title: Decomposing income-related inequality in cervical screening in 67 countries.
abstract: OBJECTIVE
  The development of successful policies to reduce income-related inequalities in cervical cancer screening rates requires an understanding of the reasons why low-income women are less likely to be screened. We sought to identify important determinants contributing to inequality in cervical screening rates.
  
  
  METHODS
  We analyzed data from 92,541 women aged 25-64 years, who participated in the World Health Survey in 2002-2003. Income-related inequality in Pap screening was measured using the concentration index (CI). Using a decomposition method for the CI, we quantified the contribution to inequality of age, education level, marital status, urbanicity and recent health-care need.
  
  
  RESULTS
  There was substantial heterogeneity in the contributions of different determinants to inequality among countries. Education generally made the largest contribution (median = 15%, interquartile range [IQR] = 23%), although this varied widely even within regions (e.g., 5% in Austria, 28% in Hungary). The contribution of rural residence was greatest in African countries (median = 10%, IQR = 13%); however, there was again substantial within-region variation (e.g., 26% in Zambia, 2% in Kenya).
  
  
  CONCLUSIONS
  Considerable heterogeneity in the contributions of screening determinants among countries suggests interventions to reduce screening inequalities may require country-specific approaches.
authors.affiliation: Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Purvis Hall, Montreal, QC, H3A 1A2, Canada. brittany.mckinnon@mail.mcgill.ca
authors.forename: Brittany
authors.initials: B
authors.lastname: McKinnon
authors.forename: Sam
authors.initials: S
authors.lastname: Harper
authors.forename: Spencer
authors.initials: S
authors.lastname: Moore
mesh_terms: D000328:Adult; D000349:Africa; D000569:Americas; D001208:Asia; D003431:Cross-Cultural Comparison; D003430:Cross-Sectional Studies; D055088:Early Detection of Cancer / Q000191:economics* / Q000706:statistics & numerical data; D005060:Europe; D005260:Female; D006801:Humans; D007182:Income; D008875:Middle Aged; D012959:Socioeconomic Factors; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis* / Q000517:prevention & control; D014626:Vaginal Smears / Q000191:economics* / Q000706:statistics & numerical data; D016387:Women's Health