Relationships between components of physical activity, cardiorespiratory fitness, cardiac autonomic health, and brain-derived neurotrophic factor

Abstract

The aim of this study was to examine the relationships between physical activity, cardiorespiratory fitness, cardiac autonomic health, and brain-derived neurotrophic factor concentrations in healthy men (n = 28) and women (n = 16). Cardiorespiratory fitness ([Vdot]O_2max, litres · min⁻¹) was estimated from heart rate and work rate using a 6-min cycle ergometer test, cardiac autonomic health was assessed from supine measures of heart rate variability using standard telemetry techniques, physical activity was assessed by questionnaire, and brain-derived neurotrophic factor by enzyme-linked immunosorbant assay (ELISA). There was no significant difference in cardiorespiratory fitness between men (3.75 ± 0.84 litres · min⁻¹) and women (3.43 ± 0.72 litres · min⁻¹) (P = 0.206). Similarly, there was no significant difference in Baecke scores (work, sport, and leisure) between men and women. Cardiorespiratory fitness was significantly correlated with seated heart rate (r = −0.445, P = 0.002, n = 44), the heart rate variability measure SD12 (index of cardiac autonomic health) (r = 0.462, P = 0.035, n = 21), and Baecke sport score (r = 0.536, P = 0.000, n = 43). Cardio autonomic health (SD12) was negatively associated with brain-derived neurotrophic factor concentration although this correlation did not attain statistical significance (r = −0.324, P = 0.152, n = 21). The results show that cardiorespiratory fitness was significantly correlated with the Baecke sport (rather than work or leisure) score and cardiac autonomic function (SD12). However, SD12 was not significantly associated with resting concentrations of serum brain-derived neurotrophic factor, a key regulator of energy metabolism and neural plasticity.

Keywords:

• Sport
• cardiorespiratory fitness
• cardiac autonomic health
• serum brain-derived neurotrophic factor

Acknowledgement

The authors would like to thank the Biosignal Analysis and Medical Imaging Group of the University of Kuopio for use of the software for advanced heart rate variability analysis.