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From the Clinical Research Centers |
Divisions of Clinical Pharmacology and Metabolic Research (M.B., R.D.S., E.T.P.) and Cardiology (M.B., P.A.A.), Department of Medicine, University of Vermont College of Medicine, Burlington, Vermont 05405
Address all correspondence and requests for reprints to: Eric T. Poehlman, Ph.D., Given Building, B-247, Department of Medicine, University of Vermont, Burlington, Vermont 05405. E-mail: epoehlma{at}zoo.uvm.edu
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Abstract |
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One hundred and eighty healthy older patients (96 females and 84 males) between 45–90 yr of age were studied. Total energy expenditure was measured from doubly labeled water. PAEE was calculated as the difference between total energy expenditure, resting metabolic rate, and estimated thermic effect of a meal. Peak VO2 was assessed from an exercise test to volitional fatigue. Fat mass and fat-free mass were assessed from dual energy x-ray absorptiometry.
After correction for age, fat mass, and fat-free mass, significant correlations were observed between peak VO2 and PAEE for older males (r = 0.42; P < 0.0001) and females (r = 0.24; P < 0.05), although significant variation among volunteers was noted. When subjects were subdivided by tertiles based on their peak VO2 (liters per min), males with the highest peak VO2 showed greater free-living PAEE than individuals with low peak VO2 (P < 0.01). Similar results were observed in females (P < 0.05).
Our results suggest a positive association between higher levels of peak VO2 and greater free-living PAEE in older individuals. This relationship is stronger in older men than in women. These additional energy-dissipating properties during their free-living time may serve to preserve leanness and buffer fat gain with age.
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Introduction |
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There exists considerable controversy regarding factors regulating free-living PAEE. We would suggest, however, that this component is under regulatory control. That is, individuals increase free-living nonvolitional activity during periods of caloric surplus in an attempt to offset weight gain (5) and decrease this component during intense exercise training to preserve energy (8). These results raise interesting and provocative questions regarding the impact of this component in the regulation of energy balance.
Recently, the level of maximal aerobic fitness (VO2 max) as been suggested as a potential modulator of free-living PAEE (2, 9). Intuitively, one may hypothesize that individuals with a high VO2 max may be more physically active in their free-living nonexercise time. Contrary to these expectations, there exists divergent results in the literature regarding the association between VO2 max and PAEE (1, 2, 9, 10). Some studies have reported a positive relationship between these variables (11, 12), whereas others have found no association (1, 13, 14, 15). In the only intervention study performed in the elderly, we found that an increase in VO2 max was associated with a compensatory decrease in PAEE after endurance training in older individuals (8). It should be noted, however, that small sample sizes (a frequent problem in expensive, DLW studies), age-related differences in the cohorts, and different experimental designs preclude firm conclusions. Because there exists considerable interest regarding factors that may influence PAEE, particularly in older individuals (1, 2, 7, 8, 9, 10, 16), elucidation of variables modulating PAEE have important public health implications for the aging population.
To this end, we examined the relationship between maximal aerobic capacity and PAEE using direct assessments of peak VO2 (maximal exercise tests) and PAEE (DLW) in the largest sample size using a doubly labeled study published to date.
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Subjects and Methods |
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The study population consisted of 180 healthy patients (females, 63 Caucasians and 33 African-Americans; males, 61 Caucasians and 23 African-Americans) between 45–90 yr old. The subjects were part of 2 cohorts recruited by solicitation through the media between 1988 and 1995. A subsample of this population has previously been studied (17, 18). Participants were sedentary (<2 periods a week of exercise participation), nonsmokers, and moderate alcohol consumers. All participants were apparently healthy and had no history on physical examination of 1) coronary heart disease (e.g. S-T segment depression >1 mm at rest or exercise), 2) hypertension (resting blood pressure >140/90 mm Hg), 3) medications that could affect cardiovascular function or metabolism, 4) diabetes, 5) body weight fluctuation of >2 kg in the past year, 6) exercise-limiting noncardiac disease (arthritis, peripheral vascular disease, or cerebral vascular disease), or 7) hormone replacement therapy. All participants were asked to sign an informed consent document. This study was approved by the medical sciences committee on human research at the University of Vermont.
Measures of energy expenditure
Total daily energy expenditure (TEE). TEE was determined using the DLW technique over a 10-day period. During that period, subjects were asking to maintain their normal daily physical activity routines. These individuals, however, were not participating in structured exercise training program. Specific details about the DLW are provided below and have been described extensively previously (17, 18).
Resting metabolic rate (RMR). RMR was determined from 45 min of indirect calorimetry on an in-patient basis. RMR was measured by indirect calorimetry using the ventilated hood technique (19) after an overnight 12-h fast in the General Clinical Research Center. Respiratory gas analysis was performed using a Deltatrac metabolic cart (Sensormedics, Yorba Linda, CA). The RMR (kilocalories per day) was calculated from the equation of Weir (20). The test-retest correlation coefficient within 1 week has been shown to be 0.90 for RMR in our laboratory.
Daily PAEE. DLW in conjunction with indirect calorimetry was used to measure PAEE. PAEE was calculated as the difference among TEE, RMR, and the thermic effect of a meal using the equation: PAEE (Cal/day) = [TEE (Cal/day) x 0.9] - RMR (Cal/day) as previously described (17, 18). This approach assumes that the thermic effect of feeding is 10% of the TEE in the elderly (21).
Leisure time activity (LTA). LTA was measured by the Minnesota LTA questionnaire (22). This is a commonly used, interviewer-administered questionnaire that assesses daily physical activity accumulated during leisure and household activities over the past 12 months. Trained personnel administered the questionnaire during a 20-min interview. Leisure time physical activity was calculated based on the number of months spent completing the specific activity per yr, the average number of times for the specific activity each month, the total time of each physical activity session, and the activity specific intensity code. The test-retest correlation coefficient over a month has been shown to be 0.92 in older women and men (23). Average PAEE (kilocalories per day) for the 12-month period was used for data analyses.
Nonvolitional activity. In addition, we estimated the energy cost of nonvolitional activity (i.e. fidgeting), by using the following equation: nonvolitional activity = PAEE (Cal/day) - volitional activity (LTA, Cal/day). This approach assumed that all activities quantified by the LTA questionnaire are volitional in nature.
Specific details about the DLW. Between 1200–1600 h, a premixed dose containing 0.078 g 2H2O and 0.092 g H218O/kg body mass was orally consumed by each subject to measure TEE over a 10-day period using the method of Schoeller and van Santen (24). One urine sample was collected before treatment, two the following morning, and two samples 10 days later. Samples were frozen at -20 C in vacutainer tubes until later analysis for 2H and 18O enrichment by isotope ratio mass spectrometry. 18O isotopic enrichment was determined from the carbon dioxide (CO2) equilibration techniques, and 2H enrichment was determined by the zinc catalyst method reported by Wong et al. (25). The rate of CO2 production (rCO2; moles per day) was calculated using Eq 3 from the report by Speakman et al. (26): rCO2 = N/2.196 x (cOkO - cHkH), where kO and kH are the elimination rates of 18O and 2H tracers from the body, and cO and cH are the dilution spaces for 18O and 2H tracers as recommended by Racette et al. (27). Assuming an RQ of the food consumed of 0.85 (28), total CO2 production was converted to TEE (kilocalories per day) using the Weir formula (20).
Dual energy x-ray absorptiometry
Determination of fat mass, fat-free mass, and percentage of body fat were assessed using dual energy x-ray absorptiometry (model DPX-L, Lunar Corp., Madison, WI) as previously described (17, 18). The subjects were asked to wear only a standard hospital gown during the scan procedure and to maintain a supine position.
Peak aerobic capacity (peak VO2)
Subjects performed a graded exercise test on a treadmill to voluntary exhaustion to measure peak VO2 as previously described (19). Standard 12-lead electrocardiograms were performed at the end of each 2-min stage. Peak VO2 (liters per min) was considered to be the highest value obtained during the test. Expired gas was analyzed during the exercise protocol using a Sensormedics Horizon metabolic cart (Yorba Linda, CA). Data collection included oxygen consumption (VO2) and respiratory equivalent ratio (CO2 production/O2 consumption).
Statistical analyses
Data are presented as the mean ± SD. Unpaired
t tests examined potential differences between males and
females. Because age, fat-free mass, and fat mass influence PAEE and
peak VO2 (29, 30), PAEE and peak VO2 were
adjusted using analysis of covariance. Partial correlations were used
to determine the relationship between dependent and independent
variables. We also examined the relationship between peak
VO2 and PAEE (adjusted for age, fat mass, and fat-free
mass) using a tertile approach. Subjects were divided on the basis of
low (tertile 1), medium (tertile 2), and high (tertile 3) values. ANOVA
was used for the comparison among groups. When this procedure revealed
a significant group effect, the Tukey-Kramer highest significant
difference test was used for a
posteriori comparisons among the three groups. Because of a
similar distribution (by 
2 analysis) of
African-Americans in males (29%) and females (35%) cohorts, data were
pooled. Moreover, no race difference in the relationship between
Caucasians and African-Americans was noted between PAEE and peak
VO2 (Caucasians: r = 0.26; P < 0.005;
African-Americans: r = 0.37, P < 0.005) using a
general linear model procedure. A level of significance of
P < 0.05 was used for hypotheses testing. All
statistical analyses were carried out using Jump 3.1 (1989–1994;
SAS Institute, Inc., Cary, NC) statistical software
program.
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Results |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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. Older females and males were of
similar age and body mass index. Females had greater absolute and
relative amounts of fat mass (P < 0.0001), whereas
males displayed higher values for body weight and fat free mass
(P < 0.0001). Males had a higher absolute (liters per
min) and relative (milliliters per kg/min) peak VO2. TEE,
RMR, daily PAEE, LTA, and estimated nonvolitional activity were higher
in males than in females (P < 0.005).
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). We
were also interested in the relationship between peak VO2
and nonvolitional physical activity (PAEE - LTA). We observed a
low, but significant, association between peak VO2 and
nonvolitional activity in both males (r = 0.25;P < 0.05) and females (r = 0.25; P <
0.05) after correction for age, fat-free mass, and fat mass (results
not shown in figures). No statistical differences in slopes between men
and women were observed (results not shown).
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).
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Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Our results support a moderate linear relationship among peak
VO2, free-living physical activity, and estimated
nonvolitional activity after controlling for the potential confounders
of age, fat-free mass, and fat mass. We also examined our data using a
tertile approach. This analysis addresses whether there is a threshold
of peak VO2 that may influence PAEE in older men and women.
We found that a difference in peak VO2 of 1.4 L/min in men
and 0.7 L/min in women is needed to observe a significant difference in
PAEE between individuals with high vs. low peak
VO2. Based on the regression equation proposed in Fig. 1
, a
20% increase in peak VO2 (an increase frequently observed
in exercise training programs) would be associated with increases of
54, 67, and 88 Cal/day for females in tertiles 1, 2, and 3,
respectively. In males, a similar improvement in peak VO2
would correspond to increases of 85, 116, and 162 Cal/day for
individuals in tertiles 1, 2, and 3, respectively. These results may
suggest a stronger association between PAEE and peak VO2 in
men than in women. Although cross-sectional results cannot always be
extrapolated to prospective studies, this finding supports a sexual
dimorphism in this relationship, as previously suggested (31, 32).
Gender differences in the energetic adaptation to exercise,
particularly in the physical activity component, may partially explain
the resistance of women to lose body fat in response to chronic
exercise challenges (10, 13, 16, 31).
It is important to highlight the statistical approach used to arrive at our conclusions. We used a regression-based approach to remove the confounding influences of age, fat mass, and fat-free mass on peak VO2 and PAEE, rather than expressing the dependent variables as ratios (i.e. peak VO2, expressed as milliliters per kg/min). Both peak VO2 and PAEE are influenced by age and body composition (9, 10, 16). Moreover, we have shown that the more traditional ratio approach provides spurious conclusions when comparing individuals of varying body size and composition (29, 30).
Previous investigators have relied on less accurate measures, such as structured interviews, interviews, and mechanical devices to measure PAEE in free-living individuals (3, 4, 23). Recent reports suggest that these instruments do not accurately predict individual levels of physical activity and underestimate mean group levels by 40–50% compared to the criterion method of DLW (7). DLW, on the other hand, provides an unbiased and unobtrusive assessment of physical activity in free-living persons over an extended period of time (9). Unfortunately, its high cost and complex analyses have limited its widespread application, and thus, sample sizes have generally been small. This issue is problematic because of the high inter- and intraindividual variations associated with physical activity in free-living older individuals (1, 2, 7, 33).
We attempted to overcome several of these obstacles by measuring PAEE using DLW in a relatively large sample size of middle-aged and older individuals. In addition, we directly assessed peak VO2 and body composition. We were particularly interested in the relationship between peak VO2 (a biological attribute) and physical activity (a behavioral characteristic) because of discrepancies in previous studies (1, 8, 11, 12, 13, 14, 15). For example, in studies that used DLW, some investigators found no relationship between aerobic fitness and PAEE during free-living activities (1, 13), whereas others found a positive relationship between these variables (11, 12). Others have examined differences in physical activity between trained and untrained individuals in a room calorimeter and found no association between PAEE and peak VO2 (14, 15). Other studies examined the effects of strength training on PAEE, but found no significant changes in PAEE despite increases in fat-free mass (34, 35).
In the only intervention study performed in the elderly, we found that older individuals decreased their PAEE despite an increase of about 10% in peak VO2 after a 2-month training program (8). It is likely that the high intensity exercise program (75–80% of peak VO2) fatigued individuals who may not have adapted to the relatively short exercise training. On the other hand, the positive relationship between peak VO2 and PAEE in the present study may reflect a chronic adaptation to their free-living physical activity habits. Further studies using larger sample sizes with an exercise intervention are needed to clarify this issue.
It is important to clarify the assessment of physical activity with DLW. In the present study, free-living physical activity was calculated by measuring TEE and subtracting from it the sum of the RMR and an estimated cost of postprandial energy expenditure (18). Because the majority of our volunteers were sedentary (less than two periods per week of exercise) and not engaging in structured and regular exercise programs, PAEE reflects mostly the energy expenditure associated with physical activity other than regularly performed exercise. This includes volitional and nonvolitional activities. However, we cannot totally exclude the possibility that PAEE does not contain some structured physical activity performed on an intermittent basis. We estimated nonvolitional energy expenditure (i.e. fidgeting) in the present study by subtracting from TEE the energy costs of RMR, estimated postprandial thermogenesis, and purposeful physical activity, as estimated by the LTA questionnaire (22). We found that nonvolitional activity comprised between 65–70% of PAEE. This component has been shown to be predictive of weight gain in individuals over time (6) and consists of the energy expenditure associated with nonpurposeful activity such as fidgeting, postural control, etc. Moreover, we found that the linear relationship between nonvolitional physical activity and peak VO2 persisted in older men and women. Collectively, this finding suggests an important contribution of nonvolitional physical activity to daily energy expenditure, which is probably influenced by an individual’s level of peak VO2.
An understanding of the physiological or pharmacological factors required to activate PAEE would broaden our knowledge regarding energy balance and therapeutic options to treat obesity. Although not examined in the present study, previous work from our laboratory have shown that in trained individuals that training per se increases sympathetic nervous system activity (36, 37, 38). Increased sympathetic nervous system activity has been associated with higher levels of energy expenditure (39, 40). Thus, it is possible that the greater PAEE and nonvolitional activity observed in this study may be sympathetically mediated.
There are several caveats of our study that should be noted. First, the cross-sectional design precludes conclusions regarding cause and effect. Indeed, it is equally plausible that PAEE may be the modulating factor of peak VO2. However, this is a truism that can be directed at any cross-sectional study. Second, it is not possible to identify and characterize physical activity on the basis of duration, intensity, and/or frequency, which may affect the relationships observed. Finally, we cannot exclude the possibility that PAEE may be influenced by errors associated with the estimated thermic effect of meal, although the magnitude of these errors is likely to be trivial because the thermic effect of a meal is a small percentage of the TEE. Nonetheless, the present study suggests an association between levels of peak VO2 and PAEE in older individuals. This relationship appears to be stronger in older men than in older women. Thus, there may be additional energy-dissipating properties during free-living daily physical activity that are associated with a high peak VO2. This cluster of phenotypes may serve to preserve leanness and buffer fat gain with age.
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Footnotes |
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Received February 24, 1999.
Revised July 1, 1999.
Accepted July 7, 1999.
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