[Geographic information systems as a tool for monitoring health inequalities]

To show how geographic information systems (GISs) can be used as technological tools to support health policy and public health actions.

We assessed the relationship between infant mortality and a number of socio-economic and geographic determinants. In explaining how GISs are applied, we stressed their ability to integrate data, which makes it possible to perform epidemiologic evaluations in a simpler, faster, automated way that simultaneously analyzes multiple variables with different levels of aggregation. In this study, GISs were applied in analyzing infant mortality data with three levels of aggregation in countries of the Americas from 1995 to 2000.

Infant mortality in the Region of the Americas was estimated at an overall average of 24.4 deaths per 1,000 live births. However, the inequalities that were found indicate that the probability of an infant death is almost 20 times greater in the less developed countries of the Region than in more developed ones. Mapping infant mortality throughout the Region of the Americas allowed us to identify the countries that need to focus more attention on health policy and health programs, but not to determine what specific actions are of the highest priority. An analysis of smaller geopolitical units (states and municipalities) revealed important differences within countries. This shows that, as is true of data for the entire Region of the Americas, using national-level average figures for indicators can obscure the differences that exist within countries. When we examined the relationship between female illiteracy and malnutrition as determinants of infant mortality in Brazil and Ecuador, we identified social and epidemiologic strata where risk factors had different distribution patterns and that thus require health interventions that match their individual social and epidemiologic profiles.

With this type of epidemiologic study using GISs at the local level of health services, it is easy to see how a health event and its risk factors behave at a specific period in time. It is also possible to identify patterns in the spatial distribution of risk factors and in these factors' potential impact on health. Using GISs in an appropriate way will make it easier to deliver more effective, equitable public health services.