Trajectories of cognitive function and frailty in older adults in China: a longitudinal study

Front Aging Neurosci. 2024 Nov 14:16:1465914. doi: 10.3389/fnagi.2024.1465914. eCollection 2024.

Abstract

Background: Cognitive impairment and frailty are common issues in older adults. Understanding the co-development trajectories of these conditions can provide valuable sights for early detection and intervention in high-risk individuals.

Objectives: This study aims to identify the co-development of cognitive function and frailty and explore the associated characteristics.

Methods: We analyzed data from 8,418 individuals aged 55 years and above who participated in the China Health and Retirement Longitudinal Survey between 2011 and 2018. Group-based dual trajectory modeling and logistic regression were used to identify trajectory groups and assess associations with risk factors.

Results: Two distinct dual trajectories were identified: "Consistently Robust" group (76.12%) and "Consistently Severe" group (23.88%). Factors such as being female, older age, lower levels of education, residing in rural areas, being unmarried, and having comorbidities such as hypertension, diabetes, complete tooth loss, vision impairment, or hearing impairment were associated with a higher likelihood of being assigned to the "Consistently Severe" group.

Conclusion: Our findings suggest a co-development pattern between cognitive function and frailty in Chinese older adults aged 55 years and above. While cognitive impairment may be irreversible, frailty is a condition that can be potentially reversed. Early detecting is crucial in preventing cognitive decline, considering the shared trajectory of these conditions.

Keywords: aging; cognitive function; dual trajectories; frailty; older adults.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study received support from the National Natural Science Foundation of China (grant number: 72174133) and the Natural Science Foundation of Sichuan Province (grant number: 2022NSFSC0668).