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From The Clinical Research Centers |
Divisions of Clinical Pharmacology and Metabolic Research (R.V.D., A.T., R.D.S., E.T.P.) and Cardiology (P.A.A.), Department of Medicine, University of Vermont, Burlington, Vermont 05405; and The John D. Pierce Laboratory and Department of Epidemiology and Public Health, Yale University School of Medicine (L.D.), New Haven, Connecticut 06519
Address all correspondence and requests for reprints to: Eric T. Poehlman, Ph.D., Clinical Pharmacology and Metabolic Unit, Department of Medicine, Given Building C-247, University of Vermont, Burlington, Vermont 05405. E-mail: epoehlma{at}zoo.uvm.edu
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Abstract |
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 Top Abstract IntroductionSubjects and MethodsResultsDiscussionReferences |
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Introduction |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Cardiorespiratory fitness, a physiological attribute, quantifies the ability of the body to transport and use oxygen. It is determined principally by training status and, to some extent, by genetic predisposition (9). On the other hand, physical activity is a behavioral attribute and comprises the energy expenditure from volitional and nonvolitional activity throughout the day. Physical activity has also been shown to be genotype dependent (10). Although there is shared biological variance between these two phenotypes, they may interact in a unique and independent manner to improve metabolic and cardiovascular risk factors in older people. Unfortunately, data on both cardiorespiratory fitness and physical activity levels are seldom available for older individuals.
Controversy regarding the effects of cardiorespiratory fitness and physical activity energy expenditure on cardiovascular health in older individuals may be partially due to limitations in their assessment. Whereas cardiorespiratory fitness can be directly and accurately quantified with graded exercise tests by measuring oxygen consumption, the measure of physical activity energy expenditure has relied on cruder methods, such as self-reports, motion detectors (i.e. Caltrac) (11), or structured interviews (12). Although these proxy measures of physical activity may be useful for detecting broad health trends or ranking the relative physical activity levels in epidemiological investigations, they may lack the precision and validity necessary to predict health outcomes in individuals. For example, our laboratory has recently shown, using doubly labeled water as the criterion method, that both uniaxial motion detectors and various physical activity recall questionnaires underestimate physical activity energy expenditure in older individuals by as much as 50% (13). These results raise questions regarding whether physical activity was accurately assessed in previous investigations (6, 7).
The methodological assessment of physical activity energy expenditure has been advanced in recent years with the use of doubly labeled water. This method, which relies on the administration of stable isotopes of oxygen and hydrogen (2H218O), is objective, unobtrusive, and measures physical activity energy expenditure over an extended period of time in free living older individuals (14). Thus, this approach becomes a powerful technique to increase our understanding of the impact of free living physical activity on health outcomes in the elderly, which has not previously been possible. To this end, we directly measured both cardiorespiratory fitness (VO2max) and physical activity energy expenditure using doubly labeled water in a relatively large sample of older men and women. We identified older individuals with high levels of VO2max, but low levels of physical activity energy expenditure. We compared their metabolic risk profile to older individuals with low levels of VO2max, but high levels of physical activity energy expenditure. This approach permits an investigation of the relative importance of cardiorespiratory fitness vs. physical activity energy expenditure on selected CVD risk factors in older individuals.
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Subjects and Methods |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Healthy older Caucasian men and women [53 men (68 ± 9 yr) and 63 women (67 ± 7 yr)] were recruited for the study from the greater Burlington, VT, area from local advertisements and radio announcements. Subjects were clinically screened, and exclusion criteria included 1) hypertension (resting systolic/diastolic blood pressure, >140/90 mm Hg), 2) diabetes, 3) coronary heart disease (ST segment depression, >1 mm at rest or during exercise), 4) smoking, 5) major orthopedic limitations, 6) thyroid disorders, and 7) medications that influence energy expenditure, lipid metabolism, or cardiovascular function (lipid-lowering drugs, ß-blockers, etc.). Women receiving hormone replacement therapy were also excluded from the study. Each subject signed a consent form approved by the institutional review board at the University of Vermont before participating in the study.
Testing protocol
All subjects were tested during an overnight stay in the General Clinical Research Center at the University of Vermont. On the first day, body composition was determined with dual energy x-ray absorptiometry (DXA), abdominal adiposity was estimated from waist circumference and trunk fat mass, and each subject was treated with doubly labeled water to measure total daily energy expenditure (TEE) over the subsequent 10 days. The morning after treatment, following an overnight fast, the resting metabolic rate was determined from indirect calorimetry, and a blood sample was obtained to measure fasting concentrations of plasma insulin and lipids. Specific details of all procedures are provided below.
Cardiorespiratory fitness
Maximum aerobic capacity (VO2max) was determined from an incremental exercise test on a bicycle ergometer to volitional exhaustion, as previously described (15). Cycling cadence was 50 rpm with a workload of 25 and 50 watts during the first 3 min for women and men, respectively. Thereafter, workload was increased 25 watts every 2 min until the test was terminated. The criteria for achieving VO2max (milliliters per kg/min) were a respiratory exchange ratio greater than 1.0 and a heart rate at or above the age-predicted maximum [220 - age (years)]. At least one of these criteria was reached by 93% of the volunteers. Test-retest conditions for nine older subjects (on two occasions, spaced 1 week apart) yielded an intraclass correlation of 0.94 and a coefficient of variation of 3.8% in our laboratory.
Physical activity energy expenditure (PAEE)
We used doubly labeled water in combination with indirect calorimetry to measure free living physical activity energy expenditure. TEE was determined over a 10-day period. Each subject was treated with a 1 g/kg body mass dose of 2H218O using the method of Schoeller and van Santen (14), as previously described (16). Briefly, a baseline urine sample was collected before treatment. The following morning, two additional urine samples were collected, and two more samples were collected 10 days later. Urine samples were stored frozen in Vacutainers at -20 C until analyzed for 2H and 18O enrichments by isotope ratio mass spectrometry. 18O isotopic enrichment was determined from the carbon dioxide (CO2) equilibration technique, and 2H enrichment was determined by the zinc catalyst method (17). The daily rate of CO2 production (moles per day) was calculated using the equation of Speakman et al. (18): 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. (19). Assuming a respiratory quotient of 0.85 for the food consumed (20), total CO2 production was converted to TEE (kilojoules per day) using the Weir formula (21).
The resting metabolic rate (RMR) was determined from 45 min of indirect calorimetry using the ventilated hood technique, as previously described (22). Respiratory gas analysis was performed using a Deltatrac metabolic cart (Sensormedics, Yorba Linda, CA). The RMR (kilojoules per day) was then calculated from the Weir equation (21). We previously reported an intraclass correlation of 0.90 and a coefficient of variation of 4.3% for the measurement of RMR in 17 older volunteers who were tested on 2 different occasions, 1 week apart. Assuming a thermic effect of feeding of 10% in older individuals (23), total PAEE was then calculated from the equation: PAEE = (TEE x 0.90) - RMR.
Body composition and abdominal adiposity
Body composition was measured by DXA using a DPX-L densitometer (Lunar Corp., Madison, WI). A total body scan was completed in 30–40 min and provided measures of total lean tissue mass (kilograms), fat mass (kilograms), and trunk lean and fat masses (kilograms). Abdominal adiposity was also assessed from the waist circumference taken between the xiphoid process and the superior anterior iliac crest (24). The waist circumference has demonstrated a strong correlation (r > 0.84) with visceral fat mass, as determined from computed tomography in middle-aged (25) and older subjects (26). Coefficients of variation for repeat measurements of body composition by DXA and waist circumference were 1.7% and 4%, respectively, in our laboratory.
Cardiovascular and metabolic risk factors
Plasma insulin concentrations were determined by RIA as previously described (27). Plasma cholesterol, triglyceride, and high density lipoprotein cholesterol (HDL-C) concentrations were determined from standard enzymatic techniques at the nationally accredited laboratory of the Fletcher Allen Medical Center. The interassay coefficients of variation for the measurement of total and HDL-C were 3.35% and 1.15%, respectively. Low density lipoprotein cholesterol (LDL-C) was determined from the Friedewald equation (28).
Dietary intake
Dietary intake was measured for 3 days (1 weekend day and 2 weekdays), as previously described (29). Participants were instructed by registered dietitian and encouraged to maintain their usual diet. Moreover, they were provided with dietary scales and measuring cups and spoons to further increase the precision of the data obtained. Diets were analyzed using the Nutritionist III software version 4.0 (N-Squared Computing, Salem, OR).
Statistical analysis
We divided our sample into four groups based on the median
cut-off points for the sex-specific distributions of both
cardiorespiratory fitness and physical activity energy expenditure: 1)
high cardiorespiratory fitness and high physical activity, 2) high
cardiorespiratory fitness and low physical activity, 3) low
cardiorespiratory fitness and high physical activity, and 4) low
cardiorespiratory fitness and low physical activity. We used a two-way
ANOVA to test the main effects of cardiorespiratory fitness, physical
activity, and interactions on the physical characteristics of our
sample of older individuals. No interactions were found, so main
effects are presented. To examine the effects of cardiorespiratory
fitness, physical activity, and gender on selected CVD risk factors, we
employed a three-way analysis of covariance with age as a covariate. To
examine the contribution of body composition and body fat distribution
variables on the effects of cardiorespiratory fitness, physical
activity, and gender on CVD risk factors, we used a three-way analysis
of covariance with age, gender, waist circumference, trunk fat, and
body fat percentage as covariates. Statistical significance was
accepted at 
< 0.05.
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Results |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Values for VO2max and physical activity
energy expenditure for the four groups with high and low
cardiorespiratory fitness and with high and low physical activity
energy expenditure are presented in Table 1
. The median cut-off points were
VO2max of 27.7 and 21.7 mL/kg·min for men and
women, respectively, and the physical activity energy expenditure was
3449 kJ/day for men and 2742 kJ/day for women. The
VO2max values in the high cardiorespiratory
fitness groups reflect population norms for older people who are
considered fit (30). Furthermore, physical activity energy expenditure
values for individuals in all four groups exceeded the recommended
level of daily exercise energy expenditure in older individuals (
849
kJ/day) (1). Thus, our volunteer sample represented a physically active
cohort of older individuals. In the present sample of older, healthy
individuals, we found a modest association between cardiorespiratory
fitness and physical activity energy expenditure (r = 0.37;
P < 0.01).
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The physical characteristics of our cohort are presented in Table 2. We found a significant main effect of
cardiorespiratory fitness on age, body mass, body mass index, fat mass,
body fat percentage, and waist circumference. That is, older
individuals with high cardiorespiratory fitness were slightly younger
(P < 0.01); had lower body mass (P <
0.01), body mass index (P < 0.01), fat mass
(P < 0.01), body fat percentage (P <
0.01), and trunk fat mass (P < 0.01); and had smaller
waist circumference (P < 0.01) than older individuals
with low cardiorespiratory fitness. There was no significant effect of
cardiorespiratory fitness on fat-free mass in our cohort of older
individuals. Analysis of dietary habits revealed no significant effect
of cardiorespiratory fitness on total energy intake, macronutrient
composition (Table 2), or daily intake of saturated fat and cholesterol
(data not shown in table form).
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), saturated fat, and
cholesterol intake (data not shown in table form). However, as
expected, we found that more active individuals had significantly
greater total daily energy intake than their less active counterparts
(Table 2). Cardiovascular disease risk factors
Cardiovascular disease and metabolic risk factors were examined
with age as a covariate (Fig. 1, A and
B). We observed a significant main effect of cardiorespiratory fitness
on total cholesterol, LDL-C, total cholesterol to HDL-C ratio, fasting
insulin levels, and triglycerides. That is, older individuals with high
cardiorespiratory fitness, regardless of their physical activity level,
showed lower total cholesterol levels (P < 0.01),
lower fasting LDL levels (P < 0.05), lower total
cholesterol to HDL-C ratio (P < 0.05), lower fasting
insulin levels (P < 0.01), and lower fasting
triglycerides levels (P < 0.05). We found no effect of
physical activity on HDL cholesterol levels. Also, we found no effect
of gender on any variable examined.
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Total and regional adiposity
We assessed the association of body composition and fat
distribution with the effects of cardiorespiratory fitness and physical
activity on CVD risk factors using analyses of covariance. The
rationale underlying this approach is that individuals with a high
cardiorespiratory fitness, independent of their levels of physical
activity energy expenditure, showed lower levels of body weight, total
body fat, fat mass, trunk fat mass, and waist circumference (see Table 2). Therefore, we statistically controlled for waist circumference,
trunk fat mass, or body fat percentage using analysis of covariance. We
found that the inclusion of waist circumference, trunk fat mass, or
body fat percentage as covariates eliminated all of the differences
among groups for all CVD risk factors. Fat mass-adjusted marginal means
were: for cholesterol levels, 5.2 ± 0.2, 5.6 ± 0.2,
5.7 ± 0.2 and 5.6 ± 0.2 mmol/L; for LDL-C levels, 3.5
± 0.2, 3.7 ± 0.2, 3.7 ± 0.2, and 3.9 ± 0.2 mmol/L;
for HDL-C levels, 1.6 ± 0.1, 1.5 ± 0.1, 1.5 ± 0.1,
and 1.5 ± 0.1 mmol/L; for the total/HDL-C ratio, 3.4 ± 0.2,
3.8 ± 0.2, and 3.9 ± 0.2, 3.9 ± 0.2 mmol/L; for
fasting insulin levels, 64.3 ± 10.4, 69.5 ± 10.2, and
84.9 ± 10.4, 87.5 ± 9.5 pmol/L; and for triglyceride
levels, 1.3 ± 0.2, 1.7 ± 0.2, 1.9 ± 0.2, and 1.6
± 0.2 mmol/L for groups 1–4 respectively. Waist circumference- and
trunk fat-adjusted values were similar (not shown).
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Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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The cardioprotective benefits of cardiorespiratory fitness vs. free living physical activity in older individuals are controversial. In our opinion, this is partially due to 1) the use of proxy and often inaccurate assessments of physical activity (13), and 2) the failure to measure both cardiorespiratory fitness and physical activity in older individuals. The present study addresses these limitations by directly measuring both variables using criterion measures (graded exercise test and doubly labeled water) in older individuals. Moreover, our relatively large sample size permitted the identification of four groups of older individuals that differed in cardiorespiratory fitness and physical activity levels. This approach allowed us to estimate whether older individuals with high cardiorespiratory fitness (but low physical activity energy expenditure) exhibited a more favorable CVD risk profile than individuals with high physical activity energy expenditure, but low cardiorespiratory fitness.
We found that older men and women with high cardiorespiratory fitness, regardless of their physical activity levels, showed lower concentrations of total cholesterol, LDL-C levels, the total to HDL cholesterol ratio, fasting insulin, and triglycerides, than individuals with low cardiorespiratory fitness. This point is particularly highlighted by the comparison of group 2 (high cardiorespiratory fitness, but low physical activity) vs. group 3 (low cardiorespiratory fitness, but high physical activity). Despite the fact that individuals in group 2 had lower levels of physical activity than those in group 3, their CVD risk profile was more favorable. Our results are particularly striking when one considers the healthy nature of our cohort.
How physiologically distinct are cardiorespiratory fitness and physical activity? Although one may hypothesize a strong positive association between these two phenotypes (e.g. individuals with a high physical activity level have high cardiorespiratory fitness and vice versa), this relationship is not straightforward. To address this point, we examined the relationship between VO2max and physical activity energy expenditure. We found a low order correlation between these two variables (r = 0.37) in our cohort of 117 older individuals. That is, only 13% of shared variance between these two variables was found. This finding supports the idea that these variables may act in a unique and independent manner to improve cardiovascular and metabolic health in older individuals.
There is limited evidence in the literature regarding the relative influence of cardiorespiratory fitness vs. physical activity on health outcomes in the elderly. It has been documented that individuals with higher cardiorespiratory fitness (3, 4, 5), and higher levels of physical activity (6, 7, 31) have both lower CVD and overall mortality. However, previous studies that assessed the relationship between physical activity and mortality may be questioned given recent data suggesting that physical activity questionnaires significantly underestimate true physical activity levels in older individuals (13). Moreover, few studies have examined both the effects of cardiorespiratory fitness and free living physical activity on CVD risk factors using doubly labeled water methodology. Hein et al. (32) found that the effect of cardiorespiratory fitness level on ischemic heart disease was dependent on the level of leisure-time activity in a middle-aged Danish population. Among sedentary men, cardiorespiratory fitness was not related to ischemic heart disease; however, among moderately or highly active men, there was a strong inverse relationship between the level of cardiorespiratory fitness and ischemic heart disease risk. However, other investigators (33, 34, 35, 36, 37) reported that a number of CVD risk factors showed a stronger association with measures of cardiorespiratory fitness than with physical activity levels in populations of younger to middle-aged adults. The present study extends the findings of previous investigations by directly measuring both physical activity energy expenditure and cardiorespiratory fitness using criterion measures in older individuals, a population that is particularly susceptible to the comorbidities associated with low fitness and low physical activity.
How does cardiorespiratory fitness exert greater cardioprotective effects than physical activity energy expenditure? These findings are unlikely to be due to differences in dietary habits. We found no differences in dietary intake among groups, except for the higher total energy intake in more physically active individuals compared with less active individuals. On the other hand, several investigators have suggested that favorable effects of exercise or high physical activity on CVD risk factors may be mediated through differences in body composition or total and visceral body fatness (38, 39, 40, 41, 42). To examine this question, we statistically controlled for body composition (body fat percentage) and visceral adiposity measures (waist circumference, trunk fat), which are predictors of CVD risk factors (38). As described in Results, we found no effect of cardiorespiratory fitness on the CVD risk profile variables after this analysis was performed. Taken together, these findings support the hypothesis that the effects of cardiorespiratory fitness on CVD risk profile may be mediated through lower levels of total and/or central adiposity. In support of this idea, Hunter and colleagues (43) recently reported that vigorous physical activity is effective in reducing total and abdominal adiposity. These investigators suggested that the exercise-induced reduction in total and regional adiposity may be mediated not only by the direct caloric cost of exercise, but also by the increase in postexercise RMR and greater appetite suppression. Furthermore, Tremblay and colleagues (44) reported a preferential mobilization of visceral adipose tissue with higher intensity exercise training in younger adults. Thus, it seems reasonable to suggest that older individuals may accrue greater health benefits from exercise prescriptions that stimulate cardiorespiratory fitness with concomitant reduction in total and central adiposity.
The strengths of our study are the use of two precise and direct measures to determine both cardiorespiratory fitness (graded exercise test) and free living physical activity energy expenditure (doubly labeled water) in the same older population. Furthermore, we considered the possible influence of dietary habits on CVD risk factors examined. By stratifying the sample into four groups based on their cardiorespiratory fitness and physical activity energy expenditure levels, we were able to examine the unique effects of cardiorespiratory fitness vs. physical activity on various CVD risk factors. The limitations of the present investigation include the cross-sectional design, which precludes any idea regarding causal relationships, and the fact that all of our volunteers were Caucasian. Thus, our results cannot be extrapolated to other ethnic groups. Moreover, it could be argued that a selective mortality effect was operative in which healthy older survivors volunteered for our study. These individuals may possess a cluster of favorable metabolic and CVD phenotypes. This could be attributable in part or in totality to genotypes that are responsible for both higher cardiorespiratory fitness and a favorable CVD risk profile, such as low total cholesterol, high HDL-C, low accumulation of visceral fat, high insulin sensitivity, and low blood pressure (9, 10).
Our results are not intended to discount the importance of a physically active lifestyle for maintaining health and physical function in aging (45). Indeed, substantial health benefits can be achieved through physical activity levels that are not associated with discernible changes in cardiorespiratory fitness (1, 46). Rather, we suggest that our findings underscore the probable importance of vigorous physical activity in which levels of cardiorespiratory fitness are increased. This point was most recently supported by the findings of Erikssen and colleagues (47), who showed a significant decrease in mortality in individuals who improved their cardiorespiratory fitness.
In conclusion, we found that high levels of cardiorespiratory fitness appear to have greater cardioprotective effects than high levels of physical activity in older men and women. It is possible that greater emphasis should be placed on exercise interventions to increase cardiorespiratory fitness in the elderly.
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Acknowledgments |
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Footnotes |
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Received August 10, 1999.
Revised October 21, 1999.
Accepted November 11, 1999.
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References |
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