Featured research (9)
INTRODUCTION: Exercise is recommended for weight management, yet weight loss from exercise is often less than expected based on measured energy expenditure. This is primarily due to compensatory energy intake, which occurs in most exercisers and overrides the appetite-suppressing effects of acute exercise. Exercising in a fasted state seems to be a promising way to decrease overall energy intake, as it has been reported that ad libitum 24h energy intake following fasting exercise is significantly lower than after non-fasting exercise. Acute effects of fasted exercise on post-exercise energy intake and particularly on post-exercise decision-making about food remain poorly understood. Therefore, the present study aimed to investigate whether fasting exercise and exercise after a standardized breakfast have different effects on hypothetical post-exercise food intake. METHODS: In this crossover study, ten healthy participants (29.7 [SD=2.2] years, 22.8 [SD=2.1] kg/m2, 50% women, regular habitual exercise, regular breakfast consumption) completed two identical 30-min exercise sessions on either a treadmill or bike ergometer (as preferred). The exercise sessions occurred following (1) an overnight (12h) fast (FE) or (2) a standardized breakfast (BE; oatmeal, low-fat milk, and apple; ~10-15% of individual daily energy requirements) after an overnight fast. Before (pre), immediately after (post), and 30 minutes after (post30) the exercise session, participants completed electronic questionnaires with visual food cues to determine hypothetical food amount preferences and intertemporal food preferences (immediate vs. delayed consumption after 4 hours). RESULTS: The preferred food amount for immediate consumption was significantly decreased compared to pre immediately after FE (161 [SD=85] kcal vs 236 [SD=81] kcal, p=0.006) but not after BE (p=0.26). For both exercise conditions, the amount of food selected for immediate consumption at post30 was significantly greater compared to pre (FE: 309 [SD=93] vs 236 [SD=81], p<0.001; BE: 201 [SD=103] vs 124 [SD=67], p=0.009). The preferred food amount for immediate consumption was significantly greater for FE compared to the BE, both for pre (difference: 113 [SD=57] kcal, p<0.001) and post30 (difference: 109 [SD=87] kcal, p=0.004) but not post (p=0.47). There were no significant differences between time points for delayed consumption in either exercise condition. CONCLUSION: The results of the present study suggest that fasting exercise may contribute to an overall daily energy deficit despite higher post-exercise energy intake (at post30) compared to exercise after a small breakfast. Importantly, hypothetical food intake did not differ between the two conditions immediately after exercise, suggesting that consumption of a meal at that time might maximize the calorie deficit-related benefits of fasting exercise. More (longitudinal) research in larger samples is needed to determine whether fasting exercise is an adequate method for weight loss.
OBJECTIVE: Energy intake in response to exercise is highly variable. While some individuals show reduced energy intake post-exercise, allowing for an exercise-induced energy deficit, others show increased energy intake, (over-) compensating the expended energy. In an exploratory analysis, we aimed to identify biological and behavioral predictors of ad libitum food intake following a one-time aerobic exercise session. METHODS: After an overnight fast and a standardized breakfast, 57 healthy participants (21.7±2.5 years; 23.7±2.3 kg/m2, 54% female) completed a 45-min exercise session (60% VO2peak) on a bike ergometer followed by an ad libitum single-item (cheese pizza) food intake test. We used simple linear regression analyses to assess the associations between biological and behavioral baseline characteristics and energy intake (kcal). RESULTS: On average, participants expended 343±85 kcal during the exercise session and consumed 867±411 kcal during the subsequent test meal. We found an inverse association between participants’ habitual exercise behavior (on average 246±181 min/week, via self-report) and energy intake during the test meal (β=−0.29, P=0.03) and a positive association between fasting concentrations of peptide YY (PYY) and energy intake (β=0.35, P=0.03). Results also differed by sex (P=0.02): PYY (β=0.82, P<0.01) and additionally adiponectin (β=0.61, P=0.01) were significant predictors of energy intake only in men, while habitual exercise (β=−0.44, P=0.02) was a significant predictor of post-exercise energy intake only in women. CONCLUSIONS: Our results suggest sex differences in predictors of post-exercise energy intake – in women, greater amounts of habitual exercise seem to protect from compensatory eating, while in men appetite-regulating hormones are predictive of post-exercise energy intake. These findings may help explain why some individuals compensate the energy expended via exercise and others do not.
Energy intake in the post-exercise state is highly variable and compensatory eating – i.e., (over‑) compensation of the expended energy via increased post-exercise energy intake – occurs in some individuals but not others. We aimed to identify predictors of post-exercise energy intake and compensation. In a randomized crossover design, 57 healthy participants (21.7 [SD=2.5] years; 23.7 [SD=2.3] kg/m², 75% White, 54% female) completed two laboratory-based test-meals following (1) 45-min exercise and (2) 45-min rest (control). We assessed associations between biological (sex, body composition, appetite hormones) and behavioral (habitual exercise via prospective exercise log, appetitive traits) characteristics at baseline and total energy intake, compensatory energy intake (intake – exercise expenditure), and the difference between post-exercise and post-rest intake. We found a differential impact of biological and behavioral characteristics on total post-exercise energy intake in men and women. In men, only fasting (baseline) concentrations of appetite-regulating hormones (peptide YY [PYY, β=0.88, P<0.001] and adiponectin [β=0.66, P=0.005] predicted total post-exercise energy intake, while in women, only habitual exercise (β=−0.44, P=0.017) predicted total post-exercise energy intake. Predictors of compensatory intake (intake – exercise expenditure) were almost identical to those of total intake. The difference in energy intake between exercise and rest was associated with VO2peak (β=−0.45, P=0.020), fasting PYY (β=0.53, P=0.036), and fasting adiponectin (β=0.57, P=0.021) in men but not women (all P>0.51). Our results show that biological and behavioral characteristics differentially affect total and compensatory post-exercise energy intake in men and women. This may help identify individuals who are more likely to compensate for the energy expended in exercise. Targeted countermeasures to prevent compensatory energy intake after exercise should take the demonstrated sex differences into account.
Objective To characterize the contributions of the loss of energy-expending tissues and metabolic adaptations to the reduction in resting metabolic rate (RMR) following weight loss. Methods A secondary analysis was conducted on data from the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy study. Changes in RMR, body composition, and metabolic hormones were examined over 12 months of calorie restriction in 109 individuals. The contribution of tissue losses to the decline in RMR was determined by weighing the changes in the size of energy-expending tissues and organs (skeletal muscle, adipose tissue, bone, brain, inner organs, and residual mass), as assessed by dual-energy X-ray absorptiometry, with their tissue-specific metabolic rates. Metabolic adaptations were quantified as the remaining reduction in RMR. Results RMR was reduced by 101 ± 12 kcal/d as participants lost 7.3 ± 0.2 kg (both p < 0.001). On average, 60% of the total reduction in RMR were explained by losses of energy-expending tissues, while 40% were attributed to metabolic adaptations. The loss of skeletal muscle mass was not significantly related to RMR changes (p = 0.17), whereas adipose tissue losses were positively associated with the reduction in RMR (p = 0.02) and metabolic adaptations (p < 0.001). Metabolic adaptations were further correlated with declines in leptin (r = 0.27, p < 0.01), triiodothyronine (r = 0.19, p < 0.05), and insulin (r = 0.25, p < 0.05). Conclusions During weight loss, tissue loss and metabolic adaptations both contribute to the reduction in RMR, although their contribution is variable. Contrary to popularly belief, it is not skeletal muscle, but rather adipose tissue losses that seem to drive RMR reductions following weight loss. Future research should be directed at personalized strategies addressing the predominant cause of RMR reduction for weight maintenance.
- Faculty of Sport and Health Science
About Karsten Koehler
- Our overarching goal is to understand the interactions between diet and exercise and how we can use this knowledge to improve human health and performance. We are particularly interested in the multiple pathways how exercise affects energy balance, and how acute and chronic under- or overeating impact the regulation of body weight, body composition, metabolism, and musculoskeletal health.