[Methods to smooth mortality indicators: application to analysis of inequalities in mortality in Spanish cities [the MEDEA Project]]. / Métodos para la suavización de indicadores de mortalidad: aplicación al análisis de desigualdades en mortalidad en ciudades del Estado español (Proyecto MEDEA).

ABSTRACT

Although there is some experience in the study of mortality inequalities in Spanish cities, there are large urban centers that have not yet been investigated using the census tract as the unit of territorial analysis. The coordinated project <mortality in Spanish cities. The MEDEA project>> was designed to fill this gap, with the participation of 10 groups of researchers in Andalusia, Aragon, Catalonia, Galicia, Madrid, Valencia, and the Basque Country. The MEDEA project has four distinguishing features a) the census tract is used as the basic geographical area; b) statistical methods that include the geographical structure of the region under study are employed for risk estimation; c) data are drawn from three complementary data sources (information on air pollution, information on industrial pollution, and the records of mortality registrars), and d) a coordinated, large-scale analysis, favored by the implantation of coordinated research networks, is carried out. The main objective of the present study was to explain the methods for smoothing mortality indicators in the context of the MEDEA project. This study focusses on the methodology and the results of the Besag, York and Mollié model (BYM) in disease mapping. In the MEDEA project, standardized mortality ratios (SMR), corresponding to 17 large groups of causes of death and 28 specific causes, were smoothed by means of the BYM model; however, in the present study this methodology was applied to mortality due to cancer of the trachea, bronchi and lung in men and women in the city of Barcelona from 1996 to 2003. As a result of smoothing, a different geographical pattern for SMR in both genders was observed. In men, a SMR higher than unity was found in highly deprived areas. In contrast, in women, this pattern was observed in more affluent areas.