Individual and contextual determinants of inequalities in health: the Italian case

Int J Health Serv. 2003;33(4):635-67; discussion 743-9. doi: 10.2190/AM8R-K0DY-F7PM-3RNP.


The geographic distribution of health status across Italian regions shows a North-South gradient, with better conditions in the North for both males and females. Using data from the 2000 National Health Interview Survey, the authors first analyze the geographic variation in subjective health and presence of chronic conditions, with specific attention to the effects of individual and area-based socioeconomic conditions and their heterogeneity across regions. The results suggest the North-South gradient in health is mainly affected, at least for subjective health, by the different composition of macro-areas with respect to individual education, and is slightly influenced by contextual circumstances. Moreover, being less educated results in poorer health in some regions (mainly South and Isles) than in others (mainly Northeast). The authors next analyze the circumstances affecting the presence of more disadvantaged people in the South, to highlight features of the Southern context that might exacerbate social inequalities in health and features of Northern areas that might allay them. Indicators of inequalities, welfare, labor, and power resources were analyzed. The results confirm the disadvantage of the South in terms of social, economic, and cultural features, mainly revealing the compositional effects found in the first part of the study. However, the contextual predictive value of income inequalities, quality of care, and social cohesion can have a supplementary effect on health outcomes of disadvantaged persons.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Developed Countries
  • Female
  • Geography*
  • Health Status Indicators*
  • Humans
  • Italy / epidemiology
  • Male
  • Middle Aged
  • Morbidity
  • Politics
  • Quality of Life
  • Rural Health / statistics & numerical data
  • Social Welfare
  • Socioeconomic Factors*
  • Urban Health / statistics & numerical data
  • Vulnerable Populations / statistics & numerical data*