Analysis of energy metabolism in humans: A review of methodologies

Lam, Yan Y.; Ravussin, Éric

doi:10.1016/j.molmet.2016.09.005

Cited by 107 publications

(77 citation statements)

References 178 publications

(209 reference statements)

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“…Energy intake was calculated as the sum of mean energy expenditure across pregnancy (doubly labeled water) and energy deposition in fat and fat-free tissues (3-compartment model by plethysmography and isotope dilution) measured across the same observation period (29,30). Secondary outcomes were changes in physical activity by accelerometry (31), energy expenditure during sleep by whole-body calorimetry (32), metabolic biomarkers, dietary intake by remote food photography (33,34), and eating behavior constructs by validated questionnaires. Pregnancy, delivery, and infant outcomes were obtained from prenatal and delivery records.…”

Section: Methodsmentioning

confidence: 99%

Evidence-based recommendations for energy intake in pregnant women with obesity

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Amant

Hsia

et al. 2019

Journal of Clinical Investigation

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METHODS. This was a prospective, observational study of pregnant women with obesity. The primary outcome was energy intake calculated by the energy intake-balance method. Energy expenditure was measured by doubly labeled water and whole-room indirect calorimetry and body composition as a 3-compartment model by air displacement plethysmography and isotope dilution in early (13-16 weeks) and late (35-37 weeks) pregnancy. RESULTS. In pregnant women with obesity (n = 54), recommended weight gain (n = 8, 15%) during the second and third trimesters was achieved when energy intake was 125 ± 52 kcal/d less than energy expenditure. In contrast, women with excess weight gain (67%) consumed 186 ± 29 kcal/d more than they expended (P < 0.001). Energy balance affected maternal adiposity (recommended:-2.5 ± 0.8 kg fat mass; excess: +2.2 ± 0.5; inadequate:-4.5 ± 0.5; P < 0.001) but not fetal growth. Weight gain was not related to demographics, activity, metabolic biomarkers, or diet quality. We estimated that energy intake requirements for recommended weight gain during the second and third trimesters were not increased as compared with energy requirements early in pregnancy (34 ± 53 kcal/d, P = 0.83). CONCLUSION. We here provide what we believe are the first evidence-based recommendations for energy intake in pregnant women with obesity. Contrary to current recommendations, energy intake should not exceed energy expenditure. TRIAL REGISTRATION. ClinicalTrials.gov, NCT01954342.

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Section: Methodsmentioning

confidence: 99%

Evidence-based recommendations for energy intake in pregnant women with obesity

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Amant

Hsia

et al. 2019

Journal of Clinical Investigation

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“…The equipment for measuring EE varied substantially among the studies (heart rate monitor, accelerometers, indirect calorimetry, spirometry). Spirometry remains the gold standard for evaluating EE [58]. EE data derived from the SenseWear (BodyMedia, Inc., USA) accelerometers were shown to be reliable during light-intensity stepping [59].…”

Section: Discussionmentioning

confidence: 99%

Effects of cycle and treadmill desks on energy expenditure and cardiometabolic parameters in sedentary workers: review and meta-analysis

Podrekar

Kozinc

Šarabon

2019

International Journal of Occupational Safety and Ergonomics

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The aim of this article was to evaluate the effects of cycle and treadmill desks on energy expenditure and cardiovascular and biochemical indicators in sedentary workers. Materials and methods. In February 2018, six databases were searched. Both parallel and crossover design studies evaluating workplace cycle and treadmill desks compared to a conventional seated condition were included. Results. Twenty-two studies met the inclusion criteria. Cycle and treadmill desks significantly increased energy expenditure (standard mean difference [SMD] = 3.84, p < 0.001, I 2 = 95%) and the heart rate (SMD = 1.68, p < 0.001, I 2 = 91%), and lowered blood glucose and insulin levels (SMD =-0.54, p < 0.001, I 2 = 0% and SMD =-3.13, p < 0.001, I 2 = 76%, respectively). The interventions had no effect on blood pressure and other biochemical indicators. Conclusion. Cycle and treadmill desks may positively influence energy expenditure in sedentary workers and could be effective for reducing negative effects of workplace-related sedentary behaviour. However, considerable heterogeneity is present in the measuring protocols for energy expenditure.

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“…Additional applications for which knowledge of metabolic cost is useful include prescription of training intensities (American College of Sports Medicine, 2000), advancement of geriatric medicine (Mian et al, 2006;Canavan et al, 2009;Corbett et al, 2017), treatment of clinical gait disorders (Waters and Mulroy, 1999), and to monitor energy intake and expenditure in obese patients (Brychta et al, 2010). Though various methods exist to measure metabolic cost (Lam and Ravussin, 2016), technical challenges resulting from cost, feasibility, or medical restrictions of the subject population limit the availability of metabolic cost measurements.…”

Section: Model Personalization Affects Metabolic Cost?mentioning

confidence: 99%

Musculoskeletal Model Personalization Affects Metabolic Cost Estimates for Walking

Arones

Shourijeh

Patten

et al. 2020

Preprint

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Assessment of metabolic energy cost as a metric for human performance has expanded across various fields within the scientific, clinical, and engineering communities. As an alternative to measuring metabolic cost experimentally, musculoskeletal models incorporating metabolic cost models have been developed. However, to utilize these models for practical applications, the accuracy of their metabolic cost predictions requires improvement. Previous studies have reported the benefits of using personalized musculoskeletal models for various applications, yet no study has evaluated how model personalization affects metabolic cost estimation. This study investigated the effect of musculoskeletal model personalization on estimates of metabolic cost of transport (CoT) during post-stroke walking using three commonly used metabolic cost models. We analyzed data previously collected from two male stroke survivors with right-sided hemiparesis. The three metabolic cost models were implemented within three musculoskeletal modeling approaches involving different levels of personalization. The first approach used a scaled generic OpenSim model and found muscle activations via static optimization (SOGen). The second approach used a personalized EMG-driven musculoskeletal model with personalized functional axes but found muscle activations via static optimization (SOCal). The third approach used the same personalized EMG-driven model but calculated muscle activations directly from EMG data (EMGCal). For each approach, the muscle activation estimates were used to calculate each subject’s cost of transport (CoT) at different gait speeds using three metabolic cost models (Umberger 2003, Umberger 2010, and Bhargava 2004). The calculated CoT values were compared with published CoT trends as a function of stance time, double support time, step positions, walking speed, and severity of motor impairment (i.e., Fugl-Meyer score). Overall, U10-SOCal, U10-EMGCal, U03-SOCal, and U03-EMGCal were able to produce slopes between CoT and the different measures of walking asymmetry that were statistically similar to those found in the literature. Although model personalization seemed to improve CoT estimates, further tuning of parameters associated with the different metabolic cost models in future studies may allow for realistic CoT predictions. An improvement in CoT predictions may allow researchers to predict human performance, surgical, and rehabilitation outcomes reliably using computational simulations.

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Analysis of energy metabolism in humans: A review of methodologies

Cited by 107 publications

References 178 publications

Evidence-based recommendations for energy intake in pregnant women with obesity

Evidence-based recommendations for energy intake in pregnant women with obesity

Effects of cycle and treadmill desks on energy expenditure and cardiometabolic parameters in sedentary workers: review and meta-analysis

Musculoskeletal Model Personalization Affects Metabolic Cost Estimates for Walking

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