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Background: An adequate dietary energy supply is particularly important in patients with lipedema as it promotes weight and fat loss. Accurate estimation of resting metabolic rate (RMR) allows implementing a proper calorie restriction diet in patients with lipedema. Therefore, an accurate assessment of energy demand in patients with lipedema is crucial in clinical practice. Our study aimed to compare actual resting metabolic rate (aRMR) with predicted resting metabolic rate (pRMR) in women with lipedema and to determine the association between individual anthropometric measurements and aRMR.Methods: A total of 108 women diagnosed with lipedema were enrolled in the study. aRMR was measured by indirect calorimetry (IC) using FitMate WM metabolic system (Cosmed, Rome, Italy). pRMR was estimated with predictive equations and BIA. All anthropometric measurements were based on BIA (bioelectric impedance analysis).Results: The mean aRMR in the study group was 1705.2 ± 320.7 kcal/day. Most methods of predicted RMR measurement used in our study significantly underpredicted aRMR in patients with lipedema. We reported statistically significant high correlations between all anthropometric measurements and aRMR/pRMR and a moderate correlation between visceral fat level (VFL) and aRMR. Conclusions: aRMR in patients with lipedema calculated with predictive equations was significantly lower than aRMR measured with other methods. This study found the agreement of predictive equations compared to IC is low (<60%). Fat-free mass (FFM) is a stronger determinant of RMR in patients with lipedema than fat mass.
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Background: An adequate dietary energy supply is particularly important in patients with lipedema as it promotes weight and fat loss. Accurate estimation of resting metabolic rate (RMR) allows implementing a proper calorie restriction diet in patients with lipedema. Our study aimed to compare actual resting metabolic rate (aRMR) with predicted resting metabolic rate (pRMR) in women with lipedema and to determine the association between individual body composition parameters, body mass index, and aRMR. Methods and Results: A total of 108 women diagnosed with lipedema were enrolled in the study. aRMR was obtained by indirect calorimetry (IC) using FitMate WM metabolic system (Cosmed, Rome, Italy). pRMR was estimated with predictive equations and bioelectric impedance analysis (BIA). All body composition parameters were based on BIA. The mean aRMR in the study group was 1705.2 ± 320.7 kcal/day. This study found the agreement of predictive equations compared to IC is low (<60%). Most methods of predicted RMR measurement used in our study significantly underpredicted aRMR in patients with lipedema. Therefore, the most applied equations remain useless in clinical practice in this specific population due to large individual differences among the studied women. Conclusions: IC is the best tool to evaluate RMR in evaluated patients with lipedema. It is necessary to propose a new equation to RMR determination in clinical practice.
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