# Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity

Alicia Fillon, Kristine Beaulieu, Maud Miguet, Mélina Bailly, Graham Finlayson, Valérie Julian, Julie Masurier, Bruno Pereira, Martine M. Duclos, Yves Boirie, et al.

► To cite this version:

Alicia Fillon, Kristine Beaulieu, Maud Miguet, Mélina Bailly, Graham Finlayson, et al. Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity. International Journal of Pediatric Obesity, 2020, 15 (9), pp.e12651. 10.1111/ijpo.12651. hal-03013137

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# Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity

Alicia Fillon, Kristine Beaulieu, Maud Miguet, Mélina Bailly, Graham Finlayson, Valérie Julian, Julie Masurier, Bruno Pereira, Martine Duclos, Yves Boirie, et al.

<figure><img src="image_1.png" /></figure>

## ► To cite this version:

Alicia Fillon, Kristine Beaulieu, Maud Miguet, Mélina Bailly, Graham Finlayson, et al. Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity. International Journal of Pediatric Obesity, 2020, 15 (9), pp.e12651. 10.1111/ijpo.12651. hal-03013137

HAL Id: hal-03013137

https://uca.hal.science/hal-03013137v1

Submitted on 25 Jun 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
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UNIVERSITY OF LEEDS

This is a repository copy of *Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity*.

White Rose Research Online URL for this paper:
https://eprints.whiterose.ac.uk/168421/

Version: Accepted Version

**Article:**

Fillon, A, Beaulieu, K orcid.org/0000-0001-8926-6953, Miguet, M et al. (8 more authors) (2020) Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity. Pediatric Obesity, 15 (9). e12651. ISSN 2047-6310

https://doi.org/10.1111/ijpo.12651

© 2020 World Obesity Federation. This is the peer reviewed version of the following article: Fillon, A, Beaulieu, K, Miguet, M, et al. Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity. Pediatric Obesity. 2020; 15:e12651. , which has been published in final form at https://doi.org/10.1111/ijpo.12651. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

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White Rose
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Universities of Leeds, Sheffield & York

eprints@whiterose.ac.uk
https://eprints.whiterose.ac.uk/
<figure><img src="image_3.png" /></figure>

This is a repository copy of *Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity*.

White Rose Research Online URL for this paper:
https://eprints.whiterose.ac.uk/168421/

Version: Accepted Version

**Article:**

Fillon, A, Beaulieu, K orcid.org/0000-0001-8926-6953, Miguet, M et al. (8 more authors) (2020) Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity. Pediatric Obesity, 15 (9). e12651. ISSN 2047-6310

https://doi.org/10.1111/ijpo.12651

© 2020 World Obesity Federation. This is the peer reviewed version of the following article: Fillon, A, Beaulieu, K, Miguet, M, et al. Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity. Pediatric Obesity. 2020; 15:e12651. , which has been published in final form at https://doi.org/10.1111/ijpo.12651. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

**Reuse**

Items deposited in White Rose Research Online are protected by copyright, with all rights reserved unless indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of the full text version. This is indicated by the licence information on the White Rose Research Online record for the item.

**Takedown**

If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request.

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White Rose
university consortium
Universities of Leeds, Sheffield & York

eprints@whiterose.ac.uk
https://eprints.whiterose.ac.uk/
1

2

3

4

# Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity

## Abstract

5

6

**Background.** While the beneficial effects of exercise on appetite might depend on its timing during the day or relative to a meal, this remains poorly explored in youth.

7

8

**Objectives.** To examine the importance of meal timing (+30vs.+90minutes) after performing exercise on energy intake, appetite and food reward in adolescents with obesity.

9

10

11

12

13

**Methods.** Eighteen adolescents with obesity randomly completed 3 conditions: i) lunch (12:00pm) set 30min after a rest session (11:00am); ii) lunch (12:00pm) set 30min after an exercise session (11:00am)(MEAL-30); iii) lunch (01:00pm) set 90min after an exercise session (11:00am)(MEAL-90). Lunch and dinner *ad libitum* energy intake was assessed, food reward (LFPQ) assessed before and after lunch, and before dinner, appetite sensations were assessed at regular intervals.

14

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17

**Results.** Energy intake was lower at MEAL-90 than MEAL-30 and CON at lunch (p<0.05 and p<0.01, respectively) and lunch+dinner combined(p<0.001). A decrease in intake (g) of protein, fat and carbohydrate was observed. Post-exercise hunger was lower on MEAL-90 compared with CON. No condition effects were found at lunch for food reward.

18

19

20

**Conclusions.** Delaying the timing of the meal after exercise might help affect energy balance by decreasing *ad libitum* energy intake without increasing hunger and by improving satiety in adolescents with obesity.

21

22

**Key words.** Exercise Timing, Appetite, Energy Intake, Obesity, Adolescent, Food reward

23

**Clinical Trial reference:** NCT03968458
1

2

3

4

# Delayed meal timing after exercise is associated with reduced appetite and energy intake in adolescents with obesity

## Abstract

5

6

**Background.** While the beneficial effects of exercise on appetite might depend on its timing during the day or relative to a meal, this remains poorly explored in youth.

7

8

**Objectives.** To examine the importance of meal timing (+30vs.+90minutes) after performing exercise on energy intake, appetite and food reward in adolescents with obesity.

9

10

11

12

13

**Methods.** Eighteen adolescents with obesity randomly completed 3 conditions: i) lunch (12:00pm) set 30min after a rest session (11:00am); ii) lunch (12:00pm) set 30min after an exercise session (11:00am)(MEAL-30); iii) lunch (01:00pm) set 90min after an exercise session (11:00am)(MEAL-90). Lunch and dinner *ad libitum* energy intake was assessed, food reward (LFPQ) assessed before and after lunch, and before dinner, appetite sensations were assessed at regular intervals.

14

15

16

17

**Results.** Energy intake was lower at MEAL-90 than MEAL-30 and CON at lunch (p<0.05 and p<0.01, respectively) and lunch+dinner combined(p<0.001). A decrease in intake (g) of protein, fat and carbohydrate was observed. Post-exercise hunger was lower on MEAL-90 compared with CON. No condition effects were found at lunch for food reward.

18

19

20

**Conclusions.** Delaying the timing of the meal after exercise might help affect energy balance by decreasing *ad libitum* energy intake without increasing hunger and by improving satiety in adolescents with obesity.

21

22

**Key words.** Exercise Timing, Appetite, Energy Intake, Obesity, Adolescent, Food reward

23

**Clinical Trial reference:** NCT03968458
25 **Introduction**

26 While practitioners and clinicians constantly work on the improvement of their weight loss
27 interventions, trying to identify the best exercise characteristics (modality, intensity, duration, etc.) to
28 prescribe, the need to also consider the timing of exercise has been recently suggested ¹. Recent
29 studies effectively show that the beneficial effects of exercise might also depend on its timing during
30 the day or its delay/position regarding a meal ¹. Some studies for instance showed that performing
31 acute exercise one to three hours after a meal could enhance the glycemic response in patients with
32 type II diabetes 2-5 while others showed a better postprandial lipemia response when exercise was
33 performed immediately before the meal 6-8.

34 Looking at the alarming progression of overweight and obesity among children and adolescents, it
35 seems necessary to deepen our understanding on the effects of exercise on overall energy balance, in
36 order to optimize our weight loss strategies. It is now clear that physical exercise does not only impact
37 energy expenditure, it also affects energy intake and appetite control in youth and adolescents with
38 obesity 9. The current literature mainly investigated the effect of exercise duration 10,11, intensity 12-14
39 or modality 15 on subsequent food intake, appetite sensations or food reward, while the potential role
40 played by the timing of exercise remains poorly explored 16.

41 In 2017, Mathieu and collaborators assessed the effects of exercising immediately before or after a
42 lunch meal in primary school children on overall energy balance ¹⁷. Although they did not observe any
43 difference on energy intake between conditions (before or after the meal), their results highlight the
44 beneficial effect of performing pre-meal moderate-to-vigorous over low-intensity exercise on
45 subsequent energy intake ¹⁷. More recently, similar results were obtained among adolescents with
46 obesity whose energy intake and food reward remained unchanged whether the adolescents
47 performed 30 min of cycling exercise (65% VO₂peak) immediately before or after their lunch meal ¹⁸.
48 Interestingly, others investigated the potential effect of the delay between an acute exercise bout and
49 the following meal on energy intake and appetite. In their work, Albert and colleagues compared the
50 effects of exercising (treadmill running at 70% VO₂max) 45 min or 180 min before lunch, in normal
25 **Introduction**

26 While practitioners and clinicians constantly work on the improvement of their weight loss
27 interventions, trying to identify the best exercise characteristics (modality, intensity, duration, etc.) to
28 prescribe, the need to also consider the timing of exercise has been recently suggested ¹. Recent
29 studies effectively show that the beneficial effects of exercise might also depend on its timing during
30 the day or its delay/position regarding a meal ¹. Some studies for instance showed that performing
31 acute exercise one to three hours after a meal could enhance the glycemic response in patients with
32 type II diabetes 2-5 while others showed a better postprandial lipemia response when exercise was
33 performed immediately before the meal 6-8.

34 Looking at the alarming progression of overweight and obesity among children and adolescents, it
35 seems necessary to deepen our understanding on the effects of exercise on overall energy balance, in
36 order to optimize our weight loss strategies. It is now clear that physical exercise does not only impact
37 energy expenditure, it also affects energy intake and appetite control in youth and adolescents with
38 obesity 9. The current literature mainly investigated the effect of exercise duration 10,11, intensity 12-14
39 or modality 15 on subsequent food intake, appetite sensations or food reward, while the potential role
40 played by the timing of exercise remains poorly explored 16.

41 In 2017, Mathieu and collaborators assessed the effects of exercising immediately before or after a
42 lunch meal in primary school children on overall energy balance ¹⁷. Although they did not observe any
43 difference on energy intake between conditions (before or after the meal), their results highlight the
44 beneficial effect of performing pre-meal moderate-to-vigorous over low-intensity exercise on
45 subsequent energy intake ¹⁷. More recently, similar results were obtained among adolescents with
46 obesity whose energy intake and food reward remained unchanged whether the adolescents
47 performed 30 min of cycling exercise (65% VO₂peak) immediately before or after their lunch meal ¹⁸.
48 Interestingly, others investigated the potential effect of the delay between an acute exercise bout and
49 the following meal on energy intake and appetite. In their work, Albert and colleagues compared the
50 effects of exercising (treadmill running at 70% VO₂max) 45 min or 180 min before lunch, in normal
weight adolescents ¹⁹. The authors observed an 11% reduction of the adolescents' *ad libitum* energy intake and a 23% decrease in fat intake when the exercise was performed 45 min before lunch, compared to 180 min. Moreover, there were no difference in terms of appetite sensations and no energy compensation at the following snack or dinner. Our research group recently examined the effect of the exercise-meal delay on energy intake, appetite and food reward among adolescents with obesity ²⁰. According to our results, a 30-min cycling exercise bout (65% VO₂max) performed 60 min before lunch favored a 14% reduction of *ad libitum* energy intake while the same exercise performed 180 min before lunch did not affect the adolescents' energy intake. While appetite sensations (hunger, fullness, prospective food consumption and desire to eat) did not differ between conditions, our results also showed a significantly lower pre-meal explicit liking for high-fat relative to low-fat foods when the exercise was set close to the meal, suggesting the implication of the food reward system ²⁰. Altogether, these results seem to show a beneficial effect of exercising close to a meal on overall energy balance in adolescents.

Although these studies compared exercises of similar characteristics (e.g. duration, modality, intensity), their metabolic demand might have been different due to their divergent delay from breakfast, which might have important implications when it comes to subsequent energy intake.

Indeed, it has been shown that the metabolic activity during exercise, particularly the contribution of the energy substrates, is different depending on the delay between a breakfast and this exercise ²¹.

The substrate oxidation during exercise, especially the rate of carbohydrate oxidation has been associated with subsequent energy intake ²², particularly in adults with obesity ²³,²⁴. Investigating the effect of the timing of exercise on appetite and energy intake needs to consider not only its delay with the following meal but also the time interval between exercise and the previous food intake.

In that context, the aim was to examine the importance of meal timing (+30 or +90 minutes) after performing exercise on energy intake, appetite and food reward in adolescents with obesity.

75

## 76 Materials and methods
weight adolescents <sup>19</sup>. The authors observed an 11% reduction of the adolescents' *ad libitum* energy intake and a 23% decrease in fat intake when the exercise was performed 45 min before lunch, compared to 180 min. Moreover, there were no difference in terms of appetite sensations and no energy compensation at the following snack or dinner. Our research group recently examined the effect of the exercise-meal delay on energy intake, appetite and food reward among adolescents with obesity <sup>20</sup>. According to our results, a 30-min cycling exercise bout (65% VO<sub>2max</sub>) performed 60 min before lunch favored a 14% reduction of *ad libitum* energy intake while the same exercise performed 180 min before lunch did not affect the adolescents' energy intake. While appetite sensations (hunger, fullness, prospective food consumption and desire to eat) did not differ between conditions, our results also showed a significantly lower pre-meal explicit liking for high-fat relative to low-fat foods when the exercise was set close to the meal, suggesting the implication of the food reward system <sup>20</sup>. Altogether, these results seem to show a beneficial effect of exercising close to a meal on overall energy balance in adolescents.

Although these studies compared exercises of similar characteristics (e.g. duration, modality, intensity), their metabolic demand might have been different due to their divergent delay from breakfast, which might have important implications when it comes to subsequent energy intake.

Indeed, it has been shown that the metabolic activity during exercise, particularly the contribution of the energy substrates, is different depending on the delay between a breakfast and this exercise <sup>21</sup>.

The substrate oxidation during exercise, especially the rate of carbohydrate oxidation has been associated with subsequent energy intake <sup>22</sup>, particularly in adults with obesity <sup>23,24</sup>. Investigating the effect of the timing of exercise on appetite and energy intake needs to consider not only its delay with the following meal but also the time interval between exercise and the previous food intake.

In that context, the aim was to examine the importance of meal timing (+30 or +90 minutes) after performing exercise on energy intake, appetite and food reward in adolescents with obesity.

75

## 76 Materials and methods
77 **Participants**

Eighteen adolescents with obesity (according to ²⁵) aged 12-15 years (Tanner stage 3-4) were enrolled in this study (12 boys (12.6 ± 1.2 years) and 6 girls (13.0 ± 1.6 years)). They were recruited through the local Pediatric Obesity Center (Tza Nou, La Bourboule, France), based on the following main inclusion criteria: i) to be free of any medication known to influence appetite or metabolism; ii) to be free of any contraindication to physical activity; iii) to be classified as physically inactive (taking part in less than 2 hours of physical activity per week as assessed using the International Physical Activity Questionnaire -IPAQ ²⁶). This study was conducted in accordance with the Helsinki declaration and all the adolescents and their legal representative received information sheets and signed consent forms as requested by the local ethical authorities (Human Ethical Committee authorization reference: 2019-A00530-57; Clinical Trial reference: NCT03968458).

88 **1.1. Design**

After a preliminary medical inclusion visit performed by a pediatrician to control for the ability of the adolescents to complete the study, they were asked to perform a maximal aerobic test and their body composition was assessed by dual-energy x-ray absorptiometry (DXA). The adolescents thereafter completed the three following experimental sessions (one week apart) in randomized order: i) lunch (at 12:00pm) set 30 min after a rest session (at 11:00 am) ii) lunch (at 12:00pm) set 30 min after an exercise session (at 11:00am; MEAL-30); iii) lunch (at 1:00pm) set 90 min after an exercise session (at 11:00am; MEAL-90). On the three occasions, participants received a standardized breakfast (08:00am) and were asked to remain at rest (CON) or to cycle for 30 min at 11:00am and eat either 30 min (on MEAL-30; lunch at 12:00pm) or 90 min (on MEAL-90; lunch at 1:00pm) after exercise. Dinner was provided to the adolescents at 6:30pm. They were asked to complete the Leeds Food Preference Questionnaire (LFPQ) ²⁷ before and after the lunch meal and before dinner. Lunch and dinner energy intake were assessed via *ad libitum* buffet-style meals. Appetite sensations were measured at regular intervals throughout the day. Outside the experimental conditions and between the two *ad libitum* test meals, the adolescents stayed in the laboratory, devoid of any food cues, and were requested not
77 **Participants**

Eighteen adolescents with obesity (according to ²⁵) aged 12-15 years (Tanner stage 3-4) were enrolled in this study (12 boys (12.6 ± 1.2 years) and 6 girls (13.0 ± 1.6 years)). They were recruited through the local Pediatric Obesity Center (Tza Nou, La Bourboule, France), based on the following main inclusion criteria: i) to be free of any medication known to influence appetite or metabolism; ii) to be free of any contraindication to physical activity; iii) to be classified as physically inactive (taking part in less than 2 hours of physical activity per week as assessed using the International Physical Activity Questionnaire -IPAQ ²⁶). This study was conducted in accordance with the Helsinki declaration and all the adolescents and their legal representative received information sheets and signed consent forms as requested by the local ethical authorities (Human Ethical Committee authorization reference: 2019-A00530-57; Clinical Trial reference: NCT03968458).

88 **1.1. Design**

After a preliminary medical inclusion visit performed by a pediatrician to control for the ability of the adolescents to complete the study, they were asked to perform a maximal aerobic test and their body composition was assessed by dual-energy x-ray absorptiometry (DXA). The adolescents thereafter completed the three following experimental sessions (one week apart) in randomized order: i) lunch (at 12:00pm) set 30 min after a rest session (at 11:00 am) ii) lunch (at 12:00pm) set 30 min after an exercise session (at 11:00am; MEAL-30); iii) lunch (at 1:00pm) set 90 min after an exercise session (at 11:00am; MEAL-90). On the three occasions, participants received a standardized breakfast (08:00am) and were asked to remain at rest (CON) or to cycle for 30 min at 11:00am and eat either 30 min (on MEAL-30; lunch at 12:00pm) or 90 min (on MEAL-90; lunch at 1:00pm) after exercise. Dinner was provided to the adolescents at 6:30pm. They were asked to complete the Leeds Food Preference Questionnaire (LFPQ) ²⁷ before and after the lunch meal and before dinner. Lunch and dinner energy intake were assessed via *ad libitum* buffet-style meals. Appetite sensations were measured at regular intervals throughout the day. Outside the experimental conditions and between the two *ad libitum* test meals, the adolescents stayed in the laboratory, devoid of any food cues, and were requested not
to engage in any moderate-to-vigorous physical activity and mainly completed sedentary activities such as reading, homework or board games. Figure 1 details the whole design of the study.

Figure 1

## 1.2. Anthropometric characteristics and body composition

Body mass and height were measured wearing light clothing while bare-footed, using a digital scale and a standard wall-mounted stadiometer, respectively. Body mass index (BMI) was calculated as body mass (kg) divided by height squared (m²) and the sex and age dependent French reference curves were used to obtain the BMI percentile ²⁸. Fat mass (FM) and fat-free mass (FFM) were assessed by dual-energy X-ray absorptiometry (DXA) following standardized procedures (QDR4500A scanner, Hologic, Waltham, MA, USA). These measurements were obtained during the preliminary visit by a trained technician.

## 1.3. Peak oxygen uptake test (VO₂peak)

Each adolescent performed a VO₂peak test on a traditional ergometer ²⁹. The initial power was set at 30W during 3 minutes, followed by a 15W increment every minute until exhaustion. The adolescents were strongly encouraged by the experimenters throughout the test to perform their maximal effort. Maximal criteria were: heart rate >90% of the theoretical maximum heart rate (210 – 0.65 × age), respiratory exchange ratio (RER = VO₂/VO₂) > 1.1 and/or VO₂ plateau. Cardiac electrical activity (Ultima SeriesTM, Saint Paul, MN) and heart rate (Polar V800) were monitored and the test was coupled with a measurement of breath-by-breath gas exchanges (BreezeSuite Software, Saint Paul, MN), that determined VO₂ and VO₂. Volumes and gases were calibrated before each test. VO₂peak was defined as the average of the last 30 s of exercise before exhaustion.

## 1.4. Experimental conditions

*Rest condition (CON):* During this condition, the adolescents were asked to remain quiet and were not allowed to engage in any physical activity. They were asked to stay seated on a comfortable chair (30
to engage in any moderate-to-vigorous physical activity and mainly completed sedentary activities such as reading, homework or board games. Figure 1 details the whole design of the study.

Figure 1

## 1.2. Anthropometric characteristics and body composition

Body mass and height were measured wearing light clothing while bare-footed, using a digital scale and a standard wall-mounted stadiometer, respectively. Body mass index (BMI) was calculated as body mass (kg) divided by height squared (m²) and the sex and age dependent French reference curves were used to obtain the BMI percentile ²⁸. Fat mass (FM) and fat-free mass (FFM) were assessed by dual-energy X-ray absorptiometry (DXA) following standardized procedures (QDR4500A scanner, Hologic, Waltham, MA, USA). These measurements were obtained during the preliminary visit by a trained technician.

## 1.3. Peak oxygen uptake test (VO₂peak)

Each adolescent performed a VO₂peak test on a traditional ergometer ²⁹. The initial power was set at 30W during 3 minutes, followed by a 15W increment every minute until exhaustion. The adolescents were strongly encouraged by the experimenters throughout the test to perform their maximal effort. Maximal criteria were: heart rate >90% of the theoretical maximum heart rate (210 – 0.65 × age), respiratory exchange ratio (RER = VO₂/VO₂) > 1.1 and/or VO₂ plateau. Cardiac electrical activity (Ultima SeriesTM, Saint Paul, MN) and heart rate (Polar V800) were monitored and the test was coupled with a measurement of breath-by-breath gas exchanges (BreezeSuite Software, Saint Paul, MN), that determined VO₂ and VO₂. Volumes and gases were calibrated before each test. VO₂peak was defined as the average of the last 30 s of exercise before exhaustion.

## 1.4. Experimental conditions

Rest condition (CON): During this condition, the adolescents were asked to remain quiet and were not allowed to engage in any physical activity. They were asked to stay seated on a comfortable chair (30
127 min) between 11:00am and 11:30am, not being allowed to talk, read, watch TV or to complete any
128 intellectual tasks. Energy expenditure was assessed during the 30-min rest period using portable
129 indirect calorimetry (K4b², COSMED Inc., Rome, Italy).

130 *Lunch condition 30 min after exercise (MEAL-30)*: Between 11:00am and 11:30am, the participants
131 performed a 30-min moderate-intensity exercise bout (65% VO₂peak) on a cycle ergometer. The
132 intensity was controlled by heart rate records (Polar V800) using the results from the maximal aerobic
133 capacity testing. Exercise-induced energy expenditure was calculated based on the results obtained
134 during the maximal oxygen uptake test.

135 *Lunch condition 90 min after exercise (MEAL-90)*: The adolescents performed the same exercise bout
136 as MEAL-30 and at the same time, but the *ad libitum* lunch meal was served at 1:00pm (90 min after
137 the end of the exercise).

138 **1.5. Energy intake**

139 At 08:00am, the adolescents consumed a standardized calibrated breakfast (500 kcal) respecting the
140 recommendations for their age (composition: bread (50 g), butter (10 g), marmalade (15 g), yoghurt
141 (125 g) or semi-skimmed milk (20 cl), fruit or fruit juice (20 cl)). Lunch and dinner meals were served
142 *ad libitum* using a buffet-type meal. The content of the buffets was determined using a food
143 preference and habits questionnaire filled in by the adolescents during the inclusion visit, as previously
144 described ³⁰. Top rated items as well as disliked items and items liked but not usually consumed were
145 excluded to avoid over-, under- and occasional consumption. The lunch menu was beef steak, pasta,
146 mustard, cheese, yoghurt, compote, fruits and bread. The dinner menu was ham/turkey, beans,
147 mashed potato, cheese, yoghurt, compote, fruits and bread. Food items were presented in abundance
148 and the adolescents were told to eat until comfortably full. Adolescents made their choices and
149 composed their trays individually before joining their habitual table (5 adolescents per table). Lunch
150 and dinner were served in a quiet environment free of music, cellphones or television. Food items
151 were weighed by the experimenters before and after each meal. Energy intake and macronutrient
127 min) between 11:00am and 11:30am, not being allowed to talk, read, watch TV or to complete any
128 intellectual tasks. Energy expenditure was assessed during the 30-min rest period using portable
129 indirect calorimetry (K4b², COSMED Inc., Rome, Italy).

130 *Lunch condition 30 min after exercise (MEAL-30)*: Between 11:00am and 11:30am, the participants
131 performed a 30-min moderate-intensity exercise bout (65% VO₂peak) on a cycle ergometer. The
132 intensity was controlled by heart rate records (Polar V800) using the results from the maximal aerobic
133 capacity testing. Exercise-induced energy expenditure was calculated based on the results obtained
134 during the maximal oxygen uptake test.

135 *Lunch condition 90 min after exercise (MEAL-90)*: The adolescents performed the same exercise bout
136 as MEAL-30 and at the same time, but the *ad libitum* lunch meal was served at 1:00pm (90 min after
137 the end of the exercise).

138 **1.5. Energy intake**

139 At 08:00am, the adolescents consumed a standardized calibrated breakfast (500 kcal) respecting the
140 recommendations for their age (composition: bread (50 g), butter (10 g), marmalade (15 g), yoghurt
141 (125 g) or semi-skimmed milk (20 cl), fruit or fruit juice (20 cl)). Lunch and dinner meals were served
142 *ad libitum* using a buffet-type meal. The content of the buffets was determined using a food
143 preference and habits questionnaire filled in by the adolescents during the inclusion visit, as previously
described ³⁰. Top rated items as well as disliked items and items liked but not usually consumed were
145 excluded to avoid over-, under- and occasional consumption. The lunch menu was beef steak, pasta,
146 mustard, cheese, yoghurt, compote, fruits and bread. The dinner menu was ham/turkey, beans,
147 mashed potato, cheese, yoghurt, compote, fruits and bread. Food items were presented in abundance
148 and the adolescents were told to eat until comfortably full. Adolescents made their choices and
149 composed their trays individually before joining their habitual table (5 adolescents per table). Lunch
150 and dinner were served in a quiet environment free of music, cellphones or television. Food items
151 were weighed by the experimenters before and after each meal. Energy intake and macronutrient
composition (proportion of fat, carbohydrate and protein) were calculated using the software Bilnut
4.0. This methodology has been previously validated and published <sup>30</sup>. Lunch and total relative energy
intake (REI) were calculated such as: energy intake – exercise-induced energy expenditure.

1.6. **Subjective appetite sensations**

Appetite sensations were collected at regular intervals throughout the day using visual analogue scales (150-mm scales) <sup>31</sup>. Adolescents had to report their hunger, fullness, desire to eat (DTE) and prospective food consumption (PFC) before and immediately after breakfast, prior and after rest (CON) or exercise (MEAL-30 and MEAL-90), before and immediately after lunch, 30 min and 60 min after lunch, before and immediately after dinner.

1.7. Food liking and wanting

The Leeds Food Preference Questionnaire, described in greater methodological detail by Dalton and
Finlayson ³², provided measures of food preference and food reward. The adolescents were presented
with a culturally (food items and language) adapted version of the LFPQ following the recent
recommendations from Oustric and collaborators ³³. Participants were presented with an array of
pictures of individual food items common in the diet. Foods were chosen by the local research team
from a validated database to be either predominantly high (>50% energy) or low (<20% energy) in fat
but similar in familiarity, protein content, palatability and suitable for the study population. The LFPQ
has been deployed in a range of research ³² including a recent exercise/appetite trial in young French
males ³⁴ and adolescents ²⁰,³⁵,³⁶.

Explicit liking was measured by participants rating the extent to which they like each food ("How pleasant would it be to taste this food now?"). The food images were presented individually, in a randomized order and participants made their ratings using a 100-mm VAS. Implicit wanting was assessed using a forced choice methodology in which the food images were paired so that every image from each of the four food types was compared to every other type over 96 trials (food pairs). Participants were instructed to respond as quickly and accurately as they could to indicate the food
composition (proportion of fat, carbohydrate and protein) were calculated using the software Bilnut
4.0. This methodology has been previously validated and published <sup>30</sup>. Lunch and total relative energy
intake (REI) were calculated such as: energy intake – exercise-induced energy expenditure.

1.6. **Subjective appetite sensations**

Appetite sensations were collected at regular intervals throughout the day using visual analogue scales (150-mm scales) <sup>31</sup>. Adolescents had to report their hunger, fullness, desire to eat (DTE) and prospective food consumption (PFC) before and immediately after breakfast, prior and after rest (CON) or exercise (MEAL-30 and MEAL-90), before and immediately after lunch, 30 min and 60 min after lunch, before and immediately after dinner.

1.7. Food liking and wanting

The Leeds Food Preference Questionnaire, described in greater methodological detail by Dalton and
Finlayson <sup>32</sup>, provided measures of food preference and food reward. The adolescents were presented
with a culturally (food items and language) adapted version of the LFPQ following the recent
recommendations from Oustric and collaborators <sup>33</sup>. Participants were presented with an array of
pictures of individual food items common in the diet. Foods were chosen by the local research team
from a validated database to be either predominantly high (>50% energy) or low (<20% energy) in fat
but similar in familiarity, protein content, palatability and suitable for the study population. The LFPQ
has been deployed in a range of research <sup>32</sup> including a recent exercise/appetite trial in young French
males <sup>34</sup> and adolescents <sup>20,35,36</sup>.

Explicit liking was measured by participants rating the extent to which they like each food ("How pleasant would it be to taste this food now?"). The food images were presented individually, in a randomized order and participants made their ratings using a 100-mm VAS. Implicit wanting was assessed using a forced choice methodology in which the food images were paired so that every image from each of the four food types was compared to every other type over 96 trials (food pairs). Participants were instructed to respond as quickly and accurately as they could to indicate the food
they want to eat the most at that time ("Which food do you most want to eat now?"). Reaction times for all responses were covertly recorded and used to compute mean response times for each food type after adjusting for frequency of selection.

Responses on the LFPQ were used to compute mean scores for high-fat, low-fat, sweet or savoury food types (and different fat-taste combinations). Fat bias scores were calculated as the difference between the high-fat scores and the low-fat scores, with positive values indicating greater liking or wanting for high-fat relative to low-fat foods and negative values indicating greater liking or wanting for low-fat relative to high-fat foods. Sweet bias scores were calculated as the difference between the sweet and savoury scores, with positive values indicating greater liking or wanting for sweet relative to savoury foods and negative values indicating greater liking or wanting for savoury relative to sweet foods.

## 1.8. Statistical analysis

Statistical analyses were performed using Stata software, Version 13 (StataCorp, College Station, TX, US). The sample size estimation was determined according to (i) CONSORT 2010 statement, extension to randomized pilot and feasibility trials (Eldridge et al. CONSORT 2010 statement: extension to randomized pilot and feasibility trials. Pilot and Feasibility Studies (2016) 2:64) and (ii) Cohen's recommendations³⁷ who has defined effect-size bounds as : small (ES: 0.2), medium (ES: 0.5) and large (ES: 0.8, "grossly perceptible and therefore large"). So, with 15 patients by condition, an effect-size around 1 can be highlighted for a two-sided type I error at 1.7% (correction due to multiple comparisons), a statistical power greater than 80% and an intra-class correlation coefficient at 0.5 to take into account between and within participant variability. All tests were two-sided, with a Type I error set at 0.05. Continuous data was expressed as mean ± standard deviation (SD) or median [interquartile range] according to statistical distribution. The assumption of normality was assessed by using the Shapiro-Wilk test. Daily (total) area under the curve (AUC) were calculated using the trapezoidal method. Random-effects models for repeated data were performed to compare three
they want to eat the most at that time ("Which food do you most want to eat now?"). Reaction times for all responses were covertly recorded and used to compute mean response times for each food type after adjusting for frequency of selection.

Responses on the LFPQ were used to compute mean scores for high-fat, low-fat, sweet or savoury food types (and different fat-taste combinations). Fat bias scores were calculated as the difference between the high-fat scores and the low-fat scores, with positive values indicating greater liking or wanting for high-fat relative to low-fat foods and negative values indicating greater liking or wanting for low-fat relative to high-fat foods. Sweet bias scores were calculated as the difference between the sweet and savoury scores, with positive values indicating greater liking or wanting for sweet relative to savoury foods and negative values indicating greater liking or wanting for savoury relative to sweet foods.

## 1.8. Statistical analysis

Statistical analyses were performed using Stata software, Version 13 (StataCorp, College Station, TX, US). The sample size estimation was determined according to (i) CONSORT 2010 statement, extension to randomized pilot and feasibility trials (Eldridge et al. CONSORT 2010 statement: extension to randomized pilot and feasibility trials. Pilot and Feasibility Studies (2016) 2:64) and (ii) Cohen's recommendations³⁷ who has defined effect-size bounds as : small (ES: 0.2), medium (ES: 0.5) and large (ES: 0.8, "grossly perceptible and therefore large"). So, with 15 patients by condition, an effect-size around 1 can be highlighted for a two-sided type I error at 1.7% (correction due to multiple comparisons), a statistical power greater than 80% and an intra-class correlation coefficient at 0.5 to take into account between and within participant variability. All tests were two-sided, with a Type I error set at 0.05. Continuous data was expressed as mean ± standard deviation (SD) or median [interquartile range] according to statistical distribution. The assumption of normality was assessed by using the Shapiro-Wilk test. Daily (total) area under the curve (AUC) were calculated using the trapezoidal method. Random-effects models for repeated data were performed to compare three
conditions (i) considering the following fixed effects: time, condition and time x condition interaction,
and (ii) taking into account between and within participant variability (subject as random-effect). A
Sidak's type I error correction was applied to perform multiple comparisons. As proposed by some
statisticians 38,39 a particular focus will be also given to the magnitude of differences, in addition to
inferential statistical tests expressed using p-values. The normality of residuals from these models was
studied using the Shapiro-Wilk test. When appropriate, a logarithmic transformation was proposed to
achieve the normality of dependent outcome.

209

## 2. Results

Eighteen adolescents with obesity participated in this study. Their mean age was 12.7 ± 1.3 years,
body weight was 88.9 ± 23.6 kg (with a BMI of 33.3 ± 6.5 kg/m² (z-BMI 2.2 ± 0.4), with a percentage of
body fat mass of 37.6 ± 5.0 % and a FFM of 53.1 ± 12.5 kg.

The adolescents had a VO2peak of 21.8 ± 4.6 ml/min/kg. Energy expenditure induced by the exercise
(total duration 30 min) was significantly higher compared to the 30-min resting energy expenditure
(168.8 ± 43.6 kcal and 46.9 ± 14.9 kcal, respectively; p<0.001).

Table 1 details the results related to absolute and relative energy intake. At lunch, absolute ad libitum
energy intake was significantly lower in MEAL-90 than MEAL-30 and CON (p<0.05 and p<0.01,
respectively) and in MEAL-30 than CON (p<0.05). Dinner ad libitum energy intake was significantly
lower in MEAL-90 compared with MEAL-30 (p<0.01) with no difference between the exercise
conditions and CON. Total daily absolute ad libitum energy intake was significantly lower in MEAL-90
compared with both CON and MEAL-30 (p<0.001).

REI at lunch was significantly higher in CON compared with MEAL-30 and MEAL-90 (p<0.05 and
p<0.001, respectively) and total REI was significantly higher in CON compared with MEAL-90 (p<0.001).
Both lunch (p<0.05) and total REI (p<0.001) were significantly lower in MEAL-90 than MEAL-30.
conditions (i) considering the following fixed effects: time, condition and time x condition interaction,
and (ii) taking into account between and within participant variability (subject as random-effect). A
Sidak's type I error correction was applied to perform multiple comparisons. As proposed by some
statisticians 38,39 a particular focus will be also given to the magnitude of differences, in addition to
inferential statistical tests expressed using p-values. The normality of residuals from these models was
studied using the Shapiro-Wilk test. When appropriate, a logarithmic transformation was proposed to
achieve the normality of dependent outcome.

209

## 2. Results

Eighteen adolescents with obesity participated in this study. Their mean age was 12.7 ± 1.3 years,
body weight was 88.9 ± 23.6 kg (with a BMI of 33.3 ± 6.5 kg/m² (z-BMI 2.2 ± 0.4), with a percentage of
body fat mass of 37.6 ± 5.0 % and a FFM of 53.1 ± 12.5 kg.

The adolescents had a VO2peak of 21.8 ± 4.6 ml/min/kg. Energy expenditure induced by the exercise
(total duration 30 min) was significantly higher compared to the 30-min resting energy expenditure
(168.8 ± 43.6 kcal and 46.9 ± 14.9 kcal, respectively; p<0.001).

Table 1 details the results related to absolute and relative energy intake. At lunch, absolute ad libitum
energy intake was significantly lower in MEAL-90 than MEAL-30 and CON (p<0.05 and p<0.01,
respectively) and in MEAL-30 than CON (p<0.05). Dinner ad libitum energy intake was significantly
lower in MEAL-90 compared with MEAL-30 (p<0.01) with no difference between the exercise
conditions and CON. Total daily absolute ad libitum energy intake was significantly lower in MEAL-90
compared with both CON and MEAL-30 (p<0.001).

REI at lunch was significantly higher in CON compared with MEAL-30 and MEAL-90 (p<0.05 and
p<0.001, respectively) and total REI was significantly higher in CON compared with MEAL-90 (p<0.001).
Both lunch (p<0.05) and total REI (p<0.001) were significantly lower in MEAL-90 than MEAL-30.
277 immediately precede the meal. Additionally, total and dinner absolute energy intake were lower
278 during MEAL-90 only, with total daily energy intake reduced by 12% (250 kcal/day) and 16% (352
279 kcal/day) compared with CON and MEAL-30, respectively. These results are reinforced by a lower
280 lunch relative energy intake after MEAL-30 compared with CON and lower lunch and total REI during
281 MEAL-90 compared with both MEAL-30 and CON. Importantly, while most of the available evidence
282 supports the anorexigenic effect of intensive exercise<sup>13,35,41,42</sup>, our results reinforce more recent work
283 also observing reduced food intake in response to moderate-to-vigorous exercise in adolescents and
284 children with obesity<sup>40,40</sup>.

285 While available evidence indicates the beneficial effect of exercising close to a meal on subsequent
286 energy intake<sup>19,20</sup>, our results seem to suggest that more than the exercise-meal delay itself, the
287 interval between the exercise and the following eating episode is of importance.

288 A balanced buffet meal offering several items selected to avoid any over-, under- or occasional-
289 consumption (as previously validated <sup>30</sup>) was offered to adolescents which provided the opportunity
290 to also assess their macronutrient intake. While none of the relative intake of fat, protein and
291 carbohydrate were found different between conditions, their absolute consumption at lunch was
292 reduced only in MEAL-90 compared with CON, and compared with MEAL-30 for protein and lipid.
293 Interestingly, the absolute intake of carbohydrate at dinner increased in MEAL-30 compared with the
294 two other conditions. The macronutrient responses observed in MEAL-90 seem in line with Albert et
295 al. in lean adolescents <sup>19</sup> and with our previous study in adolescents with obesity <sup>20</sup>, showing reduced
296 absolute macronutrient intake after moderate exercise set at the end of the morning. The current
297 study however missed to find similar results in MEAL-30, suggesting here the potential importance of
298 the delay between the exercise and the previous eating episode (breakfast). Indeed, in these previous
299 studies, the appetitive responses to exercise set at different times of the morning, and then at
300 different delays from breakfast, were compared, meaning that despite similar duration, modality and
301 intensity, the exercise was not of similar metabolic and energetic load <sup>21</sup>, which might explain our
277 immediately precede the meal. Additionally, total and dinner absolute energy intake were lower
278 during MEAL-90 only, with total daily energy intake reduced by 12% (250 kcal/day) and 16% (352
279 kcal/day) compared with CON and MEAL-30, respectively. These results are reinforced by a lower
280 lunch relative energy intake after MEAL-30 compared with CON and lower lunch and total REI during
281 MEAL-90 compared with both MEAL-30 and CON. Importantly, while most of the available evidence
282 supports the anorexigenic effect of intensive exercise<sup>13,35,41,42</sup>, our results reinforce more recent work
283 also observing reduced food intake in response to moderate-to-vigorous exercise in adolescents and
284 children with obesity<sup>40,40</sup>.

285 While available evidence indicates the beneficial effect of exercising close to a meal on subsequent
286 energy intake<sup>19,20</sup>, our results seem to suggest that more than the exercise-meal delay itself, the
287 interval between the exercise and the following eating episode is of importance.

288 A balanced buffet meal offering several items selected to avoid any over-, under- or occasional-
289 consumption (as previously validated <sup>30</sup>) was offered to adolescents which provided the opportunity
290 to also assess their macronutrient intake. While none of the relative intake of fat, protein and
291 carbohydrate were found different between conditions, their absolute consumption at lunch was
292 reduced only in MEAL-90 compared with CON, and compared with MEAL-30 for protein and lipid.
293 Interestingly, the absolute intake of carbohydrate at dinner increased in MEAL-30 compared with the
294 two other conditions. The macronutrient responses observed in MEAL-90 seem in line with Albert et
295 al. in lean adolescents <sup>19</sup> and with our previous study in adolescents with obesity <sup>20</sup>, showing reduced
296 absolute macronutrient intake after moderate exercise set at the end of the morning. The current
297 study however missed to find similar results in MEAL-30, suggesting here the potential importance of
298 the delay between the exercise and the previous eating episode (breakfast). Indeed, in these previous
299 studies, the appetitive responses to exercise set at different times of the morning, and then at
300 different delays from breakfast, were compared, meaning that despite similar duration, modality and
301 intensity, the exercise was not of similar metabolic and energetic load <sup>21</sup>, which might explain our
results. Unfortunately, it was not possible in the present study to measure the substrate oxidation during exercise and at rest. Furthermore, it remains difficult to reach a consensus regarding the effect of acute exercise on macronutrient intake in lean adolescents and in adolescents with obesity based on the available evidence<sup>42</sup>. 302 303 304 305

Regarding the adolescents' subjective appetite sensations, our results show a lower daily (AUC) hunger and desire to eat in both exercise conditions compared with CON. Although pre-lunch hunger and PFC were significantly lower in MEAL-30 compared with CON, which could have contributed to the lower observed *ad libitum* energy intake, they remained unchanged in MEAL-90 while the decreased food consumption was even more pronounced. This inconsistency between appetite sensations and energy intake reinforce the previously described uncoupling effect of exercise between these sensations and food consumption<sup>43</sup>. Interestingly however, post-lunch sensations were identical between exercise conditions, suggesting a similar satiating effect of lunch meals despite lower intakes in MEAL-30 and particularly in MEAL-90, limiting any potential subsequent compensatory responses. This is even reinforced by the significantly reduced food intake observed at dinner in MEAL-90. This is of particular importance since energy deficits, especially when induced by reduced energy intake, have been shown to generate a subsequent compensatory rise in food intake, with physical exercise limiting or avoiding such a compensation<sup>34,44</sup>. 306 307 308 309 310 311 312 313 314 315 316 317 318

Some recent studies have highlighted the importance of considering the effect of exercise on food reward to better understand its impact on subsequent energy intake in adolescents with obesity<sup>35</sup>. We also assessed whether the liking and wanting for food could be impacted by the delay between eating episodes and exercise in this population. In 2018, Miguet and colleagues observed reduced relative preference for fat and sweet taste, and implicit wanting for high-fat foods (also using the LFPQ) in response to an *ad libitum* meal set 30 minutes after a 16-minute cycling high intensity interval exercise in a similar population<sup>35</sup>. According to the present results, none of the pre or post lunch components of liking and wanting were different between conditions. These results are contradictory 319 320 321 322 323 324 325 326
results. Unfortunately, it was not possible in the present study to measure the substrate oxidation during exercise and at rest. Furthermore, it remains difficult to reach a consensus regarding the effect of acute exercise on macronutrient intake in lean adolescents and in adolescents with obesity based on the available evidence<sup>42</sup>. 302 303 304 305

Regarding the adolescents' subjective appetite sensations, our results show a lower daily (AUC) hunger and desire to eat in both exercise conditions compared with CON. Although pre-lunch hunger and PFC were significantly lower in MEAL-30 compared with CON, which could have contributed to the lower observed *ad libitum* energy intake, they remained unchanged in MEAL-90 while the decreased food consumption was even more pronounced. This inconsistency between appetite sensations and energy intake reinforce the previously described uncoupling effect of exercise between these sensations and food consumption<sup>43</sup>. Interestingly however, post-lunch sensations were identical between exercise conditions, suggesting a similar satiating effect of lunch meals despite lower intakes in MEAL-30 and particularly in MEAL-90, limiting any potential subsequent compensatory responses. This is even reinforced by the significantly reduced food intake observed at dinner in MEAL-90. This is of particular importance since energy deficits, especially when induced by reduced energy intake, have been shown to generate a subsequent compensatory rise in food intake, with physical exercise limiting or avoiding such a compensation<sup>34,44</sup>. 306 307 308 309 310 311 312 313 314 315 316 317 318

Some recent studies have highlighted the importance of considering the effect of exercise on food reward to better understand its impact on subsequent energy intake in adolescents with obesity<sup>35</sup>. We also assessed whether the liking and wanting for food could be impacted by the delay between eating episodes and exercise in this population. In 2018, Miguet and colleagues observed reduced relative preference for fat and sweet taste, and implicit wanting for high-fat foods (also using the LFPQ) in response to an *ad libitum* meal set 30 minutes after a 16-minute cycling high intensity interval exercise in a similar population<sup>35</sup>. According to the present results, none of the pre or post lunch components of liking and wanting were different between conditions. These results are contradictory 319 320 321 322 323 324 325 326
with those from Miguet et al. (2018), especially regarding our MEAL-30 condition that had the same delay between the exercise and the meal. However, the exercise intensities were different (high intensity intermittent exercise vs. moderate intensity continuous exercise), reinforcing once more the importance of the exercise intensity in the subsequent control of energy intake. Interestingly, we can see here a significantly lower explicit liking for high-fat food immediately before dinner in MEAL-90 compared with the two others, which might contribute to the observed reduced dinner *ad libitum* food intake. Our results are however also in contradiction with some recently published from our group, showing different food reward responses depending on exercise-meal timing in adolescents with obesity ²⁰. A lower pre-meal explicit liking for high-fat relative to low-fat foods was observed when the adolescents performed 30 min of moderate intensity cycling 60 min before lunch compared with the same exercise performed 180 min before lunch ²⁰. The different LFPQ timing between MEAL-90 and the two other conditions must be considered when interpreting our results. Indeed, food reward was assessed pre- and post- lunch meaning that its delay from exercise was different, which might have affected the results. Although there is a growing interest in the effect of exercise on food reward in this population, evidence remains too limited to draw any conclusion and further studies using standardized designs are needed.

The present results must be interpreted in light of some limitations. First, as for the other published studies examining the timing of exercise relative to a meal ¹⁶,¹⁷,¹⁹,²⁰, the lack of direct evaluation of the adolescents' oxygen consumption and substrate oxidation using indirect calorimeters, as well as the lack of a lean control group to examine the potential weight status effect, are the two main limitations. Although the laboratory-based nature of this work constitutes a strength as it allows a better control of the adolescents' activity and intake, it might also not be representative of their habitual daily free-living setting, such as the school setting for instance, as previously underlined by Mathieu et al. in healthy adolescents ¹⁷. Finally, the lack of tracking of the adolescents' food intake over 24 to 48 hours for practical reasons also limits the interpretation of our results ¹².
with those from Miguet et al. (2018), especially regarding our MEAL-30 condition that had the same delay between the exercise and the meal. However, the exercise intensities were different (high intensity intermittent exercise vs. moderate intensity continuous exercise), reinforcing once more the importance of the exercise intensity in the subsequent control of energy intake. Interestingly, we can see here a significantly lower explicit liking for high-fat food immediately before dinner in MEAL-90 compared with the two others, which might contribute to the observed reduced dinner *ad libitum* food intake. Our results are however also in contradiction with some recently published from our group, showing different food reward responses depending on exercise-meal timing in adolescents with obesity ²⁰. A lower pre-meal explicit liking for high-fat relative to low-fat foods was observed when the adolescents performed 30 min of moderate intensity cycling 60 min before lunch compared with the same exercise performed 180 min before lunch ²⁰. The different LFPQ timing between MEAL-90 and the two other conditions must be considered when interpreting our results. Indeed, food reward was assessed pre- and post- lunch meaning that its delay from exercise was different, which might have affected the results. Although there is a growing interest in the effect of exercise on food reward in this population, evidence remains too limited to draw any conclusion and further studies using standardized designs are needed.

The present results must be interpreted in light of some limitations. First, as for the other published studies examining the timing of exercise relative to a meal ¹⁶,¹⁷,¹⁹,²⁰, the lack of direct evaluation of the adolescents' oxygen consumption and substrate oxidation using indirect calorimeters, as well as the lack of a lean control group to examine the potential weight status effect, are the two main limitations. Although the laboratory-based nature of this work constitutes a strength as it allows a better control of the adolescents' activity and intake, it might also not be representative of their habitual daily free-living setting, such as the school setting for instance, as previously underlined by Mathieu et al. in healthy adolescents ¹⁷. Finally, the lack of tracking of the adolescents' food intake over 24 to 48 hours for practical reasons also limits the interpretation of our results ¹².
In line with the present work, another potential important factor, while not addressed in the current study, is the timing of exercise (and food intake) with regards to circadian/diurnal rhythms. Emerging evidence suggests that the timing of exercise <sup>45,46</sup> (and food intake <sup>47,48</sup>) impact body weight regulation. Any effects observed from exercise-meal delays may be a result of an interaction with circadian/diurnal oscillations occurring relative to sleep/wake times. Future studies should propose a more complete and integrative exploration of the chronobiologic regulations of energy intake and overall energy metabolism in such adolescents with obesity. Indeed, not only the timings of exercise and /or energy intake should be considered, but also their interactions with the adolescents' sleep, to better understand and potentially regulate their 24-hour circadian rhythm <sup>49,50</sup>. Some key physiological actors of this circadian clock, such as ghrelin and leptin for instance, who are particularly involved in the control of appetite and respondents to sleep and exercise should be mainly considered <sup>51</sup>.

363

## Conclusion

To conclude, the present study reinforces the interest in the timing of exercise relative to a meal to affect overall energy balance in youth with obesity; highlighting the importance of the time interval between both the exercise and the previous eating episode, and the exercise and the following meal. According to these results, delaying the timing of the meal after exercise might help reduce energy balance by decreasing *ad libitum* energy intake without increasing hunger and by improving satiety in adolescents with obesity. Future studies should question the importance of the exercise-meal timing on the longer term. While further acute and chronic studies are needed, these results contribute to the current limited body of evidence in the area and seem important in order to optimize weight loss strategies.

374

## Conflicts of interest statement

None and this research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
In line with the present work, another potential important factor, while not addressed in the current study, is the timing of exercise (and food intake) with regards to circadian/diurnal rhythms. Emerging evidence suggests that the timing of exercise <sup>45,46</sup> (and food intake <sup>47,48</sup>) impact body weight regulation. Any effects observed from exercise-meal delays may be a result of an interaction with circadian/diurnal oscillations occurring relative to sleep/wake times. Future studies should propose a more complete and integrative exploration of the chronobiologic regulations of energy intake and overall energy metabolism in such adolescents with obesity. Indeed, not only the timings of exercise and /or energy intake should be considered, but also their interactions with the adolescents' sleep, to better understand and potentially regulate their 24-hour circadian rhythm <sup>49,50</sup>. Some key physiological actors of this circadian clock, such as ghrelin and leptin for instance, who are particularly involved in the control of appetite and respondents to sleep and exercise should be mainly considered <sup>51</sup>.

363

## Conclusion

To conclude, the present study reinforces the interest in the timing of exercise relative to a meal to affect overall energy balance in youth with obesity; highlighting the importance of the time interval between both the exercise and the previous eating episode, and the exercise and the following meal. According to these results, delaying the timing of the meal after exercise might help reduce energy balance by decreasing *ad libitum* energy intake without increasing hunger and by improving satiety in adolescents with obesity. Future studies should question the importance of the exercise-meal timing on the longer term. While further acute and chronic studies are needed, these results contribute to the current limited body of evidence in the area and seem important in order to optimize weight loss strategies.

374

## Conflicts of interest statement

None and this research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
378

379

380 Author contributions

381 AF and DT conceived experiments. AF, MM and MB carried out experiments, AF and DT analysed data.

382 KB was involved in writing the paper and all authors had final approval of the submitted and published

383 versions.

384

385 Acknowledgements

386 The authors are grateful to all of the adolescents that participated in the program, and to the Nutrition

387 Obesity Ambulatory Hospital (UGECAM) that provided their generous support.

388
378

379

380 Author contributions

381 AF and DT conceived experiments. AF, MM and MB carried out experiments, AF and DT analysed data.

382 KB was involved in writing the paper and all authors had final approval of the submitted and published

383 versions.

384

385 Acknowledgements

386 The authors are grateful to all of the adolescents that participated in the program, and to the Nutrition

387 Obesity Ambulatory Hospital (UGECAM) that provided their generous support.

388
389 **Table legends**

390 Table 1: Absolute and Relative Energy Intake in response the three conditions.

391 Table 2: Macronutrient Intake in response the three conditions.

392 Table 3: Pre- and Post-test meal food reward on the three experimental conditions

393

394

395 **Figures legends**

396 Figure 1 : Study design

397 Figure 2 : Daily appetite sensations and AUC for hunger, fullness, prospective food consumption and

398 desire to eat

399
389 **Table legends**

390 Table 1: Absolute and Relative Energy Intake in response the three conditions.

391 Table 2: Macronutrient Intake in response the three conditions.

392 Table 3: Pre- and Post-test meal food reward on the three experimental conditions

393

394

395 **Figures legends**

396 Figure 1 : Study design

397 Figure 2 : Daily appetite sensations and AUC for hunger, fullness, prospective food consumption and

398 desire to eat

399
<table><caption>400 Table 1: Absolute and Relative Energy Intake in response to the three conditions.</caption><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="3">CON</th><th rowspan="2">p</th><th colspan="3">ES</th></tr><tr><th>Mean (SD)</th><th>MEAL-30<br>Mean (SD)</th><th>MEAL-90<br>Mean (SD)</th><th>CON vs. MEAL-30</th><th>CON vs. MEAL-90</th><th>MEAL-30 vs.<br>MEAL-90</th></tr></thead><tbody><tr><td rowspan="3">Energy Intake (kcal)</td><td>Lunch</td><td>1380 (185)</td><td>1347 (313)*</td><td>1168 (234)**<sup>a</sup></td><td>0.0143</td><td>-0.12[-0.60, 0.35]</td><td>-0.71[-1.19, -0.24]</td><td>0.59[0.11, 1.06]</td></tr><tr><td>Dinner</td><td>796 (294)</td><td>931 (260)</td><td>748 (245)<sup>b</sup></td><td>0.0363</td><td>0.48[0.00, 0.96]</td><td>-0.20[-0.67, 0.28]</td><td>0.68[0.20, 1.15]</td></tr><tr><td>Total</td><td>2175 (330)</td><td>2277 (476)</td><td>1925 (360)***<sup>c</sup></td><td>0.0001</td><td>0.27[-0.21, 0.74]</td><td>-0.80[-1.28, -0.33]</td><td>1.07[0.59, 1.54]</td></tr><tr><td rowspan="2">Relative Energy Intake (kcal)</td><td>Lunch</td><td>1337 (188)</td><td>1172 (313)*</td><td>1006 (246)***<sup>a</sup></td><td>0.0003</td><td>-0.56[-1.03, -0.08]</td><td>-1.08[-1.56, -0.61]</td><td>0.52[0.04, 1.00]</td></tr><tr><td>Total</td><td>2119 (332)</td><td>2110 (489)</td><td>1755 (366)***<sup>c</sup></td><td>&lt;0.0001</td><td>-0.11[-0.58, 0.37]</td><td>-1.16[-1.63, -0.68]</td><td>1.06[0.59, 1.54]</td></tr></tbody></table>

401 CON: control condition; MEAL-30: Test meal 30 min after exercise; MEAL-90: Test meal 90 min after exercise; SD: Standard

402 Deviation; ES: Effect Size; *p<0.05 vs. CON; **p<0.01 vs. CON; ***p<0.001 vs. CON; $^{ap}<0.05$ MEAL-30 vs. MEAL-90;

403 $^{b}$p<0.01 MEAL-30 vs. MEAL-90; $^{c}$p<0.001 MEAL-30 vs. MEAL-90; ES: post hoc effect size

404
<table><caption>400 Table 1: Absolute and Relative Energy Intake in response to the three conditions.</caption><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="3">CON</th><th rowspan="2">p</th><th colspan="3">ES</th></tr><tr><th>Mean (SD)</th><th>MEAL-30<br>Mean (SD)</th><th>MEAL-90<br>Mean (SD)</th><th>CON vs. MEAL-30</th><th>CON vs. MEAL-90</th><th>MEAL-30 vs.<br>MEAL-90</th></tr></thead><tbody><tr><td rowspan="3">Energy Intake (kcal)</td><td>Lunch</td><td>1380 (185)</td><td>1347 (313)*</td><td>1168 (234)**<sup>a</sup></td><td>0.0143</td><td>-0.12[-0.60, 0.35]</td><td>-0.71[-1.19, -0.24]</td><td>0.59[0.11, 1.06]</td></tr><tr><td>Dinner</td><td>796 (294)</td><td>931 (260)</td><td>748 (245)<sup>b</sup></td><td>0.0363</td><td>0.48[0.00, 0.96]</td><td>-0.20[-0.67, 0.28]</td><td>0.68[0.20, 1.15]</td></tr><tr><td>Total</td><td>2175 (330)</td><td>2277 (476)</td><td>1925 (360)***<sup>c</sup></td><td>0.0001</td><td>0.27[-0.21, 0.74]</td><td>-0.80[-1.28, -0.33]</td><td>1.07[0.59, 1.54]</td></tr><tr><td rowspan="2">Relative Energy Intake (kcal)</td><td>Lunch</td><td>1337 (188)</td><td>1172 (313)*</td><td>1006 (246)***<sup>a</sup></td><td>0.0003</td><td>-0.56[-1.03, -0.08]</td><td>-1.08[-1.56, -0.61]</td><td>0.52[0.04, 1.00]</td></tr><tr><td>Total</td><td>2119 (332)</td><td>2110 (489)</td><td>1755 (366)***<sup>c</sup></td><td>&lt;0.0001</td><td>-0.11[-0.58, 0.37]</td><td>-1.16[-1.63, -0.68]</td><td>1.06[0.59, 1.54]</td></tr></tbody></table>

401 CON: control condition; MEAL-30: Test meal 30 min after exercise; MEAL-90: Test meal 90 min after exercise; SD: Standard

402 Deviation; ES: Effect Size; *p<0.05 vs. CON; **p<0.01 vs. CON; ***p<0.001 vs. CON; $^{ap}<0.05$ MEAL-30 vs. MEAL-90;

403 $^{b}$p<0.01 MEAL-30 vs. MEAL-90; $^{c}$p<0.001 MEAL-30 vs. MEAL-90; ES: post hoc effect size

404
<table><caption>405 Table 2: Macronutrient Intake in response the three conditions.</caption><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="3">CON</th><th colspan="3">ES</th></tr><tr><th>Mean (SD)</th><th>MEAL-30<br>Mean (SD)</th><th>MEAL-90<br>Mean (SD)</th><th>P</th><th>CON vs. MEAL-30</th><th>CON vs. MEAL-90</th><th>MEAL-30 vs.<br>MEAL-90</th></tr></thead><tbody><tr><td rowspan="3">Proteins (g)</td><td>Lunch</td><td>73.8 (11.5)</td><td>71.9 (17.2)</td><td>60.7 (13.9)**<sup>b</sup></td><td>0.0059</td><td>-0.13[-0.61, 0.34]</td><td>-0.76[-1.24, -0.29]</td><td>0.63[0.15, 1.10]</td></tr><tr><td>Dinner</td><td>42.0 (18.4)</td><td>46.8 (14.4)</td><td>37.2 (13.2)<sup>a</sup></td><td>0.1811</td><td>0.25[-0.22, 0.73]</td><td>-0.30[-0.78, 0.17]</td><td>0.56[0.08, 1.03]</td></tr><tr><td>Total</td><td>115.9 (22.6)</td><td>118.7 (23.8)</td><td>98.8 (19.4)***<sup>c</sup></td><td>0.0007</td><td>0.08[-0.40, 0.55]</td><td>-0.85[-1.32, -0.37]</td><td>0.93[0.45, 1.40]</td></tr><tr><td rowspan="3">Proteins (%)</td><td>Lunch</td><td>21.5 (2.3)</td><td>21.4 (3.0)</td><td>20.8 (2.3)</td><td>0.5108</td><td>0.05[-0.42, 0.53]</td><td>-0.07[-0.55, 0.40]</td><td>0.23[-0.25, 0.70]</td></tr><tr><td>Dinner</td><td>20.8 (5.2)</td><td>19.9 (3.1)</td><td>20.1 (3.6)</td><td>0.8811</td><td>0.17[-0.31, 0.64]</td><td>0.01[-0.46, 0.49]</td><td>-0.06[-0.53, 0.42]</td></tr><tr><td>Total</td><td>21.3 (2.5)</td><td>21.0 (2.0)</td><td>20.6 (2.3)</td><td>0.6248</td><td>0.10[-0.38, 0.58]</td><td>-0.05[-0.53, 0.42]</td><td>0.14[-0.33, 0.62]</td></tr><tr><td rowspan="3">Lipids (g)</td><td>Lunch</td><td>45.4 (9.6)</td><td>45.0 (14.2)</td><td>38.1 (12.5)*<sup>a</sup></td><td>0.0146</td><td>-0.06[-0.53, 0.42]</td><td>-0.54[-1.01, -0.06]</td><td>0.48[0.06, 1.01]</td></tr><tr><td>Dinner</td><td>28.8 (19.0)</td><td>33.8 (15.1)</td><td>26.1 (14.3)<sup>a</sup></td><td>0.0642</td><td>0.33[-0.15, 0.80]</td><td>-0.18[-0.66, 0.30]</td><td>0.51[0.03, 0.98]</td></tr><tr><td>Total</td><td>74.3 (18.0)</td><td>78.8 (19.9)</td><td>65.8 (19.1)*<sup>b</sup></td><td>0.0123</td><td>0.25[-0.23, 0.72]</td><td>-0.54[-1.01, -0.06]</td><td>0.79[0.31, 1.26]</td></tr><tr><td rowspan="3">Lipids (%)</td><td>Lunch</td><td>29.8 (5.8)</td><td>30.3 (8.0)</td><td>29.2 (7.3)</td><td>0.1910</td><td>0.05[-0.42, 0.53]</td><td>-0.07[-0.55, 0.40]</td><td>0.13[-0.35, 0.60]</td></tr><tr><td>Dinner</td><td>30.0 (12.9)</td><td>31.3 (10.6)</td><td>29.7 (9.8)</td><td>0.0277</td><td>0.17[-0.31, 0.64]</td><td>0.01[-0.46, 0.49]</td><td>0.15[-0.32, 0.63]</td></tr><tr><td>Total</td><td>30.7 (5.8)</td><td>31.2 (4.8)</td><td>30.5 (5.7)</td><td>0.9655</td><td>0.10[-0.38, 0.58]</td><td>-0.05[-0.53, 0.42]</td><td>0.15[-0.32, 0.63]</td></tr><tr><td rowspan="3">CHO (g)</td><td>Lunch</td><td>166.7 (39.4)</td><td>160.8 (52.8)</td><td>144.2 (34.6)*</td><td>0.1649</td><td>-0.14[-0.62, 0.33]</td><td>-0.52[-0.99, -0.04]</td><td>0.37[-0.10, 0.85]</td></tr><tr><td>Dinner</td><td>92.8 (31.5)</td><td>109.9 (31.5)*</td><td>91.9 (29.4)<sup>a</sup></td><td>0.0269</td><td>0.52[0.04, 0.99]</td><td>-0.036[-0.54, 0.41]</td><td>0.58[0.11, 1.06]</td></tr><tr><td>Total</td><td>259.5 (56.1)</td><td>270.7 (70.0)</td><td>233.9 (49.7)<sup>a</sup></td><td>0.0751</td><td>0.17[-0.31, 0.64]</td><td>-0.45[-0.92, 0.03]</td><td>0.61[0.14, 1.09]</td></tr><tr><td rowspan="3">CHO (%)</td><td>Lunch</td><td>48.0 (7.6)</td><td>47.5 (10.5)</td><td>49.5 (9.1)</td><td>0.2149</td><td>0.06[-0.53, 0.42]</td><td>0.15[-0.33, 0.62]</td><td>-0.20[-0.68, 0.27]</td></tr><tr><td>Dinner</td><td>49.7 (15.6)</td><td>48.9 (12.4)</td><td>50.7 (10.7)</td><td>0.0840</td><td>-0.01[-0.48, 0.47]</td><td>0.13[-0.34, 0.61]</td><td>-0.14[-0.61, 0.34]</td></tr><tr><td>Total</td><td>47.8 (7.4)</td><td>47.4 (6.1)</td><td>48.7 (7.3)</td><td>0.9547</td><td>-0.05[-0.53, 0.42]</td><td>0.14[-0.34, 0.61]</td><td>-0.19[-0.67, 0.28]</td></tr></tbody></table>

406 CON: control condition; MEAL-30: Test meal 30 minutes after exercise; MEAL-90: Test meal 90 minutes after exercise; SD:

407 Standard Deviation; *p<0.05 vs. CON ; **p<0.01 vs. CON ; ***p<0.001 vs. CON ; p<0.05 MEAL-30 vs. MEAL-90 ; p<0.01

408 MEAL-30 vs. MEAL-90 ; c<0.001 MEAL-30 vs. MEAL-90; ES: Effect Size; CHO: Carbohydrates; ES: post hoc effect size.

409
<table><caption>405 Table 2: Macronutrient Intake in response the three conditions.</caption><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="3">CON</th><th rowspan="2">P</th><th colspan="3">ES</th></tr><tr><th>Mean (SD)</th><th>MEAL-30 (SD)</th><th>MEAL-90 (SD)</th><th>CON vs. MEAL-30</th><th>CON vs. MEAL-90</th><th>MEAL-30 vs. MEAL-90</th></tr></thead><tbody><tr><td rowspan="3">Proteins (g)</td><td>Lunch</td><td>73.8 (11.5)</td><td>71.9 (17.2)</td><td>60.7 (13.9)**<sup>b</sup></td><td>0.0059</td><td>-0.13[-0.61, 0.34]</td><td>-0.76[-1.24, -0.29]</td><td>0.63[0.15, 1.10]</td></tr><tr><td>Dinner</td><td>42.0 (18.4)</td><td>46.8 (14.4)</td><td>37.2 (13.2)<sup>a</sup></td><td>0.1811</td><td>0.25[-0.22, 0.73]</td><td>-0.30[-0.78, 0.17]</td><td>0.56[0.08, 1.03]</td></tr><tr><td>Total</td><td>115.9 (22.6)</td><td>118.7 (23.8)</td><td>98.8 (19.4)***<sup>c</sup></td><td>0.0007</td><td>0.08[-0.40, 0.55]</td><td>-0.85[-1.32, -0.37]</td><td>0.93[0.45, 1.40]</td></tr><tr><td rowspan="3">Proteins (%)</td><td>Lunch</td><td>21.5 (2.3)</td><td>21.4 (3.0)</td><td>20.8 (2.3)</td><td>0.5108</td><td>0.05[-0.42, 0.53]</td><td>-0.07[-0.55, 0.40]</td><td>0.23[-0.25, 0.70]</td></tr><tr><td>Dinner</td><td>20.8 (5.2)</td><td>19.9 (3.1)</td><td>20.1 (3.6)</td><td>0.8811</td><td>0.17[-0.31, 0.64]</td><td>0.01[-0.46, 0.49]</td><td>-0.06[-0.53, 0.42]</td></tr><tr><td>Total</td><td>21.3 (2.5)</td><td>21.0 (2.0)</td><td>20.6 (2.3)</td><td>0.6248</td><td>0.10[-0.38, 0.58]</td><td>-0.05[-0.53, 0.42]</td><td>0.14[-0.33, 0.62]</td></tr><tr><td rowspan="3">Lipids (g)</td><td>Lunch</td><td>45.4 (9.6)</td><td>45.0 (14.2)</td><td>38.1 (12.5)*<sup>a</sup></td><td>0.0146</td><td>-0.06[-0.53, 0.42]</td><td>-0.54[-1.01, -0.06]</td><td>0.48[0.06, 1.01]</td></tr><tr><td>Dinner</td><td>28.8 (19.0)</td><td>33.8 (15.1)</td><td>26.1 (14.3)<sup>a</sup></td><td>0.0642</td><td>0.33[-0.15, 0.80]</td><td>-0.18[-0.66, 0.30]</td><td>0.51[0.03, 0.98]</td></tr><tr><td>Total</td><td>74.3 (18.0)</td><td>78.8 (19.9)</td><td>65.8 (19.1)*<sup>b</sup></td><td>0.0123</td><td>0.25[-0.23, 0.72]</td><td>-0.54[-1.01, -0.06]</td><td>0.79[0.31, 1.26]</td></tr><tr><td rowspan="3">Lipids (%)</td><td>Lunch</td><td>29.8 (5.8)</td><td>30.3 (8.0)</td><td>29.2 (7.3)</td><td>0.1910</td><td>0.05[-0.42, 0.53]</td><td>-0.07[-0.55, 0.40]</td><td>0.13[-0.35, 0.60]</td></tr><tr><td>Dinner</td><td>30.0 (12.9)</td><td>31.3 (10.6)</td><td>29.7 (9.8)</td><td>0.0277</td><td>0.17[-0.31, 0.64]</td><td>0.01[-0.46, 0.49]</td><td>0.15[-0.32, 0.63]</td></tr><tr><td>Total</td><td>30.7 (5.8)</td><td>31.2 (4.8)</td><td>30.5 (5.7)</td><td>0.9655</td><td>0.10[-0.38, 0.58]</td><td>-0.05[-0.53, 0.42]</td><td>0.15[-0.32, 0.63]</td></tr><tr><td rowspan="3">CHO (g)</td><td>Lunch</td><td>166.7 (39.4)</td><td>160.8 (52.8)</td><td>144.2 (34.6)*</td><td>0.1649</td><td>-0.14[-0.62, 0.33]</td><td>-0.52[-0.99, -0.04]</td><td>0.37[-0.10, 0.85]</td></tr><tr><td>Dinner</td><td>92.8 (31.5)</td><td>109.9 (31.5)*</td><td>91.9 (29.4)<sup>a</sup></td><td>0.0269</td><td>0.52[0.04, 0.99]</td><td>-0.036[-0.54, 0.41]</td><td>0.58[0.11, 1.06]</td></tr><tr><td>Total</td><td>259.5 (56.1)</td><td>270.7 (70.0)</td><td>233.9 (49.7)<sup>a</sup></td><td>0.0751</td><td>0.17[-0.31, 0.64]</td><td>-0.45[-0.92, 0.03]</td><td>0.61[0.14, 1.09]</td></tr><tr><td rowspan="3">CHO (%)</td><td>Lunch</td><td>48.0 (7.6)</td><td>47.5 (10.5)</td><td>49.5 (9.1)</td><td>0.2149</td><td>0.06[-0.53, 0.42]</td><td>0.15[-0.33, 0.62]</td><td>-0.20[-0.68, 0.27]</td></tr><tr><td>Dinner</td><td>49.7 (15.6)</td><td>48.9 (12.4)</td><td>50.7 (10.7)</td><td>0.0840</td><td>-0.01[-0.48, 0.47]</td><td>0.13[-0.34, 0.61]</td><td>-0.14[-0.61, 0.34]</td></tr><tr><td>Total</td><td>47.8 (7.4)</td><td>47.4 (6.1)</td><td>48.7 (7.3)</td><td>0.9547</td><td>-0.05[-0.53, 0.42]</td><td>0.14[-0.34, 0.61]</td><td>-0.19[-0.67, 0.28]</td></tr></tbody></table>

406 CON: control condition; MEAL-30: Test meal 30 minutes after exercise; MEAL-90: Test meal 90 minutes after exercise; SD:

407 Standard Deviation; *p<0.05 vs. CON ; **p<0.01 vs. CON ; ***p<0.001 vs. CON ; p<0.05 MEAL-30 vs. MEAL-90 ; p<0.01

408 MEAL-30 vs. MEAL-90 ; c<0.001 MEAL-30 vs. MEAL-90; ES: Effect Size; CHO: Carbohydrates; ES: post hoc effect size.

409
<table><caption>410 Table 3: Pre- and Post-test meal food reward on the three experimental conditions</caption><thead><tr><th rowspan="2"></th><th rowspan="2">CON</th><th rowspan="2">MEAL-30</th><th rowspan="2">MEAL-90</th><th rowspan="2">P</th><th colspan="3">Interaction time x condition</th></tr><tr><th>CON vs. MEAL-30</th><th>CON vs. MEAL-90</th><th>MEAL-30 vs. MEAL-90</th></tr></thead><tbody><tr><td><strong>Implicit Wanting</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><em>Fat Bias</em></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Before lunch</td><td>22.32 (31.15)</td><td>19.96 (33.15)</td><td>22.80 (31.68)</td><td>0.78</td><td></td><td></td><td></td></tr><tr><td>After lunch</td><td>20.21 (45.58)</td><td>17.63 (48.49)</td><td>12.61 (29.50)</td><td>0.46</td><td>0.99</td><td>0.58</td><td>0.56</td></tr><tr><td><em>p before vs. after lunch</em></td><td>0.88</td><td>0.80</td><td>0.90</td><td></td><td>0.00[-0.48-0.48]</td><td>-0.13[-0.61-0.34]</td><td>-0.14[-0.62-0.33]</td></tr><tr><td>Before dinner</td><td>4.37 (64.45)</td><td>20.74 (19.89)</td><td>14.99 (26.63)</td><td>0.49</td><td></td><td></td><td></td></tr><tr><td><em>Taste Bias</em></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Before lunch</td><td>31.60 (33.67)</td><td>34.17 (41.81)</td><td>24.90 (32.49)</td><td>0.76</td><td></td><td></td><td></td></tr><tr><td>After lunch</td><td>25.60 (54.02)</td><td>27.00 (67.00)</td><td>43.59 (30.79)</td><td>0.59</td><td>0.93</td><td>0.14</td><td>0.26</td></tr><tr><td><em>p before vs. after lunch</em></td><td>0.69</td><td>0.85</td><td>0.04</td><td></td><td>0.02[-0.45-0.50]</td><td>0.36[-0.11-0.84]</td><td>0.27[-0.20-0.75]</td></tr><tr><td>Before dinner</td><td>38.24 (37.81)</td><td>40.40 (40.11)</td><td>42.30 (28.12)</td><td>0.98</td><td></td><td></td><td></td></tr><tr><td><strong>Explicit Liking</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><em>Fat Bias</em></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Before lunch</td><td>10.02 (19.71)</td><td>12.52 (16.35)</td><td>10.53 (19.64)</td><td>0.34</td><td></td><td></td><td></td></tr><tr><td>After lunch</td><td>5.29 (9.39)</td><td>5.14 (10.66)</td><td>4.08 (9.25)</td><td>0.94</td><td>0.57</td><td>0.77</td><td>0.86</td></tr><tr><td><em>p before vs. after lunch</em></td><td>0.27</td><td>0.03</td><td>0.11</td><td></td><td>-0.14[-0.61-0.34]</td><td>-0.07[-0.55-0.40]</td><td>0.04[-0.43-0.52]</td></tr><tr><td>Before dinner</td><td>11.35 (19.83)</td><td>9.04 (16.34)</td><td>2.44 (13.00)<sup>***b</sup></td><td>&lt;0.001</td><td></td><td></td><td></td></tr><tr><td><em>Taste Bias</em></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Before lunch</td><td>26.18 (20.37)</td><td>21.95 (23.03)</td><td>20.31 (22.89)</td><td>0.82</td><td></td><td></td><td></td></tr><tr><td>After lunch</td><td>12.78 (19.10)</td><td>18.08 (25.78)</td><td>14.47 (27.62)</td><td>0.73</td><td>0.10</td><td>0.25</td><td>0.74</td></tr><tr><td><em>p before vs. after lunch</em></td><td>&lt;0.001</td><td>0.38</td><td>0.19</td><td></td><td>0.40[-0.07-0.88]</td><td>0.28[-0.19-0.76]</td><td>-0.08[-0.56-0.40]</td></tr><tr><td>Before dinner</td><td>24.00 (24.58)</td><td>21.40 (26.08)</td><td>20.76 (28.74)</td><td>0.99</td><td></td><td></td><td></td></tr></tbody></table>

411 CON: control condition; MEAL-30: Test meal 30 min after exercise; MEAL-90: Test meal 90 min after exercise; SD:

412 Standard Deviation; ***p<0.001 vs. CON; $^{b}$p<0.01 MEAL-30 vs. MEAL-90; P values and Effect Size are presented for

413 interactions.

414
<table><caption>410 Table 3: Pre- and Post-test meal food reward on the three experimental conditions</caption><thead><tr><th rowspan="2"></th><th rowspan="2">CON</th><th rowspan="2">MEAL-30</th><th rowspan="2">MEAL-90</th><th rowspan="2">P</th><th colspan="3">Interaction time x condition</th></tr><tr><th>CON vs. MEAL-30</th><th>CON vs. MEAL-90</th><th>MEAL-30 vs. MEAL-90</th></tr></thead><tbody><tr><td><strong>Implicit Wanting</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><em>Fat Bias</em></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Before lunch</td><td>22.32 (31.15)</td><td>19.96 (33.15)</td><td>22.80 (31.68)</td><td>0.78</td><td></td><td></td><td></td></tr><tr><td>After lunch</td><td>20.21 (45.58)</td><td>17.63 (48.49)</td><td>12.61 (29.50)</td><td>0.46</td><td>0.99</td><td>0.58</td><td>0.56</td></tr><tr><td><em>p before vs. after lunch</em></td><td>0.88</td><td>0.80</td><td>0.90</td><td></td><td>0.00[-0.48-0.48]</td><td>-0.13[-0.61-0.34]</td><td>-0.14[-0.62-0.33]</td></tr><tr><td>Before dinner</td><td>4.37 (64.45)</td><td>20.74 (19.89)</td><td>14.99 (26.63)</td><td>0.49</td><td></td><td></td><td></td></tr><tr><td><em>Taste Bias</em></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Before lunch</td><td>31.60 (33.67)</td><td>34.17 (41.81)</td><td>24.90 (32.49)</td><td>0.76</td><td></td><td></td><td></td></tr><tr><td>After lunch</td><td>25.60 (54.02)</td><td>27.00 (67.00)</td><td>43.59 (30.79)</td><td>0.59</td><td>0.93</td><td>0.14</td><td>0.26</td></tr><tr><td><em>p before vs. after lunch</em></td><td>0.69</td><td>0.85</td><td>0.04</td><td></td><td>0.02[-0.45-0.50]</td><td>0.36[-0.11-0.84]</td><td>0.27[-0.20-0.75]</td></tr><tr><td>Before dinner</td><td>38.24 (37.81)</td><td>40.40 (40.11)</td><td>42.30 (28.12)</td><td>0.98</td><td></td><td></td><td></td></tr><tr><td><strong>Explicit Liking</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><em>Fat Bias</em></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Before lunch</td><td>10.02 (19.71)</td><td>12.52 (16.35)</td><td>10.53 (19.64)</td><td>0.34</td><td></td><td></td><td></td></tr><tr><td>After lunch</td><td>5.29 (9.39)</td><td>5.14 (10.66)</td><td>4.08 (9.25)</td><td>0.94</td><td>0.57</td><td>0.77</td><td>0.86</td></tr><tr><td><em>p before vs. after lunch</em></td><td>0.27</td><td>0.03</td><td>0.11</td><td></td><td>-0.14[-0.61-0.34]</td><td>-0.07[-0.55-0.40]</td><td>0.04[-0.43-0.52]</td></tr><tr><td>Before dinner</td><td>11.35 (19.83)</td><td>9.04 (16.34)</td><td>2.44 (13.00)<sup>***b</sup></td><td>&lt;0.001</td><td></td><td></td><td></td></tr><tr><td><em>Taste Bias</em></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Before lunch</td><td>26.18 (20.37)</td><td>21.95 (23.03)</td><td>20.31 (22.89)</td><td>0.82</td><td></td><td></td><td></td></tr><tr><td>After lunch</td><td>12.78 (19.10)</td><td>18.08 (25.78)</td><td>14.47 (27.62)</td><td>0.73</td><td>0.10</td><td>0.25</td><td>0.74</td></tr><tr><td><em>p before vs. after lunch</em></td><td>&lt;0.001</td><td>0.38</td><td>0.19</td><td></td><td>0.40[-0.07-0.88]</td><td>0.28[-0.19-0.76]</td><td>-0.08[-0.56-0.40]</td></tr><tr><td>Before dinner</td><td>24.00 (24.58)</td><td>21.40 (26.08)</td><td>20.76 (28.74)</td><td>0.99</td><td></td><td></td><td></td></tr></tbody></table>

411 CON: control condition; MEAL-30: Test meal 30 min after exercise; MEAL-90: Test meal 90 min after exercise; SD:

412 Standard Deviation; ***p<0.001 vs. CON; $^{b}$p<0.01 MEAL-30 vs. MEAL-90; P values and Effect Size are presented for

413 interactions.

414
415

416

417

418

1. Reid RER, Thivel D, Mathieu M-E. Understanding the potential contribution of a third "T" to FITT exercise prescription: the case of timing in exercise for obesity and cardiometabolic management in children. *Appl Physiol Nutr Metab.* 2019;44(8):911-914. doi:10.1139/apnm-2018-0462

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3. Chacko E. Exercising Tactically for Taming Postmeal Glucose Surges. *Scientifica*. 2016;2016:4045717. doi:10.1155/2016/4045717

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4. Haxhi J, Scotto di Palumbo A, Sacchetti M. Exercising for Metabolic Control: Is Timing Important. *Ann Nutr Metab.* 2013;62(1):14-25. doi:10.1159/000343788

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11. Tamam S, Bellissimo N, Patel BP, Thomas SG, Anderson GH. Overweight and obese boys reduce food intake in response to a glucose drink but fail to increase intake in response to exercise of short duration. *Appl Physiol Nutr Metab.* 2012;37(3):520-529. doi:10.1139/h2012-038

445

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447

12. Thivel D, Isacco L, Montaurier C, Boirie Y, Duché P, Morio B. The 24-h Energy Intake of Obese Adolescents Is Spontaneously Reduced after Intensive Exercise: A Randomized Controlled Trial in Calorimetric Chambers. *PLoS ONE.* 2012;7(1). doi:10.1371/journal.pone.0029840

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415

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1.

Reid RER, Thivel D, Mathieu M-E. Understanding the potential contribution of a third "T" to FITT exercise prescription: the case of timing in exercise for obesity and cardiometabolic management in children. *Appl Physiol Nutr Metab.* 2019;44(8):911-914. doi:10.1139/apnm-2018-0462

419

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421

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422

423

3.

Chacko E. Exercising Tactically for Taming Postmeal Glucose Surges. *Scientifica*. 2016;2016:4045717. doi:10.1155/2016/4045717

424

425

4.

Haxhi J, Scotto di Palumbo A, Sacchetti M. Exercising for Metabolic Control: Is Timing Important. *Ann Nutr Metab.* 2013;62(1):14-25. doi:10.1159/000343788

426

427

5.

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428

429

6.

Petitt DS, Cureton KJ. Effects of prior exercise on postprandial lipemia: A quantitative review. *Metabolism*. 2003;52(4):418-424. doi:10.1053/meta.2003.50071

430

431

432

7.

Zhang JQ, Ji LL, Nunez G, Feathers S, Hart CL, Yao WX. Effect of exercise timing on postprandial lipemia in hypertriglyceridemic men. *Can J Appl Physiol Rev Can Physiol Appl.* 2004;29(5):590-603.

433

434

435

8.

Zhang JQ, Thomas TR, Ball SD. Effect of exercise timing on postprandial lipemia and HDL cholesterol subfractions. *J Appl Physiol.* 1998;85(4):1516-1522. doi:10.1152/jappl.1998.85.4.1516

436

437

438

9.

Thivel D, Finlayson G, Blundell JE. Homeostatic and neurocognitive control of energy intake in response to exercise in pediatric obesity: a psychobiological framework. *Obes Rev Off J Int Assoc Study Obes.* 2019;20(2):316-324. doi:10.1111/obr.12782

439

440

441

10.

Masurier J, Mathieu M-E, Fearnbach SN, et al. Effect of Exercise Duration on Subsequent Appetite and Energy Intake in Obese Adolescent Girls. *Int J Sport Nutr Exerc Metab.* August 2018. doi:10.1123/ijsnem.2017-0352

442

443

444

11.

Tamam S, Bellissimo N, Patel BP, Thomas SG, Anderson GH. Overweight and obese boys reduce food intake in response to a glucose drink but fail to increase intake in response to exercise of short duration. *Appl Physiol Nutr Metab.* 2012;37(3):520-529. doi:10.1139/h2012-038

445

446

447

12.

Thivel D, Isacco L, Montaurier C, Boirie Y, Duché P, Morio B. The 24-h Energy Intake of Obese Adolescents Is Spontaneously Reduced after Intensive Exercise: A Randomized Controlled Trial in Calorimetric Chambers. *PLoS ONE.* 2012;7(1). doi:10.1371/journal.pone.0029840

448

449

13.

Thivel D, Isacco L, Rousset S, Boirie Y, Morio B, Duché P. Intensive exercise: A remedy for childhood obesity? *Physiol Behav.* 2011;102(2):132-136. doi:10.1016/j.physbeh.2010.10.011

450

451

452

14.

Thivel D, Metz L, Julien A, Morio B, Duché P. Obese but not lean adolescents spontaneously decrease energy intake after intensive exercise. *Physiol Behav.* 2014;123:41-46. doi:10.1016/j.physbeh.2013.09.018
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461

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19. Albert M-H, Drapeau V, Mathieu M-E. Timing of moderate-to-vigorous exercise and its impact on subsequent energy intake in young males. *Physiol Behav.* 2015;151:557-562. doi:10.1016/j.physbeh.2015.08.030

466

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468

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21. Aucouturier J, Isacco L, Thivel D, et al. Effect of time interval between food intake and exercise on substrate oxidation during exercise in obese and lean children. *Clin Nutr Edinb Scotl.* 2011;30(6):780-785. doi:10.1016/j.clnu.2011.03.011

471

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475

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23. Burton FL, Malkova D, Caslake MJ, Gill JMR. Substrate metabolism, appetite and feeding behaviour under low and high energy turnover conditions in overweight women. *Br J Nutr.* 2010;104(8):1249-1259. doi:10.1017/S0007114510002023

478

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480

24. Hopkins M, Blundell JE, King NA. Individual variability in compensatory eating following acute exercise in overweight and obese women. *Br J Sports Med.* 2014;48(20):1472-1476. doi:10.1136/bjsports-2012-091721

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486

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27. 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):120-127. doi:10.1016/j.appet.2007.06.007

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502
503
504
505
506

33. Oustric P, Thivel D, Dalton M, et al. Measuring food preference and reward: application and cross-cultural adaptation of the Leeds Food Preference Questionnaire in human experimental research. *Oustric P, Thivel D, Dalton M, Beaulieu K, Gibbons C, Hopkins M, Blundell J, Finlayson G*. Food Qual Pref. 2020; 80: 103824. doi: 10.1016/j.foodqual.2019.103824. Food Qual Pref. 2020;80. doi:doi: 10.1016/j.foodqual.2019.103824

507
508
509

34. Thivel D, Finlayson G, Miguet M, et al. Energy depletion by 24-h fast leads to compensatory appetite responses compared with matched energy depletion by exercise in healthy young males. *Br J Nutr.* 2018;120(5):583-592. doi:10.1017/S0007114518001873

510
511
512

35. Miguet M, Fillon A, Khammassi M, et al. Appetite, energy intake and food reward responses to an acute High Intensity Interval Exercise in adolescents with obesity. *Physiol Behav.* 2018;195:90-97. doi:10.1016/j.physbeh.2018.07.018

513
514
515

36. Thivel D, Roche J, Miguet M, et al. Post-moderate intensity exercise energy replacement does not reduce subsequent appetite and energy intake in adolescents with obesity. *Br J Nutr.* in press.

516
517

37. Cohen J. *Statistical Power Analysis for the Behavioral Sciences (2nd Ed.)*. Lawrence Erlbaum. New Jersey; 1988.

518
519

38. Feise RJ. Do multiple outcome measures require p-value adjustment? *BMC Med Res Methodol.* 2002;2:8. doi:10.1186/1471-2288-2-8

520

39. Rothman K, Greenland S. *Modern Epidemiology*. 2nd edn. Philadelphia: Lippincott-Raven; 1998.

521
522

40. Fearnbach SN, Masterson TD, Schlechter HA, et al. Impact of imposed exercise on energy intake in children at risk for overweight. *Nutr J*. 2016;15(1):92. doi:10.1186/s12937-016-0206-5

523
524
525
526

41. Prado WL, Lofrano-Prado MC, Oyama LM, et al. Effect of a 12-Week Low vs. High Intensity Aerobic Exercise Training on Appetite-Regulating Hormones in Obese Adolescents: A Randomized Exercise Intervention Study. *Pediatr Exerc Sci.* 2015;27(4):510-517. doi:10.1123/pes.2015-0018

527
528
529

42. Thivel D, Rumbold PL, King NA, Pereira B, Blundell JE, Mathieu M-E. Acute post-exercise energy and macronutrient intake in lean and obese youth: a systematic review and meta-analysis. *Int J Obes 2005*. 2016;40(10):1469-1479. doi:10.1038/ijo.2016.122
530 43. Thivel D, Chaput J-P. Are Post-Exercise Appetite Sensations and Energy Intake Coupled in Children and Adolescents? *Sports Med*. 2014;44(6):735-741. doi:10.1007/s40279-014-0160-3

532 44. Thivel D, Doucet E, Julian V, Cardenoux C, Boirie Y, Duclos M. Nutritional compensation to exercise- vs. diet-induced acute energy deficit in adolescents with obesity. *Physiol Behav*. 2017;176:159-164. doi:10.1016/j.physbeh.2016.10.022

535 45. Alizadeh Z, Younespour S, Rajabian Tabesh M, Haghravan S. Comparison between the effect of 6 weeks of morning or evening aerobic exercise on appetite and anthropometric indices: a randomized controlled trial. *Clin Obes*. 2017;7(3):157-165. doi:10.1111/cob.12187

538 46. Willis EA, Creasy SA, Honas JJ, Melanson EL, Donnelly JE. The effects of exercise session timing on weight loss and components of energy balance: midwest exercise trial 2. *Int J Obes 2005*. July 2019. doi:10.1038/s41366-019-0409-x

541 47. Ruddick-Collins LC, Johnston JD, Morgan PJ, Johnstone AM. The Big Breakfast Study: Chrono-nutrition influence on energy expenditure and bodyweight. *Nutr Bull*. 2018;43(2):174-183. doi:DOI: 10.1111/nbu.12323

544 48. Johnston JD. Physiological Responses to Food Intake Throughout the Day. *Nutr Res Rev*. 2014;27(1):107-118. doi:DOI: 10.1017/S0954422414000055

546 49. Summa KC, Turek FW. Chronobiology and Obesity: Interactions Between Circadian Rhythms and Energy Regulation. *Adv Nutr*. 2014;5(3):312-319.

548 50. de Castro MA, Riccioppo Garcez M, Lopes Pereira J, Mara Fisberg R. Eating Behaviours and Dietary Intake Associations With Self-Reported Sleep Duration of Free-Living Brazilian Adults. *Appetite*. 2019;137:207-217.

551 51. Westerterp-Plantenga MS. Sleep, Circadian Rhythm and Body Weight: Parallel Developments. *Proc Nutr Soc*. 2016;75(4):431-439. doi:DOI: 10.1017/S0029665116000227

553
530 43. Thivel D, Chaput J-P. Are Post-Exercise Appetite Sensations and Energy Intake Coupled in Children and Adolescents? *Sports Med*. 2014;44(6):735-741. doi:10.1007/s40279-014-0160-3

532 44. Thivel D, Doucet E, Julian V, Cardenoux C, Boirie Y, Duclos M. Nutritional compensation to exercise- vs. diet-induced acute energy deficit in adolescents with obesity. *Physiol Behav*. 2017;176:159-164. doi:10.1016/j.physbeh.2016.10.022

535 45. Alizadeh Z, Younespour S, Rajabian Tabesh M, Haghravan S. Comparison between the effect of 6 weeks of morning or evening aerobic exercise on appetite and anthropometric indices: a randomized controlled trial. *Clin Obes*. 2017;7(3):157-165. doi:10.1111/cob.12187

538 46. Willis EA, Creasy SA, Honas JJ, Melanson EL, Donnelly JE. The effects of exercise session timing on weight loss and components of energy balance: midwest exercise trial 2. *Int J Obes 2005*. July 2019. doi:10.1038/s41366-019-0409-x

541 47. Ruddick-Collins LC, Johnston JD, Morgan PJ, Johnstone AM. The Big Breakfast Study: Chrono-nutrition influence on energy expenditure and bodyweight. *Nutr Bull*. 2018;43(2):174-183. doi:DOI: 10.1111/nbu.12323

544 48. Johnston JD. Physiological Responses to Food Intake Throughout the Day. *Nutr Res Rev*. 2014;27(1):107-118. doi:DOI: 10.1017/S0954422414000055

546 49. Summa KC, Turek FW. Chronobiology and Obesity: Interactions Between Circadian Rhythms and Energy Regulation. *Adv Nutr*. 2014;5(3):312-319.

548 50. de Castro MA, Riccioppo Garcez M, Lopes Pereira J, Mara Fisberg R. Eating Behaviours and Dietary Intake Associations With Self-Reported Sleep Duration of Free-Living Brazilian Adults. *Appetite*. 2019;137:207-217.

551 51. Westerterp-Plantenga MS. Sleep, Circadian Rhythm and Body Weight: Parallel Developments. *Proc Nutr Soc*. 2016;75(4):431-439. doi:DOI: 10.1017/S0029665116000227

553