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Cluster Analysis of the Associations among Physical Frailty, Cognitive Impairment and Mental Disorders

Authors
  • Majnarić, Ljiljana Trtica1, 2
  • Bekić, Sanja3, 4
  • Babič, František5
  • Pusztová, Ľudmila5
  • Paralič, Ján5
  • 1 Department of Internal Medicine, Family Medicine and the History of Medicine, Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
  • 2 Department of Public Health, Faculty of Dental Medicine and Health, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
  • 3 General Medical Practice, Osijek, Croatia
  • 4 Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
  • 5 Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Košice, Slovakia
Type
Published Article
Journal
Medical Science Monitor
Publisher
"International Scientific Information, Inc."
Publication Date
Sep 15, 2020
Volume
26
Identifiers
DOI: 10.12659/MSM.924281
PMID: 32929055
PMCID: PMC7518080
Source
PubMed Central
Keywords
License
Green

Abstract

Background 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/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.

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