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American Journal of Clinical Nutrition, Vol. 87, No. 5, 1268-1276, May 2008
© 2008 American Society for Nutrition

ORIGINAL RESEARCH COMMUNICATION

Twenty-four–hour analysis of elevated energy expenditure after physical activity in a metabolic chamber: models of daily total energy expenditure1,2,3

Kazunori Ohkawara, Shigeho Tanaka, Kazuko Ishikawa-Takata and Izumi Tabata

1 From the Health Promotion and Exercise Program, National Institute of Health and Nutrition, Tokyo, Japan

2 Supported by the Health and Labour Sciences Research Grants for Comprehensive Research on Cardiovascular and Life-Style Related Diseases from the Japanese Ministry of Health, Labour and Welfare (PI: S Tanaka).

3 Address reprint requests to K Ohkawara, Health Promotion and Exercise Program, National Institute of Health and Nutrition, 1-23-1 Toyama, Shinjuku-ku, Tokyo, 162-8636, Japan. E-mail: ohkawara{at}nih.go.jp.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: The Institute of Medicine proposed that 15% of energy expenditure (EE) as excess post-exercise oxygen consumption should be added to additional physical activity energy expenditure ({Delta}PAEE) to estimate total EE. However, the magnitude of elevated post–physical activity energy expenditure (EPEE) under normal daily living conditions has not been examined.

Objective: We examined the effects of EPEE on 24-h EE by modeling standard living conditions in a metabolic chamber.

Design: Eleven Japanese men completed three 24-h metabolic chamber measurements: a control day (C-day), a day with high-frequency moderate-intensity physical activity (M-day), and a day with high-frequency vigorous-intensity physical activity (V-day).

Results: Mean (± SD) 24-h EE for the C-day, the M-day, and the V-day was 2228 ± 143 kcal, 2816 ± 197 kcal, and 2813 ± 163 kcal, respectively. No significant difference was observed in 24-h EE between an M-day and a V-day. Mean EPEEs on the M-day and the V-day did not significantly contribute to increasing 24-h EE. Relative EPEEs to {Delta}PAEEs were 6.2 ± 13.9% (M-day) and 5.1 ± 9.2% (V-day). However, EPEE/24-h EE was negatively correlated with maximal oxygen uptake on the V-day (r = –0.68, P = 0.02), although no significant correlation between these variables was observed on the M-day (r = –0.41, P = 0.21).

Conclusions: These results suggest that EPEE has a small effect on 24-h EE in the course of normal daily activities, findings that do not support the proposition by the Institute of Medicine for estimating TEE. However, persons with low physical fitness levels could enhance EE as EPEE by increasing vigorous-intensity daily physical activity.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The prevalence of obesity has been increasing over the past few decades (1). The increase in weight or body fat is explained by a chronic imbalance between energy expenditure (EE) and energy intake. It is reported that regular exercise could play a major role in the control of body weight (2). Exercise (or physical activity) contributes to weight maintenance or weight reduction in several ways. First, thermogenesis is retained by maintaining fat-free mass. Second, EE is increased through exercise itself corresponding to work. Finally, increased EE may be induced by excess post-exercise oxygen consumption (EPOC) (3, 4).

EPOC is due to elevated oxygen consumption during the post-exercise period and consists of a rapid component and a prolonged component (5). The rapid component decays within approximately 1 h, followed by the prolonged component, which lasts for several hours. Many laboratories have examined the relation between exercise duration or intensity and the magnitude of EPOC (4, 6). According to Bahr and Sejersted (7), exercise intensity is curvilinearly related to EPOC. They suggested that exercise intensity must exceed 40% to 50% of maximal oxygen uptake (VO2max) to produce the prolonged component of EPOC, whereas 30% of VO2max produces the rapid component of EPOC (7). Furthermore, it has been suggested that exercise duration has a linear relation to the magnitude of EPOC (8).

Physical activity thermogenesis can be divided into volitional exercise thermogenesis (sports and fitness-related activities) and nonexercise activity thermogenesis (9). It is generally accepted that obesity could be reduced through exercise or physical activity. That is, persons should increase total energy expenditure (TEE) by a range of physical activities including daily activities such as cleaning and gardening (10, 11). Levine et al (12) suggested that increasing nonexercise activity thermogenesis could be a strong contributor to preventing obesity. To support this proposition, it is important to verify the effects of additional EE after physical activity (elevated post–physical activity energy expenditure, or EPEE). There are no data on the effect of EPEE on 24-h EE under normal living conditions. Nevertheless, the Institute of Medicine proposed that 15% of EE as EPOC should be added to the additional physical activity energy expenditure ({Delta}PAEE) from sedentary conditions to estimate TEE, because adjustment for EPOC and dietary induced thermogenesis is expected to improve the underestimation of TEE by the factorial method compared with TEE measured by doubly labeled water (13, 14). Although it has been reported that these adjustments improved estimates of TEE (15, 16), they could be inappropriate for other studies in which TEE was not underestimated (17, 18). The purpose of this study was to examine the effects of EPEE on 24-h EE by modeling normal living conditions in a metabolic chamber.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Subjects
Eleven Japanese men participated in this study. All subjects were adults (≥20 y) and lacked chronic diseases that could affect metabolism or daily physical activity. They had not participated in regular intensive sports or physical activity for the past year but were able to complete a jogging regimen (8.0 km/h). The descriptive characteristics of the study subjects are presented in Table 1Go. Informed consent was signed by all subjects. The study protocol was approved by the Ethical Committee of the National Institute of Health and Nutrition.


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  		TABLE 1. Physical characteristics of the subjects1

 
Experimental design
Weight, height, and body composition were measured while the men were in a fasting state. Each subject completed a 24-h metabolic chamber measurement under 3 different protocols so that we could examine the effects of physical activity intensity: a control day (C-day); a day with high-frequency, moderate-intensity physical activity (M-day); and a day with high-frequency, vigorous-intensity physical activity (V-day). A test for peak oxygen uptake and metabolic chamber measurements were done at intervals of 2 to 3 d, but within 14 d to avoid metabolic influences from other protocols. We instructed the subjects to live under normal daily conditions during the measurement period (within 14 d) to maintain the same conditions, weight, and body composition for each measurement day. The order of the 3-d metabolic chamber measurements was randomly assigned to each subject.

Anthropometry and body composition
A digital scale was used to measure body weight to the nearest 0.1 kg while the subjects were dressed in light clothing. Barefoot standing height was measured to the nearest 0.1 cm by using a wall-mounted stadiometer. Body mass index was calculated as body weight (kg) divided by height squared (m2).

Lean soft tissue mass, fat mass, and bone mineral content were measured by dual-energy X-ray absorptiometry (QDR-4500A scanner; Hologic, Waltham, MA). The subjects were positioned for whole-body scans according to the manufacturer's protocol. They lay in a supine position on the scanner table with their limbs close to their bodies. Fat-free mass was defined as the sum of lean soft tissue mass and bone mineral content.

Peak oxygen uptake
Peak oxygen uptake (VO2peak) was measured by use of an incremental running test on a treadmill (TREAD-MILL; Nishikawa Iron Works, Kyoto, Japan). The subjects warmed up at 160, 180, or 200 m/min at a fixed 0° grade for 5 min. The treadmill speed increased at a rate of 10 m/min for each successive minute of running until fatigue, defined as the speed at which the subject could no longer continue to keep up with the treadmill. Heart rate and rating of perceived exertion were monitored continuously. The rating of perceived exertion was obtained by using the modified Borg scale (19). Oxygen uptake was measured over 30-s intervals after the rating of perceived exertion reached 15. Subjects breathed through a low-resistance 2-way valve, and the expired air was collected in Douglas bags. Expired oxygen and carbon dioxide gas concentrations were measured by mass spectrometry (ARCO-1000A; Arco System, Kashiwa, Japan), and gas volume was determined by using a certified dry gas meter (DC-5; Shinagawa, Tokyo, Japan). For each measurement, the gas analyzer was initially calibrated by using a certified gas mixture and atmospheric air. The highest value of VO2 during the exercise test was designated as VO2peak.

Metabolic chamber
An open-circuit indirect metabolic chamber was used to evaluate 24-h EE, basal metabolic rate (BMR), and sleeping metabolic rate (SMR) (20, 21). Briefly, the respiratory chamber was an airtight room (20 000 L) equipped with a bed, desk, chair, TV with video deck, CD player, telephone, toilet, sink, and treadmill. The temperature and relative humidity in the room were controlled at 25 °C and 55%, respectively. The oxygen and carbon dioxide concentrations of the air supply and exhaust were measured by mass spectrometry. For each experiment, the gas analyzer (ARCO-1000A-CH; Arco System, Kashiwa, Japan) was initially calibrated by using a certified gas mixture and atmospheric air. The flow rate exhausted from the chamber was measured by pneumotachography (FLB1; Arco System). The flow meter was calibrated before each measurement, and the flow rate was maintained at {approx}90 L/min (ATP). VO2 and carbon dioxide production (VCO2) were determined by the flow rate of exhaust from the chamber, and the concentrations of the inlet and outlet air of the chamber, respectively (20). EE was estimated from VO2 and VCO2 by using Weir's equation (22). The accuracy and precision of our metabolic chamber for measuring EE as determined by the alcohol combustion test was 99.8 ± 0.5% (mean ± SD) over 6 h and 99.4 ± 3.1% over 30 min.

Spontaneous physical activity was evaluated by using a motion-detecting system. The chamber had 2 independent sensors of passive infrared type (Matsushita Automation Controls Co, Ltd, AMP2009B01, Tokyo, Japan) that detected movement at speeds >7 cm/s. When at least 1 sensor detected movement, the movement was regarded as positive. The system provided percentage of time when movement was observed in each minute, and averaged spontaneous physical activity over each 15-min interval was used for analyses.

Design for timetables in the metabolic chamber
Physical activity level (PAL), which is calculated as TEE divided by BMR, has been categorized by the Institute of Medicine as low active (average: 1.5; range: 1.4–1.59), active (average: 1.75; range: 1.6–1.89), and very active (average: 2.2; range: 1.9–2.49) (14). The 2005 Japanese Dietary Reference Intakes reported similar categorization (23). Therefore, C-day was designed to correspond to a PAL of 1.4–1.59 including reference physical activity. On the basis of the C-day, we modeled M-day and V-day as follows: 1) comparable PAL between M-day and V-day for comparing with these EPEEs, 2) PALs to include the normal human range, and 3) actual percentages of low-, moderate-, and vigorous-intensity physical activity encountered in daily living (24, 25).

In the present study, we sought to model normal daily living in the metabolic chamber. Daily living activities consist of various physical activities, such as cleaning, cooking, washing, and gardening. However, it is very difficult to prescribe daily physical activity strictly, as well as to continue them for extended periods of time. Therefore, daily physical activity was substituted as follows: slow walking [3.2 km/h, 2.5 metabolic equivalents (METs)] as low-intensity physical activity, brisk walking (5.6 km/h, 3.8 METs) as moderate-intensity activity, and jogging (8.0 km/h, 8.0 METs) as vigorous-intensity activity (26). Note that physical activities in the course of daily living are carried out at high frequencies, but are relatively short in duration. For that reason, each activity was limited to a period of 15 min, which is the minimum duration required by our instrument to measure EE with high accuracy.

The schedules in the metabolic chamber are shown in Table 2Go. The subjects entered the chamber at 1750 and stayed until 1805 the next day. Sampling data were collected between 1800 and 1800 (24 h). The subjects went to bed at 2400 and were gently awakened at 0700 (7 h). The mean metabolic rate during this period was used as the SMR. After getting up, the subjects were permitted to use the toilet and were required to return to bed immediately. Then, the subjects remained in a supine position without movement until 0800. BMR was determined as the mean metabolic rate between 0715 and 0800. Except for prescribed physical activity and using the toilet, the subjects were only permitted to carry out light activities in a sitting position, such as reading, writing, and viewing television. Sleeping was not permitted. Meals were given 3 times a day to provide the predicted BMR (23) multiplied by the estimated PAL of 1.75, as an intermediate value for C-day and M-day (or V-day) modeling. Ratios of protein to fat to carbohydrate in total energy intake per day were 18:20:62. The same meals were provided on each of the 3 d to unify dietary induced thermogenesis.


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  		TABLE 2. Timetables for each modeling day in the metabolic chamber1

 
Calculation of elevated post–physical activity energy expenditure
We estimated EPEE on the M-day and the V-day as measured 24-h EE minus predicted 24-h EE without EPEE. Predicted 24-h EE without EPEE was obtained from a model based on the C-day with use of the factorial method (Figure 1Go). That is, 24-h EE without EPEE for M-day and V-day was predicted by the 24-h EE for the C-day plus the reference EE for brisk walking and jogging. The reference EEs for brisk walking (5.6 km/h) and jogging in this model were calculated from each activity during C-day. To calculate steady state values for EE for these activities, EE values for the first 3 min and the last 1 min during the 2 reference activities were removed, and mean EE in the remainder was extended to 15 min (27, 28). Furthermore, for comparing with relative EE as EPOC to additional physical activity energy expenditure ({Delta}PAEE) in the US and Canada DRI equation, {Delta}PAEE was calculated as the predicted 24-h EE without EPEE on the M-day or V-day minus the 24-h EE for the C-day.


Figure 1
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  		FIGURE 1.. Model for predicting 24-h energy expenditure (EE) without elevated post–physical activity energy expenditure (EPEE). M-day, a day with high-frequency, moderate-intensity physical activity; V-day, a day with high-frequency, vigorous-intensity physical activity; W, reference energy expenditure for walking (5.6 km/h); J, reference energy expenditure for jogging; empty bar, actual energy expenditure by the prescribed physical activity for each day; filled bar, reference energy expenditure for brisk walking (5.6 km/h) or jogging.

 
Statistical analysis
We performed a power calculation ({alpha} = 0.05 and β = 0.80) to determine whether the EPEE value corresponded to 15% of {Delta}PAEE, which was {approx}100 kcal in our subjects. Data from previous observations showed that the SD for the 24-h EE measurement in our metabolic chamber is {approx}75 kcal. From this power calculation, we determined that ≥9 subjects were needed. All values are presented as means ± SDs. Differences were considered to be statistically significant if the P value was <0.05. The SMR, 24-h EE, and 24-h EE/SMR values obtained in the 3 protocols were compared by one-way analysis of variance, and significant differences were analyzed by using Scheffe's post hoc test. Differences between actual 24-h EE and predicted 24-h EE without EPEE on M-day or V-day were assessed by the paired t test. Differences in any variable between M-day and V-day were assessed by the paired t test. Correlations between EPEE on the M-day or the V-day and VO2peak or body composition were assessed by Pearson's correlation coefficients (r). All statistical analyses were performed by using SPSS version 14.0J for WINDOWS (SPSS Inc, Chicago, IL).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
All subjects completed the 3-d metabolic chamber measurements according to prescribed timetables. The subjects' average total energy intake was 2685 ± 303 kcal, and this did not differ between the 3 d in each subject, because they ate all provided meals completely. Mean VO2peak was 47.3 ± 8.3 mL · min–1 · kg–1. Relative physical activity intensities for slow walking, brisk walking, and jogging were 21.4 ± 5.1%, 33.3 ± 7.0%, and 65.0 ± 14.1% of VO2peak, respectively.

Mean SMR, 24-h EE, and 24-h EE/SMR are shown in Figure 2Go. Twenty-four–hour EE for C-day, M-day, and V-day was 2228 ± 143 kcal, 2816 ± 197 kcal, and 2813 ± 163 kcal, respectively. No significant differences were observed in 24-h EE values between M-day and V-day, although there were significant differences between C-day and M-day or V-day. There were no significant differences between SMR values (or BMR values) for the 3-d periods for the subjects. CVs for SMR and BMR over 3 d were 1.0% and 1.7%, respectively. Twenty-four–hour EE/SMR for 3 d was 1.58 ± 0.06 for C-day, 2.02 ± 0.07 for M-day, and 2.00 ± 0.08 for V-day.


Figure 2
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  		FIGURE 2.. Sleeping metabolic rate (SMR), 24-h energy expenditure (24-h EE), and 24-h EE/SMR for each modeling day (n = 11). C-day, a control day; M-day; a day with high-frequency, moderate-intensity physical activity; V-day, a day with high-frequency vigorous-intensity physical activity. Error bars indicate SD. Bars with the same letter were not significantly different by one-way ANOVA with Scheffe's post hoc test (P < 0.05).

 
There were no significant differences between the measured 24-h EE value and the predicted 24-h EE value without EPEE for M-day or V-day (Table 3Go). Mean EPEE values for M-day and V-day were not significantly different. Relative EPEE values to measured 24-h EE values were 1.2 ± 2.7% and 1.0 ± 0.8%. Furthermore, relative EPEEs to {Delta}PAEEs were 6.2 ± 13.9% and 5.1 ± 9.2%, respectively.


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  		TABLE 3. Elevated post–physical activity energy expenditure (EPEE) for the M-day and the V-day1

 
Mean percentages of spontaneous physical activity during prescribed physical activity (slow walking, brisk walking, and jogging) for the 3 d were {approx}100%. There were no significant differences in mean percentages of spontaneous physical activity for resting periods for the 3 d (C-day: 38.1 ± 9.0%; M-day: 43.8 ± 5.6%; V-day: 40.4 ± 8.2%).

The relations between EPEE/24-h EE and VO2peak or fat-free mass for M-day or V-day are shown in Figure 3Go and Figure 4Go. EPEE/24-h EE for V-day was negatively correlated with VO2peak, whereas no significant correlation between these variables was observed for EPEE/24-h EE for M-day. As for the relation between EPEE/24-h EE or EPEE and fat-free mass, no significant correlations were observed for either M-day or V-day. Also, fat mass and body mass indexes were not significantly correlated with EPEE/24-h EE or EPEE for either day. The correlation coefficients for EPEE versus between-day SMR difference were 0.31 (NS) and 0.63 (P < 0.05) for M-day and V-day, respectively.


Figure 3
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  		FIGURE 3.. Relation between elevated post–physical activity energy expenditure (EPEE) and peak oxygen uptake (VO2peak) for the M-day (a day with high-frequency, moderate-intensity physical activity) and the V-day (a day with high-frequency, vigorous-intensity physical activity). 24-h EE, 24-h energy expenditure.

 

Figure 4
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  		FIGURE 4.. Relation between elevated post–physical activity energy expenditure (EPEE) and fat-free mass for the M-day (a day with high-frequency, moderate-intensity physical activity) and the V-day (a day with high-frequency, vigorous-intensity physical activity). 24-h EE, 24-h energy expenditure. There were no significant correlations between EPEE and fat-free mass for any day (P < 0.05).

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
This investigation examined the effects of EPEE on 24-h EE by modeling normal living activities in a metabolic chamber. There was no significant additional EE as EPEE in total 24-h EE when the subjects spent 24 h in a metabolic chamber under conditions that were {approx}2.0 for 24-h EE/SMR (similar to PAL) for high-frequency, moderate-intensity or vigorous-intensity physical activity. However, subjects with low physical fitness may produce significant additional EE as EPEE by increasing daily vigorous-intensity physical activity.

Although EPOC has been studied in depth, most analyses examined the effects of EPOC after a single bout of exercise (4, 6). However, if one is to understand the effects of EPOC in weight reduction or maintenance, it is important to investigate the magnitude of EPOC after physical activity under normal living conditions. Previous studies suggested that EPOC after a single bout of exercise was generated in proportion to exercise duration, when exercise intensity exceeds about 50–60% VO2max (6–8). Almuzaini et al (29) reported that dividing a 30-min exercise session into 2 parts significantly increased the magnitude of EPOC. However, this study was limited to the 40-min period after exercise, and the difference between EPOC values was only {approx}10 kcal. Normal daily activity conditions evidently differ from those experimental conditions, because in the normal course of daily activity, people engage in a wide range of physical activity, the intensity of which vary from light to vigorous (26). The duration of most of these activities and the intervals between moderate-to-vigorous physical activity are short, but their frequencies are high. This situation requires examination of the effects of EPEE (similar to, but a broader component than EPOC) on 24-h EE under normal activity conditions.

If significant EPEE by combined physical activity in daily living exists, one reason might be that the total duration of all physical activity amounted to several hours per 24 h, even though each activity was short. Furthermore, short intervals between physical activities with high frequencies may produce higher EPEE than the EPEE induced by a prolonged, single bout of exercise. However, the present study failed to identify any significant additional EE as EPEE in the 24-h EE. That is, multiplying short-duration physical activities with short intervals between activities may not contribute much toward increasing the 24-h EE, compared with prolonged physical activity, even if persons perform these short-duration physical activities with high frequencies during a 24-h period. The Institute of Medicine has proposed that 15% of EE as EPOC to {Delta}PAEE from sedentary condition should be added in estimating total energy expenditure (14). This proposition is based on the report by Bahr et al (13), which compared EPOC magnitudes between 20, 40, and 80 min of ergometer exercise at 70% VO2max. As a result, each EPOC was {approx}15% of exercise-induced EE for 12 h after the exercise sessions. However, this evidence was obtained from a single-bout trial. In our experimental design, normal daily activity conditions were modeled, and EPEE resulted in 6.2 ± 13.9% (M-day) and 5.1 ± 9.2% (V-day) of {Delta}PAEE. Therefore, the equation estimating TEE proposed by the Institute of Medicine, which adds 15% EE as EPOC to {Delta}PAEE, would overestimate 24-h EE.

Previous studies using a single round of exercise suggest that one possible explanation for not observing significant EPEE in daily activity was that many daily activities do not reach the intensity threshold of 50–60% VO2max (7, 8). We adopted brisk walking (3.8 METs) as a moderate-intensity physical activity and jogging (8.0 METs) as a vigorous-intensity physical activity. Note that Pate et al (30) have defined that moderate-intensity physical activity ranged from 3 to 6 METs and vigorous-intensity physical activity was >6 METs. The relative exercise intensities of brisk walking and jogging were 33.3 ± 7.0% and 65.0 ± 14.1%, respectively. Brisk walking did not reach 50–60% VO2max as the intensity threshold for producing EPOC. On the other hand, Melanson et al (31) reported that if energy expenditures were matched between high-intensity exercise and low-intensity exercise with well-controlled conditions in a metabolic chamber, no significant difference was observed in 24-h EE values between these 2 conditions. Saris and Schrauwen (32). reported that in obese subjects, no significant differences in 24-h EE values were observed between the day with high-intensity interval exercise and the day with low-intensity endurance exercise when the exercise sessions were equicaloric in energy expenditure. From our results and previous studies, it appears that exercise or physical activity intensity does not influence the contribution of EPOC to 24-h EE. However, a significant difference of EPOC magnitude may be found between high- and low-intensity exercise when one measures EPOC within several hours of a single-bout trial.

The inclusion (or lack thereof) of oxygen deficit in calculations of EPOC may contribute to discrepancies among studies. Most studies with a single-bout trial compared EPOC to oxygen consumption during an exercise bout (4, 6), in which case oxygen deficit is not taken into account. On the other hand, we discuss EPEE without EE equivalent to oxygen deficit, by extrapolating steady state EE (excluding EE in the first 3 min and the last 1 min) to the whole EE in each physical activity period. Although total EPOC is greater than oxygen deficit, a large part of the rapid component of EPOC is explained by oxygen deficit during the exercise (5). If we consider the extra energy expenditure due to exercise or physical activity in 24-h EE, such as the estimation of TEE in the Institute of Medicine (14), EE corresponding to oxygen deficit should be excluded. However, the study by Bahr et al (13) discussed the contribution of EPOC to EE during an exercise bout, so adding 15% as EPOC to {Delta}PAEE should lead to overestimation of TEE.

Although EPEE did not contribute to a significant increase in 24-h EE in the present study, EPEE/24-h EE for V-day was significantly correlated with VO2peak. That is, a person with low fitness may generate more EPEE by increasing daily physical activity. Short and Sedlock (33) reported that even though EE during exercise in trained subjects was much higher than that in untrained subjects, EPOC was similar between the groups if different subjects exercised at the same relative intensity of 70%VO2peak. When compared with subjects with higher VO2max, those with lower oxygen uptake produced more lactate, a major biochemical component of EPOC (34). Therefore, a negative relation between VO2peak and EPEE/24-h EE observed in the present investigation is reasonable.

Trained individuals have better thermoregulatory capacities than do untrained individuals because physical training enhances the sweating mechanism at a given level of the central sweating drive (35). Therefore, elevated body temperature in untrained individuals could last longer than in trained individuals (36). These phenomena require extra oxygen consumption for recovery. Therefore, fitness level may contribute to the magnitude of EPEE. On the other hand, there was no significant relation between EPEE/24-h EE for the M-day and VO2peak. In other words, it is assumed that exercise duration (with relative intensity over the threshold for producing the slow component of EPOC) may be longer in less fit subjects than in fit subjects, leading to more slow-component production in less fit subjects. However, the relative intensities of the 3 physical activities in this study were different in individuals, because these physical activities were prescribed by the same absolute intensities. Interestingly, EPEE was negative on both the M-day and the V-day in several subjects. One possible reason may have been interday variations in resting metabolic rate. In the present study, SMR values on M-day or V-day were lower than the SMR values on C-day in some cases, and the correlation coefficients for EPEE versus between-day SMR difference were 0.31 and 0.63 on M-day and V-day, respectively. Therefore, the negative values of EPEE may reflect interday variations in resting metabolic rate. In addition, people may compensate for an increase in EE due to activity by decreasing their nonexercise EE (37). In the present study, the total duration of prescribed physical activity was 240 min on the M-day. That is, the duration on the M-day was 60 min longer than on the V-day. Therefore, the total duration or frequency of physical activity during the day may affect the observed decrease in nonexercise EE.

In the present study, there were no significant correlations between EPEE for M-day (or V-day) and physical status (fat-free mass, fat mass, and body mass index). Crommett and Kinzey (38) have reported similar results. Although body composition may not influence EPEE, many obese persons are untrained and have a low level of fitness. Therefore, our results suggest that obese persons with a low fitness level could expect additional EE as EPEE to assist in weight reduction, provided that they perform high-frequency, relatively vigorous physical activity in the course of daily living. Otherwise, persons with a high fitness level may not expect significant EPEE through daily physical activity, because daily activity is difficult to adjust to high intensity, like typical exercise activity.

This study had several limitations. First, we could not measure actual daily physical activity because we conducted the measurements in a metabolic chamber. Additionally, the duration of each physical activity under normal living conditions may be shorter than 15 min in many cases, whereas 15 min was the minimum duration of activity required for accurate measurement values in this study. Even though we gathered data under well-controlled conditions, our experimental protocol could not detect any EPEE on the control day. However, control day EPEE values should be added to the calculated EPEE values on M-day and V-day. Although we believe that control day EPEE values would not be large, the actual {Delta}PAEE in normal daily living may thus be slightly higher than our calculated results. Furthermore, future studies are needed to clarify the association between fitness and EPEE, because inclusion of a single subject in our data set, the one with the lowest fitness, strongly contributed to the significant (but modest) inverse association observed between these variables.

In conclusion, we found that EPEE has a only small effect on 24-h EE under normal living conditions. Therefore, adding 15% EE as EPOC to {Delta}PAEE, in accord with the Institute of Medicine recommendation for estimating TEE, would overestimate 24-h EE. However, persons with a low physical fitness level may produce additional EE as EPEE by increasing relatively vigorously intense daily living physical activity.


   ACKNOWLEDGMENTS
 
We express our heartfelt thanks to the subjects who participated in this study. We thank the members of the National Institute of Health and Nutrition, especially Hiroko Kogure, Emiko Taguri, and Rieko Miyake, for their help in data acquisition and analyses.

The responsibilities of the authors were as follows—KO: study design, data acquisition, data analysis, data interpretation, and writing the manuscript; ST: study design, data acquisition, data analysis, data interpretation, and writing the manuscript; KI: study design and editing the manuscript, IT: study design and editing key aspects of the manuscript. None of the authors had a personal or financial conflict of interest.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. World Health Organization. Diet, nutrition and the prevention of chronic diseases. World Health Organ Tech Rep Ser 2003;916:1–149.
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Received for publication August 9, 2007. Accepted for publication November 5, 2007.





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