Resting Energy Expenditure: From Cellular to Whole‐Body Level, a Mechanistic Historical Perspective

Heymsfield, Steven B.; Smith, Brooke; Dahle, Jared H; Kennedy, Samantha; Fearnbach, Nicole; Thomas, Diana M.; Bosy‐Westphal, Anja; Müller, Manfred J.

doi:10.1002/oby.23090

Cited by 35 publications

(34 citation statements)

References 81 publications

(143 reference statements)

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“…The same applies to FFM alone or combined with fat mass in REE prediction models. In the present study, we observed that high muscularity was accompanied mainly by a larger liver and kidney mass but not by a larger brain mass, an organ with a high mass‐specific metabolic rate (240 kcal/kg/day) 3 . Resting energy expenditure prediction equations with weight, height and age as covariates have lower R 2 s and SEEs than those that include individual organs and tissues, as do REE prediction equations formulated on fat mass, FFM, and age as covariates 8 .…”

Section: Discussionsupporting

confidence: 39%

“…That is, for the same BMI, body builders have a smaller percentage of body weight as fat mass than their sex‐matched and age‐matched inactive counterparts. Similarly, people of the same sex, age, and body mass but who differ in muscularity will also differ in REE; for the same mass, SM has a three‐fold higher mass‐specific metabolic rate than does adipose tissue 3 . Sparingly little is known about how muscularity and its accompanying physical and metabolic effects vary between people in the general population.…”

Section: Introductionmentioning

confidence: 99%

“…2 Basal metabolic rate, or resting energy expenditure (REE), may be only second to BMI as a globally used measure predicted from body weight, height, and in some cases age in clinical settings. 3 Resting energy expenditure equations typically only account for about 47% and 62% of between individual differences in measured REE in men and women, respectively. 4 As with BMI-%fat associations, 53% and 38% of the variance in respective REE predictions based on weight, height, and age go unaccounted for.…”

Section: Introductionmentioning

confidence: 99%

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Phenotypic differences between people varying in muscularity

Heymsfield

Smith

Chung

et al. 2022

J cachexia sarcopenia muscle

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Background Body mass is the primary metabolic compartment related to a vast number of clinical indices and predictions. The extent to which skeletal muscle (SM), a major body mass component, varies between people of the same sex, weight, height, and age is largely unknown. The current study aimed to explore the magnitude of muscularity variation present in adults and to examine if variation in muscularity associates with other body composition and metabolic measures. Methods Muscularity was defined as the difference (residual) between a person's actual and model‐predicted SM mass after controlling for their weight, height, and age. SM prediction models were developed using data from a convenience sample of 492 healthy non‐Hispanic (NH) White adults (ages 18–80 years) who had total body SM and SM surrogate, appendicular lean soft tissue (ALST), measured with magnetic resonance imaging and dual‐energy X‐ray absorptiometry, respectively; residual SM (SMR) and ALST were expressed in kilograms and kilograms per square meter. ALST mass was also evaluated in a population sample of 8623 NH‐White adults in the 1999–2006 National Health and Nutrition Examination Survey. Associations between muscularity and variation in the residual mass of other major organs and tissues and resting energy expenditure were evaluated in the convenience sample. Results The SM, on average, constituted the largest fraction of body weight in men and women up to respective BMIs of 35 and 25 kg/m2. SM in the convenience sample varied widely with a median of 31.2 kg and an SMR inter‐quartile range/min/max of 3.35 kg/−10.1 kg/9.0 kg in men and 21.1 kg and 2.59 kg/−7.2 kg/7.5 kg in women; per cent of body weight as SM at 25th and 75th percentiles for men were 33.1% and 39.6%; corresponding values in women were 24.2% and 30.8%; results were similar for SMR indices and for ALST measures in the convenience and population samples. Greater muscularity in the convenience sample was accompanied by a smaller waist circumference (men/women: P < 0.001/=0.085) and visceral adipose tissue (P = 0.014/0.599), larger liver (P = 0.065/<0.001), kidneys (P = 0.051/<0.009), and bone mineral (P < 0.001/<0.001), and larger magnitude resting energy expenditure (P < 0.001/<0.001) than predicted for the same sex, age, weight, and height. Conclusions Muscle mass is the largest body compartment in most adults without obesity and is widely variable in mass across people of similar body size and age; and high muscularity is accompanied by distinct body composition and metabolic characteristics. This previously unrecognized heterogeneity in muscularity in the general population has important clinical and research implications.

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Section: Discussionsupporting

confidence: 39%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Phenotypic differences between people varying in muscularity

Heymsfield

Smith

Chung

et al. 2022

J cachexia sarcopenia muscle

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“…Of note, body components including fat mass (FM) and lean tissue mass (LTM) are key contributors of REE. 24 The distribution of body composition differs between sexes in CKD. 25 More importantly, FM per se is closely associated with adipokines levels.…”

Section: Introductionmentioning

confidence: 99%

Association of Serum Adipokines and Resting Energy Expenditure in Patients with Chronic Kidney Disease

Abi

Yang

et al. 2022

Preprint

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Background and aim: Metabolic disorders are prevalent in patients with chronic kidney disease (CKD) and may lead to protein energy wasting. Adipokines play a vital role in energy metabolism. We aimed to determine the relationship between adipokine levels and resting energy expenditure (REE) in patients with CKD.Methods: A total of 208 patients in non-dialyzed CKD stages 3–5 were enrolled in this cross-sectional study. Serum adipokines (leptin, adiponectin, and interleukin 6 (IL-6) were measured using enzyme-linked immunosorbent assay. Patient's REE was measured using indirect calorimetry. Fat mass (FM) and lean tissue mass (LTM) were measured using multiple-frequency bioimpedance analysis. Spearman correlation analyses and multivariate linear regression models were used to assess the association between serum adipokines and REE.Results: The mean age was 52.7 ± 14.6 years, and 26.9%, 26.4%, and 46.7% of our participants had CKD stages 3, 4, and 5, respectively. The median values of serum adiponectin, leptin, and IL-6 were 470.4 (range, 291.1–802.2), 238.1 (range, 187.9–418.4), and 4.0 (range, 2.4–9.5) pg/mL, respectively. The male participants had significantly lower FM% (P = 0.001) and lower leptin levels (P < 0.001) than the female participants. After adjusting for age, diabetes, high-sensitivity C-reactive protein, intact parathyroid hormone, LTM, and FM, multiple linear regression analysis revealed that serum leptin levels were significantly positively associated with REE in men rather than in women (P < 0.05). Serum adiponectin levels were inversely associated with REE in men, but this association disappeared while FM was additionally adjusted. Adiponectin levels in women were not correlated with REE (P > 0.05). IL-6 was not significantly associated with REE in either men or women.Conclusions: A sex-specific relationship between serum adipokines (leptin and adiponectin) and REE was observed in patients with CKD stages 3–5, which was partly confounded by FM.Trial registration: This trial was registered at clinicaltrials.gov (NCT03377413).

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“…Therefore, we aimed to explore the independent relationship between circulating adipokines (leptin, adiponectin, and IL-6) and REE. Of note, body components including fat mass (FM) and lean tissue mass (LTM) are key contributors of REE ( 24 ). The distribution of body composition differs between sexes in CKD ( 25 ).…”

Section: Introductionmentioning

confidence: 99%

Association of Serum Adipokines and Resting Energy Expenditure in Patients With Chronic Kidney Disease

Abi

Yang

et al. 2022

Front. Nutr.

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Background and AimMetabolic disorders are prevalent in patients with chronic kidney disease (CKD) and may lead to protein energy wasting (PEW). Adipokines improve connections between PEW and energy metabolism. We aimed to determine the relationship between adipokine levels and resting energy expenditure (REE) in patients with CKD.MethodsA total of 208 patients in non-dialyzed CKD stages 3–5 were enrolled in this cross-sectional study. Serum adipokines (leptin, adiponectin, and interleukin 6 (IL-6) were measured using enzyme-linked immunosorbent assay. Patient's REE was measured using indirect calorimetry. Fat mass (FM) and lean tissue mass (LTM) were measured using multiple-frequency bioimpedance analysis. Spearman correlation analyses and multivariate linear regression models were used to assess the association between serum adipokines and REE.ResultsThe mean age was 52.7 ± 14.6 years, and 26.9, 26.4, and 46.7% of our participants had CKD stages 3, 4, and 5, respectively. The median values of serum adiponectin, leptin, and IL-6 were 470.4 (range, 291.1–802.2), 238.1 (range, 187.9–418.4), and 4.0 (range, 2.4–9.5) pg/mL, respectively. The male participants had significantly lower FM% (P = 0.001) and lower leptin levels (P < 0.001) than the female participants. After adjusting for age, diabetes, high-sensitivity C-reactive protein, intact parathyroid hormone, LTM, and FM, multiple linear regression analysis revealed that serum leptin levels were significantly positively associated with REE in men rather than in women (P < 0.05). Serum adiponectin levels were inversely associated with REE in men, but this association disappeared while FM was additionally adjusted. Adiponectin levels in women were not correlated with REE (P > 0.05). IL-6 was not significantly associated with REE in either men or women.ConclusionsA sex-specific relationship between serum adipokines (leptin and adiponectin) and REE was observed in patients with CKD stages 3–5, which was partly confounded by FM.

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Resting Energy Expenditure: From Cellular to Whole‐Body Level, a Mechanistic Historical Perspective

Cited by 35 publications

References 81 publications

Phenotypic differences between people varying in muscularity

Phenotypic differences between people varying in muscularity

Association of Serum Adipokines and Resting Energy Expenditure in Patients with Chronic Kidney Disease

Association of Serum Adipokines and Resting Energy Expenditure in Patients With Chronic Kidney Disease

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