0021-972X/99/$03.00/0
The Journal of Clinical Endocrinology & Metabolism
Copyright © 1999 by The Endocrine Society
Vol. 84, No. 11
Printed in U.S.A.
Are Aerobically Fit Older Individuals More Physically
Active in Their Free-Living Time? A Doubly Labeled
Water Approach*
MARTIN BROCHU, RAYMOND D. STARLING, PHILIP A. ADES,
ERIC T. POEHLMAN
AND
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
ABSTRACT
There is considerable controversy regarding factors regulating
free-living physical activity energy expenditure (PAEE) in older individuals. This component is highly variable, is difficult to accurately
assess, and reflects both volitional and nonvolitional activities. We
examined the association between maximal aerobic fitness (peak VO2)
and free-living PAEE in older individuals.
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.
F
REE-LIVING daily physical activity energy expenditure
(PAEE) is the most variable component of daily energy
expenditure (1, 2) and is a significant predictor of age-related
changes in body composition, mortality, and morbidity (3, 4).
This component consists of both volitional (purposeful physical activity) and nonvolitional (i.e. fidgeting) energy expenditures. This latter component has been shown to be an
important buffer against fat gain during experimental overfeeding (5) and predictive of subsequent weight gain in Pima
Indians (6). Unfortunately, the accurate assessment of PAEE
has proven problematic. Previous investigators have relied
on less precise measures, such as structured interviews,
physical activity questionnaires, and mechanical devices, to
measure PAEE. These approaches variably underestimate
the energy cost of PAEE compared with the criterion method
of doubly labeled water (DLW) in older individuals (7).
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
Received February 24, 1999. Revision received July 1, 1999. Accepted
July 7, 1999.
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@
zoo.uvm.edu.
* This work was supported by the General Clinical Research Center
of the University of Vermont (RR-00109), NIH Grants AG-13978 and
DK-52754 (to E.T.P.), National Research Service Award AG-05791 (to
R.D.S.), and a Medical Research Council of Canada fellowship (to M.B.).
After correction for age, fat mass, and fat-free mass, significant
correlations were observed between peak VO2 and PAEE for older
males (r 5 0.42; P , 0.0001) and females (r 5 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. (J Clin Endocrinol
Metab 84: 3872–3876, 1999)
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, 13–15). 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, 7–10, 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.
3872
PHYSICAL ACTIVITY AND AEROBIC FITNESS IN OLDER INDIVIDUALS
Subjects and Methods
Subjects
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) 5 [TEE (Cal/day) 3 0.9] 2 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
3873
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 5 PAEE (Cal/day) 2 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 220 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 5 N/2.196 3 (cOkO 2 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 6 sd. Unpaired t tests examined
potential differences between males and females. Because age, fat-free
TABLE 1. Characteristics of the female and male subjects
Females
Age (yr)
Body weight (kg)
Body mass index (kg/m2)
Body fat (%)
Fat mass (kg)
Fat-free mass (kg)
Peak VO2 (L/min21)
Peak VO2 (ml/kg21/min21)
TEE (Cal/day)
RMR (Cal/day)
PAEE (Cal/day)
LTA (Cal/day)a
Estimated non-volitionala activity (Cal/day)
Results are mean 6SD
a
Females (n 5 74) and males (n 5 66).
Males
(n 5 96)
Range
(n 5 84)
Range
P,
66 6 8
71 6 16
26 6 4
41 6 9
29 6 13
41 6 5
1.4 6 0.3
21 6 7
2115 6 360
1303 6 192
600 6 260
238 6 169
425 6 241
(50 – 88)
(46 –114)
(18 – 45)
(11– 65)
(5– 64)
(32–56)
(0.8 –2.7)
(12–29)
(1491–3163)
(930 –1860)
(158 –1327)
(20 – 881)
(66 –1117)
67 6 8
80 6 14
27 6 6
26 6 7
20 6 9
59 6 7
2.2 6 0.6
27 6 8
2755 6 511
1622 6 225
860 6 355
365 6 235
562 6 309
(45–90)
(56 –139)
(18 – 41)
(7– 43)
(4 –51)
(46 – 82)
(0.8 –3.6)
(7–52)
(1791– 4285)
(1210 –2470)
(178 –1824)
(60 –979)
(66 –1444)
NS
0.0001
NS
0.0001
0.0001
0.0001
0.0001
0.0001
0.0001
0.0001
0.0001
0.0005
0.005
3874
BROCHU ET AL.
JCE & M • 1999
Vol 84 • No 11
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 x2 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 5 0.26; P , 0.005;
African-Americans: r 5 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.
Results
The characteristics of female and male subjects are presented in Table 1. 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).
To examine the relationship between peak VO2 and PAEE,
independent of age, fat-free mass, and fat mass, we used an
analysis of covariance approach as previously suggested (29,
30). Peak VO2 was significantly associated with PAEE in
males (r 5 0.42; P , 0.0001) and females (r 5 0.24; P , 0.05;
Fig. 1). We were also interested in the relationship between
peak VO2 and nonvolitional physical activity (PAEE 2 LTA).
We observed a low, but significant, association between peak
VO2 and nonvolitional activity in both males (r 5 0.25;
P , 0.05) and females (r 5 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).
Data were also analyzed using a tertile approach. Individuals were characterized based on their peak VO2 (adjusted for age, fat mass, and fat-free mass) to examine the possibility of a threshold effect of peak VO2 on PAEE. These
analyses showed that males with a higher peak VO2 (tertile
3) had a higher PAEE than individuals in the tertile 1 (low
peak VO2; P 5 0.01). No significant difference in PAEE was
observed in males between tertile 2 vs. tertile 1 and tertile 3.
Similar results were observed in females. Subjects in tertile
3 had higher PAEE compared to individuals in tertile 1 (P 5
0.05), whereas no difference was observed between females
in tertile 2 vs. those in tertiles 1 and 3 (Fig. 2).
Discussion
The new finding is that older individuals who are aerobically fit (i.e. higher peak VO2) show a higher level of freeliving PAEE. Second, this relationship appears to be gender
dependent, with men showing a higher PAEE than women
for a given peak VO2.
Our results support a moderate linear relationship among
FIG. 1. Relationships between PAEE and peak VO2 (liters per min)
in sedentary male and female subjects. Partial correlation analyses
were used to remove the potential effect of age, fat-free mass, and fat
mass on peak VO2 and PAEE. A level of significance of P , 0.05 was
used for hypotheses testing. Females 5 450.063573 1 [239.492687 3
peak VO2 (L/min)] 1 [20.8411712 3 age (yr)] 1 [2.33688181 3 fat
mass (kg)] 1 [25.0214432 3 fat-free mass (kg)]. Males 5 276.498164
1 [281.443841 3 peak VO2 (L/min)] 1 [21.6426666 3 age (yr)] 1
[0.20232759 3 fat mass (kg)] 1 [1.42158179 3 fat-free mass (kg)].
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 ac-
PHYSICAL ACTIVITY AND AEROBIC FITNESS IN OLDER INDIVIDUALS
3875
FIG. 2. Average PAEE in sedentary
male and female subjects when characterized on the basis of low (T1), average
(T2), and high (T3) peak VO2 (liters per
min). Values are the mean 6 SE. Analysis of covariance was used to remove
the potential linear effect of age, fat-free
mass, and fat mass on peak VO2 and
PAEE. ANOVA was used for the comparison between groups, and the
Tukey-Kramer highest significant difference test was used for a posteriori
comparisons among the three groups. A
level of significance of P , 0.05 was used
for hypotheses testing.
tivity 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 interand 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, 11–15). 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
3876
BROCHU ET AL.
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 –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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