Estimates of Resting Energy Expenditure and Total Energy Expenditure Using Predictive Equations for Individuals After Bariatric Surgery: a Systematic Review with Meta-analysis.

PURPOSE: Patients after metabolic bariatric surgery (MBS) require attention to maintain energy balance and avoid weight regain. Predictive equations for resting energy expenditure (REE) and total energy expenditure (TEE) are needed since gold standard methods like calorimetry and doubly labeled water are rarely available in routine clinical practice. This study aimed to determine which predictive equation for REE and TEE has the lowest bias in subjects after MBS. METHODS: MEDLINE, Embase, Web of Science, and CENTRAL searches were performed. Meta-analyses were performed with the data calculated by the predictive equations and measured by the gold standard methods for those equations that had at least two studies with these data. The DerSimonian and Laird random-effects model and the I2 statistic were used to quantify heterogeneity in the quantitative analyses. The risk of bias was assessed using the Joanna Briggs Institute critical appraisal checklist. RESULTS: Seven studies were included. The present study found that the Mifflin St. Jeor (1990) equation had the lowest bias (mean difference = - 39.71 kcal [95%CI = - 128.97; 49.55]) for calculating REE in post-BS individuals. The Harris-Benedict (1919) equation also yielded satisfactory results (mean difference = - 54.60 kcal [95%CI = - 87.92; - 21.28]). CONCLUSION: The predictive equation of Mifflin St. Jeor (1990) was the one that showed the lowest bias for calculating the REE of patients following MBS.

The relationship between total energy expenditure and physical activity level in women living in an impoverished Brazilian urban area.

OBJECTIVE: This study aimed to describe how strong is the relationship between TEE and PAL in women living in an impoverished Brazilian urban area. METHODS: Anthropometric, hormonal (insulin, TSH, FT4 , and FT3 ), body composition (deuterium), TEE (doubly labeled water) and PAL (metabolic equivalent task [MET]-7-day triaxial accelerometer, ActivPAL®) data were collected from 55 women (mean age: 31y, mean BMI: 27.4 kg/m2 ). Adjusted-TEE models were calculated incorporating the residuals of anthropometric, hormonal, and body composition variables in the TEE, to assess the relation between MET and adjusted-TEE, through three different analyzes: linear regression, nonlinear regression and change-point regression. RESULTS: Most participants (89.1%, n = 49) were classified as low-active. There was no association between crude TEE and MET.h/d (R2  = 0.05; p = 0.09). There was a positive, although weak, linear relationship between adjusted-TEE and MET.h/d (ß = 2705.26 kcal; 95% CI: 436.25; 4974.27; adj-R2  = 0.08). A change point of this relationship was identified in the MET.h/d value of 1.53 (SD = 0.02; adj-R2 = 0.13). The association between adjusted-TEE and MET.h/d before the change point (ß = 5101.46 kcal; 95%CI: 978.84; 9224.08; adj-R2  = 0.11) was stronger than the association in the full linear model, nevertheless, it was still weak. This association stop existing when it is assessed in individuals after the change point (ß = -6609.92 kcal; 95%CI: -16773.24; 3553.40; adj-R2  = 0.08). CONCLUSIONS: These results suggest that the relationship between TEE and PAL is weak and it is not completely linear in women living in an impoverished Brazilian urban area.

Agreement between the total energy expenditure calculated with accelerometry data and the BMR yielded by predictive equations v. the total energy expenditure obtained with doubly labelled water in low-income women with excess weight.

Low-income women are the group with the highest levels of obesity worldwide. In low-income settings, the use of predictive equations, which yield a measure of the individuals' BMR, is a feasible approach to estimate the individuals' total energy expenditure (TEE), using the factorial method (calculated-TEE = BMR × physical activity level), an important step of the obesity nutritional care. The present study aimed to identify the predictive equation that, in conjunction with metabolic equivalents of tasks (MET) data from accelerometers, yields the calculated-TEE with better agreement compared with the TEE measured by doubly labelled water (TEE-DLW). Forty-five women aged 19-45 years, with excess weight and mothers of undernourished children, were included. They received DLW to determine TEE (14 d); at the same time, they used triaxial accelerometers (7 d) to estimate their MET. The Bland-Altman method, paired-sample t tests, concordance correlation coefficient and root-mean-square error were used to assess the agreement. Maximum allowed differences were defined as 24 %, based on the within-variance coefficient of the energy intake of the sample. Eleven equations were studied. The calculated-TEE obtained by five equations showed non-significant bias: Dietary Reference Intake (Institute of Medicine (2005) Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids), FAO/WHO/UNU ((2001) Food and Nutrition Technical Report Series), Harris & Benedict ((1919) Proc Natl Acad Sci USA4, 370-373), Henry & Rees ((1991) Eur J Clin Nutr45, 177-185) and Schofield ((1985) Hum Nutr Clin Nutr39, 5-41). The mean percentage differences were -1·5, -0·8, 2·2, -2·2 and 2·0 %, respectively. Considering all parameters, FAO/WHO/UNU ((2001) Food and Nutrition Technical Report Series) equation performed slightly better than the others; nevertheless, no equation in conjunction with the estimated-MET showed a calculated-TEE with its CI for the Bland-Altman limits of agreement inside the pre-defined acceptable range.