Xiaoqian Hu1, Shuyan Gu2, Xueshan Sun3, Yuxuan Gu4, Xuemei Zhen5, Yuanyuan Li6, Minzhuo Huang7, Jingming Wei8, Hengjin Dong9. 1. Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China. Electronic address: huxiaoqian@zju.edu.cn. 2. Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China. Electronic address: gushuyan@zju.edu.cn. 3. Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China. Electronic address: sunxueshan@zju.edu.cn. 4. Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China. Electronic address: guyuxuan@zju.edu.cn. 5. Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China. Electronic address: zhenxuemei@zju.edu.cn. 6. Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China. Electronic address: sun89521@126.com. 7. Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China. Electronic address: 1031065503@qq.com. 8. Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China. Electronic address: weijm@zju.edu.cn. 9. Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China. Electronic address: donghj@zju.edu.cn.
Abstract
OBJECTIVE: This study aims to identify distinctive cognitive trajectories jointly with mortality probabilities and to explore factors related to the particular trajectories of cognitive ageing in China. METHOD: 6842 individuals aged 80 years and above from 7 waves of the Chinese Longitudinal Healthy Longevity Survey were assessed with the Mini-Mental State Examination for up to 16 years. A group-based trajectory model was used to jointly estimate cognitive ageing and mortality trajectories; and to explore the factors related to membership of the trajectory groups. RESULTS: A four-group model best fit the data. For all groups, the cognitive function declined with age according to different rates. Group 4, 3, 2, and 1 showed slow (prevalence 52.8%), moderate (31.1%), progressive (12.6%) and rapid (3.5%) cognitive decline, respectively. Mortality probability trajectories followed a hierarchy in consistence with cognitive trajectories approximately. Females, illiteracy, and those born in rural areas were less likely to belong to the most favorable trajectory group. CONCLUSIONS: The heterogeneity of cognitive ageing was identified among Chinese oldest-old. Childhood socioeconomic status, especially education, was associated with the rate of cognitive decline.
OBJECTIVE: This study aims to identify distinctive cognitive trajectories jointly with mortality probabilities and to explore factors related to the particular trajectories of cognitive ageing in China. METHOD: 6842 individuals aged 80 years and above from 7 waves of the Chinese Longitudinal Healthy Longevity Survey were assessed with the Mini-Mental State Examination for up to 16 years. A group-based trajectory model was used to jointly estimate cognitive ageing and mortality trajectories; and to explore the factors related to membership of the trajectory groups. RESULTS: A four-group model best fit the data. For all groups, the cognitive function declined with age according to different rates. Group 4, 3, 2, and 1 showed slow (prevalence 52.8%), moderate (31.1%), progressive (12.6%) and rapid (3.5%) cognitive decline, respectively. Mortality probability trajectories followed a hierarchy in consistence with cognitive trajectories approximately. Females, illiteracy, and those born in rural areas were less likely to belong to the most favorable trajectory group. CONCLUSIONS: The heterogeneity of cognitive ageing was identified among Chinese oldest-old. Childhood socioeconomic status, especially education, was associated with the rate of cognitive decline.
Authors: Kathleen M Hayden; Bruce R Reed; Jennifer J Manly; Douglas Tommet; Robert H Pietrzak; Gordon J Chelune; Frances M Yang; Andrew J Revell; David A Bennett; Richard N Jones Journal: Age Ageing Date: 2011-09-02 Impact factor: 10.668
Authors: Robert S Wilson; Laurel A Beckett; Lisa L Barnes; Julie A Schneider; Julie Bach; Denis A Evans; David A Bennett Journal: Psychol Aging Date: 2002-06
Authors: Zimu Wu; Robyn L Woods; Trevor T J Chong; Suzanne G Orchard; Raj C Shah; Rory Wolfe; Elsdon Storey; Kerry M Sheets; Anne M Murray; John J McNeil; Joanne Ryan Journal: Front Med (Lausanne) Date: 2022-06-27