With increased life expectancy and prolongation of an active life over one’s seventh or even eighth decade, health promotion for “successful aging” has never been so developed as today. Heart rate variability (HRV), evaluated by time and frequency domain indexes that are considered to reflect the activity of the autonomic nervous system (26), has been reported to decline overall with aging (11,24). The standard deviation of normal R-R intervals (SDNN) reflects global variability, whereas the root-mean-square of successive normal R-R interval differences (RMSSD) and high-frequency (HF) power are reasonably linked to vagal activity (26). Low-frequency (LF) power is considered mainly as an index of sympathetic activity with a parasympathetic component, but some studies (7,10) provide evidence that it is a rather unreliable marker of sympathetic activity. Nevertheless, the LF/HF or the normalized LF/(LF+HF) ratios are thought to represent sympathovagal balance at rest (15,26). The decline of global HRV with aging (11,24) has been associated with increased cardiovascular risks and all-cause mortality prognostics in older people (5,28).
It has become clear that physical activity can partially offset the age-associated fitness decline and preserve cardiovascular function (2,1,25), but there is limited information on the type and the amount of activity needed to improve HRV in the elderly. In particular, little information on the influence of lifestyle, all-day activities, and long-term physical activity on HRV is available (3,17). Concerning the elderly, the only study comparing senior long-term athletes and sedentary older subjects (mean age 69 yr) (31) concluded that athletes exhibited higher parasympathetic HRV indexes such as RMSSD and HF power than age-matched control subjects. Then, in the elderly, although the effectiveness of vigorous aerobic training on physical fitness and HRV is generally accepted (13,22), benefits of long-term physical activity on HRV are less clear (16). Guidelines on the quantity and intensity of this physical activity still need to be corroborated.
The purpose of this study was to investigate HRV in old subjects (around 75 yr) with two distinct long-term lifestyle profiles of physical activity parameters. We compared elderly subjects routinely practicing sport activities with active sedentary subjects not involved in any sportive activity on the basis of the score for sport activities from the Modified Baecke Questionnaire for Older Adults (MBQOA;29). We evaluated daily energy expenditure and assessed physical activity parameters in terms of intensity, duration, and time spent at a given intensity level for the two groups by triaxial accelerometry. To determine the impact of physical activity on sympathovagal balance, HRV temporal and spectral indexes measured at rest in two groups with different lifestyle profiles were confronted with individual physical activity parameters and energy expenditures.
Twenty-four older nonsmoking adults (14 women, 10 men, aged 75.7 ± 0.2 yr (mean ± SEM), body mass index (BMI) 24.5 ± 0.2 kg·m−2), free of cardiovascular and pulmonary disease and not subject to syncope, volunteered for this study. About 60% of elderly who were candidates were taking some kind of medication and were excluded. Others presenting abnormal cardiac ECG patterns or more than 10% ectopic heartbeats were also excluded from the study: dysrhythmia or abnormal ECG were detected in 9 of the 33 subjects who underwent medical screening. Because the accelerometer used for physical activity assessment has not to be in contact with water, subjects reporting activities like swimming were excluded. The participants gave their informed consent to participate in this experiment, which had been approved by the local Ethics Committee.
Habitual physical activity level.
Twenty-four selected subjects were divided into two groups on the basis of their physical activity level: sportive elderly (SP) who routinely practice sport activities and active sedentary elderly (SED) not involved in any sportive activity. Two physical activity criteria were used for the classifications: the MBQOA and general comments on habitual long-term physical activity collected in a second questionnaire formulated especially for this purpose. The MBQOA gives a total activity score, which is the sum of a household score, a sporting activity score, and a leisure-time activity score. The separate scores are obtained from activity duration (h·wk−1), frequency (months·yr−1), and intensity at which the activity is normally performed. The MBQOA intensity codes are unit less and were originally based on energy costs (28). To be classified as SP, subjects had to present an MBQOA sport score higher than 7, the median of all the sport scores collected, and to report sportive activity for more than 30 yr without major interruption. SP (aged 76.7 ± 0.4 yr; BMI 25.1 ± 0.3 kg·m−2; N = 12, 5 women and 7 men) presented significantly higher total activity scores than the SED (aged 74.7 ± 0.4 yr; BMI 24.0 ± 0.3 kg·m−2; N = 12, 9 women and 3 men): 14.5 ± 0.5 vs 12.0 ± 0.4 (P < 0.05). Regarding the three separate scores, household activities and leisure-time activity scores were not different between SP and SED (2.8 ± 0.1 vs 2.7 ± 0.1 and 3.5 ± 0.3 vs 2.9 ± 0.2, respectively), whereas the sport activities score was significantly higher (9.5 ± 0.3 vs 4.9 ± 0.2, P < 0.001) in SP.
The experiments were performed between 10:00 and 12:00 a.m. in an air-conditioned room with ambient temperature maintained at 21°C. The subjects had their usual breakfast at least 3 h before the beginning of the experimentation, avoiding coffee. After 20 min of rest lying down, subjects were asked to stay supine quietly for 10 min without speaking or making any movements. Subjects breathed at 15 cycles·min−1 (0.25 Hz) by synchronizing their breathing pattern with an electronic metronome rhythm, so that the respiratory rate would influence HRV in the same way for each subject.
Heart rate (HR) was continuously monitored using a Holter with sampling frequency of 256 Hz (Ela Medical, Paris, France) for determination of HRV. Thoracic and abdominal movements were recorded using a Crystal Trace Piezo Respiration Sensor (Astro-Med EEG System, Grass Instruments, West Warwick, RI) to get breathing frequency.
Physical activity assessment by accelerometry.
Energy expenditure and physical activity parameters were assessed by a triaccelerometer device (RT3, Stayhealthy, Monrovia, CA). Participants were instructed to wear the small (2.8″ × 2.2″ × 1.1″) and lightweight (2.8 oz) monitor on their right hip during waking hours for 1 wk, excluding periods of bathing or other water activities. Accelerometer calibration was verified before each measurement period using a standard calibration furnished by the constructor. When the device is attached to the side of the body it measures acceleration (counts·min−1) in the anterior-posterior, mediolateral, and vertical directions and summarizes that information as a vector magnitude (Vmag). This vector is calculated as a square-root of the sum of the squared acceleration for each direction. Physical activity energy expenditure is then calculated by converting the Vmag data into energy expenditure (kcal) via the manufacturer’s proprietary equations taking into consideration the subjects’ body mass. Total physical activity energy expenditure is the mean activity energy expenditure recorded during the week-long recordings, whereas total energy expenditure represents the total physical activity energy expenditure with individual resting basal metabolism added (calculated by the accelerometer software on the basis of a subjects’ anthropometric data and age).
Total activity time was the time over the full week during which movements had been recorded by the accelerometer. A threshold activity count (15 counts·min−1) was arbitrarily set to detect only substantial body movements and eliminate artifacts (shocks or light vibrations of the recorder detected in the absence of body movements). To evaluate time spent at various activity levels, we used cutoff points given as intensity thresholds by the U.S. Department of Health and Human Services for adults more than 75 yr old (25). An individual’s energy expenditure measured by the accelerometer was converted into metabolic equivalents (METs). Activities scored <2 METs were interpreted as having very light intensity, activities from 2 to 3.5 as light, 3.6 to 4.7 as moderate, 4.8 to 6.7 as hard, and more than 6.8 as very hard and maximal. Times spent at these different intensities are reported in absolute values (h).
The R-R intervals, that is, the time between the R peaks of consecutive QRS complexes recorded by the Holter, were calculated and checked for artifacts. Occasional ectopic beats were identified and replaced with interpolated R-R interval values. HRV analyses were performed on the last 5 min of the 10-min controlled breathing in the lying-resting period to be able to assume stability of the data. SDNN and RMSSD were calculated for the 5-min period. Power frequency analysis of the 5-min recordings was performed sequentially with a fast Fourier transform based on a nonparametric algorithm with a Welsh window after the ectopic-free data were detrended and resampled. A fixed resampling frequency of 1024 equally spaced points per 5-min period was used. The power densities in the LF band (0.04–0.15 Hz) and the HF band (0.15–0.50 Hz) were calculated from each 5-min density spectrum by integrating the frequency power density in the respective frequency bands. The different HRV indexes, SDNN, RMSSD, LF, HF, and the LF/(LF+HF) and HF/(LF+HF) ratios were computed.
Because the data have a skewed distribution, all analyses were done on log-transformed values to allow parametric statistical comparisons that presume a normal distribution. Student’s unpaired t-tests were used to compare HRV and energy expenditure parameters between the two experimental groups. The level of significance was set at P < 0.05.
Physical activity assessment.
Total energy expenditures of both the SP and SED groups are presented in Table 1. Unmeasured calculated resting metabolic rate (RMR) was not significantly different between the two groups. In contrast, total energy expenditure and total physical activity energy expenditure were respectively 8.8 and 21.0% higher in SP than in SED. Total activity time over 1 wk was significantly lower in SP than in SED (Table 2). Expressed in hours, SP spent significantly less time at very light intensity (P < 0.05), tended to practice more light and moderate activities, and spent significantly more time at hard intensity (P < 0.05).
Values from both groups are illustrated in Figure 1. SP exhibited lower resting HR (60.1 ± 0.7 vs 66.4 ± 0.6 bpm; P < 0.05). The temporal HRV indexes SDNN and RMSSD were significantly higher in SP than in SED (37.7 ± 1.1 vs 28.5 ± 0.8, P < 0.05; and 36.6 ± 1.5 vs 19.8 ± 0.6, P < 0.05, respectively). The absolute HF power was significantly increased in SP (624.9 ± 66.1 vs 165.1 ± 12.3, P < 0.05), as the HF/(LF+HF) ratio (0.5 ± 0.1 vs 0.4 ± 0.1, P < 0.05).
Based on the evaluation of physical activity parameters via the questionnaire and accelerometry, this study reveals that a long-term practice of sporting activities associated with higher daily energy expenditure, in contrast to routine daily activities, is associated with higher global HRV and vagal-related HRV indexes in very old subjects. The level of global variability (SDNN) and vagally mediated indexes as RMSSD, HF power, and HF/(LF+HF), which have previously shown to be decreased with age (11,24), were higher in the SP group compared to the SED. This may be related to higher daily energy expenditure and a longer time spent at a higher level of physical activity. Since total activity time was lower in SP, we cannot distinguish which parameter of the total energy expenditure or of the intensity of physical activity is the most influent on HRV.
Habitual physical activity evaluation by questionnaire.
The total MBQOA scores indicated a high level of physical activity for our experimental groups, which both had similar total scores as reported in active elderly (20). The additional questionnaire directed at identifying long-term habits confirmed that SP had been practicing sport for more than three decades without major interruption, whereas SED had not. It is important to note that the subjects in our study were selected to be very healthy, compared with many elderly that are generally taking mediations or have chronic diseases. In addition, the SED who participated were still quite active even in the absence of sport activities. The SP subjects exhibited only significantly higher total and sport activity scores than the SED. Household and leisure-time activity scores were similar in both groups. This indicates that the groups differed only by their involvement or not in sport activities.
Habitual physical activity evaluation by accelerometry.
The higher total energy expenditure observed in SP is in accordance with previous studies (19) comparing trained old people (aged 60–69 yr) with sedentary controls. As previously reported (9), we also found that total activity time was significantly lower in SP than in SED. Concerning intensity of physical activity, SP spent more time at higher activity levels than SED, whereas SED spent more time at very light activities. SP showed higher energy expenditure despite lower activity time; thus, the increased intensity during their training sessions easily compensated for the lesser activity time. The longer activity time of SED subjects may not be sufficient to offset their lower intensity activity.
The influence of short-term aerobic training programs on HRV has been repeatedly described in young and middle-aged subjects. Except for a few cases (4,14), subjects exhibit higher global HRV values after training, with enhanced parasympathetic indexes like RMSSD and HF power (5,23). In older subjects, a similar improvement after training has been reported (13,22) but not in all cases (20). It appears that total training duration can explain the discrepancies: at equivalent exercise intensity, 6 months of training has been shown to have a beneficial effect on HRV (13,22), whereas 8 wk may not be sufficient (20). Concerning the influence of lifestyle and long-term habitual physical activity on HRV, little information for young and middle-aged subjects is available (3,17). In the only study comparing senior athletes and sedentary subjects (mean age 69 yr) (31), the authors concluded that athletes had higher RMSSD and HF power than age-matched controls, although daily physical activity was not measured. We confirm these results in elderly subjects of about 75 yr with simultaneous evaluation of physical activity parameters. It is debatable whether other methods of HRV evaluation than spectral and temporal analyses could have led to different conclusions. Although some methods may be more devoted to nonstationary data (wavelet transform (21)) or to exercise (fractal analysis (18)), our methods may have been well appropriate for resting conditions (26).
Lifestyle, HRV indexes, and cardiovascular risks.
These results fit into the discussion on weekly optimal training load in terms of intensity and duration for cardiovascular disease prevention and maintaining cardiorespiratory fitness. Studies either recommend important all-day activity level (6,30), physical exercise of moderate intensity and long duration (2,16,25), or shorter vigorous exercise (1). Despite the inverse relationship between HRV and mortality prognostics previously described in healthy subjects (27,28) and in patients (8,12), care should be taken in extrapolating these results to our elderly due to the small differences found both in physical activity and HRV levels.
Limitation of the study.
As discussed above, our results show that older adults having higher energy expenditure have higher vagal-related indexes. Although we may hypothesize that sport activities in the elderly better counteract the HRV decrease with aging than a sedentary lifestyle, it also can be advanced that only older persons with genetically high HRV indexes still participate in sports in their seventh decade. Thus, care has to be taken in determining whether a high level of physical activity is the cause or the consequence of high HRV.
Based on physical activity parameter analysis in elderly subjects (aged about 75 yr), this study indicates that a long-term sportive lifestyle together with an increased daily energy expenditure is associated with higher vagal-mediated HRV indexes than a active but nonsportive way of life. This may be linked to the longer time spent at higher intensity activities or to higher daily total energy expenditure related to physical activity. Sports activities may constitute a worthwhile way to increase energy expenditure because of the higher activity intensity reached. Further investigation on active (but nonsportive) and on sportive subjects presenting equivalent total energy expenditure related to physical activity may help to determine the separate effects on HRV of energy expenditure, activity intensity, and exercise duration in these two lifestyle profiles.
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Keywords:©2004The American College of Sports Medicine
SYMPATHOVAGAL BALANCE; LIFESTYLE; ENERGY EXPENDITURE; AGING