title: A multicentre community-based study of dementia cases and subcases in older people in China--the GMS-AGECAT prevalence and socio-economic correlates.
abstract: BACKGROUND
  Previous studies indicated overall relatively low prevalence of dementia in older people in China, which may be biased by studied samples or methods. We determined the prevalence of dementia cases and subcases in China and examined their socio-economic correlates.
  
  
  METHODS
  Using the Geriatric Mental State interview, we examined random samples of 2917 participants aged ≥ 65 years in urban and rural Anhui, China in 2001-2003, and 3327 in four other provinces in 2008-2009. Dementia cases and subcases were diagnosed by Geriatric Mental State-Automated Geriatric Examination for Computer Assisted Taxonomy.
  
  
  RESULTS
  Age-standardised prevalence for cases and subcases of dementia in the Anhui elders was 7.20% (95%CI 6.29%-8.20%) and 10.5% (9.38%-11.6%), and in the four provinces, 9.86% (8.80%-10.9%) and 8.51% (7.51%-9.52%). The matched figures among the participants who were literate were 3.05% (2.08%-4.02%) and 10.0% (8.38%-11.6%), and 4.92% (3.89%-5.96%) and 6.76% (5.55%-7.96%), respectively. There were higher prevalence rates of dementia cases and subcases in the rural elders than in the urban. Both the Anhui and four-province studies showed an obvious association of dementia with higher and lower incomes among elders who had lower educational levels or had the lowest occupational class. The highest risk of dementia was found in those who were illiterate but had the highest income or had the job of business/nonmanual labouring.
  
  
  CONCLUSIONS
  People in China have a higher prevalence of dementia than previously reported. Its U-shaped relationship with income and the excess subcases prevalence predicates a significant burden of disease, both now and for the future, suggesting preventive strategy for dementia in China.
authors.affiliation: Centre for Health and Social Care Improvement, School of Health and Wellbeing, University of Wolverhampton, UK. r.chen@wlv.ac.uk
authors.forename: Ruoling
authors.initials: R
authors.lastname: Chen
authors.forename: Ying
authors.initials: Y
authors.lastname: Ma
authors.forename: Ken
authors.initials: K
authors.lastname: Wilson
authors.forename: Zhi
authors.initials: Z
authors.lastname: Hu
authors.forename: David
authors.initials: D
authors.lastname: Sallah
authors.forename: Jiaji
authors.initials: J
authors.lastname: Wang
authors.forename: Lihua
authors.initials: L
authors.lastname: Fan
authors.forename: Ruo-Li
authors.initials: RL
authors.lastname: Chen
authors.forename: John R
authors.initials: JR
authors.lastname: Copeland
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002681:China / Q000453:epidemiology; D003704:Dementia / Q000453:epidemiology*; D004522:Educational Status; D004651:Employment / Q000145:classification; D005260:Female; D006801:Humans; D007182:Income; D008297:Male; D015999:Multivariate Analysis; D015995:Prevalence; D012307:Risk Factors; D012424:Rural Population; D012959:Socioeconomic Factors; D014505:Urban Population