title: Social-Economic Status and Cognitive Performance among Chinese Aged 50 Years and Older.
abstract: BACKGROUND
  Numerous population-based studies have suggested that socio-economic status (SES) is associated with cognitive performance, but few nationally representative epidemiological studies on cognitive performance with a large sample of older adults are available in China. And many studies explore the factors associated with cognitive performance, mainly focusing on individual level and more rarely on multiple levels that include the individual and community.
  
  
  METHODS
  This study uses SAGE-China Wave 1 data which consisted of 13,157 adults aged 50 years and older to explore socioeconomic inequalities in the cognitive performance from a multilevel perspective (individual and community levels). The overall cognition score was based on the seven separate components of the cognition tests, including the four verbal recall trials, the verbal fluency test, the forward digit span test and the backward digit span test. Factor analysis was applied to evaluate and generate a single overall score. A two-level hierarchical linear model was used to evaluate the association between SES at these two levels and the overall cognition score adjusted for age, sex and marital status.
  
  
  RESULTS
  At individual level, years of education was significantly associated with overall cognition score for both urban and rural dwellers. At the community level, a positive association was obtained between median household income and median years of education and overall cognition score among urban participants.
  
  
  CONCLUSIONS
  A significant association between SES at both individual-level and community-level (only for urban area) and cognitive performance were found in this study of a national sample of 13,157 Chinese aged 50 years and older, even after adjusting for demographic characteristics. Identifying community-based SES variables that are associated with cognitive performance in the older population provides further evidence for the need to address community characteristics associated with deprivation.
authors.affiliation: School of Public Health, Fudan University, Shanghai, China.|Shanghai Institute of Preventive Medicine, Shanghai, China.|Shanghai Municipal Center for Disease Control & Prevention, Shanghai, China.
authors.forename: Fan
authors.initials: F
authors.lastname: Wu
authors.affiliation: Shanghai Institute of Preventive Medicine, Shanghai, China.|Shanghai Municipal Center for Disease Control & Prevention, Shanghai, China.
authors.forename: Yanfei
authors.initials: Y
authors.lastname: Guo
authors.affiliation: Shanghai Institute of Preventive Medicine, Shanghai, China.|Shanghai Municipal Center for Disease Control & Prevention, Shanghai, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Zheng
authors.affiliation: Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
authors.forename: Wenjun
authors.initials: W
authors.lastname: Ma
authors.affiliation: World Health Organization, Department of Health and Information Systems, Geneva, Switzerland.|University of Newcastle Research Centre for Generational, Health and Ageing, Newcastle, Australia.
authors.forename: Paul
authors.initials: P
authors.lastname: Kowal
authors.affiliation: World Health Organization, Department of Health and Information Systems, Geneva, Switzerland.
authors.forename: Somnath
authors.initials: S
authors.lastname: Chatterji
authors.affiliation: School of Public Health, Fudan University, Shanghai, China.
authors.forename: Ling
authors.initials: L
authors.lastname: Wang
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002681:China / Q000453:epidemiology; D003071:Cognition; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D062486:Public Health Surveillance; D012923:Social Class; D012959:Socioeconomic Factors