ABSTRACT
INTRODUCTION: Tuberculosis (TB) is the primary cause of death among infectious diseases affecting groups in extreme poverty. Social improvements could reverse this situation in Brazil. This study aims to demonstrate the spatial relationship between social development (SD) and TB mortality in Natal, a city in northeastern Brazil. METHODOLOGY: Ecological study. The study population comprised TB deaths recorded in the Mortality Information System between 2008 and 2014. The units of analysis were 59 human development units (HDUs). Raw and smoothed mortality rates were calculated using the global empirical Bayes method. Primary components analysis was used to develop the SD indicators. An association between TB mortality and SD was verified using multiple linear regression analysis. Spatial autocorrelation was verified using models with global spatial effects. Analyses were performed using Statistica version 12.0, ArcGIS version 10.2, Statistical Package for the Social Sciences version 20.0, and OpenGeoDa 1.0.1. The significance level was established at 5% (p < 0.05). RESULTS: The TB mortality rate with non-random spatial distribution ranged between 0.52 and 8.90 per 100,000 inhabitants. The spatial lag model was chosen because it presented the highest log-likelihood value, lowest AIC, and highest R2. A negative association was found between TB mortality and SD (R2 = 0.207; p = 0.03). CONCLUSIONS: The results show a negative association between TB mortality and the high SD indicator. This study can support decision-making in terms of collective projects within public health in order to link the health field to other sectors, aiming for social well-being and human development.
Subject(s)
Tuberculosis/mortality , Urbanization , Bayes Theorem , Brazil/epidemiology , Female , Humans , Longitudinal Studies , Male , Risk Factors , Spatial AnalysisABSTRACT
BACKGROUND: Tuberculosis (TB) is one of the top 10 causes of death worldwide; in 2016, over 95% of TB deaths occurred in low- and middle-income countries. Although the incidence and deaths from TB have decreased in Brazil in recent years, the disease has increased in the vulnerable population, whose diagnosis is more delayed and the chances for abandonment and deaths are significantly higher. This study aimed to identify high-risk areas for TB mortality and evidence their social determinants through a sensitive tailored social index, in a context of high inequality in South Brazil. METHODS: A multistep statistical methodology was developed, based on spatial clustering, categorical principal components analysis, and receiver operating characteristic curves (ROC). This study considered 138 spatial units in Curitiba, South Brazil. TB deaths (2008-2015) were obtained from the National Information Mortality System and social variables from the Brazilian Human Development Atlas (2013). RESULTS: There were 128 TB deaths recorded in the study: the mortality rate was 0.9/100,000 inhabitants, minimum-maximum: 0-25.51/100,000, with a mean (standard deviation) of 1.07 (2.71), and 78 space units had no deaths. One risk cluster of TB mortality was found in the south region (RR=2.64, p=0.01). Considering the social variables, several clusters were identified in the social risk indicator (SRI): income (899.82/1752.94; 0.024), GINI Index (0.41/0.45; 0.010), and overcrowding (25.07/15.39; 0.032). The SRI showed a high capacity to discriminate the TB mortality areas (area under ROC curve 0.865, 95% CI: 0.796-0.934). CONCLUSIONS: A powerful risk map (SRI) was developed, allowing tailored and personalised interventions. The south of Curitiba was identified as a high-risk area for TB mortality and the majority of social variables. This methodological approach can be generalised to other areas and/or other public health problems.
Subject(s)
Socioeconomic Factors , Tuberculosis , Brazil/epidemiology , Humans , Risk Factors , Social Conditions , Tuberculosis/epidemiologyABSTRACT
OBJECTIVE: To evaluate the magnitude of social determinants in areas of risk of mortality due to tuberculosis in a high incidence city. METHOD: Ecological study, which recruited the cases of tuberculosis deaths registered between 2006 and 2016 in the capital of Mato Grosso-Brazil. The social determinants were obtained from the Human Development Units. Sweep statistics were used to identify areas of risk of mortality due to tuberculosis. Principal component analysis was carried out to identify dimensions of social determinants. Multiple logistic regression was applied to verify associations between the dimensions of social determinants and the risk of mortality from tuberculosis. A 5% error was fixed. The standard error was established at 5% for all statistical tests. RESULTS: A total of 225 deaths due to tuberculosis were registered in the period, distributed heterogeneously in the space. A cluster of risk for tuberculosis mortality was identified, with RR=2.09 (95%CI: 1.48-2.94; p=0.04). Social determinants, low educational level and poverty were associated with the risk of mortality due to tuberculosis (OR: 2.92; 95%CI: 1.17-7.28). Income had a negative association with the risk of mortality due to tuberculosis (OR: 0.05; 95%CI: 0.00-0.70). The value of the ROC curve of the model was 92.1%. CONCLUSIONS: The results confirmed that the risk of mortality due to tuberculosis is a problem associated with social determinants. Health policies and social protection programmes can collaborate to address this problem.
