Ventilatory Thresholds Determined from HRV: Comparison of 2 Methods in Obese Adolescents

Abstract

The development of personalised training programmes is crucial in the management of obesity. We evaluated the ability of 2 heart rate variability analyses to determine ventilatory thresholds (VT) in obese adolescents. 20 adolescents (mean age 14.3±1.6 years and body mass index z-score 4.2±0.1) performed an incremental test to exhaustion before and after a 9-month multidisciplinary management programme. The first (VT1) and second (VT2) ventilatory thresholds were identified by the reference method (gas exchanges). We recorded RR intervals to estimate VT1 and VT2 from heart rate variability using time-domain analysis and time-varying spectral-domain analysis. The coefficient correlations between thresholds were higher with spectral-domain analysis compared to time-domain analysis: Heart rate at VT1: r=0.91 vs. =0.66 and VT2: r=0.91 vs. =0.66; power at VT1: r=0.91 vs. =0.74 and VT2: r=0.93 vs. =0.78; spectral-domain vs. time-domain analysis respectively). No systematic bias in heart rate at VT1 and VT2 with standard deviations <6 bpm were found, confirming that spectral-domain analysis could replace the reference method for the detection of ventilatory thresholds. Furthermore, this technique is sensitive to rehabilitation and re-training, which underlines its utility in clinical practice. This inexpensive and non-invasive tool is promising for prescribing physical activity programs in obese adolescents.

Determination of Lactate Thresholds in Maximal Running Test by Heart Rate Variability Data Set

“…Using an exhaustive incremental running test performed on a 200 m track, Cottin et al (8) showed that VT 1 and VT 2 could be assessed through a simple HRV monitor. Recently, these results were further confirmed in obese individuals (9), corroborating the usefulness of the HRV method to identify the first and second physiological threshold in different individuals, during different exercise modes. However, despite the support to use HRV data set when determining VT 1 and VT 2 (7)(8)(9), some aspects should be addressed.…”

“…Recently, these results were further confirmed in obese individuals (9), corroborating the usefulness of the HRV method to identify the first and second physiological threshold in different individuals, during different exercise modes. However, despite the support to use HRV data set when determining VT 1 and VT 2 (7)(8)(9), some aspects should be addressed. No study has currently verified the agreement between breakpoints identified through HRV and LT 1 and LT 2 , as no lactate measures were included in those previous studies (7,8).…”

An investigation into the relationship between heart rate variability and the ventilatory threshold in healthy moderately trained males

“…However , despite revealing a significant relationship between HRV and the VT post‐training, Quinart et al . () found rMSSD slightly underestimated the VT. It may be possible that HRV stabilization points are bound by specific limits with regard to %VO 2Max whilst the VT has a far greater capacity to respon d to training, which is primarily due to the delayed onset of blood lactate at higher exercise intensities.…”

“…The results of this study may be elucidated when looking at the effects of aerobic training on vagal-related stabilization points. Two studies have investigated the effects of an aerobic intervention on both the VT and HRV stabilization points (Quinart et al, 2014;Vasconcellos et al, 2015). In both studies, obese adolescents with a low aerobic capacity were recruited and underwent an aerobic training intervention.…”

“…A more simplistic approach stems on from the seminal work of Tulppo et al (1996) who observed vagal withdrawal occurring around the VT in untrained individuals. Using this novel approach, a strong relationship was observed between time, spectral and nonlinear indices of HRV representative of vagal modulation and the VT in a number of different groups including older adults (Dourado & Guerra, 2013), type 2 diabetics (Sales et al, 2011), chronic heart failure patients (Lepretre et al, 2013) and obese adolescents (Quinart et al, 2014;Vasconcellos et al, 2015). On the other hand, when this technique was applied to well-trained individuals, it generated conflicting results.…”