Influence of segmental body composition and adiposity hormones on resting metabolic rate and substrate utilization in overweight and obese adults

Hirsch, Katie R.; Smith‐Ryan, Abbie E.; Blue, Malia N.M.; Mock, Meredith G.; Trexler, Eric T.

doi:10.1007/s40618-017-0616-z

Cited by 25 publications

(20 citation statements)

References 48 publications

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“…The strong baseline associations we found between FFM and fat mass on one side and RMR on the other side have previously been reported ( 35 ). Interestingly, when comparing intervention-induced changes in Study 2, the association between FFM and RMR disappeared, whereas the association between fat mass and RMR persisted.…”

Section: Discussionsupporting

confidence: 82%

Resting Metabolic Rate Does Not Change in Response to Different Types of Training in Subjects with Type 2 Diabetes

et al. 2017

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Background and objectivesAmbiguous results have been reported regarding the effects of training on resting metabolic rate (RMR), and the importance of training type and intensity is unclear. Moreover, studies in subjects with type 2 diabetes (T2D) are sparse. In this study, we evaluated the effects of interval and continuous training on RMR in subjects with T2D. Furthermore, we explored the determinants for training-induced alterations in RMR.MethodsData from two studies, both including T2D subjects, were encompassed in this manuscript. Study 1 was a randomized, crossover study where subjects (n = 14) completed three, 2-week interventions [control, continuous walking training (CWT), interval-walking training (IWT)] separated by washout periods. Training included 10 supervised treadmill sessions, 60 min/session. CWT was performed at moderate walking speed [aiming for 73% of walking peak oxygen uptake (VO2peak)], while IWT was performed as alternating 3-min repetitions at slow (54% VO2peak) and fast (89% VO2peak) walking speed. Study 2 was a single-arm training intervention study where subjects (n = 23) were prescribed 12 weeks of free-living IWT (at least 3 sessions/week, 30 min/session). Before and after interventions, RMR, physical fitness, body composition, and glycemic control parameters were assessed.ResultsNo overall intervention-induced changes in RMR were seen across the studies, but considerable inter-individual differences in RMR changes were seen in Study 2. At baseline, total body mass (TBM), fat-free mass (FFM), and fat mass were all associated with RMR. Changes in RMR were associated with changes in TBM and fat mass, and subjects who decreased body mass and fat mass also decreased their RMR. No associations were seen between changes in physical fitness, glycemic control, or FFM and changes in RMR.ConclusionNeither short-term continuous or interval-type training, nor longer term interval training affects RMR in subjects with T2D when no overall changes in body composition are seen. If training occurs concomitant with a reduction in fat mass, however, RMR is decreased.Clinical Trials Registration ()NCT02320526 and NCT02089477.

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Section: Discussionsupporting

confidence: 82%

Resting Metabolic Rate Does Not Change in Response to Different Types of Training in Subjects with Type 2 Diabetes

et al. 2017

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“…The 24‐h RQ has been shown to aggregate in family, and it has been suggested that it is at least in part genetically determined . The 24‐h RQ has also been shown to be statistically related to various individual characteristics such as percent body fat, plasma insulin, free fatty acid concentration, sex, ethnicity, age, waist circumference, fat mass and trunk fat mass, and adipocyte size and basal lipolysis measured in isolated hepatocytes from the periumbilical region . However, in perfect energy balance as well as in a given energy imbalance, the 24‐h RQ measured with a stable diet for some days only depends on the macronutrient composition of the diet and energy balance.…”

Section: Significance Of Rqmentioning

confidence: 99%

Low capacity to oxidize fat and body weight

Péronnet

Haman

2019

Obesity Reviews

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For a given positive energy balance, a low capacity to oxidize fat could contribute to weight gain (low fat oxidation hypothesis). This hypothesis is based on the arguments that for a given stable diet and food quotient (FQ), the respiratory quotient (RQ) is higher in obesity prone (OP) than in obesity resistant individuals (OR) and that a high RQ predicts higher future weight gain. A review of 42 studies shows that there is no convincing experimental support to these arguments and thus for the low fat oxidation hypothesis. A power analysis also shows that this hypothesis might be impossible to experimentally confirm because very large numbers of subjects would be needed to reject the null hypotheses that the 24-h RQ is not different in OP and OR or that future weight gain is not different in individuals with a low and high 24-h RQ at baseline. A re-examination of the significance of the 24-hour and fasting RQ also shows that the assumption underlying the low fat oxidation hypothesis that a high RQ reflects a low capacity to oxidize fat is not valid: For a stable diet, the 24-h RQ entirely depends on FQ and energy balance, and the fasting RQ mainly depends on the FQ and energy balance and on the size of glycogen stores. KEYWORDS food quotient, fuel partitioning, obesity, respiratory quotient 1 | INTRODUCTION It has been hypothesized that fat accumulation and weight gain could be favoured by two defects in fat oxidation: (a) a low intrinsic capacity to oxidize fat, 1-3 which characterizes "low fat oxidizers" 3,4 ("low fat oxidation hypothesis" of weight gain), or (b) a low ability to quickly adjust fat oxidation to an increase in fat intake, 5-8 which is one of the characteristics of individuals with "metabolic inflexibility" 9 ("metabolic inflexibility hypothesis" of weight gain). According to the low fat oxidation hypothesis of weight gain, for a given positive energy balance, fat oxidation is lower and fat accumulation is higher in individuals with a low than a high intrinsic capacity to oxidize fat, and over time, this could result in larger weight gains. 3 According to the "metabolic inflexibility hypothesis" of weight gain, for a given energy intake (EI), the slow adjustment of fat oxidation to an increase in fat intake in individuals with metabolic inflexibility favours fat storage with a compensatory increase in glucose oxidation from carbohydrate (CHO) stores. The result is a reduction in glycogen stores that could be a signal for increasing food intake and EI through the glycogenostatic model of the control of appetite. [5][6][7][8] Because of constant day-to-day variations in the percentage of fat in the diet, individuals with metabolic inflexibility could repeatedly accumulate small amounts of fat, which over time could lead to weight gain.List of abbreviations: ACC2, acetyl-CoA carboxylase 2; AICAR, 5-aminoimidazole-4-carboxamide ribonucleotide; AMPK, AMP-activated kinase; BMI, body mass index; CHO, carbohydrate; d, difference in 24-h RQ estimated between OP and OR; d/SD, standardized difference; EE, ...

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“…The rate of age-related loss in LM has been shown to be greater in the lower body/legs (Goodpaster et al, 2006;Janssen et al, 2000). Greater leg LM has previously been shown to be associated with a higher resting metabolic rate in both men and women (Hirsch et al, 2017). In addition to LM quantity, muscle quality also declines with age and obesity.…”

Section: Introductionmentioning

confidence: 99%

High‐intensity interval training and essential amino acid supplementation: Effects on muscle characteristics and whole‐body protein turnover

et al. 2020

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Influence of segmental body composition and adiposity hormones on resting metabolic rate and substrate utilization in overweight and obese adults

Cited by 25 publications

References 48 publications

Resting Metabolic Rate Does Not Change in Response to Different Types of Training in Subjects with Type 2 Diabetes

Resting Metabolic Rate Does Not Change in Response to Different Types of Training in Subjects with Type 2 Diabetes

Low capacity to oxidize fat and body weight

High‐intensity interval training and essential amino acid supplementation: Effects on muscle characteristics and whole‐body protein turnover

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