Background: Frailty and cognitive decline are highly prevalent among older adults. However, the relationship between frailty and mild behavioral impairment (MBI), a dementia risk syndrome characterized by later-life emergence of persistent neuropsychiatric symptoms, has yet to be elucidated. We aimed to evaluate the associations between MBI and frailty in older adults without dementia.Methods: In this cross-sectional study, a consecutive series of 137 older adults without dementia in the Anti-Aging Study, recruited from primary care clinics, were enrolled. Frailty was estimated using the Fried phenotype. MBI was evaluated by the Mild Behavioral Impairment Checklist (MBI-C) at a cut-off point of > 8. Cognition was assessed with the Chinese versions of the Montreal Cognitive Assessment (MoCA-BC) and Mini-mental State Examination (MMSE). Multivariable logistic regression was performed to estimate the relationship between MBI and objective cognition with frailty status.Results: At baseline, 30.7% of the older adults had frailty and 18.2% had MBI (MBI+ status). Multivariable logistic regression analysis demonstrated that compared to those without MBI (MBI- status), MBI+ was more likely to have frailty (odds ratio [OR] = 7.44, 95% CI = 1.49–37.21,p = 0.02). Frailty and MBI were both significantly associated with both MMSE and MoCA-BC score (p < 0.05).Conclusions: Both frailty and MBI status were associated with higher odds of cognitive impairment. MBI was significantly associated with an increased risk of having frailty in the absence of dementia. This association merits further study to identify potential strategies for the early detection, prevention and therapeutic intervention of frailty.

Background: Frailty is a dynamic and complex geriatric condition characterized by multi-domain declines in physiological, gait and cognitive function. This study examined whether digital health technology can facilitate frailty identification and improve the efficiency of diagnosis by optimizing analytical and machine learning approaches using select factors from comprehensive geriatric assessment and gait characteristics.Methods: As part of an ongoing study on observational study of Aging, we prospectively recruited 214 individuals living independently in the community of Southern China. Clinical information and fragility were assessed using comprehensive geriatric assessment (CGA). Digital tool box consisted of wearable sensor-enabled 6-min walk test (6MWT) and five machine learning algorithms allowing feature selections and frailty classifications.Results: It was found that a model combining CGA and gait parameters was successful in predicting frailty. The combination of these features in a machine learning model performed better than using either CGA or gait parameters alone, with an area under the curve of 0.93. The performance of the machine learning models improved by 4.3–11.4% after further feature selection using a smaller subset of 16 variables. SHapley Additive exPlanation (SHAP) dependence plot analysis revealed that the most important features for predicting frailty were large-step walking speed, average step size, age, total step walking distance, and Mini Mental State Examination score.Conclusion: This study provides evidence that digital health technology can be used for predicting frailty and identifying the key gait parameters in targeted health assessments.

Liangyi Gao (LYG), a traditional Chinese medicine, is composed of Ginseng and Radix Rehmanniae Preparata, both of which have been shown to have antiaging properties. In Eastern countries, LYG is used to delay functional declines related to aging and has an obvious antiaging effect in clinical practice. However, little data from evidence-based medicine is available regarding whether LYG is beneficial overall, particularly with respect to lifespan, and how LYG functions. To address these issues, Caenorhabditis elegans, a useful organism for such studies, was employed to explore the antiaging effect and mechanism of LYG in this study. The results showed that LYG could obviously extend lifespan and slow aging-related declines in N2 wild-type C. elegans. To further characterize these antiaging effects and stress resistance, reproductive tests and other aging-related tests were performed. We found that LYG enhanced resistance against oxidative and thermal stress, reproduction, pharynx pumping, motility and growth in N2 wild-type C. elegans. In addition, we analyzed the mechanism for these effects by measuring the activity of superoxide dismutase (SOD) and the expression levels of aging-related genes. We found that LYG enhanced the activities of antioxidant enzymes and upregulated the genes daf-16, sod-3 and sir-2.1, which mediated stress resistance and longevity. In conclusion, LYG had robust and reproducible life-prolonging and antiaging benefits in C. elegans via DAF-16/FOXO regulation.