Basal metabolic rate using indirect calorimetry among individuals living with overweight or obesity: The accuracy of predictive equations for basal metabolic rate.

BACKGROUND & AIMS: Weight reduction programs in people with overweight or obesity can be informed by indirect calorimetry (IC) which is the gold standard to measure basal metabolic rate (BMR). Since IC is labor intensive and expensive, predictive equations are often used as an alternative. In this study the accuracy rate was assessed and bias statistics of predictive equations were compared to IC among subjects with overweight or obesity. Secondly, differences in clinical features between individuals with over-, accurate or underestimation of their BMR were evaluated. METHODS: This cross sectional study included 731 subjects from the outpatient obesity clinic of the Antwerp University Hospital, Belgium. Fourteen equations were evaluated. Overestimation and underestimation was defined as >10 % and <10 % of measured BMR. RESULTS: In the total population, mean age was 43 ± 13 years, mean BMI 35.6 ± 5.8 kg/m2 and 79.5 % were female. The highest accuracy rates were reached by the Henry (73 %), Ravussin (73 %) and Mifflin St. Jeor (73 %) equations. In the total population, the Mifflin St. Jeor and Henry equation were unbiased. The Akern, Livingston and Ravussin equations were biased to underestimation. All other equations were biased to overestimation. Subjects with an underestimation of BMR had significantly higher waist-hip ratio (1.02 ± 0.13 vs 0.91 ± 0.11; P < 0.001), higher visceral adipose tissue (239 ± 96 vs 162 ± 93; P < 0.001), lower fat free mass (kg) (67.6 (45.4-95.9) vs 54.0 (39.6-95.5); P < 0.001) and a higher prevalence of the Metabolic Syndrome (24 (77.4) vs 112 (37.5); P < 0.001). Individuals with an overestimation of BMR had significantly higher subcutaneous adipose tissue (545 ± 149 vs 612 ± 149; P < 0.05), lower fasting plasma insulin (81 (10-2019) vs 67 (27-253); P < 0.001) and lower 2-h plasma glucose (132 (30-430) vs 116 (43-193); P < 0.001) during OGTT. CONCLUSIONS: In this study, the Henry and Mifflin St. Jeor equations have the highest accuracy and lowest bias to estimate the basal metabolic rate in a Caucasian, predominantly female, population living with overweight or obesity. Visceral and subcutaneous adipose tissue and presence of metabolic syndrome were significantly different in individuals with over- or underestimation of BMR.

Cardio-renal-metabolic disease in primary care setting.

In the primary care setting providers have more tools available than ever before to impact positively obesity, diabetes, and their complications, such as renal and cardiac diseases. It is important to recognise what is available for treatment taking into account diabetes heterogeneity. For those who develop type 2 diabetes (T2DM), effective treatments are available that for the first time have shown a benefit in reducing mortality and macrovascular complications, in addition to the well-established benefits of glucose control in reducing microvascular complications. Some of the newer medications for treating hyperglycaemia have also a positive impact in reducing heart failure (HF). Technological advances have also contributed to improving the quality of care in patients with diabetes. The use of technology, such as continuous glucose monitoring systems (CGM), has improved significantly glucose and glycated haemoglobin A1c (HbA1c) values, while limiting the frequency of hypoglycaemia. Other technological support derives from the use of predictive algorithms that need to be refined to help predict those subjects who are at great risk of developing the disease and/or its complications, or who may require care by other specialists. In this review we also provide recommendations for the optimal use of the new medications; sodium-glucose co-transporter-2 inhibitors (SGLT2i) and Glucagon-like peptide-receptor agonists 1 (GLP1RA) in the primary care setting considering the relevance of these drugs for the management of T2DM also in its early stage.