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Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
Published on: February 14, 2014
The income-related distribution of cognitive function and its mobility among the Chinese elderly over a 14-year
Yiting Zhou1, Yongjian Xu1, Liang Zhu2
1School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China.
Background:
With population ageing, cognitive function among the elderly is a growing public health concern in China. This study aimed to investigate the trend of income-related inequality in cognitive function, and to track health-related income mobility among the Chinese elderly.
Methods:
Data were drawn from the Chinese Longitudinal Healthy Longevity Survey conducted in 2005, 2008, 2011, 2014, and 2018. Cognitive function was evaluated by the Mini-Mental State Examination. Cross-sectional and longitudinal concentration indices were used to measure the magnitudes of inequalities at different length of time. The mobility index was used to capture the discrepancy between short-term and long-term assessments. The contributions of determinants to mobility were estimated by decomposition analysis.
Results:
The results showed the cognitive function score among the Chinese elderly as 21.13 at the baseline. Men, activities, daily living ability, education, marriage status, income, receipt of community service, vision and hearing condition were positively associated with cognitive function, whereas age, negative well-being, and drinking were negatively associated with cognitive function. The cross-sectional concentration index was positive and significant only at the baseline. In the long run, however, the concentration indices were all positive and became larger over time. After five waves, the mobility index reached -4.84. The largest negative contributor to the mobility index was daily living ability, followed by relaxing activity, domestic activity, and hearing condition. The two largest positive contributors were negative well-being and income.
Conclusions:
As a whole, cognitive function did not perform well among the Chinese elderly. In the long term, the weighted cross-sectional concentration indices underestimated the inequality in cognitive function, and good cognitive performance was concentrated more among the rich. When formulating intervention measures, the Chinese government should give priority to vulnerable groups, especially the elderly who are poor or downwardly mobile in income.
