Journal of Applied Physiology Information on EB 2010
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

J Appl Physiol 105: 561-568, 2008. First published May 29, 2008; doi:10.1152/japplphysiol.00091.2008
8750-7587/08 $8.00
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF) Free
Right arrow All Versions of this Article:
105/2/561    most recent
00091.2008v1
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Web of Science (1)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by den Hoed, M.
Right arrow Articles by Westerterp, K. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by den Hoed, M.
Right arrow Articles by Westerterp, K. R.

Habitual physical activity in daily life correlates positively with markers for mitochondrial capacity

Marcel den Hoed,1 Matthijs K. C. Hesselink,2 Gerrit P. J. van Kranenburg,2 and Klaas R. Westerterp1

Departments of 1Human Biology and 2Movement Sciences, Maastricht University, Maastricht, The Netherlands

Submitted 29 January 2008 ; accepted in final form 23 May 2008


   ABSTRACT
TOP
 ABSTRACT
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Physical exercise training is a powerful tool to maintain or improve mitochondrial density and function (mitochondrial capacity). This study aims to determine whether mitochondrial capacity is also associated with habitual physical activity in daily life (PADL). The capacity of classic markers for mitochondrial density, i.e., the capacity of citrate synthase (CS) and succinate dehydrogenase (SDH), as well the capacity of cytochrome c oxidase (COX) and β-hydroxyacyl-CoA dehydrogenase (HAD), was determined in homogenized muscle biopsy samples obtained from the vastus lateralis muscle of nonexercising healthy young (age 20 ± 2 yr) subjects (31 women, 7 men). PADL was measured during two periods of 14 days using a triaxial accelerometer for movement registration. CS, SDH, and COX were positively associated with PADL [P < 0.05, R = 0.36, 95% confidence interval (CI): 1.3·10–4 to 2.2·10–3; P < 0.05, R = 0.39, 95% CI: 1.1·10–5 to 9.9·10–5; and P < 0.05, R = 0.33, 95% CI: 7.5·10–6 to 3.6·10–4, respectively], and HAD tended to correlate positively with PADL (P = 0.06, R = 0.31, 95% CI: –2.2·10–5 to 1.1·10–3). The population was subsequently stratified based on the intensity of the activities performed. CS was only associated with PADL in subjects spending more time on high-intensity physical activity, whereas HAD was only associated with PADL in subjects spending less time on low intensity physical activity. We are the first to report that even within the range of normal daily life activities, mitochondrial capacity is positively associated with the level of habitual physical activity in daily life. Thus an active lifestyle may help to maintain or improve mitochondrial capacity.

accelerometer; intensity; citrate synthase; succinate dehydrogenase; cyctochrome c oxidase; β-hydroxyacyl-CoA dehydrogenase

IN WESTERNIZED SOCIETIES, the prevalence of Type 2 diabetes and obesity has increased significantly over the past few decades (18, 25). A decreased physical activity has been associated with both Type 2 diabetes (13, 17) and obesity (15). Part of the pathophysiology related to these diseases has been attributed to a reduced mitochondrial capacity: the product of mitochondrial density and function (2, 16, 22).

Mitochondria are vital organelles in the oxidative degradation of macronutrients to maintain cellular ATP levels. Mitochondrial aberrations, resulting in a reduced mitochondrial capacity, may therefore seriously impair normal energy and substrate metabolism. Mitochondrial aberrations have not only been reported for metabolic disorders like Type 2 diabetes and obesity but also in diseases like chronic heart failure and chronic obstructive pulmonary disease (11, 24).

Proper mitochondrial function and maintenance of mitochondrial capacity rely on a delicate balance between mitochondrial biogenesis and degradation. While the precise mechanisms of mitochondrial biogenesis and degradation are not fully elucidated yet, it has been known for decades that one of the most potent triggers to improve or maintain mitochondrial capacity is physical exercise (9). Engagement in physical exercise programs results in increased mitochondrial biogenesis and improved mitochondrial function in healthy controls (12, 29) and is even capable of restoring mitochondrial capacity in diseased states like Type 2 diabetes and obesity (21, 30). Unfortunately, long-term adherence to strenuous exercise programs is limited (32), and life-long engagement in sports and exercise to prevent mitochondrial aberrations may be an unrealistic goal in Westernized societies. If, however, mitochondrial capacity can also be maintained by high levels of habitual physical activity in daily life (PADL), the goal of maintaining mitochondrial capacity and preventing mitochondrial aberrations by physical activity may become feasible.

Interestingly, wide ranges in PADL have been reported (23) with the most active people showing daily life activity levels approaching those reported for people actively engaged in endurance sports (5). While it is obvious that mitochondrial capacity is higher in trained athletes than in sedentary controls, it is not known to date whether differences also exist within the ranges of normal daily life activities. The aim of the present study was therefore to examine the association between markers of mitochondrial capacity with habitual physical activity in daily life in a young and healthy population. To this end, classic markers for muscle mitochondrial density, the capacity of citrate synthase (CS) and succinate dehydrogenase (SDH) (10), were measured along with the capacity of cytochrome c oxidase or complex IV (COX) from the electron transport chain and β-hydroxyacyl-CoA dehydrogenase (HAD) from the β-oxidation (8, 28). PADL was recorded using our validated noninvasive triaxial accelerometer approach (23). We hypothesized a higher mitochondrial enzymatic capacity in subjects with a higher PADL.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Subjects

Thirty-eight healthy, nonsmoking subjects (31 women, 7 men), 20 ± 2 yr of age (means ± SD), gave written informed consent to participate in this study. To minimize the effect of physical exercise training, subjects spending over 2 h/wk on endurance sports or 5 h/wk on sports and exercise in general were excluded from participation. Information about the purpose and protocol of the study, as well as its risks and discomfort, was provided both orally and in writing. The study conformed to the standards set by the Declaration of Helsinki, and the local Ethics Committee approved the study.

PADL

PADL was measured using a triaxial accelerometer for movement registration (Tracmor IV; Philips Research, Eindhoven, The Netherlands) sensitive to a wide range of body movements. The accelerometer has been validated against doubly labeled water, the gold standard for measuring energy expenditure in daily life (23). The Tracmor registers accelerations of the trunk along the anteroposterior, mediolateral, and longitudinal axis using three uniaxial piezoelectric accelerometers [details are provided elsewhere (23)]. To ensure a valid reflection of long-term daily life activities, the accelerometer was worn for two 14-day periods under free-living conditions. Subsequently, PADL was defined as the average of both measurement periods.

Subjects were instructed to wear the Tracmor from the moment they woke up in the morning until they went back to bed at night. To verify whether subjects lived up to this instruction, waking hours and clock times of wearing the Tracmor were noted. To make sure only representative days were included, the difference between the total time the subject was awake and the time the accelerometer was worn was not allowed to exceed 75 min/day. The few days during which this difference exceeded 75 min were excluded from the analysis. This resulted in an average of 26 representative days per subject. To ensure that subjects met the inclusion criterion concerning their participation in sports and exercise, the actual sporting hours were also recorded in the diary.

PADL was acquired by summing the output of all three axes and is presented as megacounts per day (Mcnts/day). Using Tracmor data, the proportion of time subjects were physically active at a low, moderate, and high intensity (%Low, %Moderate, and %High, respectively) was determined. The cut-off points for the intensity categories were determined in a pilot study (n = 5). The cut-off point for low-intensity physical activity was set by Tracmor outputs associated with walking on a treadmill at 3.5 km/h, which corresponds with ~3 metabolic equivalents (METs), i.e., three times basal metabolic rate. For moderate-intensity physical activity, a Tracmor output associated with walking on a treadmill at 5 km/h was used, which corresponds with ~4.5 METs (1). The relevant Tracmor outputs were 16.0 ± 3.0 and 28.9 ± 3.0 Mcnts/min, respectively. All physical activity associated with a Tracmor output higher than the latter cut-off point was considered high-intensity physical activity. The proportion of time per intensity category was calculated as the sum of all minutes per intensity category divided by the total duration of the measurement, i.e., 28 days minus the number of excluded days.

Using linear regression analysis in a population similar to the present study with respect to PADL, body composition, and age, Plasqui et al. (23) were able to predict physical activity level (PAL), i.e., the factor by which average daily metabolic rate exceeds basal metabolic rate, with an explained variation of 70% using only megacounts per day. Whereas the MET score represents the factor by which energy expenditure exceeds basal metabolic rate for a certain predefined physical activity, PAL represents the factor by which energy expenditure exceeds basal metabolic rate during 24 h. For a proper reflection of 24-h daily life energy expenditure under free-living conditions, PAL thus provides a more valid reflection than MET scores, which in turn provide a more valid reflection of energy expenditure when considering predefined physical activities. The regression equation developed by Plasqui et al. was used in the present study to estimate PAL.

Muscle Biopsies

A muscle biopsy was obtained after an overnight fast with subjects refraining from strenuous physical activity for 24 h before the collection. The biopsy was obtained from the vastus lateralis muscle under local anesthesia (2% xylocaine) using a Bergström needle with suction (3). After muscle samples were freed from blood, visible fat, and connective tissue, they were immediately frozen in liquid nitrogen and stored at –80°C until analyzed.

Measurements of Enzyme Activities

SET buffer was prepared by dissolving 8.557 g sucrose (250 mM), 0.211 g Tris (10 mM), and 0.0744 g EDTA (2 mM) in 80 ml distilled water. pH was adjusted to 7.4, and distilled water was added to a final volume of 100 ml. Muscle samples were weighed (mean ± SD: 39.0 ± 18.8 mg) and homogenized in 1 ml of SET buffer using a Polytron homogenizer (Polytron-Aggregate; Kinematica, Littau, Lucerne, Switzerland). Homogenates were frozen and thawed two additional times using liquid nitrogen to break mitochondrial membranes and were subsequently stored at –80°C until analyzed.

On analysis, muscle homogenates were centrifuged at 13,000 g for 2 min. Supernatant was used for analysis. Absorbance changes for all enzyme assays were measured in a COBAS-FARA semiautomatic analyzer (COBAS-FARA; Roche, Basel, Switzerland). The molar extinction coefficients used were 13,600 l·mol–1·cm–1 for coenzyme A-DTNB at 412 nm for CS, 21,000 l·mol–1·cm–1 for dichlorophenol indophenol (DCPIP) at 600 nm for SDH, 15,300 l·mol–1·cm–1 for reduced cytochrome c at 550 nm for COX, and 63,000 l·mol–1·cm–1 for nicotinamide-adenine dinucleotide (NADH) at 340 nm for HAD. Enzyme capacities were expressed as micromoles per minute per gram wet weight. The compositions of the assay solutions were as follows.

1) CS.   For reagent 1, 1.21 g Tris (100 mM), 4 mg DTNB (100 µM), and 4.2 mg acetyl CoA (50 µM) were dissolved in 80 ml distilled water, pH was adjusted to 8.0, and distilled water was added to a total volume of 100 ml. For reagent 2 (starting reagent), 3.3 mg oxaloacetate was dissolved in 1 ml distilled water.

2) SDH.   For NaPi 50 mM buffer, 0.890 g Na2HPO4·2H2O (50 mM) (A) and 0.780 g NaH2PO4·2H2O (50 mM) (B) were both dissolved in 100 ml distilled water. Subsequently, B was added to A until the pH was 7.4. For reaction reagent, 6.5 mg KCN (1 mM), 1.7 mg 2,6-DCPIP (0.06 mM), 162 mg sodium succinate (10 mM), and 50 mg albumin were dissolved in 100 ml KPi buffer.

3) COX.   For KPi 50 mM buffer, 0.684 g KH2PO4 (50 mM) and 1.14 g K2HPO4 (50 mM) were both dissolved in 100 ml distilled water. Subsequently, both solutions were mixed, and pH was adjusted to 7.4 using KOH. For reduced cytochrome c solution, 17.6 mg ascorbic acid was added to 10 ml KPi 50 mM buffer, and pH was adjusted to 7.4 using NaOH (1 M). One-hundred microliters of this ascorbic acid solution and 25 mg cytochrome c were mixed. This mixture was incubated at 25°C for 5 min before 900 µl KPi 50 mM buffer was added. This solution was kept on ice until analyzed. For MgCl2 solution, 566 mg MgCl2 was dissolved in 10 ml distilled water (final volume). For reaction reagent, 10 ml KPi 50 mM buffer, 200 µl MgCl2 solution, and 400 µl reduced cytochrome c solution were mixed. Fifty microliters supernatant was mixed with 200 µl KPi 50 mM buffer, which was kept on ice for 10 min before analysis.

4) HAD.   For buffer, 3.3 g tetrasodiumpyrophosphate (100 mM) was dissolved in 80 ml distilled water, pH was adjusted to 7.3, and distilled water was added to a total volume of 100 ml. For NADH solution, 8.0 mg NADH was dissolved in 1 ml distilled water. For reagent 1, 10 ml buffer and 200 µl NADH solution were mixed. For reagent 2 (starting reagent), 5.0 mg acetoacetyl-CoA was dissolved in 2.5 ml distilled water.

All analyses for a given enzyme were performed simultaneously at 37°C. Enzyme capacities were measured twice on the same homogenate for each subject. Intra-assay coefficients of variation were 2.0% for CS, 2.1% for SDH, 5.0% for COX and 1.7% for HAD, indicating that the capacity of mitochondrial enzymes was reproducibly determined.

Body Composition

Body mass and height were measured in the morning after an overnight fast (ID 1 Plus, Mettler Toledo, Giessen, Germany; Mod. 220, SECA, Hamburg, Germany). Body volume was determined using the underwater weighing technique while correcting for residual lung volume using the helium dilution technique (Volugraph VG 2000; Mijnhardt, Bunnik, The Netherlands). Total body water was determined overnight using the deuterium dilution technique (34). Percent body fat was subsequently calculated using Siri's three-compartment model (27).

Statistics

Differences in PADL, the capacity of mitochondrial enzymes, and body composition between men and women were tested using Student's t-tests for unpaired samples. Simple linear regression was used to test the association between CS, SDH, COX, and HAD on the one hand and PADL on the other hand. Multiple linear regression analyses were used to test the interaction between sex and PADL for the capacity of the mitochondrial enzymes. Backward multiple linear regression analyses were used to correct the associations between the capacity of mitochondrial enzymes and PADL for sex, age, and body mass index (BMI). On log transformation, the association between PADL and the capacity of the mitochondrial enzymes with %Low, %Moderate, and %High was determined using simple linear regression analyses.

Statistical analyses were carried out using the Statistical Package for Social Sciences (SPSS) version 11 for Macintosh OS X (SPSS; Chicago, IL). Data are expressed as means ± SD. P values <0.05 were considered statistically significant; 95% confidence intervals (95% CI) are provided.


   RESULTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
PADL was similar between men and women (Table 1). The proportion of time subjects were physically active at a low, moderate, and high intensity was also comparable between sexes, although %High was significantly higher in men: 18 min/day vs. 9 min/day in women (P < 0.01, 95% CI: 2.4 to 14.3). No significant differences between men and women were found for CS, SDH, COX, or HAD, which confirms the findings of previous studies (14, 26, 29). Furthermore, no interaction was observed between sex and PADL for the capacity of the mitochondrial enzymes. Hence, both sexes were combined for further analyses.


View this table:
[in this window]
[in a new window]

  		Table 1. Results

 
Capacity of Mitochondrial Enzymes and Physical Activity in Daily Life

Applying the regression equation developed by Plasqui et al. (23) to the present population showed that the physical activity level, PAL, ranged from 1.62 to 2.04. Positive associations were observed between CS, SDH, and COX with PADL (P < 0.05, R = 0.36, 95% CI: 1.3·10–4 to 2.2·10–3; P < 0.05, R = 0.39, 95% CI: 1.1·10–5 to 9.9·10–5; and P < 0.05, R = 0.33, 95% CI: 7.5·10–6 to 3.6·10–4, respectively). HAD tended to correlate positively with PADL (P = 0.06, R = 0.31, 95% CI: –2.2·10–5 to 1.1·10–3) (Fig. 1). These associations remained when sex, age, and/or BMI were taken into account.


Figure 1
View larger version (21K):
[in this window]
[in a new window]

  		Fig. 1. Mitochondrial capacity as a function of habitual physical activity in daily life. Capacity of citrate synthase (CS; A), succinate dehydrogenase (SDH; B), cytochrome c oxidase (COX; C), and β-hydroxyacyl-CoA dehydrogenase (HAD; D) as a function of habitual physical activity in daily life (PADL), measured using a triaxial accelerometer for movement registration, for men and women combined, is shown. A, B, and C: P < 0.05. D: P = 0.06. Mcnts, megacounts.

 
PADL was positively associated with %Moderate and %High (P < 0.001, R = 0.74, 95% CI: 3.3·10–1 to 6.3·10–1; and P < 0.001, R = 0.74, 95% CI: 1.4·10–1 to 2.6·10–1, respectively) and negatively with %Low (P < 0.001, R = 0.86, 95% CI: –20.4 to –13.7). CS and HAD tended to correlate positively with %High (P = 0.06, R = 0.31, 95% CI: –4.5·10–3 to 2.6·10–1; and P = 0.07, R = 0.30, 95% CI: –1.0·10–2 to 2.5·10–1, respectively). COX and SDH on the other hand correlated positively with %Moderate (P < 0.05, R = 0.37, 95% CI: 1.1·10–1 to 1.3; and P < 0.05, R = 0.37, 95% CI: 2.6·10–2 to 3.3·10–1, respectively). To examine if the associations between markers for mitochondrial capacity and PADL were influenced by the intensity of the activities performed, the population was subsequently stratified based on the intensity of the activities measured.

Capacity of Mitochondrial Enzymes and Physical Activity in Daily Life Stratified Based on the Intensity of Physical Activity

Stratification of the population based on the median of %High resulted in a cut-off point of 8 min/day. Within the population stratified based on %High, CS was only associated with PADL in the subgroup spending more than 8 min/day on high-intensity physical activity (P < 0.05, 95% CI: 7.5·10–5 to 2.9·10–3). SDH also correlated positively with PADL in the subgroup spending more than 8 min/day on high-intensity physical activity but tended to correlate positively with PADL in the subgroup spending less time on high-intensity physical activity as well (P < 0.01, 95% CI: 2.4·10–5 to 1.2·10–4; and P = 0.07, 95% CI: –1.1·10–5 to 2.1·10–4, respectively). COX tended to correlate positively with PADL in both the subgroup spending more and less than 8 min/day on high-intensity physical activity (P = 0.06, 95% CI: –1.3·10–5 to 4.5·10–4; and P = 0.09, 95% CI: –7.2·10–5 to 7.7·10–4, respectively), and HAD was not associated with PADL in either the subgroup spending more or less time on high-intensity physical activity (Fig. 2).


Figure 2
View larger version (19K):
[in this window]
[in a new window]

  		Fig. 2. Capacity of CS (A and B), SDH (C and D), COX (E and F), and HAD (G and H) as a function of PADL, measured using a triaxial accelerometer for movement registration, stratified based on the proportion of time subjects were physically active at a high intensity. A, C, E, and G show the association for subjects who spent 2–8 min/day on high-intensity physical activity, and B, D, F, and H for subjects who spent 9–34 min/day on high-intensity physical activity. B: P < 0.05. C: P = 0.07. D: P < 0.01. E: P = 0.09. F: P = 0.06.

 
Stratification of the population based on the median of %Moderate resulted in a cut-off point of 29 min/day. Within the population stratified based on %Moderate, no associations were observed between markers for mitochondrial capacity and PADL in either the subgroup spending more or less time on moderate-intensity physical activity.

Stratification of the population based on the median of %Moderate and %High combined resulted in a cut-off point of 39 min/day. Within the population stratified based on the proportion of moderate- and high-intensity physical activity, CS and HAD were only positively associated with PADL in the subgroup spending more time on moderate- and high-intensity physical activity (P < 0.05, 95% CI: 1.9·10–4 to 4.1·10–3; and P < 0.01, 95% CI: 5.7·10–4 to 2.6·10–3, respectively). SDH and COX were positively associated with PADL in both the subgroup spending more and less time on moderate- and high-intensity physical activity (P < 0.01, 95% CI: 3.8·10–5 to 1.7·10–4 and P < 0.05, 95% CI: 1.1·10–5 to 2.4·10–4 for SDH; P < 0.05, 95% CI: 2.2·10–5 to 6.0·10–4 and P < 0.05, 95% CI: 8.4·10–5 to 9.6·10–4 for COX) (Fig. 3).


Figure 3
View larger version (19K):
[in this window]
[in a new window]

  		Fig. 3. Capacity of CS (A and B), SDH (C and D), COX (E and F), and HAD (G and H) as a function of PADL, measured using a triaxial accelerometer for movement registration, stratified based on the proportion of time subjects were physically active at a moderate and high intensity. A, C, E, and G show the association for subjects who spent 18–39 min/day on moderate- and high-intensity physical activity, and B, D, F, and H for subjects who spent 39–72 min/day on moderate- and high-intensity physical activity. B, C, E, and F: P < 0.05. D and H: P < 0.01.

 

   DISCUSSION
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
We are the first to show that within the range of normal daily life activities, mitochondrial capacity measured as the capacity of CS, SDH, and COX correlated positively with PADL, and HAD capacity tended (P = 0.06) to correlate positively with PADL. These associations were independent of sex, age, and BMI.

PAL can vary from 1.2 to 2.5 in sustainable lifestyles with 1.2 observed in bed-bound subjects that are still eating and 2.5 being defined as a highly physically active lifestyle (4). In extreme situations, such as the Tour the France cycling competition, PAL has been shown to increase up to 5 (33). The range in PAL obtained in the present study was 1.6 to 2.0, so lower than the 2.5 observed for highly physically active lifestyles. A PAL of 1.6 is regarded to reflect a sedentary lifestyle (4), and a PAL of 2.1 represents a physically active lifestyle (31). Thus our subjects covered the range of normal daily life activity levels as reflected in PAL but were not highly physically active.

The normal range of daily life activities in the present population is confirmed by the proportion of time that subjects on average spent on moderate- and high-intensity physical activity, i.e., 30 and 11 min, respectively. These proportions are close to those recently reported in other studies that used accelerometry in healthy young adults (7, 35). McClain et al. (20), on the other hand, recruited regular endurance runners and although %Moderate was similar in their study (27 min/day), %High was more pronounced (48 min/day) compared with the present population. This suggests that although physically active subjects were evidently recruited in the present study, the proportion of high-intensity physical activity was much lower than previously observed for people actively engaged in endurance sports.

PADL correlated positively with %Moderate and with %High. Furthermore, positive associations were observed between markers for mitochondrial capacity and both %Moderate and %High. This suggests that the intensity of the activities performed may have affected the association between our markers for mitochondrial capacity and PADL. Indeed, stratification of the population based on the intensity of the activities performed made the association between markers for mitochondrial capacity and PADL more prominent. Evidently, as a classic marker for mitochondrial density, CS was only associated with PADL in the subgroup spending more than 8 min/day on high-intensity physical activity. Importantly, this suggests that although CS was associated with PADL in the entire population, there may be a lower limit for the time spent on high-intensity physical activity that should be met for the association to become apparent. Since PADL and %High were both significantly higher in the subgroup spending more time on high-intensity physical activity (data not shown), the association found could theoretically also result from an increased PADL. However, stratification of the population based on %Moderate did not reveal an association between CS or any other marker for mitochondrial capacity and PADL in either the subgroup spending more or less than 29 min/day on moderate-intensity physical activity. Therefore, we conclude that high-intensity physical activity may be a prerequisite for a positive association between CS and PADL.

Within the population stratified based on the median of the time spent on moderate- and high-intensity physical activity combined, HAD showed a positive association with PADL in subjects spending more but not in subjects spending less than 39 min/day on moderate- and high-intensity physical activity. On first thought, this seems inconsistent since HAD was not associated with PADL within the population stratified based on %Moderate or %High separately. However, the proportion of moderate- and high-intensity physical activity combined is by definition the inverse of the proportion of low-intensity physical activity. In other words, the association observed between HAD and PADL in subjects spending more than 39 min/day on moderate- and high-intensity physical activity probably results from a decreased time spent on low-intensity physical activity. This implies that the capacity to oxidize fatty acids is positively associated with habitual physical activity in daily life if the latter is accompanied by a decreased time spent on low-intensity physical activity.

For SDH and COX, a positive association with PADL was found both in subjects spending more and less than 39 min on moderate- and high-intensity physical activity per day. Comparable results were obtained within the population stratified based on %High, suggesting that SDH and COX are associated with habitual physical activity in daily life irrespective of the intensity of the activities performed.

In general, it can be concluded that a sedentary lifestyle does not result in positive associations with mitochondrial capacity, whereas an active lifestyle does. The intensity of the activities performed influences the association with PADL differently for different markers of mitochondrial capacity; it does not appear to affect the association between SDH and COX with PADL, whereas a limited time spent on low-intensity physical activity appears to be a prerequisite for a positive association between HAD and PADL. CS on the other hand only correlated positively with PADL in subjects spending more time on high-intensity physical activity. Interestingly though, spending more than 8 min/day on high-intensity physical activity already resulted in a positive association between CS and PADL in healthy young subjects. Whether the positive association between mitochondrial capacity and habitual physical activity in daily life persists in populations at risk for developing Type 2 diabetes and obesity remains to be established. More importantly, it should be examined if spending more than 8 min/day on high-intensity physical activity accompanied by a high level of habitual physical activity in daily life suffices to maintain or improve proper mitochondrial capacity in populations at risk for developing Type 2 diabetes and obesity. It should be stressed that even if this association holds in populations at risk, no extrapolations to prevention of Type 2 diabetes and obesity can be made. In fact, based on previous studies, 8 min of high-intensity physical activity per day is unlikely to be sufficient to delay the development of Type 2 diabetes and obesity (6, 19).

In conclusion, evidence was found for a positive association between CS, SDH, and COX with PADL and a trend toward a positive association between HAD and PADL irrespective of sex, age, and BMI. With CS and SDH as classic markers for mitochondrial density, mitochondrial capacity was found to be positively associated with PADL. Thus, in our population of healthy young adults, an active lifestyle within the range of normal daily life activities is associated with a higher mitochondrial capacity than a sedentary lifestyle and may help to maintain or improve mitochondrial capacity.


   GRANTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
ACKNOWLEDGMENTS
 REFERENCES
 
This study was funded by Maastricht University.


   ACKNOWLEDGMENTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
REFERENCES
 
We thank Milou Beelen, Luc van Loon, and René Koopman for their skillful way of obtaining the muscle biopsies. We also thank Loek Wouters for analyzing the deuterium samples.


   FOOTNOTES
 

Address for reprint requests and other correspondence: M. den Hoed, P.O. Box 616, 6200 MD Maastricht, The Netherlands (e-mail: m.denhoed{at}hb.unimaas.nl)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   REFERENCES
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 

  1. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, O'Brien WL, Bassett DR Jr, Schmitz KH, Emplaincourt PO, Jacobs DR Jr, Leon AS. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 32: S498–S504, 2000.[Web of Science][Medline]
  2. Befroy DE, Petersen KF, Dufour S, Mason GF, de Graaf RA, Rothman DL, Shulman GI. Impaired mitochondrial substrate oxidation in muscle of insulin-resistant offspring of type 2 diabetic patients. Diabetes 56: 1376–1381, 2007.[CrossRef][Web of Science][Medline]
  3. Bergstrom J. Percutaneous needle biopsy of skeletal muscle in physiological and clinical research. Scand J Clin Lab Invest 35: 609–616, 1975.[Medline]
  4. Black AE, Coward WA, Cole TJ, Prentice AM. Human energy expenditure in affluent societies: an analysis of 574 doubly-labelled water measurements. Eur J Clin Nutr 50: 72–92, 1996.[Web of Science][Medline]
  5. Bouten CV, Verboeket-van de Venne WP, Westerterp KR, Verduin M, Janssen JD. Daily physical activity assessment: comparison between movement registration and doubly labeled water. J Appl Physiol 81: 1019–1026, 1996.[Abstract/Free Full Text]
  6. Brooks GA, Butte NF, Rand WM, Flatt JP, Caballero B. Chronicle of the Institute of Medicine physical activity recommendation: how a physical activity recommendation came to be among dietary recommendations. Am J Clin Nutr 79: 921S–930S, 2004.[Abstract/Free Full Text]
  7. Dinger MK, Behrens TK. Accelerometer-determined physical activity of free-living college students. Med Sci Sports Exerc 38: 774–779, 2006.[CrossRef][Web of Science][Medline]
  8. Faxen K, Gilderson G, Adelroth P, Brzezinski P. A mechanistic principle for proton pumping by cytochrome c oxidase. Nature 437: 286–289, 2005.[CrossRef][Web of Science][Medline]
  9. Gollnick PD, Armstrong RB, Saltin B, Saubert CW 4th, Sembrowich WL, Shepherd RE. Effect of training on enzyme activity and fiber composition of human skeletal muscle. J Appl Physiol 34: 107–111, 1973.[Free Full Text]
  10. Gollnick PD, Armstrong RB, Saubert CW 4th, Piehl K, Saltin B. Enzyme activity and fiber composition in skeletal muscle of untrained and trained men. J Appl Physiol 33: 312–319, 1972.[Free Full Text]
  11. Gosker HR, Hesselink MK, Duimel H, Ward KA, Schols AM. Reduced mitochondrial density in the vastus lateralis muscle of patients with COPD. Eur Respir J 2007.
  12. Hansen AK, Fischer CP, Plomgaard P, Andersen JL, Saltin B, Pedersen BK. Skeletal muscle adaptation: training twice every second day vs. training once daily. J Appl Physiol 98: 93–99, 2005.[Abstract/Free Full Text]
  13. Hu G, Qiao Q, Silventoinen K, Eriksson JG, Jousilahti P, Lindstrom J, Valle TT, Nissinen A, Tuomilehto J. Occupational, commuting, and leisure-time physical activity in relation to risk for Type 2 diabetes in middle-aged Finnish men and women. Diabetologia 46: 322–329, 2003.[Web of Science][Medline]
  14. Jaworowski A, Porter MM, Holmback AM, Downham D, Lexell J. Enzyme activities in the tibialis anterior muscle of young moderately active men and women: relationship with body composition, muscle cross-sectional area and fibre type composition. Acta Physiol Scand 176: 215–225, 2002.[CrossRef][Web of Science][Medline]
  15. Jebb SA, Moore MS. Contribution of a sedentary lifestyle and inactivity to the etiology of overweight and obesity: current evidence and research issues. Med Sci Sports Exerc 31: S534–541, 1999.[Web of Science][Medline]
  16. Kelley DE, He J, Menshikova EV, Ritov VB. Dysfunction of mitochondria in human skeletal muscle in type 2 diabetes. Diabetes 51: 2944–2950, 2002.[Abstract/Free Full Text]
  17. Kriska AM, Saremi A, Hanson RL, Bennett PH, Kobes S, Williams DE, Knowler WC. Physical activity, obesity, and the incidence of type 2 diabetes in a high-risk population. Am J Epidemiol 158: 669–675, 2003.[Abstract/Free Full Text]
  18. Kuczmarski RJ, Flegal KM, Campbell SM, Johnson CL. Increasing prevalence of overweight among US adults. The National Health and Nutrition Examination Surveys, 1960 to 1991. JAMA 272: 205–211, 1994.[Abstract/Free Full Text]
  19. Laaksonen DE, Lindstrom J, Lakka TA, Eriksson JG, Niskanen L, Wikstrom K, Aunola S, Keinanen-Kiukaanniemi S, Laakso M, Valle TT, Ilanne-Parikka P, Louheranta A, Hamalainen H, Rastas M, Salminen V, Cepaitis Z, Hakumaki M, Kaikkonen H, Harkonen P, Sundvall J, Tuomilehto J, Uusitupa M. Physical activity in the prevention of type 2 diabetes: the Finnish diabetes prevention study. Diabetes 54: 158–165, 2005.[Abstract/Free Full Text]
  20. McClain JJ, Sisson SB, Tudor-Locke C. Actigraph accelerometer interinstrument reliability during free-living in adults. Med Sci Sports Exerc 39: 1509–1514, 2007.[CrossRef][Web of Science][Medline]
  21. Menshikova EV, Ritov VB, Ferrell RE, Azuma K, Goodpaster BH, Kelley DE. Characteristics of skeletal muscle mitochondrial biogenesis induced by moderate-intensity exercise and weight loss in obesity. J Appl Physiol 103: 21–27, 2007.[Abstract/Free Full Text]
  22. Mogensen M, Sahlin K, Fernstrom M, Glintborg D, Vind BF, Beck-Nielsen H, Hojlund K. Mitochondrial respiration is decreased in skeletal muscle of patients with type 2 diabetes. Diabetes 56: 1592–1599, 2007.[CrossRef][Web of Science][Medline]
  23. Plasqui G, Joosen AM, Kester AD, Goris AH, Westerterp KR. Measuring free-living energy expenditure and physical activity with triaxial accelerometry. Obes Res 13: 1363–1369, 2005.[Web of Science][Medline]
  24. Santoro C, Cosmas A, Forman D, Morghan A, Bairos L, Levesque S, Roubenoff R, Hennessey J, Lamont L, Manfredi T. Exercise training alters skeletal muscle mitochondrial morphometry in heart failure patients. J Cardiovasc Risk 9: 377–381, 2002.[CrossRef][Web of Science][Medline]
  25. Seidell JC. Dietary fat and obesity: an epidemiologic perspective. Am J Clin Nutr 67: 546S–550S, 1998.[Abstract]
  26. Simoneau JA, Bouchard C. Human variation in skeletal muscle fiber-type proportion and enzyme activities. Am J Physiol Endocrinol Metab 257: E567–E572, 1989.[Abstract/Free Full Text]
  27. Siri WE. Body composition from fluid spaces and density: analysis of methods. 1961. Nutrition 9: 480–491; discussion 480, 492, 1993.[Web of Science][Medline]
  28. Stryer L. Biochemistry. New York: Freeman, 1999.
  29. Tarnopolsky MA, Rennie CD, Robertshaw HA, Fedak-Tarnopolsky SN, Devries MC, Hamadeh MJ. Influence of endurance exercise training and sex on intramyocellular lipid and mitochondrial ultrastructure, substrate use, and mitochondrial enzyme activity. Am J Physiol Regul Integr Comp Physiol 292: R1271–R1278, 2007.[Abstract/Free Full Text]
  30. Toledo FG, Menshikova EV, Ritov VB, Azuma K, Radikova Z, DeLany J, Kelley DE. Effects of physical activity and weight loss on skeletal muscle mitochondria and relationship with glucose control in type 2 diabetes. Diabetes 56: 2142–2147, 2007.[CrossRef][Web of Science][Medline]
  31. Westerterp KR. Pattern and intensity of physical activity. Nature 410: 539, 2001.
  32. Westerterp KR, Meijer GA, Janssen EM, Saris WH, Ten Hoor F. Long-term effect of physical activity on energy balance and body composition. Br J Nutr 68: 21–30, 1992.[CrossRef][Web of Science][Medline]
  33. Westerterp KR, Saris WH, van Es M, ten Hoor F. Use of the doubly labeled water technique in humans during heavy sustained exercise. J Appl Physiol 61: 2162–2167, 1986.[Abstract/Free Full Text]
  34. Westerterp KR, Wouters L, van Marken Lichtenbelt WD. The Maastricht protocol for the measurement of body composition and energy expenditure with labeled water. Obes Res 3, Suppl 1: 49–57, 1995.[Web of Science][Medline]
  35. Yoshioka M, Ayabe M, Yahiro T, Higuchi H, Higaki Y, St-Amand J, Miyazaki H, Yoshitake Y, Shindo M, Tanaka H. Long-period accelerometer monitoring shows the role of physical activity in overweight and obesity. Int J Obes (Lond) 29: 502–508, 2005.[Medline]



This article has been cited by other articles:


Home page
 J. Appl. Physiol.Home page
R. G. Larsen, D. M. Callahan, S. A. Foulis, and J. A. Kent-Braun
In vivo oxidative capacity varies with muscle and training status in young adults
J Appl Physiol, September 1, 2009; 107(3): 873 - 879.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF) Free
Right arrow All Versions of this Article:
105/2/561    most recent
00091.2008v1
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Web of Science (1)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by den Hoed, M.
Right arrow Articles by Westerterp, K. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by den Hoed, M.
Right arrow Articles by Westerterp, K. R.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Visit Other APS Journals Online
Copyright © 2008 by the American Physiological Society.