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2010-01最新HRV臨床論文摘要 

台灣地區肥胖的兒童其身體質量指數

台灣地區肥胖的兒童其身體質量指數Body Mass Index,血壓及LF/HF均較正常者高,而其HF(副交感)則較低

Heart Rate Variability in Taiwanese Obese Children

Chen-Chung Fu, Yin-Ming Li1, Dee Pei, Chien-Lin Chen, Huey-Ming Lo2, Du-An Wu, Terry BJ Kuo3

Department of Internal Medicine, Family Medicine1, Buddhist Tzu Chi General Hospital, Hualien, Taiwan; Department

of Internal Medicine2, Shin Kong Wu Ho Su Memorial Hospital, Taipei, Taiwan; Institute of Neuroscience3, Tzu Chi

University, Hualien, Taiwan

ABSTRACT

Objective: The primary purpose of the present community-based study was to investigate early changes in cardiac autonomic

function in obese children. Materials and Methods: A survey of juvenile obesity in Hualien in eastern Taiwan was performed in

2002. A total of 1,724 adolescents who were 12 or 13 years old were recruited. The overall prevalences of normal weight, overweight

and obese adolescents were 71.5% 13.1%, and 15.4%, respectively. A stratified random sampling scheme was performed.

We selected 100, 50 and 75 subjects from the above-mentioned three groups, and invited them to join this study. Totally, 170

students (normal-weight: overweight: obese= 81: 34: 55) participated in this study. They received blood checks and a heart rate

variability (HRV) examination. The homeostasis model assessment of insulin resistance (HOMA-IR) was used to evaluate insulin

sensitivity. Results: Compared with the normal-weight group, the obese children had significantly elevated body mass indexes

(BMI), HOMA-IR, and systolic and diastolic blood pressure levels. In addition, compared to their normal weight counterparts,

obese children had significantly reduced high-frequency power (HF) but elevated low-frequency power in normalized units (LF %),

and elevated ratios of low-frequency power to high-frequency power (LF/HF ratio). Further analyses revealed that compared with

the normal weight counterparts; obese boys had significantly reduced HF but elevated LF % and LF/HF ratios. Among obese girls,

the HF was reduced significantly, and LF% and the LF/HF ratio were increased, though not significantly. In stepwise multiple

regression analysis, the BMI and heart rate were negatively associated with the HF component and positively associated with the

LF/HF ratio and LF %. For every 1 kg/m2 increment in the BMI, the LF/HF ratio and LF % components of HRV increased ln(0.02)

and 0.42% respectively, while HF decreased 0.03 ln(ms2). Boys had a higher LF/HF ratio and LF % than girls. Conclusions: The

obese boys and girls had increased insulin resistance and changes in autonomic nervous function that included reduced parasympathetic

control and obese boys had elevated sympathovagal modulation. Gender-related autonomic differences, such as girls having

lower sympathetic modulations of HRV, were also noted. ( Tzu Chi Med J 2006; 18:199-204)

Key words: obese children, heart rate variability, autonomic nerve dysfunction

Received: February 15, 2006, Revised: March 17, 2006, Accepted: April 13, 2006

Address reprint requests and correspondence to: Dr. Chen-Chung Fu, Department of Internal Medicine, Buddhist Tzu Chi

General Hospital, 707, Section 3, Chung Yang Road, Hualien, Taiwan

ORIGINAL ARTICLE

INTRODUCTION

The prevalence and severity of obesity are increasing

worldwide [1]. Obesity is characterized by hemodynamic

and metabolic alterations and these alterations

involve autonomic nervous system control of cardiac

function [2-4]. In recent years, heart rate variability

(HRV) measurements have been used as markers of autonomic

modulation of the heart. Because of its accessible

and noninvasive nature, analysis of HRV has gained

popularity with broad applications as a functional indicator

of the autonomic nervous system. HRV studies

among adults with obesity have revealed inconsistent

results including high [5,6], and low [7] sympathetic tone

coupled with a reduction in vagal tone [5,7]. Some have

attributed this to age differences in study subjects, because

HRV has been known to change with age [8]. In

addition, changes in autonomic balance may accompany

natural development processes as well as the onset of

some chronic diseases in adults, which is why studies

focused on children may provide important information

C. C. Fu, Y. M. Li, D. Pei, et al

Tzu Chi Med J 2006 _18 _No. 3 OMM

about obesity. Few studies of HRV had been done in the

pediatric population, and inconsistent findings from these

studies include a reduction in vagal tone [9-12] coupled

with significantly increased [9,10], non-significantly

changed [11], and reduced [12] sympathetic tone. One

reason for this disparity is that all these studies used a

hospital-based method with a possibility of referral bias.

The primary purpose of the present community-based

study was to investigate cardiac autonomic function in

Chinese obese children by using frequency-domain heart

rate variability methods. There has been no previous

HRV study in Chinese children. Our hypothesis was that

changes in cardiac autonomic function are present not

only in obese adults, but also in obese adolescents in

Taiwan.

MATERIALS AND METHODS

A survey of overweight in all first-year junior high

school students in Hualien in eastern Taiwan was performed

from 2001 to 2002. A total of 1,724 adolescents

who were 12 or 13 years old, were recruited. The overall

prevalence rates of normal weight, overweight and

obese adolescents were 71.5% 13.1%, and 15.4%, respectively

[13]. To recruit enough obese children, a stratified

random sampling scheme was performed. We selected

100, 50 and 75 subjects from the above-mentioned

three groups, and invited them to join this study. Totally,

170 students (normal weight:overweight:obese=81:34:

55) agreed to participate in this study. Obesity was defined

based on the BMI index reference released by the

Department of Health of Taiwan in 2002 [13,14]. The

indexes for boys and girls are shown in Table 1. None

of the children were smokers. They did not have any

history of hypertension or diabetes.

Approval to conduct the study was given by the Ethics

Committee of Buddhist Tzu Chi General Hospital

(Hualien, Taiwan). All students and their parents were

carefully instructed about the details of the study. All

gave written informed consent to participate in the study.

We collected data on their current body height and body

weight and their fasting blood sugar and insulin were

measured after fasting at least 10 hours. An ECG examination

was done on a different day. Both food and

beverages were prohibited for at least 60 minutes before

the testing.

Processing of ECG signals

A precordial electrocardiogram (ECG) was taken

in the daytime from each subject for 5 minutes with subjects

lying quietly and breathing normally. The digitized

ECG signals were analyzed on-line and simultaneously

stored on removable hard disks for off-line verification.

Signal acquisition, storage, and processing were performed

on IBM PC-compatible computers. The computer

program for HRV analysis was modified from our

previous method [15,16] according to recommended

procedures [17]. In the QRS complex identification

procedure, the computer first detected all peaks of the

digitalized ECG signals using a spike detection algorithm

similar to general QRS complex detection

algorithms. Parameters such as amplitude and duration

of all spikes were measured so that their means and standard

deviations (SD) could be calculated as standard

QRS templates. Each QRS complex was then identified,

and each ventricular premature complex or noise was

rejected according to its likelihood in standard QRS

templates. The R point of each valid QRS complex was

defined as the time point of each heart beat, and the interval

between two R points (R-R interval) was estimated

as the interval between current and latter R points. In

the R-R interval rejection procedure, a temporary mean

and SD of all R-R intervals were first calculated for standard

reference. Each R-R interval was then validated.If

the standard score of an R-R value exceeded 3, it was

considered erroneous or non-stationary and was rejected.

The average percentile of R-R rejection according to this

procedure was 1.2%. The validated R-R values were

subsequently resampled and interpolated at the rate of

7.11 Hz to achieve continuity in the time domain.

Frequency-domain analysis

Frequency-domain analysis was performed using the

nonparametric method of the fast Fourier transform

(FFT). The direct current component was deleted and a

Table 1. Body Mass Index Cut-offs for Overweight Children Recommended by the Department of Health of Taiwan in 2002

Boys Girls

Age (yrs)

normal overweight obese normal overweight obese

12 16.4-21.4 ≥21.5 ≥24.2 16.4-21.5 ≥21.6 ≥23.9

13 17.0-22.1 ≥22.2 ≥24.8 17.0-22.1 ≥22.2 ≥24.6

Heart rate variability in children

Tzu Chi Med J 2006 _18 _No. 3 OMN

Hamming window was used to attenuate the leakage

effect [18]. For each time segment (288s, 2,048 data

points), our algorithm estimated the power spectral density

on the basis of FFT. The resulting power spectrum

was corrected for attenuation resulting from the sampling

and the Hamming window [19,20]. The power

spectrum was subsequently quantified into various frequency-

domain measurements, including total variance,

high-frequency power (HF; 0.15-0.40 Hz), low-frequency

power (LF; 0.04-0.15 Hz), very low-frequency

power (VLF; 0.003-0.04 Hz), and the ratio of LF to HF

(LF/HF ratio). In particular, LF power was normalized

by the percentage of total power except for VLF (total

power-VLF) to detect sympathetic influence on HRV

(LF%) [16]. A similar procedure was also applied to HF

(HF%). All HRV parameters were expressed in original,

square root, and natural logarithmic form to demonstrate

and correct possible skewness.

HOMA-IR was used to evaluate insulin sensitivity.

The formula for the HOMA-IR is as follows: fasting

insulin (µU/mL) × fasting glucose (mmole/L)/22.5 or

fasting insulin (µU/mL) × fasting glucose (mg/dL)/405

[21]. Plasma glucose was measured by the glucose-oxidase

technique (Hitachi 717 analyzer, Hitachi, Ltd.

Tokyo, Japan). Fasting insulin concentrations were

measured by a microparticle enzyme immunoassay

(Axsym Insulin Reagent Pack, Abbott Laboratories,

Abbott Park, IL, USA). The intraassay coefficient of

variation was 4% and the interassay coefficient was 6%

for insulin concentrations in the range between 14.68

and 124.51 µU/mL.

Statistical analysis

All the data were analyzed through a statistical SPSS

software package. Analysis of variance (ANOVA) with

the post hoc test was used to compare the mean value of

continuous variables. Correlation analysis was used to

evaluate the relationships between variables. Stepwise

multiple regression analysis was used to study the independent

contributions of different potential variables to

the spectral component of HRV. The independent variables

included sex, age, BMI, HOMA-IR, heart rate, and

systolic and diastolic blood pressure levels.

RESULTS

Clinical anthropometrical data on the children are

summarized in Table 2. There were no statistically significant

gender differences between the obese children

and the control group; however, there were more boys

in the obese group than in the overweight group. Compared

with the control group, obese children had significantly

elevated mean BMI, HOMA-IR, and systolic

and diastolic blood pressure levels. The differences between

the overweight and control groups were significant

for BMI, HOMA-IR and diastolic blood pressure

levels. Table 3 shows spectral HRV parameters of the

study subjects. The obese children had significantly reduced

HF but elevated LF% and LF/HF ratios compared

to the normal weight children. Further analyses revealed

that, compared with their normal weight counterparts,

obese boys had significantly reduced HF, and elevated

LF% and LF/HF ratios. HF was reduced significantly in

the obese girls, and LF% and LF/HF ratios were

increased, although not significantly. In correlation

analysis as shown in Table 4, the HF spectral value of

HRV was negatively correlated to BMI, HOMA-IR and

heart rate, while both LF/HF and the LF% spectral value

were positively correlated to BMI, systolic blood

pressure, HOMA-IR and heart rate. In stepwise multiple

regression analysis, the contributions of sex, age, BMI,

Table 2. Clinical Characteristics of Study Subjects

Variables Control (n=81) Overweight (n=34) Obese (n=55)

Sex (M/F) 47/34 16/18 38/17#

Age (years) 12.5±0.5 12.5±0.6 12.5±0.5

BMI (kg/m2) 20.0±2.5 24.7±0.8** 30.3±3.7**##

SBP (mmHg) 110±12 111±11 121±10**##

DBP (mmHg) 67±7 70±8* 70±10*

Heart rate (beat/minute) 75±9 76±11 78±10

Fasting plasma glucose (mg/dL) 84±6 89±7 89±7

Fasting plasma insulin (µU/mL) 3.6±2.1 6.6±3.9 9.5±4.5

HOMA-IR 0.8±0.5 1.4±0.9 * 2.0±1.5 **#

Data: expressed as means±standard deviation; BMI: body mass index; SBP: systolic blood pressure; DBP: diastolic blood pressure; **: P <0.005; *:

P <0.05 Post Hoc test for difference between overweight or obese group and control group; ##: P <0.005; #: P <0.05 Post Hoc test for difference

between overweight and obese group

C. C. Fu, Y. M. Li, D. Pei, et al

Tzu Chi Med J 2006 _18 _No. 3 OMO

HOMA-IR, heart rate, and systolic and diastolic blood

pressures to the spectral power of HRV were studied. In

these models, BMI and heart rate were negatively associated

with the HF component while positively associated

with the LF/HF ratio and LF%, as shown in Table

5. Of note, for every 1 kg/m2 increment in BMI, the LF/

HF ratio and LF% components of HRV increased ln

(0.02) and 0.42% respectively, while the HF component

decreased 0.03 ln(ms2). Gender was another significant

factor. Boys had higher LF/HF ratios and LF% than girls

(means±SE: LF/HF ratios: 0.49±0.06 vs 0.28±0.07 ln

(ratio); LF%: 51.4±1.4 vs 45.6±1.6 nu). These models

explained 30%, 12%, 15% and 16% of the variability in

the HF, LF/HF, LF% and LF components, respectively.

Table 5. Multiple Stepwise Regression Analysis between Selected Variables and HRV Spectral Components

Component Variables R2 ß S.E. t p

HF Heart rate (increased every beat/minute) 0.30 -0.05 0.01 -8.04 <0.001

BMI -0.03 0.01 -2.19 <0.05

LF/HF Heart rate (increased every beat/minute) 0.12 0.02 0.01 3.29 <0.001

BMI (increased every 1 kg/m2) 0.02 0.01 2.26 <0.05

Sex (girls vs boys) -0.19 0.10 -1.98 <0.05

LF % Heart rate (increased every beat/minute) 0.15 0.38 0.10 -3.68 <0.001

Sex (girls vs boys) -5.38 2.05 -2.62 <0.05

BMI (increased every 1 kg/m2) 0.42 0.19 2.22 <0.05

LF Heart rate (increased every beat/minute) 0.16 -0.13 0.01 -5.63 <0.001

S.E.: standard error

Table 4. Correlation Coefficients of Selected Variables and Spectral Components of HRV

Variables Age BMI HOMA SBP HR HF LF LF/HF LF %

Age (years) 1.00 0.02 0.03 -0.05 -0.11 0.07 0.03 -0.06 -0.06

BMI (kg/m2) 1.00 0.47** 0.49** 0.08 -0.18* -0.04 0.21** 0.21**

HOMA 1.00 0.23** 0.24** -0.21** -0.11 0.16* 0.13

SBP (mmHg) 1.00 0.18* -0.07 0.06 0.18* 0.23*

HR (beat/min) 1.00 -0.53** -0.40** 0.25** 0.27**

HF ln(ms2) 1.00 0.75** -0.47** -0.38**

LF ln(ms2) 1.00 0.24** 0.29**

LF/HF ln(ratio) 1.00 0.94**

LF % (nu) 1.00

SBP: systolic blood pressure; HR: heart rate; nu: normalized unit; *: p< 0. 05; **: p< 0.01

Table 3. Spectral HRV Parameters of the Study Subjects

Boys Girls Total

Variables Control Overweight Obese Control Overweight Obese Control Overweight Obese

(n=47) (n=16) (n=38) (n=34) (n=18) (n=17) (n=81) (n=34) (n=55)

VLF ln(ms2) 7.09±0.14 7.37±0.22 6.72±0.17# 6.95±0.15 6.55±0.20 6.75±0.15 7.03±0.10 6.94±0.16 6.73±0.12

HF ln(ms2) 6.30±0.14 6.48±0.19 5.83±0.15*# 6.46±0.13 6.07±0.25 5.87±0.23* 6.37±0.10 6.27±0.17 5.84±0.12*#

LF ln(ms2) 6.68±0.12 6.86±0.16 6.50±0.16 6.60±0.13 6.40±0.18 6.35±0.21 6.65±0.09 6.62±0.13 6.45±0.13

LF (%) 48.5±1.9 49.9±2.8 55.8±2.5* 43.8±2.3 45.9±2.8 48.9±3.1 46.5±1.49 47.8±1.97 53.6±2.04*

HF (%) 33.9±1.7 34.6±2.3 29.1±1.7* 37.6±1.8 33.7±2.6 31.8±2.8 35.5±1.24 34.1±1.73 30.0±1.48*

LF/HF ln(ratio) 0.38±0.09 0.38±0.12 0.67±0.11* 0.15±0.10 0.33±0.13 0.48±0.17 0.28±0.07 0.35±0.09 0.61±0.09*

Data: expressed as means+standard error; **: P <0.005; *: P <0.05 Post Hoc test for difference between overweight or obese group and control

group; ##: P <0.005; #: P <0.05 Post Hoc test for difference between overweight and obese group

Heart rate variability in children

Tzu Chi Med J 2006 _18 _No. 3 OMP

HOMA-IR was not a significant factor of HRV spectral

components in multivariate analysis.

DISCUSSION

Arguments about the physiological interpretation of

LF components of HRV have been reported by the European

Society of Cardiology and some recommendations

have been made [17]. In brief, HF is considered to represent

vagal control of the heart rate [17,22] and the sympathetic

and parasympathetic nerves jointly contribute

to LF. Thus, LF% and the LF/HF ratio have also been

thought to mirror sympathovagal balance or to reflect

sympathetic modulations [17,23-25]. Thus, we chose HF,

LF% and the LF/HF ratio as representative variables of

autonomic function to examine their relationships with

other variables in this study.

In accordance with other studies, we found that both

healthy obese boys and girls had reduced parasympathetic

control [9-12]. Elevated sympathovagal modulation

was also noted in obese boys in this study and others

[9,10]. Compared with their normal weight

counterparts, obese girls had increased sympathovagal

modulation, although it was not significant because there

were only a few obese girls in this study. Of note, we

found that for every 1 kg/m2 increment in BMI, the LF/

HF and LF% components of HRV increased ln(0.02)

and 0.42% respectively, while the HF component decreased

0.03 ln(ms2) in multivariate analysis. This implies

that during the early stage of obesity, such as in

obese adolescents, there is an imbalance in cardiac autonomic

function. Some might attribute these changes of

HRV to age differences in the study subjects, because

HRV has been known to change with age [8]. However,

our subjects were all 12 or 13 years old and randomly

selected from the community. Therefore, our study results

were unaffected by age and very convincing.

Notably, we found an increase in HOMA-IR, LF%

and the LH/HF ratio in the obese children compared to

their normal-weight counterparts. As such, this has major

implications in that changes in autonomic nerve

modulation and insulin resistance might play important

roles in the pathogenesis of childhood obesity. Although

this study failed to demonstrate that HOMA-IR is a significant

factor of HRV spectral components in multivariate

analysis, it did show that HOMA-IR is negatively

correlated with HF and positively correlated with both

LF/HF and the LF% spectral value of HRV in correlation

analysis. Clearly more work is needed to precisely

define the relationship between insulin dynamics and

autonomic nerve dysfunction among obese children.

Although gender-related differences in autonomic

nerve function have been reported previously with diverse

results [26,27], our previous studies in adults demonstrated

that women younger than 50 years old had

higher vagal tone but lower sympathetic modulations of

HRV than age-matched men [20]. In this study, boys

had higher LF/HF ratios and LF% but lower HF. This

also reflects higher sympathetic modulation in males as

early as their teenage years. Compared to their male

counterparts, females are at lower risk of coronary heart

disease than males and this may be explained by their

lower sympathetic modulation [28].

There were several limitations to this study. The

BMI cut-off accepted as a definition of overweight in

adults is based on increased risks of morbidity and

mortality. The World Health Organization has suggested

a cutoff point for overweight in adults in the Asia-Pacific

region. However, there is no internationally acceptable

index cutoff point to assess overweight in childhood.

Therefore, BMI cut-offs as suggested by the Department

of Health of Taiwan in 2002 were used in this study.

Secondly, it is important to note that the physiological

interpretation of LF is not always unequivocal. Thus,

the recommendations of physiological interpretation of

spectral HRV components suggested by the European

Society of Cardiology were adopted.

In summary, this study has shown that obese children

had increased insulin resistance and changes in

autonomic nerve function that included reduced parasympathetic

control in boys and girls and elevated

sympathovagal modulation in obese boys. In addition,

boys had higher LF/HF ratios and LF% than girls. Clearly

more work is needed to explore the relationship between

gender differences in autonomic nerve function in the

pediatric population and cardiovascular disease in these

subjects when they reach adulthood.

ACKNOWLEDGEMENTS

This study was supported by a grant from Tzu Chi

General Hospital.

REFERENCES

1. World Health Organization. Obesity: Preventing and

Managing the Global Epidemic. Report of a WHO

consultation. Geneva: World Health Organization, 1998.

2. Young JB, Macdonald IA: Sympathoadrenal activity in

human obesity: Heterogeneity of findings since 1980.

Int J Obes Relat Metab Disord 1992; 16:959-967.

3. Corry DB, Tuck ML: Obesity, hypertension, and symC.

C. Fu, Y. M. Li, D. Pei, et al

Tzu Chi Med J 2006 _18 _No. 3 OMQ

pathetic nervous system activity. Curr Hypertens Rep

1999; 1:119-126.

4. Piccirillo G, Vetta F, Fimognari FL, et al: Power spectral

analysis of heart rate variability in obese subjects: Evidence

of decreased cardiac sympathetic responsiveness.

Int J Obes Relat Metab Disord 1996; 20:825-829.

5. Karason K, Molgaard H, Wikstrand J, Sjostrom L: Heart

rate variability in obesity and the effect of weight loss.

Am J Cardiol 1999; 83:1242-1247.

6. Gao YY, Lovejoy JC, Sparti A, Bray GA, Keys LK,

Partington C: Autonomic activity assessed by heart rate

spectral analysis varies with fat distribution in obese

women. Obes Res 1996; 4:55-63.

7. Piccirillo G, Vetta F, Viola E, et al: Heart rate and blood

pressure variability in obese normotensive subjects. Int

J Obes Relat Metab Disord 1998; 22:741-750.

8. O'Brien IA, O'Hare P, Corrall RJ: Heart rate variability

in healthy subjects: Effect of age and the derivation of

normal ranges for tests of autonomic function. Br Heart

J 1986; 55:348-354.

9. Rabbia F, Silke B, Conterno A, et al: Assessment of

cardiac autonomic modulation during adolescent

obesity. Obes Res 2003; 11:541-548.

10. Riva P, Martini G, Rabbia F, et al: Obesity and autonomic

function in adolescence. Clin Exp Hypertens

2001; 23:57-67.

11. Martini G, Riva P, Rabbia F, Molini V, Ferrero GB, Cerutti

F: Heart rate variability in childhood obesity. Clin Auton

Res 2001; 11:87-91.

12. Nagai N, Matsumoto T, Kita H, Moritani T: Autonomic

Nervous System Activity and the State and Development

of Obesity in Japanese School Children. Obes Res

2003; 11:25-32.

13. Fu CC, Li YM, Yeh JI, Pei D, Lin HH, Lo HM: Prevalence

of overweight adolescents and associated factors

in Hualien city. Tzu Chi Med J 2004; 16:301-307.

14. Department of Health of Taiwan: Definition of obesity.

In: Taiwan Medical Association for the study of obesity.

Bulletin. February 2003.

15. Kuo TB, Yien HW, Hseu SS, et al: Diminished vasomotor

component of systemic arterial pressure signals and

baroreflex in brain death. Am J Physiol 1997; 273:

H1291-1298.

16. Yien HW, Hseu SS, Lee LC, Kuo TB, Lee TY, Chan

SH: Spectral analysis of systemic arterial pressure and

heart rate signals as a prognostic tool for the prediction

of patient outcome in the intensive care unit. Crit Care

Med 1997; 25:258-266.

17. No authors listed: Heart rate variability. Standards of

measurement, physiological interpretation and clinical

use. Task Force of the European Society of Cardiology

and the North American Society of Pacing and

Electrophysiology. Circulation 1996; 93:1043-1065.

18. Kuo TB, Chan SH: Continuous, on-line, real-time spectral

analysis of systemic arterial pressure signals. Am J

Physiol 1993; 264:H2208-2213.

19. Tsuji H, Venditti FJ Jr, Manders ES, et al: Reduced heart

rate variability and mortality risk in an elderly cohort.

The Framingham Heart Study. Circulation 1994; 90:878-

883.

20. Kuo TB, Lin T, Yang CC, Li CL, Chen CF, Chou P: Effect

of aging on gender differences in neural control of

heart rate. Am J Physiol 1999; 277:H2233-2239.

21. Matthews DR, Hosker JP, Rudenski AS, Naylor BA,

Treacher DF, Turner RC: Homeostasis model

assessment: Insulin resistance and beta-cell function

from fasting plasma glucose and insulin concentrations

in man. Diabetologia 1985; 28:412-419.

22. Fouad FM, Tarazi RC, Ferrario CM, Fighaly S, Alicandri

C: Assessment of parasympathetic control of heart rate

by a noninvasive method. Am J Physiol 1984; 246:

H838-842.

23. Quilliot D, Fluckiger L, Zannad F, Drouin P, Ziegler O:

Impaired autonomic control of heart rate and blood pressure

in obesity: Role of age and of insulin-resistance.

Clin Auton Res 2001; 11:79-86.

24. Pagani M, Montano N, Porta A, et al: Relationship between

spectral components of cardiovascular variabilities

and direct measures of muscle sympathetic nerve

activity in humans. Circulation 1997; 95:1441-1448.

25. Montano N, Ruscone TG, Porta A, Lombardi F, Pagani

M, Malliani A: Power spectrum analysis of heart rate

variability to assess the changes in sympathovagal balance

during graded orthostatic tilt. Circulation 1994; 90:

1826-1831.

26. Bigger JT Jr, Fleiss JL, Steinman RC, Rolnitzky LM,

Schneider WJ, Stein PK: RR variability in healthy,

middle-aged persons compared with patients with

chronic coronary heart disease or recent acute myocardial

infarction. Circulation 1995; 91:1936-1943.

27. Huikuri HV, Pikkujamsa SM, Airaksinen KE, et al: Sexrelated

differences in autonomic modulation of heart rate

in middle-aged subjects. Circulation 1996; 94:122-125.

28. Ramaekers D, Ector H, Aubert AE, Rubens A, Van de

Werf F: Heart rate variability and heart rate in healthy

volunteers. Is the female autonomic nervous system

cardioprotective? Eur Heart J 1998; 19:1334-1341.

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