; GLP-1; PYY3–36; GHRELIN; HIGH-INTENSITY INTERMITTENT TRAINING

© 2017 American College of Sports Medicine