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: The study was completed in 2016 and the baseline data were gathered from four groups in a school-based randomized community trial among Year Five students from primary schools in Kota Bharu, Kelantan, Malaysia. Participants completed anthropometry assessment, three-day dietary record, and Physical Activity Questionnaire for Older Children (PAQ-C).
Results: The prevalence of obesity was higher among the boys (52.5%). Mean energy intake was significantly higher among boys as compared to the girls (P=0.003). Twenty-five percent of the participants had exceeded the recommended nutrient intakes (RNI) of energy recommended. The calcium, thiamine, riboflavin, and niacin were also significantly higher among boys as compared to the girls (P<0.05). Boys also exhibited a significantly higher score on performance of physical activity (mean=2.68; SD=0.60) as compared to the girls (mean=2.38; SD=0.51) however it is still in the category of moderately active. Approximately 14.4% of children had a very low physical activity level.
Conclusion: Overweight and obese boys had higher energy and fat intakes but were more physically active as compared to the girls. These findings might be useful in planning appropriate intervention strategies to be designed and delivered especially for this cohort.