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Development of a Heart Rate Variability Prediction Equation Through Multiple Linear Regression Analysis Using Physical Characteristics and Heart Rate Variables

Authors :
Sung-Woo Kim
Hun-Young Park
Hoeryong Jung
Sin-Ae Park
Kiwon Lim
Source :
INQUIRY: The Journal of Health Care Organization, Provision, and Financing. 60:004695802311694
Publication Year :
2023
Publisher :
SAGE Publications, 2023.

Abstract

Heart rate variability (HRV) is an effective tool for objectively evaluating physiological stress indices in psychological states. This study aimed to develop multiple linear regression equations to predict HRV variables using physical characteristics, body composition, and heart rate (HR) variables (eg, sex, age, height, weight, body mass index, fat-free mass, percent body fat, resting HR, maximal HR, and HR reserve) in Korean adults. Six hundred eighty adults (male, n = 236, female, n = 444) participated in this study. HRV variable estimation multiple linear regression equations were developed using a stepwise technique. The regression equation’s coefficient of determination for time-domain variables was significantly high (SDNN = adjusted R2: 73.6%, P 2: 84.0%, P 2: 98.0%, P 2: 99.5%, P 2: 75.0%, P 2: 77.6%, P 2: 30.1%, P 2: 71.3%, P

Subjects

Subjects :
Health Policy

Details

ISSN :
19457243 and 00469580
Volume :
60
Database :
OpenAIRE
Journal :
INQUIRY: The Journal of Health Care Organization, Provision, and Financing
Accession number :
edsair.doi...........81df737c4f99ea83a72a589c488dc516
Full Text :
https://doi.org/10.1177/00469580231169416