INTRODUCTION: Leprosy is a disease that reserves close relation with social and economic conditions. Brazil is the only country that has not yet reached the goal of eliminating the disease as a public health problem. OBJECTIVE: This study aimed to analyze social deprivation in the municipalities of Bahia and its relation with the detection of new cases of leprosy in the population. METHODS: It is an ecological study conducted in the state of Bahia, from 2001 to 2015. Variables analyzed: detection rate of new cases, social deprivation index (SDI) and Hansen's disease in children under 15 years of age. The SDI was built on four variables: socioeconomic performance index, per capita income, proportion of extremely poor, and household density. For spatial analysis, local empirical bayesian modeling and global and local Moran statistics were used. Statistical analysis used multivariate, spatial and logistic regression, odds ratio calculation and analysis of variance. RESULTS: Leprosy showed heterogeneous distribution in the state, with concentration in the north-west and south axis. 60.4% (n = 252) of the municipalities presented very low life conditions. An association was observed between living conditions and the detection of leprosy, with higher coefficients in the municipality group with better living conditions (p < 0.001). CONCLUSION: It was concluded that the worst conditions acted as an impediment to the diagnosis, while increasing the risk of illness. Good conditions have the opposite effect.
INTRODUCTION: Leprosy is a disease that reserves close relation with social and economic conditions. Brazil is the only country that has not yet reached the goal of eliminating the disease as a public health problem. OBJECTIVE: This study aimed to analyze social deprivation in the municipalities of Bahia and its relation with the detection of new cases of leprosy in the population. METHODS: It is an ecological study conducted in the state of Bahia, from 2001 to 2015. Variables analyzed: detection rate of new cases, social deprivation index (SDI) and Hansen's disease in children under 15 years of age. The SDI was built on four variables: socioeconomic performance index, per capita income, proportion of extremely poor, and household density. For spatial analysis, local empirical bayesian modeling and global and local Moran statistics were used. Statistical analysis used multivariate, spatial and logistic regression, odds ratio calculation and analysis of variance. RESULTS: Leprosy showed heterogeneous distribution in the state, with concentration in the north-west and south axis. 60.4% (n = 252) of the municipalities presented very low life conditions. An association was observed between living conditions and the detection of leprosy, with higher coefficients in the municipality group with better living conditions (p < 0.001). CONCLUSION: It was concluded that the worst conditions acted as an impediment to the diagnosis, while increasing the risk of illness. Good conditions have the opposite effect.