The effect of exercise on body mass is likely to be mediated not only directly by increasing energy expenditure but also indirectly by modulating appetite and subsequently energy intake (EI) (22). A large body of evidence has accumulated for the last two decades suggesting, first, a link between inactivity and disrupted homeostatic mechanisms involved in appetite control (16,19,24,26,32), which could contribute to positive energy balance and obesity, and second, that exercise has the ability to “fine-tune” these physiological mechanisms (19,23,35). Exercise has been shown to improve energy compensation by leading to a more sensitive eating behavior in response to previous EI (21). However, most of the evidence is cross sectional (19,35) or derived from normal-weight individuals (231). The mechanisms whereby this occurs have yet to be clarified, but exercise has been shown to induce changes in appetite-regulating hormones, which may contribute to a better appetite control (22).
Appetite-regulating hormones can be grouped, in a simplistic way, in two categories: episodic signals, which are periodically released, mainly from the gastrointestinal (GI) tract, in response to feeding or fasting, signaling acute nutritional state; and tonic signals, which are more uniformly released, mainly by the adipose tissue, in proportion to the amount of stored lipids, signaling chronic nutritional state (2). The first category of peripheral GI signals belongs to ghrelin, an orexigenic hormone released in response to fasting, and several hormones involved in satiation and/or satiety such as cholecystokinin (CCK), glucagon-like peptide-1 (GLP-1), and polypeptide YY (PYY), which are released in response to feeding. The second category of peripheral signals includes leptin, released mainly by the adipose tissue, and insulin, released by the pancreas, whose secretion is directly proportional to the amount of fat stores. However, insulin also shows episodic characteristics because it is released periodically in response to food consumption.
Obestatin and glucose insulinotropic peptide (GIP) may also be involved in appetite control. Obestatin, a peptide encoded by the ghrelin gene, was initially shown to have anorexigenic properties (36); however, more recent research has questioned these findings, and at present, the real effect of obestatin on food intake and body mass regulation remains unknown (8). GIP is best known for its incretin action; however, accumulating evidence over the last decade seems to suggest that GIP may also play a role in appetite control and body mass regulation by stimulating food intake (3,27–30).
We have recently shown that exercise-induced weight loss, in previously sedentary overweight and obese individuals, results in an increased drive to eat in the fasting state, with an increase in fasting subjective hunger together with acylated ghrelin plasma concentrations However, this increase in fasting orexigenic drive seems to be balanced by an improved satiety response to a meal and improved sensitivity of the appetite control system. We reported a significant suppression of acylated ghrelin after a fixed meal, which was not present before the exercise intervention, and a tendency toward increased late postprandial release of GLP-1 and PYY (21). However, little is known regarding the effect of chronic exercise on other appetite-related hormones.
The aim of the present study was therefore to examine the effect of chronic exercise in previously sedentary overweight/obese volunteers on: 1) fasting and postprandial plasma concentrations of obestatin, CCK, leptin, and GIP and 2) the accuracy of energy compensation in response to covert preload manipulation.
MATERIALS AND METHODS
Twenty-two overweight and obese healthy sedentary individuals were recruited for this study through 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 of the 3 months before the study. Those dieting to lose weight, those with weight unstable on the last 3 months (>2 kg), or those with a restraint score derived from the Three Factor Eating Behavior Questionnaire (33) >12 were not included in the study. Seven women did not complete the study for different reasons, including unplanned pregnancy, injury, and time constrains. Fifteen participants (eight men and seven women), with a mean body mass index of 31.3 ± 3.3 kg·m−2 and a mean age of 36.9 ± 8.3 yr, completed 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 (Midt-Norge, Trondheim, Norway). Written informed consent was obtained from all participants before enrolling in the study. The data reported here are part of a larger metabolic study that has been published previously (21).
Participants underwent a 12-wk supervised exercise program (5 d·wk−1) consisting of treadmill walking or running and were asked to maintain their normal diet throughout the study. The exercise program was individually designed to induce a 500-kcal energy deficit per session at approximately 75% maximal heart rate (HRmax). Several measurements were performed before and after the intervention, including body mass and composition, maximal oxygen consumption (V˙O2max), resting metabolic rate, habitual food intake, fasting and postprandial blood samples, and subjective sensations of appetite. For more details about the study methodology, see Martins et al. (21). The preload test-meal paradigm was also used to assess the ability of the participants to regulate their food intake in response to preload covert manipulation.
Before and immediately after the 12-wk exercise intervention (at least 48 h after the last exercise session to exclude acute effects of exercise), participants came to the laboratory on three occasions: (a) to measure the release of appetite-related hormones in fasting and after a standard breakfast, (b) for an appetite challenge day where a low-energy preload (LEP) was used, and (c) for an appetite challenge day where a high-energy preload (HEP) was used. These measurements are described in detail in the next section.
Fasting and postprandial release of appetite-related hormones
On each occasion, an intravenous cannula was inserted into an antecubital vein. Two fasting baseline blood samples (−10 and 0 min) were taken, and participants were instructed to consume a standard breakfast (time = zero) (consisting of bread, orange juice, milk, cheese, and jam: 600 kcal, 17% protein, 35% fat, and 48% carbohydrate) within 10 min. Blood samples were collected at 30-min intervals for a period of 3 h. Venous blood was collected into potassium EDTA-coated tubes containing 500 KIU aprotinin (Pentapharm, Basle, Switzerland) per milliliter of whole blood. Samples were then centrifuged at 2000g for 10 min and kept at –20°C for later analyses. All samples were batch analyzed at the end of the study to reduce interassay variability.
Obestatin and leptin were quantified using human-specific RIA kits (Phoenix Pharmaceuticals, CA, and Millipore, Billerica, MA, respectively), CCK using an extensively characterized “in-house” RIA method (27), and GIP using an ELISA kit (Millipore). The sensitivity of the assays was 50 pg·mL−1 for obestatin, 0.5 ng·mL−1 for leptin, 0.3 pmol·L−1 for CCK, and 8.2 pg·mL−1 for GIP. 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 of <10% for all assays. Because of the expected low concentrations of obestatin in these samples, they were previously concentrated by freeze drying.
Preload–test meal paradigm.
Using a randomized single-blind crossover design, participants consumed either an HEP or an LEP at baseline (week 0) on different days of the week (appetite challenge days), at least 2 d apart to avoid participants from becoming bored with the pasta lunch and to prevent any crossover effects. This was repeated after the 12-wk exercise intervention (week 13), with participants acting as their own controls.
On the morning of each appetite challenge day, participants were asked to consume their usual breakfast before 8.00 a.m. and to eat exactly the same type and amount of food in each of the four “appetite challenge days.” Compliance with this recommendation was achieved by asking each participant to describe in detail his breakfast on the first preload session and the researcher recording this information. On the morning of subsequent “appetite challenge days,” participants were asked what they had eaten for breakfast to ensure that this was the same as previous days. After the standard breakfast, participants were instructed not to eat or drink anything except water. Participants were also asked to avoid alcohol consumption and exercise during the 24 h before and during each appetite challenge day and to record everything they ate and drank on the day before each “appetite challenge day.” No significant differences on 24-h energy or macronutrient intake on the day before each preload session were observed.
The appetite challenge days after the exercise intervention were performed at least 48 h after the last exercise session to exclude acute effects of exercise. Subjective sensations of hunger (“How hungry do you feel?”), fullness (“How full do you feel?”), desire to eat (“How much would you like to eat?”), and prospective food consumption (“How much do you think you can eat?”) were assessed, throughout each appetite challenge day, using 10-cm self-rated visual analog scales (VAS) as previously described (11). Participants sat quietly after arrival, and instructions regarding the completion of the VAS were provided. The first VAS was completed to assess baseline appetite feelings. Preloads were then presented, and participants were asked to consume them within 5 min. Further VAS were completed immediately after the preload and then at 20, 40, and 60 min. During this period, participants stayed in the research unit, but they were permitted to write and read. The ad libitum lunch test meal was served 60 min after the preload, and participants ate in an individual booth and instructed to eat until comfortably full. After lunch, participants left the unit and were instructed to record all they consumed until the end of the day in a food diary to estimate cumulative EI over that day (lunch plus subsequent food intake till bedtime). To facilitate and improve the accuracy of estimating portion sizes, participants were provided with a booklet with pictures of the most commonly eaten food/dishes in Norway (validated for the Norwegian population, with each food/dish being presented at four different portions sizes). Participants were also taught how to use the booklet and how to ensure that all food eaten was reported. Dietary analysis was performed using Mat på Data 5.0 program (Landsforeningen for kosthold og helse, Oslo, Norway).
Two preloads with different energy contents (HEP and LEP) but similar sensory properties were used in this study. They were presented as 450-mL flavored milkshakes differing in energy content by 361 kcal, which was achieved by adding maltodextrin to the LEP (Table 1).
Food intake after preload consumption was assessed using an ad libitum test-meal lunch, consisting of pasta with tomato sauce and cheese, which was provided in excess of expected consumption (total energy and macronutrient value: 2091 kcal, 76 g protein, 65 g fat, and 295 g carbohydrates). Food was weighed before participants ate and reweighed after each participant had finished eating to allow calculations of energy and macronutrient intake. All dietary analysis was performed according to manufacturers’ nutritional composition information. Participants were presented with exactly the same type and amount of food on all four appetite challenge days.
Statistical analysis and treatment of data.
Statistical analysis was carried out using the Statistical Package for the Social Sciences (SPSS Inc., Chicago, IL). All variables were checked regarding their normal distribution using the Shapiro–Wilk test. Statistical significance was assumed at P < 0.05, unless otherwise stated.
Differences in the fasting plasma concentrations of the hormones measured, before and after the exercise intervention, were assessed by paired sample t-tests. The effect of time and exercise (pre- versus postintervention) on postprandial concentrations of the hormones was assessed by a repeated-measures ANOVA.
The effect of preload (HEP versus LEP) and exercise (preexercise versus postexercise) on EI, at the test-meal lunch and on cumulative EI over the day, was assessed by a repeated-measures ANOVA.
Energy compensation was calculated as the difference in EI at the pasta lunch (or over the day − cumulative EI) between the two study days (HEP versus LEP) divided by the difference in preload energy content and expressed as a percentage (13). This was labeled as the compensation index. The area under the curve (AUC) for each subjective feeling of appetite was calculated for a period of 1 h (from before preload till before pasta lunch) using the trapezoidal rule. The effect of preload (HEP versus LEP) and exercise (preexercise versus postexercise) on the AUC for each subjective feeling of appetite was assessed by a repeated-measures ANOVA.
Anthropometry and Fitness Level
The 12-wk exercise intervention resulted in significant reductions in body mass (96.1 ± 11.0 to 92.6 ± 11.7 kg, P < 0.0001) and percentage of body fat (35.3% ± 5.6% to 33.5% ± 5.9%, P < 0.0001) and a significant increase in V˙O2max (32.9 ± 6.6 to. 37.7 ± 5.9 mL·kg−1·min−1, P < 0.0001). For more details on the effect of this exercise program on metabolism, see Martins et al. (21).
Plasma Concentrations of Hormones
The fasting plasma concentrations of the hormones measured, before and after the 12-wk exercise intervention, are shown in Table 2. The exercise intervention resulted in a significant reduction in leptin and GIP fasting concentrations (t = 2.51, df = 14, P = 0.025; t = 2.83, df = 14, P = 0.014, respectively), but there were no significant changes in obestatin or CCK fasting concentrations.
No significant effect of time, exercise, or interaction was observed on obestatin plasma concentrations (Fig. 1A).
A significant effect of time (F 5,8 = 23.7, P < 0.0001) but no effect of exercise or interaction was observed on CCK concentrations, which increased after the standard breakfast, peaking at 90–120 min after ingestion (Fig. 1B).
A significant effect of time (F 5,10 = 6.25, P < 0.01) and exercise (F 1,14 = 5.74, P < 0.05) but no interaction was observed on leptin concentrations, which decreased after the standard breakfast, with a nadir at 60 min after ingestion (Fig. 1C) and were lower after the exercise intervention compared with baseline concentrations.
A significant effect of time (F 5,9 = 19.85, P < 0.0001), but no effect of exercise or interaction was observed on GIP concentrations, which increased after the standard breakfast, peaking at 90–120 min after ingestion (Fig. 1D).
Test-meal lunch EI.
EI at lunch after the LEP and HEP before and after the exercise intervention is shown in Figure 2. ANOVA revealed a significant effect of preload on lunch EI (kcal). EI after the LEP was significantly higher compared with the HEP (615 ± 323 vs 545 ± 268 kcal; F 1,13 = 6.09, P < 0.05). No significant effects of exercise or interaction were observed on lunch EI. There was also no significant effect of exercise on short-term energy compensation (%) at lunch (15.5% ± 33.6% vs 23.4% ± 42.0%, t = −0.63, df = 14, P > 0.05).
There was a significant exercise–preload interaction (F 1,13 = 8.89, P = 0.011) on cumulative EI but no significant effects of exercise or preload (Fig. 3). Post hoc analysis revealed that, at baseline, cumulative EI after HEP was significantly higher than after the LEP (2118 ± 775 vs 1803 ± 421 kcal, P = 0.001), whereas after the 12-wk exercise program, the opposite was observed: cumulative EI after the HEP was significantly lower than after the LEP (1799 ± 649 vs 2044 ± 763 kcal, P = 0.001).
When energy compensation was calculated using cumulative EI over the day, the exercise intervention exerted a significant increase in the accuracy of compensatory adjustment for the different preloads (preintervention = −87 ± 196 vs postintervention = 68% ± 165%, t = −2.93, df = 14, P = 0.011). There were no significant effects of exercise, preload, or interaction on the relative (%) contribution of each macronutrient to 24 h cumulative EI.
Changes in subjective sensations of appetite.
The AUC for subjective sensations of hunger, fullness, desire to eat, and prospective food consumption (before preload intake to before lunch −60-min period) are presented in Figure 4. ANOVA showed no significant effects of exercise, preload, or interaction on the AUC of any subjective sensations of appetite.
To the best of our knowledge, this is the first study to assess the effect of chronic supervised exercise, in overweight/obese sedentary individuals, on CCK and obestatin secretion before and after a meal. Counterintuitively, 12 wk of exercise inducing an average 3.5-kg weight loss had no significant effect on either fasting or postprandial concentrations of CCK or obestatin in plasma, in previously sedentary overweight/obese individuals. Previous studies on the effect of acute exercise on CCK secretion had reported an increase in fasting (1) and postprandial concentrations in normal-weight individuals (31). Evidence regarding the effect of chronic exercise on CCK concentrations in plasma was, however, up to now, limited to one study showing no change in fasting CCK plasma concentrations after a 4-wk exercise program in active men (1). Regarding obestatin, no significant changes had been described after a single bout of resistance exercise in both men (6) and women (7) and after six consecutive days of anaerobic exercise in normal-weight women (20).
In the present study, we also assessed changes in circulating leptin and GIP concentrations in response to 12 wk of exercise, in previously sedentary overweight/obese individuals, and found a significant reduction in fasting GIP concentrations and both fasting and postprandial leptin concentrations in plasma. Studies on the effect of chronic exercise on GIP secretion are relatively scarce. Three months of exercise in obese women were shown to reduce both fasting and postprandial GIP concentrations in plasma (18). However, another study in older obese adults with impaired glucose tolerance reported no change in fasting or postprandial GIP concentrations after 12 wk of exercise (14). This is unexpected given that the exercise intervention used and the magnitude of weight loss achieved were very similar to those described in our study. It is possible that older subjects with impaired glucose tolerance may need a bigger stimulus to alter GIP secretion. If GIP has indeed orexigenic properties, as previously discussed in the Introduction section (3,27–29), then the significant reduction in fasting GIP concentrations observed in the present study is not in line with the raised fasting hunger feelings and ghrelin concentrations reported previously in response to exercise-induced weight loss (21). It needs to be acknowledged that a recent study (9) reported no change in either fasting hunger or acylated ghrelin after 12 wk of aerobic or resistance exercise inducing a significant fat mass loss. As highlighted by the authors, lower fat mass loss, lower volume of exercise, and the inclusion of only men versus men and women compared with our study (19) are likely to have contributed to the discrepancy.
Although the effect of chronic exercise on leptin secretion has been extensively studied and a consensus exists that exercise, when associated with fat mass loss, is generally followed by a significant reduction in fasting leptin concentrations (17), very little is known regarding the effect of chronic exercise on postprandial leptin secretion. The present study has shown that exercise-induced weight loss leads not only to a reduction in leptin concentrations in fasting, as expected, but also in the postprandial state. Leptin is the primary adipose hormone that conveys information to the hypothalamus concerning the status of energy stores. It helps to regulate energy homeostasis and body mass by suppressing appetite and increasing energy expenditure (25). Moreover, leptin seems to be able to modulate the responsivity to satiety signals, such as CCK (4), and has been shown to be correlated with satiety ratings in the postexercise period (34). The increase in hunger levels and the reduction in leptin concentrations experienced by obese individuals after weight loss were previously shown to be correlated (10). The reduced leptin concentration observed after chronic exercise might reflect improved leptin transport and thus greater leptin sensitivity (34). The second aim of this study was to examine the effect of chronic exercise on the accuracy of energy compensation in response to covert preload energy manipulation in overweight/obese individuals. The results suggest that exercise improves appetite control in overweight/obese individuals by leading to a more sensitive eating behavior in response to previous EI. These findings confirm previous cross-sectional data reporting a more accurate energy compensation in active versus inactive individuals (19,35) and confirm our previous findings in normal-weight individuals involved in a 6-wk exercise program (23). These results are also consistent with the outcome of another study showing that 12 wk of exercise increases the satiating effect of a fixed meal in obese individuals (15). However, in two of the previous three studies (23,35), and in agreement with the findings of the present study, no difference in energy compensation was observed at the laboratory test meal, but only after including the self-reported measures of EI, for the remainder of the day, after leaving the laboratory. In the present study, sedentary overweight/obese individuals had a higher cumulative EI after the HEP compared with after the LEP at baseline, denoting a weak compensatory response. A 12-wk exercise intervention was able to normalize that pattern, with participants being able to subconsciously detect difference in preload energy content by eating less throughout the day after the HEP compared with after the LEP. Energy compensation during the course of the day (expressed as a percentage) increased significantly from an average of −87% ± 196% at baseline to 68% ± 165% after the exercise intervention, despite a very large interindividual response. Interestingly, this improvement in energy compensation was not correlated with weight loss. This finding, combined with previous evidence demonstrating improvement in energy compensation during a 24-h period after exercise in normal-weight individuals, in the absence of weight loss (23), suggests that the improvements may be independent of weight loss.
We acknowledge that this study has some limitations. First, we did not include a no-exercise control group and, as such, we cannot be sure that other factors, apart from exercise, could not have played a role. Although familiarization with the test procedure could have played a role, pre- and postintervention testing were more than 3 months apart, making it unlikely to have played a major role. Second, it is intriguing that the improvement in energy compensation with exercise was only observed outside the laboratory environment. This is likely to be a result of the type of laboratory test meal used: pasta with tomato sauce and cheese. It is possible that there was a delay in compensation, or that participants were better able to compensate in their natural environment (outside the laboratory). Although self-reported diet records used to estimate EI after leaving the laboratory may be susceptible to inaccurate reporting, it is unlikely that a systematic error has occurred. Energy expenditure outside the laboratory was not measured. Therefore, it is possible that compensation occurred in the form of activity-based energy expenditure; however, there is no strong evidence for this elsewhere. Although we found no significant exercise–preload interaction on the AUC of any of the subjective feelings of appetite assessed, a closer analysis of Figure 4 reveals nonsignificant patterns of change that are consistent with an improved discriminatory response between preloads with the exercise intervention. At baseline, AUC hunger after the HEP was higher than after the LEP (denoting an abnormal response). After the exercise intervention, the effect was reversed. A similar pattern was observed for AUC fullness. The AUC values for desire to eat and prospective food consumption were very similar after each preload at baseline, whereas the AUC values after HEP were lower than after the LEP after the exercise intervention. The lack of significance may be a result of the small sample size, and more studies with large samples need to be carried out to confirm this finding.
The question that naturally arises from the previous findings is what physiological changes, at the level of the appetite control system, occurred with exercise that can explain this improved discriminatory ability to differentiate between preloads with different energy contents. GI hormones involved in short-term appetite control, such as the orexigenic hormone ghrelin and the satiation/satiety hormones CCK, GLP-1, and PYY are potential candidates. However, in this study, we did not measure the release of these hormones after each preload at baseline and after the 12-wk exercise intervention. Other potential candidates are via changes in substrate metabolism (12) or alteration in the neuronal responses to food (3) in response to training.
We had previously shown that exercise-induced weight loss induces a dual effect on appetite control by increasing the drive to eat in the fasting state (early morning) while improving the satiating effect of a meal and the sensitivity of the appetite control system in overweight/obese individuals (15,21). The results of the present study showing reduced leptin plasma concentrations in the absence of changes in fasting CCK or obestatin and a better compensatory response to an energy preload extend and strengthen our previous findings. More studies are needed to completely understand the implications of reduced GIP fasting levels in response to chronic exercise in the context of appetite control.
Catia Martins was supported by a postdoctoral grant (SFRH/BPD/36940/2007) from Fundação para a Ciência e Tecnologia (Portugal) under the Third European Union Community Support Program. Running costs were covered by a grant from the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology in partnership with St. Olav Hospital (Trondheim, Norway).
The authors thank all the participants that took part in this study for their time and enthusiasm and Mrs. Sissel Salater and Mrs. Trude Haugen for their help with cannulation.
The authors’ responsibilities were as follows: CM, NAK, and JEB were involved in the design of the study; CM was involved in data collection and statistical analysis; and BK was involved in clinical support and study implementation. JFR was responsible for the plasma CCK measurements. All the authors were involved in manuscript writing.
The authors declare that there is no conflict of interest that would prejudice the impartiality of this scientific work.
Moreover, the results of the present study do not constitute endorsement by the American College of Sports Medicine.
1. Bailey DM, Davies B, Castell LM, Newsholme EA, Calam J. Physical activity and normobaric hypoxia: independent modulators of peripheral cholecystokinin
metabolism in man. J Appl Physiol
. 2001; 90: 105–13.
2. Blundell JE. Perspective on the central control of appetite. Obesity Res
. 2006; 14: 160–3S.
3. Cornier MA, Melanson EL, Salzberg AK, Bechtell JL, Tregellas JR. The effects of exercise on the neuronal response to food cues. Physiol Behav
. 2012; 105 (4): 1028–34
4. Daousi C, Wilding JPH, Aditya S, et al.. Effects of peripheral administration of synthetic human glucose-dependent insulinotropic peptide (GIP) on energy expenditure and subjective appetite sensations in healthy normal weight subjects and obese patients with type 2 diabetes. Clin Endocrinol (Oxf)
. 2009; 71: 195–201.
5. Emond M, Schwartz GJ, Ladenheim EE, Moran TH. Central leptin
modulates behavioral and neural responsivity to CCK. Am J Physiol
. 1999; 276: R1545–9.
6. Ghanbari-Niaki A. Ghrelin and glucoregulatory hormone responses to a single circuit resistance exercise in male college students. Clin Biochem
. 2006; 10: 966–70.
7. Ghanbari-Niaki A, Saghebjoo M, Rahbarizadeh F, Hedayati M, Rajabi H. A single circuit-resistance exercise has no effect on plasma obestatin
levels in female college students. Peptides
. 2008; 29: 487–90.
8. Gourcerol G, St-Pierre DH, Tache Y. Lack of obestatin
effects on food intake: should obestatin
be renamed ghrelin-associated peptide (GAP)? Regulatory Peptides
. 2007; 141 (1–3): 1–7.
9. Guelfi KJ, Donges CE, Duffield R. Beneficial effects of 12 weeks of aerobic compared with resistance exercise training on perceived appetite in previousy sedentary overweight and obese men. Metabolism
. 2013; 62: 235–43.
10. Heini AF, Lara-Castro C, Kirk KA, Considine RV, Caro JF, Weinsier RL. Association of leptin
and hunger-satiety ratings in obese women. Int J Obes
. 1998; 22: 1084–7.
11. 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; 41A: 244–57.
12. Hopkins M, Jeukendrup A, King NA, Blundell JE. The relationship between substrate metabolism, exercise and appetite control: does glycogen availability influence the motivation to eat, energy intake or food choice? Sports Med
. 2011; 41 (6): 507–21.
13. Johnson SL, Birch LL. Parents’ and children’s adiposity and eating style. Peptides
. 1994; 84: 653–61.
14. Kelly KR, Brooks LM, Solomon TP, Kashyap SR, O’Leary VB, Kirwan JP. The glucose-dependent insulinotropic polypeptide and glucose-stimulated insulin response to exercise training and diet in obesity. Am J Physiol Endocrinol Metab
. 2009; 296: E1269–74.
15. 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: 921–7.
16. King NA, Tremblay A, Blundell JE. Effects of exercise on appetite control: implications for energy balance. Med Sci Sports Exerc
. 1997; 29 (8): 1076–89.
17. Kraemer RR, Chu H, Castracane VD. Leptin
and Exercise. Exp Biol Med
. 2002; 227: 701–8.
18. Krotkiewski M, Björntorp P, Holm G, et al.. Effects of physical training on insulin, connecting peptide (C-peptide), gastric inhibitory polypeptide (GIP) and pancreatic polypeptide (PP) levels in obese subjects. Int J Obes
. 1984; 8: 193–9.
19. Long SJ, Hart K, Morgan LM. The ability of habitual exercise to influence appetite and food intake in response to high- and low-energy preloads in man. Br J Nutr
. 2002; 87: 517–23.
20. Manshouri M, Ghanbari-Niaki A, Kraemer RR, Shemshaki A. Time course alterations of plasma obestatin
and growth hormone levels in response to short-term anaerobic exercise training in college women. Appl Physiol Nutr Metab
. 2008; 33: 1246–9.
21. 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: 1609–16.
22. Martins C, Morgan L, Truby H. A review of the effects of exercise on appetite regulation: an obesity perspective. Int J Obes
. 2008; 32: 1337–47.
23. Martins C, Truby H, Morgan LM. Short-term appetite control in response to a 6-week exercise programme in sedentary volunteers. Br J Nutr
. 2007; 98: 834–42.
24. Mayer J, Roy P, Mitra KP. Relation between caloric intake, body weight, and physical work: studies in an industrial male population in West Bengal. Am J Clin Nutr
. 1956; 4: 169–75.
25. Morris DL, Rui L. Recent advances in understanding leptin
signaling and leptin
resistance. Am J Physiol Endocrinol Metab
. 2009; 297: E1247–59.
26. Murgatroyd PR, Goldberg GR, Leahy FE, Gilsenan MB, Prentice AM. Effects of inactivity and diet composition on human energy balance. Int J Obes
. 1999; 23: 1269–75.
27. Raben A, Andersen HB, Christensen NJ, Madsen J, Holst JJ, Astrup A. Evidence for an abnormal postprandial response to a high-fat meal in women predisposed to obesity. Am J Physiol
. 1994; 267: E549–59.
28. Raben A, Andersen K, Karberg MA, Holst JJ, Astrup A. Acetylation of or beta-cyclodextrin addition to potato beneficial effect on glucose metabolism and appetite sensations. Am J Clin Nutr
. 1997; 66: 304–14.
29. Raben A, Tagliabue A, Christensen NJ, Madsen J, Holst JJ, Astrup A. Resistant starch: the effect on postprandial glycemia, hormonal response, and satiety. Am J Clin Nutr
. 1994; 60: 544–51.
30. Rehfeld JF. Accurate measurement of cholecystokinin
in plasma. Clin Chem
. 1998; 44: 991–1001.
31. Sliwowsk Z, Lorens K, Konturek SJ, Bielanski W, Zoladz JA. Leptin
, gastrointestinal and stress hormones in response to exercise in fasted or fed subjects and before or after blood donation. J Physiol Pharmacol
. 2001; 52: 53–70.
32. Stubbs RJ, Hughes DA, Johnstone AM, Horgan GW, King N, Blundell JE. A decrease in physical activity affects appetite, energy, and nutrient balance in lean men feeding ad libitum. Am J Clin Nutr
. 2004; 79: 62–9.
33. Stunkard AJ, Messick S. The Three-Factor Eating Questionnaire to measure dietary restraint, desinhibition and hunger. J Psychosom Res
. 1985; 29: 71–83.
34. Tsofliou F, Pitsiladis YP, Malkova D, Wallace AM, Lean ME. Moderate physical activity permits acute coupling between serum leptin
and appetite-satiety measures in obese women. Int J Obes Relat Metab Disord
. 2003; 27 (11): 1332–9.
35. van Walleghen EL, Orr JS, Gentile CL, Davy KP, Davy BM. Habitual physical activity differentially affects acute and short-term energy intake regulation in young and older adults. Int J Obes
. 2007; 31: 1277–85.
36. Zhang JV, Ren PG, Avsian-Kretchmer O, Luo C-W, Rauch R, Klein C, Hsueh AJW. Obestatin
, a peptide encoded by the ghrelin gene, opposes ghrelin’s effects on food intake. Science
. 2005; 310: 996–9.