Heart rate variability and baroreflex sensitivity in subjects without heart disease : effects of age, sex and cardiovascular risk factors
1University of Oulu, Faculty of Medicine, Department of Internal Medicine
|Online Access:||PDF Full Text (PDF, 4.4 MB)|
|Persistent link:|| http://urn.fi/urn:isbn:9514252276
|Publish Date:|| 1999-04-15
|Thesis type:||Doctoral Dissertation
|Defence Note:||Academic Dissertation to be presented with the assent of the Faculty of Medicine, University of Oulu, for public discussion in Auditorium 10 of the University Hospital of Oulu, on May 8th, 1999, at 10 a.m.
Docent Juha Hartikainen
Docent Markku Mäkijärvi
Healthy subjects show wide interindividual variation in their heart rate behavior, but the factors affecting heart rate dynamics are not well known. This research was undertaken to evaluate heart rate variability (HRV) and baroreflex sensitivity (BRS) in a large random sample of subjects without evidence of heart disease, and to estimate the relation of heart rate behavior to age, sex and cardiovascular risk factors.
Short-term HRV was analyzed from 15-minute periods of standardized recording in supine and upright positions using time and frequency domain measures, and BRS was calculated using the Valsalva maneuver in an original randomly selected population of 600 hypertensive and 600 control middle-aged subjects. In addition, HRV was analyzed from the same segments using new measures based on fractals and complexity (chaos theory) of R–R interval dynamics in the same random population, and from 24-hour period in 114 healthy subjects aged from 1 to 82 years.
Large interindividual variation was observed in the measures of HRV and BRS in middle-aged subjects; coefficient of variation (CV) of the standard deviation of R–R intervals (SDNN) 39% (54 ± 21 ms) and CV of BRS 49% (9.9 ± 4.9 ms/mmHg). In healthy middle-aged men, SDNN was weakly related to age (r = −0.19, p < 0.01), HDL cholesterol (0.19, p < 0.01), serum insulin (−0.23, p < 0.001) and triglyceride (−0.25, p < 0.001) levels. In women, SDNN was only related to insulin levels (r = −0.23, p < 0.001). BRS was related to systolicblood pressure (r = −0.31 and -0.30, in men and women respectively, p < 0.001 for both) and blood glucose (r = −0.25, p < 0.01) and serum insulin levels (r = −0.34, p < 0.001) in women. Lesser intersubject variation was observed in the non-linear measures of HRV; CV 14% of short-term scaling exponent (a1), a measure of fractal-like correlation properties of HRV, (1.21 ± 0.17) and CV 12% of approximate entropy, a measure of complexity, (1.13 ± 0.14). Neither a1 or ApEn was related to any risk factors. Women had lower overall short-term HRV (p < 0.01) and BRS (p < 0.001), but a higher spectral high-frequency component of HRV, higher ApEn and lower a1 (p < 0.001 for all) compared to men. The impairment in overall HRV was confined to the hypertensive subjects with metabolic features of the insulin resistance syndrome (IRS, n = 69), but the BRS and spectral high-frequency component were also impaired in hypertensive subjects without IRS compared to normotensive subjects. The 24-hour cardiac interbeat interval dynamics changed markedly from childhood to old age. Children showed similar complexity and fractal correlation properties of R–R intervals as young adults. Healthy aging resulted in R–R interval dynamics with higher regularity and predictability and altered fractal scaling.
The traditional measures of HRV and BRS are weakly related to many cardiovascular risk factors in subjects without heart disease, but the interindividual variation of HRV and BRS is only partly explained by these factors, suggesting a genetic background of the intersubject variation in cardiovascular autonomic regulation. The new dynamical measures of HRV show less interindividual variation than the conventional measures of HRV in healthy subjects and are not related to cardiovascular risk variables, suggesting that these dynamical measures quantify the “intrinsic” capacity of a healthy cardiovascular control system without the significant influence of life-style, metabolic or demographic variables. However, there are sex and age-related differences also in the fractal and complexity measures of heart rate behavior.
Acta Universitatis Ouluensis. D, Medica
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