Open Access Research Article Article ID: GJODMS-4-122

    Study of the Effect of Mobile Indirect Calorimeter on Weight Management

    Craig Stump*, David Jackemeyer, Yulia Abidov, Karen Herbst, Nongjian Tao and Erica Forzani

    This study investigates the effect of utilizing a personalized resting metabolic rate (RMR) mobile tracker based on indirect calorimetry during a 6-month pilot weight loss intervention. Volunteer subjects were randomized to an intervention group participating in a weight loss program utilizing the mobile tracker (IG; N=19) or a control group (CG: N=20) who participated in the same weight loss program, but without the RMR mobile tracker. All subjects were overweight or obese with either type 2 diabetes mellitus (T2DM) or high risk for T2DM. The subjects measured their body weight, physical activity, and caloric intake for 6 months attempting to meet a specific caloric intake goal. The total energy expenditure (TEE) of the subjects was defined as follows: For the CG, TEE was calculated based on daily physical activity, and resting energy expenditure estimated by the Harris-Benedict predictive equation. For the IG, TEE was calculated based on daily physical activity and measuring weekly resting energy expenditure with the mobile indirect calorimeter. The calorie intake goal for each subject was defined as a deficit of 500 kCal/day with respect to their TEE. Adherence to the recommended calorie intake goal during the 6-month period was evaluated via the entries in a calorie intake counter application. In addition, changes in weight, body composition, and blood metabolic profile after 6 months was compared to baseline measurements. The results indicated that the use of the mobile indirect calorimeter in the IG had positive effects on weight loss rate (89% in the IG vs. 50% in the CG, p = 0.05), and a 70% higher adherence to calorie tracking than the CG (p = 0.03). Furthermore, the IG showed statistically significant reduction vs. the CG in weight (p=0.03), body mass index (p = 0.03) and percent of weight loss (p=0.01), and an increase in HDL cholesterol vs. CG (p = 0.04).

    Keywords: Resting metabolic rate; Resting energy expenditure; Energy expenditure; Weight management; Energy balance; Calorie intake tracking; Diabetes; Overweight; Personal fitness monitors

    Published on: Apr 17, 2017 Pages: 44-50

    Full Text PDF Full Text HTML DOI: 10.17352/2455-8583.000022
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