title: Unexplained health inequality--is it unfair?
abstract: BACKGROUND
  Accurate measurement of health inequities is indispensable to track progress or to identify needs for health equity policy interventions. A key empirical task is to measure the extent to which observed inequality in health - a difference in health - is inequitable. Empirically operationalizing definitions of health inequity has generated an important question not considered in the conceptual literature on health inequity. Empirical analysis can explain only a portion of observed health inequality. This paper demonstrates that the treatment of unexplained inequality is not only a methodological but ethical question and that the answer to the ethical question - whether unexplained health inequality is unfair - determines the appropriate standardization method for health inequity analysis and can lead to potentially divergent estimates of health inequity.
  
  
  METHODS
  We use the American sample of the 2002-03 Joint Canada/United States Survey of Health and measure health by the Health Utilities Index (HUI). We model variation in the observed HUI by demographic, socioeconomic, health behaviour, and health care variables using Ordinary Least Squares. We estimate unfair HUI by standardizing fairness, removing the fair component from the observed HUI. We consider health inequality due to factors amenable to policy intervention as unfair. We contrast estimates of inequity using two fairness-standardization methods: direct (considering unexplained inequality as ethically acceptable) and indirect (considering unexplained inequality as unfair). We use the Gini coefficient to quantify inequity.
  
  
  RESULTS
  Our analysis shows that about 75% of the variation in the observed HUI is unexplained by the model. The direct standardization results in a smaller inequity estimate (about 60% of health inequality is inequitable) than the indirect standardization (almost all inequality is inequitable).
  
  
  CONCLUSIONS
  The choice of the fairness-standardization method is ethical and influences the empirical health inequity results considerably. More debate and analysis is necessary regarding which treatment of the unexplained inequality has the stronger foundation in equity considerations.
authors: Department of Community Health and Epidemiology, Dalhousie University, 5790 University Avenue, Halifax, Nova Scotia, B3H1V7, Canada. yukiko.asada@dal.ca.
authors: Yukiko
authors: Y
authors: Asada
authors: Department of Economics and Centre for Health Economics and Policy Analysis, McMaster University, Hamilton, Ontario, L8S4M4, Canada. hurley@mcmaster.ca.
authors: Jeremiah
authors: J
authors: Hurley
authors: Department of Research and Development, Haukeland University Hospital, Jonas Liesvei 65, 5021, Bergen, Norway. ole.norheim@igs.uib.no.
authors: Ole Frithjof
authors: OF
authors: Norheim
authors: Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Tour Saint-Antoine, Porte S03-458, 850, rue St-Denis, Montreal, Quebec, H2X0A9, Canada. mira.johri@umontreal.ca.|Département d'administration de la santé, Université de Montréal, C.P. 6128, succursale Centre-ville, Montreal, Quebec, H3C3J7, Canada. mira.johri@umontreal.ca.
authors: Mira
authors: M
authors: Johri
mesh_terms: D002170:Canada / Q000453:epidemiology; D006297:Health Services Accessibility / Q000941:ethics* / Q000706:statistics & numerical data; D054625:Healthcare Disparities / Q000941:ethics* / Q000706:statistics & numerical data; D006801:Humans; D008962:Models, Theoretical; D012015:Reference Standards; D011795:Surveys and Questionnaires; D014481:United States / Q000453:epidemiology
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