title: Monitoring subnational regional inequalities in health: measurement approaches and challenges.
abstract: BACKGROUND
  Monitoring inequalities based on subnational regions is a useful practice to unmask geographical differences in health, and deploy targeted, equity-oriented interventions. Our objective is to describe, compare and contrast current methods of measuring subnational regional inequality. We apply a selection of summary measures to empirical data from four low- or middle-income countries to highlight the characteristics and overall performance of the different measures.
  
  
  METHODS
  We use data from Demographic and Health Surveys conducted in Bangladesh, Egypt, Ghana and Zimbabwe to calculate subnational regional inequality estimates for reproductive, maternal, newborn, and child health services generated from 11 summary measures: pairwise measures included high to low absolute difference, high to low relative difference, and high to low ratio; complex measures included population attributable risk, weighted variance, absolute weighted mean difference from overall mean, index of dissimilarity, Theil index, population attributable risk percentage, coefficient of variation, and relative weighted mean difference from overall mean. Four of these summary measures (high to low absolute difference, high to low ratio, absolute weighted mean difference from overall mean, and relative weighted mean difference from overall mean) were selected to compare their performance in measuring trend over time in inequality for one health indicator.
  
  
  RESULTS
  Overall, the 11 different measures were more remarkable for their similarities than for their differences. Pairwise measures tended to support the same conclusions as complex summary measures-that is, by identifying same best and worst coverage indicators in each country and indicating similar time trends. Complex measures may be useful to illustrate more nuanced results in countries with a great number of subnational regions.
  
  
  CONCLUSIONS
  When pairwise and complex measures lead to the same conclusions about the state of subnational regional inequality, pairwise measures may be sufficient for reporting inequality. In cases where complex measures are required, mean difference from mean measures can be easily communicated to non-technical audiences.
authors.affiliation: Department of Information, Evidence and Research, World Health Organization, Geneva, Switzerland. hosseinpoora@who.int.
authors.forename: Ahmad Reza
authors.initials: AR
authors.lastname: Hosseinpoor
authors.affiliation: Department of Information, Evidence and Research, World Health Organization, Geneva, Switzerland. bergenn@who.int.
authors.forename: Nicole
authors.initials: N
authors.lastname: Bergen
authors.affiliation: International Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. abarros@equidade.org.
authors.forename: Aluisio J D
authors.initials: AJ
authors.lastname: Barros
authors.affiliation: International Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. kwong@equidade.org.
authors.forename: Kerry L M
authors.initials: KL
authors.lastname: Wong
authors.affiliation: Department of Information, Evidence and Research, World Health Organization, Geneva, Switzerland. boermat@who.int.
authors.forename: Ties
authors.initials: T
authors.lastname: Boerma
authors.affiliation: International Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. cvictora@equidade.org.
authors.forename: Cesar G
authors.initials: CG
authors.lastname: Victora
mesh_terms: D001459:Bangladesh / Q000453:epidemiology; D019985:Benchmarking; D002662:Child Health Services / Q000191:economics / Q000706:statistics & numerical data; D003906:Developing Countries / Q000191:economics / Q000706:statistics & numerical data*; D004534:Egypt / Q000453:epidemiology; D015991:Epidemiologic Measurements; D005869:Ghana / Q000453:epidemiology; D054624:Health Status Disparities; D006306:Health Surveys; D006801:Humans; D007182:Income / Q000706:statistics & numerical data / Q000639:trends; D007223:Infant; D007226:Infant Mortality / Q000639:trends; D008427:Maternal Health Services / Q000191:economics / Q000706:statistics & numerical data; D012959:Socioeconomic Factors; D015030:Zimbabwe / Q000453:epidemiology
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