Deprivation index, Factor analysis, Small-area analysis, Social indicator, Statistical model,

Within cities, gender-related differences were revealed when deprivation was correlated geographically with mortality rates. These differences were found from an ecological perspective. Further research is needed in order to validate these results from an individual approach. The idea to be analysed is to identify those factors that explain these differences at an individual level.

Mortality is one of the most widely used indicators in small-area ecologic studies. Both accessibility to mortality data and advances in the development of new disease mapping techniques have contributed to an abundance of mortality maps and atlases over the last decade. Results may be biased in this kind of study if there has been unmeasured geographic mobility of the population. Most published papers tend to neglect this possibility. We use the theory of dynamics systems to demonstrate that migratory flows unmonitored by official population registers may lead to major errors in mortality rates and relative risks. Simulations in 4 scenarios showed more than 8% underestimation of the mortality rate and more than 11% underestimation of relative risk in areas with high uncontrolled emigration, and above 19% overestimation of mortality rate and above 15% overestimation of relative risk in areas with high uncontrolled immigration.Researchers conducting small-area epidemiologic studies should explore the reliability of population information in geographic areas before drawing hypothesis or conclusions on other possible causes of mortality differences.

Until now, mortality atlases have been static. Most of them describe the geographical distribution of mortality using count data aggregated over time and standardized mortality rates. However, this methodology has several limitations. Count data aggregated over time produce a bias in the estimation of death rates. Moreover, this practice difficult the study of temporal changes in geographical distribution of mortality. On the other hand, using standardized mortality hamper to check differences in mortality among groups. The Interactive Mortality Atlas in Andalusia (AIMA) is an alternative to conventional static atlases. It is a dynamic Geographical Information System that allows visualizing in web-site more than 12.000 maps and 338.00 graphics related to the spatio-temporal distribution of the main death causes in Andalusia by age and sex groups from 1981. The objective of this paper is to describe the methods used for AIMA development, to show technical specifications and to present their interactivity. The system is available from the link products in www.demap.es. AIMA is the first interactive GIS that have been developed in Spain with these characteristics. Spatio-temporal Hierarchical Bayesian Models were used for statistical data analysis. The results were integrated into web-site using a PHP environment and a dynamic cartography in Flash. Thematic maps in AIMA demonstrate that the geographical distribution of mortality is dynamic, with differences among year, age and sex groups. The information nowadays provided by AIMA and the future updating will contribute to reflect on the past, the present and the future of population health in Andalusia.

This is the first HIA experience in Andalusia whose results have been integrated into a formal cycle of decision making in the local community. This experience has provided new evidence of the potential of HIA and its applicability and acceptance at the municipal level and has has also facilitated a learning process and the piloting of new methods and tools associated with the HIA process.