[The prevalence of mild cognitive impairment among residents aged 55 or over in Chengdu area]

Zhonghua Liu Xing Bing Xue Za Zhi. 2003 Dec;24(12):1104-7.
[Article in Chinese]

Abstract

Objective: To study the prevalence of mild cognitive impairment (MCI) in the urban and the rural areas in Chengdu, Southwest China.

Methods: Residents aged 55 or over were selected by stratified random cluster sampling from 19 districts, cities, and counties of Chengdu area in Sichuan province. A two-stage survey was carried out. In the first stage, CMMSE, CES-D were used as screening instruments. In the second stage, Diagnostic questionnaires of dementia and CDR were used as diagnostic instruments. The diagnostic criteria of mild cognitive impairment adopted from Petersen's were: (1) memory complaint; (2) normal activities of daily living; (3) normal general cognitive function; (4) memory impairment incompatible with age; (5) not demented; (6) CDR = 0.5 and (7) exclusion of the reversible cognitive impairment caused by other factors (i.e. depression).

Results: Three thousand, nine hundred and ten subjects were examined. The prevalence rates of MCI was 2.4%. The MCI prevalence rates in the urban and the rural areas were 1.5%, 2.5% respectively, without significant difference. The MCI prevalence in males and females were 1.8%, 2.9% respectively. Prevalence rate in female was higher than in males with significant difference. Prevalence of illiteracy (4.0%) was the highest among different educational levels. The accumulated prevalence increased with age.

Conclusion: The prevalence of MCI (2.4%) was slightly higher than the prevalence of AD (2.05%) in the same areas of Chengdu. MCI seemed to be a high risk factor for AD which should to be followed up. Early intervention in MCI might be helpful in the prevention of AD.

Publication types

  • English Abstract
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • China / epidemiology
  • Cognition Disorders / epidemiology*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Prevalence
  • Random Allocation
  • Residence Characteristics / statistics & numerical data
  • Risk Factors
  • Sex Factors
  • Social Class