Measured Versus Predicted Resting Metabolic Rate in Obese Diabetic and Obese Non-Diabetic Subjects

Merghani, Tarig H

doi:10.9790/0853-01026367

Cited by 3 publications

(3 citation statements)

References 23 publications

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“…Many studies show a significant overestimation of BEE with this equation (RMSE 1 = 160–184 kcal/day) (29, 78–80). Huang et al (30) also found an overestimation of 3.3% in men with DM, but an underestimation of −3.1% in women.…”

Section: Assessment Of Energy Expenditure In Subjects With Dmmentioning

confidence: 99%

“…Finally, Miyake et al (81) and de Figueiredo Ferreira et al (82) observed no significant difference with IC (MD 2 = −19 to 42.3 kcal/day). With the Mifflin–St Jeor equation, studies in patients with DM show an under/overestimation of BEE by −126 to 160 kcal/day (80, 81, 83), or no significant difference (29, 78). The Ganpule equation presented no difference with the reference measure (bias 3 = 4.5%) (79) or underestimated BEE by −110 kcal/day (81).…”

Section: Assessment Of Energy Expenditure In Subjects With Dmmentioning

confidence: 99%

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Energy Expenditure in People with Diabetes Mellitus: A Review

et al. 2016

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Physical activity (PA) is an important non-therapeutic tool in primary prevention and treatment of diabetes mellitus (DM). To improve activity-based health management, patients need to quantify activity-related energy expenditure and the other components of total daily energy expenditure. This review explores differences between the components of total energy expenditure in patients with DM and healthy people and presents various tools for assessing the energy expenditure in subjects with DM. From this review, it appears that patients with uncontrolled DM have a higher basal energy expenditure (BEE) than healthy people which must be considered in the establishment of new BEE estimate equations. Moreover, studies showed a lower activity energy expenditure in patients with DM than in healthy ones. This difference may be partially explained by patient with DMs poor compliance with exercise recommendations and their greater participation in lower intensity activities. These specificities of PA need to be taken into account in the development of adapted tools to assess activity energy expenditure and daily energy expenditure in people with DM. Few estimation tools are tested in subjects with DM and this results in a lack of accuracy especially for their particular patterns of activity. Thus, future studies should examine sensors coupling different technologies or method that is specifically designed to accurately assess energy expenditure in patients with diabetes in daily life.

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Section: Assessment Of Energy Expenditure In Subjects With Dmmentioning

confidence: 99%

Section: Assessment Of Energy Expenditure In Subjects With Dmmentioning

confidence: 99%

Energy Expenditure in People with Diabetes Mellitus: A Review

et al. 2016

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“…The results of other studies were inconclusive. In some studies, the HB equation significantly overestimated RMR [ 16 , 34 , 35 , 36 ]. Frankenfield et al [ 26 ] also found an overestimation of RMR in obese subjects—up to 62%.…”

Section: Discussionmentioning

confidence: 99%

Comparison of Equations Estimating Resting Metabolic Rate in Older Adults with Type 2 Diabetes

Buch

Diener

Stern

et al. 2021

JCM

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Measuring resting metabolic rate (RMR) is time-consuming and expensive, and thus various equations for estimating RMR have been developed. This study’s objective was to compare five equations in elderly people with type 2 diabetes (T2DM). RMR was measured in 90 older adults (≥65 years) with T2DM (mean body mass index (BMI) of 31.5 kg/m2), using indirect calorimetry. Results were compared to four frequently used equations (those of Cunningham, Harris and Benedict, and Gougeon developed for young adults with T2DM, and that of Lührmann, which was developed for the elderly), in addition to a new equation developed recently at the Academic College at Wingate (Nachmani) for overweight individuals. Estimation accuracy was defined as the percentage of subjects with calculated RMR within ±10% of measured RMR. Measured RMR was significantly underestimated by all equations. The equations of Nachmani and Lührmann had the best estimation accuracy: 71.4% in males and 50.9% in females. Skeletal muscle mass, fat mass, hemoglobin A1c (HbA1c), and the use of insulin explained 70.6% of the variability in measured RMR. RMR in elderly participants with T2DM was higher than that calculated using existing equations. The most accurate equations for this specific population were those developed for obesity or the elderly. Unbalanced T2DM may increase caloric demands in the elderly. It is recommended to adjust the RMR equations used for the target population.

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Validation of resting metabolic rate equations in obese and non-obese young healthy adults

Al-Domi

Al-Shorman

2018

Clinical Nutrition ESPEN

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Measured Versus Predicted Resting Metabolic Rate in Obese Diabetic and Obese Non-Diabetic Subjects

Cited by 3 publications

References 23 publications

Energy Expenditure in People with Diabetes Mellitus: A Review

Energy Expenditure in People with Diabetes Mellitus: A Review

Comparison of Equations Estimating Resting Metabolic Rate in Older Adults with Type 2 Diabetes

Validation of resting metabolic rate equations in obese and non-obese young healthy adults

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