Prevalence and Associated Risk Factors of Cognitive Frailty: A Systematic Review and Meta-Analysis

Abstract

ObjectiveCurrently, the prevalence of CF (Cognitive Frailty) is not very clear, and the relationship between CF and its associated risk factors has not been accurately evaluated. Therefore, it is necessary to conduct a systematic review and meta-analysis further to understand CF's prevalence and associated factors.MethodsEmbase, PubMed, Web of Science, Ovid, and Cochrane were systematically searched for articles exploring the prevalence of CF, the deadline of searching date was up to March 2021. For the prevalence of CF, the events of CF and the total number of patients in every included study were extracted to estimate the prevalence of CF. For associated factors of CF, Odds Ratios (ORs) with (corresponding) 95% confidence intervals (CIs) were used for estimations.ResultsFirstly, the estimated prevalence of CF I (Cognitive Frailty in the model I) was 16%, 95% CI (0.13–0.19), and the estimated prevalence of CF II (Cognitive Frailty in model II) was 6%, 95% CI (0.05–0.07). Secondly, both lower engagement in activities and age were calculated to be independent risk factors of CF, and the OR (95% CI) was 3.31 (2.28–4.81) and 1.10 (1.04–1.16), respectively. Finally, depression was also a prominent risk factor of CF, with the overall OR (95% CI) as 1.57 (1.32–1.87).ConclusionCF was a high prevalence in community older. The various assessment scales and the different cutoff values of diagnostic criteria would affect the prevalence of CF. Lower engagement in activities, age, and depression was the risky factor of CF.Systematic Review Registrationhttp://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42019121369.

Cross sectional association between cognitive frailty and disability among community-dwelling older adults: Focus on the role of social factors

“…Thus, subjective satisfaction with relationships including friends, community may be more influential on the health outcomes of older adults than the structural aspects of social relationships, which is supported by previous studies ( 39 , 40 ). Participation in social activities and social contacts was most consistently associated with preservation of global cognitive function ( 13 , 41 – 43 ) and prevention or slowing down of the process of physical frailty ( 44 ) across all study types. The theory of “use it or lose it” ( 45 ) suggests that the brain can be considered a muscle; thus, social activities may stimulate the brain and contribute to the preservation of cognitive function.…”

Mediating Effect of Loneliness in the Relationship between Depressive Symptoms and Cognitive Frailty in Community-Dwelling Older Adults

“…As far as we know, no research has tested the mediating role of loneliness between depression and cognitive frailty using the mediating model. Previous studies showed that depression is associated with cognitive frailty [ 10 , 39 ], but the potential mechanism has not been revealed. Our results demonstrated that older adults with depressive symptoms have a stronger sense of loneliness, which is related to their greater possibility of cognitive frailty.…”

Impact of frailty, mild cognitive impairment and cognitive frailty on adverse health outcomes among community-dwelling older adults: A systematic review and meta-analysis

“…Frailty has been described as a multidimensional clinical gerontological syndrome ( 6 , 7 ). A cumulative decline of multiple physiological systems leads to reduced energy reserves, increased susceptibility to stressors, and dysregulated physiological system dynamic balance ( 8 , 9 ).…”

“…The former is indicated by mild cognitive impairment (MCI) (CDR = 0.5), and the latter by a pre-MCI subjective cognitive decline (SCD) (CDR = 0) and positive biomarkers of neurodegeneration ( 17 ). A meta-analysis showed that the estimated prevalence of cognitive frailty was 6% in older people community-dwelling ( 7 ). Recognition of associations between predictors as mild cognitive impairment and frailty alone and combined, and multiple adverse health outcomes, could not only inform treatment decisions and goals of care, but also provide predictors for early identification and intervention among the increasing old populations to reduce the occurrence of adverse health outcomes ( 18 ).…”