Author: Patrick Eggenberger1 2, Simon Annaheim1, Kerstin A Kündig1 2, René M Rossi1, Thomas Münzer3 4, Eling D de Bruin2 5
Affiliation: <sup>1</sup> Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Biomimetic Membranes and Textiles, St. Gallen, Switzerland.
<sup>2</sup> Department of Health Sciences and Technology, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich, Switzerland.
<sup>3</sup> Geriatrische Klinik St. Gallen, St. Gallen, Switzerland.
<sup>4</sup> Department of Geriatric Medicine, University of Zurich, Zurich, Switzerland.
<sup>5</sup> Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
Conference/Journal: Front Aging Neurosci
Date published: 2020 Jul 15
Other:
Volume ID: 12 , Pages: 197 , Special Notes: doi: 10.3389/fnagi.2020.00197. , Word Count: 350
Heart rate variability (HRV) mirrors autonomic nervous system activities and might serve as a parameter to monitor health status in older adults. However, it is currently unknown which functional health measures, including cognitive, physical, and gait performance parameters, are most strongly related to HRV indices. This knowledge would enable implementing HRV assessments into health monitoring routines and training planning for older adults. Simultaneous cognitive-motor and exergame training may be effective to improve HRV indices but has not been investigated yet. Eighty-nine healthy older adults (≥70 years of age) were randomized into three groups: (1) virtual reality video game dancing, i.e., exergaming (DANCE); (2) treadmill walking with simultaneous verbal memory training (MEMORY); or (3) treadmill walking only (PHYS). Strength and balance exercises complemented each program. Over 6 months, two weekly 1-h training sessions were performed. HRV indices (standard deviation of N-N intervals, SDNN; root mean square of successive R-R interval differences, RMSSD; and absolute power of high-frequency band (0.15-0.4 Hz), HF power) and various measures of cognitive, physical, and gait performance were assessed at baseline and after 3 months and 6 months. Multiple linear regression analyses with planned comparisons were calculated. At baseline, 8-12% of HRV variance was significantly explained by cognitive executive functions and leg strength (inversely related). Verbal long-term memory, aerobic and functional fitness, and gait performance did not contribute to the model (SDNN: R2 = 0.082, p = 0.016; RMSSD: R2 = 0.121, p = 0.013; HF power: R2 = 0.119, p = 0.015). After 6 months, DANCE improved HRV indices, while MEMORY and PHYS did not (time × intervention interactions: first-contrast DANCE/MEMORY vs. PHYS: SDNN p = 0.014 one-tailed, ΔR 2 = 0.020 and RMSSD p = 0.052 one-tailed (trend), ΔR 2 = 0.007; second-contrast DANCE vs. MEMORY: SDNN p = 0.002 one-tailed, ΔR 2 = 0.035, RMSSD p = 0.017 one-tailed, ΔR 2 = 0.012, and HF power p = 0.011 one-tailed, ΔR 2 = 0.013). We conclude that mainly cognitive executive functions are associated with HRV indices and that exergame training improves global and parasympathetic autonomic nervous system activities in older adults. Periodic assessments of HRV in older citizens could be particularly beneficial to monitor cognitive health and provide indications for preventative exercise measures.
KEYWORDS: cognitive–motor training; dual-task training; elderly; executive functions; functional fitness; gait variability; normalized heart rate variability; verbal long-term memory.
PMID: 32760267 PMCID: PMC7373948 DOI: 10.3389/fnagi.2020.00197