New Predictive Equations for Estimating Resting Energy Expenditure in Adults With Crohn's Disease

Abstract

Background Increased resting energy expenditure (REE) has been hypothesized to be a potential cause of weight loss in individuals with Crohn's disease (CD). This study aimed to develop and validate new predictive equations for estimating REE in adults with CD. Methods Adults, ages 18–65 years, with CD were recruited. Anthropometry, indirect calorimetry, and bioimpedance analysis were performed in all patients. Disease activity was assessed by Crohn's Disease Activity Index. The new predictive equations were generated using different regression models. Prediction accuracy of the new equations was assessed and compared with the most commonly used equations. Results A total of 270 CD patients (159 males, 111 females) were included and randomly assigned to the calibration (n = 180) and validation groups (n = 90). REE was directly correlated with weight and bioimpedance index, whereas the relation with both age and disease activity was inverse. The new equations were suitable for estimating REE at population level (bias: −0.2 and −0.3, respectively). Individual accuracy was good in both models (≥80%, respectively), especially in females; and similar results were shown by some of the selected equations. But, when accuracy was set within ±5%, the new equations gave the highest prediction. Conclusion The new, disease‐specific, equations for predicting REE in individuals with CD give a good prediction accuracy as far as those proposed in the literature for the general population. However, the new ones performed better at the individual level. Further studies are needed to verify the reliability and usefulness of these new equations.

Dietary Habits Are Related to Phase Angle in Male Patients with Non-Small-Cell Lung Cancer

“…There are no data on the relationship between PhA and RMR in lung cancer patients. Interestingly, PhA has been found to be a significant predictor of resting energy expenditure in athletes [ 36 ], healthy subjects [ 37 , 38 ], and patients with Crohn’s disease [ 39 ], possibly reflecting the association of PhA with lean mass and muscle quality [ 40 ]. This discrepancy may be due to the inherent differences in the studied populations since we included only male subjects with advanced-stage NSCLC.…”

Resting Energy Expenditure in Elite Athletes: Development of New Predictive Equations Based on Anthropometric Variables and Bioelectrical Impedance Analysis Derived Phase Angle

“…Alternatively, raw BIA variables such as bioimpedance index (BI-Index) and phase angle (PhA) might be taken into account. Given that BI-index is a direct proxy marker of FFM, while PhA is related to body cell mass [17], a relationship between energy expenditure and BI-index and PhA has already been observed in normal-weight or overweight subjects [18] as well as in patients with obesity [19] and Crohn's disease [20].…”

“…Not surprisingly, the results of these studies showed that the raw BIA variables may improve the prediction power under physiological conditions [18], but only by a limited extent in subjects possibly with altered body water distribution [19,20].…”

“…Alternatively, raw BIA variables such as bioimpedance index (BI-Index) and phase angle (PhA) might be taken into account. Given that BI-index is a direct proxy marker of FFM, while PhA is related to body cell mass [17], a relationship between energy expenditure and BI-index and PhA has already been observed in normal-weight or overweight subjects [18] as well as in patients with obesity [19] and Crohn's disease [20].Not surprisingly, the results of these studies showed that the raw BIA variables may improve the prediction power under physiological conditions [18], but only by a limited extent in subjects possibly with altered body water distribution [19,20].Based on this background, the primary aim of this study was to develop and validate new predictive equations of REE speci c for elite athletes, considering not only the anthropometric measures, but also the raw BIA variables as predictors. Additionally, we evaluated in elite athletes of different sports the accuracy of selected predictive equations of REE (for general population or athletes) at both population and individual level.…”

Resting energy expenditure in elite athletes: development of new predictive equations based on anthropometric variables and bioelectrical impedance analysis derived phase angle

“…the ratio between extracellular water-ECW and total body water-TBW) [ 22 ], body cell mass and cellular integrity [ 23 ]. So far, a relationship between REE and BI-index and/or PhA has already been observed in normal-weight or overweight subjects [ 24 ] as well as in patients with obesity [ 25 ] and Crohn’s disease [ 26 ]. Not surprisingly, the results of these studies suggest that raw BIA variables may improve the prediction power under physiological conditions [ 24 ], but only to a limited extent in subjects with altered body water distribution [ 25 , 26 ].…”