title: Educational differentials in disability vary across and within welfare regimes: a comparison of 26 European countries in 2009.
abstract: BACKGROUND
  Social differentials in disability prevalence exist in all European countries, but their scale varies markedly. To improve understanding of this variation, the article focuses on each end of the social gradient. It compares the extent of the higher disability prevalence in low social groups (referred to as disability disadvantage) and of the lower prevalence in high social groups (disability advantage); country-specific advantages/disadvantages are discussed regarding the possible influence of welfare regimes.
  
  
  METHODS
  Cross-sectional disability prevalence is measured by longstanding health-related activity limitation (AL) in the 2009 European Statistics on Income and Living Conditions (EU-SILC) across 26 countries classified into four welfare regime groups. Logistic models adjusted by country, age and sex (in all 30-79 years and in three age-bands) measured the country-specific ORs across education, representing the AL-disadvantage of low-educated and AL-advantage of high-educated groups relative to middle-educated groups.
  
  
  RESULTS
  The relative AL-disadvantage of the low-educated groups was small in Sweden (eg, 1.2 (1.0-1.4)), Finland, Romania, Bulgaria and Spain (youngest age-band), but was large in the Czech Republic (eg, 1.9 (1.7-2.2)), Denmark, Belgium, Italy and Hungary. The high-educated groups had a small relative AL-advantage in Denmark (eg, 0.9 (0.8-1.1)), but a large AL-advantage in Lithuania (eg, 0.5 (0.4-0.6)), half of the Baltic and Eastern European countries, Norway and Germany (youngest age-band). There were notable differences within welfare regime groups.
  
  
  CONCLUSIONS
  The country-specific disability advantages/disadvantages across educational groups identified here could help to identify determining factors and the efficiency of national policies implemented to tackle social differentials in health.
authors.affiliation: Department of Mortality, Health and Epidemiology, Institut National d'Etudes Démographiques (INED), Paris, France.
authors.forename: Emmanuelle
authors.initials: E
authors.lastname: Cambois
authors.affiliation: Department of Political and Social Science, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
authors.forename: Aïda
authors.initials: A
authors.lastname: Solé-Auró
authors.affiliation: Department of Public Health, University of Copenhagen, Faculty of Health Sciences, Copenhagen, Denmark.
authors.forename: Henrik
authors.initials: H
authors.lastname: Brønnum-Hansen
authors.affiliation: Department of Statistical Science, Sapienza University of Rome, Roma, Italy.
authors.forename: Viviana
authors.initials: V
authors.lastname: Egidi
authors.affiliation: Newcastle University Institute for Ageing and Institute of Health & Society, Campus for Ageing and Vitality, Newcastle upon Tyne, UK.
authors.forename: Carol
authors.initials: C
authors.lastname: Jagger
authors.affiliation: Department of Epidemiology, Institute of Public Health, and Danish Ageing Research Center, University of Southern Denmark, Odense, Denmark.
authors.forename: Bernard
authors.initials: B
authors.lastname: Jeune
authors.affiliation: Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
authors.forename: Wilma J
authors.initials: WJ
authors.lastname: Nusselder
authors.affiliation: Department of Public Health and Surveillance, Scientific Institute of Public Health, Brussels, Belgium.
authors.forename: Herman
authors.initials: H
authors.lastname: Van Oyen
authors.affiliation: Government Statistical Service, Office for National Statistics, Government Buildings, Newport, UK.
authors.forename: Chris
authors.initials: C
authors.lastname: White
authors.affiliation: Institut National de la Santé et de la Recherche Médicale (INSERM), Ecole Pratique des Hautes Etudes (EPHE) and Institut National d'Etudes Démographiques (INED), Montpellier, France.
authors.forename: Jean-Marie
authors.initials: JM
authors.lastname: Robine
mesh_terms: D000328:Adult; D017677:Age Distribution; D000368:Aged; D003430:Cross-Sectional Studies; D006233:Persons with Disabilities / Q000523:psychology / Q000706:statistics & numerical data*; D004522:Educational Status; D005060:Europe / Q000453:epidemiology; D005260:Female; D054624:Health Status Disparities; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D017678:Sex Distribution; D012923:Social Class; D012946:Social Welfare / Q000706:statistics & numerical data
keywords: AGEING; DEMOGRAPHY; Functioning and disability; POLICY; SOCIAL INEQUALITIES