The use of geometric facial morphometry as a marker of metabolicassociated disorders. A review of the literature with the inclusion of our own data

Metabolic-associated diseases are complex disorders of lipid, protein and carbohydrate metabolism, complications of which (diabetes mellitus, arterial hypertension, obesity and others) often cause disability or premature death. In addition, the above-mentioned lesions are most often age-related diseases and are accompanied by anatomical, functional, and structural disorders, which are clearly visible in facial features. The aim: analysis of literature data on the study of external manifestations of metabolic-associated diseases using the method of geometric facial morphometry. The article presents an analysis of literature sources, which include systematic reviews, case reports and clinical trials, meta-analyses over the past 15 years, for which the PubMed, Scopus, Web of Science and Google Scholar databases were used to search. To identify the features of facial changes associated with the state of general health, it is advisable to use geometric morphometry — a method that, using certain landmarks, allows you to quantitatively assess facial features. The method consists of anthropometric measurements and can be used to screen for certain diseases and contribute to the development of treatment strategies. A digital two-dimensional photograph is used for screening, on which landmarks are then distributed with subsequent analysis. The article presents the results of studies on the use of the geometric morphometry method in general medicine. Research results prove that populations of people with metabolic disorders have anatomically and morphometrically similar facial features. It is noted that patients with diabetes mellitus have characteristic facial changes: asymmetry or elongation of the face, drooping of the brow ridges, compression of the face to the center and a pronounced skin fold around the eyes. Conclusions. Detection and analysis of facial changes associated with manifestations of the most common metabolic diseases, as well as compiling a bank of photographs and comparing them according to certain anthropometric landmarks, can contribute to the development of rapid non-invasive methods of monitoring and early screening.