Component Of Total Energy Expenditure Research Articles

Energy Expenditure in Humans and Other Primates: A New Synthesis

This review examines the proximate, ecological, and evolutionary determinants of energy expenditure in humans and primates, with an emphasis on empirical measurements of total energy expenditure (TEE). Body size is the main proximate determinant of TEE, both within and between species; physical activity, genetic variation, and endocrine regulation explain substantially less of the variation in TEE. Basal metabolism is the single largest component of TEE, far exceeding the cost of physical activity, digestion, growth and reproduction, and thermoregulation in most instances. Notably, differences in physical activity do not generally result in corresponding differences in TEE, undermining the utility of activity-based factorial estimates of TEE. Instead, empirical measurements of energy expenditure in humans and other primates suggest that the body adapts dynamically to long-term changes in physical activity, maintaining TEE within an evolved, and relatively narrow, physiological range.

Regulation of energy expenditure by estradiol in premenopausal women.

Suppressing sex hormones in women for 1 wk reduces resting energy expenditure (REE). The effects of more chronic suppression on REE and other components of total energy expenditure (TEE), and whether the reduction in REE is specifically due to loss of estradiol (E2), are not known. We compared the effects of 5 mo of sex hormone suppression (gonadotropin releasing hormone agonist therapy, GnRHAG) with placebo (PL) or E2 add-back therapy on REE and the components of TEE. Premenopausal women received GnRHAG (leuprolide acetate 3.75 mg/mo) and were randomized to receive transdermal therapy that was either E2 (0.075 mg/d; n = 24; means ± SD, aged = 37 ± 8 yr, BMI = 27.3 ± 6.2 kg/m(2)) or placebo (n = 21; aged = 34 ± 9 yr, BMI = 26.8 ± 6.2 kg/m(2)). REE was measured by using a metabolic cart, and TEE, sleep EE (SEE), exercise EE (ExEE, 2 × 30 min bench stepping), non-Ex EE (NExEE), and the thermic effect of feeding (TEF) were measured by using whole room indirect calorimetry. REE decreased in GnRHAG+PL [mean (95% CI), -54 (-98, -15) kcal/d], but not GnRHAG+E2 [+6 (-33, +45) kcal/d] (difference in between-group changes, P < 0.05). TEE decreased in GnRHAG+PL [-128 (-214, -41) kcal/d] and GnRHAG+E2 [-96 (-159, -32) kcal/d], with no significant difference in between-group changes (P = 0.55). SEE decreased similarly in both GnRHAG+PL [-0.07 (-0.12, -0.03) kcal/min] and GnRHAG+E2 [-0.07 (-0.12, -0.02) kcal/min]. ExEE decreased in GnRHAG+PL [-0.46 (-0.79, -0.13) kcal/min], but not GnRHAG+E2 [-0.30 (-0.65, +0.06) kcal/min]. There were no changes in TEF or NExEE in either group. In summary, chronic pharmacologic suppression of sex hormones reduced REE and this was prevented by E2 therapy.

Energy Expenditure After Liver Resection: Validation of a Mobile Device for Estimating Resting Energy Expenditure and an Investigation of Energy Expenditure Change After Liver Resection.

Resting energy expenditure (REE) is the major component of total energy expenditure. REE is traditionally performed by indirect calorimetry (IC) and is not well investigated after liver surgery. A mobile device (SenseWear Armband [SWA]) has been validated when estimating REE in other clinical settings but not liver resection. The aims of this study are to validate SWA vs IC, quantify REE change following liver resection, and determine factors associated with REE change. Patients listed for open liver resection prospectively underwent IC and SWA REE recordings pre- and postoperatively. In addition, the SWA was worn continuously postoperatively to estimate daily REE for the first 5 postoperative days. To determine acceptability of the SWA, validation analysis was performed. To assess REE change, peak postoperative REE was compared with preoperative levels. Factors associated with REE change were also analyzed. SWA showed satisfactory validity compared with IC when estimating REE, although postoperatively, the 95% levels of agreement (-5.56 to 3.18 kcal/kg/d) may introduce error. Postoperative REE (median, 23.5 kcal/kg/d; interquartile range [IQR], 22.6-25.7 kcal/kg/d) was significantly higher than predicted REE (median, 19.7 kcal/kg/d; IQR, 19.1-21.0 kcal/kg/d; P < .0001). Median REE rise was 11% (IQR, -1% to 25%). Factors associated with REE rise of >11% were age ( P = .017) and length of operation ( P = .03). SWA offers a suitable alternative to IC when estimating postoperative REE, but the magnitude of the error (8.74 kcal/kg/d) could hinder its accuracy. REE quantification after liver resection is important to identify patients who could be prone to energy imbalance and therefore malnutrition.

The Energy Balance Study: The Design and Baseline Results for a Longitudinal Study of Energy Balance

Purpose: The Energy Balance Study (EBS) was a comprehensive study designed to determine over a period of 12 months the associations of caloric intake and energy expenditure on changes in body weight and composition in a population of healthy men and women. Method: EBS recruited men and women aged 21 to 35 years with a body mass index between 20 and 35 kg/m2. Measurements of energy intake and multiple objective measures of energy expenditure, as well as other physiological, anthropomorphic and psychosocial measurements, were made quarterly. Resting metabolic rate and blood chemistry were measured at baseline, 6 and 12 months. Results: Four hundred and thirty (218 women and 212 men) completed all baseline measurements. There were statistically significant differences by sex uncovered for most anthropomorphic, physiological and behavioral variables. Only percent of kcals from fat and alcohol intake, as well as energy expenditure in light activity and very vigorous activity were not different. Self-reported weight change (mean ± SD) over the previous year were 0.92 ± 5.24 kg for women and − 1.32 ± 6.1 kg for men. Resting metabolic rate averages by sex were 2.88 ± 0.35 ml/kg/min for women and 3.05 ± 0.33 ml/kg/min for men. Conclusion: Results from EBS will inform our understanding of the impact of energy balance components as they relate to changes in body weight and composition. Initial findings suggest a satisfactory distribution of weight change to allow for robust statistical analyses. Resting metabolic rates well below the standard estimate suggest that the evaluation of the components of total energy expenditure will be impactful for our understanding of the roles of energy intake and expenditure on changes in energy utilization and storage.

Caffeine Intake, Short Bouts of Physical Activity, and Energy Expenditure: A Double-Blind Randomized Crossover Trial

PA energy expenditure (PAEE) is the most variable component of Total Energy Expenditure (TEE) and largely due to the balance of sedentary time (SedT) and low intensity physical activity (LIPA). There has been an emergence for seeking an understanding of factors which determine variations in SedT, LIPA, and PAEE. Sedentary behavior and physical activity are relatively resistant to change by experimental dietary treatments and significant body weight changes. Although caffeine (Caf) is by far the most heavily used nutritional agent ingested to promote a sense of vigor/alertness, it is still unknown if Caf is effective in increasing PAEE and physical activity. The aim of the study was to test the hypothesis that 2 daily doses of Caf (as a capsule to blind the treatment and divided equally during breakfast and lunch) increase PAEE and TEE, and it would do so through increasing the frequent and brief bouts of physical activity (~1-5 min long) through the day as measured by accelerometry. In 21 low Caf users (<100 mg day-1), we used a double-blind crossover trial (ClinicalTrials.govID;NCT01477294) with two conditions (4-day each with a 3-day washout period) randomly ordered as 5 mg kg-1 day-1 of Caf and maltodextrin as placebo (Plc). Resting energy expenditure (REE) by indirect calorimetry, total energy expenditure (TEE) from doubly labeled water, PAEE calculated as TEE-(REE+0.1TEE), and accelerometry measurements of both LIPA and MVPA were not different between conditions. However, regardless of caffeine or placebo, there were several significant relationships between brief bouts of LIPA and MVPA with PAEE. In conclusion, this double-blind study found that low and moderate-vigorous activity as well as the total volume of PAEE in free-living conditions is resistant to dietary caffeine intake that was equivalent to 5 cups of espresso or 7 cups of tea.Trial RegistrationClinicalTrials.gov NCT01477294

Best-fitting prediction equations for basal metabolic rate: informing obesity interventions in diverse populations.

Basal metabolic rate (BMR) represents the largest component of total energy expenditure and is a major contributor to energy balance. Therefore, accurately estimating BMR is critical for developing rigorous obesity prevention and control strategies. Over the past several decades, numerous BMR formulas have been developed targeted to different population groups. A comprehensive literature search revealed 248 BMR estimation equations developed using diverse ranges of age, gender, race, fat-free mass, fat mass, height, waist-to-hip ratio, body mass index and weight. A subset of 47 studies included enough detail to allow for development of meta-regression equations. Utilizing these studies, meta-equations were developed targeted to 20 specific population groups. This review provides a comprehensive summary of available BMR equations and an estimate of their accuracy. An accompanying online BMR prediction tool (available at http://www.sdl.ise.vt.edu/tutorials.html) was developed to automatically estimate BMR based on the most appropriate equation after user-entry of individual age, race, gender and weight.

Energy expenditure and physical activity of ambulatory children with cerebral palsy and of typically developing children

Children with cerebral palsy (CP) expend more energy when walking than do their typically developing peers. The effect this has on physical activity levels (PALs) and on total energy expenditure (TEE) will have important implications when determining energy requirements. This study aimed to investigate the components of TEE in children with CP in comparison with typically developing children and to determine what effect the higher energy expenditure during walking has in ambulatory children with CP on PAL and on TEE. Sixteen children with mild CP and 16 typically developing children, aged 5-12 y, were recruited for the study. Resting energy expenditure (REE) and the energy expenditure during walking were measured by using indirect calorimetry. TEE was determined by using the doubly labeled water technique. PAL was calculated as the ratio of TEE to REE. Body composition was estimated by using oxygen-18. TEE was lower in children with CP (7012 +/- 1268 kJ/d) than in typically developing children (8309 +/- 2088 kJ/d) because of a lower PAL (1.57 +/- 0.23 compared with 1.79 +/- 0.26). The children with CP expended significantly more energy when walking than did the typically developing children (13.8 +/- 4.9 compared with 10.3 +/- 2.3 kJ/min) while walking at a lower velocity (61 +/- 10 compared with 72 +/- 8 m/min). Correlations between energy expenditure during walking and PAL were not statistically significant for either group. Children with CP expend more energy during walking and have a lower PAL and lower energy requirements than do typically developing children. This has important implications when estimating the energy requirements of children with CP.

Exercise-induced energy expenditure: Implications for exercise prescription and obesity

Objective Walking is commonly recommended to help with weight management. We measured total energy expenditure (TEE) and its components to quantify the impact of increasing exercise-induced energy expenditure (ExEE) on other components of TEE. Methods Thirteen obese women underwent an 8-week walking group intervention. TEE was quantified using doubly labeled water, ExEE was quantified using heart rate monitors, daily movement was assessed by accelerometry and resting metabolic rate was measured using indirect calorimetry. Results Four of the 13 participants achieved the target of 1500 kcal wk −1 of ExEE and all achieved 1000 kcal wk −1. The average ExEE achieved by the group across the 8 weeks was 1434 ± 237 kcal wk −1. Vigorous physical activity, as assessed by accelerometry, increased during the intervention by an average of 30 min per day. Non-exercise activity thermogenesis (NEAT) decreased, on average, by 175 kcal d −1 (−22%) from baseline to the intervention and baseline fitness was correlated with change in NEAT. Conclusions Potential alterations in non-exercise activity should be considered when exercise is prescribed. The provision of appropriate education on how to self-monitor daily activity levels may improve intervention outcomes in groups who are new to exercise. Practice implications Strategies to sustain incidental and light physical activity should be offered to help empower individuals as they develop and maintain healthy and long-lasting lifestyle habits.

Metabolism in Patients with Rheumatoid Arthritis: Resting Energy Expenditure, Physical Activity and Diet-Induced Thermogenesis. Invited Review

Metabolism is one of the most important physiological functions. Resting energy expenditure, physical activity and diet are the main factors of total metabolism but the contribution of these components to total energy expenditure may be significantly changed with chronic inflammatory diseases such as rheumatoid arthritis (RA). RA is a disease that alters normal metabolism due to the overproduction of pro-inflammatory cytokines and may lead to rheumatoid cachexia. This review focuses on the individual components of total energy expenditure and discusses how physical activity and diet may influence resting metabolism both in the healthy population as well as patients with RA. Moreover, information is provided regarding the available patents (i.e. equipment and prediction equations) that may be used in order to predict metabolism in the normal population and RA patients.

Body composition is associated with physical activity in daily life as measured using a triaxial accelerometer in both men and women

Activity-related energy expenditure is the most variable component of total energy expenditure and thus an important determinant of energy balance. To determine whether body composition is related to physical activity in both men and women. A total of 134 healthy participants were recruited (80 women, 54 men; aged 21+/-2 years; body mass index, 22.0+/-2.4). Physical activity was measured for a period of 2 weeks using a triaxial accelerometer for movement registration (Tracmor). Percentage body fat (%BF) was determined by underwater weighing and deuterium dilution according to Siri's three-compartment model. The participant characteristics-body mass, height and gender together explained a substantial part of the variation in %BF (R(2)=0.75, SEE=4.0%). Adding physical activity to the model increased the explained variation in %BF with 4% (R(2)=0.79, SEE=3.7%, P<0.001). Taking seasonality into account by adding the number of daylight hours as an independent variable further increased the explained variation with 1% (R(2)=0.80, SEE=3.7%, P<0.05). In analogy, the association was evaluated for both genders separately. In women, %BF and physical activity were significantly associated (P<0.001). In men, %BF was only associated with physical activity when seasonality was taken into account as well (P<0.05). This probably resulted from men participating more in season bound sports, because an association was found without adjusting for seasonality when only men with a consistent year-round participation in sports were considered. Evidence was found for an association between body composition and physical activity in both genders. A consistent year-round degree of physical activity appears to be a prerequisite to reveal the association. Moreover, Tracmor-assessed physical activity improves the estimate of %BF when a participant's characteristics are taken into account.

Estimating activity energy expenditure: how valid are physical activity questionnaires?

Activity energy expenditure (AEE) is the modifiable component of total energy expenditure (TEE) derived from all activities, both volitional and nonvolitional. Because AEE may affect health, there is interest in its estimation in free-living people. Physical activity questionnaires (PAQs) could be a feasible approach to AEE estimation in large populations, but it is unclear whether or not any PAQ is valid for this purpose. Our aim was to explore the validity of existing PAQs for estimating usual AEE in adults, using doubly labeled water (DLW) as a criterion measure. We reviewed 20 publications that described PAQ-to-DLW comparisons, summarized study design factors, and appraised criterion validity using mean differences (AEEPAQ − AEEDLW, or TEEPAQ − TEEDLW), 95% limits of agreement, and correlation coefficients (AEEPAQ versus AEEDLW or TEEPAQ versus TEEDLW). Only 2 of 23 PAQs assessed most types of activity over the past year and indicated acceptable criterion validity, with mean differences (TEEPAQ − TEEDLW) of 10% and 2% and correlation coefficients of 0.62 and 0.63, respectively. At the group level, neither overreporting nor underreporting was more prevalent across studies. We speculate that, aside from reporting error, discrepancies between PAQ and DLW estimates may be partly attributable to 1) PAQs not including key activities related to AEE, 2) PAQs and DLW ascertaining different time periods, or 3) inaccurate assignment of metabolic equivalents to self-reported activities. Small sample sizes, use of correlation coefficients, and limited information on individual validity were problematic. Future research should address these issues to clarify the true validity of PAQs for estimating AEE.

Physical activity as determinant of daily energy expenditure

Inter-individual variation in energy expenditure is mainly a function of differences in body size and physical activity. Intra-individually, the energy expenditure associated with physical activity, i.e. muscular contractions to perform body postures and -movements, is the most variable component of total energy expenditure. Determinants of activity associated energy expenditure (AEE), as derived from observational and intervention studies are presented. Twin studies showed that most of the between subject variation in AEE is explained by genetic factors. AEE of subjects in the confined environment of a respiration chamber was on average halve the value as observed in the same subjects in free-living conditions with doubly labeled water. In young adults, non-training activity was not affected by exercise training. However, in elderly subjects, exercise training induced an equivalent compensatory decline in non-training activity. Similarly, AEE was reduced during energy restriction and in patients with chronic disease increasing resting energy expenditure. Studies with exercise training showed the reduction is difficult to overcome.

New resting energy expenditure prediction equations for patients with rheumatoid arthritis

Resting energy expenditure (REE), one of the main components of total energy expenditure, can be measured via indirect calorimetry and/or predicted from equations. The latter may be misleading in RA, as they do not take into account the metabolic alterations occurring in RA. The objectives of this study are to evaluate the accuracy of widely used REE-predictive equations in RA patients against measured REE and to develop RA-specific equations. We assessed REE (via indirect calorimetry and several predictive equations), fat-free mass (FFM; via bioelectrical impedance) and disease activity (CRP) in RA patients and healthy controls. Data from 60 RA patients (experimental group) were used to assess the accuracy of existing REE equations and to develop new equations. The new equations were validated in an independent cross-validation group of 22 RA patients. These two groups were merged and two final equations were developed. All equations significantly under-predicted measured REE (from 15% to 18.2%, all at P < 0.001) in the RA experimental group, but not in the control group. After both equations demonstrated a high validity in the cross-validation group, the new final REE prediction equations developed from the total RA sample (n = 82) were: Model 1: REE (kcal/day) = 126.1 x FFM(0.638) x CRP(0.045) (R(2) = 0.70) and Model 2: REE (kcal/day) = 598.8 x weight(0.47) x age(-0.29) x CRP(0.066) (R(2) = 0.62). The new equations provide an accurate prediction of REE in RA patients and could be used for clinical monitoring of resting metabolism of these patients without the requirement for specialized personnel.

Calorimetria indireta: uma ferramenta para adequação das necessidades energéticas dos recém-nascidos de muito baixo peso ao nascer

OBJECTIVE: To determine the resting metabolic rate in very low birth weight infants through indirect calorimetry. METHODS:Cross-sectional study including 29 clinically stable very low birth weight infants receiving an enteral diet > 100 kcal/kg/day. Malnutrition was defined as weight-for-age z score ≤ - 2 SD. Resting energy expenditure was measured using open circuit indirect calorimetry. RESULTS: At the time of the examination, mean weight was 1,564±393 g and corrected gestational age was 35±3 weeks. Malnutrition was diagnosed in 62.1% of the preterm infants. The mean resting metabolic rate was 57.01±7.76 kcal/kg/day. CONCLUSION: Since resting energy expenditure is the main caloric component of total energy expenditure, the high resting metabolic rate observed may have a strong impact on the development of malnutrition during hospitalization.

Indirect calorimetry: a tool to adjust energy expenditure in very low birth weight infants

To determine the resting metabolic rate in very low birth weight infants through indirect calorimetry. Cross-sectional study including 29 clinically stable very low birth weight infants receiving an enteral diet > 100 kcal/kg/day. Malnutrition was defined as weight-for-age z score < or = - 2 SD. Resting energy expenditure was measured using open circuit indirect calorimetry. At the time of the examination, mean weight was 1,564+/-393 g and corrected gestational age was 35+/-3 weeks. Malnutrition was diagnosed in 62.1% of the preterm infants. The mean resting metabolic rate was 57.01+/-7.76 kcal/kg/day. Since resting energy expenditure is the main caloric component of total energy expenditure, the high resting metabolic rate observed may have a strong impact on the development of malnutrition during hospitalization.

Role of Low Energy Expenditure and Sitting in Obesity, Metabolic Syndrome, Type 2 Diabetes, and Cardiovascular Disease

It is not uncommon for people to spend one-half of their waking day sitting, with relatively idle muscles. The other half of the day includes the often large volume of nonexercise physical activity. Given the increasing pace of technological change in domestic, community, and workplace environments, modern humans may still not have reached the historical pinnacle of physical inactivity, even in cohorts where people already do not perform exercise. Our purpose here is to examine the role of sedentary behaviors, especially sitting, on mortality, cardiovascular disease, type 2 diabetes, metabolic syndrome risk factors, and obesity. Recent observational epidemiological studies strongly suggest that daily sitting time or low nonexercise activity levels may have a significant direct relationship with each of these medical concerns. There is now a need for studies to differentiate between the potentially unique molecular, physiologic, and clinical effects of too much sitting (inactivity physiology) separate from the responses caused by structured exercise (exercise physiology). In theory, this may be in part because nonexercise activity thermogenesis is generally a much greater component of total energy expenditure than exercise or because any type of brief, yet frequent, muscular contraction throughout the day may be necessary to short-circuit unhealthy molecular signals causing metabolic diseases. One of the first series of controlled laboratory studies providing translational evidence for a molecular reason to maintain high levels of daily low-intensity and intermittent activity came from examinations of the cellular regulation of skeletal muscle lipoprotein lipase (LPL) (a protein important for controlling plasma triglyceride catabolism, HDL cholesterol, and other metabolic risk factors). Experimentally reducing normal spontaneous standing and ambulatory time had a much greater effect on LPL regulation than adding vigorous exercise training on top of the normal level of nonexercise activity. Those studies also found that inactivity initiated unique cellular processes that were qualitatively different from the exercise responses. In summary, there is an emergence of inactivity physiology studies. These are beginning to raise a new concern with potentially major clinical and public health significance: the average nonexercising person may become even more metabolically unfit in the coming years if they sit too much, thereby limiting the normally high volume of intermittent nonexercise physical activity in everyday life. Thus, if the inactivity physiology paradigm is proven to be true, the dire concern for the future may rest with growing numbers of people unaware of the potential insidious dangers of sitting too much and who are not taking advantage of the benefits of maintaining nonexercise activity throughout much of the day.

Determinants of energy expenditure and energy balance.

Energy metabolism of an individual is a function of body size, body composition, behaviour including food intake and physical activity, and health status. The analysis of determinants of energy expenditure is illustrated in relation to gender differences. Women have on average a lower energy intake and a lower average daily metabolic rate due to a lower body mass, fat-free mass, and a higher % body fat. Activity-induced energy expenditure, the energy expenditure associated with muscular contractions to perform body postures and—movements excluding exercise, is the most variable component of total energy expenditure. Determinants of activity-induced energy expenditure are presented to get a view whether it is an obligatory or a facultative phenomenon. Twin studies showed that most of the between subject variation in activity-induced energy expenditure is explained by genetic factors. Activity-induced energy expenditure of subjects in the confined environment of a respiration chamber was on average halve the value as observed in the same subjects in free-living conditions with doubly labeled water. In young adults, exercise training does not affect non-training activity. However, in elderly subjects, exercise training induced an equivalent compensatory decline in non-training activity. Similarly, activity-induced energy expenditure is reduced during energy restriction and in patients with chronic disease increasing resting energy expenditure. Studies with exercise training showed the reduction is difficult to overcome. There is little evidence for a compensatory increase in activity-induced energy expenditure during overfeeding.

Interindividual variability in sleeping metabolic rate in Japanese subjects

Basal metabolic rate (BMR) or sleeping metabolic rate (SMR) is the largest component of total energy expenditure (EE). An accurate prediction of BMR or SMR is needed to accurately predict total EE or physical activity EE for each individual. However, large variability in BMR and SMR has been reported. This study was designed to develop prediction equations using body size measurements for the estimation of both SMR and BMR and to compare the prediction errors with those in previous reports. We measured body size, height, weight and body composition (fat mass and fat-free mass) from skinfold thickness in adult Japanese men (n=71) and women (n=66). SMR was determined as the sum of EE during 8 h of sleep (SMR-8h) and minimum EE during 3 consecutive hours of sleep (SMR-3h) measured using two open-circuit indirect human calorimeters. BMR was determined using a human calorimeter or a mask and Douglas bag. The study population ranged widely in age. The SMR/BMR ratio was 1.01+/-0.09 (range 0.82-1.42) for SMR-8h and 0.94+/-0.07 (range 0.77-1.23) for SMR-3h. The prediction equations for SMR accounted for a 3-5% larger variance with 2-3% smaller standard error of estimate (SEE) than the prediction equations for BMR. SMR can be predicted more accurately than previously reported, which indicates that SMR interindividual variability is smaller than expected, at least for Japanese subjects. The prediction equations for SMR are preferable to those for BMR because the former exhibits a smaller prediction error than the latter.

Assessment of Low-to-Moderate Intensity Physical Activity Thermogenesis in Young Adults Using Synchronized Heart Rate and Accelerometry with Branched-Equation Modeling ,

Low-to-moderate intensity physical activity thermogenesis is a highly variable and quantitatively important component of total energy expenditure that is difficult to assess outside the laboratory. Greater precision and accuracy in the measurement of this key contributor to energy balance is a research priority. We developed a laboratory-based protocol that simulated a range of low-to-moderate intensity physical activities. We characterized the bias and random (individual) error in estimating energy expenditure using combined accelerometry and heart rate (AHR) with branched-equation modeling and a simple motion sensor (pedometer) against an indirect calorimetry criterion. Twenty young adult subjects performed a 2-h laboratory-based protocol, simulating 6 low-to-moderate intensity physical activities interspersed with periods of rest. The physical activity level during the laboratory-based protocol reflected an energy expenditure toward the lower end of the active category. We found that AHR-derived energy expenditure showed no evidence of substantial fixed or proportional bias (mean bias 6%), whereas pedometer-derived energy expenditure showed both fixed and proportional bias (bias at minimum, mean, and maximum energy expenditure +11, -20, and -36%, respectively). It appears that AHR provides an accurate estimate of criterion energy expenditure whereas a simple motion sensor (pedometer) does not. It is noteworthy that AHR provides quantitative information about the nature and patterns of physical activity, such as the amount of time and/or energy spent engaged in physical activity above critical health-related thresholds.

Physical activity in confined conditions as an indicator of free-living physical activity.

The main determinants of daily energy expenditure are body size and physical activity. Activity energy expenditure is the most variable component of total energy expenditure. It was assessed whether the physical activity level in confined conditions is an indicator of free-living physical activity. Activity energy expenditure was measured over 1 day in a confined environment of a respiration chamber (floor space, 7.0 m(2)), where activities were restricted to low-intensity activities of daily living, and over 2 weeks in a free-living environment using doubly labeled water. Subjects were 16 women and 29 men (age, 31 +/- 10 years; BMI, 24.2 +/- 2.7 kg/m(2)). The free-living activity level of the subjects, as a multiple of resting energy expenditure, was 1.76 +/- 0.13. Activity energy expenditure in the chamber was 47 +/- 13% of the value in daily life, and the two values were correlated (r = 0.50, p < 0.001; partial correlation corrected for age, gender, and BMI: 0.40, p < 0.01). The chamber value explained 25% of the total variance in free-living activity energy expenditure. The activity level of a subject under sedentary conditions is an indicator of activity energy expenditure in daily life, showing the importance of nonexercise activity for daily energy expenditure.