Energy balance in a respiration chamber: individual adjustment of energy intake to energy expenditure

Schrauwen, Patrick; Lichtenbelt, Wouter D. van Marken; Westerterp, K.R.

doi:10.1038/sj.ijo.0800471

Cited by 31 publications

(33 citation statements)

References 9 publications

(11 reference statements)

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“…Measurements SMR was defined as the average EE of all EEs at 15-min intervals between 2300 and 0700 over an 8 h of sleep (SMR8h) and the minimum EE during 3 consecutive hours of sleep (SMR-3h) (Schrauwen et al, 1997;Westerterp-Plantenga et al, 2002). Two open-circuit IHCs were used to evaluate SMR.…”

Section: Study Protocolmentioning

confidence: 99%

Interindividual variability in sleeping metabolic rate in Japanese subjects

et al. 2007

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Introduction: Basal metabolic rate (BMR) or sleeping metabolic rate (SMR) is the largest component of total energy expenditure (EE). An accurate prediction of BMR or SMR is needed to accurately predict total EE or physical activity EE for each individual. However, large variability in BMR and SMR has been reported. Objectives: This study was designed to develop prediction equations using body size measurements for the estimation of both SMR and BMR and to compare the prediction errors with those in previous reports. Methods: We measured body size, height, weight and body composition (fat mass and fat-free mass) from skinfold thickness in adult Japanese men (n ¼ 71) and women (n ¼ 66). SMR was determined as the sum of EE during 8 h of sleep (SMR-8h) and minimum EE during 3 consecutive hours of sleep (SMR-3h) measured using two open-circuit indirect human calorimeters. BMR was determined using a human calorimeter or a mask and Douglas bag. Results: The study population ranged widely in age. The SMR/BMR ratio was 1.0170.09 (range 0.82-1.42) for SMR-8h and 0.9470.07 (range 0.77-1.23) for SMR-3h. The prediction equations for SMR accounted for a 3À5% larger variance with 2-3% smaller standard error of estimate (SEE) than the prediction equations for BMR. Discussion: SMR can be predicted more accurately than previously reported, which indicates that SMR interindividual variability is smaller than expected, at least for Japanese subjects. The prediction equations for SMR are preferable to those for BMR because the former exhibits a smaller prediction error than the latter.

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Section: Study Protocolmentioning

confidence: 99%

Interindividual variability in sleeping metabolic rate in Japanese subjects

et al. 2007

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“…Energy balance was based on individually measured and calculated energy requirements. After measurement of sleeping metabolic rate (SMR) during the first night in the respiration chamber, an estimated total daily EE (TDEE) was calculated by multiplying SMR with a physical activity index of 1.55 (13). Macronutrient composition of all meals was 47, 38, and 15% energy from carbohydrate, fat, and protein, respectively.…”

Section: Articles Integrative Physiologymentioning

confidence: 99%

Cold‐Induced Adaptive Thermogenesis in Lean and Obese

Wijers

Saris

Lichtenbelt

2010

Obesity

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On entering a cold environment, people react by increasing insulation and energy expenditure (EE). However, large interindividual differences exist in the relative contribution of each mechanism. Short‐term studies revealed that obese subjects increase EE (i.e., adaptive thermogenesis) less than lean subjects, which might have implications for the predisposition to obesity. In this study, we validate the differences in adaptive thermogenesis between lean and obese upon midterm mild cold exposure. Therefore, 10 lean and 10 obese subjects were exposed for 48 h to mild cold (16 °C) in a respiration chamber. The preceding 36 h they stayed in the same chamber at a neutral temperature (22 °C) for the baseline measurements. EE, physical activity, skin temperature, and core temperature have been measured for the last 24 h of both parts. Mean daytime EE increased significantly in the lean subjects (P < 0.01), but not in the obese. Physical activity decreased significantly in the lean (P < 0.01) and the obese (P < 0.001) subjects. The change in EE was related to the change in physical activity in both groups (respectively R2 = 0.673, P < 0.01 and R2 = 0.454, P < 0.05). Upon mild cold exposure, lean subjects decreased proximal skin temperature less, but distal skin temperature more than obese. In conclusion, the interindividual differences in cold‐induced thermogenesis were related to changes in physical activity in both lean and obese, pointing at the existence of individual variation in physical activity to compensate for cold‐induced thermogenesis. Furthermore, although a large part of the lean subjects counteracted the cold by increasing EE, most obese subjects changed temperature distribution, and therefore, increased insulation.

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“…Spontaneous physical activity is limited in the respiratory chamber, which may explain the low CV of 24-h TEE 29) . Although, the CV for spontaneous physical activity in the respiratory chamber is around 8% to 10% 21,27,30) , the CV for 24-h TEE is essentially the same after adjusting for day-to-day differences in spontaneous physical activity 28) .…”

Section: Applicationsmentioning

confidence: 92%

“…SMR can be calculated as the lowest energy expenditure value over a period of 3 hours of continuous sleep 30) , as the energy expenditure during the time period when the amount of activity is the lowest 57) , or as the morning energy expenditure when waking consciousness is at its lowest 58) .…”

Section: Components Of Total Energy Expenditure (Resting Metabolic Ramentioning

confidence: 99%

“…Accordingly, the reproducibility of 24-h substrate oxidation, in repeated measurements of an individual subject when dietary conditions are not controlled prior to measurements, is worse with a CV of 2.6% for RQ, 24.9% for fat oxidation, and 15.3% for CHO oxidation. 64) It is important that subjects maintain their achieved energy balance when estimating substrate oxidation while in the respiratory chamber 30,65,66) .…”

Section: Components Of Total Energy Expenditure (Resting Metabolic Ramentioning

confidence: 99%

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Human calorimetry: Energy expenditure and substrate utilization easurements using a respiratory chamber

Hibi

Ando

Tanaka³

et al. 2013

JPFSM

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Respiratory chambers are the current gold standard for assessing human energy expenditure and substrate utilization over a long period of time (several hours to several days), based on oxygen consumption, carbon dioxide production, and urinary nitrogen excretion. Analysis of human energy metabolism using a respiratory chamber provides information about the total energy expenditure (TEE), sleeping metabolic rate (SMR), resting metabolic rate, dietinduced thermogenesis (DIT), activity-induced thermogenesis (AIT), and substrate oxidation. In this review, we describe the theoretical underpinnings of the respiratory chamber, as well as the measurement reproducibility and applications as study endpoints for indirect calorimetry. In humans, the coefficients of variation in energy expenditure and substrate utilization were estimated by 24-h repeatability studies. Under the appropriate conditions, the coefficients of variation for TEE were 1% to 5%, SMR was around 1%, DIT was around 40%, AIT was around 10%, and substrate oxidation was around 5%. Factors that impact energy expenditure and substrate oxidation have been reported, and future weight changes can be predicted based on the 24-h respiratory quotient and substrate oxidation. As the 24-h energy expenditure and substrate oxidation are affected by the 24-h energy balance, it is important to consider the subject's energy balance prior to and during calorimetry. Accurate measurements of energy and substrate balance (intake minus utilization) will contribute to a better understanding of the conditions that lead to changes in body weight. Properly obtaining measurements using a respiratory chamber requires a thorough understanding of the measurement principles and calculation methods, as well as an appropriate protocol.

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Energy balance in a respiration chamber: individual adjustment of energy intake to energy expenditure

Cited by 31 publications

References 9 publications

Interindividual variability in sleeping metabolic rate in Japanese subjects

Interindividual variability in sleeping metabolic rate in Japanese subjects

Cold‐Induced Adaptive Thermogenesis in Lean and Obese

Human calorimetry: Energy expenditure and substrate utilization easurements using a respiratory chamber

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