Basal metabolic rate in Brazilian patients with type 2 diabetes: comparison between measured and estimated values

Abstract

Objectives:The aims of this study are to investigate which of the seven selected predictive equation for estimating basal metabolic rate (BMR) is the best alternative to indirect calorimetry (IC) and to evaluate the dietary energy intake in patients with type 2 diabetes. Subjects and methods: Twentyone patients with type 2 diabetes participated in this diagnostic test study. Clinical and laboratorial variables were evaluated as well as body composition by absorptiometry dual X-ray emission (DXA) and BMR measured by IC and estimated by prediction equations. Dietary intake was evaluated by a quantitative food frequency questionnaire. Data were analyzed using Bland-Altman plots, paired t-tests, and Pearson's correlation coefficients. Results: Patients were 62 (48-70) years old, have had diabetes for 8 (2-36) yeas, and 52.4% were females. The mean body composition comprised a fat-free mass of 49.8 ± 9.4 kg and a fat mass of 28.3 ± 7.2 kg. The energy intake was 2134.3 ± 730.2 kcal/day and the BMR by IC was 1745 ± 315 kcal/day. There was a wide variation in the accuracy of BMR values predicted by equations when compared to IC BMR measurement. Harris-Benedict, Oxford, FAO/WHO/ UNO equations produced the smallest differences to IC, with a general bias of < 8%. The FAO/WHO/ UNO equation provided the best BMR prediction in comparison to measured BMR. Conclusion: In patients with type 2 diabetes, the equation of the FAO/WHO/UNO was the one closest to the BMR values as measured by IC.

Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: What can we use?

“…A recent survey of Brazilian patients with type 2 diabetes of both sexes demonstrated wide variation in REE values evaluated by predictive equations. The FAO/WHO/UNO equation showed the best accuracy when compared to measured REE, but still underestimated it by -5.6% as compared to IC a difference of 100 kcal/day [35].…”

“…Previous studies demonstrated that patients with diabetes and poor glycemic control had higher REE [9,25,26]. Data on the use of REE predictive equations in patients with type 2 diabetes have been described elsewhere [9, 10, 14, 21, 22, 24-26, [30][31][32][33][34][35]; however, data on Brazilian diabetic patients are still scarce [34,35]. A cross-sectional study of obese Brazilian women with type 2 diabetes showed that some predictive equations underestimated REE by approximately − 2.6%, while others overestimated it by 10.6%, when compared with IC measurement [34].…”

Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: What can we use?

“…Considering a study power of 80%, alpha error of 5%, and 20% attrition rate, 62 patients would be required. In addition, data from 21 patients with type 2 diabetes from a study previously published by our research group also were used [35]. The means of estimated REE and measured REE were compared by a paired Student's t-test.…”

Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: What can we use?

“…Final analyses were performed per protocol, and we included 62 patients patients with type 2 diabetes (31 men and 31 women). Of these 62 patients, data from 21 patients were used according to a study previously published by our research group [35].The ow diagram of patient selection is shown in Fig. 1 Data sources / measurements…”