PATIENTS AND METHODS: The available data related to cognitive frailty among a sub-sample of older adults aged 60 years and above (n=815) from two states in Malaysia were analysed. In the LRGS-TUA study, a comprehensive interview-based questionnaire was administered to obtain the socio-demographic information of the participants, followed by assessments to examine the cognitive function, functional status, dietary intake, lifestyle, psychosocial status and biomarkers associated with cognitive frailty. The factors associated with cognitive frailty were assessed using a bivariate logistic regression (BLR).
RESULTS: The majority of the older adults were categorized as robust (68.4%), followed by cognitively pre-frail (37.4%) and cognitively frail (2.2%). The data on the cognitively frail and pre-frail groups were combined for comparison with the robust group. A hierarchical BLR indicated that advancing age (OR=1.04, 95% CI:1.01-1.08, p<0.05) and depression (OR=1.49, 95% CI:1.34-1.65, p<0.001) scored lower on the Activity of Daily Living (ADL) scale (OR=0.98, 95% CI:0.96-0.99, p<0.05), while low social support (OR=0.98, 95% CI:0.97-0.99, p<0.05) and low niacin intake (OR=0.94, 95% CI:0.89-0.99, p<0.05) were found to be significant factors for cognitive frailty. Higher oxidative stress (MDA) and lower telomerase activity were also associated with cognitive frailty (p<0.05).
CONCLUSION: Older age, a lower niacin intake, lack of social support, depression and lower functional status were identified as significant factors associated with cognitive frailty among older Malaysian adults. MDA and telomerase activity can be used as potential biomarkers for the identification of cognitive frailty.
METHODS: Fifteen participants completed the intervention using Wii VR games in this pilot study. Depressive, Anxiety and Stress Scales (DASS) and Capabilities of Upper Extremity (CUE) questionnaires were used to measure psychological well-being and upper limb motor function respectively. Upper limb reaction time was measured using reaction time test.
RESULTS: Results showed that there was a significant difference (p<0.05) in DASS questionnaire and average reaction time score after intervention.
CONCLUSION: There is a potential for using interactive VR games as an exercise tool to improve psychological wellbeing and upper limb reaction time among adults with disabilities.
METHODS: A total of 2084 community dwelling older adults from wave I and II were recruited through a multistage random sampling method. TUG was performed using the standard protocol and scores were then stratified based on with and without mild cognitive impairment (MCI), gender and in a 5-year age groups ranging from ages of 60's to 80's.
RESULTS: 529(16%) participants were identified to have MCI. Past history of falls and medical history of hypertension, heart disease, joint pain, hearing and vision problem, and urinary incontinence were found to have influenced TUG performance. Cognitive status as a mediator, predicted TUG performance even when both gender and age were controlled for (B 0.24, 95% CI (0.02-0.47), β 0.03, t 2.10, p = 0.36). Further descriptive analysis showed, participants with MCI, women and older in age took a longer time to complete TUG, as compared to men with MCI across all age groups with exceptions for some age groups.
CONCLUSION: These results suggested that MCI needs to be taken into consideration when testing older adults using TUG, besides age and gender factors. Data using fast speed TUG may be required among older adults with and without MCI for further understanding.
Design: This was a retrospective cohort study.
Setting: The study was conducted in a community setting.
Participants: The participants were 1,086 community-dwelling older adults, with mean age of 69.6±5.6 years. Participants were categorized into fallers and nonfallers based on their history of falls in the past 12 months.
Method: Participants' sociodemographic data was taken, and SRMQ consisting of five falls-related questions was administered. Participants performed the TUG test twice, and the mean was taken as the result.
Results: A total of 161 participants were categorized as fallers (14.8%). Multivariate logistic regression analysis showed that the model (χ(2)(6)=61.0, p<0.001, Nagelkerke R(2)=0.10) consisting of the TUG test, sociodemographic factors (gender, cataract/glaucoma and joint pain), as well as the SRMQ items "previous falls history" (Q1) and "worried of falls" (Q5), was more robust in terms of falls risk association compared to that with TUG on its own (χ(2)(1)=10.3, p<0.001, Nagelkerke R(2)=0.02).
Conclusion: Combination of sociodemographic factors and SRMQ with TUG is more favorable as an initial falls risk screening tool among community-dwelling older adults. Subsequently, further comprehensive falls risk assessment may be performed in clinical settings to identify the specific impairments for effective management.