Activity Diary Method for Predicting Energy Expenditure as Evaluated by a Whole-Body Indirect Human Calorimeter

Yamamura, Chiaki; Tanaka, Shigeho; Futami, Jun; Oka, Jun; Ishikawa-Takata, Kazuko; Kashiwazaki, Hiroshi

doi:10.3177/jnsv.49.262

Cited by 23 publications

(10 citation statements)

References 19 publications

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“…Tacke et al [44] subjects mainly had heart failure of NYHA functional class II or III, and thus severity of heart failure was similar between their study and ours. REE in our patients with heart failure was similar to that in healthy Japanese individuals reported in previous studies [34,45,46], one of which was carried out by our group, and no increases in energy metabolism were confirmed. Also, there was no correlation between BNP level and mREE/BW; in other words, there was no correlation between severity of heart failure and energy metabolism.…”

Section: Discussion/conclusionsupporting

confidence: 90%

Energy Metabolism and Nutritional Status in Hospitalized Patients with Chronic Heart Failure

et al. 2020

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Introduction: Malnutrition is a factor that defines vital prognosis in chronic heart failure. Objective: This study investigated nutritional and metabolic disorders in patients with heart failure by examining the association of severity of heart failure with inflammatory cytokines, appetite-regulating hormones, and energy metabolism. Methods: Subjects were 50 patients with heart failure. On admission, nutritional status was assessed, and biochemical blood tests were performed, including for serum tumor necrosis factor-α, interleukin-6, ghrelin, and leptin levels. Resting energy expenditure (REE) was also measured by indirect calorimetry to examine its association with severity of heart failure and levels of inflammatory cytokines and appetite-regulating hormones. Results: There were significant associations between serum brain natriuretic peptide (BNP) level and nutrition indices, indicating that nutritional status was worse when heart failure was more severe. Inflammatory cytokine levels showed significant positive correlations with BNP level. Measured REE/bodyweight was not associated with severity of heart failure, but was negatively correlated with body fat percentage and leptin levels. Conclusions: Energy metabolism was not associated with serum BNP level among patients with heart failure with New York Heart Association functional class up to III. Body fat percentage and leptin levels may be a good predictor of energy metabolism in patients with heart failure.

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Section: Discussion/conclusionsupporting

confidence: 90%

Energy Metabolism and Nutritional Status in Hospitalized Patients with Chronic Heart Failure

et al. 2020

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“…Ganpule et al (2007) suggested recently that the use of FAO/WHO/UNU equations overestimated BMR among Japanese when compared with measured BMR. The predictive equations used in the present study were established based on the large database obtained under strictly controlled protocol, and have been reported to be accurate for Japanese (Taguchi et al, 2001;Rafamantanantsoa et al, Yamamura et al, 2003). Therefore, the error from using predicted BMR seems to be modest.…”

Section: Discussionmentioning

confidence: 98%

Physical activity level in healthy free-living Japanese estimated by doubly labelled water method and International Physical Activity Questionnaire

et al. 2007

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Objective: To measure total energy expenditure (TEE) for normal healthy Japanese by the doubly labelled water (DLW), and to compare the physical activity level (PAL) among categories classified by the categories used in daily reference intake (DRI), Japan and the International Physical Activity Questionnaire (IPAQ). Subjects and methods: A total of 150 healthy Japanese men and women aged 20-to 59-year-old living in four districts of Japan. TEE was measured by the DLW method, and the PAL was calculated from TEE divided by basal metabolic rate. Simultaneously with TEE measurement, the PAL was assessed employing the categories used in DRI, Japan and IPAQ. Results: The average TEE and PAL were 10.7871.67 MJ/day and 1.7270.22 for males and 8.3771.30 MJ/day and 1.7270.27 for females, respectively. The subjects in the highly active categories assessed by both DRI and IPAQ showed significantly higher PAL compared with less active categories. However, PALs among light and moderate categories by DRI, and insufficient and sufficiently active by IPAQ were not significantly different. Conclusions: In developed countries, highly active subjects could be assessed by a simple questionnaire. However, the questionnaire should be improved to clarify the sedentary to moderately active subjects by assessing carefully very light to moderate physical activity.

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“…The measurement was performed using a human calorimeter from 0715 to 0800, or using a mask and Douglas bag for 20 min with a minute of intermission. The detailed protocol is described in Yamamura et al (2003). To examine whether slightly different conditions caused a significant difference in the observed BMR, analysis of covariance with BMR as the dependent variable and gender, age, stature and body weight as covariates was employed.…”

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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Activity Diary Method for Predicting Energy Expenditure as Evaluated by a Whole-Body Indirect Human Calorimeter

Cited by 23 publications

References 19 publications

Energy Metabolism and Nutritional Status in Hospitalized Patients with Chronic Heart Failure

Energy Metabolism and Nutritional Status in Hospitalized Patients with Chronic Heart Failure

Physical activity level in healthy free-living Japanese estimated by doubly labelled water method and International Physical Activity Questionnaire

Interindividual variability in sleeping metabolic rate in Japanese subjects

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