title: Breast cancer stage at diagnosis and area-based socioeconomic status: a multicenter 10-year retrospective clinical epidemiological study in China.
abstract: BACKGROUND
  Although socioeconomic status (SES) has been focused on as a key determinant of cancer stage at diagosis in western countries, there has been no systemic study on the relationship of SES and breast cancer stage at diagnosis in China.
  
  
  METHODS
  The medical charts of 4,211 eligible breast cancer patients from 7 areas across China who were diagnosed between 1999 and 2008 were reviewed. Four area-based socioeconomic indicators were used to calculate area-based SES by cluster analysis. The associations between area-based SES and stage at diagnosis were analyzed by trend chi-square tests. Binary logistic regression was performed to estimate odds ratios for individual demographic characteristics' effects on cancer stages, stratified by area-based SES.
  
  
  RESULTS
  The individual demographic and pathologic characteristics of breast cancer cases were significantly different among the seven areas studied. More breast cancer cases in low SES areas (25.5%) were diagnosed later (stages III & IV) than those in high (20.4%) or highest (14.8%) SES areas (χ² for trend = 80.79, P < 0.001). When area-based SES is controlled for, in high SES areas, cases with less education were more likely to be diagnosed at later stages compared with more educated cases. In low SES areas, working women appeared to be diagnosed at earlier breast cancer stages than were homemakers (OR: 0.18-0.26).
  
  
  CONCLUSIONS
  In China, women in low SES areas are more likely to be diagnosed at later breast cancer stages than those in high SES areas.
authors.affiliation: Department of Epidemiology, West China School of Public Health, Sichuan University, 16 Ren Min Nan Lu, Chengdu, Sichuan 610041, China.
authors.forename: Qiong
authors.initials: Q
authors.lastname: Wang
authors.forename: Jing
authors.initials: J
authors.lastname: Li
authors.forename: Shan
authors.initials: S
authors.lastname: Zheng
authors.forename: Jia-Yuan
authors.initials: JY
authors.lastname: Li
authors.forename: Yi
authors.initials: Y
authors.lastname: Pang
authors.forename: Rong
authors.initials: R
authors.lastname: Huang
authors.forename: Bao-Ning
authors.initials: BN
authors.lastname: Zhang
authors.forename: Bin
authors.initials: B
authors.lastname: Zhang
authors.forename: Hong-Jian
authors.initials: HJ
authors.lastname: Yang
authors.forename: Xiao-Ming
authors.initials: XM
authors.lastname: Xie
authors.forename: Zhong-Hua
authors.initials: ZH
authors.lastname: Tang
authors.forename: Hui
authors.initials: H
authors.lastname: Li
authors.forename: Jian-Jun
authors.initials: JJ
authors.lastname: He
authors.forename: Jin-Hu
authors.initials: JH
authors.lastname: Fan
authors.forename: You-Lin
authors.initials: YL
authors.lastname: Qiao
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000453:epidemiology / Q000473:pathology*; D002681:China / Q000453:epidemiology; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D009367:Neoplasm Staging; D012189:Retrospective Studies; D012923:Social Class; D012959:Socioeconomic Factors