Cognitive decline trajectories and influencing factors in China: A non-normal growth mixture model analysis. (July 2021)

• Record Type: Journal Article
• Authors: Yu, Weiye; Chen, Rong; Zhang, Minqiang; Li, Zonglong; Gao, Fangxin; Yu, Sufang; Zhang, Xinyu
• Is Part Of: Archives of gerontology and geriatrics. Volume 95(2021)
• Publication Date: 2021-07
• Subjects: Late life -- Cognitive decline -- Growth mixture model -- Non-normal distribution; Aging -- Periodicals; Geriatrics -- Periodicals; Gerontology -- Periodicals; Electronic journals; 305.26
• DOI: 10.1016/j.archger.2021.104381
• Languages: English
• ISSNs: 0167-4943

Abstract

Highlights: How to delay cognitive decline is an important public health issue, but the heterogeneity of the population is rarely considered in existing studies. This study used a non-normal distribution growth mixture model to identify the population heterogeneity in the data, which is a new development of statistical techniques. Different subgroups not only showed differences in the initial level of cognition, but also have different downward trends. Education and life experience may affect current cognitive level but may not delay cognitive decline. Small amounts of alcohol intake and participation in physical and cognitive activities have been found to delay cognitive decline, which are useful for future tailored interventions. Abstract: Background: With the increase in the aging population worldwide, cognitive decline has become an important research topic. The purpose of this study is to examine the cognitive development trajectories and influencing factors of different latent classes of Chinese elderly people. This will provide us with effective guidance for prevention and intervention. Methods: Four waves of data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) were collected and included 2440 Chinese elderly individuals. The cognitive function of elderly individuals was measured using the Mini Mental State Examination (MMSE). A nonnormal Growth Mixture model (GMM) with five time-invariant covariates was used to identify the different trajectories of cognitive decline in elderly individuals. Results: Three latent decline trajectory groups were identified: stable cognitive group (SCG), high initial level – cognitive decline group (HIL–CDG), and high initial level – cognitive decline group (LIL–CDG). Elderly women were more likely to be assigned to a lower level subgroup than men. People who smoked and played cards or mahjong were more likely to be assigned to a cognitively stable group. Conclusion: Education may help raise the upper limit of cognition. Smoking may impair cognitive upper limit. A small amount of alcohol intake and participation in cognitive and physical activities may help the elderly to delay cognitive decline in their later years.