Features of the body's adaptation in a state of relative physiological rest

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Arbab A.V.
I.M. Sechenov First Moscow State Medical University, Moscow, Baku

Panakhova R.N.
I.M. Sechenov First Moscow State Medical University, Moscow, Baku

Bulgakova Ya.V.
I.M. Sechenov First Moscow State Medical University, Moscow, Baku

Pokhachevsky A.L.
I.M. Sechenov First Moscow State Medical University, Moscow, Baku
Ryazan State Medical University named after I.P. Pavlov, Ryazan

Keywords: physical activity, binary marker, functional state, youth

Introduction

Heart rate (HR) variability, as a dynamic response to autonomic, humoral, and reflex influences, serves as a sensitive indicator of the organism’s adaptive capacity. Analysis of HR variability reveals the characteristics of autonomic regulation and provides insight into the current functional state (FS) of the body [1, 2].

Research objective

To identify critical markers that determine the functional state of the organism in a young adult population.

Methodology and research organization

A mixed group of 54 young individuals aged 18–23 years, varying in training status, was studied. In the supine position (clinostasis), the following heart rate variability (HRV) parameters were analyzed:

  • Total Power (TP – 0.003–0.40 Hz, ms²/Hz): total neurohumoral influence on HR;
  • Relative (%) and absolute values of High-Frequency (HF – parasympathetic, 0.15–0.4 Hz), Low-Frequency (LF – sympathetic, 0.04–0.15 Hz), and Very Low-Frequency (VLF – humoral-metabolic, 0.003–0.04 Hz) components;
  • pNNx: percentage of adjacent normal-to-normal intervals differing by ≥10 ms up to ≥100 ms.
Statistical analysis was performed using Statistica 10.0 and Microsoft Excel 2021. Group differences were assessed via the Mann–Whitney U test; statistical significance was set at p < 0.05. Cluster analysis (K-means method) was used to form homogeneous subgroups based on HRV profiles.
Results and discussion

Bimodality in the distribution of HRV spectral power revealed heterogeneity within the sample. Cluster analysis identified two distinct groups:

  • Group 1 (n = 36): non-athletes with no systematic physical training;
  • Group 2 (n = 18): active athletes in cyclic sports, training ≥5 times per week.
HRV parameters in the athletic group significantly exceeded those of the non-athletic group:
  • TP: 6730 vs. 2380 ms²/Hz (2.8× higher);
  • LF: 1573 vs. 777 ms²/Hz (2.0× higher);
  • HF: 2150 vs. 635 ms²/Hz (3.4× higher).
The sympathovagal balance (LF/HF ratio) was higher in the non-athletic group (1.0 vs. 0.7), indicating dominant sympathetic tone. Similarly, the relative contribution of slow spectral components was greater in non-athletes: VLF% (36% vs. 29%; 1.25×) and LF% (32% vs. 27%; 1.2×). Conversely, HF% remained significantly higher in athletes (37.5% vs. 27%; 1.4×), reflecting superior parasympathetic modulation.
These findings indicate not only greater overall adaptive reserves in athletes but also a fundamental qualitative difference: dominance of rapid, parasympathetically mediated regulatory mechanisms (HF component). The LF/HF ratio corroborates this conclusion.
pNNx indices declined progressively from pNN10 to pNN90 in both groups, but at markedly different rates. While initial pNN10 differed by only 9% (75% in non-athletes vs. 86% in athletes), pNN50 dropped sharply in non-athletes (9.16%) compared to athletes (37%). By pNN70 and pNN80, values in non-athletes approached 1% (1.2% and 0.8%), while athletes maintained levels of 23% and 18%, respectively.
All pNNx values were statistically significantly higher in athletes, and the magnitude of intergroup differences increased progressively:
  • pNN10: +9% (1.15×);
  • pNN30: +25.5% (1.8×);
  • pNN50: +27.45% (4.0×);
  • pNN60: +25% (7.3×);
  • pNN70: +22% (19.3×);
  • pNN80: +17% (22×).
This demonstrates that the distinguishing feature of the athletic group is not merely elevated long-duration RR intervals, but an accelerating divergence in their prevalence along the pNNx scale — indicating enhanced vagal persistence and resilience under stress.
 
Conclusion

Physical activity is the primary critical marker determining functional state in youth. The cluster-based differentiation between athletes and non-athletes reveals a fundamental physiological distinction: athletes exhibit superior functional regulation characterized by dominant high-frequency (parasympathetic) modulation and significantly greater persistence of long-term heart rate variability. This reflects a more robust, flexible, and resilient autonomic control system, directly linked to regular physical training.

References
  1. Lapkin, M.M., Trutneva, E.A. & Kalinin, A.V. (2022) Sistemnaya organizatsiya fiziologicheskikh funktsii, obespechivayushchaya maksimal’nuyu fizicheskuyu rabotosposobnost’ [Systemic organization of physiological functions ensuring maximal physical work capacity], Chelovek. Sport. Meditsina, 22(S2), pp. 37–45.
  2. Mikhailov, V.M. (2017) Variabel’nost’ ritma serdtsa (novyy vzglyad na staruyu paradigmu) [Heart rate variability (a new look at an old paradigm)]. Ivanovo: Neirosoft, 516 p.