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Historically, obese individuals were believed to have lower energy expenditure (EE) rates than nonobese individuals (normal and overweight), which, in the long term, would contribute to a positive energy balance and subsequent weight gain. The aim of this review was to critically appraise studies that compared measures of EE and its components, resting EE (REE), activity EE (AEE), and diet-induced thermogenesis (DIT), in obese and nonobese adults to elucidate whether obesity is associated with altered EE. Contrary to popular belief, research has shown that obese individuals have higher absolute REE and total EE. When body composition (namely the metabolically active component, fat-free mass) is taken into account, these differences between obese and nonobese individuals disappear, suggesting that EE in obese individuals is not altered. However, an important question is whether AEE is lower in obese individuals because of a decrease in overall physical activity or because of less energy expended while performing physical activity. AEE and DIT could be reduced in obese individuals, mostly because of unhealthy behavior (low physical activity, higher intake of fat). However, the current evidence does not support the hypothesis that obesity is sustained by lower daily EE or REE. Future studies, comparing EE between obese and nonobese and assessing potential physiologic abnormalities in obese individuals, should be able to better answer the question of whether these individuals have altered energy metabolism.
In 2008, the WHO released a report highlighting that >1 in 10 of the world’s adult population was obese (1). The latest publication that presented worldwide prevalence rates for overweight and obesity estimated that the proportion of adults with a BMI (in kg/m2) of ≥25 increased between 1980 and 2013 from 28.8% to 36.9% in men and from 29.8% to 38.0% in women (2). With increasing prevalence rates, the epidemic shows no signs of abating without dedicated efforts to countermeasure it. Unfortunately, currently available approaches to treat obesity are often deemed ineffective, owing to the high rate of relapse seen with treatment-induced weight loss (3). However, to be successful in this approach, an understanding of the physiologic determinants of obesity should be carefully considered.
Obesity is characterized by an excess storage of fat, arising from an imbalance between energy intake and energy expenditure (EE)7. Although our understanding of the regulation of body weight and energy balance has advanced substantially over the past few decades, the influence that the alterations in EE can have on tipping the scale toward a positive energy balance remains debatable. Low EE was suggested to play a role in the development of obesity because of lower resting EE (REE), activity EE (AEE), diet-induced thermogenesis (DIT), or a combination of all these components, contributing toward positive energy balance and subsequent weight gain (4). Although the concept that individuals with obesity have a “slow metabolism” is a popular belief introduced in an earlier study (5), studies conducted over the past 30 y have reported contradictory findings, proposing that these individuals may, in fact, have higher absolute EE than their nonobese counterparts (6–13).
The aim of this review is to critically appraise published studies that have compared measures of REE, AEE, DIT, and total EE between obese and nonobese adults. Here, potential differences in EE (and its components) between obese and nonobese adults are examined, and whether these differences could contribute to sustaining obesity is discussed. Notably, this discussion may not be valid for all obesity cases. Genetic and endocrine disorders that may affect energy metabolism are conditions beyond the scope of this review.
Unless otherwise specified, the WHO classification of normal weight, overweight, and obesity is used (1). The term “nonobese” is used for normal-weight and overweight individuals (BMI < 30), whereas the term “obese” is used for obese (class I of BMI between 30 and 35 and class II of BMI between 35 and 40) and severely obese (class III of BMI ≥ 40) individuals.
Relevant terms related to energy metabolism are defined in Table 1.
We have understood and documented the cause of obesity as an imbalance between energy consumption and expenditure since the early 1900s. Although this view underlies the premise of much of today’s research into the causes of obesity, the past few decades have substantially contributed toward a dramatic increase in our understanding of the physiology that drives the regulation of energy balance.
We now know that the origin of this disease is an interaction between genetic, environmental, and psychosocial factors that lead to a positive energy balance. The 1990s marked an era in which many of the initial physiologic pathways and systems associated with obesity were developed, and, although debated at the time, they are now being considered in molecular detail. A review by Jebb (14) highlighted the many interactions that mediate energy intake and EE. It was previously suggested that body weight and energy stores are homeostatically regulated (15); however, at the turn of the century, several obesity genes had been cloned, and peptides were characterized and shown to profoundly influence food intake and EE, revealing that there may be a physiologic system for energy homeostasis (16). A central tenet to that is the sympathetic nervous system, which was recently explored by Messina et al. (17) in 2013. Activity of the sympathetic nervous system was found to influence some components of EE. Cross-sectional studies indicated that individuals prone to obesity have lower rates of muscle sympathetic activity, which may lower their DIT, and influence their 24-h respiratory quotient (14).
For decades, adaptation to changes in energy intake was an area of controversy (18). Although the theory that EE changes in relation to alterations in intake exists, the magnitude of change remains disputed (19). Early research suggested that obese subjects generally consumed less than their nonobese counterparts and that blame for their development of obesity lay with their sedentary behaviors (20). However, with the introduction of doubly labeled water (DLW), new insights into energy intake and free-living EE were provided. It soon became evident that obese individuals substantially underreported their energy intake, resulting in what looked like lower absolute energy requirements (21). Furthermore, it was previously proposed that an inherent metabolic abnormality, defined by a low basal EE (BEE) was associated with obesity, yet other studies suggested that obesity is associated with a high absolute EE, both in resting conditions and over 24 h (18). By using DLW, it was clear that total EE tended to increase with weight.
Weinsier et al. (22) reported diverging trends of decreasing energy intake and increasing body weight and suggested that a reduction in physical activity may be the most important factor to explain the rising prevalence of obesity. Furthermore, Hill et al. (23) speculated that, with a decrease in physical activity, body weight may increase if energy intake is not altered, subsequently increasing total EE (as a result of increases in REE and AEE).
Although decades of research have shown advancements in the field, the documented effects of different EE components on total EE in obese adults are inconsistent. Uncertainty still exists as to which (if any) components of EE are altered in the obese individual.
Most studies presented in this review examined differences in either REE or BEE between obese and nonobese adults, using indirect calorimetry (IC). Of the 21 selected studies, 20 assessed differences in REE between these 2 groups (6–12, 24–35), and 2 studies measured BEE (13, 36). Study details that include the population investigated, the methods used to determine REE or BEE, and other EE components measured are presented in Table 2.
Most studies found that REE was significantly higher in obese individuals (~360 kcal/d higher), with the mean differences in REE values ranging from 49 kcal/d (class I obese compared with nonobese) to 826 kcal/d (severely obese compared with nonobese) (6–12). However, 2 studies documented no difference in REE between obese and nonobese adults (31, 32), and, although the investigators did not speculate about the possible reasons for the similar REE, fat-free mass (FFM) between obese and nonobese individuals were not different in these studies, potentially explaining this finding. A more in-depth discussion about the influence of FFM on REE is presented next.
Overall, REE was found to be positively associated with higher weight (6–12, 24). When studies categorized obese individuals into different groups according to their BMI, the greatest difference was observed when severely obese were compared with their nonobese counterparts (6, 8, 9, 11, 30). The documented difference between REE values of severely obese individuals compared with nonobese individuals was ~540 kcal/d, whereas a difference of ~240 kcal/d was reported when class I obese individuals were compared with nonobese individuals. In a cohort of European women, Weijs and Vansant (11) reported differences in REE values as large as 800 kcal/d (P < 0.001) when individuals with a BMI > 50 (REE = 2157 kcal/d) were compared with normal-weight individuals (REE = 1331 kcal/d).
Although 2 studies measured BEE instead of REE, similar findings were shown; absolute values of BEE were significantly higher in the obese group (13, 36). BEE was ~340 kcal higher in the obese individuals than in the nonobese controls.
REE is well established as the main component of daily EE, accounting for 50–75% of total EE (37). A major determinant of REE is body composition, specifically metabolically active tissues such as FFM. The FFM compartment includes bone, skeletal muscle mass, and highly metabolically active organs such as the brain, heart, liver, kidney, and gastrointestinal tract (38). Consequently, differences in body composition may directly affect REE values (39–41). The higher REE in obese individuals observed in most studies may be a reflection of the lack of adjustment for body composition. As FFM increases concurrently with increased fat mass (to support excess body weight), the higher FFM observed in obese individuals may potentially account for the higher REE or BEE observed in these individuals than in those with normal weight (8).
Therefore, the lack of body composition assessment may confound the association between energy metabolism and body size or BMI. We used data from a large sample of adult male and female subjects (n = 3500; 18–81 y of age) previously published (42) to demonstrate the association between BMI and REE (Figure 1). Considering this relation, we will now discuss differences in REE between obese and nonobese individuals as reported by values adjusted for FFM.
In 1932, Kleiber (43) was interested in determining the relation between body size and metabolism of organisms in general. On the basis of the analysis of energy metabolism of several animals, Kleiber (43) concluded that basal metabolism was proportional to three-quarters of body weight. We now know that the main determinant of basal metabolism is the metabolically active portion of the body, or the FFM compartment. Nevertheless, the amount of FFM (in kg) can vary considerably between obese and nonobese individuals and even across the spectrum of obesity itself. Overall, obese individuals tend to have higher amounts of both fat and FFM because these variables increase concomitantly with an increase in body weight. The exception to this is in a small number of individuals who develop sarcopenic obesity, a condition characterized by the concomitant appearance of low FFM and high fat mass (44–46); although FFM increases, this increase is not enough to sustain the excess adiposity. Therefore, absolute values of REE or BEE tend to be higher in obese individuals because of a higher amount of FFM. This could potentially explain why differences in REE or BEE between obese and nonobese individuals disappear in most studies after the adjustment for FFM (8, 10, 12, 13, 25, 26, 35). Nevertheless, it is important to highlight that, in most studies (6–8, 10, 13, 25, 35), adjustments were performed by simply dividing REE or BEE by FFM.
Expressing REE as kcal/kg body composition variables such as FFM is the equivalent to the expression kcal/kg, FFM1. Here, FFM is raised to the power of 1, but this is certainly not necessarily an appropriate adjustment approach. The simplest method to calculate the power function is to consider the correlation between the natural logarithms of the index REE/FFM and FFM. The use of logarithms allows the index to be expressed as a linear function of log REE and log FFM, which is then suitable for analysis with the use of linear regression. In this case the P value is the slope of the regression line relating log (REE) to log (FFM) and is the best power function to which FFM should be raised to adjust for differences in FFM between individuals. Although this is a sophisticated approach, it is imperative to note that it is only feasible in epidemiologic analyses or full data sets, but it is rather difficult to apply at the individual level.
According to Heymsfield et al. (38), although simply using a ratio of REE to FFM (REE:FFM) or ratio of BEE to FFM (BEE:FFM) is a commonly used method, this approach is not suitable, especially when a comparison between obese and nonobese individuals is made. The logic behind this argument is that FFM is composed of different tissues and organs, some more metabolically active than others. In this review, we divided FFM into 3 components: bone, skeletal muscle, and residual mass (which includes highly metabolically active tissues and organs such as the heart, brain, liver, kidneys, spleen, and gastrointestinal tract). With the increase in body weight, FFM tends to increase, but its less metabolically active components (skeletal muscle and bone) increase in a greater proportion than the more metabolically active one (residual mass). This can be explained because residual mass is composed mainly of organs that do not tend to substantially increase their volume with the increase of body weight. Therefore, REE:FFM of obese individuals tends to be lower than the ratio of nonobese individuals, because FFM tends to be higher in these individuals. Nonetheless, REE does not increase at the same proportion, because their FFM is proportionally less metabolically active than in their nonobese counterparts.
With the use of the data set previously mentioned as an example (42), when REE was plotted against FFM, a positive association was observed (R2 = 0.741; P < 0.001), whereas when REE:FFM was plotted against FFM a negative association was observed (R2 = 0.246; P < 0.001) (Figure 2). These findings support the hypothesis that higher amounts of FFM are associated with lower REE:FFMs.
The use of REE:FFM would only be appropriate if the y-intercept of the regression line for the relation between REE and FFM was zero; when in reality, this is not the case (47). A practical way to demonstrate that this is an inappropriate method is to consider the case where all subjects were to fit the same regression line given by:
Where a is the y-intercept and b is the coefficient for FFM. If both sides are divided by FFM, as demonstrated below, the “normalized” or “adjusted” expression for REE per kilogram of FFM is not a constant unless a = 0. Rather, individuals with large FFM will seem to have a lower metabolic rate per kilogram of FFM, whereas individuals with low FFM will seem to have a higher metabolic rate per kilogram of FFM.
In addition to the REE:FFM adjustment, another procedure observed in the literature is to present REE as the ratio to body weight when body composition variables are not available (4). Despite the denominator, this approach is not optimal (Figure 1) and investigators are urged to adjust REE for FFM by applying regression models and also to include confounding variables as covariates when possible (47).
A more appropriate method to adjust REE for FFM would be to calculate residuals from regression models and to include other covariates (sex, age, fat mass) to determine whether REE is high or low (47).
An adjustment method that used a regression model was made in the study by DeLany et al. (9) to assess REE in North American men and women. The investigators adjusted REE by both body weight and FFM, including sex and race in the model. Interestingly, even after adjusting for FFM, REE values were higher in the obese group. Nevertheless, not having fat mass included in the model is a limitation, because fat mass is an independent predictor of REE, with a greater effect on individuals with higher amounts of fat mass (48). The investigators reported differences between nonobese and class I, class II, and severely obese individuals of 101, 125, and 199 kcal, respectively, contradicting the idea that obesity is sustained by lower REE. This suggests that as an individual gains weight, their REE adjusted for FFM increases. If this person were to maintain the higher weight, more calories would have to be consumed on a daily basis to “preserve” the newly increased weight (compared with the former lower weight). In addition, an increase in REE could also occur when energy intakes are chronically higher than EE, resulting in an increase in weight and subsequent compensatory mechanisms that lead to an increase in REE (49). Therefore, this finding indicates that obesity occurs despite a compensatory increase in REE and not because of an inherent predisposition toward a lower REE.
Similar findings were reported in a large multicenter study (n = 818) in which REE was assessed in European men and women (30). Differences in REE between nonobese and obese individuals remained even after proper FFM adjustment. The reported differences in REE values between nonobese and obese classes I, II, and III were, respectively, 130, 216, and 346 kcal (P < 0.001). As previously mentioned, although fat mass is less metabolically active than FFM, it is still an independent determinant of REE, especially in individuals with high amounts of this tissue (48). As such, the higher REE in obese individuals even after appropriately adjusting for FFM could be potentially explained by the difference in their fat mass compartment.
Two other studies reported higher values of REE for obese individuals after adjusting for FFM, although the adjustment method was done by calculating the ratio between these variables (REE:FFM) (6, 11). These findings are discrepant from the ones previously reported in this section (no difference between obese and nonobese REE:FFMs), although the same adjustment method was used (REE:FFM). This may suggest that the negative relation between REE:FFM and FFM does not hold true for all studies and that other factors could be involved.
Overall, the studies seem to show that, although obese individuals have higher absolute REE than nonobese individuals, their REE:FFM or REE-to-body weight ratios are lower. However, these findings should be interpreted with caution as a consequence of the limitations inherent to the use of these ratios. Not only does the lack of adjustment of REE for body composition enter into the debate surrounding whether obese individuals have an altered REE compared with nonobese individuals, but discrepancies in the adjustment methods used may also be responsible for conflicting results between studies that adjusted REE for FFM.
In a cohort study of European women (aged 20–45 y) Di Renzo et al. (24) reported no differences in REE values between obese and nonobese individuals; however, women characterized as normal-weight obese (NWO) showed lower values of REE than both obese and nonobese women. The NWO individuals had normal BMI and a higher percentage of fat mass (fat mass > 30% as assessed by DXA). Interestingly, no differences were found in FFM among NWO, nonobese, and obese women. Unfortunately, FFM was not adjusted by height, which limits our interpretation of the body composition data. Nonetheless, lean-to-fat ratios were reported, showing that NWO women presented with a lower ratio than normal-weight women and a higher ratio than obese ones. This may partially explain the lower values of REE observed in the NWO group. The findings of this study highlighted the long-held notion that body composition is a better indicator of differences in EE than BMI, considering there were differences in EE between the NWO and the nonobese groups but not between the obese and nonobese groups. Therefore, it is crucial to reevaluate the available methods to predict EE. Nevertheless, because REE was not adjusted for FFM, our interpretation of this finding is limited.
The importance of considering body composition when determining energy requirements in obese individuals is also evident in the presence of sarcopenic obesity. As mentioned previously, although FFM increases in parallel with increase in body weight, the increase is insufficient to support the excess fat mass in the sarcopenic obese individual. There are considerable gaps in the evidence that document EE in sarcopenic obese individuals. However, if FFM is a major determinant of REE and it is decreased in sarcopenic obesity, it is reasonable to expect EE will be lower in these individuals. In fact, sedentariness may compound the effect of decreased EE and promote the hypothesized vicious cycle in this condition (higher body weight → lower physical activity → decreased FFM → body weight gain) (50). Furthermore, sarcopenic obesity is associated with an increase in adverse effects of adiposity such as insulin resistance, hypertension, and dyslipidemia (51); overestimating energy requirements in this population might lead to further increase in their fat mass and, therefore, negatively affect this condition (52).
Such concern can also be extended to normal-weight individuals who might present with a body composition phenotype similar to sarcopenic obesity (lower FFM with higher fat mass). Prado et al. (53) reported a 23% prevalence of a “sarcopenic obesity-like phenotype” among underweight/normal-weight individuals from a population-representative cohort study. Because energy requirements are estimated on the basis of body weight, the large variability in body composition in a contemporary population is ignored by using this “one-size-fits-all” formula (52, 53). Consequently, energy requirements might be overestimated in these individuals, leading to weight gain and an increase in their fat mass. Therefore, the implications of both the sarcopenic obese and the NWO phenotypes on metabolism contextualize the need for body composition assessment for personalized energy requirements.
Although only 4 studies examined differences in AEE between the nonobese and obese groups, they reported consistent findings (6, 9, 12, 26). Obese individuals presented with higher absolute AEE than nonobese individuals. However, the differences in AEE between the 2 groups disappeared or were reversed after adjusting for FFM or body weight, similarly to what was discussed in the above section about REE adjustment (6, 9, 12).
The studies of Elbelt et al. (6) and DeLany et al. (9) in European and North American cohorts, respectively, both showed that higher body weight was associated with higher AEE in free-living conditions (measured by DLW). Nevertheless, AEE was lower in the obese group after adjusting for body weight [with the use of either a regression model that included covariates as in the study of DeLany et al. (9) or an AEE-to-body weight ratio as used by Elbelt et al. (6)]. The investigators inferred that the higher unadjusted AEE values in obese individuals are because of their higher body weight burden. However, after adjusting for body weight, AEE was reported to be lower in the obese population, perhaps as a reflection of the lower activity as assessed by accelerometry (8).
Johannsen et al. (26) reported similar findings. The investigators also compared physical activity between obese and nonobese individuals under free-living conditions and showed no differences in estimated values of AEE between the 2 groups, even after regressing it against FFM. An interesting finding, however, was that data provided by activity monitors worn by the subjects during the study assessments showed that obese individuals spent more time (~2.7 h/d) being sedentary compared with nonobese individuals.
The findings in these studies suggest that adjusted AEE under free-living conditions is lower in obese individuals because of lower physical activity (exercise and non-exercise). Accelerometry data showed that obese individuals tend to have lower physical activity than nonobese individuals, especially for spending more time engaging in sedentary activities (e.g., sitting, laying down, watching television) (6, 9, 26). Nevertheless, none of these studies was able to answer the question whether the energy expended would be different between the 2 groups while performing the same activity under standardized conditions.
LeCheminant et al. (12) assessed AEE in obese and nonobese adults under controlled conditions while individuals performed the same activity (walking or jogging) at a standardized speed for the same distance. The investigators used IC to measure EE and reported higher absolute values of AEE in the obese group. However, there are a few limitations to this study such as the inclusion of individuals who were overweight or obese class I (with a mean BMI of 27.2 ± 2.1) in the obese group. Therefore, it is possible that potential differences in AEE were blunted by this definition of obesity (lower overall BMI) and that the results would have been different if the obese group included only individuals classified as obese (classes I to III). The proportion of energy used for physical activity provided some insight as to whether physical activity per se could lead to imbalanced EE. It is possible that the time spent in physical activity is a more relevant factor than EE attributable to physical activity in the maintenance of energy balance.
Altogether these findings suggest that AEE is not altered in obese individuals. However, these individuals tend to have more sedentary behavior, resulting in lower adjusted AEE. Therefore, a sedentary lifestyle is one of the contributors to a positive energy balance and, consequently, the maintenance or aggravation of the obese phenotype.
The association between lower DIT and obesity remains controversial. Although some studies showed lower values of DIT in obese individuals (27, 30–32, 36, 54), other studies have defended that no difference exists between the 2 groups (28, 29, 33, 34). DIT is influenced by the amount of calories provided and by the meal macronutrient composition (55). Therefore, an adequate comparison between obese and nonobese individuals would have to be standardized for both the caloric and composition content of the meal.
Ten studies included in this review compared DIT between obese and nonobese adults. DIT values were obtained in these studies with the use of various methods: subtracting AEE from BEE (36), calculating the difference between postprandial and postabsorptive REE (28, 29, 32, 54), or by assessing the incremental increase on EE over REE after a meal is ingested (33, 34).
In a study that compared DIT in obese (defined by percentage of fat mass > 30) and nonobese women, Schutz et al. (36) showed that the thermogenic response to 3 meals over a day was greater in the nonobese group, regardless of this group having a lower energy intake. The macronutrient composition of the meals was identical for both groups (15% of calories derived from protein, 40% from fat, and 45% from carbohydrates). Although the caloric content of the meals was higher in the obese group, the investigators reported DIT values as a percentage of energy intake in an attempt to control for bias. The reported DIT values were 8.7% ± 0.8% in the obese women compared with 14.8% ± 1.1% in the nonobese women (P < 0.001). The investigators reported a negative correlation between DIT and body weight (r = −0.55, P < 0.001) and body fat (r = −0.61, P < 0.001). Comparable findings were reported for men after consuming a 720-kcal liquid mixed meal that contained 24% of calories from protein, 21% from fat, and 55% from carbohydrates (32). The investigators reported significantly higher values in the nonobese group after 3 h of measurement (67 ± 6 compared with 49 ± 3 kcal/3 h; P < 0.01) but not for the second 3 h (34 ± 6 compared with 20 ± 4 kcal/3 h; P = 0.10).
Another study that investigated altered DIT in obese individuals (54) has to be interpreted with caution. Although the individuals in the 2 groups had similar height and weight, those included in the nonobese groups were athletes with a higher amount of FFM (85.0 ± 3.2 compared with 67.4 ± 2.7 kg; P < 0.001). This could have led to a potential bias in the study findings, which showed greater DIT in the nonobese group (48 ± 7 compared with 28 ± 4 kcal/3 h; P < 0.05) after consuming a meal that contained identical caloric and macronutrient content.
Swaminathan et al. (27) compared the responses to carbohydrate, protein, fat, and mixed meals between nonobese and obese subjects. All meals were eucaloric (~400 kcal), and both groups were compared after ingesting a meal of similar composition. Compared with the nonobese group, the investigators observed a significantly lower change in metabolic rate in the obese group after the fat-rich meal (−0.01 ± 0.02 compared with 0.12 ± 0.02 kcal/min; P < 0.01) and the mixed meal (0.14 ± 0.02 compared with 0.20 ± 0.04 kcal/min; P < 0.05). The investigators concluded that obese individuals may present with an impaired thermogenic response to dietary fat that could consequently affect the response to the mixed meal. Although this study had a small sample size (n = 11 obese and 11 nonobese individuals), similar findings were observed in a multicenter study with a large sample size (n = 701 obese and 113 nonobese individuals) (30). This study assessed EE in Europeans who consumed a test meal that contained 95% lipids, and it showed that DIT after the fat-rich meal was lower in the obese individuals. As a comparison, although individuals with a BMI < 25 had an increase in postprandial EE of 31.7%, it only increased 8.8% in those with a BMI from 30 to 35 (P < 0.01). Another study found no differences in DIT when obese and nonobese individuals were compared (28). The study compared 15 nonobese and 15 obese healthy women under 2 different circumstances: consuming isocaloric protein-rich meals compared with fat-rich meals. Both protein and fat-rich diets for the obese and nonobese individuals were of standard composition. In addition to DIT, the investigators estimated macronutrient oxidation with the use of formulas described elsewhere (56, 57), reporting no significant differences. Nonetheless, the fat-rich meal led to a lower effect on thermogenesis than the protein-rich meal in both nonobese and obese individuals. The investigators speculated that a reduction on DIT is unlikely to promote obesity but that the regular consumption of fat-rich meals may be a contributor. Under free-living conditions, the latter could possibly reduce EE, ultimately leading to weight gain and obesity. In a similar design (with the use of standard meal composition), Tentolouris et al. (29) compared DIT after a carbohydrate-rich meal and a fat-rich meal in nonobese and obese subjects. No differences were observed in DIT or macronutrient oxidation between the 2 groups. Comparably with what was observed in the first study, DIT was significantly lower after the fat-rich meal in both the nonobese and obese groups.
In another study not primarily exploring differences in DIT between nonobese and obese subjects (33), the investigators showed a greater increase on EE in obese European men than in their nonobese counterparts (351 ± 58 compared with 301 ± 19 kcal; P = 0.026) after consuming a test meal (isocaloric with predefined composition). D’Alessio et al. (34) tested the effect of 4 mixed meals that contained different amounts of kilocalorie per kilogram of FFM (0, 8, 16, 24, and 32 kcal/kg FFM) and showed comparable increases in EE in the obese and nonobese groups. Furthermore, DIT was not associated with FFM.
There are several inconsistencies among studies that compare DIT in obese and nonobese subjects. Some of these inconsistencies, such as the inclusion criteria for both the nonobese and obese groups, may introduce bias to interpreting the findings, whereas others, such as the choice of different methods to estimate and report DIT, make comparison among findings difficult. Furthermore, the inclusion and exclusion criteria in these studies need to be considered. The inclusion of control (nonobese) individuals that differ from their obese counterparts on aspects such as physical activity may lead to a greater difference in DIT between these 2 groups, because trained individuals were shown to have higher DIT than those who are sedentary (58). Another relevant limitation about participants’ characteristics is related to the presence of comorbidities that might affect DIT such as glucose intolerance (59). Nevertheless, most studies compared DIT between these individuals after consuming a standard meal, which eliminates the bias associated with meal composition and caloric content. Unfortunately, the evidence is insufficient to support the theory of an altered DIT in obese individuals. It is possible that the duration of the DIT measurement is a confounder because obesity may lead to a prolonged absorptive state (similar EE but spread over a longer period of time).
Among the studies reviewed, only 3 compared daily EE in obese and nonobese individuals (6, 9, 13). In these studies, daily EE was shown to be higher in the obese group. The absolute values of daily EE in these studies were ~2380 and 2690 kcal/d for nonobese and obese individuals, respectively.
Elbelt et al. (6) however, found that after adjusting for body weight, severely obese individuals presented with the lowest daily EE. Nevertheless, an important limitation of the study is the method used to assess EE, the SenseWear Armband, which is a method that has not yet been validated for use in obese individuals. Although the investigators reported a positive correlation between daily EE and FFM in both the obese and nonobese groups, the accuracy of the daily EE values with the use of this method is questionable.
In the study conducted by DeLany et al. (9) differences between the 2 groups (obese and nonobese) remained even after adjusting for FFM by regression. Conversely, no differences were observed when EE was adjusted for body weight except in the severely obese group which had the lowest values of body weight-adjusted daily EE. However, as discussed by Hall et al. (49), adjusting REE by body weight leads to lower values of mass-specific metabolic rate because it also accounts for fat mass (high in obese individuals and is less metabolically active than FFM).
Prentice et al. (13) compared daily EE in obese and nonobese women under controlled conditions (measured by IC with the use of a whole-body calorimetry unit under standard conditions) and under free-living conditions (with the use of DLW). In this study, the women were considered obese if their body weight was >135% of the ideal body weight defined by the Metropolitan Life Insurance Company’s table (13). Higher absolute values were observed in the obese group under both conditions: 2146 compared with 1775 kcal/d (P < 0.001) by IC and 2445 compared with 1911 kcal/d (P < 0.001) by DLW. The investigators attributed such disparities mainly to the difference in FFM between the 2 groups (49.1 ± 5.2 compared with 41.3 ± 3.9 kg, in the obese group compared with the nonobese group, respectively). They reported that the remaining difference corresponded to the extra cost of the weight-bearing activities (stepping and standing) in the obese group. When adjustments were done by dividing daily EE by FFM or body weight, obese and nonobese individuals showed comparable values (data not shown).
In summary, although the findings about differences in daily EE remain controversial, results from more controlled studies seem to point to a direction of higher absolute values in the obese group and no difference when adjusting for FFM and body weight.
The studies reported in this review do not support the hypothesis of an association between obesity and altered EE. However, future studies that measure all components of EE and correctly adjust for FFM will help further clarify this hypothesis. These findings are especially relevant to dietitians and other health professionals who are confronted with obese individuals who believe that their excess body weight is related to a “slow metabolism” or a reduced EE.
Emerging obesity phenotypes such as the NWO (24) and sarcopenic obesity or “low FFM, high-fat mass” phenotype (53) may present with altered EE compared with those who are nonobese or obese with normal body composition. Future studies should compare components of EE in these individuals, correlating them with potential physiologic abnormalities associated with each phenotype. In addition, because little is known about AEE in the obese population, further studies that compare AEE between obese and nonobese individuals are needed. Another noteworthy limitation is related to a possible confounder effect of weight loss to the studies’ findings. Although most of the studies reviewed reported to have included only weight-stable individuals (8, 10, 25, 26, 28–34), the remaining studies provided no information about weight stability. Because metabolic adaptation is thought to occur subsequently to changes in body weight (60, 61), the inclusion of obese individuals who presented with recent weight changes may introduce bias to study findings. Although some of the studies reviewed may have included individuals whom had previously lost weight, our conclusions would not be tainted, because overall absolute EE was shown to be higher in obese individuals.
On the basis of the studies hereby reviewed, it seems feasible to conclude that, although obese individuals tend to spend more energy performing activities as a consequence of higher weight burden, AEE is lower under free-living conditions, which is representative of a more sedentary lifestyle. Therefore, an active lifestyle should translate in expected increases in daily EE and consequently to promote weight loss.
Although this critical review does not support an association between obesity and altered EE, the ability of losing body weight in these individuals may be halted by adaptive thermogenesis. Evidence suggests obese individuals present with a decreased EE while trying to lose weight, a phenomenon explored in Tremblay et al. (62).
Although the studies reviewed addressed differences in EE between obese and nonobese individuals, underlying physiologic pathways that could be contributing to alterations in energy metabolism have not been discussed. Further research is needed to elucidate how the various interactions between genetics, environment, and psychosocial factors act to regulate energy metabolism.
All authors read and approved the final manuscript.
7Abbreviations used: AEE, activity energy expenditure; BEE, basal energy expenditure; DIT, diet-induced thermogenesis; DLW, doubly labelled water; EE, energy expenditure; FFM, fat-free mass; IC, indirect calorimetry; NWO, normal weight obese; REE, resting energy expenditure; REE:FFM, ratio of REE to FFM.