肥胖兒童其HRV較低,血壓及心跳較高
Heart Rate Variability in Obese Children: Relations to Total Body and Visceral Adiposity, and Changes with Physical Training and Detraining
Obesity Research (2000) 8, 12–19; doi: 10.1038/oby.2000.3

Bernard Gutin*, Paule Barbeau*, Mark S. Litaker†, Michael Ferguson* and Scott Owens*

1. *Georgia Prevention Institute, Department of Pediatrics, Medical College of Georgia, Augusta, GA 30912 and the

2. †Office of Biostatistics, Medical College of Georgia, Augusta, GA 30912

Correspondence: Bernard Gutin, PhD, HS1640 Medical College of Georgia, Augusta, GA 30912. E-mail: bgutin@mail.mcg.edu

Received 17 March 1999; Accepted 6 May 1999.

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Abstract
Objective: Heart rate variability provides non-invasive information about cardiac parasympathetic activity (PSA). We determined in obese children: (1) relations of baseline PSA to body composition and hemodynamics; (2) effects of physical training (PT) and cessation of PT; and (3) which factors explained individual differences in responsivity of PSA to the PT.

Research Methods and Procedures: The root mean square of successive differences (RMSSD) was the index of PSA. Obese children (n = 79) were randomly assigned to groups that participated in PT during the first or second 4-month periods of the study.

Results: Baseline RMSSD was significantly (p < 0.05) associated with lower levels of: fat mass, fat-free mass, subcutaneous abdominal adipose tissue, resting heart rate (HR), resting systolic blood pressure, and exercise HR. Stepwise multiple regression produced a final model (R2 = 0.36) that included only resting HR. The analysis of changes over the three time points of the study found a significant (p = 0.026) time by group interaction, such that RMSSD increased during periods of PT and decreased following cessation of PT. Greater individual increases in response to the PT (p < 0.05) were seen in those who had lower pre-PT RMSSD levels, showed the greatest decreases in resting HR, and increased most in vigorous physical activity. The final regression model retained only the change in resting HR as a significant predictor of the changes in the RMSSD (R2 = 0.23).

Discussion: Regular exercise that improved fitness and body composition had a favorable effect on PSA in obese children.

Keywords:
parasympathetic activity, exercise, body composition

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Introduction
Beat-to-beat variability in heart rate, which is called heart period or heart rate variability (HRV), provides non-invasively derived information about cardiac autonomic activity (1). Low levels of parasympathetic activity (PSA), as indicated by low HRV, are powerful predictors of mortality after myocardial infarction (2). The potential clinical importance of exercise is illustrated by a study in which dogs that exercise-trained for 6 weeks increased their PSA substantially, and were afforded protection against the ventricular fibrillation associated with acute myocardial ischemia (3).

Some adult studies have shown PSA to be relatively low in obese subjects (4) and relatively high in endurance-trained subjects (5, 6, 7, 8, 9, 10). Moreover, some studies (11, 12, 13, 14, 15) have found it to increase as a result of physical training (PT). In a preliminary study, we (16) showed that obese children who engaged in 4 months of PT exhibited favorable changes in PSA compared to non-exercising controls.

The primary purpose of the present study was to investigate changes over an 8-month period in two groups of obese children; one group participated in PT for 4 months and ceased PT for the next 4 months, while the second group followed the opposite pattern. This modified crossover design permitted us to see what would happen to PSA during 8-month periods in the lives of obese children during which they were engaged in more or less physical activity. It also permitted us to see what happened when the first group discontinued the PT. To our knowledge no previous study has used this approach. We hypothesized that PSA would increase during periods of PT compared with periods of no-PT in both groups, and that it would decline in the 4-month period following cessation of PT in the group that did PT during the first 4-month period.

An additional component of the study involved exploration of individual differences in the PSA at baseline and in response to the PT. At baseline, the independent variables included: age, gender, ethnicity, total body composition, visceral adipose tissue (VAT), subcutaneous abdominal adipose tissue (SAAT), resting heart rate (HR), resting blood pressure (BP), cardiovascular (CV) fitness, and free-living vigorous physical activity. Little is known about these relationships in black and white obese children. To explore determinants of individual differences in response to the PT, we calculated a pre-PT to post-PT change score in PSA for each child, regardless of which group he/she was in. The independent variables included: pre-PT values of variables used in the baseline analyses; pre- to post-PT change scores for these variables; free-living diet and physical activity during the 4-month PT period; and PT process variables (i.e., attendance in PT sessions, energy used in the PT sessions, and HR during the PT sessions). These exploratory analyses of individual differences were designed to generate hypotheses for future investigations.

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Methods
Subjects and Design
Obese 7- to 11-year-old children were recruited via flyers and newspaper advertisements. Interested children and parents signed informed consent documents in accordance with the procedures of our Human Assurance Committee. To be included, a child needed to have a triceps skinfold greater than the 85th percentile for age, gender, and ethnicity (17). Because of the increased prevalence of obesity over the last 15 to 20 years (18), the actual percentage of children in our region who are above this cutpoint is likely to be considerably greater than 15%.

We recruited 81 children, but two were dropped for medical reasons before randomization to experimental groups. Children underwent baseline testing and were randomly assigned, within gender and ethnicity, to Group 1 or Group 2. Group 1 engaged in PT for the first 4-month period and then ceased PT for the next 4 months, while Group 2 did not engage in PT for the first 4 months and then engaged in PT for the next 4 months. Testing sessions were conducted at baseline, after 4 months, and after 8 months. No lifestyle or nutritional counseling of any kind was provided. Approximately 50% of the children underwent the protocol in the first year of the project (Cohort 1) and the other 50% participated in the second year (Cohort 2); the possibility that there might be a cohort effect was taken into account in the statistical analyses.

The mean (plusminusSD) age of the 79 experimental subjects was 9.5 (plusminus1.0) years; 26 were male and 53 were female. With respect to self-designated ethnicity, 34 were white, 44 were black, and 1 was Asian. Because we wanted to include ethnicity as a correlate of baseline HRV values and as a possible determinant of change in HRV, the Asian child was omitted from these analyses. However, he was randomly assigned to Group 2 and was included in the within-subject analyses of changes over the 8-month intervention period. Of the 79 subjects who began the intervention period, three from Group 2 did not return for 4-month testing; thus 76 were tested at the 4-month time point. Three children dropped from each group in the next 4 months, with the result that 70 completed the 8-month testing. Table 1 shows the baseline descriptive characteristics of the entire group.

Table 1 - Descriptive values at baseline (month 0) and Pearson correlations between independent variables and baseline RMSSD.
Table 1 - Descriptive values at baseline (month 0) and Pearson correlations between independent variables and baseline RMSSD - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the authorFull table



Measurement of Heart Rate Variability, HR, and BP
Resting measures were made in a supine position after 10 minutes of quiet rest. HRV parameters were measured as previously described (16) with a Schiller ECG system (Baar, Switzerland) over 256 R-R intervals. The power spectral analysis applied a Hanning window to the signals, and a Fourier transformation of the R-R intervals was performed. We focused on the root mean square of successive differences (RMSSD) as our outcome variable because this index has been recommended as the best estimate of short-term HRV by a recent consensus committee (19). By determining HRV from differences between successive beats, the RMSSD minimizes the influence of overall fluctuations in HR. At baseline, this index of PSA was highly correlated (r = 0.80, p 0.001) with the frequency domain index of PSA: i.e., high frequency power (0.15 to 0.35 Hz).

Exercise hemodynamic measures were made during submaximal cycling at a work rate of 49 W (300 kpm/minute) on a supine ergometer (Quinton 486T, Seattle, WA). The ergometer work rate was increased gradually until it reached the 49-W level, after which the child maintained that power output for 8 minutes; HR and BP measurements were made during the last 5 minutes. HR was measured with an ECG embedded in an echocardiograph (Sonos 100; Hewlett-Packard, Andover, MA), and BP was measured with a monitor (Dinamap; Critikon, Inc., Tampa, FL); five readings were made at 1-minute intervals and the last threewere averaged.

CV fitness was expressed as the average HR over the 5-minute period (submaxHR). We decided to omit a test of peak oxygen consumption because we wanted to minimize the unpleasantness of a maximal effort in obese children who would be required to return repeatedly for testing and PT, and because we have found that it is frequently difficult to elicit a "true" peak effort from obese children (20). Moreover, by measuring HR in a supine position, changes due to PT would not be influenced by alterations in body weight; i.e., if measured in a task such as treadmill walking, weight change would result in altered energy expenditure which might lead to a change in HR that was not necessarily a reflection of changed CV fitness.

Measurement of body composition
Total body composition was measured with DXA (QDR-1000; Hologic, Waltham, MA), using software version 6.0. The reliability of DXA for measurement of body composition in children has been established (21).

Magnetic resonance imaging (MRI) was used to measure VAT and SAAT, as described in detail elsewhere (22). Briefly, images were acquired on a 1.5-T MRI system (General Electric Medical Systems, Milwaukee, WI), with subjects in the supine position. Five 1-cm wide transverse images were acquired, beginning at the inferior border of the fifth lumbar vertebra and proceeding toward the head; a 2-mm gap between images was utilized to prevent cross talk. To calculate volumes for VAT and SAAT, the cross sectional area (cm2) from each slice was multiplied by the slice width (1 cm); the individual volumes (cm3) were then summed. All images were analyzed by the same experienced observer and the intra-class correlation coefficients for separate-day repeat analyses of the same scans exceeded 0.99 for both VAT and SAAT. Due to funding limitations, the baseline correlations involving the MRI measurements are based on only 62 children, whereas the analysis of change scores from before to after PT involves only 28 children. Details of the changes in VAT and SAAT are provided elsewhere (22).

Assessment of Free-Living Physical Activity and Diet
Physical activity was estimated from 7-day recalls (23) using a semistructured interview format during the 7 days just before the interview: i.e., before the baseline testing and the week before the 4- and 8-month test sessions. Thus, the 7-day recall included the PT associated with the exercise classes for the group involved in the PT during these periods. The child was asked to recall the intensity of the activities as being either moderate ("those that make you breathe as hard as during normal walking"), very hard ("those that make you breathe as hard as when running"), or hard ("those activities that are between walking and running"). Only those activities that were engaged in for at least 10 minutes were included. Time spent in hard and very hard categories were summed to derive an index of vigorous activity; we analyzed the relations of the RMSSD to both moderate and vigorous activity.

Diet assessment was designed to assist in interpretation of changes in outcome measures of the study; no dietary information was involved in the intervention. We obtained a 2-day recall at baseline to familiarize the children with the procedure. Then 2-day recalls were obtained after 2, 4, 6, and 8 months, providing 4 days of diet information for each child during his/her period of PT and 4 days for the period of no-PT. The child was given a form on which to record all food eaten for the 2 days before the interview; this information was used to assist the child in remembering what he/she ate. The Nutrition Data System of the Nutrition Coordinating Center at the University of Minnesota was used to determine intake of total energy and the percent of energy from each macronutrient.

Physical Training
Details about the PT program are provided elsewhere (24). Briefly, the program was designed to provide a substantial stimulus to the CV system, while providing an enjoyable experience for the children. The 40-minute PT sessions were offered 5 days each week and were designed to keep HR above 150 bpm. The first 20 minutes were spent on machines (e.g., treadmill, cycle, Nordic ski machine), and the next 20 minutes were devoted to games modified to maintain a high rate of energy expenditure. Each child wore a heart rate monitor (Polar Vantage, Port Washington, NY) during every session; after each session, the minute-by-minute HR data were downloaded into a computer and displayed to the child. Points were earned for maintenance of the target HR and prizes were given after accumulation of specified numbers of points. For all subjects in both groups, the average attendance was 80% (i.e., 4 days per week), and the average HR was 157 bpm over the 40-minute exercise sessions. Thus, during their periods of PT, the children clearly met the exercise recommendations put forth by various professional groups ((25), p. 28).

Statistical Analyses
All statistical analyses were performed using SAS 6.12 (SAS Institute Inc, Cary, NC). For the purpose of baseline and pre- to post-PT correlations and regressions, only white and black subjects were used, because there was only one Asian subject. An ANOVA was performed to see if gender, ethnicity, or the interaction between the two were related to RMSSD at baseline. The cross-sectional correlates of baseline RMSSD were determined in a two-step process. First, we computed the bivariate correlations between each independent variable and the RMSSD. Then the independent variables significantly correlated with the RMSSD were entered into stepwise multiple regression models to assess the extent to which they explained independent proportions of the variance. The first regressions were run separately for each domain (adiposity, physical activity, hemodynamic), the variables retained from each domain were then run together, and interactions were tested when required.

To assess the effects of the PT and cessation of PT over the three time points of the study, we used a mixed-model ANOVA, with subject as the random factor, and group and time as fixed factors. For this analysis, all 79 subjects (including the Asian subject) were used. This procedure allowed unequal sample sizes at different time points, so that the maximum number of subjects could be utilized in each analysis. Measurements that were not available at a given time point did not cause other observations for that subject to be excluded from the analysis, because least-squares estimates of the missing observations were utilized. Least-squares means provided estimates of the expected values of the group means if the design was balanced.

To explore what factors might explain individual differences in responsivity to the PT, we derived a change score for each child from before to after the PT, regardless of which group he/she was in. Thus, for Group 1 the baseline value was subtracted from the 4-month value, while for Group 2, the 4-month value was subtracted from the 8-month value. To determine if the RMSSD increased significantly across all subjects during the 4-month PT period, a paired observations t test was applied to the change scores; because an increase had been hypothesized, a one-sided test was used. Correlations were computed between change in the RMSSD and the possible determinants of change, including: (1) demographics (age, ethnicity, gender, cohort, and group); (2) changes in adiposity and hemodynamics; (3) physical activity and diet during the 4-month PT period; and (4) individual differences in aspects of the PT itself (attendance in PT sessions, and HR and energy expenditure during the PT sessions). Again, the first regressions were run separately for each domain, the variables retained from each domain were then run together, and interactions were tested when required.

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Results
At baseline, the ethnicity and gender subgroups did not differ significantly in the RMSSD, and there was no significant interaction between ethnicity and gender. Because age, group, and cohort were also not significantly associated with the RMSSD, subsequent analyses were done across all subjects together. Table 1 shows the baseline descriptive statistics and the correlations between the RMSSD and the independent variables. Percent body fat was not significantly associated with the RMSSD, whereas higher levels of both fat mass and fat-free mass were significantly associated with lower RMSSD values. With respect to abdominal adipose tissue, SAAT, but not VAT, was significantly correlated with the RMSSD. With respect to hemodynamic variables, higher resting HR and SBP were significantly associated with lower RMSSD values. The index of CV fitness, (i.e., lower submaxHR), was associated with higher values of the RMSSD. The final stepwise multiple regression analysis, in which each variable was adjusted for other variables in the model, produced the following final model (R2 = 0.36):

Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

Figure 1 shows the RMSSD pattern over the three points in the intervention period. The significant group-by-time interaction (p = 0.026) indicates that the pattern for the two groups differed. Group 1 increased during the first 4-month period when it was engaged in PT, while Group 2 remained stable during that period. When the groups changed assignments during the next 4-month period, Group 1 declined and Group 2 increased in the RMSSD.

Figure 1.
Figure 1 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

Pattern of changes in the RMSSD over the three time points of the study. The thicker lines denote the periods of physical training for each group.

Full figure and legend (85K)



With respect to the analysis of individual differences in pre-PT to post-PT change scores, the demographic factors of age, gender, ethnicity, cohort, and group were not found to be significantly correlated with the change in RMSSD. Thus, subsequent analyses were done across all subjects together. Table 2 shows the pre-PT to post-PT change scores and the correlations between the change in RMSSD and the independent variables. The change in RMSSD from pre-PT to post-PT was significant for the group as a whole (p = 0.035). However, there was a great deal of variability in the individual response to the PT, as evidenced by the large standard deviation, prompting the exploration of which factors might explain this variation. The variables that were significantly associated with individual differences in responsivity to the PT were: (1) the pre-PT RMSSD level—higher pre-PT values were associated with lower change scores (r = -0.28, p = 0.018); (2) the change in vigorous physical activity (r = 0.25, p = 0.040)—those who increased most in vigorous activity increased most in RMSSD; and (3) the change in resting HR—smaller increases in resting HR were associated with greater increases in the RMSSD (r = -0.48, p = 0.0001). When stepwise multiple regression was applied, only the change in resting HR remained in the final model (R2 = 0.23):

Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

Table 2 - Descriptive values of change scores with PT and Pearson correlations with change in RMSSD.
Table 2 - Descriptive values of change scores with PT and Pearson correlations with change in RMSSD - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the authorFull table



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Discussion
The primary result of this study was that the RMSSD increased during 4-month periods during which the obese children were engaged in PT, and declined in the 4-month period following cessation of PT in Group 1. This demonstration of what occurred as a result of increases and decreases in controlled vigorous activity supports the idea that regular exercise has a favorable influence on PSA in this population. The pattern of change for PSA is consistent with the pattern for body composition and submaxHR; i.e., improvements during periods of PT compared to periods of no-PT (26). Our findings are consistent with those of the studies that showed positive effects of PT on PSA (11, 12, 13, 14, 15). The failure of some studies to find improvements (27, 28, 29, 30) may be due to factors such as: small sample sizes; use of subjects who were not especially fat and/or unfit at baseline; relatively short periods of PT; or inadequate control and documentation of the PT stimulus. This project used a relatively large number of youths who were obese and unfit at baseline, conducted the PT for 17 weeks, achieved a mean attendance of 4 days per week, and clearly documented the PT stimulus. Our use of a modified crossover design allowed us to demonstrate the influence of both increases and decreases in vigorous activity on PSA. To our knowledge, no previous studies have utilized this approach.

At baseline, higher levels of both total body fat mass and fat-free mass, as well as SAAT, were associated with lower RMSSD levels, whereas VAT was not significantly associated with the RMSSD. Thus, it appears that visceral adiposity is not especially deleterious to PSA as it seems to be for other aspects of CV health (31). Higher levels of RMSSD were significantly associated with lower levels of resting HR. These cross-sectional associations are consistent with adult studies that found higher PSA levels in leaner and more fit subjects (6, 13, 14, 15). Urbina et al. (32) found that black male adolescents had higher PSA than white boys, while we did not find an ethnic difference. It is important to note that our study was not designed specifically to examine ethnic differences in PSA; i.e., subjects were chosen on the basis of being obese and were not chosen to be representative of their ethnic groups. Thus, we are not prepared to draw any conclusions about ethnic differences in PSA. However, the absence of ethnic or gender differences at baseline or in response to the PT suggests that our results may be generalized across these subgroups.

To our knowledge, this is the first study to explore correlates of individual differences in the responsivity of PSA to exercise training. It is noteworthy that those who increased most in vigorous activity during the 4-month PT period tended to increase the most in PSA. The correlation between change in submaxHR, our main index of CV fitness, and change in the RMSSD was r = -0.23, which just failed to reach significance (p = 0.069). The change in resting HR was the only variable that was retained in the final regression model; this is consistent with the concept that resting HR is controlled to a large extent by PSA ((33), p. 289). A parsimonious generalization for these results is that greater changes in the RMSSD were associated with a pattern that included more free-living vigorous exercise and greater reductions in resting and exercise heart rates. None of the body composition changes or dietary variables were associated with individual variation in HRV change; this suggests that the changes in HRV were due more to the PT and/or the free-living exercise.

Although the exact mechanism through which increased PSA contributes to CV health is unclear, increased vagal activity seems to antagonize sympathetic effects at the ventricular level, concomitantly improving cardiac electrical stability and protecting against experimentally induced myocardial infarction (3). Of course, the risk of death associated with lower HRV is ordinarily seen much later in life (2), making the clinical significance of our findings unclear. However, even during childhood, low levels of PSA are associated with: cardiac autonomic neuropathy in diabetics with poor metabolic control (34); duration of diabetes (35); elevated BP (36); and risk of the sudden infant death syndrome (37). It is not known whether low HRV levels are causes, consequences, or merely markers for these abnormalities. Because HRV declines with age from the years of 10 to 99 (38), it is tempting to speculate that a lifestyle that enables children to develop higher levels of HRV early in life will carry over into the adult years, thereby enabling them to slow this aspect of the aging process.

The clinical significance of the magnitude of change elicited by the 4 months of PT is difficult to assess, partly because different studies use different ways of quantifying HRV. From before to after the PT, we saw an increase in the mean RMSSD from 54 to 60 msec, which is comparable to the change seen in 23- to 69-year-old smokers several weeks after they quit smoking, in whom the mean RMSSD increased significantly from 30 to 38 msec (39); the lower values in the subjects of this study compared with the values in our subjects may reflect the differences in age. Changes in response to short-term interventions are smaller than the cross-sectional differences that may be observed between normal and diseased groups in whom the impact of the disease has had longer to manifest itself; for example, one study found that, in youths slightly older than our sample, the healthy children had a mean RMSSD value of 76 msec, whereas children with diabetes under good and poor glycemic control had mean values of 64 and 30 msec, respectively (34). The higher mean value in the healthy youths of this study (76 msec) compared with the pre-PT mean of our subjects (54 msec) may reflect the fact that our subjects were obese and sedentary before the PT. Because it is difficult to assess the clinical importance of the magnitude of change we elicited with the PT, it may be reasonable simply to conclude that 4 months of PT in obese children led to improvements in PSA that are not likely to have occurred by chance variation. Moreover, upon cessation of PT, the values declined. This pattern provides rather strong evidence of the positive influence of higher levels of physical activity on PSA, supporting the idea that obese youths who increase their regular exercise levels are likely to improve this aspect of CV health.

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Acknowledgments
Supported by the National Heart, Lung and Blood Institute (HL49549) and the American Heart Association–Parke Davis Company.