Cheng-Lun Li1, Hui-Chuan Hsu2. 1. Department of Health Care Administration, Research Center on Health Policy and Management, Asia University, No. 500, Lioufeng Road, Wufeng, Taichung 41354, Taiwan. 2. Department of Health Care Administration, Research Center on Health Policy and Management, Asia University, No. 500, Lioufeng Road, Wufeng, Taichung 41354, Taiwan; Department of Medical Research, China Medical University Hospital, China Medical University. Electronic address: gingerhsu@seed.net.tw.
Abstract
PURPOSE: The aim of this study was to examine cognitive function and the risk and the protective factors by age and sex among Taiwanese older people. METHODS: The data were from a nation-representative panel of older people in Taiwan. The participants completing both the 2003 and 2007 waves were included for analysis in this study (n=3228). Descriptive analysis and generalized linear model were applied, and the samples were stratified by age groups and by sex. RESULTS: The factors related to higher cognitive function at the intercept included being younger, male, higher education, and doing unpaid work. At the time slope, the age effect and physical function difficulties would reduce the cognitive function across time, while education and providing informational support would increase the cognitive function across time. There were age- and sex-differences in the factors related to cognitive function, particularly on the working status and social participation. CONCLUSION: Different health promotion strategies to target these populations should be accordingly developed.
PURPOSE: The aim of this study was to examine cognitive function and the risk and the protective factors by age and sex among Taiwanese older people. METHODS: The data were from a nation-representative panel of older people in Taiwan. The participants completing both the 2003 and 2007 waves were included for analysis in this study (n=3228). Descriptive analysis and generalized linear model were applied, and the samples were stratified by age groups and by sex. RESULTS: The factors related to higher cognitive function at the intercept included being younger, male, higher education, and doing unpaid work. At the time slope, the age effect and physical function difficulties would reduce the cognitive function across time, while education and providing informational support would increase the cognitive function across time. There were age- and sex-differences in the factors related to cognitive function, particularly on the working status and social participation. CONCLUSION: Different health promotion strategies to target these populations should be accordingly developed.