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Pulse rate variability and health-related quality of life assessment with the Short Form-8 Japanese version in the general Japanese population – Scientific Reports


Study subjects

We enrolled 6013 men and women, 30–79 years of age, who lived in Ozu and Toon Cities in Ehime prefecture, Japan, from 2009 to 2012 and 2014–2018 (Toon City only). Both cities are in rural areas of Shikoku Island Japan. We excluded subjects who did not have a PRV examination (n = 33) and who had atrial fibrillation on an electrocardiogram (ECG) (n = 37). After the exclusion of those who did not respond to the HRQOL questionnaire (n = 36), 5908 individuals remained and were included in the analysis.

This study was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants. The study protocol was approved by the Human Ethics Review Committee of the Faculty of Medicine, Oita University (approval number, 2114).

Measurements

Blood pressure was measured twice with an automatic sphygmomanometer (BP-103iII; OMRON Colin Co., Tokyo, Japan) with the subject in the sitting position after a rest of at least 5 min. We used the mean of the two measurements for the analysis. The use of antihypertensive drugs was ascertained by questionnaire. Diabetes was defined as hemoglobin A1c (HbA1c) ≥ 6.5% or current use of anti-diabetes agents. HbA1c was measured with high-performance liquid chromatography (Ozu City) and the immunoagglutination inhibition method (Toon City). Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared.

HRQOL was assessed with the Short Form-8 (SF-8) Japanese version questionnaire1, which consists of eight subscales—general health (GH), physical functioning (PF), role physical (RP), bodily pain (BP), vitality (VT), social functioning (SF), mental health (MH), and role emotional (RE)—and two summary scores—the physical component score (PCS), which consists of GH, PF, RP, and BP and the mental component score (MCS), which consists of VT, SF, MH, and RE. All subscales and summary scores were standardized in the general Japanese population (mean = 50 and standard deviation = 10). In the present study, poor HRQOL was defined as a score of less than 50 for each subscale and summary score.

A self-administered questionnaire was used to assess medical history (heart disease, stroke, and kidney disease), smoking habits (≥ 20 cigarettes/day, 1–19 cigarettes/day, past smoker, and never smoker), regular alcohol drinking, exercise habits, and sleep duration. Current smokers were defined as individuals who had smoked 100 cigarettes in their lifetime and who currently smoked cigarettes. Exercise was defined as doing continuous sports or physical exercise ≥ 2 times/week during the year. Unhealthy sleep duration was defined as < 6-h or ≥ 9-h of sleep per day26.

Assessment of autonomic function

Analysis of PRV was performed with the TAS9 device (YKC Co. Ltd, Japan) and its software to assess cardiac autonomic control. The pulse rate was recorded for 5 min with a fingertip pulse wave sensor using a photoplethysmographic signal. The sensor was attached to the index finger, with the subject in the sitting position after a rest of at least 5 min, with the software filtering out arrhythmias and artifacts. Filtering was based on the Butterworth bandpass filter method to detect the normal-to-normal intervals accurately27. The five-minute PRV measurement procedure, including PRV indices and standardization, was based on the recommendation of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology28. The Task Force recommends appropriate HRV parameters in the time and frequency domains and states that five-minute recordings with a stationary system are preferable. The sampling frequency for all recordings was 1000 Hz. PRV obtained from the fingertip pulse wave sensor is comparable with that of an ECG signal29.

All PRV assessments were done between 10:00 am and 12:00 pm to control for daily variation. We maintained a comfortable room temperature with air conditioners. Participants were required to have at least a five-minute rest before the measurement. The TAS9 software-provided resting heart rate (RHR) was expressed as beats per minute (bpm), and the following time-domain measures of PRV were then determined: standard deviation of normal-to-normal intervals (SDNN), root mean square of successive difference (RMSSD), and percentage differences between normal NN intervals > 50 ms (pNN50). PRV in the frequency domain was calculated using the fast Fourier Transform with a sample rate of 3 Hz. The area under the curve fitted by the power spectral density was measured for the frequency bands of low-frequency (LF) power (0.04–0.15 Hz) and high-frequency (HF) power (0.15–0.40 Hz).

In general, SDNN reflects the total modulation of autonomic function, while RMSSD and pNN50 reflect vagal control of the heart. LF power reflects both sympathetic and parasympathetic stimulation of the heart, and HF power reflects vagal activity28.

Although PRV-derived parameters were determined based on five-minute recordings, we confirmed that they were significantly correlated with those provided by 24-h Holter ECG assessment30.

Statistical analysis

Because of their skewed distribution, SDNN, RMSSD, LF power, and HF power were log-transformed before analysis. An analysis was also carried out to measure differences in the means of age, BMI, RHR, systolic blood pressure (SBP), and the proportions of men and women, subjects with hypertension, diabetes, smoking, regular alcohol drinking, regular exercise, unhealthy sleep duration, and medical history, grouped by PCS and MCS (poor versus good conditions). The differences between groups were tested with a t-test or chi-square test. While stratified by community, we created a sex and age-adjusted model, and a multivariable model including covariates, i.e., BMI (continuous), hypertension (Yes or No), diabetes (Yes or No), smoking (≥ 20 cigarettes, 1–19 cigarettes, past smoker, and never smoker), regular alcohol drinking (Yes or No), regular exercise (Yes or No), unhealthy sleep duration (Yes or No), and medical history (Yes or No) and to estimate odds ratios (ORs) and 95% confidence intervals (Cis) for poor HRQOL. Trend tests were performed in the two models with linear or quadratic equations for a linear or nonlinear trend test, respectively. To illustrate the nonlinear trends of lnSDNN, lnRMSSD, lnLF power, and lnHF power for poor HRQOL, the generalized additive model (GAM) with a smoothing spline [degree of freedom = 3] was adopted in the logistic regression model31, adjusting for covariates in the multivariable-adjusted model. Statistical significance was assumed at P < 0.05. All statistical analyses were performed with SAS software, version 9.4 (SAS Institute, Inc., Cary, NC, USA).



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