Prevalence and Distribution of Cognitive Impairment no Dementia (CIND) Among the Aged Population and the Analysis of Socio-demographic Characteristics The Community-based Cross-sectional Study

The epidemiology on "cognitive impairment no dementia" (CIND) and its natural history are of great importance for understanding the transition from normal aging to dementia. Epidemiologic studies of CIND, however, are limited in China. The goal of our study was to determine the prevalence and distribution of CIND in the aged population and analyze socio-demographic factors. To accomplish this, we performed cluster random sampling of 6192 people aged over 65 years in Taiyuan, a metropolitan city located in northern China. Socio-demographic factors were surveyed by self-administered questionnaires. Neuropsychologic testing consisting of the Mini-Mental State Examination, Boston Naming Test, Trail Making Tests A and B, Block Design. Rey Auditory Verbal Learning Test. Visual Reproduction, Logical Memory, letter and category fluency, the National Adult Reading Test, the Geriatric Depression Scale, and the "state" section of the State-Trait Anxiety Inventory was also obtained. Pearson chi(2) statistics and odds ratio with 95% confidence intervals were used to identify the relationship between CIND and socio-demographic factors. Logistic regression modeling was undertaken to identify potential risk factors. Results showed that all overall prevalence of CIND was 9.70% (95% confidence intervals: 9.62%-9.77%). Univariate analyses showed that the prevalence of CIND differed significantly according to age, sex, education level, monthly household income, and marital status (P<0.01), but not by occupational achievement (P > 0.05). In a multiple logistic regression analysis, age, sex, marital status, educational level, and occupation were significantly associated with increased risk for CIND (P<0.01). This study confirms the high prevalence of CIND among the elderly population of China, similar to previous epidemiologic studies in other countries. Nearly all socio-demographic characteristics are associated with CIND. The putative risk factors identified merit further study.