Abnormalities of Energy Expenditure and the Development of Obesity

The role of energy expenditure in the development of obesity remains unclear. This issue is examined using data from prospective studies of energy expenditure and obesity, the effects of overfeeding and diet composition on energy expenditure, and studies of the relationship between energy expenditure for physical activity and body composition. The combined results from these investigations strongly support the view that low energy expenditure can facilitate rapid weight gain in susceptible individuals. It is speculated that, in susceptible individuals, low energy expenditure for resting energy expenditure as well as physical activity are part of a range of mechanisms available for providing surplus energy for rapid weight gain. In addition, both cross-sectional and intervention studies indicate that there is an equilibration between the level of energy expenditure for physical activity and body fat content. While genetic and other factors clearly play an important role in this relationship, it appears that a modest reduction in body fat content can be achieved by increasing energy expenditure for physical activity in physical exercise programs.     

The Obesity Epidemic: A Consequence of Reduced Energy Expenditure and the Uncoupling of Energy Intake?

Obesity prevalence has increased, and increased energy intake or decreased physical activity are the two most obvious contributing factors. The percentage of Americans engaging in exercise has been stable over the past few decades, but decreases in occupation‐related energy expenditure are sufficient to partially explain increased obesity prevalence. Further, the contribution of energy intake and energy expenditure to the obesity epidemic is complicated because they are not independent—they are influenced by each other. For example, Mayer found that low activity levels were marked by higher body weight and higher “unregulated” energy intake levels. Conversely, higher activity levels were marked by lower body weight and energy intake that matched energy expenditure. Consistent with Mayer, we propose that because most Americans have low levels of occupation‐related activity, they do not benefit from the regulation of energy intake achieved at higher activity levels, resulting in weight gain due to energy intake exceeding energy expenditure.     

The energetics of obesity

Although there is little argument about the state of energy imbalance that produces weight gain, there is considerable argument about the respective role of genetics, diet and physical activity in achieving obesity. In the USA, obesity has increased in the last decades despite a concomitant decrease in total energy and fat intake suggesting that there has been a dramatic drop in total energy expenditure. In this review, we investigated the respective role of resting metabolic rate, post-prandial thermogenesis, and activity energy expenditure in this lower energy output, and provided evidence that physical inactivity is the major contributor. Based on Jean Mayer original observation (Mayer et al., 1954), we hypothesize that there is a level of physical activity below which mechanisms of body mass regulation are impaired. The increasing prevalence of obesity may reflect the fact the majority of the population has fallen below such a level of physical activity. However, a causal relation between physical inactivity and obesity is still difficult to prove, probably because of the lack of longitudinal models to investigate the physiological consequences of inactivity and because the deleterious consequences of sedentary behaviors are essentially deduced from the benefits of exercise training. By using long term strict bed rest as a unique model of inactivity, we provide evidence that inactivity per se indeed disrupts fuel homeostasis and partitions post-absorptive and post-prandial fat use towards storage, thus promoting weight gain in the long term. More research is needed to investigate mechanisms and to determine the minimal physical activity our body has been engineered for by evolution.     

Role of physical activity in preventing and treating obesity.

There is an inverse relationship between physical activity and weight gain. However, additional research is needed to quantify the amount of physical activity required to prevent weight gain in different populations, improve the way we convey physical activity recommendations to the public, and help the individuals increase their physical activity. Although physical activity does not appear to contribute significantly to weight loss, it is critical for maintenance of weight loss. Available data are consistent in that 60-90 min/day of moderate-intensity physical activity is required to maintain a significant weight loss. Although there is agreement about the need for high levels of physical activity to maintain weight loss, there is a need for more research to understand why physical activity is critical for weight loss maintenance. Finally, additional research is needed to determine whether there is an optimal level of physical activity below which it is difficult for most people to achieve a balance between energy intake and expenditure at a healthy body weight. The increasing prevalence of obesity may reflect the fact that the majority of the population has fallen below such a level of physical activity.     

Non Linear Weight Gain with Long Term Overfeeding in Man

This study deals with the pattern of body weight gain during an overfeeding period with a constant energy intake, in order to assess whether total daily energy expenditure (TEE) increased with body weight and thus could account for the progressive slow down in body weight gain over time. Twenty-four young adult males (12 pairs of identical twins) were overfed by 4.2 MJ per day, six days a week, for a total of 84 days during a 100-day overfeeding period. The total excess amount each man consumed was 353 MJ. It was assumed that, at a given time, the TEE increase (E) was dependent on body weight gain and energy cost (C) was proportional to the daily body weight gain. Results show an exponential increase in body weight, fat free mass, and fat mass (with half-times of 86, 57, and 84 days, respectively) that allows the calculation of E (246 ± 37 kJ*kg^?1 d^?1, mean ± SE) and C (32.3 ± 2.4 MJ kg^?1). Energy expenditure from other sources besides resting metabolic rate, such as physical activity and thermic effect of food, may represent as much as 65% of E. At the beginning of the overfeeding period, almost all the energy surplus was recovered as body substances but this proportion decreased to 60% after 100 days of overfeeding. It is concluded that 1) TEE changes were related to body weight change, 2) about 65% of E were accounted for by physical activity, thermic effect of food, or some other components, and 3) the fraction of the energy surplus stored as body substances decreased with the duration of overfeeding.     

Muscle metabolic function and free-living physical activity.

We have previously shown that muscle metabolic function measured during exercise is related to exercise performance and subsequent 1-yr weight gain. Because it is well established that physical activity is important in weight maintenance, we examined muscle function relationships with free-living energy expenditure and physical activity. Subjects were 71 premenopausal black and white women. Muscle metabolism was evaluated by (31)P magnetic resonance spectroscopy during 90-s isometric plantar flexion contractions (45% maximum). Free-living energy expenditure (TEE) was measured using doubly labeled water, activity-related energy expenditure (AEE) was calculated as 0.9 x TEE - sleeping energy expenditure from room calorimetry, and free-living physical activity (ARTE) was calculated by dividing AEE by energy cost of standard physical activities. At the end of exercise, anaerobic glycolytic rate (ANGLY) and muscle concentration of phosphomonoesters (PME) were negatively related to TEE, AEE, and ARTE (P < 0.05). Multiple regression analysis showed that both PME (partial r = -0.29, <0.02) and ANGLY (partial r = -0.24, P < 0.04) were independently related to ARTE. PME, primarily glucose-6-phosphate and fructose-6-phosphate, was significantly related to ratings of perceived exertion (r = 0.21, P < or = 0.05) during a maximal treadmill test. PME was not related to ARTE after inclusion of RPE in the multiple regression model, suggesting that PME may be obtaining its relationship with ARTE through an increased perception of effort during physical activity. In conclusion, physically inactive individuals tend to be more dependent on anaerobic glycolysis during exercise while relying on a glycolytic pathway that may not be functioning optimally.     

Feedback models allowing estimation of thresholds for self-promoting body weight gain

Objective: Most people maintain almost constant body weight over long time with varying physical activity and food intake. This indicates the existence of a regulation that works well for most individuals. Yet some people develop obesity, indicating that this regulation sometimes fails. The difference between the two situations is typically an energy imbalance of about 1% over a long period of time.Theory: Weight gain increases basal metabolic rate. Weight gain is often associated with a decrease in physical activity, although not to such an extent that it prevents an increase in total energy expenditure and energy intake. Dependent on the precise balance between these effects of weight gain, they may make the body weight unstable and tend to further promote weight gain. With the aim of identifying the thresholds beyond which such self-promoting weight gain may take place, we develop a simple mathematical model of the body as an energy-consuming machine in which the changes in physical activity and food intake are described as feedback effects in addition to the effect of the weight gain on basal metabolic rate. The feedback parameters of the model may differ between individuals and only in some cases do they take values that make weight gain self-promoting.Results: We determine the quantitative conditions under which body weight gain becomes self-promoting. We find that these conditions can easily be met, and that they are so small that they are not observable with currently available techniques. This phenomenon encourages emphasis on even minor changes in food intake and physical activity to abate or stop weight gain.     

Metabolic Determinants of Weight Gain in Humans

One of the fundamental challenges in obesity research is to identify subjects prone to weight gain so that obesity and its comorbidities can be promptly prevented or treated. The principles of thermodynamics as applied to human body energetics demonstrate that susceptibility to weight gain varies among individuals as a result of interindividual differences in energy expenditure and energy intake, two factors that counterbalance one another and determine daily energy balance and, ultimately, body weight change. This review focuses on the variability among individuals in human metabolism that determines weight change. Conflicting results have been reported about the role of interindividual differences in energy metabolism during energy balance in relation to future weight change. However, recent studies have shown that metabolic responses to acute, short‐term dietary interventions that create energy imbalance, such as low‐protein overfeeding or fasting for 24 hours, may reveal the underlying metabolic phenotype that determines the degree of resistance to diet‐induced weight loss or the propensity to spontaneous weight gain over time. Metabolically “thrifty” individuals, characterized by a predilection for saving energy in settings of undernutrition and dietary protein restriction, display a minimal increase in plasma fibroblast growth factor 21 concentrations in response to a low‐protein overfeeding diet and tend to gain more weight over time compared with metabolically “spendthrift” individuals. Similarly, interindividual variability in the causal relationship between energy expenditure and energy intake (“energy sensing”) and in the metabolic response to cold exposure (e.g., brown adipose tissue activation) seems, to some extent, to be indicative of individual propensity to weight gain. Thus, an increased understanding and the clinical characterization of phenotypic differences in energy metabolism among individuals (metabolic profile) may lead to new strategies to prevent weight gain or improve weight‐loss interventions by targeted therapies on the basis of metabolic phenotype and susceptibility to obesity in individual persons.     

Energy Expenditure Compared to Physical Activity Measured by Accelerometry and Self-Report in Adolescents: A Validation Study

Background

Physical inactivity is responsible for 5.3 million deaths annually worldwide. To measure physical activity energy expenditure, the doubly labeled water (DLW) method is the gold standard. However, questionnaires and accelerometry are more widely used. We compared physical activity measured by accelerometer and questionnaire against total (TEE) and physical activity energy expenditure (PAEE) estimated by DLW.

Methods

TEE, PAEE (TEE minus resting energy expenditure) and body composition were measured using the DLW technique in 25 adolescents (16 girls) aged 13 years living in Pelotas, Brazil. Physical activity was assessed using the Actigraph accelerometer and by self-report. Physical activity data from accelerometry and self-report were tested against energy expenditure data derived from the DLW method. Further, tests were done to assess the ability of moderate-to-vigorous intensity physical activity (MVPA) to predict variability in TEE and to what extent adjustment for fat and fat-free mass predicted the variability in TEE.

Results

TEE varied from 1,265 to 4,143 kcal/day. It was positively correlated with physical activity (counts) estimated by accelerometry (rho  = 0.57; p = 0.003) and with minutes per week of physical activity by questionnaire (rho  = 0.41; p = 0.04). An increase of 10 minutes per day in moderate-to-vigorous intensity physical activity (MVPA) relates to an increase in TEE of 141 kcal/day. PAEE was positively correlated with accelerometry (rho  = 0.64; p = 0.007), but not with minutes per week of physical activity estimated by questionnaire (rho  = 0.30; p = 0.15). Physical activity by accelerometry explained 31% of the vssariability in TEE. By incorporating fat and fat-free mass in the model, we were able to explain 58% of the variability in TEE.

Conclusion

Objectively measured physical activity significantly contributes to the explained variance in both TEE and PAEE in Brazilian youth. Independently, body composition also explains variance in TEE, and should ideally be taken into account when using accelerometry to predict energy expenditure values.     

Is the ArteACC Index a Valid Indicator of Free‐Living Physical Activity in Adolescents?

Objective: The principal aim of this study was to validate a proposed new index of physical activity, the activity‐related time equivalent based on accelerometry (ArteACC), in adolescents. A secondary aim was to develop regression equations for prediction of total energy expenditure (TEE) and activity energy expenditure [AEE = 0.9 × TEE ? resting metabolic rate (RMR)]. Research Methods and Procedures: RMR and energy expenditure (EE) under standardized exercises were measured by indirect calorimetry in 36 adolescents (14 to 19 years old). TEE was measured by the doubly labeled water method, and physical activity was assessed simultaneously with an accelerometer for 14 days. AEE, AEE in relation to body weight (AEE per kilogram), and activity‐related time equivalent based on energy expenditure (ArteEE = AEE/[EE reference activity ? RMR]) were calculated from laboratory and free‐living EE data. ArteACC was calculated as total activity counts/activity counts of reference activity. Results: ArteACC was significantly related to AEE per kilogram (r = 0.57; p < 0.0001) and ArteEE (r = 0.68; p < 0.001). The absolute amount of time (minutes per day) spent in physical activity was significantly lower when calculated from ArteACC than from ArteEE (p < 0.001). TEE was significantly influenced by RMR, sex, and ArteACC (r² = 0.89). AEE was significantly influenced by sex and ArteACC (r² = 0.59). Discussion: Despite an absolute difference between the two indexes, ArteEE and ArteACC, ArteACC seems to be a valid indicator of free‐living physical activity. It contributed significantly, by 3.3% and 12.5%, to the explained variations in TEE and AEE, respectively.     

Energy compensation and metabolic adaptation: “The Biggest Loser” study reinterpreted

“The Biggest Loser” weight-loss competition offered a unique opportunity to investigate human energy metabolism and body composition before, during, and after an extreme lifestyle intervention. Here, I reinterpret the results of “The Biggest Loser” study in the context of a constrained model of human energy expenditure. Specifically, “The Biggest Loser” contestants engaged in large, sustained increases in physical activity that may have caused compensatory metabolic adaptations to substantially decrease resting metabolic rate and thereby minimize changes in total energy expenditure. This interpretation helps explain why the magnitude of persistent metabolic adaptation was largest in contestants with the greatest increases in sustained physical activity and why weight-loss interventions involving lower levels of physical activity have not measured similarly large metabolic adaptations. Additional longitudinal studies quantifying the interrelationships between various components of energy expenditure and energy intake are needed to better understand the dynamics of human body weight regulation.     

Genotype by Energy Expenditure Interaction with Metabolic Syndrome Traits: The Portuguese Healthy Family Study

Moderate-to-high levels of physical activity are established as preventive factors in metabolic syndrome development. However, there is variability in the phenotypic expression of metabolic syndrome under distinct physical activity conditions. In the present study we applied a Genotype X Environment interaction method to examine the presence of GxEE interaction in the phenotypic expression of metabolic syndrome. A total of 958 subjects, from 294 families of The Portuguese Healthy Family study, were included in the analysis. Total daily energy expenditure was assessed using a 3 day physical activity diary. Six metabolic syndrome related traits, including waist circumference, systolic blood pressure, glucose, HDL cholesterol, total cholesterol and triglycerides, were measured and adjusted for age and sex. GxEE examination was performed on SOLAR 4.3.1. All metabolic syndrome indicators were significantly heritable. The GxEE interaction model fitted the data better than the polygenic model (p<0.001) for waist circumference, systolic blood pressure, glucose, total cholesterol and triglycerides. For waist circumference, glucose, total cholesterol and triglycerides, the significant GxEE interaction was due to rejection of the variance homogeneity hypothesis. For waist circumference and glucose, GxEE was also significant by the rejection of the genetic correlation hypothesis. The results showed that metabolic syndrome traits expression is significantly influenced by the interaction established between total daily energy expenditure and genotypes. Physical activity may be considered an environmental variable that promotes metabolic differences between individuals that are distinctively active.     

Determinants affecting physical activity levels in animal models

Weight control is dependent on energy balance. Reduced energy expenditure (EE) associated with decreased physical activity is suggested to be a major underlying cause in the increasing prevalence of weight gain and obesity. Therefore, a better understanding of the biological determinants involved in the regulation of physical activity is essential. To facilitate interpretation in humans, it is helpful to consider the evidence from animal studies. This review focuses on animal studies examining the biological determinants influencing activity and potential implications to human. It appears that physical activity is influenced by a number of parameters. However, regardless of the parameter involved, body weight appears to play an underlying role in the regulation of activity. Furthermore, the regulation of activity associated with body weight appears to occur only after the animal achieves a critical weight. This suggests that activity levels are a consequence rather than a contributor to weight control. However, the existence of an inverse weight-activity relationship remains inconclusive. Confounding the results are the multifactorial nature of physical activity and the lack of appropriate measuring devices. Furthermore, many determinants of body weight are closely interlocked, making it difficult to determine whether a single, combination, or interaction of factors is important for the regulation of activity. For example, diet-induced obesity, aging, lesions to the ventral medial hypothalamus, and genetics all produce hypoactivity. Providing a better understanding of the biological determinants involved in the regulation of activity has important implications for the development of strategies for the prevention of weight gain leading to obesity and subsequent morbidity and mortality in the human population.     

Age is independently related to muscle metabolic capacity in premenopausal women.

The purpose of this study was to determine whether muscle metabolic capacity was inversely related to age after adjusting for physical activity in sedentary premenopausal women. Eighty-three women (ages 23-47 yr) had their free-living, activity-related energy expenditure evaluated with doubly labeled water procedures, and room calorimeter determined sleeping energy expenditure. Maximum O(2) uptake and strength were evaluated in all subjects, whereas 31P-magnetic resonance spectroscopy determined metabolic economy during maximal exercise, and muscle biopsy maximal enzyme activity was evaluated in subsets of the sample (48 and 18 subjects, respectively). Age was significantly related to whole body treadmill endurance time (r = -0.32), plantar flexion strength (r = -0.29), maximum O(2) uptake (r = -0.27), (31)P-magnetic resonance spectroscopy ADP recovery rate (r = -0.44), and anaerobic glycolytic capacity (r = -0.37), and muscle biopsy citrate synthase activity (r = -0.48), glyceraldehyde-3-phosphate dehydrogenase (r = -0.54), phosphofructokinase (r = -0.62), and phosphorylase (r = -0.58) activity even after adjusting for activity-related energy expenditure. These data suggest that, in sedentary premenopausal women, both oxidative and glycolytic muscle capacity decrease with age even when physical activity is taken into account.     

Meal-feeding studies in mice: effects of diet on blood lipids and energy expenditure

To identify optimal study-design conditions to investigate lipid metabolism, male, C57BL/6J mice (age, 59 +/- 3 days) were allotted to eight groups, with six animals per group that were stratified by three factors: diet type (high fat [HF]: 60% of energy from fat versus that of a standard rodent diet, 14% fat, fed for 7 weeks), feeding regimen (ad libitum [ad lib] versus meal fed), and metabolic state (data collected in fasted or fed states). Serum free fatty acids (FFA) and triacylglycerols (TAG) concentrations, and energy expenditure (EE) were assessed. Mice gained 0.30 +/- 0.11 g of body weight/day when allowed ad lib access to HF diet, similar weight when meal-fed the HF or ad lib-fed the standard diet (0.10 +/- 0.03 g/day), and no weight when meal-fed the standard diet (0.01 +/- 0.02 g/day). Fed-state TAG concentration was 88 to 100% higher (P < 0.02) than that of the fasted state, except when animals were ad lib-fed the HF diet. When the standard diet was meal fed, FFA concentration was 30% higher in the fasted compared with the fed state (P = 0.003). Mice had 33% higher postprandial EE when either diet was meal fed (P = 0.01). Mice adapted to meal feeding developed transitions in metabolism consistent with known physiologic changes that occur from fasting to feeding. When fed the standard diet, a 6-h per day meal-feeding regimen was restrictive for normal growth. These data support use of a meal-feeding regimen when HF diets are used and research is focused on metabolic differences between fasted and fed states. This protocol allows study of the metabolic effects of an HF diet without the confounding effects of over-consumption of food and excess body weight gain.     

FTO variant, energy intake, physical activity and basal metabolic rate in Caucasians. The HAPIEE study

The FTO gene variants are the most important genetic determinants of body weight and obesity known so far, but the mechanism of their effect remains unclear. We have analyzed FTO rs17817449 variant (G>T in first intron) in 6024 adults aged 45-69 years to assess the potential mediating role of diet and physical activity. Diet was assessed by a 140-item food frequency questionnaire. Physical activity was measured by hours spent during a typical week by sport, walking and other activities outside of work requiring heavy and medium physical activity. Basal metabolic rate was calculated according Schofield formula. The FTO variant was significantly associated with body mass index (means in GG, GT and TT carriers were 28.7, 28.2 and 27.8 kg/m(2), p<0.001) and basal metabolic rate (BMR) (means in GG, GT and TT were 1603, 1588 and 1576 kcal per day, respectively, p<0.008) but it was not associated with physical activity, total energy intake or with energy intakes from fat, carbohydrates, proteins or alcohol. Results were essentially similar in men and women and the adjustment for physical activity or dietary energy intake did not reduce the effect of the FTO polymorphism. Means of BMR per kg of body weight was lowest in GG carriers (20.09, 20.21 for GT and 20.30 for TT, p<0.006) and this effect was more pronounced in females. These results suggest that the effect of the FTO rs17817449 variant on BMI in Caucasian adults is not mediated by energy intake or physical activity, but some effect on BMR per kg of body weight is possible.     

Pharmacological actions of the peptide hormone amylin in the long-term regulation of food intake, food preference, and body weight

The ability of amylin to reduce acute food intake in rodents is well established. Longer-term administration in rats (up to 24 days) shows a concomitant reduction in body weight, suggesting energy intake plays a significant role in mediating amylin-induced weight loss. The current set of experiments further explores the long-term effects of amylin (4-11 wk) on food preference, energy expenditure, and body weight and composition. Furthermore, we describe the acute effect of amylin on locomotor activity and kaolin consumption to test for possible nonhomeostatic mechanisms that could affect food intake. Four-week subcutaneous amylin infusion of high-fat fed rats (3-300 microg.kg(-1).day(-1)) dose dependently reduced food intake and body weight gain (ED(50) for body weight gain = 16.5 microg.kg(-1).day(-1)). The effect of amylin on body weight gain was durable for up to 11 wks and was associated with a specific loss of fat mass and increased metabolic rate. The body weight of rats withdrawn from amylin (100 microg.kg(-1).day(-1)) after 4 wks of infusion returned to control levels 2 wks after treatment cessation, but did not rebound above control levels. When self-selecting calories from a low- or high-fat diet during 11 wks of infusion, amylin-treated rats (300 microg.kg(-1).day(-1)) consistently chose a larger percentage of calories from the low-fat diet vs. controls. Amylin acutely had no effect on locomotor activity or kaolin consumption at doses that decreased food intake. These results demonstrate pharmacological actions of amylin in long-term body weight regulation in part through appetitive-related mechanisms and possibly via changes in food preference and energy expenditure.     

The Role of Thermogenesis in Antipsychotic Drug‐induced Weight Gain

The administration of antipsychotic drugs to human patients or experimental animals leads to significant weight gain, which is widely presumed to be driven by hyperphagia; however, the contribution from energy expenditure remains unclear. These studies aim to examine the contribution of shifts in energy expenditure, particularly those involving centrally mediated changes in thermogenesis, to the body weight gain associated with the administration of olanzapine to female Sprague Dawley rats. Olanzapine (6 mg/kg/day orally) caused a transient increase in food intake but a maintained increase in body weight. When pair‐fed rats were treated with olanzapine, body weight continued to rise compared to vehicle‐treated rats, consistent with a reduction in energy expenditure. Brown adipose tissue (BAT) temperature, measured using biotelemetry devices, decreased immediately after the onset of olanzapine treatment and remained depressed, as did physical activity. UCP1 expression in interscapular BAT was reduced following chronic olanzapine treatment. An acute injection of olanzapine was preceded by an injection of a retrograde tracer into the spinal cord to evaluate the nature of the olanzapine‐activated neural pathway. Levels of Fos protein in a number of spinally projecting neurons within discrete hypothalamic and brainstem sites were elevated in olanzapine‐treated rats. Some of these neurons in the perifornical region of the lateral hypothalamus (LHA) were also Orexin A positive. These data collectively show a significant impact of thermogenesis (and physical activity) on the weight gain associated with olanzapine treatment. The anatomical studies provide an insight into the central neuroanatomical substrate that may subserve the altered thermogenic responses brought about by olanzapine.     

Nonexercise activity thermogenesis (NEAT): environment and biology

Nonexercise activity thermogenesis (NEAT) is the energy expended for everything that is not sleeping, eating, or sports-like exercise. It includes the energy expended walking to work, typing, performing yard work, undertaking agricultural tasks, and fidgeting. NEAT can be measured by one of two approaches. The first is to measure or estimate total NEAT. Here, total daily energy expenditure is measured, and from it "basal metabolic rate-plus-thermic effect of food" is subtracted. The second is the factoral approach, whereby the components of NEAT are quantified, and total NEAT is calculated by summing these components. The amount of NEAT that humans perform represents the product of the amount and types of physical activities and the thermogenic cost of each activity. The factors that impact a human's NEAT are readily divisible into environmental factors, such as occupation or dwelling within a "concrete jungle," and biological factors such as weight, gender, and body composition. The combined impact of these factors explains the substantial variance in human NEAT. The variability in NEAT might be viewed as random, but human and animal data contradict this. It appears that changes in NEAT subtly accompany experimentally induced changes in energy balance and are important in the physiology of weight change. Inadequate modulation of NEAT plus a sedentary lifestyle may thus be important in obesity. It then becomes intriguing to dissect mechanistic studies that delineate how NEAT is regulated into neural, peripheral, and humoral factors. A scheme is described in this review in which NEAT corresponds to a carefully regulated "tank" of physical activity that is crucial for weight control.     

Energetically costly behaviour and the evolution of resting metabolic rate in insects

1. A general hypothesis is presented to explain interspecific differences in size-independent resting metabolic rate. This hypothesis is based on a presumed trade-off between a low resting metabolism and adaptations of metabolism during activity.
2. With such a trade-off, selection to reduce resting metabolism is less intense in active species than in species where resting metabolism constitutes a large proportion of the daily metabolic costs. Those animals that spend more energy on activity should therefore have a higher resting metabolic rate than animals that spend less energy on activity.
3. A literature review reveals that flying insects have higher resting metabolic rates than species that use energetically less demanding types of locomotion.
4. Insects producing acoustic advertisement signals can be shown to have higher mass-independent resting metabolic rates than closely related species without this energetically demanding behaviour.
5. Literature data on vertebrate resting metabolic rates are also consistent with the presented hypothesis: the more energy animals spend on activity, the higher the mass-independent resting metabolic rate.