The structure of the relationship between indicators of aerobic performance, central hemodynamics, microcirculation and hemorheology

Introduction. In physiological research, an important task is to find the relationship between the various functional parameters of the organism, its individual systems and its elements. These relationships can be complex, mediated by additional factors and when using pair correlation, they cannot be detected. In this case, it seems justified to use factor analysis to search for the hidden structure of relationships between many variables. The aim. Factor analysis of a set of data, including indicators of aerobic performance, central hemodynamics, microcirculation (MC) and hemorheology.

Materials and methods. The study involved 172 men aged 20 to 60 years. Physical performance was determined using the PWC170 test. Microcirculation parameters were determined using biomicroscopy and Laser Doppler Imaging (LDI). The complex of hemorheological characteristics included the viscosity of blood and plasma, aggregation and deformability of erythrocytes. Statistical processing, including factor analysis, was carried out using the Statistica 6.0 software package. The factorial model included 32 parameters. When interpreting the results of factor analysis, variables with factor loadings of more than 0.60 were considered.

Results. Three factors were identified, which accounted for 71 % of the total variance. The first factor closely correlated with the level of the body’s aerobic performance parameters and its adaptive potential. The second factor correlated with hemodynamic parameters at the central and microcirculatory level, including integral rheological parameters. The third factor correlated with the parameters of microvessels and the rheological properties of erythrocytes.

Conclusions. The constructed factor model demonstrates the level structure of the relationships of indicators of aerobic performance, central hemodynamics, microcirculation, and hemorheology. The selected factors – the hidden elements of this structure linking individual variables – were interpreted as levels of integration: organismic, systemic and microlevel.

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