Variability in the acute effect of exercise on appetite ...
Acute compensatory eating following exercise is associated with implicit hedonic wanting for food
1Finlayson G, 1Bryant E, 1Blundell JE & 2King NA.
1BioPsychology Group, Institute of Psychological Sciences, University of Leeds, Leeds, LS29JT, UK; 2Institute of Health and Biomedical Innovation, Human Movement Studies, Queensland University of Technology, Brisbane. Australia
Correspondence to:
Graham Finlayson
Biopsychology group
Institute of Psychological Sciences
University of Leeds
Leeds LS2 9JT
United Kingdom
Tel: 44 113 343 7601
Fax: 44 113 343 6674
Authors’ email addresses:
g.s.finlayson@leeds.ac.uk
e.j.bryant@leeds.ac.uk
j.e.blundell@leeds.ac.uk
n.king@qut.edu.au
Running head: Acute compensatory eating following exercise
Abstract
The efficacy of exercise to promote weight loss could potentially be undermined by its influence on explicit or implicit processes of liking and wanting for food which in turn alter food preference. The present study was designed to examine hedonic and homeostatic mechanisms in the acute effects of exercise on food intake. 24 healthy female subjects were recruited to take part in two counterbalanced activity sessions; 50 minutes of high intensity (70% max heart rate) exercise (Ex) or no exercise (NEx). Subjective appetite sensations, explicit and implicit hedonic processes, food preference and energy intake (EI) were measured immediately before and after each activity session and an ad libitum test meal. Two groups of subjects were identified in which exercise exerted different effects on compensatory EI and food preference. After exercise, compensators (C) increased their EI, rated the food to be more palatable, and demonstrated increased implicit wanting. Compensators also showed a preference for high-fat sweet food compared with non-compensators (NC), independent of the exercise intervention. Exercise-induced changes in the hedonic response to food could play an important role in weight control. The exercise-induced increase in implicit wanting for food may help to explain the variable efficacy of exercise as a method of weight loss. Some individuals could be resistant to the beneficial effects of exercise due to a predisposition to compensate for exercise-induced energy expenditure as a result of changes in food preferences.
Introduction
Physical activity is currently strongly promoted as a method of weight control. However, in some individuals, a compensatory increase in energy intake (EI) might serve as a barrier for the potential for exercise to promote a negative energy balance (1). Therefore, the efficacy of exercise as a successful method of weight management will vary between individuals (2). EI is commonly put forward as the compensatory mechanism responsible for a lack of, or lower than expected, exercise-induced weight loss. Therefore, it is important to identify the homeostatic and hedonic processes which could be mobilised by exercise to influence food intake. For example, exercise may be linked to food intake through changes in food preferences and macronutrient selection (3;4). This relationship seems to depend on the characteristics of the population studied (5;6;7) and may reflect a biological drive for foods with particular sensory or nutrient properties (8;9;10).
Exercise and food intake may also be linked by their rewarding potential. Evidence indicates that vigorous exercise can stimulate brain substrates which are associated with reward and dependence (11;12). More recently, ‘Sensitivity to Reward’ – thought to reflect an innate characterological trait – has been identified (13;14) and is suggestive of a common neural substrate for determining the impact of pleasurable activities including exercise and feeding (15). It has been hypothesised that exercise may act as a buffer for reward driven eating (15), however it is also possible that exercise has a sensitising action that enhances food reward. Differences in the impact of exercise on food reward may explain some inter-individual variability in compensatory eating after exercise.
Of course, deliberate inappropriate food choices and allowance of food ‘treats’ could also be responsible for increases in EI (2). Nevertheless, the influence of hedonic processes on the behavioural action of eating can be considered as two-fold: Strength of motivational response to obtain available food, and the degree of subjective pleasure induced. Recently, the terms liking and wanting have been used to distinguish such hedonic processes that are either explicitly affective or implicitly motivational (16;17) and these may represent dual components of food preference (18;19;20). Therefore, it can be hypothesised that hedonic processes – via their influence on food preference – could be modulated by exercise-induced energy expenditure to promote overconsumption in those prone to compensatory eating.
A key issue is whether changes in exercise-induced food preference and nutrient selection are associated with hedonic or homeostatic mechanisms. Recent considerations of homeostatic and non-homeostatic determinants of eating imply that such systems interact in the overall expression of appetite (21;22;23). Since most of the evidence from acute exercise interventions indicates that there is no automatic increase in hunger following exercise (24;25;2), other non-homeostatic mechanisms need to be explored. Traditionally, methods such as test meals providing a selection of foods varying in nutrient composition (26), palatability visual analogue scales (27), and titration of the ratio of sweetness to fat in drinks (28) can be used to assess the acute effects of exercise on food preference. However, these methods are not designed – and therefore may not be sensitive enough – to detect more subtle exercise-induced alterations in the hedonic processes that influence food preference.
Therefore, this study used a novel computer-based procedure to allow the separate assessments of explicit and implicit operations of liking and wanting for an array of food items (19) to determine the acute effects of exercise on food preference, and explore individual variability in the compensatory response to exercise.
Method
Participants
Participants were recruited from the staff and student population of the University of Leeds. Screening sessions involved completion of the Three Factor Eating Questionnaire (29), acceptance of the study foods and level of habitual exercise (mean = 2.4 SD = 1.2 engagements/week) were verified by self report, and body composition was measured using bioelectrical impedance analysis (Inbody, Biospace, California). 24 healthy females aged 18-40 years (mean = 24.0, SD = 6.1 yr) and body mass index (BMI) between 20-25 kg/m2 (mean = 22.3, SD = 2.9 kg/m2) were selected from the initial screening process to exclude those who were taking medication, smokers, those currently following a weight loss routine, or reported a history of eating or psychological disorders. Following criteria from previous studies (Brunstrom et al. 2004; Tepper, 1992), all were classed as non-dietary restrained indicated by a score of less than 11 for Restraint on the TFEQ (mean = 6.1, SD = 3.1). Two cases were excluded from the analyses due to incomplete data, leaving a final sample of N=22.
Design
All the manipulations and measures were administered in the Human Appetite Research Unit at University of Leeds. The study conformed to a within-subjects design consisting of two counterbalanced conditions separated by approximately one week. The two conditions were moderate-intensity exercise (Ex) which involved stationery cycling at approximately 70% maximum heart rate for 50 minutes, and 50 minutes of no exercise (NEx). The NEx condition involved being sedentary (e.g. reading, sitting quietly). The exercise sessions were conducted under supervision. Physical activity levels prior to testing were standardised by asking participants to refrain from exercise on the day before each condition. Prior to their involvement in the study all participants were informed about the procedures and gave their written consent. On the final test session, they received written and verbal debriefing and were invited to ask questions. All procedures were followed in accordance with the standards of the institutional ethics committee.
Measures
Subjective appetite sensations and hedonic evaluation of the test meal
Subjective appetite sensations were recorded throughout the test days using 100mm visual analogue scales (VAS), anchored at each end with the statements “not at all” and “extremely”. Appetite sensations were assessed by questions relating to hunger, thirst, fullness and desire to eat. These were assessed immediately before and after the Ex and NEx sessions, and following the test meal. VAS hedonic ratings of the test meal were recorded immediately following consumption according to the pleasantness of the food.
Liking and wanting computer procedure
The computer procedure comprised two tasks designed to assess 1) explicit liking, 2) implicit wanting, and 3) relative preference for the same visual food stimuli. This experimental procedure has been described in more detail previously (19) and follows other laboratories successful use of reaction time as an indicator of implicit processes (for example, the Implicit Association Test; 30). The procedure uses a ‘forced choice’ reaction time measure of implicit wanting in addition to explicit subjective measures of liking for visual food stimuli varying in fat content and taste. Implicit wanting is operationalised as the reaction time of each pair trial decision. Thus, the speed with which one category of stimuli is chosen relative to alternative categories provides a quantifiable measure of implicit wanting for each food category in the procedure. The visual food stimuli were selected from a database of photographs and sorted according to their fat content and taste properties into one of four separate categories: high fat savoury (HFSA); low fat savoury (LFSA); high fat sweet (HFSW); and low fat sweet (LFSW). Each category was represented by five different foods; hence a total of 20 different food stimuli were presented in the procedure (see table 1). Participants completed the task immediately before Ex or NEx, immediately after Ex or NEx, and immediately after consuming the test meal. Stimuli were presented using experiment generator software (E-Prime v1.1.4) via 17” monitor and measured 150×100 mm2.
Table 1 about here
Explicit liking trials
The explicit task recorded subjective hedonic ratings for each food stimulus using VAS. The trials consisted of the twenty food stimuli presented one at a time and rated according to a 100-mm VAS anchored at each end by the statements “not at all” and “extremely”. Subjects were prompted with the statement “How pleasant would it be to taste some of this food now?”. The VAS was presented on-screen beneath each food stimulus and subjects used the mouse to move a centred cursor along the line to indicate their response. When a rating was made, the procedure automatically cycled to the next stimulus trial. Mean ratings for each food category (HFSA, LFSA, etc.) were automatically computed.
Implicit wanting trials and relative preference
Implicit wanting and relative preference were measured by a behavioural ‘forced choice’ methodology. In this task, a food stimulus from one of the four food categories was paired with one stimulus from the remaining categories to form a series of 150 trials in which the subjects were given the standardised instruction to select the food they “most want to eat now”. In addition to measuring relative preference for the stimuli by recording the frequency of selections made in each category (with a possible range of 0-75), reaction time (in ms) of each choice was also captured. By covertly recording reaction time, subjects remained unaware of implicit changes in their behaviour on the task, while remaining free to determine the direction of their choices. Data from the forced choice task – including relative preference (freq. of choice) and implicit wanting (reaction time in ms) – were recorded online for later calculation of the means.
Test meal
The ad libitum test meal consisted of cheese salad sandwiches, ready-salted crisps and fruit yoghurt. The average percentage energy provided by protein, fat and carbohydrate in the test meal was 13%, 45% and 42% respectively. Energy intake was calculated by weighing the food before and after consumption (to the nearest 0.1g) and with reference to the manufacturers energy values and food tables (30).
Heart rate
Prior to the experimental sessions, subjects were fitted with a heart rate monitor (Polar Electronic-4000, Finland). This was to ensure that exercise was performed at a fixed intensity (~70% maximum heart rate) and to estimate net energy expenditure from the exercise bout. Maximum heart rate was assessed on a screening day prior to test days, using an incremental test on a cycling ergometer (Proergo, Tunturi Ltd, Japan). Participants were required to cycle until volitional exhaustion, at which point maximum heart rate was inferred. Mean heart rate from the 50-minute exercise bout was calculated to predict energy expenditure using the Keytel-Hiiloskorpi equation for women (Keytel et al, 2005). Net energy expenditure was then estimated by subtracting the energy cost of 50-minutes of no exercise using the Mifflin-St Jeor equation for resting metabolic rate in women multiplied by the predicted energy cost of sitting from the World Health Organisation technical report series appendices (FAO/WHO/UNU, 1985).
Procedure
Participants arrived at 0900 and were required to stay in the research unit until the end of the test session after lunch. On arrival at the unit they were provided with a fixed energy breakfast (cereal with milk). Immediately before the exercise session, the liking and wanting computer procedure and ratings of appetite were completed (T1). Participants were navigated through the procedures at all times by written instructions presented on-screen. At 1100 they began either the Ex or NEx activity. Immediately after the activity, participants completed the liking and wanting procedure and subjective ratings of appetite (T2). They then showered and changed before being provided with an ad libitum test meal at 1230. Participants ate alone and were instructed to eat to comfortable fullness. Immediately after the test meal they completed the liking and wanting procedure and a final set of appetite ratings (T3). Figure 1 shows a schematic diagram of the procedure. The testing procedure lasted approximately 2 hours. The experimental protocol was approved by the Institute of Psychological Sciences Ethical Committee at University of Leeds. Participants gave their written consent and were not paid for their participation.
Figure 1 about here
Treatment of data and statistical analyses
The main analyses for this report focused on the variability in compensatory eating measured from energy intake at the test meal. Differences among participants classified on the basis of relative energy intake (Ex-NEx) were used to guide further post hoc analyses and tested by within-between subjects ANOVA.
Analysis of the liking and wanting measures focused on the explicit liking, implicit wanting and relative food preference measures. The parametric data were analysed in separate 3-way ANOVA with exercise activity (Ex or NEx), time (T1, T2, T3), and food category (HFSA, LFSA, HFSW and LFSW) treated as repeated factors. Trends in the relative preference measure were assessed descriptively.
From the initial sample of 24 women, two cases were excluded from the analyses due to incomplete data, leaving a final sample of N=22.
Results
Energy intake and energy expenditure
As expected, differences in energy expenditure were highly significant between Ex and Nex sessions. Mean heart rate and predicted energy expenditure were 94.2 ± 2.7 bpm and 189.3 ± 13.0 kcal for the Ex session and 81.4 ± 2.7 bpm and 47.0 kcal for the Nex session. No differences were found between Ex and Nex for energy intake. Total energy intakes for the Ex and NEx conditions were 1128.2 ± 72.8 and 1018.1 ± 73.0 kcal respectively.
Inter-individual variability in the acute effect of exercise on compensatory eating
Individual variability in relative energy intake (REI) was examined by subtracting energy intake after NEx from energy intake after Ex. In addition, net differences in compensatory eating were calculated by subtracting net energy expenditure (EE during Ex – EE during NEx) from REI. These calculations provided measures of the impact of the exercise bout on compensatory eating. Figure 2 illustrates this variability in compensatory eating and demonstrates the range of responses including individuals who suppressed or made no adjustment to their intake and some for whom exercise stimulated energy intake. As the mean energy cost of exercise for the whole sample (n=22) was 149.0 kcal ±11.2, REI of >150kcal indicated complete acute compensation.
Figure 2 about here
On the basis of this variation in relative energy intake, the sample was subdivided into two groups of response. These groups corresponded to a) those who ate approximately the same or less after exercise (non-compensators; N=11) and b) those who compensated or ate more after exercise (compensators; N=11). The exercise-induced energy expenditure for the compensators (146.3 kcal ±8.5) was similar to the non-compensators (151.2 kcal ±13.9).
Subject characteristics
The demographic and eating behaviour trait characteristics of compensators (C) and non-compensators (NC) were compared to try and identify factors that might explain the differences in compensatory eating. C scored higher on BMI, % body fat and lower on self reported frequency of habitual exercise compared with NC. Independent samples t-tests did not reveal the differences to be statistically significant (highest t= -1.26, p=n.s.).
Subjective sensations of appetite and hedonic evaluation of the test meal
Examination of appetite sensations revealed no group differences in terms of hunger, fullness, thirst or desire to eat. There was an overall main effect of time for hunger (F(2,40) = 46.35, p ................
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