Abstract:
Considering the existence of different ways of the course of multiple sclerosis, the
disability caused by this disease, modern medicine needs the creation of new, easy-to use and cheap methods to solve this issue. Promising in this case may be the use of
clinical anthropometry, which is already successfully used to predict the forms of
development and severity of various diseases of various human organ systems. The
objective of the study was to construct and analyze discriminant models predicting the
likelihood and characteristics of multiple sclerosis progression in young Ukrainian
women, based on anthropometric and somatotypological parameters. A clinical laboratory and anthropo-somatotypological examination was conducted on 59 young
Ukrainian women diagnosed with multiple sclerosis. Disability levels were assessed
using the Expanded Disability Status Scale. The control group consisted of primary
anthropometric and somatotypological data from 101 healthy Ukrainian women of the
same age group (sourced from the database of the Scientific and Research Center of
the National Pirogov Memorial Medical University, Vinnytsya). Discriminant models
predicting the occurrence and progression of multiple sclerosis based on body anthroposomatotypological parameters were constructed using the licensed “Statistica 6.0”software. The analysis revealed significant discrimination between healthy individuals
and the general multiple sclerosis patient group, as evidenced by the discriminant
equations (Wilks’ Lambda=0.052, p<0.001). Key contributors to the discrimination
models for distinguishing healthy women from those with multiple sclerosis included
pelvic dimensions (37.50 %, contributing the most), body circumferences and head
dimensions (25.0 % each), and the transverse lower thoracic diameter of the torso
(12.5 %). Further analysis differentiated women with multiple sclerosis based on the
severity of their symptoms mild, moderate, or moderately severe also demonstrated
statistically significant differentiation (Wilks’ Lambda=0.349, p<0.001). The most
influential factors for mild, moderate, or moderately severe patients groups in these
models were distal epiphyseal widths of long tubular bones in the extremities (33.33 %,
contributing the most), pelvic conjugate diameter, maximum head length, the
ectomorphic component of somatotype according to Heath-Carter, and the skeletal
mass component according to Matiegka (each contributing 16.67 %). These findings
underscore the importance of anthropometric and somatotypological parameters in
predicting multiple sclerosis occurrence and progression severity in young Ukrainian
women.
