In previous studies, the property of â€˜complexityâ€™ was suggested as a systemic profile of a human cardiovascular system. A loss of complexity in heartbeat time series is a significant bio-marker for assessing the aging and dysfunctions of a cardiac system. In different approaches by phase-rectified signal average (PRSA), a low deceleration capacity (DC) in heart rate variability (HRV) demonstrated a high risk of cardiac sudden death. In this present study, these two nonlinear bio-markers were used to characterize the health of cardiac systems in obesity. A total of 12 obese subjects with a body mass index (BMI) of > 35 and 38 control subjects with a BMI of < 35 were recruited for this study. The complexity and DC of heartbeat time series was evaluated by the multiscale entropy (MSE) and PRSA, respectively. In addition, time-domain and frequency-domain parameters of HRV were also used in HRV analysis. According to the results, the reduced heart rate complexity was associated with obesity. Moreover, aging decreased heart rate variance, which can be observed in many time-domain, frequency-domain, and nonlinear parameters. Moreover, the ratio of the anchor numbers of decelerations and accelerations in the heartbeat time series evaluated using PRSA revealed a specific fluctuation pattern in the heartbeat time series, which represents an asymmetric structure in the heartbeat time series. The increased anchor ratio is associated with the increased BMI. These results imply that a low heart rate complexity is a warning sign of cardiac health to obese subjects. The DC term reflects the total variance of HRV and the decrease of DC is a good assessment of aging.
Keywords: Obesity, heart rate variability, nonlinear parameters