The role of physical activity (PA) in homeostatic appetite control and body weight regulation is gaining more attention within the scientific community. Earlier reports have proposed an enhancement in the sensitivity of appetite control with increasing levels of PA (6,27), and the J-shape relationship between PA level and energy intake (EI) initially observed by Mayer et al. (30) has been recently confirmed by Shook et al. (36) and a systematic review (4). To better understand the effect of PA on food intake, it is important that distinct appetite processes such as satiation and satiety are examined. Satiation leads to meal termination, whereas satiety is the postmeal suppression of hunger and inhibition of further eating (9).
Recent evidence showed that satiation, measured with a passive overconsumption paradigm comparing EI at a high-fat meal with EI at a high-carbohydrate meal, was not influenced by PA level in nonobese individuals matched for body mass index (BMI) (5). Satiety, however, has been shown to be improved in physically active individuals. Using a preload test meal paradigm, studies have found that physically active individuals show better energy compensation than do inactive individuals such that they reduce EI to offset the difference in energy consumed in the preload (23,25,28,39). Moreover, measuring the satiety quotient (change in appetite scores relative to the energy content of a meal) in the hours after a fixed meal, studies have shown that satiety increases after 12 wk of exercise training in previously inactive overweight and obese individuals (11,22). These improvements in satiety signaling may relate to exercise-induced changes in postprandial satiety hormones such as leptin (19,25), insulin (19,24), and glucagon-like peptide-1 (24).
However, the beneficial effects of PA on satiety were based mainly on food diaries and all on self-reported habitual PA (23,39). Test meals for the assessment of EI under controlled laboratory conditions are preferred over food diaries because self-report measures are subject to bias and misreporting and cannot be relied on to provide a veridical account of food actually consumed (13). In addition, with wearable technologies being more available, objective assessment of habitual PA via accelerometry can now readily be used, reducing bias from participants overestimating their PA (13,34). Furthermore, the preloads used in previous studies were liquid based and not matched for macronutrient composition, which may affect individuals’ compensatory response (2,29).
In addition to an action on homeostatic mechanisms (satiation and satiety), other mechanisms in which habitual PA may affect appetite control is the rewarding value of foods (liking and wanting) and hedonic preference for high-fat foods (21). These can override physiological satiety signals and lead to overconsumption (14). Therefore, the objective of this study was to investigate the homeostatic (energy compensation) and hedonic (liking and wanting for high-fat foods) responses to high-energy preloads (HEP), low-energy preloads (LEP), and control preloads in nonobese individuals differing in objectively measured PA using an experimental system assessing several dimensions of appetite control (10). We hypothesized that more active individuals would have a greater reduction of energy after the HEP relative to the LEP compared with their less active counterparts.
Thirty-four participants 18–55 yr old were included on the basis of the following criteria: BMI between 20.0 and 29.9 kg·m−2, nonsmoker, weight stable (±2 kg for the previous 3 months), no change in PA over the previous 6 months, not currently dieting, no history of eating disorders, not taking any medication known to affect metabolism or appetite, and acceptance of the study foods. To recruit three groups of participants that differed in PA level (i.e., low, ≤1 d·wk−1; moderate, 2–3 d·wk−1; or high, ≥4 d·wk−1), we used the short-form of the validated International Physical Activity Questionnaire (12) as part of the screening process to estimate habitual moderate-to-vigorous PA (MVPA). Age, sex, and BMI were also monitored throughout screening to ensure that the groups were similar in these characteristics. After initial screening, habitual MVPA was then measured and confirmed using a multisensor device (SenseWear Armband (SWA); BodyMedia, Inc, Pittsburgh, PA) and used to group participants into a posteriori sex-specific tertiles of daily MVPA (low, LoMVPA; moderate, ModMVPA; or high, HiMVPA). Approximately half of the participants remained in their original self-report PA group estimated by the International Physical Activity Questionnaire (45%, 45%, and 58%, in the LoMVPA, ModMVPA, and HiMVPA tertiles, respectively). For men, LoMVPA corresponded to <112 min of MVPA per day and HiMVPA to >148 min of MVPA per day, whereas for women, LoMVPA corresponded to <90 min of MVPA per day and HiMVPA corresponded to >143 min of MVPA per day. This study was approved by the School of Psychology Ethical Committee at the University of Leeds, and participants provided written informed consent before taking part and were remunerated upon completing the study.
After a preliminary assessment, LoMVPA (82.7 ± 16.2 min of MVPA per day), ModMVPA (120.7 ± 14.8 min of MVPA per day), and HiMVPA (174.0 ± 38.6 min of MVPA per day) underwent 3 laboratory probe days in a Latin square crossover design that included a fixed breakfast followed by a HEP, LEP, or control, and ad libitum lunch, dinner, and snack box meals to examine the 24-h EI response to preloads varying in energy content relative to no-energy control (Fig. 1).
For the 24 h before the testing sessions, the participants refrained from exercise and did not consume caffeine or alcohol. On each test day, the participants arrived at the research unit between 7:00 and 9:00 AM following a 10-h fast (no food or drink except water). Before the first meal day, the participants consumed their habitual diet but were required to record their food intake for 24 h in a diary that was provided to them during the preliminary assessment, and replicated their food intake before the subsequent meal days. Compliance with these guidelines was verified upon arrival at the laboratory for each testing session.
During the meal days, participants restricted their PA (i.e., were not allowed to exercise), and at each meal day, upon arrival at the laboratory, participants were fitted with the SWA and wore the monitor until the following morning (~24 h) to assess energy expenditure. Subjective appetite ratings were measured using visual analog scales (VAS) before and after each meal and at hourly intervals throughout the day, and the hedonic preference for high-fat foods was measured using the Leeds Food Preference Questionnaire (LFPQ; (16)) before and after consumption of the preloads. EI at individual meals was measured (described in the Fixed energy and ad libitum meals section) and subsequently used to calculate 24-h EI. After a fixed-energy breakfast, participants returned 3 h later for the consumption of the preloads, 1 h after which they consumed an ad libitum lunch. Dinner was consumed 4 h after lunch, and participants were given an ad libitum snack box for the remainder of the evening. Each meal day was separated by at least 7 d.
Preliminary assessment and habitual PA
At least 8 d before the meal days, resting metabolic rate (RMR; indirect calorimetry), body composition (fat mass, fat-free mass; BodPod), maximal aerobic capacity (maximal aerobic capacity (V˙O2max); modified Balke protocol), and eating behavior traits (restraint, disinhibition, binge eating, craving control) were assessed as previously described (5). Upon completion, participants were fitted with an SWA and were instructed to wear the armband on their nondominant arm for 7 d for at least 23 h·d−1 (awake and asleep, except for the time around showering, bathing, or swimming). Compliance was defined as 5 d of wear (including one weekend day) with at least 22 h·d−1. Proprietary algorithms available in the accompanying software (version 8.0 professional) were used to calculate total daily energy expenditure (TDEE), PAL (TDEE/basal metabolic rate), and minutes spent sleeping, sedentary (<1.5 METs), or in light-intensity (1.5–2.9 METs) or moderate-intensity and higher (≥3.0 METs) PA (1).
Fixed energy and ad libitum meals
Participants consumed a fixed-energy breakfast that provided 25% of individual RMR. Upon consumption, participants were free to leave the research unit but were instructed not to eat or drink any food (except water). Three hours after breakfast, participants returned to the laboratory and consumed either a porridge HEP (699 kcal) or LEP (258 kcal) with 150 g of water or 445.5 g of water (control). HEP and LEP were of similar macronutrient composition (39% energy from carbohydrates, 46% energy from fat, and 15% energy from protein; see Table, Supplemental Digital Content 1, Ingredients and macronutrient composition of the high-energy preload (HEP) and low-energy preload (LEP), http://links.lww.com/MSS/A987), weight (295.5 g), volume, and palatability. Pilot testing (n = 9) showed no difference in sweetness, liking, pleasantness, and desire to eat between preloads (P ≥ 0.41). Participants had 15 min to consume the fixed-energy meals, and food items were weighed before and after consumption to ensure compliance.
One hour after the start of the preload, an ad libitum lunch consisting of risotto (1.99 kcal·g−1, 53.3% carbohydrate, 39.9% fat, 6.8% protein) with a side of cucumber and tomatoes was provided, and 4 h after lunch, an ad libitum dinner was provided, consisting of vegetarian chili (1.30 kcal·g−1, 49.8% carbohydrate, 37.4% fat, 12.8% protein) with a side of pineapple. For these meals, food was provided in excess of expected consumption, and the participants were instructed to eat as much or as little as they liked until comfortably full. After dinner, the participants were given a snack box containing a selection of foods (strawberry yogurt, apples, tangerines, cheese crackers, almonds, popcorn, and granola bars) and were instructed to eat only from this snack box until they went to bed that evening and return any remaining food and packaging the following morning. Food items were weighed before and after consumption, and EI was calculated using energy equivalents for protein, fat, and carbohydrate of 4, 9, and 3.75 kcal·g−1, respectively, from the manufacturers’ food labels. Cumulative EI was calculated as EI at lunch, dinner, and evening snack box.
Appetite ratings were assessed before and after each meal and at hourly intervals throughout the meal day via VAS for hunger, fullness, desire to eat, and prospective food consumption (PFC) using an electronic system (17). To specifically examine the effect of the preloads on satiety, area under the curve (AUC) was calculated using the trapezoid rule for the 1-h period after preload consumption (post-preload, VAS 5–7 in Fig. 1) and the 2-h period after lunch consumption (post-preload and lunch, VAS 7–10 in Fig. 1).
Hedonic preference for high-fat foods
The LFPQ (16) was administered pre- and post-preload consumption to determine scores of implicit wanting and explicit liking for high-fat (>50% energy) and low-fat (<20% energy) foods matched for familiarity, sweetness, protein, and acceptability and has been validated in a wide range of research (15,18,40). Implicit wanting was assessed by asking the participants to select as fast as possible which food from specific categories “they most want to eat.” Scores for implicit wanting were computed from mean response times adjusted for frequency. To measure explicit liking, the participants rated the extent to which they liked each food (“How pleasant would it be to taste this food now?”) using a 100-mm VAS. Low-fat scores were subtracted from high-fat scores to obtain the fat appeal bias score; a positive score indicates greater liking or wanting toward high-fat compared with low-fat foods.
The sample size was based on the study by Long et al. (23), who demonstrated that nonobese active individuals consumed less after a HEP relative to a LEP (d = 0.88). A similar effect size in the present study was estimated, and it was calculated that n = 10 per group would be sufficient to detect a difference in intake between HEP and LEP within groups with 1 − β = 0.8 and α = 0.05 (one-tailed).
Differences in characteristics of the MVPA tertiles were determined via one-way ANOVA. Pearson correlations were conducted to examine associations between fat-free mass, RMR, and daily EI. To examine the effect of the preloads, EI, appetite sensations, and food hedonics (liking and wanting) in HEP and LEP relative to control were computed. Differences in relative EI and appetite AUC were determined via two-way mixed-model ANOVA with condition (HEP, LEP) as the within-subject factor and MVPA tertile as the between-subject factor. Changes in relative liking and wanting were assessed with three-way mixed-model ANOVA with condition and time (pre- and post-preload consumption) as the within-subject factors and MVPA tertile as the between-subject factor. Bonferroni post hoc analyses adjusted for multiple comparisons were used when significance was achieved. Significance was established at P < 0.05.
Participant characteristics and habitual PA
The characteristics of the three MVPA tertiles are presented in Table 1. The tertiles did not significantly differ in age, BMI, body composition, RMR, or eating behavior traits, but by design, differed in terms of V˙O2max, habitual PA, and sedentary behavior. Because SWA wear time differed significantly between tertiles (LoMVPA, 1415.8 ± 13.5 min·d−1; ModMVPA, 1420.6 ± 8.4 min·d−1; HiMVPA, 1406.7 ± 13.8 min·d−1; P = 0.03), one-way ANCOVA controlling for SWA wear time were conducted on habitual free-living TDEE, light PA, MVPA, sedentary time, and PAL.
Ad libitum EI
In the control condition, there were no significant differences between tertiles in EI at lunch, dinner, evening snack box, or daily 24-h EI (all P ≥ 0.16; see Table, Supplemental Digital Content 2, Absolute energy intake in the control, low-energy preload (LEP) and high-energy preload (HEP) conditions across tertiles of MVPA, http://links.lww.com/MSS/A988). Daily EI was associated with fat-free mass (r = 0.51, P = 0.002) and RMR (r = 0.53, P = 0.001).
For EI at lunch after HEP and LEP relative to control, there was a significant effect of condition, as expected, with HEP reducing subsequent EI to a greater degree than LEP overall (P = 0.01). Furthermore, there was a significant condition–MVPA tertile interaction (P = 0.03), revealing that ModMVPA (P < 0.01) and HiMVPA (P = 0.01) had a greater reduction in intake after HEP compared with LEP, but no differences existed for LoMVPA (P = 0.59; Fig. 2 and see Figure, Supplemental Digital Content 3, Individual response in lunch and cumulative EI relative to control in the low-energy preload (LEP) and high-energy preload (HEP) conditions across tertiles of MVPA, http://links.lww.com/MSS/A989). There were no main effects or interaction for cumulative EI relative to control (lunch, dinner, and evening snack box combined; all P > 0.10; Table 2 and see Figure, Supplemental Digital Content 3, Individual response in lunch and cumulative EI relative to control in the low-energy preload (LEP) and high-energy preload (HEP) conditions across tertiles of MVPA, http://links.lww.com/MSS/A989). Daily EI (including breakfast and preload) was greater in HEP compared with LEP in all tertiles (P < 0.001; Table 2).
After preload consumption, hunger AUC relative to control was more suppressed in HEP compared with LEP, with no differences between tertiles (P = 0.03; Fig. 3A). There were no condition effects for fullness, desire to eat, and PFC (Fig. 3B, C, D). After both preload and lunch consumption, AUC for hunger, desire to eat, and PFC relative to control were all more suppressed, and fullness was greater in HEP compared with LEP, again with no differences between tertiles (all P ≤ 0.03; Fig. 3).
Two participants in HiMVPA did not have complete LFPQ data. In the control condition, there were no differences in liking and wanting fat appeal bias from pre– to post–water consumption or between tertiles (all P ≥ 0.26; see Table, Supplemental Digital Content 4, Absolute liking and wanting fat appeal bias scores pre- and post-preload consumption in the control, low-energy preload (LEP) and high-energy preload (HEP) conditions across tertiles of MVPA, http://links.lww.com/MSS/A990). For both liking and wanting pre- to post-preload relative to control, a three-way ANOVA revealed a main effect of preload consumption (P ≤ 0.01) and condition–preload consumption interaction (P ≤ 0.05), revealing a greater reduction in liking and wanting for high-fat foods after HEP compared with LEP but no differences relating to MVPA tertile (Fig. 4).
Meal day energy expenditure
Four participants (2 ModMVPA and 2 HiMVPA) did not have valid SWA meal day data because they removed the sensor before going to bed. In the control condition, there were no significant differences between tertiles in meal day energy expenditure (LoMVPA, 1964.6 ± 341.4 kcal; ModMVPA, 2077.0 ± 309.4 kcal; HiMVPA, 2270.4 ± 394.3 kcal; P = 0.15). In response to the HEP and LEP, there was no main effect of condition (P = 0.76), MVPA tertile (P = 0.21), or interaction between condition and MVPA tertile (P = 0.38) on meal day energy expenditure (Table 2). However, overall, meal day energy expenditure was lower than habitual TDEE by 238 ± 232 kcal as measured by the SWA for 7 d (P < 0.001).
This study examined the strength of satiety, energy compensation, and 24-h EI in individuals varying in PA level using objective assessment of EI and habitual PA. Including the measurement of other biopsychological determinants of appetite control such as food hedonics allowed for inferences about their effect on PA level and satiety to be drawn. In the entire sample, as expected, 24-h EI was positively associated with fat-free mass and RMR, and HEP gave rise to greater suppression of subsequent food intake than did LEP, confirming functional appetite control (7,8). In addition, the HEP also led to a greater suppression of hunger and reduction in food hedonics (liking and wanting for high-fat foods) compared with the LEP across all MVPA tertiles. However, an examination of the different PA levels showed that ModMVPA and HiMVPA had a greater reduction of ad libitum EI at lunch after consumption of the HEP compared with the LEP, whereas LoMVPA did not, supporting a role for habitual PA in the sensitivity of appetite control.
Habitual PA and energy compensation
Unlike previous studies examining the impact of PA level on energy compensation, this study classified groups on objective and quantified habitual MVPA. Furthermore, to reduce the likelihood of confounding effects on the compensatory response, the preloads were matched for macronutrient composition and consisted of a semisolid food (rather than a liquid), and the MVPA tertiles were similar in terms of participant age, sex, and BMI. The results show that the LoMVPA tertile was less sensitive to the nutritional manipulation of the preload compared with the ModMVPA and HiMVPA groups, who showed a greater reduction in subsequent intake in response to HEP. This is consistent with previous studies in which low levels of PA were found to be detrimental to homeostatic appetite control (23,25,28,39). In contrast, previous studies have reported that the physiological processes that signal satiety seem to be enhanced with habitual PA or exercise training, with changes seen in postprandial appetite-related peptides favoring satiety (19,24,25). Interestingly, Sim et al. (37) observed a tendency toward a reduction in EI after intake of a HEP with a concomitant improvement in insulin sensitivity after 12 wk of high-intensity intermittent exercise training but not moderate-intensity continuous exercise training. This supports the thought that insulin sensitivity may mediate the strength of satiety peptides such as glucagon-like peptide-1 and cholecystokinin (31,35). Another process that could mediate the release of appetite-related peptides to signal satiety is gastric emptying, which was found to be faster in active compared with inactive men (20).
The interrelationships that exist between PA, sedentary behavior, body composition, and TDEE make it difficult to isolate which specific component associated with PA is contributing to the sensitivity of appetite control. Nonetheless, long-term habitual PA may lead to chronic physiological adaptations involved in satiety signaling, including reduced fat mass and enhanced insulin sensitivity, fine tuning the appetite control system in its ability to detect adjustments in EI (overconsumption or underconsumption) and to compensate appropriately at a subsequent meal. In line with these findings, the present study found intake to be reduced in the ModMVPA and HiMVPA groups in response to HEP. Although improved postmeal satiety has been noted in physically active individuals, studies have reported that satiation does not differ between active and inactive individuals, because these distinct appetite processes may have differing underlying mechanisms (5).
The acute preload response at the ad libitum lunch meal in ModMVPA and HiMVPA was similar to that previously observed; however, previous evidence on daily (cumulative) energy compensation is conflicting. Some studies have demonstrated improvements in daily energy compensation with greater PA (25,28), whereas another study, in line with the current results, suggests no improvements (37). Of note, assessment of daily EI in the aforementioned studies was done via food diaries, which are prone to bias and misreporting, but in the current study, EI was objectively assessed for 24 h. Furthermore, there was a large variability in the individual response in terms of cumulative EI, which may have contributed to the nonsignificant results. Other methodological factors may also explain these inconsistent findings, such as the different designs (exercise training vs cross sectional) or physical characteristics (liquid vs semisolid) and macronutrient composition (matched vs unmatched) of the preloads used between studies (3). Nevertheless, total daily EI was greater after HEP compared with LEP in all MVPA tertiles. This highlights the importance of promoting the consumption of foods lower in energy density to avoid a passive overconsumption of energy (33), irrespective of PA level (5).
Impact of HEP and LEP on appetite sensations and food hedonics
In all MVPA tertiles, compared with LEP, HEP led to a greater suppression of hunger and, after lunch, to greater fullness and suppression of hunger, desire to eat, and PFC. Changes in appetite sensations after consumption of liquid preloads varying in energy content in inactive and active individuals have been inconsistent across studies, with one showing greater fullness after HEP compared with LEP (26), whereas others showing no differences in appetite sensations (23,25). In the current study, a semisolid preload was preferred over a liquid preload to elicit a strong impact on appetite and in the following compensatory response in EI within the time frame allocated between preload consumption and ad libitum meal (2). Interestingly, all tertiles showed a greater suppression of hunger after HEP but only the more active tertiles reduced EI at lunch after its consumption. The effects observed on appetite sensations are difficult to translate into clinical significance and may depend on PA level.
The consumption of the HEP was reflected by a greater reduction in both liking and wanting fat appeal bias relative to LEP, without any differences between tertiles. This reduction in the hedonic preference for high-fat foods was likely mediated by the greater energy content of the HEP (~400 kcal) and subsequent greater suppression of hunger after its consumption. In contrast, we have recently observed no differences in liking and wanting fat appeal bias after ad libitum consumption of a high-fat/high-energy-dense meal compared with a low-fat/low-energy-dense meal (to a similar level of fullness) despite a greater EI of approximately 400 kcal at the high-fat meal (5). Thus, it seems that an individual’s hunger/satiety state may mediate the hedonic response to meals to a greater extent compared with EI or macronutrient composition, with greater suppression of hunger and/or perceived fullness leading to a greater reduction in liking and wanting for high-fat relative to low-fat foods. Alternatively, consumption of fixed (i.e., preload) and ad libitum meals may produce distinct hedonic responses. As with the appetite sensations, considering that all tertiles responded similarly in their liking and wanting response but differently in terms of EI, the effects observed on food hedonics were likely small. The mechanisms responsible for the blunted compensatory response in EI in LoMVPA remain to be fully elucidated and, in the current study, seem not to be related to the subjective appetite or hedonic response to the preloads.
In terms of the influence of PA on the hedonic preference for high-fat foods, in the current nonobese sample, no differences in liking and wanting among MVPA tertiles were observed. These findings corroborate our previous findings where similarities in food hedonics in nonobese individuals differing in PA level were also found (5). Heightened rewarding value of foods may be dependent on a greater accumulation of body fat because greater liking and wanting for high-fat foods have been observed in overweight inactive men compared with their leaner active counterparts (21) and in overweight/obese women compared with healthy-weight women (32).
Strengths of this study include robust measurements of objective PA to classify groups according to MVPA tertiles and probe meal days to quantify 24-h EI within a multilevel experimental platform to assess various components of appetite control and eating behavior. However, this enhanced control did not allow for a very large sample size and may not have reflected real-world or long-term effects. Furthermore, a standardized diet on the days before the meal days was not provided, which may have strengthened the results. Assessment of postprandial appetite-related peptides after the preloads could also have provided a better depiction of satiety signaling differences between the MVPA tertiles and should be addressed in future studies. It should also be acknowledged that the study only included nonobese individuals and this did not allow for the inclusion of very inactive and sedentary individuals; therefore, the individuals in the LoMVPA tertile were relatively active (~80 min·d−1 of total MVPA). Although according to a recent analysis comparing data obtained from PA sensors (as in the present study) with current PA guidelines, the amount of total daily MVPA (through structured PA and nonstructured daily activities) to achieve PA guidelines (a PAL of 1.75) is approximately 140 min·d−1 of total MVPA (38). Nevertheless, this study was conducted in lean individuals and the findings may not be applicable to individuals who are obese and/or very inactive. Indeed, it is now our view that PA will exert differing effects on appetite control according to the amount of fat mass and the proportion of truly sedentary behavior. There is not one general rule that covers the relationship of PA and appetite control across the entire population.
Consumption of a HEP reduced EI at the following meal in nonobese individuals with moderate to high levels of MVPA compared with a LEP; however, this effect was absent in individuals with lower levels of MVPA. This suggests that individuals with low levels of PA have a weaker satiety response to food. On the other hand, individuals who are more physically active are sensitive to the energy content of foods and have better ability to adjust intake at a subsequent meal. The mechanisms underlying this process remain to be fully elucidated but could be linked to physiological satiety signaling rather than hedonic factors. Using objective measures of PA and EI, these data support previous evidence that lower levels of PA in nonobese individuals are detrimental to acute homeostatic appetite control.
No external funding was received to conduct this study.
The authors have no conflicts of interest to declare. The results of the present study do not constitute endorsement by the American College of Sports Medicine and are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.
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