title: Decomposing socioeconomic inequalities in depressive symptoms among the elderly in China.
abstract: Accelerated population ageing brings about unprecedented challenges to the health system in China. This study aimed to measure the prevalence and the income-related inequality of depressive symptoms, and also identify the determinants of depressive symptom inequality among the elderly in China.
  
  
  
  Data were drawn from the second wave of the China Health and Retirement Longitudinal Study (CHARLS). Depressive symptoms were assessed with a 10-item Center for Epidemiologic Studies-Depression Scale (CES-D), which was preselected in CHARLS. The concentration index was used to measure the magnitude of income-related inequality in depressive symptoms. A decomposition analysis, based on the logit model, was employed to quantify the contribution of each determinant to total inequality.
  
  
  
  More than 32.55% of the elderly in China had depressive symptoms. Women had a higher prevalence of depressive symptoms than men. The overall concentration index of depressive symptoms was -0.0645 among the elderly, indicating that depressive symptoms are more concentrated among the elderly who lived in economically disadvantaged situations, favoring the rich. Income was found to have the largest percentage of contribution to overall inequality, followed by residents' location and educational attainment.
  
  
  
  The prevalence of depressive symptoms in the elderly was considerably high in China. There was also a pro-rich inequality in depressive symptoms amongst elderly Chinese. It is suggested that some form of policy and intervention strategies, such as establishing the urban-rural integrated medical insurance scheme, enhancing the medical assistance system, and promoting health education programs, is required to alleviate inequitable distribution of depressive symptoms.
authors.affiliation: School of Public Policy and Administration, Xi'an Jiaotong University, No.28, Xianning West Road, Xi'an, Shaanxi, China.
authors.forename: Yongjian
authors.initials: Y
authors.lastname: Xu
authors.affiliation: School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
authors.forename: Jinjuan
authors.initials: J
authors.lastname: Yang
authors.affiliation: School of Public Policy and Administration, Xi'an Jiaotong University, No.28, Xianning West Road, Xi'an, Shaanxi, China. gaojm@mail.xjtu.edu.cn.
authors.forename: Jianmin
authors.initials: J
authors.lastname: Gao
authors.affiliation: School of Public Policy and Administration, Xi'an Jiaotong University, No.28, Xianning West Road, Xi'an, Shaanxi, China.
authors.forename: Zhongliang
authors.initials: Z
authors.lastname: Zhou
authors.affiliation: School of Medicine, Hangzhou Normal University, Hangzhou, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Zhang
authors.affiliation: School of Medicine, Hangzhou Normal University, Hangzhou, China.
authors.forename: Jianping
authors.initials: J
authors.lastname: Ren
authors.affiliation: School of Public Policy and Administration, Xi'an Jiaotong University, No.28, Xianning West Road, Xi'an, Shaanxi, China.
authors.forename: Yanli
authors.initials: Y
authors.lastname: Li
authors.affiliation: School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
authors.forename: Yuyan
authors.initials: Y
authors.lastname: Qian
authors.affiliation: School of Public Policy and Administration, Xi'an Jiaotong University, No.28, Xianning West Road, Xi'an, Shaanxi, China.
authors.forename: Sha
authors.initials: S
authors.lastname: Lai
authors.affiliation: Centre for Health Economics, Monash Business School, Monash University, Melbourne, Australia. gang.chen@monash.edu.
authors.forename: Gang
authors.initials: G
authors.lastname: Chen
mesh_terms: D000368:Aged; D002681:China / Q000453:epidemiology; D003863:Depression / Q000453:epidemiology*; D005260:Female; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D012179:Retirement / Q000523:psychology*; D012424:Rural Population / Q000706:statistics & numerical data; D012923:Social Class; D012959:Socioeconomic Factors
keywords: Concentration index; Decomposition analysis; Depressive symptoms; Health inequality