comment Progress and challenges in analyzing rodent energy expenditure Whole-body energy expenditure is the summed metabolic activities of tissues and, to remove the infuence of body size, ratios of energy expenditure to body mass are often applied but can generate spurious diferences. In 2011, a group of experts proposed adoption of ANCOVA for the analysis of metabolic rate but, seven years later, analyses based on ratios remain the most frequent. We discuss some of the barriers to adopting better analytical procedures. Rodrigo Fernández-Verdejo, Eric Ravussin, John R. Speakman and Jose E. Galgani I n humans, average body mass index has increased over the last few decades 1 . This is mostly explained by a shift towards the right in the distribution of individuals with larger body mass, while body mass of leaner individuals has remained unaltered 2 . Such heterogeneous propensity to weight-gain prompts the search for factors that alter the energy balance. Technologies to measure energy expenditure in humans and rodents have made remarkable progress 3,4 . Additionally, genetic manipulation of rodent models allows discernment of the influence of genetics on metabolic rate with an unprecedented sophistication. However, this has not been mirrored by improved methodologies to analyze metabolic rates. Metabolic rate is often divided by body mass to “normalize” data for size differences between animals, which is mathematically wrong. Knowledge of this problem, and the approach to overcome it, dates back to the 1950s 5,6 . However, compared with calculating ratios, manual calculation of the analysis of covariance (ANCOVA) was time consuming. In the 1980s, computational analysis eased calculations and increased interest in the appropriate analyses in the field of human metabolism 7 and in ecological studies of small mammals 8 . ANCOVA thus became the common approach to adjust for body size. In contrast, studies of small laboratory rodents persisted in using ratios. This erroneous practice has continued despite papers pointing out the potential for spurious results 9,10 . To reach a consensus on how mouse energy metabolism should be analyzed, a large group of experts in mouse and human metabolism discussed conceptual, analytical and practical aspects involved in measuring energy metabolism in mice 11 . They proposed ANCOVA as a way to conduct, analyze and interpret metabolic studies. Here, we assess how successful the application of ANCOVA has been in mouse metabolism studies. Energy balance and weight gain Body weight represents the combined mass of water, protein, fat and carbohydrate. The extent to which these molecules are retained in a living organism is a function of the energy flux 12 . Such flux is dynamic, with a constant exchange between the macromolecules entering the body through feeding, and the molecules leaving the body through oxidation. A mismatch of this flux (in versus out) modifies body weight and composition, leading to obesity in the case of chronic positive energy balance. Accurate, precise and continuous determination of energy expenditure and intake is thus crucial for understanding body weight control. In the best scenario, we should isolate the primary event driving energy imbalance, that is, higher energy intake or lower energy expenditure, before changes in body mass occur. Living organisms are, however, almost never in neutral energy balance, because organisms acquire and dissipate energy at variable rates. Therefore, distinguishing normal hour-to-hour energy disparity from the imbalance that will lead to obesity is challenging. Thus, energy balance is often compared in animals of different body mass and/or composition. Nevertheless, as body mass and composition influence energy metabolism, these variables must be controlled to determine the influence of other variables (for example, genotype). Comparison of energy expenditure in mice Several studies have assessed the effect of factors, such as diets and genes, on energy expenditure of animals that differ in body mass and/or composition. Such differences may alter metabolic rate. Therefore, a highly debated issue is how to normalize energy expenditure for differences in body size. An extensively used normalization method is dividing metabolic rate by body mass. However, this approach is inappropriate because the regression line between body mass and metabolic rate does not have a zero intercept, and is therefore not linearly ANCOVA and no normalization (n = 3) ANCOVA and ratios (n = 2) ANCOVA only (n = 6) Detectable difference between groups (kcal d –1 ) 1.5 kcal d –1 s.d. 1.0 kcal d –1 s.d. 0.5 kcal d –1 s.d. a b 0 0 1.5 1.0 0.5 2.0 64 48 32 16 6 Mice per group (n) Ratios only (n = 45) No normalization (n = 10) ANCOVA, ratios and no normalization (n = 3) Ratios and no normalization (n = 8) Total = 77 articles Fig. 1 | Analytical aspects in rodent metabolic studies. a, Detectable difference in energy expenditure according to the number of mice per group. The mean energy expenditure of the control group was assumed as 10 kcal d –1 , with standard deviations (s.d) for control and experimental groups of 0.5, 1.0 and 1.5 kcal d –1 . SAS 9.2 (SAS Institute) was used for calculations, using two-sided Student’s t test with α = 0.05 and β = 0.20. b, Frequency of the method used to compare energy expenditure in mice among the studies retrieved. NATURE METHODS | www.nature.com/naturemethods