Inequalities in mortality in small areas of eleven Spanish cities (the multicenter MEDEA project)

Health Place. 2010 Jul;16(4):703-11. doi: 10.1016/j.healthplace.2010.03.002. Epub 2010 Mar 23.

Abstract

The objectives of this study are to identify inequalities in mortality among census tracts of 11 Spanish cities in the period 1996-2003 and to analyse the relationship between these geographical inequalities and socioeconomic deprivation. It is a cross-sectional ecological study where the units of analysis are census tracts. We obtained an index of socioeconomic deprivation and estimated SMR by each census tract using hierarchical Bayesian models which take into account the spatial structure. In the majority of the cities geographical patterns in total mortality were found in both sexes, which were similar to those for the index of socioeconomic deprivation. Among men, four specific causes of death (lung cancer, ischemic heart diseases, respiratory diseases and cirrhosis) were positively associated with deprivation in the majority of cities. Among women the specific causes diabetes and cirrhosis were positively associated, while lung cancer was negatively associated with deprivation. The excess of mortality related with deprivation was 59,445 deaths among men and 23,292 among women. These results highlight the importance of intra-urban inequalities in health.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Distribution
  • Analysis of Variance
  • Cause of Death*
  • Cross-Sectional Studies
  • Educational Status
  • Employment / statistics & numerical data
  • Female
  • Health Status Disparities*
  • Humans
  • International Classification of Diseases / statistics & numerical data
  • Male
  • Mortality*
  • Population Surveillance
  • Poverty Areas*
  • Principal Component Analysis
  • Registries
  • Regression Analysis
  • Residence Characteristics / statistics & numerical data
  • Sex Distribution
  • Small-Area Analysis
  • Socioeconomic Factors
  • Spain / epidemiology
  • Urban Health / statistics & numerical data*