Cluster Analysis of the Associations among Physical Frailty, Cognitive Impairment and Mental Disorders
Ljiljana Trtica Majnarić, Sanja Bekić, František Babič, Ľudmila Pusztová, Ján Paralič
Department of Internal Medicine, Family Medicine and the History of Medicine, Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
Med Sci Monit 2020; 26:e924281
Available online: 2020-07-21
Physical frailty, cognitive impairment, and symptoms of anxiety and depression frequently co-occur in later life, but, to date, each has been assessed separately. The present study assessed their patterns in primary care patients aged ≥60 years.
MATERIAL AND METHODS: This cross-sectional study evaluated 263 primary care patients aged ≥60 years in eastern Croatia in 2018. Physical frailty, cognitive impairment, anxiety and depression, were assessed using the Fried phenotypic model, the Mini-Mental State Examination (MMSE), the Geriatric Anxiety Scale (GAS), and the Geriatric Depression Scale (GDS), respectively. Patterns were identified by latent class analysis (LCA), Subjects were assorted by age, level of education, and domains of psychological and cognitive tests to determine clusters.
RESULTS: Subjects were assorted into four clusters: one cluster of relatively healthy individuals (61.22%), and three pathological clusters, consisting of subjects with mild cognitive impairment (23.95%), cognitive frailty (7.98%), and physical frailty (6.85%). A multivariate, multinomial logistic regression model found that the main determinants of the pathological clusters were increasing age and lower mnestic functions. Lower performance on mnestic tasks was found to significantly determine inclusion in the three pathological clusters. The non-mnestic function, attention, was specifically associated with cognitive impairment, whereas psychological symptoms of anxiety and dysphoria were associated with physical frailty.
CONCLUSIONS: Clustering of physical and cognitive performances, based on combinations of their grades of severity, may be superior to modelling of their respective entities, including the continuity and non-linearity of age-related accumulation of pathologic conditions.
Keywords: Cluster Analysis, Frail Elderly, mild cognitive impairment, Primary Health Care