Metabolic profile of clinically severe obese patients.

Autor: Faria SL; Gastrocirurgia de Brasília, Brasilia, Brazil. silvialeitefaria@brturbo.com.br, Faria OP, Menezes CS, de Gouvêa HR, de Almeida Cardeal M
Jazyk: angličtina
Zdroj: Obesity surgery [Obes Surg] 2012 Aug; Vol. 22 (8), pp. 1257-62.
DOI: 10.1007/s11695-012-0651-y
Abstrakt: Background: Since low basal metabolic rate (BMR) is a risk factor for weight regain, it is important to measure BMR before bariatric surgery. We aimed to evaluate the BMR among clinically severe obese patients preoperatively. We compared it with that of the control group, with predictive formulas and correlated it with body composition.
Methods: We used indirect calorimetry (IC) to collect BMR data and multifrequency bioelectrical impedance to collect body composition data. Our sample population consisted of 193 patients of whom 130 were clinically severe obese and 63 were normal/overweight individuals. BMR results were compared with the following predictive formulas: Harris-Benedict (HBE), Bobbioni-Harsch (BH), Cunningham (CUN), Mifflin-St. Jeor (MSJE), and Horie-Waitzberg & Gonzalez (HW & G). This study was approved by the Ethics Committee for Research of the University of Brasilia. Statistical analysis was used to compare and correlate variables.
Results: Clinically severe obese patients had higher absolute BMR values and lower adjusted BMR values (p < 0.0001). A positive correlation between fat-free mass and a negative correlation between body fat percentage and BMR were found in both groups. Among the clinically severe obese patients, the formulas of HW & G and HBE overestimated BMR values (p = 0.0002 and p = 0.0193, respectively), while the BH and CUN underestimated this value; only the MSJE formulas showed similar results to those of IC.
Conclusions: The clinically severe obese patients showed low BMR levels when adjusted per kilogram per body weight. Body composition may influence BMR. The use of the MSJE formula may be helpful in those cases where it is impossible to use IC.
Databáze: MEDLINE