The Role of Diet and Exercise for the Maintenance of Fat-Free Mass and Resting Metabolic Rate During Weight Loss

2006 ◽  
Vol 36 (3) ◽  
pp. 239-262 ◽  
Author(s):  
Petra Stiegler ◽  
Adam Cunliffe
2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 526-526
Author(s):  
Rachel Silver ◽  
Sai Das ◽  
Michael Lowe ◽  
Susan Roberts

Abstract Objectives There is persistent controversy over the extent to which different components of energy expenditure disproportionately decrease after weight loss and contribute to weight regain through decreased energy requirements. We conducted a secondary analysis of the CALERIE I study to test the hypothesis that decreased resting metabolic rate (RMR) and energy expenditure for physical activity (EEPA) after a 6-month calorie restriction intervention would predict weight regain at 12 months, with a greater decrease in RMR than EEPA. Methods Participants (n = 46) received all food and energy-containing beverages for 6 months. Outcome measures included total energy expenditure by doubly labeled water, RMR by indirect calorimetry, and body composition by BOD POD. Predictions for RMR and EEPA were derived from baseline linear regression models including age, sex, fat mass, and fat free mass. Baseline regression coefficients were used to calculate the predicted RMR and EEPA at 6 months. Residuals were calculated as the difference between measured and predicted values and were adjusted for body weight. The presence of metabolic adaptation was evaluated by a paired t-test comparing measured and predicted RMR at 6 months. Differences between 6-month RMR and EEPA residuals were evaluated by the same method. Linear regression was used to assess the association between 6-month residuals and weight loss maintenance (% weight change, 6 to 12 months). Results Mean weight loss was 6.9% at 6 months with 2.1% regain from 6 to 12 months. No adaptation in RMR was observed at 6 months (mean residual: 19 kcal; 95% confidence interval: −9, 48; P = 0.18). However, significant adaptation was observed in EEPA (mean residual: −199 kcal; −126, −272; P < 0.0001). In addition, the mean 6-month RMR residual was significantly greater than the mean 6-month EEPA residual (218 kcal; 133, 304; P < 0.0001). There was no significant association between 6-month RMR or EEPA residuals and weight regain at 12 months (P = 0.56, 0.34). Conclusions There was no measurable decrease in RMR with weight loss after adjusting for changes in fat free mass and fat mass, but there was a decrease in EEPA. Changes in RMR and EEPA with weight loss over 6 months did not predict weight regain at 12 months. Funding Sources Jean Mayer USDA Human Nutrition Research Center on Aging Doctoral Scholarship; USDA agreement #8050–51000-105–01S


2000 ◽  
Vol 84 (4) ◽  
pp. 515-520 ◽  
Author(s):  
R. Menozzi ◽  
M. Bondi ◽  
A. Baldini ◽  
M. G. Venneri ◽  
A. Velardo ◽  
...  

The reduction in resting metabolic rate (RMR) during weight loss exceeds that accounted for by changes in body composition by 15%, suggesting that factors other than fat-free mass (FFM) explain the metabolic adaptation during food restriction in obesity. Our study aimed to establish if changes in the sympathoadrenal system activity, as inferred from an integrated measure such as 24 h urinary excretion of catecholamines, may play a role in the RMR adaptation observed during dietary restriction in obese patients. Ninety-three obese female subjects consumed a low-energy diet (LED) (2930 kJ/d (700 kcal/d)) for a 3-week period. At the beginning and at the end of the study, 24 h urinary excretion of catecholamines, FFM and RMR were measured. The LED induced a significant reduction in body weight (-3·3 (SEM 0·4) KG; P < 0·01), FFM (-1·9 (sem 0·7) kg; P < 0·01) and in the fat mass (-1·2 (sem 0·5) kg; P < 0·01). Noradrenalin excretion (24 h) decreased during the LED from 264 (sem 26) during a weight-maintenance period to 171 (sem 19) nmol/24 h after consumption of the LED for 3 weeks (P < 0·001); mean 24 h adrenalin excretion did not change during the LED (22 (sem 3) during the weight-maintenance period v. 21 (sem 3) nmol/24 h after consumption of the LED for 3 weeks; NS). The LED induced a significant decrease in RMR (7300 (sem 218) v. 6831 (sem 138) kJ/24 h; P < 0·001). The only independent variable that significantly explained variations in RMR both before and after consumption of the LED for 3 weeks, was FFM (r2 0·79 and r2 0·80 respectively). Urinary noradrenalin excretion explained a further 4 % of the variability in RMR, but only before the diet, so that a role of sympathoadrenal system on RMR seems to be present in obese patients in basal conditions but not at the end of the LED.


Author(s):  
Christopher L. Pankey ◽  
Kyle Flack ◽  
Kelsey Ufholz ◽  
LuAnn Johnson ◽  
James N. Roemmich

Abstract Purpose Models of appetite control have been largely based on negative feedback from gut and adipose signaling to central appetite centers. However, contemporary models posit that fat-free mass (FFM) or the energy demand of FFM [i.e., resting metabolic rate (RMR)] may play a primary role in the motivational drive for food intake (i.e., food reinforcement). The relative reinforcing value of food (RRVfood) is associated with energy intake (EI) and increases with an acute energy deficit. Chronic exercise-induced energy deficits lead to alterations in fat mass (FM), FFM, and RMR and provide an opportunity to test whether change in (∆) FM, ∆FFM, ∆usual EI, or ∆RMR are associated with ∆RRVfood. Methods Participants (n = 29, BMI = 25–35 kg/m2) engaged in aerobic exercise expending 300 or 600 kcal, 5 days/weeks for 12 weeks. The reinforcing value of food (PMaxfood) was measured via a computer-based operant responding task and RRVfood was calculated as the reinforcing value of food relative to non-eating sedentary behaviors. RMR was determined by indirect calorimetry and body composition by DXA. Results Post-training FFM correlated with usual post-training EI (rs = 0.41, p < 0.05), PMaxfood (rs=0.52, p < 0.01), and RMR (rs = 0.85, p < 0.0001). ∆RMR negatively correlated with ∆PMaxfood (rs = − 0.38, p < 0.05) and with ∆RRVfood (rs = − 0.37, p < 0.05). ∆PMaxfood and ∆RRVfood were not associated with ∆FFM (p = 0.71, p = 0.57, respectively). Conclusions Reductions in RMR with weight loss may increase food reinforcement as means of restoring FFM and RMR to pre-weight loss amounts. Limiting reductions in RMR during weight loss may benefit weight maintenance by restricting increases in food reinforcement after weight loss.


2020 ◽  
Author(s):  
Seyedeh Forough Sajjadi ◽  
Atieh Mirzababaei ◽  
nasim Ghodoosi ◽  
Sara Pooyan ◽  
Hana Arghavani ◽  
...  

Abstract Objective Resting metabolic rate (RMR) accounts for most of the daily energy expenditure. The low-carb diet attenuates decreases in RMR. This study aims to investigate the relationship between a low-carb diet and resting metabolic rate status. Methods We enrolled 304 overweight and obese women in this cross-sectional study. BMI, fat mass, fat-free mass, visceral fat, insulin level were assessed. RMR was measured using indirect calorimetry. A low carbohydrate diet score was measured using a validated semi-quantitative food frequency questionnaire (FFQ). Results Our results showed no relationship between LCDS and DNR even after adjust for confounders (Inc. RMR: OR: 0.97; 95% CI: 0.92–1.01, P = 0.20; Dec. RMR: OR: 0.97; 95% CI: 0.94-1.00, P = 0.14). Some components of LCDS had significant differences with DNR, such as carbohydrate and Dec. RMR in adjusted model (OR: 1.62; 95% CI: 0.98–1.37, P = 0.08), MUFA and Dec. RMR in adjusted model (OR: 0.48; 95% CI: 0.21–1.10, P = 0.08) and refined grain and Inc. RMR in crude model (OR: 0.87; 95% CI: 0.77–0.99, P = 0.04). Conclusion Our study showed that there is no association between a low-carb diet and RMR status but carbohydrate, MUFA, and refined grain had a significant relationship.


Nutrients ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 3394
Author(s):  
Sarah A. Purcell ◽  
Ryan J. Marker ◽  
Marc-Andre Cornier ◽  
Edward L. Melanson

Many breast cancer survivors (BCS) gain fat mass and lose fat-free mass during treatment (chemotherapy, radiation, surgery) and estrogen suppression therapy, which increases the risk of developing comorbidities. Whether these body composition alterations are a result of changes in dietary intake, energy expenditure, or both is unclear. Thus, we reviewed studies that have measured components of energy balance in BCS who have completed treatment. Longitudinal studies suggest that BCS reduce self-reported energy intake and increase fruit and vegetable consumption. Although some evidence suggests that resting metabolic rate is higher in BCS than in age-matched controls, no study has measured total daily energy expenditure (TDEE) in this population. Whether physical activity levels are altered in BCS is unclear, but evidence suggests that light-intensity physical activity is lower in BCS compared to age-matched controls. We also discuss the mechanisms through which estrogen suppression may impact energy balance and develop a theoretical framework of dietary intake and TDEE interactions in BCS. Preclinical and human experimental studies indicate that estrogen suppression likely elicits increased energy intake and decreased TDEE, although this has not been systematically investigated in BCS specifically. Estrogen suppression may modulate energy balance via alterations in appetite, fat-free mass, resting metabolic rate, and physical activity. There are several potential areas for future mechanistic energetic research in BCS (e.g., characterizing predictors of intervention response, appetite, dynamic changes in energy balance, and differences in cancer sub-types) that would ultimately support the development of more targeted and personalized behavioral interventions.


1990 ◽  
Vol 259 (2) ◽  
pp. E233-E238 ◽  
Author(s):  
N. K. Fukagawa ◽  
L. G. Bandini ◽  
J. B. Young

The relationship between fat-free mass (FFM) and resting metabolic rate (RMR) was compared in young men (n = 24; age 18-33 yr), old men (n = 24; 69-89 yr), and old women (n = 20; 67-75 yr). Body composition was assessed using anthropometry, bioelectrical impedance analysis (BIA), and isotope dilution with 18O-labeled water. RMR was measured at least twice using an open-circuit indirect calorimetry system with a ventilated hood. The results indicate that the different methods for assessing body composition vary substantially and should not be used interchangeably. Anthropometry was not adequate to assess group differences in body fatness, although skinfold measures may be appropriate for within-group comparisons. BIA correlated well with the isotope-dilution technique and may be a useful measure of FFM. Finally, RMR was lower in the old men than the young (1.04 +/- 0.02 vs. 1.24 +/- 0.03 kcal/min, P less than 0.001) and remained lower even when adjusted for FFM estimated by isotope dilution (P less than 0.001). RMR in the women was also lower (0.84 +/- 0.02 kcal/min), but in contrast to the difference between young and old men, RMR adjusted for FFM did not differ (P = 0.16) between old men and women. Therefore, it is clear that differences in FFM cannot fully account for the lower RMR in the old, suggesting that aging is associated with an alteration in tissue energy metabolism.


Sign in / Sign up

Export Citation Format

Share Document