Socio-economic and environmental differentials, and mortality in a developing urban area (Belo Horizonte - Brazil)

Studies on health inequalities on developing cities are scarce. They have mainly focused on infant and child mortality and life expectancy at birth. Studies of adult mortality and cause- specific studies have seldom been carried out. An ecological study was performed in order to investigate the relationship between mortality due to all causes of death, infectious diseases, combined illness of diarrhoea, pneumonia and malnutrition, external causes, homicides, and motor vehicle traffic accidents, and socio- environmental conditions in a developing city, Belo Horizonte in Brazil. Death certificates relating to 1994 were processed. A total of 10,558 certificates were geocoded according to 75 geographical areas. The areas were classified according to the income of the head of family (or female illiteracy when appropriate), and plausible routinely environmental factors. In the study of mortality due to infectious diseases, water, sanitation, crowding, and rubbish collection were tested. Among the external causes, the study focused on homicide and motor vehicle traffic accidents, testing the effect of public illumination, crowding and the average time for police response to a phone call. Analytical and descriptive techniques were used in the study. Mortality rate (MR) ratios were estimated using random effects Poisson regression. A high correlation was found between socio-economic and environmental variables. These correlated to the distribution of mortality rates across the areas. Shantytown areas (the favelas) presented higher risk of mortality than non-favela areas. Infectious diseases, homicide, and combined illness of diarrhoea, pneumonia and malnutrition (under 5 years old) presented MR ratios of 1.59,2.05, 1.62, respectively. All of them presented p-values for trend <0.00. Deaths due to all causes presented 1.12 (p=0.04). Adverse socio-economic and environmental conditions are associated with higher rates of specific cause of death. Deprived areas encompass highest vulnerable groups. The use of routine data in developing countries can be used to measure the inequalities in health, helping build up more adequate urban and health policies.