title: Differences in self reported morbidity by educational level: a comparison of 11 western European countries.
abstract: OBJECTIVE
  To assess whether there are variations between 11 Western European countries with respect to the size of differences in self reported morbidity between people with high and low educational levels.
  
  
  METHODS
  National representative data on morbidity by educational level were obtained from health interview surveys, level of living surveys or other similar surveys carried out between 1985 and 1993. Four morbidity indicators were included and a considerable effort was made to maximise the comparability of these indicators. A standardised scheme of educational levels was applied to each survey. The study included men and women aged 25 to 69 years. The size of morbidity differences was measured by means of the regression based Relative Index of Inequality.
  
  
  RESULTS
  The size of inequalities in health was found to vary between countries. In general, there was a tendency for inequalities to be relatively large in Sweden, Norway, and Denmark and to be relatively small in Spain, Switzerland, and West Germany. Intermediate positions were observed for Finland, Great Britain, France, and Italy. The position of the Netherlands strongly varied according to sex: relatively large inequalities were found for men whereas relatively small inequalities were found for women. The relative position of some countries, for example, West Germany, varied according to the morbidity indicator.
  
  
  CONCLUSIONS
  Because of a number of unresolved problems with the precision and the international comparability of the data, the margins of uncertainty for the inequality estimates are somewhat wide. However, these problems are unlikely to explain the overall pattern. It is remarkable that health inequalities are not necessarily smaller in countries with more egalitarian policies such as the Netherlands and the Scandinavian countries. Possible explanations are discussed.
authors.affiliation: Department of Public Health, Erasmus University, Rotterdam, The Netherlands.
authors.forename: A E
authors.initials: AE
authors.lastname: Cavelaars
authors.forename: A E
authors.initials: AE
authors.lastname: Kunst
authors.forename: J J
authors.initials: JJ
authors.lastname: Geurts
authors.forename: R
authors.initials: R
authors.lastname: Crialesi
authors.forename: L
authors.initials: L
authors.lastname: Grötvedt
authors.forename: U
authors.initials: U
authors.lastname: Helmert
authors.forename: E
authors.initials: E
authors.lastname: Lahelma
authors.forename: O
authors.initials: O
authors.lastname: Lundberg
authors.forename: J
authors.initials: J
authors.lastname: Matheson
authors.forename: A
authors.initials: A
authors.lastname: Mielck
authors.forename: A
authors.initials: A
authors.lastname: Mizrahi
authors.forename: A
authors.initials: A
authors.lastname: Mizrahi
authors.forename: N K
authors.initials: NK
authors.lastname: Rasmussen
authors.forename: E
authors.initials: E
authors.lastname: Regidor
authors.forename: T
authors.initials: T
authors.lastname: Spuhler
authors.forename: J P
authors.initials: JP
authors.lastname: Mackenbach
mesh_terms: D000328:Adult; D000368:Aged; D004522:Educational Status; D005060:Europe / Q000453:epidemiology; D005260:Female; D006305:Health Status Indicators; D006306:Health Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D009017:Morbidity / Q000639:trends*; D012044:Regression Analysis; D012189:Retrospective Studies; D012959:Socioeconomic Factors