Energy Compensation Following a Supervised Exercise Intervention in Women Living With Overweight/Obesity Is Accompanied by an Early and Sustained Decrease in Non-structured Physical Activity.

BACKGROUND/OBJECTIVES: Body composition (BC) does not always vary as a function of exercise induced energy expenditure (exercise EE - resting EE). Energy balance variables were measured to understand energy compensation (EC) in response to an exercise intervention performed at low (LOW) or moderate (MOD) intensity. SUBJECTS/METHODS: Twenty-one women with overweight/obesity (33 ± 5 kg/m2; 29 ± 10 yrs; 31 ± 4 ml O2/kg/min) were randomized to a 3-month LOW or MOD (40 or 60% of VÈ®2reserve, respectively) matched to expend 1500 kcal/week (compliance = 97 ± 5%). Body energy stores (DXA), energy intake (EI) (food menu and food diaries), resting EE (indirect calorimetry), total EE (doubly-labeled water), time spent in different activities (accelerometers), appetite (visual analog scale), eating behavior traits and food reward (liking and wanting) were assessed at baseline, after weeks 1 and 2 and at the end of the 3-month exercise intervention. RESULTS: EC based on BC changes (fat mass and fat-free mass) was 49 ± 79% and 161 ± 88% in LOW and MOD groups, respectively (p = 0.010). EI did not change significantly during the intervention. However, eating behavior traits and food reward had changed by the end of the 3-month supervised exercise. Non-structured physical activity (NSPA) decreased across the intervention (p < 0.002), independent of the intensity of the exercise training. CONCLUSION: Women with overweight/obesity training at LOW presented lower EC for a given energy cost of exercise. Our results strongly suggest that NSPA plays a major role in mediating the effects of exercise on energy balance and ultimately on changes in BC. CLINICAL TRIAL REGISTRATION: www.ClinicalTrials.gov, identifier ISRCTN31641049.

Investigating predictors of eating: is resting metabolic rate really the strongest proxy of energy intake?

Background: Evidence suggests that fat-free mass and resting metabolic rate (RMR), but not fat mass, are strong predictors of energy intake (EI). However, body composition and RMR do not explain the entire variance in EI, suggesting that other factors may contribute to this variance.Objective: We aimed to investigate the associations between body mass index (in kg/m2), fat mass, fat-free mass, and RMR with acute (1 meal) and daily (24-h) EI and between fasting appetite ratings and certain eating behavior traits with daily EI. We also evaluated whether RMR is a predictor of the error variance in acute and daily EI.Design: Data collected during the control condition of 7 studies conducted in Ottawa, Ontario, Canada, were included in these analyses (n = 191 and 55 for acute and daily EI, respectively). These data include RMR (indirect calorimetry), body composition (dual-energy X-ray absorptiometry), fasting appetite ratings (visual analog scales), eating behavior traits (Three-Factor Eating Questionnaire), and EI (food buffet or menu).Results: Fat-free mass was the best predictor of acute EI (R2 = 0.46; P < 0.0001). The combination of fasting prospective food consumption ratings and RMR was the best predictor of daily EI (R2 = 0.44; P < 0.0001). RMR was a statistically significant positive predictor of the error variance for acute (R2 = 0.20; P < 0.0001) and daily (R2 = 0.23; P < 0.0001) EI. RMR did, however, remain a statistically significant predictor of acute (R2 = 0.32; P < 0.0001) and daily (R2 = 0.30; P < 0.0001) EI after controlling for this error variance.Conclusions: Our findings suggest that combined measurements of appetite ratings and RMR could be used to estimate EI in weight-stable individuals. However, greater error variance in acute and daily EI with increasing RMR values was observed. Future studies are needed to identify whether greater fluctuations in daily EI over time occur with increasing RMR values. This trial was registered at clinicaltrials.gov as NCT02653378.

Fitness, adiposopathy, and adiposity are independent predictors of insulin sensitivity in middle-aged men without diabetes

Adiposopathy, or sick fat, refers to adipose tissue dysfunction that can lead to several complications such as dyslipidemia, insulin resistance, and hyperglycemia. The relative contribution of adiposopathy in predicting insulin resistance remains unclear. We investigated the relationship between adiposopathy, as assessed as a low plasma adiponectin/leptin ratio, with anthropometry, body composition (hydrostatic weighing), insulin sensitivity (hyperinsulinemic-euglycemic clamp), inflammation, and fitness level (ergocycle VO2max, mL/kgFFM/min) in 53 men (aged 34-53 years) from four groups: sedentary controls without obesity (body mass index [BMI] <25 kg/m2), sedentary with obesity (BMI > 30 kg/m2), sedentary with obesity and glucose intolerance, and endurance trained active without obesity. The adiponectin/leptin ratio was the highest in trained men (4.75 ± 0.82) and the lowest in glucose intolerant subjects with obesity (0.27 ± 0.06; ANOVA p < 0.0001) indicating increased adiposopathy in those with obesity. The ratio was negatively associated with adiposity (e.g., waist circumference, r = −0.59, p < 0.01) and positively associated with VO2max (r = 0.67, p < 0.01) and insulin sensitivity (M/I, r = 0.73, p < 0.01). Multiple regression analysis revealed fitness as the strongest independent predictor of insulin sensitivity (partial R2 = 0.61). While adiposopathy was also an independent and significant contributor (partial R2 = 0.10), waist circumference added little power to the model (partial R2 = 0.024). All three variables remained significant independent predictors when trained subjects were excluded from the model. Plasma lipids were not retained in the model. We conclude that low fitness, adiposopathy, as well as adiposity (and in particular abdominal obesity) are independent contributors to insulin resistance in men without diabetes (AU)

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Fitness, adiposopathy, and adiposity are independent predictors of insulin sensitivity in middle-aged men without diabetes.

Adiposopathy, or sick fat, refers to adipose tissue dysfunction that can lead to several complications such as dyslipidemia, insulin resistance, and hyperglycemia. The relative contribution of adiposopathy in predicting insulin resistance remains unclear. We investigated the relationship between adiposopathy, as assessed as a low plasma adiponectin/leptin ratio, with anthropometry, body composition (hydrostatic weighing), insulin sensitivity (hyperinsulinemic-euglycemic clamp), inflammation, and fitness level (ergocycle VO2max, mL/kgFFM/min) in 53 men (aged 34-53 years) from four groups: sedentary controls without obesity (body mass index [BMI] <25 kg/m(2)), sedentary with obesity (BMI > 30 kg/m(2)), sedentary with obesity and glucose intolerance, and endurance trained active without obesity. The adiponectin/leptin ratio was the highest in trained men (4.75 ± 0.82) and the lowest in glucose intolerant subjects with obesity (0.27 ± 0.06; ANOVA p < 0.0001) indicating increased adiposopathy in those with obesity. The ratio was negatively associated with adiposity (e.g., waist circumference, r = -0.59, p < 0.01) and positively associated with VO2max (r = 0.67, p < 0.01) and insulin sensitivity (M/I, r = 0.73, p < 0.01). Multiple regression analysis revealed fitness as the strongest independent predictor of insulin sensitivity (partial R (2) = 0.61). While adiposopathy was also an independent and significant contributor (partial R (2) = 0.10), waist circumference added little power to the model (partial R (2) = 0.024). All three variables remained significant independent predictors when trained subjects were excluded from the model. Plasma lipids were not retained in the model. We conclude that low fitness, adiposopathy, as well as adiposity (and in particular abdominal obesity) are independent contributors to insulin resistance in men without diabetes.

Energy depletion by diet or aerobic exercise alone: impact of energy deficit modality on appetite parameters.

BACKGROUND: Millions of Americans attempt to lose weight each year, and it is unclear whether the modality of acute, tightly controlled energy depletions can differently affect appetite parameters and olfaction. OBJECTIVE: The objectives were to examine how the modality of an acute 3-d isocaloric 25% energy depletion by dieting alone or by aerobic exercise alone differently affects appetite and appetite-related hormones, ad libitum feeding, food reward (snack points), and olfaction. DESIGN: Ten male participants with a mean ± SD age of 23.7 ± 5.1 y and an initial mean ± SD body weight of 83.2 ± 11.5 kg participated in this randomized crossover design. Baseline measurement [day 1 of the control condition (CON1)] was performed and repeated 3 d later [day 4 of the control condition (CON4)], after which randomization was applied to the order of the 2 experimental conditions: 25% daily needs energy deficits induced by diet only (DIET) and by exercise only (EX) and tested before [day 1 of DIET (DIET1) and day 1 of EX (EX1)] and after 3 d [day 4 of DIET (DIET4) and day 4 of EX (EX4)] of the intervention. Body weight, leptin and ghrelin concentrations, relative-reinforcing value of food, and olfaction were measured at days 1 and 4. Body composition (dual-energy X-ray absorptiometry), ad libitum energy intake (EI; buffet), and palatability (visual analog scale) were measured only at day 4. RESULTS: Relative to CON4, EI (P= 0.001), palatability (P= 0.01), and odor threshold (P= 0.05) were higher at DIET4; relative to CON4, palatability (P= 0.03) was higher at EX4. Compared with EX4, EI was higher for DIET4 (P= 0.006). Relative to CON4, snack points earned were higher at DIET4 (P= 0.03) and EX4 (P= 0.001); more snack points were earned at EX4 relative to DIET4 (P= 0.001). CONCLUSIONS: Compared with the control condition, DIET represented a greater acute challenge to appetite regulation than EX, as demonstrated by greater appetite and ad libitum EI. This study confirms that compared with depletions by exercise alone, acute caloric restriction results in rapid changes in appetite that result in compensatory eating, which may initially dissuade potential success in weight-loss efforts. This trial was registered at clinicaltrials.gov as NCT02653378.

Validation and Reliability of a Classification Method to Measure the Time Spent Performing Different Activities.

The aim of this study was to validate the performance and reliability of results obtained from a classification model that measures time spent performing activities in confined (CE) and unrestricted (UE) environments. In CE, participants wore a pair of biaxial and/or triaxial accelerometers while performing pre-determined training activities classified as variants of lying down, dynamic standing, sitting, walking and running on two separate days. A classification model trained with activities performed in a specific order during the first day was developed to validate the activities performed in a random order on the second day (CE) and over 24 hours on a separate day (UE). The performance of the classification model was validated against triaxial accelerometers using six (x, y and step counts for arm and thigh) or eight (same as six features plus z axis) features. The reliability of the classification model was tested in both environments using six features. Results revealed an overall accuracy of 94% in CE and 90% in UE. The sensitivity in CE and UE was 94% and 95% for lying down, 88% and 80% for dynamic standing, 97% and 89% for sitting, 96% and 78% for walking and 90% and 64% for running, respectively. No significant differences were noted between performances obtained with six or eight features. Results were highly reproducible in both environments. The results obtained from the classification model were accurate and reproducible, and highlight the potential use of this approach in research to quantify the time spent performing different activities.

Predictors of Energy Compensation during Exercise Interventions: A Systematic Review.

Weight loss from exercise-induced energy deficits is usually less than expected. The objective of this systematic review was to investigate predictors of energy compensation, which is defined as body energy changes (fat mass and fat-free mass) over the total amount of exercise energy expenditure. A search was conducted in multiple databases without date limits. Of 4745 studies found, 61 were included in this systematic review with a total of 928 subjects. The overall mean energy compensation was 18% ± 93%. The analyses indicated that 48% of the variance of energy compensation is explained by the interaction between initial fat mass, age and duration of exercise interventions. Sex, frequency, intensity and dose of exercise energy expenditure were not significant predictors of energy compensation. The fitted model suggested that for a shorter study duration, lower energy compensation was observed in younger individuals with higher initial fat mass (FM). In contrast, higher energy compensation was noted for younger individuals with lower initial FM. From 25 weeks onward, energy compensation was no longer different for these predictors. For studies of longer duration (about 80 weeks), the energy compensation approached 84%. Lower energy compensation occurs with short-term exercise, and a much higher level of energy compensation accompanies long-term exercise interventions.

Resistance and aerobic exercises do not affect post-exercise energy compensation in normal weight men and women.

BACKGROUND: Previous research has reported no effect of exercise modality (aerobic vs. resistance) on energy intake (EI). However, the relatively low energy cost of resistance training, the absence of total energy expenditure (TEE) measurements and the short duration of these studies justify further investigation. OBJECTIVE: To evaluate the effects of exercise modality on EI, TEE, non-exercise activity thermogenesis (NEAT) and post-exercise energy compensation (PEEC) measured acutely, as well as for 10 and 34 h following exercise. DESIGN: Eight men and 8 women participated in three randomized crossover sessions: aerobic-based exercise, resistance-based exercise, and sedentary control. Exercise energy expenditure (ExEE) was continuously measured (indirect calorimetry) throughout the exercise sessions, which were designed to produce an isocaloric ExEE of 4 kcal/kg body weight. TEE and EI were monitored for 34 h post-exercise with biaxial accelerometers and a validated food menu, respectively. RESULTS: There were no differences in EI between exercise modalities acutely, as well as 10 and 34 h following exercise. However, a modality by sex interaction was noted for acute EI. Men ate more after the resistance than after the aerobic session (1567±469; 1255±409 kcal, respectively; P=0.034), while no differences were seen in women (568±237; 648±270 kcal, respectively; P=NS). No differences in TEE, NEAT and PEEC were found 10h and 34 h post-exercise, while a positive correlation (r=0.897; P<0.01) was found between both modalities across participants for PEEC. CONCLUSION: Exercise modality does not impact PEEC when ExEE is controlled. Our results also show that within-individual PEEC seems to be relatively constant across exercise modality.

The TaqIA RFLP is associated with attenuated intervention-induced body weight loss and increased carbohydrate intake in post-menopausal obese women.

INTRODUCTION: Polymorphisms of the dopamine receptor D2 (DRD2) gene have been associated with obesity phenotypes. Our aim was to examine if the genotype of TaqIA Restriction Fragment Length Polymorphism (RFPL) was related to an attenuated weight loss response or to changes in energy expenditure (EE) and food preference before and after weight loss. methods: Obese post-menopausal women (age=57.1 ± 4.6 yr, weight=85.4 ± 15.4 kg and BMI=32.8 ± 4.5 kg/m(2)) were genotyped for TaqIA (n=127) by using PCR-RFLP analysis and categorized as possessing at least one copy of the A1 allele (A1(+)) or no copy (A1(-)). Women were randomized into two groups, caloric restriction (CR) and caloric restriction+resistance training (CRRT) and in this study were further classified as follows: A1(+)CR, A1(+)CRRT, A1-(-)CR and (-)A1(-)CRRT. Body composition, total daily EE, physical activity EE, Resting EE (REE), and energy intake were obtained at baseline and post-intervention using DXA, doubly-labeled water, indirect calorimetry, and 3-day dietary records, respectively. RESULTS: Overall, all of the anthropometric variables and REE significantly decreased post-intervention (p<0.001). Women in the CRRT group lost significantly more fat mass (FM) than the CR women (p<0.05). There were significant time by group by allele interactions for attenuated body weight (BW), BMI, and FM loss for A1(+) (vs. A1(-)) in CRRT (p<0.05) and for increased % carbohydrate intake (p<0.01). CONCLUSION: TaqIA genotype was associated with body weight loss post-intervention; more specifically, carriers of the A1 allele lost significantly less BW and FM than the A1(-) and had increased carbohydrate intake in the CRRT group.

Reproducibility of a food menu to measure energy and macronutrient intakes in a laboratory and under real-life conditions.

Given the limitations associated with the measurement of food intake, we aimed to determine the reliability of a food menu to measure energy intake (EI) and macronutrient intake within the laboratory and under free-living conditions. A total of eight men and eight women (age 25·74 (sd 5·9) years, BMI 23·7 (sd 2·7) kg/m²) completed three identical in-laboratory sessions (ILS) and three out-of-laboratory sessions (OLS). During the ILS, participants had ad libitum access to a variety of foods, which they chose from a menu every hour, for 5 h. For the OLS, the foods were chosen from the menu at the start of the day and packed into containers to bring home. There were no significant differences in total EI (6118·6 (sd 2691·2), 6678·8 (sd 2371·3), 6489·5 (sd 2742·9) kJ; NS) between the three ILS and three OLS (6816·0 (sd 2713·2), 6553·5 (sd 2364·5), 6456·4 (sd 3066·8) kJ; NS). Significant intraclass correlations (ICC) for total energy (r 0·77, P<0·0001), carbohydrate (r 0·81, P<0·0001), dietary fat (r 0·54, P<0·0001) and protein (r 0·81, P<0·0001) intakes for the ILS and significant ICC for total energy (r 0·85, P<0·0001), carbohydrate (0·85, P<0·0001), dietary fat (0·72 P<0·0001) and protein (0·80, P<0·0001) intakes for the OLS were noted. The average within-subject CV for total EI was 18·3 (sd 10·0) and 16·1 (sd 10·3) % for the ILS and OLS, respectively, with a pleasantness rating for foods consumed of 124 (sd 14) mm out of 150 mm (83 %). Overall, the food menu produces a relatively reliable measure of EI inside and outside the laboratory. The results also underscore the difficulties in capturing a representative image of food intake given the relatively high day-to-day variation in the amount and composition of foods consumed.

The contribution of visceral adiposity and mid-thigh fat-rich muscle to the metabolic profile in postmenopausal women.

This study explored the relationship between muscle fat infiltration derived from mid-thigh computed tomography (CT) scan, central fat distribution and insulin sensitivity in postmenopausal women. Mid-thigh CT scans were used to measure low attenuation muscle surface (LAMS) (0-34 Hounsfield units (HU)), which represented a specific component of fat-rich muscle. Whole-body insulin sensitivity (M/I) was evaluated by an euglycemic-hyperinsulinemic clamp. A group of 103 women aged 57.0 ± 4.4 years was studied. Women with higher levels of LAMS presented higher metabolic risk features, particularly elevated fasting, 2-h plasma glucose (2hPG) concentrations and diminished M/I (P < 0.05). To further study the contribution of muscle fat infiltration and central adiposity on metabolic parameters, we divided the whole group based on the median of LAMS and visceral adipose tissue (VAT). As expected, the best metabolic profile was found in the Low-LAMS/Low-VAT group and the worst in the High-LAMS/High-VAT group. Women with Low-LAMS/High-VAT presented similar metabolic risks to those with High-LAMS/High-VAT. There was no difference between High-LAMS/Low-VAT and Low-LAMS/Low-VAT, which presents the most healthy metabolic and glycemic profiles as reflected by the lowest levels of cardiovascular disease risk variables. This suggests that High-LAMS/Low-VAT is also at low risk of metabolic deteriorations and that High-LAMS, only in the presence of High-VAT seems associated with deteriorated risks. Although increased mid-thigh fat-rich muscle was related to a deteriorated metabolic profile, VAT appears as a more important contributor to alterations in the metabolic profile in postmenopausal women.

Influence of Physical Activity Participation on the Associations between Eating Behaviour Traits and Body Mass Index in Healthy Postmenopausal Women.

Available data reveals inconsistent relationships between eating behaviour traits and markers of adiposity level. It is thus relevant to investigate whether other factors also need to be considered when interpreting the relationship between eating behaviour traits and adiposity. The objective of this cross-sectional study was thus to examine whether the associations between variables of the Three-Factor Eating Questionnaire (TFEQ) and adiposity are influenced by the level of physical activity participation. Information from the TFEQ and physical activity was obtained from 113 postmenopausal women (56.7 ± 4.2 years; 28.5 ± 5.9 kg/m(2)). BMI was compared between four groups formed on the basis of the physical activity participation and eating behaviour traits medians. In groups of women with higher physical activity participation, BMI was significantly lower in women who presented higher dietary restraint when compared to women who had lower dietary restraint (25.5 ± 0.5 versus 30.3 ± 1.7 kg/m(2), P < .05). In addition, among women with lower physical activity participation, BMI was significantly lower in women presenting a lower external hunger than in those with a higher external hunger (27.5 ± 0.8 versus 32.4 ± 1.1 kg/m(2), P < .001). Our results suggest that physical activity participation should also be taken into account when interpreting the relationship between adiposity and eating behaviour traits.

Predictors of cardiovascular fitness in sedentary men.

The relative contribution of anthropometric and skeletal muscle characteristics to cardiorespiratory fitness was studied in sedentary men. Cardiorespiratory fitness (maximal oxygen consumption) was assessed using an incremental bicycle ergometer protocol in 37 men aged 34-53 years. Vastus lateralis muscle biopsy samples were used to assess fiber type composition (I, IIA, IIX) and areas, capillary density, and activities of glycolytic and oxidative energy metabolic pathway enzymes. Correlations (all p < 0.05) were observed between maximal oxygen consumption (L.min-1) and body mass (r = 0.53), body mass index (r = 0.39), waist circumference (r = 0.34), fat free mass (FFM; r = 0.68), fat mass (r = 0.33), the enzyme activity of cytochrome c oxidase (COX; r = 0.39), muscle type IIA (r = 0.40) and IIX (r = 0.50) fiber area, and the number of capillaries per type IIA (r = 0.39) and IIX (r = 0.37) fiber. When adjusted for FFM in partial correlations, all correlations were lost, with the exception of COX (r = 0.48). Stepwise multiple regression revealed that maximal oxygen consumption was independently predicted by FFM, COX activity, mean capillary number per fiber, waist circumference, and, to a lesser extent, muscle capillary supply. In the absence of regular physical activity, cardiorespiratory fitness is strongly predicted by the potential for aerobic metabolism of skeletal muscle and negatively correlated with abdominal fat deposition.

Cardiorespiratory fitness and components of the metabolic syndrome in sedentary men.

OBJECTIVE: To investigate the relationships between fitness and components of the metabolic syndrome in sedentary men. SUBJECTS AND METHODS: 39 subjects (34-53 years) were evaluated for fitness (VO(2max)) and anthropometric, metabolic, and skeletal muscle phenotypes. VO(2max) was assessed on a bicycle ergometer whereas other variables were obtained from an oral glucose tolerance test (OGTT), hydrostatic weighing, and a muscle biopsy. RESULTS: Pearson and partial correlations adjusted for fat mass (FM), waist circumference (WC), muscle enzyme activities (citrate synthase (CS), cytochrome c oxidase (COX)), and capillary density were used to investigate the independent relationships be tween variables. Negative correlations between VO(2max) and WC as well as blood pressure and OGTT test were observed. When adjusted for FM, correlations remained between VO(2max) and WC (r = -0.46, p < 0.01) and systolic blood pressure (r = -0.35, p < 0.05). When adjusted for WC and CS activity, all correlations were lost except for high-sensitivity C-reactive protein (hs-CRP) (r = -0.34, p < 0.05) which remained when adjusted for CS activity. Adjustment for COX activity failed to remove correlations with hs-CRP (r = -0.36, p < 0.05), age (r = 0.34, p < 0.05), WC (r = -0.35, p < 0.05), and blood pressure. Negative correlations persisted when fitness was adjusted for the mean number of capillaries. CONCLUSION: The effects of fitness on components of the metabolic syndrome in sedentary men are explained by abdominal obesity and muscle phenotypes.