title: Inequality in cataract blindness and services: moving beyond unidimensional analyses of social position.
abstract: Inequalities in cataract blindness are well known, but data are rarely disaggregated to explore the combined effects of a range of axes describing social disadvantage. We examined inequalities in cataract blindness and services at the intersection of three social axes.
  
  
  
  Three dichotomous social variables (sex (male/female); place of residence (urban/rural); literacy (literate/illiterate)) from cross-sectional national blindness surveys in Pakistan (2001-2004; n=16 507) and Nigeria (2005-2007; n=13 591) were used to construct eight subgroups, with disadvantaged subgroups selected a priori (ie, women, rural dwellers, illiterate). In each data set, the social distribution of cataract blindness, cataract surgical coverage (CSC) and effective cataract surgical coverage (eCSC) were examined. Inequalities were assessed comparing the best-off and worst-off subgroups using rate differences and rate ratios (RRs). Logistic regression was used to assess cumulative effects of multiple disadvantage.
  
  
  
  Disadvantaged subgroups experienced higher prevalence of cataract blindness, lower CSC and lower eCSC in both countries. A social gradient was present for CSC and eCSC, with coverage increasing as social position improved. Relative inequality in eCSC was approximately twice as high as CSC (Pakistan: eCSC RR 2.7 vs CSC RR 1.3; Nigeria: eCSC RR 8.7 vs CSC RR 4.1). Cumulative disadvantage was observed for all outcomes, deteriorating further with each additional axis along which disadvantage was experienced.
  
  
  
  Each outcome tended to be worse with the addition of each layer of social disadvantage. Illiterate, rural women fared worst in both settings. Moving beyond unidimensional analyses of social position identified subgroups in most need; this permits a more nuanced response to addressing the inequitable distribution of cataract blindness.
authors.affiliation: University of New South Wales, School of Social Sciences, Faculty of Arts and Social Sciences, Sydney, New South Wales, Australia.|University of Auckland, School of Population Health, Auckland, New Zealand.
authors.forename: Jacqueline
authors.initials: J
authors.lastname: Ramke
authors.affiliation: University of New South Wales, School of Social Sciences, Faculty of Arts and Social Sciences, Sydney, New South Wales, Australia.|Health, Rights and Development, UNSW (@HEARDatUNSW), Sydney, Australia.
authors.forename: Anthony B
authors.initials: AB
authors.lastname: Zwi
authors.affiliation: University of Auckland, School of Population Health, Auckland, New Zealand.
authors.forename: Arier C
authors.initials: AC
authors.lastname: Lee
authors.affiliation: University of New South Wales, School of Public Health and Community Medicine, Sydney, New South Wales, Australia.|Western Sydney University, School of Medicine, Centre for Health Research, Campbelltown, New South Wales, Australia.
authors.forename: Ilse
authors.initials: I
authors.lastname: Blignault
authors.affiliation: Department of Clinical Research, Faculty of Infectious & Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.
authors.forename: Clare E
authors.initials: CE
authors.lastname: Gilbert
mesh_terms: D000328:Adult; D017677:Age Distribution; D001766:Blindness / Q000453:epidemiology* / Q000517:prevention & control; D002386:Cataract / Q000453:epidemiology*; D002387:Cataract Extraction / Q000706:statistics & numerical data; D003430:Cross-Sectional Studies; D003695:Delivery of Health Care / Q000706:statistics & numerical data*; D004522:Educational Status; D005260:Female; D006306:Health Surveys; D054625:Healthcare Disparities; D006801:Humans; D016015:Logistic Models; D008297:Male; D009549:Nigeria / Q000453:epidemiology; D010154:Pakistan / Q000453:epidemiology; D015995:Prevalence; D012307:Risk Factors; D017678:Sex Distribution; D012959:Socioeconomic Factors; D014944:World Health Organization
keywords: Epidemiology