Faculty Opinions recommendation of What causes intraspecific variation in resting metabolic rate and what are its ecological consequences?

Abstract. Objectives: Obesity plays an important role in the development of chronic diseases including cardiovascular disease and diabetes. A low resting metabolic rate (RMR) for a given body size and composition is a risk factor for obesity, however, there is limited evidence available regarding the association of nutrient patterns and RMR. The aim of this study was to determine the association of nutrient patterns and RMR in overweight and obese women. Study design: This cross-sectional study was conducted on 360 women who were overweight or obese. Method: Dietary intake was assessed using a semi-quantitative standard food frequency questionnaire (FFQ). Nutrient patterns were also extracted by principal components analysis (PCA). All participants were evaluated for their body composition, RMR, and blood parameters. Result: Three nutrient patterns explaining 64% of the variance in dietary nutrients consumption were identified as B-complex-mineral, antioxidant, and unsaturated fatty acid and vitamin E (USFA-vit E) respectively. Participants were categorized into two groups based on the nutrient patterns. High scores of USFA-vit E pattern was significantly associated with the increase of RMR (β = 0.13, 95% CI = 0.79 to 68.16, p = 0.04). No significant associations were found among B-complex-mineral pattern (β = −0.00, 95% CI = −49.67 to 46.03, p = 0.94) and antioxidant pattern (β = 0.03, 95% CI −41.42 to 22.59, p = 0.56) with RMR. Conclusion: Our results suggested that the “USFA-vit E” pattern (such as PUFA, oleic, linoleic, vit.E, α-tocopherol and EPA) was associated with increased RMR.

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Use of an ECAL indirect calorimeter measuring resting metabolic rate and fat burning capacity in a lifestyle medicine clinic for adults with diabetes, pre-diabetes and unwanted obesity

Obesity Abstracts ◽

10.1530/obabs.01.p28 ◽

2019 ◽

Author(s):

Sue Beckers

Keyword(s):

Metabolic Rate ◽

Resting Metabolic Rate ◽

Lifestyle Medicine ◽

Medicine Clinic

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Validation of Equations for the Prediction of Resting Metabolic Rate in Sri Lankan Adults

International Journal of Scientific and Research Publications (IJSRP) ◽

10.29322/ijsrp.9.10.2019.p9462 ◽

2019 ◽

Vol 9 (10) ◽

pp. p9462

Author(s):

Pathima Fairoosa ◽

Indu Waidyatilaka ◽

Maduka de Lanerolle-Dias ◽

Pujitha Wickramasinghe ◽

Pulani Lanerolle

Keyword(s):

Metabolic Rate ◽

Resting Metabolic Rate ◽

Sri Lankan

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High Intensity Interval Circuit Training on Resting Metabolic Rate in Overweight Adults

Case Medical Research ◽

10.31525/ct1-nct03972059 ◽

2019 ◽

Author(s):

Keyword(s):

Metabolic Rate ◽

High Intensity ◽

Resting Metabolic Rate ◽

Circuit Training ◽

High Intensity Interval ◽

Overweight Adults

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The Metabolic Theory of Ecology

10.1093/oso/9780199551668.003.0012 ◽

2017 ◽

Author(s):

Andrew Clarke

Keyword(s):

Metabolic Rate ◽

Resting Metabolic Rate ◽

Effect Of Temperature ◽

Thermal Ecology ◽

Model Data ◽

Metabolic Theory ◽

Physical Explanation ◽

Boltzmann Factor ◽

Scaling Exponents ◽

Metabolic Theory Of Ecology

The model of West, Brown & Enquist (WBE) is built on the assumption that the metabolic rate of cells is determined by the architecture of the vascular network that supplies them with oxygen and nutrients. For a fractal-like network, and assuming that evolution has minimised cardiovascular costs, the WBE model predicts that s=metabolism should scale with mass with an exponent, b, of 0.75 at infinite size, and ~ 0.8 at realistic larger sizes. Scaling exponents ~ 0.75 for standard or resting metabolic rate are observed widely, but far from universally, including in some invertebrates with cardiovascular systems very different from that assumed in the WBE model. Data for field metabolic rate in vertebrates typically exhibit b ~ 0.8, which matches the WBE prediction. Addition of a simple Boltzmann factor to capture the effects of body temperature on metabolic rate yields the central equation of the Metabolic Theory of Ecology (MTE). The MTE has become an important strand in ecology, and the WBE model is the most widely accepted physical explanation for the scaling of metabolic rate with body mass. Capturing the effect of temperature through a Boltzmann factor is a useful statistical description but too simple to qualify as a complete physical theory of thermal ecology.

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The low-carbohydrate-diet score is associated with resting metabolic rate: an epidemiologic study among Iranian adults

Journal of Diabetes & Metabolic Disorders ◽

10.1007/s40200-021-00832-0 ◽

2021 ◽

Author(s):

Saba Mohammadpour ◽

Parivash Ghorbaninejad ◽

Hossein Shahinfar ◽

Mojdeh Ebaditabar ◽

Nadia Babaei ◽

...

Keyword(s):

Metabolic Rate ◽

Resting Metabolic Rate ◽

Epidemiologic Study ◽

Carbohydrate Diet ◽

Low Carbohydrate Diet ◽

Low Carbohydrate ◽

Diet Score

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Metabolic traits in brown trout (Salmo trutta) vary in response to food restriction and intrinsic factors

Conservation Physiology ◽

10.1093/conphys/coaa096 ◽

2020 ◽

Vol 8 (1) ◽

Author(s):

Louise C Archer ◽

Stephen A Hutton ◽

Luke Harman ◽

W Russell Poole ◽

Patrick Gargan ◽

...

Keyword(s):

Life History ◽

Metabolic Rate ◽

Intraspecific Variation ◽

Brown Trout ◽

Environmental Conditions ◽

Food Restriction ◽

Metabolic Rates ◽

Intrinsic Factors ◽

Metabolic Traits ◽

Food Conditions

Abstract Metabolic rates vary hugely within and between populations, yet we know relatively little about factors causing intraspecific variation. Since metabolic rate determines the energetic cost of life, uncovering these sources of variation is important to understand and forecast responses to environmental change. Moreover, few studies have examined factors causing intraspecific variation in metabolic flexibility. We explore how extrinsic environmental conditions and intrinsic factors contribute to variation in metabolic traits in brown trout, an iconic and polymorphic species that is threatened across much of its native range. We measured metabolic traits in offspring from two wild populations that naturally show life-history variation in migratory tactics (one anadromous, i.e. sea-migratory, one non-anadromous) that we reared under either optimal food or experimental conditions of long-term food restriction (lasting between 7 and 17 months). Both populations showed decreased standard metabolic rates (SMR—baseline energy requirements) under low food conditions. The anadromous population had higher maximum metabolic rate (MMR) than the non-anadromous population, and marginally higher SMR. The MMR difference was greater than SMR and consequently aerobic scope (AS) was higher in the anadromous population. MMR and AS were both higher in males than females. The anadromous population also had higher AS under low food compared to optimal food conditions, consistent with population-specific effects of food restriction on AS. Our results suggest different components of metabolic rate can vary in their response to environmental conditions, and according to intrinsic (population-background/sex) effects. Populations might further differ in their flexibility of metabolic traits, potentially due to intrinsic factors related to life history (e.g. migratory tactics). More comparisons of populations/individuals with divergent life histories will help to reveal this. Overall, our study suggests that incorporating an understanding of metabolic trait variation and flexibility and linking this to life history and demography will improve our ability to conserve populations experiencing global change.

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