AUTHOR=Plaza-Florido Abel , Migueles Jairo H. , Mora-Gonzalez Jose , Molina-Garcia Pablo , Rodriguez-Ayllon Maria , Cadenas-Sanchez Cristina , Esteban-Cornejo Irene , Solis-Urra Patricio , de Teresa Carlos , Gutiérrez Ángel , Michels Nathalie , Sacha Jerzy , Ortega Francisco B. TITLE=Heart Rate Is a Better Predictor of Cardiorespiratory Fitness Than Heart Rate Variability in Overweight/Obese Children: The ActiveBrains Project JOURNAL=Frontiers in Physiology VOLUME=10 YEAR=2019 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2019.00510 DOI=10.3389/fphys.2019.00510 ISSN=1664-042X ABSTRACT=

Cardiac autonomic function can be quantified through mean heart rate (HR) or heart rate variability (HRV). Numerous studies have supported the utility of different HRV parameters as indicators of cardiorespiratory fitness (CRF). However, HR has recently shown to be a stronger predictor of CRF than HRV in healthy young adults, yet these findings need to be replicated, in other age groups such as children. Therefore, this study aimed: (1) to study the associations between indicators of cardiac autonomic function (HR, standard and corrected HRV parameters) and CRF in overweight/obese children; and (2) to test which of the two indicators (i.e., HR or HRV) is a stronger predictor of CRF. This study used cross-sectional baseline data of 107 overweight/obese children (10.03 ± 1.13 years, 58% boys) from the ActiveBrains project. Cardiac autonomic indicators were measured with Polar RS800CX®. CRF was assessed using a gas analyzer while performing a maximal incremental treadmill test. Correlations and stepwise linear regressions were performed. Mean HR and standard HRV parameters (i.e., pNN50, RMSSD, and SDNN) were associated with CRF (r coefficients ranging from -0.333 to 0.268; all p ≤ 0.05). The association of HR with CRF persisted after adjusting for sex, peak height velocity (PHV), adiposity moderate-to-vigorous physical activity, energy intake and circadian-related variable intradaily variability of activity patterns whilst for HRV parameters (i.e., pNN50, RMSSD, and SDNN) disappeared. Stepwise linear regression models entering HR and all HRV parameters showed that mean HR was the strongest predictor of CRF (β = -0.333, R2 = 0.111, p < 0.001). Standard and corrected HRV parameters did not provide additional value to the coefficient of determination (all p > 0.05). Our findings suggest that HR is the strongest indicator of CRF. It seems that quantification of HRV parameters in time and frequency domain do not add relevant clinical information about the cardiovascular health status (as measured by CRF) in overweight/obese children beyond the information already provided by the simple measure of HR.