Abstract
It is well known that degenerative-dystrophic and metabolic changes in the musculoskeletal system progress with age and lead to the development of pathologies, including osteoporosis, sarcopenia etc. With the development of new methods for studying bone and muscle systems, it is important to predict the biological age of the musculoskeletal system to assess the rate of ageing and the possibilities for preventing these diseases and their consequences. The study aimed to develop a mathematical model for the assessment of the biological age of the musculoskeletal system, taking into account indicators of bone mineral density (BMD), trabecular bone score (TBS), parameters of body composition, and some functional tests. 77 women and 44 men aged 30 to 90 years without significant somatic pathology were examined. Measurements of BMD and TBS, as well as indicators of body composition, were performed using dual-energy X-ray absorptiometry (DXA). Statistical processing was performed using the Statistica 7.0 software (StatSoft Inc., USA). The results indicated a significant correlation between age and the BMD and TBS parameters, and body composition indicators. A model for determining the musculoskeletal system’s biological age was built using multiple regression analysis with stepwise inclusion of informative indicators. The model's coefficient of determination (R2) was 0.77, indicating its high significance. The mean absolute error of age calculation after correction for the regression equation error was 5.21 years. The developed model for assessing the musculoskeletal system’s biological age had high accuracy and can be used to assess the risk of osteoporosis, sarcopenia, and complications. ________________________________________________________________________________________Keywords: biological age; musculoskeletal system; osteoporosis; sarcopenia
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